In recent years, the prediction of air quality has become a critical task due to its significant impact on human health and the environment. With urbanization and industrial growth, the need for accurate air quality forecasting has become more urgent. Traditional methods for air quality prediction are often based on statistical models or physical simulations, which, while valuable, can struggle to capture the complexity of air pollution dynamics. This study explores the use of deep learning (...) techniques to predict air quality, providing a comparative analysis of different neural network models and their performance. (shrink)

The results show that the hybrid CNN-LSTM model outperforms the individual models in terms of prediction accuracy and robustness, suggesting that combining convolutional layers with recurrent units is beneficial for capturing both spatial and temporal patterns in air quality data. This study demonstrates the potential of deep learning methods to offer real-time, accurate air quality forecasting systems, which can aid policymakers and urban planners in managing air pollution more effectively.

In recent years, the prediction of air quality has become a critical task due to its significant impact on human health and the environment. With urbanization and industrial growth, the need for accurate air quality forecasting has become more urgent. Traditional methods for air quality prediction are often based on statistical models or physical simulations, which, while valuable, can struggle to capture the complexity of air pollution dynamics. This study explores the use of deep learning (...) techniques to predict air quality, providing a comparative analysis of different neural network models and their performance. (shrink)

We investigate the application of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a hybrid CNN-LSTM model for forecasting air pollution levels based on historical data. Our experimental setup uses real-world air quality datasets from multiple regions, containing measurements of pollutants like PM2.5, PM10, CO, NO2, and SO2, alongside meteorological data such as temperature, humidity, and wind speed. The models are trained, validated, and tested using a split dataset, and their accuracy is evaluated using performance metrics like (...) Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared. (shrink)

This study presents a neural network-based model for predicting smoke potential in a specific area using a Kaggle-derived dataset with 15 environmental features and 62,631 samples. Our five-layer neural network achieved an accuracy of 89.14% and an average error of 0.000715, demonstrating its effectiveness. Key influential features, including temperature, humidity, crude ethanol, pressure, NC1.0, NC2.5, SCNT, and PM2.5, were identified, providing insights into smoke occurrence. This research aids in proactive smoke mitigation and public health protection. The model's accuracy and feature (...) analysis empower decision-makers, with potential applications in real-time smoke event monitoring and preparedness strategies. This work contributes to the field of air quality forecasting and environmental stewardship, offering a data-driven approach to address smoke-related challenges and enhance community well-being. (shrink)

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future work (...) will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future work (...) will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution (...) to enhancing water quality monitoring and decision-making for stakeholders and policymakers. (shrink)

The current study is conducted to examine the following research question: What are the factors associated with the sensitivity towards the air quality rating index to reduce outdoor activities?

The current study is conducted to examine the following research question: 1) Who were the people who had no access to wildfire smoke notifications during the smoke event in the summer of 2018 in the Boise Metropolitan Area in Idaho? 2) Who were the people who were not familiar with the air quality rating system?

We investigate the application of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a hybrid CNN-LSTM model for forecasting air pollution levels based on historical data. Our experimental setup uses real-world air quality datasets from multiple regions, containing measurements of pollutants like PM2.5, PM10, CO, NO2, and SO2, alongside meteorological data such as temperature, humidity, and wind speed. The models are trained, validated, and tested using a split dataset, and their accuracy is evaluated using performance metrics like (...) Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared. (shrink)

Expeditious increase in population and industrialization has led to alarming rates of air pollution in all countries. However, developing economies have had to face a more adverse and severe impact. This had led to many changes in the day to day living of citizens. In this paper we have focused on the psychological process and predictors of migration intention of the people living in Hanoi, Vietnam. Two stratified random datasets of 475 people were used, and Bayesian analysis was performed on (...) this dataset. We found out that the intent to move was negatively associated to the individual’s satisfaction with air quality. We also found that people who have family members that have fallen victim to a disease caused by air pollution are more likely to migrate. This paper discusses an important topic: immigration of the younger demographic, i.e. the Hanoi workforce, which may cause restrictions and hurdles in the city's urbanisation and development. The findings suggest that, if measures against air pollution are not taken, economic forces may be disrupted, posing a threat to urban growth. As a result, collaborative activities and steps need to be taken by the government to curb this unfortunate consequence. (shrink)

Purpose: This article aims to highlight key indicators of residents' quality of life in a specific contemporary building in Kruja, Albania. -/- Design/Method/Approach: A questionnaire with 30 questions was prepared for the inhabitance, and the Binary or Tobit probabilistic models were taken into consideration as part of the methodology, to conclude. The study will further analyze the implications of the inhabitants and their behavior in a specific contemporary building in the city of Kruja. It was examined the statistical significance (...) of each variable (questions) in the models elaborated with EViews 8 software. The stable models that are associated with the “Log-likelihood” statistics were statistically significant at a significance level of p < 5%, or with 95% confidence, based on the model tests. -/- Findings: The study concluded that the most statistically significant quality of life indicators part of the questionnaire is related to the typology of the apartments, methods of cooling during summer, present living conditions, apartment improvement, apartment orientation, and time spent in the living room. Furthermore, the study reveals that most of the quality-of-life indicators (part of the questionnaire) are not statistically important, so they will not be considered part of the models created in the article. The study reveals that increasing the living space and improving orientation is crucial to enhance the satisfaction of apartment inhabitants. When apartment sizes increase and orientation is improved, residents are more likely to opt for fans over air conditioners to reduce electricity costs and avoid installing additional cooling facilities during summer. They believe that better living conditions require larger apartments, additional water supply, increased electrical costs, and more time spent in the living room. The inhabitants also emphasize the importance of reducing moisture levels, decreasing window opening frequency, and increasing time spent with family. Interestingly, a one-degree improvement in summer cooling methods (e.g., switching from air blowers to air conditioning) corresponds to a one-degree improvement in winter heating methods (e.g., switching from gas to electricity), leading to a heightened need for clean electric heating. Overall, the study emphasizes the importance of meeting the physical and spatial needs of the residents to enhance their overall satisfaction and quality of life. Urban policies significantly impact housing affordability, quality, transport systems, environmental sustainability, and social equity, affecting overall living standards and economic growth. Cities must create well-designed policies that consider residents' needs and study findings to ensure sustainable development and citizen welfare. -/- Theoretical Implications: Gujarati’s (Basic Economics) theory was developed in the article. -/- Practical Implications: This study will serve as an indicator to analyze the further improvements that might occur in the specific building (not just in the city of Kruja), considering the main quality of life indicators. -/- Originality/Value: The article will serve as a base for further analysis of resident’s behavior and their social impact in the community in order to be aware of their needs for further developments in the construction field. -/- Research Limitations/Future Research: The findings depend profoundly on the type of building the residents are living in. The research stream that can be inspired by the research is strongly related to mathematical regression models, statistics, and probability. -/- Paper Type: Empirical . (shrink)

