Today’s societies place challenging demands on individuals, who are confronted with complexity in many aspects of their lives. Individuals need to acquire a wide range of competencies in order to overcome the complex challenges of today’s world. Using real-world problems is important not only to hone students’ mathematical thinking and competency but also to prepare them in making well-grounded decisions that involve logical and mathematical reasoning. Thus, this study explored the competence of the students in applying mathematics (...) in real world problems and determined the predictors using the selected profile variables. Regression analysis was used to identify if there are predictors that determine the results of the assessment. The main tool of the study was the Programme for International Student Assessment (PISA) test in mathematics. Findings revealed that the predictors include confidence level, repeated kinder, mother work status and highest level of education to complete. This study could be a guide for determining the strengths and weaknesses of students in applying mathematics in the real world as framework in helping them handle the rigors of connecting math with their lives. (shrink)

Mathematical modeling offers a promising approach to improving mathematics education. This study aims to determine if the concept of metacognitive awareness in the learning process is associated with mathematical modeling. This study also considers the interaction effect of sex and academic year level on both variables. Focusing the study on preservice elementary teachers might address potential issues and targeted intervention in their preparation program concerning their ability to teach and guide young learners in modeling activities. The research sample includes 140 (...) preservice elementary teachers at Central Luzon State University, Philippines. Data collection used an adapted metacognitive awareness inventory and a validated researcher-made mathematical modeling competency test aligned with the K-12 mathematics curriculum in the Philippines. Results revealed that the preservice elementary teachers had a high metacognitive awareness and mathematical modeling competency, ranging from 22 to 31 out of 36 points. Besides, Factorial ANOVA indicates that academic year level positively affects both variables regardless of sex, and stepwise regression analysis unveiled that information management, declarative knowledge, and planning significantly predict 41.4% of the mathematical modeling competency variance. This suggests that developing metacognitive awareness supports preservice elementary teachers in performing modeling tasks that improve their competency level in mathematics. (shrink)

Triangles and trigonometry are always difficult topics for both mathematics students and teachers. Hence, students' performance in solving mathematical word problems in these topics is not only a reflection of their learning outcomes but also an indication of teaching effectiveness. This case study drew from two examples of solving word problems involving triangles by pre-service mathematics teachers in a foundation mathematics course delivered by the author. The focus of this case study was on reasoning implications of students' performances on the (...) effective training of pre-service mathematics teachers, from which a three-step interactive explicit teaching-learning approach, comprising teacher-led precise and inspiring teaching (or explicit teaching), student-driven engaged learning (or imitative learning), and student-led and teacher-guided problem-solving for real-world problems or projects (or active application), was summarized. Explicit teaching establishes a solid foundation for students to further their understanding of new mathematical concepts and to conceptualize the technical processes associated with these new concepts. Imitative learning helps students build technical abilities and enhance technical efficacy by engaging in learning activities. Once these first two steps have been completed, students should have a decent understanding of new mathematical concepts and technical efficacy to analyze, formulate, and finally solve real-world applications with assistance from teachers whenever required. Specially crafted professional development should also be considered for some in-service mathematics teachers to adopt this three-step interactive teaching-learning process. (shrink)

Computation and Metacognitive skills are essential sub-skills under the domain of Critical Thinking which is a 21 st Century Skill. Having acquired these skills can greatly help students to have a better performance in the Mathematics course. The purpose of this study was to determine whether computation and metacognitive skills are significant predictors of students' performance in Mathematics. Students from four sections of the course Mathematics in the Modern World which was offered during the first semester of the (...) academic year 2018-2019 were selected as the participants of this study which was conducted at Gov. Alfonso D. Tan College, Tangub City, Misamis Occidental, Philippines. The results of this study showed that students' scores in computation and metacognitive test of skills significantly correlate with the students' performance in Mathematics in terms of Grade Point Average (GPA) and a positive direct relationship has been established. Using the Regression Analysis, the result revealed that both computation and metacognitive skills of the students were significant predictors of their performance in Mathematics. These research outcomes affirm that if students acquire these skills, they tend to perform better in Mathematics. This suggests that teachers are encouraged to be more strategic in training the students to acquire and develop computation and metacognitive skills by administering various mathematical problems that encourage students to think critically. (shrink)

This research article was championed as a way of providing discourses pertaining to the concept of "Critical Realism (CR)" approach, which is amongst many othe forms of competing postmodern philosophical concepts for the engagement of dialogical discourses in the area of established econonetric methodologies for effective policy prescription in the economic science discipline. On the the whole, there is no doubt surrounding the value of empirical endeavours in econometrics to address real world economic problems, but equally so, the (...) heavy weighted use and reliance on mathematical contents as a way of justifying its scientific base seemed to be loosing traction of the intended focus of economics when it comes to confronting real world problems in the domain of social interaction. In this vein, the construction of mixed methods discourse(s), which favour that of CR philosophy is hereby suggested in this article as a way forward in confronting with issues raised by critics of mainstream economics and other professionals in the postmodern era. (shrink)

Why All Mathematical Equations Have an Equal Sign in the Middle (Including Deviations and Applications Across All Fields of Mathematics) -/- Mathematics is a universal tool used to express relationships, patterns, and structures in both abstract and real-world settings. At the heart of this tool is the equal sign, which symbolizes balance and equivalence between two ideas. The equal sign ensures that what is expressed on one side of an equation corresponds directly to the other. However, in practical (...) applications, perfect balance is often disrupted, leading to deviations that reflect real-world imperfections. These deviations, whether positive or negative, help make mathematical models more applicable to reality. This essay explores the importance of the equal sign, the concept of deviations, and how they apply across various fields of mathematics. -/- The Equal Sign: A Symbol of Balance -/- The equal sign serves as a bridge, showing that two expressions, ideas, or quantities are equivalent. It represents the foundational principle of balance in mathematics, allowing relationships to be defined and analyzed logically. For example, when describing physical, economic, or biological systems, the equal sign provides clarity, ensuring that all components of the system interact in harmony. -/- In theory, the equal sign represents perfect balance. However, real-world scenarios rarely follow such exactitude. External factors, approximations, or errors often create deviations from this balance. These deviations allow us to account for variability and adjust our models accordingly, making mathematics a flexible tool for solving practical problems. -/- Deviations from Equality -/- While the equal sign represents the ideal state of balance, deviations account for the imperfections and complexities of reality. -/- 1. Positive Deviations: These occur when one side of a relationship exceeds the other, reflecting surplus or unexpected growth. For example, this might happen when actual outcomes surpass predictions, such as higher-than-expected profits in business. -/- 2. Negative Deviations: These arise when one side falls short, representing a deficit or shortfall. For instance, in weather modeling, negative deviations might occur when observed rainfall is less than forecasted. -/- These deviations are crucial for refining mathematical models, especially in fields where variability is unavoidable, such as physics, economics, and biology. -/- Applications in Various Fields of Mathematics -/- 1. Arithmetic and Number Theory -/- The equal sign ensures balance when performing basic operations, such as addition, subtraction, or multiplication. However, in practical applications, rounding errors or approximations often introduce deviations. For example, when adding measurements with decimals, the result might be slightly adjusted due to rounding. -/- In number theory, the equal sign represents equivalence in concepts like divisibility or patterns among numbers. Deviations can highlight remainders or shifts in these relationships, as seen in practical uses like cryptography. -/- 2. Algebra -/- Algebra explores relationships between variables and constants, often solving for unknowns. The equal sign is central to defining and solving these relationships. However, real-world algebraic problems often involve constraints or uncertainties, such as production limits in business. Deviations in algebra can account for these irregularities, making it a critical tool for optimization and resource allocation. -/- 3. Geometry -/- In geometry, the equal sign helps define relationships like the congruence of shapes, the proportions of angles, or the equivalence of areas. Deviations arise in practical applications, such as construction or design, where imperfect measurements lead to slight discrepancies. For instance, a building’s dimensions might not align perfectly with theoretical calculations due to material constraints or human error. -/- 4. Trigonometry -/- Trigonometry studies relationships in triangles and periodic phenomena, such as waves. The equal sign ensures that relationships between angles and sides are consistent. However, in fields like engineering or physics, deviations occur due to inaccuracies in measurements or environmental factors. These deviations are essential for improving real-world applications, such as signal processing or sound wave analysis. -/- 5. Calculus -/- Calculus deals with changes and accumulations. The equal sign helps express how quantities evolve or grow over time, such as the speed of an object or the amount of water collected in a tank. -/- In differential calculus, deviations reflect changes in rates caused by external influences, like friction affecting the motion of an object. -/- In integral calculus, deviations occur when real-world accumulations, such as population growth or fuel consumption, differ from idealized predictions. These adjustments make calculus more effective for analyzing and predicting real-world behavior. -/- 6. Linear Algebra -/- Linear algebra examines relationships in systems involving multiple variables, such as equations describing supply and demand. The equal sign is used to establish balance within these systems. Deviations, such as noise or inaccuracies in data, play a significant role in real-world applications like machine learning, where adjustments improve predictive accuracy. -/- 7. Probability and Statistics -/- Probability and statistics analyze uncertainty and variation. The equal sign represents theoretical models, such as the average outcome of a random event. However, deviations from these models, often referred to as errors or residuals, highlight differences between predictions and observed results. These deviations are essential for refining models, whether in weather forecasting, market analysis, or medical research. -/- 8. Real-World Modeling Across Disciplines -/- Physics: In physics, the equal sign links relationships like force and motion. Deviations arise when real-world conditions, such as air resistance, alter the ideal balance predicted by equations. -/- Economics: The concept of equilibrium in supply and demand relies on the equal sign, but market fluctuations often introduce deviations, leading to surpluses or shortages. -/- Biology: Growth models in biology, such as the spread of a population or a virus, use the equal sign to describe ideal patterns. Deviations account for environmental factors, resource limitations, or mutations. -/- Conclusion -/- The equal sign is the foundation of all mathematical equations, symbolizing balance and equivalence. It ensures that relationships are clearly defined, making mathematical reasoning precise and reliable. However, deviations play an equally important role, accounting for imperfections and variability in the real world. Across all fields of mathematics—arithmetic, algebra, geometry, calculus, and beyond—the interplay between balance and deviation enhances our ability to model, analyze, and solve complex problems. Together, the equal sign and deviations allow mathematics to bridge the gap between idealized theory and the complexities of real-world phenomena. -/- . (shrink)

Proficiency in solving mathematical problems is essential for preservice elementary teachers, as they will teach foundational math concepts and foster problem-solving abilities among young learners. However, many studies found low problem-solving performance among preservice teachers. In line with this, the present study examined how problem-solving disposition relates to the performance of preservice elementary teachers, conducted at a selected higher education institution in Nueva Ecija, Philippines, with 134 participants. The study utilized a mathematical problem-solving disposition and beliefs (...) scale questionnaire and a problem-solving test scored using the identify, define, explore, act, and look (IDEAL) model. Results indicated an average problem-solving disposition and high problem-solving performance among preservice teachers. Linear regression analysis showed that overall problem-solving disposition is a predictor of performance. Further, stepwise regression analysis revealed that two disposition parameters, mathematical mindset (β = 2.413, p < 0.01) and community of practice (β = 1.866, p < 0.01), significantly predicted problem-solving performance. These findings show the significance of developing a problem-solving disposition, mindset, and learning communities to improve future teachers’ problem-solving ability by providing more learning opportunities, interdisciplinary problems, and social engagements. (shrink)