In this paper, a predictive artificial neural network (ANN) model was developed and validated for the purpose of prediction whether a watermelon is good or bad, the model was developed using JUSTNN software environment. Prediction is done based on some watermelon attributes that are chosen to be input data to the ANN. Attributes like color, density, sugar rate, and some others. The model went through multiple learning-validation cycles until the error is zero, so the model is 100% percent (...) accurate for the purpose of prediction whether good or bad the watermelon is. (shrink)

On the basis of PM2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided premature (...) deaths in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors. (shrink)

Continued urbanization, along with anthropogenic global warming, has and will increase land surface temperature and air temperature anomalies in urban areas when compared to their rural surroundings, leading to Urban Heat Islands (UHI). UHI poses environmental and health risks, affecting both psychological and physiological aspects of human health. Thus, using a deep learning approach that considers morphological variables, this study predicts UHI intensity in 69 European cities from 2007 to 2021 and projects UHI impacts for 2050 and 2080. The research (...) employs Artificial Neural Networks, Deep Neural Networks, and Gated Recurrent Units, combining high-resolution 3D urban models with environmental data to analyze UHI trends. The results indicate strong associations between urban form, weather patterns, and UHI intensity, highlighting the need for customized urban planning and policy measures to reduce UHI impacts and foster sustainable urban settings. This research enhances understanding of UHI dynamics and serves as a valuable tool for urban planners and policymakers to address the challenges of climate change, urbanization, and air pollution, ultimately aiding in the improvement of health outcomes and building energy consumption. Moreover, the methodology effectively demonstrates the ability of the GRU to link its scores with UHI projections, offering crucial insights into potential health impacts. (shrink)

Abstract: This study introduces a machine learning-based model for predicting student performance using a comprehensive dataset derived from educational sources, encompassing 15 key features and comprising 62,631 student samples. Our five-layer neural network demonstrated remarkable performance, achieving an accuracy of 89.14% and an average error of 0.000715, underscoring its effectiveness in predicting student outcomes. Crucially, this research identifies pivotal determinants of student success, including factors such as socio-economic background, prior academic history, study habits, and attendance patterns, shedding light on the (...) nuanced dynamics of student performance. The key influential features identified in this study offer valuable insights into the complex factors shaping student achievement. These insights are vital for educators, policymakers, and institutions seeking to enhance educational outcomes and promote equitable access to quality education. This research provides a data-driven foundation for proactive interventions, personalized learning strategies, and support systems, ultimately contributing to improved student performance and academic success. The high accuracy of the predictive model and the feature analysis it provides empower decision-makers in the education sector. This model holds significant potential for applications in student performance monitoring, early intervention, and tailored educational strategies. By adopting a data-driven approach, this work advances the field of educational analytics and contributes to the goal of fostering student success and educational equity. (shrink)

Abstract: Heart attacks, or myocardial infarctions, are a leading cause of mortality worldwide. Early prediction and accurate analysis of potential risk factors play a crucial role in preventing heart attacks and improving patient outcomes. In this study, we conduct a comprehensive review of datasets related to heart attack analysis and prediction. We begin by examining the various types of datasets available for heart attack research, encompassing clinical, demographic, and physiological data. These datasets originate from diverse sources, including hospitals, (...) research institutions, and public health agencies. Our analysis aims to identify common features, data quality, and potential biases in these datasets. Next, we explore the predictive modeling techniques employed in heart attack prediction. Machine learning algorithms, such as decision trees, support vector machines, and deep neural networks, have gained prominence in predicting heart attacks. We discuss the strengths and limitations of these methods and highlight recent advancements in predictive modeling. Furthermore, we delve into the critical risk factors associated with heart attacks. Factors such as age, gender, hypertension, diabetes, and cholesterol levels are examined for their significance in predicting cardiac events. We also investigate the role of lifestyle factors, including smoking, diet, and physical activity, in heart attack risk assessment. Additionally, this review addresses the importance of data preprocessing and feature engineering in improving prediction accuracy. Feature selection methods, missing data handling, and data scaling techniques are discussed to enhance the robustness of heart attack prediction models. In conclusion, this comprehensive dataset review provides valuable insights into the state of heart attack analysis and prediction. It serves as a resource for researchers and healthcare professionals seeking to better understand the datasets available for heart attack research and the methods employed for accurate prediction. Ultimately, our efforts in dataset analysis and predictive modeling contribute to the advancement of preventive cardiology and the reduction of heart attack-related morbidity and mortality. (shrink)

Previous research has assessed school facilities, administrative expenditures and curriculum and their relative contributions to students’ cognitive learning outcomes. This suggested the need to investigate further how these predictors may impact students’ affective and psychomotor outcomes. The current research studied the combined and relative prediction of school facilities, administrative expenses and curriculum on students’ overall cognitive, affective and psychomotor learning outcomes in public secondary schools. A cross-sectional research design was employed in this study, involving 87 school administrators and a (...) randomly selected group of 915 senior secondary class II (SS2) students. For data collection, we utilised the School Inputs Questionnaire (SIQ) and Educational Outcomes Questionnaire (EOQ), both developed by the researchers and validated through expert assessments, including content validity, Exploratory Factor Analysis (EFA) for dimensionality, Confirmatory Factor Analysis (CFA) for goodness of fit, and reliability using Cronbach's alpha. The results of these assessments demonstrated acceptable outcomes aligned with international standards. Hierarchical regression analysis was conducted to analyse the collected data. The findings indicated that enhancing the provision of quality school facilities, administrative expenses, and school curricula improved students' overall cognitive, affective, and psychomotor learning outcomes. Specifically, administrative expenses and school curriculum had significant predictive power for students’ overall cognitive, affective, and psychomotor learning outcomes. However, while school facilities significantly predicted students' overall, affective, and psychomotor dimensions, they did not significantly predict the cognitive dimension. These findings offer valuable insights for policymakers and educators aiming to enhance the educational quality in public secondary schools. (shrink)

After long arguments between positivism and falsificationism, the verification of universal hypotheses was replaced with the confirmation of uncertain major premises. Unfortunately, Hemple proposed the Raven Paradox. Then, Carnap used the increment of logical probability as the confirmation measure. So far, many confirmation measures have been proposed. Measure F proposed by Kemeny and Oppenheim among them possesses symmetries and asymmetries proposed by Elles and Fitelson, monotonicity proposed by Greco et al., and normalizing property suggested by many researchers. Based on the (...) semantic information theory, a measure b* similar to F is derived from the medical test. Like the likelihood ratio, measures b* and F can only indicate the quality of channels or the testing means instead of the quality of probability predictions. Furthermore, it is still not easy to use b*, F, or another measure to clarify the Raven Paradox. For this reason, measure c* similar to the correct rate is derived. Measure c* supports the Nicod Criterion and undermines the Equivalence Condition, and hence, can be used to eliminate the Raven Paradox. An example indicates that measures F and b* are helpful for diagnosing the infection of Novel Coronavirus, whereas most popular confirmation measures are not. Another example reveals that all popular confirmation measures cannot be used to explain that a black raven can confirm “Ravens are black” more strongly than a piece of chalk. Measures F, b*, and c* indicate that the existence of fewer counterexamples is more important than more positive examples’ existence, and hence, are compatible with Popper’s falsification thought. (shrink)

The emergence of new techniques in both microbial biotechnology and artificial intelligence (AI) is opening up a completely new field for monitoring and sometimes even controlling the evolution of pathogens. However, the now famous generative AI extracts and reorganizes prior knowledge from large datasets, making it poorly suited to making predictions in an unreliable future. In contrast, an unfamiliar perspective can help us identify key issues related to the emergence of new technologies, such as those arising from synthetic biology, whilst (...) revisiting old views of AI or including generative AI as a generator of abduction as a resource. This could enable us to identify dangerous situations that are bound to emerge in the not-too-distant future, and prepare ourselves to anticipate when and where they will occur. Here, we emphasize the fact that amongst the many causes of pathogen outbreaks, often driven by the explosion of the human population, laboratory accidents are a major cause of epidemics. This review, limited to animal pathogens, concludes with a discussion of potential epidemic origins based on unusual organisms or associations of organisms that have rarely been highlighted or studied. (shrink)

Air pollution is a significant environmental concern that affects human health, ecosystems, and climate change. Effective monitoring and management of outdoor air quality are crucial for mitigating its adverse effects. This paper presents an advanced approach to outdoor pollution measurement utilizing Internet of Things (IoT) technology, combined with optimization techniques to enhance system efficiency and data accuracy. The proposed framework integrates a network of IoT sensors that continuously monitor various air pollutants, such as particulate matter (PM), carbon monoxide (CO), (...) sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃), across different geographic locations. The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. (shrink)

Integrating the concept of place meanings into protected area management has been difficult. Across a diverse body of social science literature, challenges in the conceptualization and application of place meanings continue to exist. However, focusing on relationships in the context of participatory planning and management allows protected area managers to bring place meanings into professional judgment and practice. This paper builds on work that has outlined objectives and recommendations for bringing place meanings, relationships, and lived experiences to the forefront of (...) land-use planning and management. It proposes the next steps in accounting for people’s relationships with protected areas and their relationships with protected area managers. Our goals are to 1) conceptualize this relationship framework; 2) present a structure for application of the framework; and 3) demonstrate the application in a specific protected area context, using an example from Alaska. We identify three key target areas of information and knowledge that managers will need to sustain quality relationship outcomes at protected areas. These targets are recording stories or narratives, monitoring public trust in management, and identifying and prioritizing threats to relationships. The structure needed to apply this relationship-focused approach requires documenting and following individual relationships with protected areas in multiple ways. The goal of this application is not to predict relationships, but instead to gain a deeper understanding of how and why relationships develop and change over time. By documenting narratives of individuals, managers can understand how relationships evolve over time and the role they play in individual’s lives. By understanding public trust, the shared values and goals of individuals and managers can be observed. By identifying and prioritizing threats, managers can pursue efforts that steward relationships while allowing for the protection of experiences and meanings. The collection and interpretation of these three information targets can then be integrated and implemented within planning and management strategies to achieve outcomes that are beneficial for resource protection, visitor experiences, and stakeholder engagement. By investing in this approach, agencies will gain greater understanding and usable knowledge towards the achievement of quality relationships. It represents an investment in both place relationships and public relations. By integrating such an approach into planning and management, protected area managers can represent the greatest diversity of individual place meanings and connections. relationships, place meanings, trust, narratives, planning, protected areas. (shrink)

Wearable devices are increasingly present in the health context, as tools for biomedical research and clinical care. In this context, wearables are considered key tools for a more digital, personalised, preventive medicine. At the same time, wearables have also been associated with issues and risks, such as those connected to privacy and data sharing. Yet, discussions in the literature have mostly focused on either technical or ethical considerations, framing these as largely separate areas of discussion, and the contribution of wearables (...) to the collection, development, application of biomedical knowledge has only partially been discussed. To fill in these gaps, in this article we provide an epistemic (knowledgerelated) overview of the main functions of wearable technology for health: monitoring, screening, detection, and prediction. On this basis, we identify 4 areas of concern in the application of wearables for these functions: data quality, balanced estimations, health equity, and fairness. To move the field forward in an effective and beneficial direction, we present recommendations for the 4 areas: local standards of quality, interoperability, access, and representativity. (shrink)