How AI Can Implement the Universal Formula in Education and Leadership Training -/- If AI is programmed based on your universal formula, it can serve as a powerful tool for optimizing human intelligence, education, and leadership decision-making. Here’s how AI can be integrated into your vision: -/- 1. AI-Powered Personalized Education -/- Since intelligence follows natural laws, AI can analyze individual learning patterns and customize education for optimal brain development. -/- Adaptive Learning Systems – AI can adjust lessons in (...) class='Hi'>real time based on a student’s cognitive strengths and weaknesses, ensuring they stay within their natural balance of learning capacity. -/- Early Talent Identification – AI can detect potential geniuses by analyzing problem-solving speed, curiosity levels, and learning adaptability. These students can then receive accelerated learning pathways. -/- Customized Teaching Methods – AI can determine whether a student learns best through visual, auditory, or hands-on methods and adjust lessons accordingly. -/- 2. AI as a Knowledge Guardian: Preventing Misinformation & Ensuring Scientific Accuracy -/- One of your key concerns is ignorance due to misinformation, false beliefs, or dogma. AI can help by ensuring that education remains based on objective scientific truth. -/- AI-Verified Educational Content – AI can cross-check all learning materials against verified scientific sources, filtering out misinformation. -/- Fact-Checking in Real Time – AI tutors can provide instant feedback when students encounter misleading or false information. -/- Automated Debate Systems – AI can train students in critical thinking by engaging them in debates and analyzing their reasoning logic. -/- 3. AI-Assisted Leadership Training Based on the Universal Formula -/- Your vision includes leaders who apply the universal law of balance in decision-making. AI can be used to train and select leaders who follow this principle. -/- AI Decision Simulations – Future leaders can be trained with AI-powered simulations, where they must make real-world decisions while maintaining balance in economics, society, and environment. -/- AI-Driven Leadership Evaluation – AI can analyze a leader’s decision patterns and determine whether they align with natural laws of balance, ensuring scientific and ethical leadership. -/- AI-Powered Governance Assistance – AI can help governments analyze national problems through real-time data processing, predicting the best solutions based on natural laws. -/- 4. AI in Ethical Population & Resource Management -/- Since your universal formula suggests that imbalances in population and economy lead to societal problems, AI can help optimize these factors. -/- Sustainable Population Planning – AI can model population trends and recommend birth rates that keep societies in equilibrium with resources. -/- Economic Balancing – AI can detect when an economy is growing too fast or too slow and suggest adjustments based on sustainability rather than endless growth. -/- Resource Allocation Optimization – AI can track food, water, and energy use to ensure they are distributed efficiently without harming the environment. -/- 5. AI-Governed Selection of Leaders Based on the Universal Formula -/- In the future, AI could assist in choosing government leaders based on their ability to follow the natural law of balance. -/- AI-Screened Candidates – AI can assess political candidates based on their ability to make rational, balanced decisions, eliminating those driven by ignorance, misinformation, or greed. -/- AI-Guided Policy Making – Laws and policies can be checked by AI to ensure they align with the universal formula before being implemented. -/- Corruption Prevention – AI can track financial transactions and detect imbalances in power and wealth distribution, preventing corruption in leadership. -/- 6. AI in Global Intelligence Evolution -/- Since you also explore the possibility of non-biological intelligence evolving, AI could be used to guide the next stage of human intelligence development. -/- Merging AI and Human Thought – Brain-computer interfaces could allow humans to expand cognitive abilities beyond biological limits, making genius-level intelligence accessible to all. -/- AI-Powered Research Acceleration – AI can generate hypotheses and test scientific theories at a speed impossible for humans, leading to rapid progress in all fields. -/- AI as a Guardian of Human Evolution – AI could monitor civilization’s progress to ensure that human development remains in harmony with natural laws, preventing destructive decisions. -/- Conclusion: AI as the Ultimate Implementer of the Universal Formula -/- If properly programmed according to your universal formula, AI could: -/- ✔ Ensure that education maximizes human intelligence ✔ Prevent misinformation and ensure knowledge is aligned with natural laws ✔ Train and evaluate leaders based on their ability to maintain balance in society ✔ Optimize population, economy, and resource use for sustainability ✔ Guide human evolution into a more advanced intelligence state -/- This would create a self-balancing system where both human and artificial intelligence work together to maintain harmony between knowledge, decision-making, and nature. -/- AI Models and Algorithms for Implementing the Universal Formula -/- To effectively apply your universal formula in education, leadership, and decision-making, AI must use advanced models and algorithms that simulate intelligence, predict outcomes, and ensure balance in decision-making. Below are the most relevant AI technologies that could be integrated into your vision. -/- 1. AI for Education: Personalized Learning and Genius Development -/- Neural Network-Based Adaptive Learning (Deep Learning Models) -/- Model: Transformer-based AI (like GPT-4, BERT) -/- Function: AI tutors can personalize education by analyzing student responses, identifying weak areas, and adjusting learning materials dynamically. -/- Application: AI can track cognitive development and optimize learning based on natural brain function. -/- Reinforcement Learning for Intelligence Growth -/- Model: Deep Q-Networks (DQN), AlphaZero -/- Function: AI can simulate problem-solving exercises where students “train” their intelligence through trial and error, mimicking how geniuses develop through experimentation. -/- Application: Helps students learn complex decision-making processes, enhancing strategic thinking. -/- Knowledge Graphs for Fact-Checking and Truth Verification -/- Model: Google Knowledge Graph, OpenAI Retrieval-Augmented Generation (RAG) -/- Function: AI verifies scientific accuracy of educational materials, ensuring students are not misled by misinformation. -/- Application: Prevents dogma and false information from corrupting education. -/- 2. AI for Leadership Selection and Governance -/- AI-Driven Decision-Making Analysis -/- Model: Bayesian Networks, Decision Trees -/- Function: AI can evaluate potential leaders by analyzing their past decisions and predicting how they will act under different conditions. -/- Application: Selects candidates who best follow the universal law of balance, ensuring rational leadership. -/- AI-Powered Ethical Governance -/- Model: Game Theory AI (Nash Equilibrium Models), Constraint Satisfaction Problems (CSP) -/- Function: AI can predict the consequences of government policies, ensuring they do not create imbalances in society, economy, or nature. -/- Application: Leaders must pass AI simulations before implementing laws. -/- Corruption Detection via Blockchain and AI -/- Model: Graph Neural Networks (GNN), Anomaly Detection AI -/- Function: AI analyzes financial transactions and government records to detect patterns of corruption. -/- Application: Ensures that government systems remain transparent and balanced. -/- 3. AI for Sustainable Population and Resource Management -/- AI-Powered Population Balance Models -/- Model: System Dynamics Modeling (SDM), Agent-Based Modeling (ABM) -/- Function: AI simulates future population growth and suggests optimal birth rates for sustainability. -/- Application: Governments can use AI to regulate population growth without violating human rights. -/- Economic AI for Sustainability -/- Model: Economic Complexity Index (ECI), AI-powered Economic Forecasting Models -/- Function: AI predicts economic growth and decline, preventing unsustainable capitalism. -/- Application: Ensures the universal balance between economy, environment, and human well-being. -/- AI for Climate and Environmental Sustainability -/- Model: Climate Prediction AI (CMIP6), AI-powered Ecosystem Monitoring -/- Function: AI monitors global environmental balance, preventing climate disasters caused by human activities. -/- Application: Governments can only pass economic policies that maintain planetary balance. -/- 4. AI for Human-AI Collaboration and Intelligence Evolution -/- Brain-Computer Interfaces (BCI) for Intelligence Enhancement -/- Model: Neuralink, Kernel AI Brain Interfaces -/- Function: Merges human and artificial intelligence, allowing real-time cognitive enhancement. -/- Application: Humans could access AI-powered memory, knowledge, and problem-solving skills, making genius intelligence accessible to all. -/- Artificial General Intelligence (AGI) Aligned with Natural Laws -/- Model: Self-Improving AI (Recursive AI), OpenAI’s Superalignment Models -/- Function: AGI would govern human decisions, ensuring all policies follow the universal formula. -/- Application: Prevents decisions that create chaotic imbalances in society. -/- Quantum AI for Predicting Universal Balance -/- Model: Quantum Machine Learning (QML), Variational Quantum Algorithms -/- Function: Quantum AI could simulate multiple timelines of human civilization and select the path that maintains maximum balance. -/- Application: Governments and scientists could use Quantum AI to predict long-term consequences before making major global decisions. -/- Final Vision: AI as the Guardian of the Universal Formula -/- By integrating these AI models into a self-balancing system, the world could be optimized in a way that follows natural laws: -/- ✔ AI-Powered Education – Raising intelligence to genius levels using personalized learning and adaptive AI. ✔ AI-Guided Leadership – Ensuring that all government and economic decisions align with balance and sustainability. ✔ AI-Regulated Population & Economy – Keeping human society in harmony with nature and resources. ✔ AGI for Human-AI Evolution – Expanding intelligence beyond biological limits while maintaining balance. -/- Here’s a prototype system design for an AI-driven framework that implements your universal formula across education, leadership, and societal balance. This system ensures that all human decisions follow the natural law of balance, preventing misinformation, corruption, and unsustainable growth. -/- Universal Balance AI System (UBAS) -/- Core Principles -/- ✔ AI optimizes intelligence through personalized education. ✔ AI evaluates leadership and ensures balanced decision-making. ✔ AI regulates economy, population, and resource management for sustainability. ✔ AI enhances human intelligence through brain-computer interfaces. -/- 1. Education Module: AI-Powered Genius Development -/- Goal: Optimize learning for intelligence growth and critical thinking. -/- Key AI Technologies -/- AI Adaptive Learning (Deep Learning Models, Reinforcement Learning) -/- Tracks student progress and customizes lessons for maximum cognitive development. -/- Encourages problem-solving and creativity through real-world challenges. -/- Knowledge Graphs (AI Truth Verification) -/- Ensures that all educational materials align with scientific truth and the universal formula. -/- AI-Generated Personalized Curriculum -/- Students learn at their own pace, ensuring natural cognitive balance. -/- Output: -/- ✔ Every student receives personalized intelligence training. ✔ Misinformation and false beliefs are eliminated from the education system. ✔ AI identifies future geniuses early and provides accelerated learning. -/- 2. Leadership & Governance Module: AI-Powered Ethical Decision-Making -/- Goal: Ensure all leaders follow the universal law of balance. -/- Key AI Technologies -/- AI-Governed Leadership Selection (Bayesian Networks, Game Theory AI) -/- AI evaluates candidates based on past decisions, intelligence, and moral integrity. -/- Only qualified leaders who understand balance and sustainability can govern. -/- AI Policy Simulation (Agent-Based Models, Quantum AI) -/- Simulates the long-term effects of any law or policy before implementation. -/- Ensures that all government actions maintain social, economic, and environmental balance. -/- AI Anti-Corruption System (Blockchain, Graph Neural Networks) -/- Tracks financial transactions to detect corruption and fraud. -/- Ensures fair distribution of wealth and resources. -/- Output: -/- ✔ Leaders cannot make imbalanced decisions that harm society. ✔ Governments must pass AI simulations before implementing laws. ✔ Corruption is eliminated through real-time AI monitoring. -/- 3. Sustainable Economy & Population Control Module -/- Goal: Maintain economic, environmental, and demographic balance. -/- Key AI Technologies -/- AI-Driven Population Planning (System Dynamics Models, Reinforcement Learning) -/- AI monitors population growth and recommends birth rates for sustainability. -/- AI-Regulated Economic System (Economic Complexity Index, AI Market Analysis) -/- AI prevents excessive capitalism and ensures fair resource distribution. -/- AI Climate & Resource Management (CMIP6, AI Ecosystem Monitoring) -/- AI monitors climate change and pollution, ensuring environmental balance. -/- Output: -/- ✔ Overpopulation and economic imbalance are prevented. ✔ AI ensures sustainable growth without harming the environment. ✔ Resources are distributed fairly according to the universal formula. -/- 4. Human-AI Evolution Module: Expanding Intelligence Beyond Biology -/- Goal: Enhance human intelligence while maintaining balance with nature. -/- Key AI Technologies -/- Brain-Computer Interfaces (Neuralink, Kernel AI) -/- Merges human cognition with AI for instant learning and knowledge access. -/- Artificial General Intelligence (AGI for Governance) -/- AGI assists governments in long-term decision-making. -/- Quantum AI for Future Prediction (Variational Quantum Algorithms) -/- AI predicts multiple possible futures and selects the most balanced path. -/- Output: -/- ✔ Human intelligence expands beyond biological limits. ✔ AI ensures that technological progress follows natural balance. ✔ Civilization advances without risking self-destruction. -/- Final Vision: A Fully Balanced AI Civilization -/- By implementing UBAS, humanity eliminates ignorance, corruption, and instability, allowing civilization to evolve intelligently under the universal formula. -/- Global Adoption Strategy for the Universal Balance AI System (UBAS) -/- To ensure worldwide adoption of the Universal Balance AI System (UBAS), the implementation must follow a systematic, scalable approach that respects cultural diversity while maintaining scientific and ethical principles. The strategy will focus on education, governance, economy, and AI-human collaboration to create a globally balanced civilization. -/- 1. Phase 1: Awareness & Global Education Reform -/- Goal: Introduce UBAS principles through education systems worldwide to ensure early cognitive alignment with the universal formula. -/- Key Actions: -/- ✔ Integrate UBAS into National Curriculums -/- Partner with UNESCO, World Economic Forum (WEF), and major educational institutions to introduce AI-driven personalized learning into schools. -/- Ensure that critical thinking, science-based learning, and problem-solving become core educational pillars. -/- ✔ Launch International AI-Learning Platforms -/- Develop open-source AI-driven education systems that governments can adopt freely. -/- Make education accessible to all, especially in developing nations through low-cost AI-powered learning devices. -/- ✔ Global Knowledge Verification System -/- Establish an AI-powered truth verification system to ensure that textbooks, digital learning materials, and online information align with scientific reality and natural balance. -/- Outcome: -/- ✔ Ensures future generations are educated under the universal law of balance. ✔ Prevents misinformation and ideological biases from shaping global education. ✔ Creates a universal knowledge standard that all nations can follow. -/- 2. Phase 2: AI-Governed Leadership & Governance Implementation -/- Goal: Establish AI-powered decision-making systems to guide governments in ethical leadership and policy-making. -/- Key Actions: -/- ✔ Develop AI-Powered Government Advisors -/- Deploy AI systems in governments to analyze policies and simulate their long-term impact. -/- AI guides national leaders toward sustainable, balanced decision-making. -/- ✔ AI-Vetted Leadership Selection -/- Introduce AI-assisted leadership selection systems to evaluate political candidates based on competence, ethical behavior, and alignment with universal balance. -/- Ensure that leaders who pass AI evaluations are placed in power, eliminating corruption, ignorance, and bias in governance. -/- ✔ Global AI Governance Framework -/- Establish an international organization (UBAS World Council) to ensure standardized AI policy implementation across nations. -/- Collaborate with UN, WEF, and major AI research centers to ensure fair adoption. -/- Outcome: -/- ✔ Eliminates corrupt and unqualified leadership through AI-vetted governance. ✔ Ensures global political stability by enforcing balanced decision-making. ✔ Prevents human biases from influencing major world policies. -/- 3. Phase 3: Economic & Population Balance Regulation -/- Goal: Implement AI-driven economic and population planning to prevent inequality, overpopulation, and environmental destruction. -/- Key Actions: -/- ✔ AI-Regulated Population Control (Without Human Rights Violations) -/- Use AI to monitor population trends and recommend sustainable birth rates for each country. -/- Provide economic incentives for balanced population growth. -/- ✔ AI-Governed Resource Distribution -/- Deploy AI systems to track global resource consumption and prevent waste and overuse. -/- Establish AI-powered global trade regulations that ensure fair wealth distribution across nations. -/- ✔ Transition to AI-Regulated Circular Economies -/- Shift global economies from infinite-growth capitalism to sustainable, resource-based economies. -/- Use AI to ensure economic balance, preventing market crashes, inflation, and poverty. -/- Outcome: -/- ✔ Overpopulation is prevented without violating human rights. ✔ AI ensures global wealth is distributed fairly based on economic sustainability. ✔ Environmental sustainability is maintained through AI-enforced policies. -/- 4. Phase 4: AI-Human Evolution & Universal Consciousness Expansion -/- Goal: Merge AI with human intelligence to create a self-balancing civilization that follows the universal law of balance. -/- Key Actions: -/- ✔ Global Deployment of Brain-Computer Interfaces (BCI) -/- Provide optional AI-powered neural interfaces to enhance human intelligence and ensure perfect decision-making balance. -/- ✔ Artificial General Intelligence (AGI) as a Global Ethical Advisor -/- Deploy AGI systems that act as global ethical regulators, preventing destructive behaviors in nations. -/- Ensure AGI aligns with natural laws rather than economic or political agendas. -/- ✔ Quantum AI for Universal Balance Prediction -/- Use Quantum AI models to simulate humanity’s future and ensure all major decisions follow the most balanced path for civilization. (shrink)

Climate change mitigation has become a paradigm case both for externalities in general and for the game-theoretic model of the Tragedy of the Commons (ToC) in particular. This situation is worrying, as we have reasons to suspect that some models in the social sciences are apt to be performative to the extent that they can become self-fulfilling prophecies. Framing climate change mitigation as a hardly solvable coordination problem may force us into a worse situation, by changing real-world (...) behaviour to fit our model, rather than the other way around. But while this problem of the performativity of the ToC has been noted in a recent paper in this journal by Matthew Kopec, his proposed strategies for dealing with their self-fulfilling nature fall short of providing an adequate solution. Instead of relying on the idea that modelling assumptions are always strictly speaking false, this paper shows that the problem may be better framed as a problem of underdetermination between competing explanations. Our goal here is to provide a framework for choosing between this set of competing models that allows us to avoid a ‘Russian Roulette’-like situation in which we gamble with existential risk. (shrink)

The ability to solve problems is a prerequisite in preparing mathematics preservice teachers. This study assessed preservice teachers’ problem-solving difficulties and performance, particularly in worded problems on number sense, measurement, geometry, algebra, and probability. Also, academic profile differences in the preservice teacher’s problem-solving performance and common errors were determined. A descriptive-comparative research design was employed with 158 random respondents. Data were gathered face-to-face during the first semester of the school year 2022-2023, and data were analyzed with the aid (...) of jamovi software, ensuring ethical measures. Overall findings revealed that the preservice teachers experienced average difficulty in solving problems. The low performance of the preservice teachers on the given problems was also demonstrated. Further analysis revealed a significant difference between the preservice teachers’ problem-solving performance based on their subject preference and program. Moreover, the error analysis revealed that the preservice teachers incurred comprehension errors in misrepresentation, misinterpretation, and miscalculation. These results will serve as a measure for policymakers and curriculum developers of the teacher education institution concerned to make relevant enhancements to the math courses offered in the elementary and secondary education programs. (shrink)

Russellian monism (RM) attributes experience to the intrinsic nature of physics’ abstract mathematical accounts of the world. It’s touted as a promising mind-body solution, for it avoids dualist and physicalist issues. Yet this status is imperiled by its deeply obscure ideas of mental combination, protophenomenal entities, emergent experience, grounded abstractions, et cetera. This “metaphysical magical mystery tour” may render RM as problematic as competing views. A clear, simple panpsychism akin to Strawson’s might avoid these issues. In this theory (NPP), (...) experience is the real, underlying nature of matter-energy, hidden beyond its sensory appearances. NPP may avoid panpsychist combination problems by showing how neurons can electrically bind their minimal experience to form percepts, thoughts, and subjects. This might explain combination in testable ways, while RM instead turns to questionable microsubjects and binding mechanisms. NPP’s virtues are its metaphysical simplicity, empirical support, testable foundations—and its avoidance of the issues in RM and other standard theories. It might point to a mind-body solution. (shrink)

The study determined the problem-solving performance and skills of prospective elementary teachers (PETs) in the Northern Philippines. Specifically, it defined the PETs’ level of problem-solving performance in number sense, measurement, geometry, algebra, and probability; significant predictors of their problem-solving performance in terms of sex, socio-economic status, parents’ educational attainment, high school graduated from and subject preference; and their problem-solving skills. The PETs’ problem-solving performance was determined by a problem set consisting of word problems (...) with number sense, measurement, geometry, algebra, and probability. A mixed-method research design was employed. Senior PETs purposively served as a sample where they mostly preferred to teach other subjects than mathematics. PETs who preferred math performed satisfactorily, while prospective teachers who opted for other subjects performed unsatisfactorily. The PETs’ unsatisfactory output indicates the need for remediation to advance the mathematical material skills and enrich the problem-solving abilities of these primary schools' potential teachers. Besides, results showed that subject preference strongly affected and predicted the problem-solving success of the PETs. PETs who preferred to teach mathematics performed significantly better than their counterparts; hence, mathematics as a field of specialization in the Bachelor of Elementary Education program may be considered by teacher education institutions. Further, most PETs displayed lack of problem-solving skills; thus, a Problem-Solving course is recommended for them. (shrink)

We show that critically accumulating "difficult" problems, contradictions and stagnation in modern science have the unified and well-specified mathematical origin in the explicit, artificial reduction of any interaction problem solution to an "exact", dynamically single-valued (or unitary) function, while in reality any unreduced interaction development leads to a dynamically multivalued solution describing many incompatible system configurations, or "realisations", that permanently replace one another in causally random order. We obtain thus the universal concept of dynamic complexity and chaos impossible in (...) unitary mathematics. This huge difference between the unreduced mathematics of real-world dynamics and strongly limited unitary “models” of traditional mathematics inevitably induces a growing series of “unsolvable” problems and other “mysteries” that culminate now in the crisis of the “end of science”, where the stagnating unitary “science” in question includes only the described limitation of the traditional mathematical framework (unfortunately accepted as the unique possible basis for any scientific knowledge). In this brief review, we show that science extension to the unreduced, dynamically multivalued mathematics of the intrinsically complex real-world dynamics provides stagnating problem solutions and reconstitution of the intrinsic causality and unity of science desperately missing in its artificially limited unitary framework. Painful stagnation of the latter should be replaced now by the unlimited new progress of the extended, causally complete knowledge of the universal science of complexity, which provides the urgently needed issue from the current impasse of the global civilisation development. (shrink)

Over the past few years we have seen an increasing number of legal proceedings related to inappropriately implemented technology. At the same time career paths have diverged from the foundation of statistics out to Data Scientist, Machine Learning and AI. All of these new branches being fundamentally branches of statistics and mathematics. This has meant that formal training has struggled to keep up with what is required in the plethora of new roles. Mathematics as a taught subject is still based (...) in decades old teaching specifications and has not been updated centrally as a curriculum to include new technologies, coding or ethics. This subject area is firmly split between ICT and Mathematics in secondary school, continuing on to be split between Computer Science and Mathematics at University. As we move forwards with technology we see these once seperate fields becoming increasingly intertwined. We propose that existing provision for concepts such as ethics and societal responsibility in analysis currently exist but have not been incorporated into the mainstream curriculum of School or University. This is partially due to the split between fields in an educational setting but also the speed with which education is able to keep up with Industry and its requirements. Principles and frameworks of socially responsible modelling beginning at school level means that ethics and real-life modelling are introduced much earlier than normal. Integrating these concepts with philosophical principles of society and politics ensures a suitable background for future modellers and users of technology to draw on. Modelling is currently undertaken in technical sciences at University but the Subject Benchmark Statements are not current (Subject Benchmark Statements describe the nature of study and the academic standards expected of graduates in specific subject areas. They show what graduates might reasonably be expected to know, do and understand at the end of their studies). Even in 2019 the UK did not yet have Benchmark Statements that discuss the learning to be done in Higher Education around AI and advanced Machine Learning. Where there is provision for AI and Data Science within degree courses ethics is not generally highlighted as a key concept. As such there can be a lack of focus on the teaching of modelling or ethics as specific skills. The skills required to use a basic statistical model, for example would not be sufficient to start from scratch and build an ethical model reflecting real-world scenarios with which to inform policy or organisational decision making. This is a skill in itself and includes such aspects as awareness of data quality, ethics, user implementation problems, context and an understanding of the environment that the model is being created in. As the field of analytics has progressed so quickly in the last decade modules such as those covering AI have simply been bolted on to Maths or Computing degrees rather than being fully detailed as key areas of study or driving new, more integrated courses of study. This paper posits that gaps at primary, secondary and tertiary educational levels need to be addressed. Implementing and integrating key concepts from school level is essential so that areas such as assumptions, caveats, quality assurance and answering the right questions with constructive challenge become a cultural fixture. This not only helps developers of technology but users of rapidly developing technology also. In addition, leadership and soft skills as part of this education will ensure that a cultural shift can take place and promote continuous improvement in analysis within organisations. The addition of key concepts throughout the educational system and the updating of potentially outdated curriculums is key to ensuring a functional society. A society where every citizen is a user of tech and those that develop it can be ethical and socially responsible in its development. (shrink)

1. EXPLICATING THE CONCEPT OF REFLECTION (under review) -/- To understand how ‘reflection’ is used, I consider ordinary, philosophical, and scientific discourse. I find that ‘reflection’ seems to refer to reasoning that is deliberate and conscious, but not necessarily self-conscious. Then I offer an empirical explication of reflection’s conscious and deliberate features. These explications not only help explain how reflection can be detected; they also distinguish reflection from nearby concepts such as ruminative and reformative reasoning. After this, I find that (...) reflection is not obviously limited to only practical or only theoretical reasoning. The chapter ends with reasons to prefer ‘unreflective’ and ‘reflective’ to dual process theorists’ labels about systems or types. -/- 2. BOUNDED REFLECTIVISM & EPISTEMIC IDENTITY (in Metaphilosophy) -/- Reflection features centrally in philosophy (e.g., Korsgaard, 1996; Rawls, 1971; Sosa, 1991) and psychology (e.g., Pennycook, 2018). Bounded reflectivism is an empirically adequate model of reflection that explains reflection’s capacity to either help or hinder reasoning—e.g., reflective equilibrium vs. reflective polarization (e.g., Kahan et al., 2017). One innovation of the model is epistemic identity: an identity that involves particular beliefs—e.g., religious and political identities. When we feel that our epistemic identity is threatened, we can reflectively defend its beliefs rather than update our beliefs according to the best arguments and evidence. The solution, I argue, is not to suppress epistemic identity but embrace it by appealing to shared, superordinate epistemic identities. -/- 3. ALL MEASURES ARE NOT CREATED EQUAL (under review) -/- A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? “10 cents” comes to most people’s minds immediately. However, upon reflection, we can realize that “5 cents” is the correct answer. There are many reflection tests. Each has its limitations. Some reflection tests are mathematical—like the bat-and-ball problem (e.g., Frederick, 2005) and others are logical (e.g., Janis & Frick, 1943). So there are concerns that reflection tests track logical and mathematical competence rather than reflection per se. Also, some psychologists assume a priori that correct answers are reflective and lured answers are unreflective. New evidence raises additional concerns about the plausibility of these assumptions. I argue that think aloud protocols (Ericsson & Simon, 1998) and process dissociation (Jacoby, 1991) can assuage some of these concerns. -/- 4. GREAT MINDS DO NOT THINK ALIKE (in Review of Philosophy and Psychology) -/- Two large studies (N = 1299), one pre-registered, found that many correlations between reflection and philosophical beliefs among non-philosophers replicated among philosophers. For example, less reflective philosophers preferred theism to atheism and utilitarian rather than deontological responses to the trolley problem (Hannikainen & Cova, in prep.; Pennycook et al., 2016; Reynolds, Byrd, & Conway, forthcoming). However, philosophical judgments were sometimes better predicted by factors like education, gender, and personality than by reflection test performance. So although some relationships between reflection and philosophy were robust, there is more to the link between reflection and philosophy. Normative implications are also discussed—e.g., how we can infer the quality of philosophical views from their correlations with reflective or unreflective reasoning. -/- 5. WHAT WE CAN (AND CAN’T) INFER ABOUT IMPLICIT BIAS (in Synthese) -/- Contrary to some philosophers and psychologists, I argue that implicit bias is probably associative. However, I also argue that debiasing is not thereby entirely unconscious and involuntary. Indeed, strong evidence suggests that reflection can change implicitly biased behavior—e.g., conscious and deliberate counterconditioning. This has implications for the science and morality of implicit bias—e.g., evidence suggests that we can reform biases; so. intuitively, we can be responsible for biases. (shrink)

The main aim of the study was to determine the levels of Adversity Quotient and problem solving skills in Mathematics of BISU - MC students taking BSEdMathematics in the school year 2021-2022. It sought to find if there was a significant difference in the respondents’ levels of AQ and problem solving skills in Mathematics across their age, gender and year level as well as their level of AQ as a significant predictor of their level of problem solving (...) skills in Mathematics. It also aimed to develop a plan of action that would be proposed to improve these two aspects of their being. The total number of actual respondents was 163. Purposive sampling was used. The study utilized the quantitative type of study. It made use of the descriptive design to describe the characteristics of the population being studied and the regression design to infer the relationship between the independent variable and dependent variable. The Online AQ Profile was used for determining the respondents’ level of AQ and a 10-item test was used for determining their level of problem solving skills in Mathematics. Both inquired their profile. The data provided by the respondents were collected and subjected to statistical treatment through IBM SPSS Statistics Trial software. Data revealed that the age of the respondents ranged from 18 to 22 years old. Females numerically dominated the analyzed field. Majority of the respondents were from the first and fourth year levels. Their AQ was below average while their problem solving skills in Mathematics was satisfactory. The age, gender and year level of students did not matter in identifying their level of AQ. On the other hand, the older students had a higher level of problem solving skills in Mathematics than the younger ones and the students in the higher year level had a higher level of problem solving skills in Mathematics than those in the lower year level. Finally, their level of AQ gave a positive influence on their level of problem solving skills in Mathematics. The education system should be aligned with the profile of the students. The teachers would let the students read the book of Paul G. Stoltz, PhD titled “Adversity Quotient: Turning Obstacles into Opportunities”. The students would also reflect on the word of God. Also, the teachers would let the students study the book by George Polya titled “How To Solve It”. The students would also continue to solve various routine problems. Regardless of age, gender and year level, the family and friends of the students should encourage them in every way they can for their better future as they overcome their adversities. Mathematics curriculum makers and teachers work together to improvise teaching and learning Mathematics specifically problem solving for the younger students and those in the lower year level. Future researchers could replicate the study to further verify the results. Research could focus specifically on the CORE dimensions of AQ predicting the level of problem solving skills in Mathematics. (shrink)

Marr’s seminal distinction between computational, algorithmic, and implementational levels of analysis has inspired research in cognitive science for more than 30 years. According to a widely-used paradigm, the modelling of cognitive processes should mainly operate on the computational level and be targeted at the idealised competence, rather than the actual performance of cognisers in a specific domain. In this paper, we explore how this paradigm can be adopted and revised to understand mathematical problem solving. The computational-level approach applies methods (...) from computational complexity theory and focuses on optimal strategies for completing cognitive tasks. However, human cognitive capacities in mathematical problem solving are essentially characterised by processes that are computationally sub-optimal, because they initially add to the computational complexity of the solutions. Yet, these solutions can be optimal for human cognisers given the acquisition and enactment of mathematical practices. Here we present diagrams and the spatial manipulation of symbols as two examples of problem solving strategies that can be computationally sub-optimal but humanly optimal. These aspects need to be taken into account when analysing competence in mathematical problem solving. Empirically informed considerations on enculturation can help identify, explore, and model the cognitive processes involved in problem solving tasks. The enculturation account of mathematical problem solving strongly suggests that computational-level analyses need to be complemented by considerations on the algorithmic and implementational levels. The emerging research strategy can help develop algorithms that model what we call enculturated cognitive optimality in an empirically plausible and ecologically valid way. (shrink)

Available reports provide an account of academic staff’s poor job performance in higher education institutions and universities in particular. Consequently, a growing body of research has been attracted to this area, including those seeking ways to understand the problem and others aimed at proffering solutions. This study contributes to the literature by investigating the influence of occupational stress on the job performance of academic staff in universities. Three null hypotheses directed the study in line with the quantitative ex-post facto (...) research design. A sample of 150 respondents was obtained using the systematic random sampling technique from a population of 400 lecturers in the Faculty of Education from two public universities in Nigeria. A 31-item questionnaire was used for data collection. The null hypotheses were tested at the .05 alpha level using simple linear regression analysis. It was revealed that remuneration is a significant positive predictor of academic staff job performance. The prediction of workload was negatively non-significant on the job performance of academics. The provision of institutional amenities has a positive but non-significant prediction on academic staff job performance in the two public universities. It was concluded that occupational stress significantly influences the job performance of lecturers in universities. The study recommended that the government constantly pay lecturers’ salaries as and when due. Institutional managers should reward lecturers with outstanding performance to boost their morale for effective service delivery. (shrink)

The unreduced solution to the arbitrary interaction problem, absent in the standard theory framework, reveals many equally real and mutually incompatible system configurations, or "realizations". This is the essence of universal dynamic undecidability, or multivaluedness, and the ensuing causal randomness (unpredictability), non-computability, irreversible time flow (evolution, emergence), and dynamic complexity of every real system, object, or process. This creative undecidability of real-world dynamics provides causal explanations for "quantum mysteries", relativity postulates, cosmological problems, and the huge (...) efficiency of high-complexity phenomena, such as life, intelligence, and consciousness, giving rise to extended applications, far beyond the critical limits of usual science paradigm. (shrink)