Plato's Theaetetus discusses and ultimately rejects Protagoras's famous claim that "man is the measure of all things." The most famous of Plato's arguments is the Self-Refutation Argument. But he offers a number of other arguments as well, including one that I call the 'Future Argument.' This argument, which appears at Theaetetus 178a−179b, is quite different from the earlier Self-Refutation Argument. I argue that it is directed mainly at a part of the Protagorean view not addressed before , namely, that all (...) beliefs concerning one's own future sensible qualities are true. This part of the view is found to be inconsistent with Protagoras's own conception of wisdom as expertise and with his own pretenses at expertise in teaching. (shrink)

Magnetic levitation system is operated primarily based at the principle of magnetic attraction and repulsion to levitate the passengers and the train. However, magnetic levitation trains are rather nonlinear and open loop unstable which makes it hard to govern. In this paper, investigation, design and control of a nonlinear Maglev train based on NARMA-L2, model reference and predictive controllers. The response of the Maglev train with the proposed controllers for the precise role of a Magnetic levitation machine have been as (...) compared for a step input signal. The simulation consequences prove that the Maglev teach system with NARMA-L2 controller suggests the quality performance in adjusting the precise function of the system and the device improves the experience consolation and street managing criteria. (shrink)

Breast cancer is the leading cause of death among women with cancer. Computer-aided diagnosis is an efficient method for assisting medical experts in early diagnosis, improving the chance of recovery. Employing artificial intelligence (AI) in the medical area is very crucial due to the sensitivity of this field. This means that the low accuracy of the classification methods used for cancer detection is a critical issue. This problem is accentuated when it comes to blurry mammogram images. In this paper, convolutional (...) neural networks (CNNs) are employed to present the traditional convolutional neural network (TCNN) and supported convolutional neural network (SCNN) approaches. The TCNN and SCNN approaches contribute by overcoming the shift and scaling problems included in blurry mammogram images. In addition, the flipped rotation-based approach (FRbA) is proposed to enhance the accuracy of the prediction process (classification of the type of cancerous mass) by taking into account the different directions of the cancerous mass to extract effective features to form the map of the tumour. The proposed approaches are implemented on the MIAS medical dataset using 200 mammogram breast images. Compared to similar approaches based on KNN and RF, the proposed approaches show better performance in terms of accuracy, sensitivity, spasticity, precision, recall, time of performance, and quality of image metrics. (shrink)

The literature is predominated by studies seeking to clarify the extent of the availability, functionality, accessibility and/or utilisation of library materials in schools at various levels. The extent of principals' management of library resources and their contribution to the lesson preparation activities of teachers seems to have been under-researched. In bridging the gap, the current study was designed to assess the extent and contribution of principals’ management of library resources to teachers’ lesson preparation practices. Six specific objectives were of interest (...) to the researchers. The quantitative research method, following the ex-post facto research design, was adopted. The stratified proportional random sampling technique was used to choose a sample of 743 respondents from a population of 1,857 secondary school teachers in Ikom Education Zone, Cross River State, Nigeria. An instrument named "Management of Library Resources and Teachers' Lesson Preparation Questionnaire" (MLRTLPQ) was used to gather data. The quantitative content validity method was used to assess the degree to which the items in the instrument were clear, relevant, and represented a wide range of the anticipated content based on the views of domain experts. One sample t-test and hierarchical regression analyses were used for data analyses. Four stepwise hierarchical linear models were specified and fitted accordingly. It was found that teachers’ lesson preparation practice is significantly low generally; there is a significantly low extent in principals’ management of textual, auditory, visual and audio-visual library resources; there is a significant composite contribution of principals’ management of library resources on teachers’ lesson preparation practices in public secondary schools in model 3 and model 4. Based on these findings, practical implications are discussed, with recommendations made for a better library management practice in secondary schools for quality lesson preparation practices. (shrink)

In my dissertation I critically survey existing theories of time consciousness, and draw on recent work in neuroscience and philosophy to develop an original theory. My view depends on a novel account of temporal perception based on the notion of temporal qualities, which are mental properties that are instantiated whenever we detect change in the environment. When we become aware of these temporal qualities in an appropriate way, our conscious experience will feature the distinct temporal phenomenology that is associated with (...) the passing of time. The temporal qualities model of perception makes two predictions about the mechanisms of time perception; one that time perception is modality specific and the other that it can occur without awareness. My argument for this view partially depends on a number of psychophysical experiments that I designed and implemented myself and which investigate subjective time distortions caused by looming visual stimuli. These results show that the mechanisms of conscious experience of time are distinct from the mechanisms of time perception, as my theory of temporal qualities predicts. (shrink)

Air pollutants pose a threat to biodiversity throughout the world. This study was conducted to evaluate atmospheric element accumulation in Isparta city, including Gölcük Nature Park, located in the Western Mediterranean Region of Turkey. It is aimed to determine the air quality and potential pollutant sources in the region through lichen biomonitoring. Specimens of the epiphytic foliose lichen Physcia aipolia (Erh. ex Humb.) Fürnr. were sampled from 14 sites in the study area and analyzed by ICP-MS with reference material (...) in order to detect 11 trace elements; Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn. The spatial distribution of these airborne elements in the study area was mapped. The results showed that the elemental sequence in terms of average concentrations measured was as follows: Ni >Cr >V >Fe >As >Al >Zn >Cu> >Cd >Mn >Pb. The results of cluster analyses of the elemental data indicated that the 3 major contaminants in the urban area were Cr, Ni, and V, probably due to the extensive use of coal in heating facilities and gasoline in vehicles. P. aipolia specimens accumulated maximal concentrations of As, Cr, Fe, Ni, and V in the northern and the southeastern localities surrounding the city, while Cd, Pb were most abundant in the eastern edge of Gölcük Nature Park. The pollution in Isparta city with heavy metal is worse than expected, mostly due to the extensive use of coal as fossil fuel. In addition, it seems to be associated with the city's topographic and climatic characteristics, e.g. inversion effects. (shrink)