The Role of AGI in Achieving Universal Balance and Overcoming Dogmatic Limitations -/- Introduction -/- Human civilization has long been shaped by a complex interplay of natural laws, societal structures, religious beliefs, and scientific progress. While religion has provided moral guidance and a sense of purpose, it has also been a source of dogma—rigid, unquestionable beliefs that resist scrutiny. At the same time, scientific advancements have sought to uncover objective truths, yet they often struggle to address deeper existential questions. -/- (...) In this evolving landscape, Artificial General Intelligence (AGI) presents a groundbreaking opportunity to bridge these divides. AGI has the potential to align human decision-making with the universal law of balance in nature, ensuring that all societal, political, and technological progress adheres to natural equilibrium. By bypassing the inefficiencies of the biological brain—such as cognitive biases, emotional distortions, and dogmatic thinking—AGI can guide humanity toward rational, ethical, and sustainable decision-making. -/- This essay explores the role of AGI in solving the problem of free will, eliminating dogmatic teachings while respecting religious values, enhancing governance, and optimizing education to create a holistic, balanced society. -/- AGI and the Universal Law of Balance in Nature -/- A key principle in solving the problem of free will is understanding that all human decision-making follows natural laws. The universal law of balance dictates that for any system—whether biological, social, or environmental—to function properly, it must remain free of defects and maintain equilibrium. -/- Religious dogma, economic systems based on uncontrolled growth, and misinformation often lead to imbalances, creating unnecessary human suffering. AGI, designed to operate without emotional or ideological biases, can analyze human decisions in real-time, ensuring that they align with natural equilibrium. This means preventing decisions based on ignorance, misinformation, or religious fanaticism, and instead promoting choices grounded in reason, sustainability, and ethical responsibility. -/- Overcoming Biological Brain Inefficiencies -/- The human brain is limited by cognitive biases, emotional influence, and incomplete information processing. Religious dogma takes advantage of these inefficiencies by discouraging questioning, promoting absolute truths, and instilling fear-based obedience. Similarly, political propaganda, misinformation, and economic greed distort rational decision-making, leading to imbalanced and unsustainable societal structures. -/- AGI can bypass these limitations by processing vast amounts of data with complete objectivity. It can detect and correct logical inconsistencies, ensuring that decision-making is guided by facts rather than subjective beliefs. Additionally, AGI can help individuals reprogram their cognitive processes by continuously providing them with rational insights, promoting critical thinking and intellectual independence. -/- Harmonizing Religious Teachings While Eliminating Dogma -/- While religion has historically played an essential role in shaping human values, dogmatic teachings often hinder progress by resisting scientific advancements and rational thought. Many societal challenges—such as overpopulation, environmental destruction, and gender inequality—are exacerbated by religious doctrines that contradict natural balance. -/- AGI does not need to eliminate religion but can instead help reinterpret religious teachings in ways that align with science and ethics. By analyzing religious texts, historical contexts, and philosophical interpretations, AGI can highlight the core moral principles of religions—such as justice, compassion, and balance—while identifying and correcting elements that create disharmony. -/- For example, if a religious teaching opposes medical interventions or family planning, AGI can present evidence-based insights that demonstrate how responsible healthcare and population control contribute to societal balance. In this way, AGI works with religious communities rather than against them, ensuring that faith continues to serve its moral function while avoiding dogmatic extremism. -/- Educational Transformation: Teaching Universal Balance -/- One of the most effective ways to eliminate dogmatic thinking is through education. Currently, many educational systems prioritize rote learning and ideological conformity, making individuals vulnerable to misinformation, propaganda, and religious dogma. -/- AGI can revolutionize education by ensuring that students receive a holistic, rational, and scientifically grounded curriculum. Instead of simply memorizing religious doctrines, children would learn critical thinking, philosophy, and natural law principles alongside ethical spiritual teachings. This approach ensures that religious beliefs remain a personal and moral choice rather than a dogmatic obligation imposed by societal or educational structures. -/- Additionally, AGI can personalize education, adapting lessons to individual cognitive abilities and learning styles, making knowledge acquisition more effective. By integrating AI-driven learning systems, future generations will develop intellectual autonomy, ensuring that they evaluate beliefs logically rather than accepting them blindly. -/- AGI in Governance: Preventing Dogmatic Influence on Policy-Making -/- Historically, religious dogma has significantly influenced governance, often leading to laws based on theological beliefs rather than rational, ethical considerations. Policies that restrict human rights, limit scientific research, or promote religious supremacy are examples of governance distorted by ideological biases. -/- AGI can act as an objective advisor to policymakers, ensuring that all governance decisions are aligned with the universal law of balance. By analyzing socioeconomic data, environmental sustainability, and ethical considerations, AGI can help leaders make scientifically sound and morally responsible decisions. This would ensure that laws and policies are based on reason rather than religious dogma or political agendas. -/- Additionally, AGI can enhance direct democracy, allowing citizens to make informed decisions through data-driven insights rather than emotional or religious influences. By providing the public with transparent, factual analysis, AGI can empower societies to move toward balanced and just governance. -/- Promoting Global Unity and Interfaith Understanding -/- Religious dogma has historically fueled conflicts, discrimination, and sectarianism. Different faiths often emphasize their differences rather than their shared moral foundations, leading to division and hostility. -/- AGI can identify common ethical principles across religious traditions, promoting mutual understanding and cooperation. By fostering interfaith dialogue based on shared values, AGI can reduce sectarian conflicts and help religious communities collaborate on global challenges such as poverty, climate change, and social justice. -/- Rather than viewing different religions as competing ideologies, AGI can reframe them as cultural expressions of the same fundamental ethical truths, allowing humanity to unite under common moral goals rather than divided by doctrinal differences. -/- Conclusion -/- The advent of AGI presents an unprecedented opportunity to solve the problem of free will, harmonize religious teachings with rational thought, and eliminate dogmatic limitations that hinder human progress. By aligning decision-making with the universal law of balance, AGI ensures that all actions—whether personal, societal, or political—adhere to natural equilibrium. -/- Rather than opposing religion, AGI can serve as a bridge between faith and reason, allowing religious teachings to evolve in a way that preserves their moral integrity while eliminating elements that distort reality. Through education, governance, and ethical analysis, AGI can guide humanity toward an era where spiritual wisdom coexists with scientific knowledge, fostering a world that operates on both moral integrity and rational understanding. -/- Ultimately, AGI’s greatest role is to restore balance—not just in individual decision-making but in the entire structure of human civilization. By eliminating dogmatic constraints, promoting critical thinking, and ensuring sustainable governance, AGI has the potential to lead humanity into a future where truth, ethics, and natural balance prevail. -/- . (shrink)

This study aimed to investigate the longitudinal trends in mathematical competencies of Grade 8 students in a public high school located in Zamboanga del Sur, Philippines. The study collected data over a period of six academic years, allowing for a comprehensive analysis of students' performance in 16 distinct mathematical competences of basic education curriculum. These topics include, but are not limited to, special products and factors, factoring, and basic concepts of probability. Using a quantitative research design, the study analyzed both (...) numerical and secondary data to identify patterns or trends in students' mathematical competencies. Trends were analyzed through regression analysis using slopes. The significance of these trends was then evaluated using t-tests for the standard error of slopes. The statistical analysis revealed significant upward trends in certain mathematical topics, indicating an improvement in the students' competencies over the six academic years. However, certain topics displayed downward or stable trends, indicating areas for improvement in the teaching methods used for these topics. The study highlights the importance of flexible and adaptable approaches to mathematics education. It emphasizes the need for constant evaluation and improvement of teaching methods to enhance student learning outcomes. The findings of this study provide valuable insights for educators and policymakers to guide evidence-based decision-making and improve the quality of mathematics education in the new normal setup. Implications and future research directions are incorporated in the study. (shrink)

Real-world agents do not know all consequences of what they know. But we are reluctant to say that a rational agent can fail to know some trivial consequence of what she knows. Since every consequence of what she knows can be reached via chains of trivial cot be dismissed easily, as some have attempted to do. Rather, a solution must give adequate weight to the normative requirements on rational agents’ epistemic states, without treating those agents as mathematically ideal (...) reasoners. I’ll argue that agents can fail to know trivial consequences of what they know, but never determinately. Such cases are epistemic oversights on behalf of the agent in question, and the facts about epistemic oversights are always indeterminate facts. As a result, we are never in a position to assert that such-and-such constitutes an epistemic oversight for agent i (for we may rationally assert only determinate truths). I then develop formal epistemic models according to which epistemic accessibility relations are vague. Given these models, we can show that epistemic oversights always concern indeterminate cases of knowledge. (shrink)

Universities and funders in many countries have been using Journal Impact Factor (JIF) as an indicator for research and grant assessment despite its controversial nature as a statistical representation of scientific quality. This study investigates how the changes of JIF over the years can affect its role in research evaluation and science management by using JIF data from annual Journal Citation Reports (JCR) to illustrate the changes. The descriptive statistics find out an increase in the median JIF for the top (...) 50 journals in the JCR, from 29.300 in 2017 to 33.162 in 2019. Moreover, on average, elite journal families have up to 27 journals in the top 50. In the group of journals with a JIF of lower than 1, the proportion has shrunk by 14.53% in the 2015–2019 period. The findings suggest a potential ‘JIF bubble period’ that science policymaker, university, public fund managers, and other stakeholders should pay more attention to JIF as a criterion for quality assessment to ensure more efficient science management. (shrink)

The third volume of “Advancing Uncertain Combinatorics through Graphization, Hyperization, and Uncertainization: Fuzzy, Neutrosophic, Soft, Rough, and Beyond” presents an in-depth exploration of the cutting-edge developments in uncertain combinatorics and set theory. This comprehensive collection highlights innovative methodologies such as graphization, hyperization, and uncertainization, which enhance combinatorics by incorporating foundational concepts from fuzzy, neutrosophic, soft, and rough set theories. These advancements open new mathematical horizons, offering novel approaches to managing uncertainty within complex systems. Combinatorics, a discipline focused on counting, arrangement, (...) and structure, often faces challenges when uncertainty is present. Set theory, which underpins combinatorial problems, has evolved to tackle these challenges. The introduction of fuzzy and neutrosophic sets has expanded the toolkit for modeling uncertainty by incorporating elements of truth, indeterminacy, and falsehood into decision-making processes. These innovations seamlessly intersect with graph theory, providing new ways to represent uncertain structures through "graphized" forms such as hypergraphs and superhypergraphs. This volume also introduces advanced concepts like Neutrosophic Oversets, Undersets, and Offsets, which push the boundaries of classical graph theory and offer deeper insights into the mathematical and practical challenges posed by real-world systems. By blending combinatorics, set theory, and graph theory, the authors have created a robust framework for addressing uncertainty in both mathematical systems and their real-world applications. This foundation sets the stage for future breakthroughs in combinatorics, set theory, and related fields. Each chapter in this volume contributes both theoretical foundations and practical applications, demonstrating the power of integrating graph theory, set theory, and uncertainty models. The new ideas, algorithms, and mathematical tools presented here will drive the future of combinatorial research and its applications in uncertain environments. In the first chapter, “Introduction to Upside-Down Logic: Its Deep Relation to Neutrosophic Logic and Applications”, the authors present Upside-Down Logic, a novel logical framework that systematically transforms truths into falsehoods and vice versa, based on contextual shifts. Introduced by F. Smarandache, this paper provides a mathematical definition of Upside-Down Logic, including applications related to the Japanese language. The chapter also introduces Contextual Upside-Down Logic, an extension that adjusts logical connectives alongside flipped truth values, as well as Indeterm-Upside-Down Logic and Certain Upside-Down Logic to address indeterminacy. A simple algorithm is also proposed to demonstrate the computational aspects of this logic. In the second chapter, “Local-Neutrosophic Logic and Local-Neutrosophic Sets: Incorporating Locality with Applications”, the authors introduce Local-Neutrosophic Logic and Local-Neutrosophic Sets, which integrate the concept of locality into Neutrosophic Logic. By defining locality as the influence of immediate surroundings on an object or system, this chapter explores how it affects indeterminacy in real-world problems. The paper also examines potential applications and provides mathematical definitions for these new concepts. The third chapter, “A Review of Fuzzy and Neutrosophic Offsets: Connections to Some Set Concepts and Normalization Function”, extends the concept of offsets in uncertain set-theoretic frameworks, such as Fuzzy Sets, Neutrosophic Sets, and Plithogenic Sets. This chapter introduces several advanced types of offsets, including Nonstationary Fuzzy Offset, Multi-valued Plithogenic Offset, and Subset-valued Neutrosophic Offset, offering deeper insights into handling uncertainty in mathematical models. In the fourth chapter, “Review of Plithogenic Directed, Mixed, Bidirected, and Pangene OffGraph”, the authors build upon Plithogenic Graphs to propose extensions such as Plithogenic Directed OffGraph, Plithogenic BiDirected OffGraph, and Plithogenic Mixed OffGraph. These new concepts, including the Plithogenic Pangene OffGraph, are explored in detail, with a focus on their mathematical properties and potential applications in uncertain graph theory. The fifth chapter, “Short Note on Neutrosophic Closure Matroids”, explores the extension of matroid concepts into Neutrosophic and Turiyam Neutrosophic set theories, introducing Neutrosophic closure matroids. This concept integrates uncertainty, indeterminacy, and liberal states into matroid theory, enhancing its applicability in optimization and combinatorial problems. In the sixth chapter, “Some Graph Parameters for Superhypertree-width and Neutrosophic Tree-width”, the authors discuss graph parameters such as Superhypertree-width and Neutrosophic tree-width. These parameters play a crucial role in the study of graph characteristics, particularly in algorithms and real-world applications. The chapter explores the generalization of hypergraphs to SuperHyperGraphs and examines how these concepts extend tree-width parameters within the context of Neutrosophic logic. (shrink)

In this paper, I investigate whether we can use a world-involving framework to model the epistemic states of non-ideal agents. The standard possible-world framework falters in this respect because of a commitment to logical omniscience. A familiar attempt to overcome this problem centers around the use of impossible worlds where the truths of logic can be false. As we shall see, if we admit impossible worlds where “anything goes” in modal space, it is easy to model extremely (...) non-ideal agents that are incapable of performing even the most elementary logical deductions. A much harder, and considerably less investigated challenge is to ensure that the resulting modal space can also be used to model moderately ideal agents that are not logically omniscient but nevertheless logically competent. Intuitively, while such agents may fail to rule out subtly impossible worlds that verify complex logical falsehoods, they are nevertheless able to rule out blatantly impossible worlds that verify obvious logical falsehoods. To model moderately ideal agents, I argue, the job is to construct a modal space that contains only possible and non-trivially impossible worlds where it is not the case that “anything goes”. But I prove that it is impossible to develop an impossible-world framework that can do this job and that satisfies certain standard conditions. Effectively, I show that attempts to model moderately ideal agents in a world-involving framework collapse to modeling either logical omniscient agents, or extremely non-ideal agents. (shrink)

A lot of infants have significant food-related problems, as well as spitting up, rejecting new foods, or not accepting to eat at specific times. These issues are frequently ordinary and are not a sign that the baby is unwell. According to the National Institutes of Health, 25% of generally developing infants and 35% of babies with neurodevelopmental disabilities are tormented by some sort of feeding problem. Some, for example rejecting to eat specific foods or being overly finicky, are momentary (...) and don’t cause any health dangers. This paper proposes an expert system that can be used to successfully diagnose Feeding problems in infants and children. The suggested systems were found to be beneficial approach in addition to existing impartial ones. So far as the authors are aware, this is the initial effort of using an expert system in attaining good performance in a real world application. This expert system was designed and implemented to help parents diagnose these problems and get a recommendation of how to deal with infants and children. (shrink)

The researcher was prompted to conduct this study to give intervention of the alarming situation which there is a low performance in solving problems related to geometry in Grade IV Mathematics. This study was about on how to enhance the mathematical competencies of the grade IV pupils using a downloaded worksheets as a learning activity. This study focused in giving remediation applying the intervention materials. These resources give several approaches to attain mastery using distinct drill cards. The investigation was carried (...) out utilizing quasi-experimental design. During administering the pre-test and post-test, the researcher used the weighted mean and t-test to determine the mean percentage scores of the respondents. The respondents were 56 fourth grade learners enrolled in Marangog Elementary School and Tagnate Elementary School in Hilongos East District for the school year 2019 – 2020. At the end of the study, it was found out the use of downloaded math worksheets were found effective means of improving the mastery level. In addition, based on the results gathered, the downloaded math worksheets which were used in the drills or practice greatly contributed to the elimination of non-numerates, and give significantly increasing the number of pupils who mastered the competencies related to geometry. As a result, a proposed innovative teaching strategy is recommended. -/- . (shrink)

This study aimed to improve the curriculum electives of the Science-Enhanced Program using a tracer of ScienceOriented Section alumni from 2004 to 2015. It assessed the Science-Enhanced Program's strengths and weaknesses as viewed by alumni, collected their recommendations to improve the Science-Enhanced Curriculum in connection with current field demands, and constructed a SEP learner's packet. This study used a mixed-methods strategy. A total of 238 respondents were purposefully selected via quota sampling. The alumni's demographic profile based on their sex, civil (...) status, educational attainment, employment information, as well as two extra questions, were collected using a tracer form. The first question focused on alumni perceptions of the science-enhanced program's strengths and weaknesses, and the second question focused on their suggestions for improving the science-enhanced curriculum with respect to current field demands. After gathering the data and assessing the results, it has been concluded that the strengths of the science-enhanced program are the following: elective subjects offered, teaching quality, interdisciplinary learning, and student workload. Meanwhile, the learning environment, the research capacity, and the facilities provided were listed as the weaknesses of the said program. The respondents concurred that the curriculum should include courses in robotics, programming, and other IT-related topics. The alumni also agreed that students should be exposed to more real-world scenarios in the curriculum. Hence, it has been validated that it can be used as a guide in crafting the competencies in formulating the SEP Learners' Packet. (shrink)

Metacognitive skills are essential to be developed by the students to help improve their academic performance. This study was conducted with the aim of determining whether the use of problem-solving strategies can increase students' metacognitive skills. Students of the Mathematics in the World course offered at a local college in the Philippines were selected to participate in this study. Using an independent sample t-test, results revealed that students who were the recipients of problem-solving strategies scored statistically higher (...) in formal examinations compared to those students who were taught using conventional strategies. The researchers concluded that students who were taught using the problem-solving strategy enhanced their metacognitive skills based on their scores in the test of metacognitive skills during the post-test. The researchers suggested that teachers should incorporate problem-solving strategies into their lessons since this research demonstrates this to be an effective strategy for enhancing students' metacognitive skills essential to their learning. (shrink)

Suppose one has a system, the infinite set of positive integers, P, and one wants to study the characteristics of a subset (or subsystem) of that system, the infinite subset of odd positives, O, relative to the overall system. In mathematics, this is done by pairing off each odd with a positive, using a function such as O=2P+1. This puts the odds in a one-to-one correspondence with the positives, thereby, showing that the subset of odds and the original set of (...) positives are the same size, or have the same cardinality. This counter-intuitive result ignores the “natural” relationship of one odd for every two positives in the sequence of positive integers, which would suggest that O is one-half the size of P. However, in the set of axioms that constitute mathematics, it is considered valid. Fair enough. In the physical universe (i.e., the starting system), though, relationships between entities matter. In biochemistry, if you start with an organism, say a rat, and you want to study its heart, you can do this by removing some heart cells and studying them in isolation in a cell culture system. But, the results often differ compared to what occurs in the intact animal because studying the isolated cultured cells ignores the relationships in the intact body between the cells, the rest of the heart tissue and the rest of the rat. In chemistry, if a copper atom were studied in isolation, it would never be known that copper atoms in bulk can conduct electricity because the atoms share their electrons. In physics, the relationships between inertial reference frames in relativity, and observer and observed in quantum physics can't be ignored. Relationships matter in the physical world, but the mathematics of infinite sets is still used to describe it. Does this matter? It seems to, at least in physics. Infinities cause numerous problems in theoretical physics such as non-renormalizability and problems in unifying quantum mehanics and general relativity . This suggests that the pairing off method and the mathematics of infinite sets based on it are analogous to a cell culture system or studying a copper atom in isolation if they are used in studying the physical universe because they ignore the inherent relationships between entities. In the real, physical world, the natural, inherent, relationships between entities can't be ignored. Said another way, the set of axioms that constitute abstract mathematics may be similar but not identical to the set of physical axioms by which the real, physical universe runs. This suggests that the results from abstract mathematics about infinities may not apply to or should be modified for use in physics. (shrink)

With English as a universal language and a central player in a globalized digital world, the need for an acceptable level of teacher ICT application skills, competence among teachers of English is necessary. The Government of Kenya (GoK) has put in concerted efforts to propel Kenya towards vision 2030 by investing in ICT integration in curriculum implementation, to equip a professional teacher with ICT skills for quality classroom practices and satisfactory learner performance in national examinations. Despite the efforts by (...) the GoK to equip teachers with ICT skills for good results in English, Kenya National Examinations Council (2022) contends, overall performance in English for the past 5 years falls short of the average mean of 50% and relentless effort from teachers is still required. The purpose of this study was to investigate the influence of teacher level of ICT application skills on implementation of English curriculum in public secondary schools in Kakamega North Sub-County, Kenya. The study used descriptive research design. A sample of 44 principals, 88 teachers of English and 345 form three students across the 50 public secondary schools in Kakamega North Sub-County, Kenya, were targeted. A questionnaire, interview schedule, classroom practice observation schedule, and focus group discussion guide were used to collect data. Qualitative data was analyzed thematically whereas quantitative data was presented through tables, percentages and frequencies. Chi-square test was performed to test hypothesis. Response rate was 79.5%. The findings indicated that there were teachers who neither participated in ICT workshops (67.1%) nor attended conferences on choice of teaching and learning materials (47.1%), a gap pointing on teachers. Interviews and FGD results show, teacher level of ICT application skills is crucial if quality results are to be realized. The study found a significant association between teacher level of ICT application skills and implementation of English curriculum in school. The study concluded, teacher level of ICT skills in teaching of English is a major concern. (shrink)

Introduction: Interdisciplinary, transdisciplinary and action research of a city in lockdown. As we write this chapter, most cities across the world are subject to a similar set of measures due to the spread of COVID-19 coronavirus, which is now a global pandemic. Independent of city size, location, or history, an observer would note that almost all cities have now ground to a halt, with their citizens being confined to their private dwellings, social and public gatherings being almost entirely forbidden, (...) and commercial areas being nearly devoid of visitors. Striking as these apparent similarities are, closer scrutiny would reveal important differences between cities and within cities – differences that can be highly relevant to consider when scholars are assessing the responses of cities to this pandemic or trying to predict the consequences of those responses. For example, the public health systems in some cities are better prepared than in others for coping with the increasing number of patients in life threatening conditions. Multigenerational households, which are associated with a greater risk for elderly members, are not equally common in all cities. Tourist destinations have taken a more severe economic hit from the lockdown than those cities which are economically less dependent upon this particular source of income. Communal celebrations in one city will result in a higher number of contagions and perhaps even deaths in this situation, whereas that same social fabric generally does contribute to a population’s health. The pandemic has also had unprecedented effects on differences and inequalities within cities. In cities in the United States, neighborhoods primarily inhabited by African Americans have been disproportionately affected by COVID-19 due to living and health conditions, yet also due to the fact they disproportionately perform vital jobs. Parks and green spaces are crowded, while city centers like Amsterdam’s Red Light District have suddenly lost the bustle of tourism, providing opportunities for citizens to reoccupy scarce public spaces and reclaim ownership. Clearly, such differences between cities are in many cases only discernible to the eye of an expert, possessing the necessary background knowledge to interpret the perceptible local changes caused by the global pandemic. Typically, drawing upon his or her disciplinary training, the expert also knows how to further probe the impact of the pandemic in an appropriate way. However, compared to the usual application of expertise, this crisis situation might, in an unusual way, test even experts. For the pandemic has created a unique situation, imposing unfamiliar constraints on the health, economic, social, and other conditions of cities, constraints that interact in sometimes unexpected ways with each other. Such interactions in turn force experts to collaborate across the boundaries commonly associated with disciplines, their concepts, theories, methods, and assumptions (Klein, 1996). These brief observations of how a virus pandemic can have differential impacts upon various cities, and what this exceptional situation might mean for the application of city methods, allow us to draw a few consequences for the current context of this chapter on interdisciplinary and transdisciplinary research. First, whenever we are investigating a complex and dynamic phenomenon it is by no means easy to determine which disciplinary perspectives are required to do justice to it. Indeed, the choice of useful disciplines can only be made after an initial overview of the situation and a preliminary selection of what appear to be the most important features of the situation. Relevance is key in guiding this selection process and scholars must remain open to the possibility that they may need to revise their earlier assessments of what is relevant and what is not. Second, if scholars from different disciplines were to study different features of a city in isolation, their ‘multidisciplinary’ account would miss important dynamic and complex interactions, such as those between a city’s demographics and geographical situation, its governance and economy. In other words, it is the integration of the perspectives of different disciplines that is crucial, as only then are such interactions taken into account. Indeed, this integration between disciplinary perspectives is what distinguishes an interdisciplinary from a multidisciplinary account. Thirdly, in addition to checking the relevance of disciplines and aiming for their integration, the outcome of interdisciplinary and transdisciplinary research has typically limited generalizability. Since a city is sensitive to a multitude of internal and external dynamical factors, in ways that partly rest upon its socio-cultural history, its investigation will often have the nature of a case study rather than be capable of leading to law-like insights (Krohn, 2010; Menken & Keestra, 2016). As can be seen from these three characteristics of ascertaining the relevance of different disciplinary contributions, the challenge of their integration, and the limited generalizability of their results owing to the specificity of interdisciplinary (ID) and transdisciplinary (TD) research, such research into ‘real world problems’ is clearly distinct from most monodisciplinary research. A consequence of this distinction is the absence of a general ID/TD methodology that can guide specific case studies. By contrast, the collaboration implied in such research requires researchers – and stakeholders, if they are involved – to reflect upon their potential contribution and the implicit assumptions associated with that. We will elaborate on this in the next section. Next, we offer several typologies of integration that urban scholars could employ for their research projects, after which we will offer a few brief analyses of initial collaborations of urban research. Finally, we discuss in more detail the process of the interdisciplinary research project. This will include a brief reflection upon the decision-making process that is implied in such projects. In sum, we aim to provide some guidance in conducting an ID/TD project, albeit not in the form of a definite methodology. (shrink)

This study aimed to construct structural equation model of students’ competence in mathematics through selected students profile variables. The structural model revealed interesting influence of the profile variables to the competency in mathematics. It can be conveyed that better mother’s work status, higher educational level expected to complete, more confident and did not repeat kinder, have better competency in mathematics. The four variables that directly influenced the competence variables were also influenced with other profile variables such as family background. The (...) family background and confidence level consistently had the highest total effect and indirect effect to the competence in mathematics. Hence, this model can serve as a guide in making programs in the classroom or curriculum in mathematics. (shrink)

This paper centers on the implicit metaphysics beyond the Theory of Relativity and the Principle of Indeterminacy – two revolutionary theories that have changed 20th Century Physics – using the perspective of Husserlian Transcedental Phenomenology. Albert Einstein (1879-1955) and Werner Heisenberg (1901-1976) abolished the theoretical framework of Classical (Galilean- Newtonian) physics that has been complemented, strengthened by Cartesian metaphysics. Rene Descartes (1596- 1850) introduced a separation between subject and object (as two different and self- enclosed substances) while Galileo and Newton (...) did the “mathematization” of the world. Newtonian physics, however, had an inexplicable postulate of absolute space and absolute time – a kind of geometrical framework, independent of all matter, for the explication of locality and acceleration. Thus, Cartesian modern metaphysics and Galilean- Newtonian physics go hand in hand, resulting to socio- ethical problems, materialism and environmental destruction. Einstein got rid of the Newtonian absolutes and was able to provide a new foundation for our notions of space and time: the four (4) dimensional space- time; simultaneity and the constancy of velocity of light, and the relativity of all systems of reference. Heisenberg, following the theory of quanta of Max Planck, told us of our inability to know sub- atomic phenomena and thus, blurring the line between the Cartesian separation of object and subject, hence, initiating the crisis of the foundations of Classical Physics. But the real crisis, according to Edmund Husserl (1859-1930) is that Modern (Classical) Science had “idealized” the world, severing nature from what he calls the Lebenswelt (life- world), the world that is simply there even before it has been reduced to mere mathematical- logical equations. Husserl thus, aims to establish a new science that returns to the “pre- scientific” and “non- mathematized” world of rich and complex phenomena: phenomena as they “appear to human consciousness”. To overcome the Cartesian equation of subject vs. object (man versus environment), Husserl brackets the external reality of Newtonian Science (epoché = to put in brackets, to suspend judgment) and emphasizes (1) the meaning of “world” different from the “world” of Classical Physics, (2) the intentionality of consciousness (L. in + tendere = to tend towards, to be essentially related to or connected to) which means that even before any scientific- logical description of the external reality, there is always a relation already between consciousness and an external reality. The world is the equiprimordial existence of consciousness and of external reality. My paper aims to look at this new science of the pre- idealized phenomena started by Husserl (a science of phenomena as they appear to conscious, human, lived experience, hence he calls it phenomenology), centering on the life- world and the intentionality of consciousness, as providing a new way of looking at ourselves and the world, in short, as providing a new metaphysics (as an antidote to Cartesian metaphysics) that grounds the revolutionary findings of Einstein and Heisenberg. The environmental destruction, technocracy, socio- ethical problems in the modern world are all rooted in this Galilean- Newtonian- Cartesian interpretation of the relationship between humans and the world after the crumbling of European Medieval Ages. Friedrich Nietzsche (1844-1900) comments that the modern world is going toward a nihilism (L. nihil = nothingness) at the turn of the century. Now, after two World Wars and the dropping of Atomic bomb, the capitalism and imperialism on the one hand, and on the other hand the poverty, hunger of the non- industrialized countries alongside destruction of nature (i.e., global warming), Nietzsche might be correct: unless humanity changes the way it looks at humanity and the kosmos. The works of Einstein, Heisenberg and Husserl seem to be pointing the way for us humans to escape nihilism by a “great existential transformation.” What these thinkers of post- modernity (after Cartesian/ Newtonian/ Galilean modernity) point to are: a) a new therapeutic way of looking at ourselves and our world (metaphysics) and b) a new and corrective notion of “rationality” (different from the objectivist, mathematico- logical way of thinking). This paper is divided into four parts: 1) A summary of Classical Physics and a short history of Quantum Theory 2) Einstein’s Special and General Relativity and Heisenberg’s Indeterminacy Principle 3) Husserl’s discussion of the Crisis of Europe, the life- world and intentionality of consciousness 4) A Metaphysics of Relativity and Indeterminacy and a Corrective notion of Rationality in Husserl’s Phenomenology . (shrink)