Coronavirus disease-19 (COVID-19), produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic, giving rise to a serious health threat globally. The global Covid-19 pandemic is a setback for sustainable development and compromise the world commitment to the 2030 Agenda for Sustainable Development. The measures taken to control the spread of the virus and the slowdown of economic activities during lockdown have significant effects on the environment. Therefore, this review discuss the indirect positive and negative (...) impacts of Covid-19 pandemic towards sustainable environment. This study indicates that, the pandemic situation significantly improves air quality in different cities across the world, reduces the emission of greenhouse gases, and decreases water and noise pollution, which may help in the restoration of the ecosystem. In addition, there are also some negative impact of Covid-19, such as increase of medical waste, haphazard use and disposal of disinfectants, mask, and gloves; and burden of untreated wastes continuously endangering the environment. It points to the fact that the net effect has been positive; in terms of reduction in greenhouse emissions, oil exploration activities, and pollution. It is expected that the proper implementation of the proposed suggestion might be helpful for the global environmental sustainability. (shrink)

Developing countries have seen rapid economic growth, but they have also faced unprecedented environmental challenges, including air pollution, water pollution, land pollution, waste pollution, etc. Take air pollution as an example. It is alarming that 99 percent of the world’s population breathes polluted air. Air pollution is deemed a “quiet killer”, giving rise to numerous consequences ranging from health and psychological impacts to economic and social costs. For example, air pollution annually causes roughly 7 million premature deaths and an economic (...) loss of USD 8.1 trillion, accounting for 6.1% of the global GDP. Furthermore, it is worth noting that the urban population is projected to exceed two-thirds of the total global population by 2050, as urbanization exacerbates the air pollution problem, creating even more air pollution challenges for humankind in the long run. Every new piece of information matters for scientific progress in air pollution assessment, policymaking, and public health protection. From this viewpoint, the goal/objective of this Special Issue (SI) of Urban Science is to keep communities, scholars, and policymakers informed on the research progress on air quality and human health. Specifically, this SI serves as a forum for advancing scientific understanding of environmental changes associated with air pollution and air quality, strategies and/or different measures that the public, particularly urban residents, can employ to lessen and/or mitigate unexpected impacts. I hope that the useful information and insightful findings presented by scholars in this SI can support or facilitate desirable urban environment policies that help, ultimately, increase human and societal wellbeing. (shrink)

Our perceptual experience is largely based on prediction, and as such can be influenced by knowledge of forthcoming events. This susceptibility is commonly exploited by magicians. In the Vanishing Ball Illusion, for example, a magician tosses a ball in the air a few times and then pretends to throw the ball again, whilst secretly concealing it in his hand. Most people claim to see the ball moving upwards and then vanishing, even though it did not leave the magician’s hand (...) (Kuhn & Land, 2006; Triplett, 1900). But what exactly can such illusions tell us? We investigated here whether seeing a real action before the pretend one was necessary for the Vanishing Ball Illusion. Participants either saw a real action immediately before the fake one, or only a fake action. Nearly one third of participants experienced the illusion with the fake action alone, while seeing the real action beforehand enhanced this effect even further. Our results therefore suggest that perceptual experience relies both on long-term knowledge of what an action should look like, as well as exemplars from the immediate past. In addition, whilst there was a forward displacement of perceived location in perceptual experience, this was not found for oculomotor responses, consistent with the proposal that two separate systems are involved in visual perception. (shrink)

Cities and towns are expanding and thriving as a result of urbanization, which also significantly changes the local climate. One of the most significant phenomena associated with urbanization is the Urban Heat Island (UHI) effect. This phenomenon is increasingly being studied worldwide. The paper aims to investigate the UHI phenomenon in the metropolitan area of Tirana, Albania. It analyses the impact of the UHI on four specific locations in Tirana, its causes and mitigation measures, as well as variations in surface (...) temperature, CO2 emissions, and relative humidity. The regions are measured and observed using a specific instrument such as the Testo 435. Considering the mean surface temperature variations between urban and rural regions ranging from 28.4°C to 33.7 °C, CO2 emissions from 302.9 ppm to 416.2 ppm, and relative humidity from 34.1% to 41.2%, it is found that the UHI impact in Tirana is significant. The lack of green spaces, high building density, urban patterns, building materials used, transport, and energy use are the main contributors to the UHI in central Tirana. Increasing green spaces, using reflective materials, and promoting sustainable urban design are some of the mitigation techniques suggested to reduce the UHI effect in Tirana. (shrink)

Aim: To elicit preferences for prognostic information, attitudes towards withdrawal of life-sustaining treatment (WLST) and perspectives on acceptable quality of life after post-anoxic coma within the adult general population of Germany, Italy, the Netherlands and the United States of America. Methods: A web-based survey, consisting of questions on respondent characteristics, perspectives on quality of life, communication of prognostic information, and withdrawal of life-sustaining treatment, was taken by adult respondents recruited from four countries. Statistical analysis included descriptive analysis and (...) chi2-tests for dierences between countries. Results: In total, 2012 respondents completed the survey. In each country, at least 84% indicated they would prefer to receive early prognostic information. If a poor outcome was predicted with some uncertainty, 37-54% of the respondents indicated that WLST was not to be allowed. A conscious state with severe physical and cognitive impairments was perceived as acceptable quality of life by 17–44% of the respondents. Clear differences between countries exist, including respondents from the U.S. being more likely to allow WLST than respondents from Germany (OR = 1.99, p < 0.001) or the Netherlands (OR = 1.74, p < 0.001) and preferring to stay alive in a conscious state with severe physical and cognitive impairments more than respondents from Italy (OR = 3.76, p < 0.001), Germany (OR = 2.21, p < 0.001), or the Netherlands (OR = 2.39, p < 0.001). Conclusions: Over one-third of the respondents considered WLST unacceptable when there is any remaining prognostic uncertainty. Respondents had a more positive perspective on acceptable quality of life after coma than what is currently considered acceptable in medical literature. This indicates a need for a closer look at the practice of WLST based on prognostic information, to ensure responsible use of novel prognostic tests. (shrink)