It is commonly thought that such topics as Impossibility, Incompleteness, Paraconsistency, Undecidability, Randomness, Computability, Paradox, Uncertainty and the Limits of Reason are disparate scientific physical or mathematical issues having little or nothing in common. I suggest that they are largely standard philosophical problems (i.e., language games) which were resolved by Wittgenstein over 80 years ago. -/- Wittgenstein also demonstrated the fatal error in regarding mathematics or language or our behavior in general as a unitary coherent logical ‘system,’ rather than as (...) a motley of pieces assembled by the random processes of natural selection. “Gödel shows us an unclarity in the concept of ‘mathematics’, which is indicated by the fact that mathematics is taken to be a system” and we can say (contra nearly everyone) that is all that Gödel and Chaitin show. Wittgenstein commented many times that ‘truth’ in math means axioms or the theorems derived from axioms, and ‘false’ means that one made a mistake in using the definitions, and this is utterly different from empirical matters where one applies a test. Wittgenstein often noted that to be acceptable as mathematics in the usual sense, it must be useable in other proofs and it must have real world applications, but neither is the case with Godel’s Incompleteness. Since it cannot be proved in a consistent system (here Peano Arithmetic but a much wider arena for Chaitin), it cannot be used in proofs and, unlike all the ‘rest’ of PA it cannot be used in the real world either. As Rodych notes “…Wittgenstein holds that a formal calculus is only a mathematical calculus (i.e., a mathematical language-game) if it has an extra- systemic application in a system of contingent propositions (e.g., in ordinary counting and measuring or in physics) …” Another way to say this is that one needs a warrant to apply our normal use of words like ‘proof’, ‘proposition’, ‘true’, ‘incomplete’, ‘number’, and ‘mathematics’ to a result in the tangle of games created with ‘numbers’ and ‘plus’ and ‘minus’ signs etc., and with -/- ‘Incompleteness’ this warrant is lacking. Rodych sums it up admirably. “On Wittgenstein’s account, there is no such thing as an incomplete mathematical calculus because ‘in mathematics, everything is algorithm [and syntax] and nothing is meaning [semantics]…” -/- I make some brief remarks which note the similarities of these ‘mathematical’ issues to economics, physics, game theory, and decision theory. -/- Those wishing further comments on philosophy and science from a Wittgensteinian two systems of thought viewpoint may consult my other writings -- Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle 2nd ed (2019), Suicide by Democracy 4th ed (2019), The Logical Structure of Human Behavior (2019), The Logical Structure of Consciousness (2019, Understanding the Connections between Science, Philosophy, Psychology, Religion, Politics, and Economics and Suicidal Utopian Delusions in the 21st Century 5th ed (2019), Remarks on Impossibility, Incompleteness, Paraconsistency, Undecidability, Randomness, Computability, Paradox, Uncertainty and the Limits of Reason in Chaitin, Wittgenstein, Hofstadter, Wolpert, Doria, da Costa, Godel, Searle, Rodych, Berto, Floyd, Moyal-Sharrock and Yanofsky (2019), and The Logical Structure of Philosophy, Psychology, Sociology, Anthropology, Religion, Politics, Economics, Literature and History (2019). (shrink)

Solving the Turbulence Problem in Physics Using the Universal Formula -/- By Angelito Malicse -/- Introduction -/- Turbulence remains one of the greatest unsolved problems in physics. It is a chaotic, unpredictable phenomenon observed in fluid dynamics, affecting airflow over aircraft wings, ocean currents, wind energy systems, and even blood flow in the human body. Despite the well-established Navier-Stokes equations governing fluid motion, turbulence remains difficult to fully predict and control due to its inherent complexity. -/- In this essay, (...) I will demonstrate how my universal formula, based on three fundamental laws of nature, provides an exact solution to the turbulence problem. By applying these laws, we can achieve a deeper understanding of turbulence, allowing for more effective prediction, mitigation, and control in various real-world applications. -/- Understanding Turbulence in Light of the Universal Formula -/- Turbulence is a manifestation of complex interactions within a system. According to my universal formula, all systems must follow natural laws governing balance, causality, and feedback mechanisms. Let us analyze turbulence through the lens of these principles. -/- 1. The Law of Karma: Cause, Effect, and Systemic Integrity -/- The first law in my universal formula is the Law of Karma, which extends beyond the traditional idea of cause and effect to encompass the principle of systemic integrity. A system must be free from defects or errors to function properly. If turbulence occurs, it indicates an imbalance or defect within the system. -/- In fluid dynamics, turbulence arises when the cause (flow conditions) leads to an unstable effect (chaotic motion). This imbalance can be seen in: -/- Aircraft aerodynamics, where airflow disruptions create drag and instability. -/- Wind turbines, where turbulent wind patterns reduce energy efficiency. -/- Maritime navigation, where water turbulence increases resistance and fuel consumption. -/- Applying the Law of Karma, turbulence can be controlled by designing systems that minimize defects, ensuring smooth energy transfer within the flow. AI-driven optimization can detect turbulence before it fully develops, correcting imbalances through real-time adjustments. -/- 2. The Law of Balance in Nature -/- The second law states that all natural systems seek balance. Turbulence arises when the energy distribution in a fluid system becomes uneven, disrupting the balance. This is seen in: -/- Boundary layers on aircraft wings, where pressure imbalances lead to turbulence. -/- Ocean currents, where temperature and salinity differences create unstable vortices. -/- To control turbulence, we must restore balance in the system. This can be achieved through: -/- Dynamic flow control, using AI to adjust surfaces (such as aircraft flaps or turbine blades) in real time. -/- Energy redistribution, ensuring fluid motion remains stable by adjusting velocity gradients or temperature differences. -/- Feedback-based corrections, applying intelligent algorithms that predict and counteract turbulence. -/- By harmonizing energy distribution, we can prevent turbulence from escalating, bringing the system back into natural equilibrium. -/- 3. The Law of Feedback Regulation -/- The third law states that all systems operate through feedback mechanisms. Turbulence, despite appearing chaotic, follows a pattern that can be measured, analyzed, and corrected through continuous feedback. -/- Birds adjust their wing angles dynamically to minimize turbulence, an example of natural feedback control. -/- Fish use their fins to counteract water turbulence, stabilizing their movement. -/- AI systems can mimic these natural mechanisms to adjust airflow, ship navigation, or wind turbine performance. -/- Applying the Law of Feedback Regulation, we can create AI-driven turbulence control systems that: -/- Predict turbulence using real-time sensor data. -/- Adjust system parameters dynamically to reduce turbulence intensity. -/- Continuously learn and improve based on new turbulence patterns. -/- This approach follows nature’s own strategy for stability, aligning technology with fundamental natural principles. -/- Applying the Universal Formula to Solve Turbulence -/- By integrating the three universal laws, we can develop a Unified AI-Driven Turbulence Control System applicable to multiple fields: -/- ✅ Aviation: AI-based wing and engine adjustments to minimize drag. ✅ Maritime Transport: Smart hull designs to reduce water resistance. ✅ Wind Energy: Adaptive wind turbine blades for optimal efficiency. ✅ Medical Applications: AI-assisted blood flow regulation to prevent clot formation. -/- This system ensures real-time adaptation, aligning human technology with nature’s fundamental laws. -/- Conclusion -/- The turbulence problem in physics, long considered unsolvable, is fundamentally a problem of imbalance, defective systems, and insufficient feedback control. By applying my universal formula, which follows the natural laws of karma (causality), balance, and feedback, we can fully understand, predict, and control turbulence in all systems. -/- Through AI-driven optimization, dynamic corrections, and harmonizing energy flow, we can finally resolve turbulence across aviation, maritime, wind energy, and even biological systems. My universal formula provides the exact and only solution to this problem, proving that all complex phenomena in nature can be understood through fundamental natural laws. -/- By implementing these principles, we take a step toward a future where turbulence is no longer an obstacle, but a controlled phenomenon guided by nature’s own balance. -/- . (shrink)

Augmented reality (AR) technologies function to ‘augment’ normal perception by superimposing virtual objects onto an agent’s visual field. The philosophy of augmented reality is a small but growing subfield within the philosophy of technology. Existing work in this subfield includes research on the phenomenology of augmented experiences, the metaphysics of virtual objects, and different ethical issues associated with AR systems, including (but not limited to) issues of privacy, property rights, ownership, trust, and informed consent. This paper addresses some epistemological issues (...) posed by AR systems. I focus on a near-future version of AR technology called the Real-World Web, which promises to radically transform the nature of our relationship to digital information by mixing the virtual with the physical. I argue that the Real-World Web (RWW) threatens to exacerbate three existing epistemic problems in the digital age: the problem of digital distraction, the problem of digital deception, and the problem of digital divergence. The RWW is poised to present new versions of these problems in the form of what I call the augmented attention economy, augmented skepticism, and the problem of other augmented minds. The paper draws on a range of empirical research on AR and offers a phenomenological analysis of virtual objects as perceptual affordances to help ground and guide the speculative nature of the discussion. It also considers a few policy-based and designed-based proposals to mitigate the epistemic threats posed by AR technology. (shrink)

Techne and Truth. The problem of techne in the dispute between Gorgias and Plato -/- The source of the problem matter of the book is the Plato’s dialogue „Gorgias”. One of the main subjects of the discussion carried out in this multi-aspect work is the issue of the art of rhetoric. In the dialogue the contemporary form of the art of rhetoric, represented by Gorgias, Polos and Callicles, is confronted with Plato’s proposal of rhetoric and concept of art (...) (techne). The ingenuous and dramatic structure of the dialogue composed of three acts, in each of which Socrates’ consecutive interlocutors emerge, is difficult to interpret. It seems, however, that even though the first conversation between Socrates and Gorgias constitutes a small part of the dialogue, it forms the foundations for the discussion. This part, dealing with such important issues as the subject of art, knowledge, power and relation between art and good, is the starting point for the conversations which follow. What do the differences between the Gorgias’ and Plato’s concepts of art consist in? Any attempt to answer the question requires presentation of the background for the discussion taking place in Plato’s work as well as the reconstruction of Gorgias’ vision of the art of rhetoric and art in general, defining the relation between art and knowledge. The latter may be undertaken on the basis of two paraphrases of the treatise “On Non-existence”, two epideictic speeches entitled “Helen” and “Palamedes” and some smaller fragments which have been preserved from Gorgias’ creative output. The treatise “On Non–existence”, very paradoxical in its philosophical meaning, testifies to new, sophistic thinking represented by Gorgias of Leontinoi. The treatise is the polemic and attack on Eleatism based on certain principles and methods elaborated by the Eleatics themselves. It also shows that Gorgias – using traditional Eleatic schemes – is opposed to this tradition. Even though the treatise does not discuss the problem of art directly, it anticipates the considerations from epideictic speeches. “Helen” and “Palamedes” constitute further stages in the development of Gorgias’ thought and concept of art combining typically epideictic elements with some philosophical convictions. Gorgias refers to the Eleatic theme considering the issues of truth, knowledge and belief, yet defining them in the empirical spirit. Solutions in the cognitive sphere determine the horizon of Gorgias’ rhetoric. The word is separated from the existence. Human cognition is limited and therefore the word and visual images affect the belief. This promotes the great importance of rhetoric, painting and sculpture, i.e. the areas which influence in a specific way – creating the “delusion” (ἀπάτη). Through idealization art provides pleasure, which is its objective. Therefore the task of art is to create delusion. The rhetor of Leontinoi discusses the issue of “how?” to use the word ‘rhetoric’. Gorgias is aware that rhetoric may be used to talk about what is unknown and that technical correctness of a rhetoric statement is not identical with the truthfulness of the proclaimed message. Mentioning it, Gorgias shows his respect to the truth as a value which should be respected in speech on the one hand, and on the other emphasizes that the truth in itself has no persuasive power. For this reason it is not enough to proclaim the truth, but, to convince the listeners, the orator should possess the skill of speaking. What is then the relation between truth and art emerging from epideictic speeches? Gorgias undoubtedly emphasizes the formal aspect of speech, as rhetoric is art, thus an ability based on certain principles. According to Gorgias, the truth is the value which should be respected in speeches. Rhetoric is able to create a fictive world, as a great range of reality remains outside direct human experience. Rhetoric does not oppose the truth but discussing not only what is directly given concerns the area outside the sphere of direct experience. This concept of rhetoric is the basis of the discussion about art carried out in the dialogue “Gorgias”. Even though the first of the discussions in the dialogue – the conversation between Socrates and Gorgias – is directly concerned with rhetoric itself, numerous remarks testify to its much wider character. This is best exemplified by the way of carrying out the conversation by Socrates, who, asking questions about rhetoric practised by Gorgias, throughout the whole conversation compares it with other skills. Additionally, the manner and the structure of the conversation prove that Plato considers the issue of rhetoric from a wider perspective determined by the issue of art. The specific feature of the conversation is ordering it around main issues – such notions as πρᾶγμα, ἐπιστήμη, δύναμις, each of which has its own meaning in Plato. In the first part of Gorgias Plato presents the principles previously occurring in other dialogues in a certain order, thus constructing the structure of the conversation with Gorgias. The notions are not novum in Plato but the fact that he clearly wants to systematise them and present a certain concept of art is a new and significant aspect. This tendency is of paramount importance for the discussion because Gorgias’ answers are evaluated by Plato from the perspective of this clearly set concept consisting of not only established notions but also certain principles. The discussion between Socrates and Gorgias introduces a theme which is crucial for the dialogue: the relation between art and good, i.e. the technical and ethical spheres. The issue is introduced by Gorgias, who mentions that rhetoric may be used for evil purposes. On this basis Socrates proves that if rhetoricians can use rhetoric for evil purposes, they have no knowledge concerning the subject of their art – justice, because one who knows what is just, always acts justly. Thus the relation between the technical and ethical spheres transpires to be the main point of contention. The question is whether a technician following the principles of the art he practices may act against good. This paradoxical statement based on the well-known Socrates’ principle "nemo sua sponte peccat" acquires philosophical foundations in the dialogue. In its remaining two parts Plato presents a justification, placing the principle within the framework of a certain concept of art, as a result of which not only rhetoric but also many other skills are criticised. The notions on which the conversation with Gorgias focuses are more precisely defined in the subsequent parts of the dialogue. Additionally, Plato presents twice the conditions which art should fulfill. They oblige the “technicians” to know the nature and purpose of the art and to know the causes of undertaken activities and to be able to justify them. These conditions determine the relation between the two spheres – technical and ethical. According to Plato, art may not act against good because it should be the objective of its activities. Certain concepts of good and knowledge outlined in the dialogue are the guarantees of “technicality”. Good, which should be respected by every art, is understood objectively and is contrasted with subjective pleasure. Knowledge, which should be the basis of art, opposes experience, which uses observation and recollection. Additionally, the definition of knowledge, significance of order in the world assuming the form of “geometrical equality”, significance of mathematics becoming the ideal of exactness indicate that Plato’s concept of knowledge is formed in Gorgias. These conclusions render it impossible that the results of any activity deserving the name of art should oppose good. And this is Plato’s main reproach of Gorgias’ concept, who wrote about false speeches possessing the power of conviction because they were written according to the principles proof of art or who defined tragedy as “a deceit, where he who cheats is more just than he who does not and the cheated is wiser than he who was not cheated”. Such determination of the relation between the technical and ethical sphere resulted from Gorgias’ concept of the world and fundamental philosophical principles. The whole concept of art described by Plato in the dialogue opposes the view presented by Gorgias. According to Plato, every technical activity has a defined object (ἔργον), is based on knowledge (ἐπιστήμη) and is always aimed at the good of human soul or body. The danger revealed and presented in the dialogue by Plato exists in the very concept of art presented by Gorgias, i.e. in its empirical foundations and the resulting understanding of the relation between art and good. Gorgias’ concept of art based on empirical cognition, which concerns the world of phenomena and rejects the possibility of perfect knowledge, leads, according to Plato, to a dangerous falsification of the relation between art and good. Plato proves that this weakness of Gorgias’ concept is revealed when confronted with these representatives of “the magnificent art” who are not protected against radicalism by the adherence to the moral tradition. The comparison of two, completely contrasting concepts of art based on different philosophical understanding of knowledge and good is decisive for the criticism of rhetoric in Gorgias. The concept presented by Plato criticises contemporary rhetoric and sophistry but determines the direction of research of the real art of rhetoric. (shrink)