Variable quality essays dominated by reductionist nonsense. This is a followup to Hofstadter´s famous Godel, Escher, Bach (1980). Like its predecessor, it is concerned largely with the foundations of artificial intelligence, but it is composed mostly of stories, essays and extracts from a wide range of people, with a few essays by DH and DD and comments to all of the contributions by one or the other of them. For my views on the attempts of D and H to (...) understand behaviour see my review of D's " I am a Strange Loop. " Much of it is very reductionistic in tone (ie, " explains " everything in terms of physics/math and denies " reality " of psychology) but as Hofstadter notes, the quantum field equations of a water molecule are too complex to solve (and so is a vacuum)and nobody has a clue about how to explain the way properties emerge(eg, water properties from H2 and 02) as you go up the scale from the vacuum to the brain, so reductionism, like holism, requires a great deal of faith and in fact is incoherent as one cannot even frame it's arguments without presupposing the coherence of higher order thought. Additional problems for reductionism are the uncertainty principle, chaos (eg, no way to predict how a pile of sand will fall) and the logically necessary incompleteness of math (and all thought). In sum, though there are many interesting comments, like nearly all writing on behavior this work lacks any coherent account of the logical structure of rationality which I give in my more recent writings. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019). (shrink)

This chapter begins with an empirical analysis of attitudes towards the law, which, in turn, inspires a philosophical re-examination of the moral status of the rule of law. In Section 2, we empirically analyse relevant survey data from the US. Although the survey, and the completion of our study, preceded the recent anti-police brutality protests sparked by the killing of George Floyd, the relevance of our observations extends to this recent development and its likely reverberations. Consistently with prior studies, we (...) find that people’s ascriptions of legitimacy to the legal system are predicted strongly by their perceptions of the procedural justice and lawfulness of police and court officials’ action. Two factors emerge as significant predictors of people’s compliance with the law: (i) their belief that they have a (content-independent, moral) duty to obey the law (which is one element of legitimacy, as defined here); and (ii) their moral assessment of the content of specific legal requirements (‘perceived moral content of laws’). We also observe an interactive relationship between these two factors. At higher levels of perceived moral content of laws, felt duty to obey is a better predictor of compliance. And, similarly, perceived moral content of laws is a better predictor of compliance at higher levels of felt duty to obey. This suggests that the moral content incorporated in specific laws interacts with the normative force people ascribe to legal authorities by virtue of other qualities, specifically here procedural justice and lawfulness. In Section 3, the focus shifts to a philosophical analysis, whereby we identify a parallel (similarly interactive) modality in the way that form and content mutually affect the value of the rule of law. We advocate a distinctive alternative to two rival approaches in jurisprudential discourse, the first of which claims that Lon Fuller’s eight precepts of legality embody moral qualities not contingent on the law’s content, while the second denies any independent moral value in these eight precepts, viewing them as entirely subservient to the law’s substantive goals. In contrast, on the view put forward here, Fuller’s principles possess (inter alia) an expressive moral quality, but their expressive effect does not materialise in isolation from other, contextual factors. In particular, the extent to which it materialises is partly sensitive to the moral quality of the law’s content. (shrink)

The laws which predict how the perceptual quality of figure-ground can be extracted from the most elementary visual signals were discovered by the Gestaltists, and form an essential part of their movement (see especially Metzger, 1930, and Wertheimer, 1923 translated and re-edited by Lothar Spillmann, 2009 and 2012, respectively). Distinguishing figure from ground is a prerequisite for perception of both form and space (the relative positions, trajectories, and distances of objects in the visual field. The human brain has an (...) astonishing capacity for selecting and combining a few critical visual signals to accurately represent both form and space. (shrink)

The triumph of scientific materialism in the Seventeenth Century not only bifurcated nature into matter and mind and primary and secondary qualities, as Alfred North Whitehead pointed out in Science and the Modern World. It divided science and the humanities. The core of science is the effort to comprehend the cosmos through mathematics. The core of the humanities is the effort to comprehend history and human nature through narratives. The life sciences can be seen as the zone in which the (...) conflict between these two very different ways of comprehending the world collide. Evolutionary theory as defended by Schelling developed out of natural history, but efforts have been made to formulate neo-Darwinism through mathematical models. However, it is impossible to eliminate stories from biology. As Stuart Kauffman argued, mathematical models attempt to pre-state all possibilities, but in evolution there can be adjacent possibles that can be embraced by organisms but cannot be pre-stated. To account for such actions it is necessary to tell stories. Mathematics provides analytic precision allowing long chains of deductions, but tends to deny temporal becoming and cannot do justice to the openness of the future, while narratives focus on processes and events, but lack exactitude that would provide precise deductions and predictions. In advancing mathematics adequate to life, Robert Rosen argued that living beings as anticipatory systems must have models of themselves, and strove to develop a form of mathematics able to model life itself. It has been convincingly argued that narratives are central to human self-creation and they are lived out before being explicitly told. Their models of themselves are first and foremost, stories or narratives. If this is the case, might not living beings as biological entities be characterized by proto-stories or narratives in their models of themselves? Biosemiotics, largely inspired by C.S. Peirce, provides a bridge between mathematical and narrative comprehension, conceiving them as different forms of semiosis. The study of life through biosemiotics could reveal how mathematics and narratives can be understood in relation to each other. This could have implications for how we understand science and the humanities and their relationship to each other. In this paper I will examine work in theoretical biology that might advance these efforts. (shrink)

Even though the evidence‐based medicine movement (EBM) labels mechanisms a low quality form of evidence, consideration of the mechanisms on which medicine relies, and the distinct roles that mechanisms might play in clinical practice, offers a number of insights into EBM itself. In this paper, I examine the connections between EBM and mechanisms from several angles. I diagnose what went wrong in two examples where mechanistic reasoning failed to generate accurate predictions for how a dysfunctional mechanism would respond to (...) intervention. I then use these examples to explain why we should expect this kind of mechanistic reasoning to fail in systematic ways, by situating these failures in terms of evolved complexity of the causal system(s) in question. I argue that there is still a different role in which mechanisms continue to figure as evidence in EBM: namely, in guiding the application of population‐level recommendations to individual patients. Thus, even though the evidence‐based movement rejects one role in which mechanistic reasoning serves as evidence, there are other evidentiary roles for mechanistic reasoning. This renders plausible the claims of some critics of evidencebased medicine who point to the ineliminable role of clinical experience. Clearly specifying the ways in which mechanisms and mechanistic reasoning can be involved in clinical practice frames the discussion about EBM and clinical experience in more fruitful terms. (shrink)

This essay is a sustained attempt to bring new light to some of the perennial problems in philosophy of mind surrounding phenomenal consciousness and introspection through developing an account of sensory and phenomenal concepts. Building on the information-theoretic framework of Dretske (1981), we present an informational psychosemantics as it applies to what we call sensory concepts, concepts that apply, roughly, to so-called secondary qualities of objects. We show that these concepts have a special informational character and semantic structure that closely (...) tie them to the brain states realizing conscious qualitative experiences. We then develop an account of introspection which exploits this special nature of sensory concepts. The result is a new class of concepts, which, following recent terminology, we call phenomenal concepts: these concepts refer to phenomenal experience itself and are the vehicles used in introspection. On our account, the connection between sensory and phenomenal concepts is very tight: it consists in different semantic uses of the same cognitive structures underlying the sensory concepts, such as the concept of red. Contrary to widespread opinion, we show that information theory contains all the resources to satisfy internalist intuitions about phenomenal consciousness, while not offending externalist ones. A consequence of this account is that it explains and predicts the so-called conceivability arguments against physicalism on the basis of the special nature of sensory and phenomenal concepts. Thus we not only show why physicalism is not threatened by such arguments, but also demonstrate its strength in virtue of its ability to predict and explain away such arguments in a principled way. However, we take the main contribution of this work to be what it provides in addition to a response to those conceivability arguments, namely, a substantive account of the interface between sensory and conceptual systems and the mechanisms of introspection as based on the special nature of the information flow between them. (shrink)

Magnetic levitation system is operated primarily based at the principle of magnetic attraction and repulsion to levitate the passengers and the train. However, magnetic levitation trains are rather nonlinear and open loop unstable which makes it hard to govern. In this paper, investigation, design and control of a nonlinear Maglev train based on NARMA-L2, model reference and predictive controllers. The response of the Maglev train with the proposed controllers for the precise role of a Magnetic levitation machine have been as (...) compared for a step input signal. The simulation consequences prove that the Maglev teach system with NARMA-L2 controller suggests the quality performance in adjusting the precise function of the system and the device improves the experience consolation and street managing criteria. (shrink)

Being sure of each other is the blossoming of Kimberley Brownlee’s earlier work on the intrinsic value and qualities of human connection (2013, 2016c, 2016b), opening with a scene from A. A. Milne’s House at Pooh Corner: lost in the woods together, Piglet takes Pooh’s paw ‘just to be sure’ of his friend. The importance of social connection is often overlooked because it is central to our lives, like breathable air. Brownlee’s work highlights the need for social connection, as deserving (...) of more philosophical attention and practical protection through rights. But her key insight is that receiving relational goods isn’t all that matters: being able and permitted to provide relational goods to others, as Piglet and Pooh receive and offer each other reassurance, is just as essential for our wellbeing. Brownlee argues these interests are strong enough to ground rights (2016c: 28). (shrink)

Legal theorists have characterized physical evidence of brain dysfunction as a double-edged sword, wherein the very quality that reduces the defendant’s responsibility for his transgression could simultaneously increase motivations to punish him by virtue of his apparently increased dangerousness. However, empirical evidence of this pattern has been elusive, perhaps owing to a heavy reliance on singular measures that fail to distinguish between plural, often competing internal motivations for punishment. The present study employed a test of the theorized double-edge pattern (...) using a novel approach designed to separate such motivations. We asked a large sample of participants (N = 330) to render criminal sentencing judgments under varying conditions of the defendant’s mental health status (Healthy, Neurobiological Disorder, Psychological Disorder) and the disorder’s treatability (Treatable, Untreatable). As predicted, neurobiological evidence simultaneously elicited shorter prison sentences (i.e., mitigating) and longer terms of involuntary hospitalization (i.e., aggravating) than equivalent psychological evidence. However, these effects were not well explained by motivations to restore treatable defendants to health or to protect society from dangerous persons but instead by deontological motivations pertaining to the defendant’s level of deservingness and possible obligation to provide medical care. This is the first study of its kind to quantitatively demonstrate the paradoxical effect of neuroscientific trial evidence and raises implications for how such evidence is presented and evaluated. (shrink)

Vaccination against various diseases has been widely practised for more than a century and on a more limited scale its use in a variety of forms stretches back far longer. During earlier eras disease spread more slowly along shipping lanes on water and traditional transport routes on land. Today, in an era of air transport, contagion spreads far more rapidly. Travelling far more rapidly (indeed instantaneously) is the spread of misinformation that hinders vaccination which can, in the instance of Covid-19, (...) reduce disease impacts, including rates of severe illness and death. This paper explores the ethical issue of informed consent in the context of the contest between personal choice and the greater public welfare. It also makes reference to a number of low, middle and high income countries where vaccine hesitance, and to a lesser extent refusal, has been fed by misinformation on a scale not previously observed but made possible by the proliferation of modern technology. This campaign of ignorance has further undermined trust in governmental health bodies and their attempts to implement quarantine and other measures such as vaccination that had already been damaged by early variations and vacillation in governmental approaches around the globe due in part to a reluctance by some governments to take actions that would have economic repercussions but also by the necessary evolution of their approaches as more became known about the disease and its variants. The paper examines the historical background and the current situation and finds that more must be done to restore or increase trust levels between citizens and governmental authorities, including the dissemination of high quality accurate information in a form relevant to readers/viewers. While potential side-effects of vaccines must be disclosed to ensure informed consent, their incidence should also be clearly communicated (e.g., in vaccine information statements) so that clients/patients are aware that a risk is 1 in 100 or 1in 1000 or 1 in 2 million etc. Governments are urged to learn from their experience and better prepare for inevitable future pandemics to minimise vaccine hesitancy and refusal and maximise its acceptance where evidence is overwhelming as to the benefit to the community. Informed consent is part of the context of efforts to use vaccination to contain or eradicate any disease. Nevertheless, while better information for clients/patients/consumers may reduce vaccine hesitancy/refusal, it is unlikely that it would but eliminate the need for mandating vaccination in some circumstances for the benefit of the broader community, although strict quarantine of those reluctant to accept it is an alternative but one not generally accepted by those reluctant to be vaccinated. The information war is one that needs to be won to increase the voluntary uptake of vaccination in the context of voluntary informed consent. (shrink)