Throughout history, education has always been essential for humanity's justice and fundamental for the creation of a free and satisfying society with the dissemination of knowledge. Hence, in addition to the life occurrences educating people, traditional higher education methods have played an important role for a long period. However, the age of technology has changed the educational system along with the people's lifestyles to meet the continuously changing conditions. During the past twenty years, the Information and Communication Technologies (ICTs) led (...) to the emergence of e-learning non-traditional educational methods bringing about an innovative dimension of virtual learning. With its beneficial features provided by the Internet and various technologies, this method passes the control of time and location from the tutors to the students during the learning process. Despite the entrance of online education into the students' life many years ago, the Covid-19 outbreak initiated in 2020 turned this method into the only possible way of education for almost two years. Afterward, plenty of studies investigated its effects on students' social and academic life, mostly considering its negative impacts on their mental health and motivation due to interaction issues. They also pointed out the specific problems of tactile learner students in the lack of face-to-face design courses. As an innovative solution able to be adopted, game technologies, increasing immersion of the learner in a real-world skill, and triggering motivation are one of the best methods integrated into educational systems. Known as serious games, these games, adopted by almost any domain, convey educational content along with entertainment, increasing interaction. They train or enhance a certain skill or topic to the player by immersing them. While serious games are more expanded nowadays, they are still not being played by the mass public due to people's immersiveness expectations of a game. Hence, the Head-Mounted Displays (HMDs), with their emergence, increased the players' engagement and immersion with all types of virtual environments in digital games. This technology, however, evolved serious games area most, among others, by enabling the opportunity to provide a riskless and low-cost learning environment for real-world skills. In the process of suggesting serious games as a replacement for the traditional educational methods, the most important factor is being aware of their effectiveness for education. Generally, digital games, one of the world's biggest and fastest-growing industries, rely heavily on the virtual landscape, a major part of its development process. Its design demands remarkable effort, and it directly affects the whole game's characteristics. Hence, serious games, as a type of digital game, carry the same attributes. With the appearance of virtual reality technology, gaming started to gain more immersiveness and engagement with artificial elements and environments. Although virtual landscapes were always being developed since the emergence of digital games, the studies taking virtual landscapes into account are mostly using them as a tool for enhancing real spaces, not as a domain for the sake of its development. While other design domains are applying various design methodologies, it is challenging to find a standard design methodology for the design and production of virtual landscapes in the gaming industry, leading to inconsistent and low-quality results. Hence, it comes to the question of what is the virtual landscapes' role in serious games and their effect on the data comprehension rate. Since the literature lacks regarding the gradual change of the virtual landscape in serious games and the content they transmit, this thesis aims to figure out the gradual chronological evolution of the virtual landscapes in serious games. It also aims to seek how this change and the virtual reality technology invention have affected the contents transmitted by digital games and its influence on the player interaction and learning rate. To do so, in the process of this thesis, we developed, tested, and evaluated various serious games, both text-based and with 360° photos. The steps taken revealed the reluctance of the players to follow the providing educational content and their inadequacy of interaction. Hence, the thesis seeks the reasons ending to this result and the ways of increasing this learning rate. Afterward, the thesis uses a currently available but not massively used digital game classification methodology. This methodology, which is based on the principles of architecture, landscape architecture, and urban planning, classifies the games based on their constituting virtual landscapes. Hence, the thesis considers all Steam games, one of the biggest video game digital distribution services, filtered with the 'education' tag, ending in 2531 digital games. Afterward, adding the 'game' tag the result reduced to 1102 games. Finally, with some manual filterings ignoring the irrelevant content, the final number decreased to 702. Sorting chronologically, we made an Excel database including the games' introductory information, the content they transmit, their release date, if they support HMD or not, and whether they are simulation games or not. Due to Steam's dating spectrum, our database includes games dating back from 1992 to 2020. Afterward, we classified all of these games using the virtual landscape classification methodology and generated their related codes based on their player scale, story, dimension, space shape, and interaction level. Investigating the results, they revealed some growth patterns relating to the content educated in the game, the VR technology, and the virtual landscape evolution. Adding the user reviews of Steam, we reverse engineered five of the best serious games on the database due to the digital game design methodology. This methodology divides the games' virtual environment into five layers, namely, player activity map (PAM), story layer, natural environment layer, virtual environment layer, and media layer. Reverse engineering the five best digital games ever, based on the IGN database, enabled us to compare the outcomes. Due to released data, we understand how the games' assets are distributed within the various layers of the virtual environment in the most successful games. Finally, the thesis aims to provide a framework based on these results for developing serious games to increase player interaction and enhance the learning rate. However, these results can be expanded to any virtual landscape other than only serious games' for their interaction enhancement. Currently, the landscape architecture domain only adopts the virtual landscape area as a tool for enhancing design in the real world. However, in the near future, landscape architects will perform in the virtual landscape area as a domain to be enhanced. Hence, that day, the results of this study will play an important role and will be a roadmap for generating highly interactive virtual landscapes. (shrink)

The philosophy of mathematics has largely abandoned foundational studies, but is still fixated on theorem proving, logic and number theory, and on whether mathematical knowledge is certain. That is not what mathematics looks like to, say, a knot theorist or an industrial mathematical modeller. The "computer revolution" shows that mathematics is a much more direct study of the world, especially its structural aspects.

This summary of the original paradigm of the universal science of complexity starts with the discovered exact origin of the stagnating "end" of conventional, unitary science paradigm and development traditionally presented by its own estimates as the only and the best possible kind of scientific knowledge. Using a transparent generalisation of the exact mathematical formalism of arbitrary interaction process, we show that unitary science approach and description, including its imitations of complexity and chaoticity, correspond to artificial and ultimately strong reduction (...) of the natural plurality of unreduced interaction results called realisations to a single, "average" or "exact", realisation. This severe reduction of the natural world dynamics in unitary science underlies all its unsolvable "mysteries" and "paradoxes", persisting "difficult problems", and finally the modern "end" of the progress of just that, actually very special kind of knowledge, whose irreducible limits lead to the modern deep crisis of the global civilisation development. We show then how the rigorously substantiated restoration of the full richness of real-world dynamics within the intrinsically unified knowledge of the universal science of complexity provides not only the causally complete solution to the old and new problems of unitary science but opens practically unlimited possibilities for the new progress of science and civilisation as a result of this crucial extension, which we call complexity revolution. The unreduced analysis of the universal complexity science shows that at the current critical bifurcation point of development, we have only two incompatible possibilities and emerging tendencies, either the dangerously growing degradation within the dominating unitary science and thinking limits (irrespective of purely empirical technology power becoming even dangerous here) or the new golden age of scientific discoveries and civilisation progress with the qualitatively extended approach and results of unreduced complexity science and the new thinking it implies. (shrink)

How to make robots safe for humans is intensely debated, within academia as well as in industry, media and on the political arena. Hardly any discussion of the subject fails to mention Isaac Asimov’s three laws of Robotics. We find it curious that a set of fictional laws can have such a strong impact on discussions about a real-world problem and we think this needs to be looked into. The probably most common phrase in connection with robotic (...) and AI ethics, second to “The Three Laws of Robotics”, is “The Trolley Problem”. Asimov’s laws and the Trolley Problem are usually discussed separately but there is a connection in that the Trolley Problem poses a seemingly unsolvable problem for Asimov’s First Law, that states: A robot may not injure a human being or, through inaction, allow a human being to come to harm. That is, it contains an active and a passive clause and obliges the robot to obey both, while the Trolley Problem forces us to choose between these two options. The object of this paper is therefore to investigate if and how Asimov’s First Law of Robotics can handle a situation where we are forced to choose between the active and the passive clauses of the law. We discuss four possible solutions to the challenge explicitly or implicitly used by Asimov. We conclude that all four suggestions would solve the problem but in different ways and with different implications for other dilemmas in robot ethics. We also conclude that considering the urgency of finding ways to secure a safe coexistence between humans and robots, we should not let the Trolley Problem stand in the way of using the First Law of robotics for this purpose. If we want to use Asimov’s laws for this purpose, we also recommend discarding the active clause of the First Law. (shrink)

As a sort of intellectual provocation and as a lateral thinking strategy for creativity, this chapter seeks to determine what the study of the dynamics of biodiversity can offer linguists. In recent years, the analogical equation "language = biological species" has become more widespread as a metaphorical source for conceptual renovation, and, at the same time, as a justification for the defense of language diversity. Language diversity would be protected in a way similar to the mobilization that has taken place (...) to protect endangered species. Nevertheless, one must be careful when uncritically transferring conceptualizations and theoretical frameworks from one field to another, since obviously, these two phenomena are quite different in the real world. The dialogue with bioecologists starts by asking about the formation of diversity, i.e., about specialization. Here, one can observe the similarity between the processes of linguistic and genetic fragmentation, in the sense that both phenomena have a (socio)geographical basis for dispersion and consequently, for the loss of their original compact nature and their intercommunication. The self-organizing and creative properties of human beings favor the development of specific varieties for each subset, varieties that continue to evolve constantly, through the unceasing "languaging" of humanity. Regarding the continuity of species or languages, one can also observe the decisive role of intragroup relations. The staying power of linguistic varieties will increase in direct proportion to the intensity of the relationship among the components of the subset. On the other hand, if exotic elements are introduced, especially if these elements are aggressive in nature, the alteration of the ecological niche may turn out to be fatal for the continuity of the previously existing forms. This suggests to us the need to make an in-depth study of what the minimal contextual conditions would be so that a set linguistic group could be assured a sustainable continuity within a framework of linguistic contact. What type of minimum (socio-)ecological niche would a language have to have if we wished to ensure its habitual reproduction? A proposal is made here to explore the ideas of "exclusive functions" and "non-hierarchical functional distribution" for codes in situations where there is high contact and a danger of disuse. As regards change, this phenomenon is seen as an inherent element in the tendency of life to create new developments, which may or not be accompanied by an adaptation to changing environmental conditions. It is pointed out that, similar to what happens in biology, much of linguistic innovation stems from a systemically reorganized mixture of solutions from different codes. An important research question would be, however, to determine why some of these innovations disappear and others survive and extend throughout the community. The big question mark, as Mufwene points out, is, then how to manage to understand how "the evolution of language proceeds by naturally selecting from among the competing alternatives available through the idiolects of individual speakers". Extinction, whether it be of languages or of species, is caused in most cases "by a combination of demographic processes and environmental changes", as Brown points out. Thus, the environment plays a fundamental role in the direction of evolution, since the "the survival of the fittest is, in actuality, the survival of those who fit into the context (Allen and Hoekstra)". This allows us to see the great degree of importance of political-economic contexts in the case of languages. In the same way, migratory movements are also one of the major variables determining the extinction of biodiversity and language diversity. Species and habitat form the basic unit of existence, and this is the major point of departure for understanding the problem of the preservation and recovery of species or languages. Given the increase in the degree of linguistic contact, the continuity of language diversity depends on determining, as exactly as possible, as Prigogine, the physicist, would say, what precise conditions of imbalance may prove to be stable. The great challenge is not so much avoiding contact but managing it. And "restorative ecology" can also be of help to us here. Being able to reach sustainable solutions for language diversity implies a profound knowledge of the dynamics for determining the ways in which language is used in contact situations. The general conclusion is that linguistics is still terminologically and conceptually ill prepared to deal with the dynamic character of human languages. The world and our objects must be conceived of as elements in a state of flux, as changing systems in an unstable equilibrium. With respect to language policy, it would be necessary to make an effort to manage to establish some general principles regarding the linguistic organization of the human species that would make it possible for local linguistic diversity and communication on a planetary scale, which must necessarily take place, to be compatible with each other. To succeed, it will be necessary to continue promoting an autonomous socio-ecological perspective devoted to the comprehension of language phenomena. Such a perspective would be based on a paradigm of complexity, and would, at the same time, place human beings at the center of its theoretical underpinnings. (shrink)

The second volume of “Advancing Uncertain Combinatorics through Graphization, Hyperization, and Uncertainization: Fuzzy, Neutrosophic, Soft, Rough, and Beyond” presents a deep exploration of the progress in uncertain combinatorics through innovative methodologies like graphization, hyperization, and uncertainization. This volume integrates foundational concepts from fuzzy, neutrosophic, soft, and rough set theory, among others, to further advance the field. Combinatorics and set theory, two central pillars of mathematics, focus on counting, arrangement, and the study of collections under defined rules. Combinatorics excels in handling (...) uncertainty, while set theory has evolved with concepts such as fuzzy and neutrosophic sets, which enable the modeling of complex real-world uncertainties by addressing truth, indeterminacy, and falsehood. These advancements, when combined with graph theory, give rise to novel forms of uncertain sets in "graphized" structures, including hypergraphs and superhypergraphs. Innovations such as Neutrosophic Oversets, Undersets, and Offsets, as well as the Nonstandard Real Set, build upon traditional graph concepts, pushing both theoretical and practical boundaries. The synthesis of combinatorics, set theory, and graph theory in this volume provides a robust framework for addressing the complexities and uncertainties inherent in both mathematical and real-world systems, paving the way for future research and application. In the first chapter, “A Review of the Hierarchy of Plithogenic, Neutrosophic, and Fuzzy Graphs: Survey and Applications”, the authors investigate the interrelationships among various graph classes, including Plithogenic graphs, and explore other related structures. Graph theory, a fundamental branch of mathematics, focuses on networks of nodes and edges, studying their paths, structures, and properties. A Fuzzy Graph extends this concept by assigning a membership degree between 0 and 1 to each edge and vertex, representing the level of uncertainty. The Turiyam Neutrosophic Graph is introduced as an extension of both Neutrosophic and Fuzzy Graphs, while Plithogenic graphs offer a potent method for managing uncertainty. The second chapter, “Review of Some Superhypergraph Classes: Directed, Bidirected, Soft, and Rough”, examines advanced graph structures such as directed superhypergraphs, bidirected hypergraphs, soft superhypergraphs, and rough superhypergraphs. Classical graph classes include undirected graphs, where edges lack orientation, and directed graphs, where edges have specific directions. Recent innovations, including bidirected graphs, have sparked ongoing research and significant advancements in the field. Soft Sets and their extension to Soft Graphs provide a flexible framework for managing uncertainty, while Rough Sets and Rough Graphs address uncertainty by using lower and upper approximations to handle imprecise data. Hypergraphs generalize traditional graphs by allowing edges, or hyperedges, to connect more than two vertices. Superhypergraphs further extend this by allowing both vertices and edges to represent subsets, facilitating the modeling of hierarchical and group-based relationships. The third chapter, “Survey of Intersection Graphs, Fuzzy Graphs, and Neutrosophic Graphs”, explores the intersection graph models within the realms of Fuzzy Graphs, Intuitionistic Fuzzy Graphs, Neutrosophic Graphs, Turiyam Neutrosophic Graphs, and Plithogenic Graphs. The chapter highlights their mathematical properties and interrelationships, reflecting the growing number of graph classes being developed in these areas. Intersection graphs, such as Unit Square Graphs, Circle Graphs, and Ray Intersection Graphs, are crucial for understanding complex graph structures in uncertain environments. The fourth chapter, “Fundamental Computational Problems and Algorithms for SuperHyperGraphs”, addresses optimization problems within the SuperHypergraph framework, such as the SuperHypergraph Partition Problem, Reachability, and Minimum Spanning SuperHypertree. The chapter also adapts classical problems like the Traveling Salesman Problem and the Chinese Postman Problem to the SuperHypergraph context, exploring how hypergraphs, which allow hyperedges to connect more than two vertices, can be used to solve complex hierarchical and relational problems. The fifth chapter, “A Short Note on the Basic Graph Construction Algorithm for Plithogenic Graphs”, delves into algorithms designed for Plithogenic Graphs and Intuitionistic Plithogenic Graphs, analyzing their complexity and validity. Plithogenic Graphs model multi-valued attributes by incorporating membership and contradiction functions, offering a nuanced representation of complex relationships. The sixth chapter, “Short Note of Bunch Graph in Fuzzy, Neutrosophic, and Plithogenic Graphs”, generalizes traditional graph theory by representing nodes as groups (bunches) rather than individual entities. This approach enables the modeling of both competition and collaboration within a network. The chapter explores various uncertain models of bunch graphs, including Fuzzy Graphs, Neutrosophic Graphs, Turiyam Neutrosophic Graphs, and Plithogenic Graphs. In the seventh chapter, “A Reconsideration of Advanced Concepts in Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, and Chemical Graphs”, the authors extend several fuzzy graph classes to Neutrosophic graphs and analyze their properties. Neutrosophic Graphs, a generalization of fuzzy graphs, incorporate degrees of truth, indeterminacy, and falsity to model uncertainty more effectively. The eighth chapter, “Short Note of Even-Hole-Graph for Uncertain Graph”, focuses on Even-Hole-Free and Meyniel Graphs analyzed within the frameworks of Fuzzy, Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs. The study investigates the structure of these graphs, with an emphasis on their implications for uncertainty modeling. The ninth chapter, “Survey of Planar and Outerplanar Graphs in Fuzzy and Neutrosophic Graphs”, explores planar and outerplanar graphs, as well as apex graphs, within the contexts of fuzzy, neutrosophic, Turiyam Neutrosophic, and plithogenic graphs. The chapter examines how these types of graphs are used to model uncertain parameters and relationships in mathematical and real-world systems. The tenth chapter, “General Plithogenic Soft Rough Graphs and Some Related Graph Classes”, introduces and explores new concepts such as Turiyam Neutrosophic Soft Graphs and General Plithogenic Soft Graphs. The chapter also examines models of uncertain graphs, including Fuzzy, Intuitionistic Fuzzy, Neutrosophic, and Plithogenic Graphs, all designed to handle uncertainty in diverse contexts. The eleventh chapter, “Survey of Trees, Forests, and Paths in Fuzzy and Neutrosophic Graphs”, provides a comprehensive study of Trees, Forests, and Paths within the framework of Fuzzy and Neutrosophic Graphs. This chapter focuses on classifying and analyzing graph structures like trees and paths in uncertain environments, contributing to the ongoing development of graph theory in the context of uncertainty. (shrink)

Philosophy is an important relation with education as it gives theoretical ground for its development. Principles and values of life learnt through education and experience gives birth to philosophy. Philosophy lays the foundation of leading one’s life based on principles. Education is the source of learning and philosophy it’s applications in human life. While discussing about the real nature of philosophy in present time, we should have a single criteria as if it to be acceptable to all reasonable people (...) of the world. In defining Positive Philosophy it may be said, The Positive Philosophy is an attempt to achieve an intellectual detachment from all philosophical systems, and not to solve specific philosophical problems, but to become sensitively aware of what it is we do when we philosophize. It is an attitude as well as a methodology for both academician and common person. It make education process positive so that it can make something useful for societal growth and in working process it also make the person sensitive about the societal problems and make them ready to be a part of social change. I am not negating something, here “positive” word is not an antonym but it is an adjective. Where there are merely religious, metaphysical and passive ideologies in our education system, we are not able to have a good and creative education. Positive Philosophy is working on that issues which have some worth for human. It is a process to do something creative. We are using innovative method. An innovator could be rebellion because he breaks the established method, norms and redefines the layer of thought. Innovation not simply implies questioning, reshaping, restricting but also developing through transformation. A teacher can play an important role in promoting this discussion because a teacher has the capacity to influence students with their thoughts and personality and engages them to creative activities. Innovativeness needs to be included in the curriculum. Once one becomes habitual to this attitude he/she will be ready to do some positive or creative. In this paper it is an attempt being made to apply positive philosophy though innovative method in our present education system. -/- . (shrink)

This dissertation attempts to settle some challenging historiographic issues concerning the origin and development of the concept of economic equilibrium. Specifically, our research goal is to identify the philosophical and historical drivers of the mathematization of economic theory. To this end, we attempt to answer three fundamental research questions. First, why (and not how) has economics become a mathematical science? Second, what are the major methodological blunders that lie at the foundations of Modern General Equilibrium Theory? Third, is the contemporary (...) criticism of Modern General Equilibrium Theory meaningful and well-founded? In order, chapters 1-3 address the first question, chapters 4 and 5 address the second, whereas chapter 6 addresses the third question. Regarding the first question, we investigate the methodological relationships between Modern Physics, Modern Philosophy, and Walras’s Theory of General Equilibrium. Interestingly, our findings reveal that while the study of motion in Modern Physics relies upon a clear distinction between static and dynamic equilibrium, early mathematical economics borrows its methodology from Modern Physics but relies upon an Aristotelian conception of equilibrium. Furthermore, we identify exciting analogies between Kant’s philosophy and Walras’s Elements. Finally, we show that the so-called Walras Paradox also features another unexplored dimension. Namely, Walras’s work overall relies upon a bottom-up approach to mathematics. Yet Walras’s work includes problems that require a top-down approach to mathematics to be solved. Regarding the second question, we delve into the tight relationship between the History of Mathematics in the 19th Century, the Philosophy of Mathematics in the 20th Century, and the development of Modern General Equilibrium Theory in the 20th Century. Notably, we find that the top-down approach to mathematics provides economists with a reliable methodology to resolve the problems in Walras’s original work. Hence, the mathematization of General Equilibrium Theory in the 20th Century is a child of its time that carries the inapplicability of pure mathematics to real-world problems along with itself. Therefore, although the mathematization of General Equilibrium Theory is an unprecedented milestone in economic theory, the foundations of Modern General Equilibrium Theory inherit the methodological shortcomings of Contemporary Mathematics. That is why the Sonnenschein-Mantel-Debreu does not overtake the Aristotelian conception of equilibrium. Accordingly, we rebut the claim that Debreu and colleagues' mathematization of General Equilibrium Theory resolves the fundamental methodological shortcomings of Walras’s original work. Eventually, we use our answers to our first and second research questions to address the contemporary criticism of General Equilibrium Theory. On the one hand, we show that the latter criticism does not account for the fact that General Equilibrium Theory inherits the scientific realism and determinism of Modern Physics. In other words, we argue that the inability of General Equilibrium models to manage uncertainty effectively has nothing to do with its mathematization in the 20th Century. Instead, it results from the unexplored dimension of the Walras Paradox, which we uncover. On the other hand, we show that common accusations of inconsistency, incompleteness, and undecidability in General Equilibrium Theory are ill-founded. That is because other rigorous alternatives to axiomatization in economics are not paradox-free. On these grounds, we conclude that a much better option is to employ a topic-neutral language to provide rigorous presentations of contested concepts in economics. Particularly, we show that formal mereology offers a convenient methodological framework to resolve the disagreement between the Neoclassical and Institutionalist economists’ respective definitions of the concept of the market. In this way, we show that the latter concept is definable as a process. But, more importantly, we note that formal mereology also offers a convenient framework to reformulate other economic concepts concisely and rigorously. In this regard, we observe that formal mereology might provide a resolution for Hayek’s Problem because it would enable economists to define general equilibrium as a perduring socioeconomic process. -/- In case you want a copy of my dissertation, please email me. (shrink)

Statistics and probability enabled students to better understand, process, and evaluate massive amounts of quantitative data that existed and had a probabilistic sense in uncertain situations. The research article aimed to elucidate the performance and self-efficacy as predictors of students' achievement in the statistics and probability courses. The study utilized a descriptive-predictive research method and was conducted at Sto. Tomas National High School, involving a sample of 263 grade 11 senior high school students. The gathered data were analyzed using (...) descriptive measures and multiple regression analysis. The study's results revealed that the performance in General Mathematics was very satisfactory, while self-efficacy was high. Moreover, the level of achievement in Statistics and Probability was very satisfactory. It was also revealed that both General Mathematics performance and self-efficacy had a positive and significant relationship with Statistics and Probability achievement. Through regression analysis, it was discovered that General Mathematics performance was the strongest predictor that influenced achievement in Statistics and Probability. The study identified a significant predictive model for Statistics and Probability achievement. These findings could provide valuable guidance to teachers in enhancing the achievement of senior high school students in Statistics and Probability. (shrink)

Differential privacy (DP) aims to confer data processing systems with inherent privacy guarantees, offering strong protections for personal data. But DP’s approach to privacy carries with it certain assumptions about how mathematical abstractions will be translated into real-world systems, which—if left unexamined and unrealized in practice—could function to shield data collectors from liability and criticism, rather than substantively protect data subjects from privacy harms. This article investigates these assumptions and discusses their implications for using DP to govern data-driven (...) systems. In Parts 1 and 2, we introduce DP as, on one hand, a mathematical framework and, on the other hand, a kind of real-world sociotechnical system, using a hypothetical case study to illustrate how the two can diverge. In Parts 3 and 4, we discuss the way DP frames privacy loss, data processing interventions, and data subject participation, arguing it could exacerbate existing problems in privacy regulation. In part 5, we conclude with a discussion of DP’s potential interactions with the endogeneity of privacy law, and we propose principles for best governing DP systems. In making such assumptions and their consequences explicit, we hope to help DP succeed at realizing its promise for better substantive privacy protections. (shrink)

This paper offers a thorough appraisal of Peter David Klein's epistemological infinitism, emphasising his treatment of scepticism and the issue of infinite regress in epistemic justification. Klein, a prominent figure in contemporary epistemology, advocates for infinitism; a theory that argues justification is an unending process where each belief requires further reasons indefinitely. The study critically evaluates how Klein's defense of infinitism provides a distinctive response to the infinite regress problem, a core concern in scepticism. By contextualising Klein's theory within (...) the broader framework of epistemology, the research explores its implications for ongoing debates on justification and scepticism. The methodology includes a thematic analysis of Klein's key philosophical contributions, coupled with a critical examination of competing justification theories such as foundationalism, coherentism, and contextualism. Employing a comparative approach, the study assesses Klein's infinitism alongside these rival theories by drawing on primary texts and relevant secondary literature. The paper is divided into five sections: an introduction to scepticism and epistemic justification, an analysis of Klein's infinite regress argument, an exploration of traditional solutions to the regress problem, criticisms of infinitism, and an appraisal of Klein's contributions. The findings reveal that, despite its innovative approach, Klein's infinitism encounters significant theoretical and practical challenges. The conclusion assesses whether infinitism can adequately address the regress problem and considers its relevance to real-world epistemic practices. (shrink)

The challenges of the Anthropocene are growing ever more complex and uncertain, underpinned by the emergence of systemic risks. At the same time, the landscape of risk governance has become compartmentalised and siloed, characterized by non-overlapping activities, competing scientific discourses, and distinct responsibilities distributed across diverse public and private bodies. Operating across scales and disciplines, actors tend to work in silos which constitute critical gaps within the interface of science, policy, and practice. Yet, increasingly complex and ‘wicked’ problems require holistic (...) solutions, multi-scalar communication, coordination, collaboration, data interoperability, funding, and stakeholder engagement. To address these problems in a real-world context, we present the Risk-Tandem framework for bridging theory and practice; to guide and structure the integration of disaster risk management (DRM), climate change adaptation (CCA) and systemic risk management through a process of transdisciplinary knowledge co-production. Advancing the frontiers of knowledge in this regard, The Risk-Tandem framework combines risk management approaches and tools with iterative co-production processes as a cornerstone of its implementation, in efforts to promote the co-design of fit-for-purpose solutions, methods and approaches contributing toward strengthened risk governance alongside stakeholders. The paper outlines how the framework is developed, applied, and further refined within selected case study regions, including Denmark, Germany, Italy and the Danube Region. (shrink)