Stove's article, 'So you think you are a Darwinian?'[ 1] was essentially an advertisement for his book, Darwinian Fairytales.[ 2] The central argument of the book is that Darwin's theory, in both Darwin's and recent sociobiological versions, asserts many things about the human and other species that are known to be false, but protects itself from refutation by its logical complexity. A great number of ad hoc devices, he claims, are used to protect the theory. If co operation is observed (...) where the theory predicts competition, then competition is referred to the time of the cavemen, or is reinterpreted as competition between some hidden entities like genes or abstract entities like populations. In a characteristic sally, Stove writes of the sociobiologists' oscillation on the meaning of kin altruism: Any discussion of altruism with an inclusive fitness theorist is, in fact, exactly like dealing with a pair of balloons connected by a tube, one balloon being the belief that kin altruism is an illusion, the other being the belief that kin altruism is caused by shared genes. If a critic puts pressure on the illusion balloon - perhaps by ridiculing the selfish theory of human nature - air is forced into the causal balloon. There is then an increased production of earnest causal explanations of why we love our children, why hymenopteran workers look after their sisters, etc., etc. Then, if the critic puts pressure on the causal balloon - perhaps about the weakness of sibling altruism compared with parental, or the absence of sibling altruism in bacteria - then the illusion balloon is forced to expand. There will now be an increased production of cynical scurrilities about parents manipulating their babies for their own advantage, and vice versa, and in general, about the Hobbesian bad times that are had by all. In this way critical pressure, applied to the theory of inclusive fitness at one point, can always be easily absorbed at another point, and the theory as a whole is never endangered.[ 3] Now, it is uncontroversial to assert that Darwinism is a logically complex theory, and that its relation to empirical evidence is distant and multi faceted. One does not directly observe chance genetic variations leading to the development of new species, or even continuous variations in the fossil record, but must rely on subtle arguments to the best explanation, scaling up from varieties to species, and so on.. (shrink)

The Upanishads reveal that in the beginning, nothing existed: “This was but non-existence in the beginning. That became existence. That became ready to be manifest”. (Chandogya Upanishad 3.15.1) The creation began from this state of non-existence or nonduality, a state comparable to (0). One can add any number of zeros to (0), but there will be nothing except a big (0) because (0) is a neutral number. If we take (0) as Nirguna Brahman (God without any form and attributes), then (...) from where and how did the universe come into existence? -/- The neutral power (0) cannot produce anything without having an element of duality in it. Although Nirguna Brahman is neutral, it has a positive, negative, and neutral pole, constituting its Prakriti or nature. Prakriti has three latent Gunas (modes or qualities): Satva, Rajas, and Tamas. They are related to Gyana Shakti (the power of knowledge) Sankalpa Shakti (the power of ideation), and Kriya Shakti (the power of action). Science says that Atom is the basic element from which the universe evolved. The Atom has three nuclei- electron, pluton, and neutron. The Satva, Rajas, and Tamas in Indian spirituality are nothing but the mystical names for the nuclei of an atom. -/- According to Bhagavata Purana, Prakriti is also constituted of the elements of Time, Karma (action/destiny) and Swabhava (innate nature). Time disturbs the equilibrium of Gunas. From the aspect of Karma is produced an entity called Mahat, in the form of intelligence. Mahat is dominated by Satva and Rajas. From Mahat manifests the next evolute dominated by Tamas with three predominant qualities – Dravya (substance), Kriya (action), as well as intelligence. It forms to become the Ego principle (Ahamkara). -/- Ahamkara has three modes – Satvic, Rajasic and Tamasic. Satvic is Jnana oriented, Rajasic action-oriented and Tamasic Dravya (substance) oriented. From the Tamasic Ahankara, five gross elements are produced (ether, air, fire, water, and earth - Akash, Vayu, Agni, Jal and Prithvi). From the Satvic Ahamkara, guardian deities (the sun and moon, deities of sense organs, and organs of action) and from Rajasic Ahamkara, ten senses (Indriyas), five senses of perception, five organs of action, the faculties of intellect and Prana (life breath) are produced. -/- Bhagavata says that since these energies, elements, and faculties remained disassociated, they were combined to form a Cosmic Egg. The egg floats in the primal waters for a thousand years. Then God enters this Cosmic Egg and manifests himself as the Cosmic Purusha. He is the first nucleus, the God particle equivalent to the number (1) which is the embodiment of everything in the universe. The concept of creation and dissolution in Hinduism can be compared to the waves in an ocean that appear and disappear incessantly. The Manvantaras are such successive episodes of creation emerging from the Cosmic Person, the Manu who is embodied God-Consciousness, God himself. These episodes of creation are measured in Hinduism in terms of Manvantaras, the epochs of Manus. -/- Manu is the ‘First-Born’ (1) of God, the Cosmic Purusha from whom the world has originated. This Cosmic Person (Purusha) has been described as having fourteen biospheres (heavens) that are inhabited by various life forms in the order of evolution of consciousness. If we begin from the human biosphere (Bhuloka), there are ten astral biospheres that a man must transcend to attain liberation or Mukti from the cycle of births and deaths. -/- The number (1) produces the primary numbers up to (9) through the transmutation of the creational energies and qualities. The process can be related to the descent and cyclical evolution of (1) through ten spiritual stages, finally merging with the nondual (0). The number (10) marks the merger of (1) with (0). The Hindu worldview is that all life forms in an episode of creation must evolve to become one with the non-dual state (0) to attain liberation from the cycle of births and deaths in a cyclical process. -/- . (shrink)

Advancements in computing, instrumentation, robotics, digital imaging, and simulation modeling have changed science into a technology-driven institution. Government, industry, and society increasingly exert their influence over science, raising questions of values and objectivity. These and other profound changes have led many to speculate that we are in the midst of an epochal break in scientific history. -/- This edited volume presents an in-depth examination of these issues from philosophical, historical, social, and cultural perspectives. It offers arguments both for and against (...) the epochal break thesis in light of historical antecedents. Contributors discuss topics such as: science as a continuing epistemological enterprise; the decline of the individual scientist and the rise of communities; the intertwining of scientific and technological needs; links to prior practices and ways of thinking; the alleged divide between mode-1 and mode-2 research methods; the commodification of university science; and the shift from the scientific to a technological enterprise. Additionally, they examine the epochal break thesis using specific examples, including the transition from laboratory to real world experiments; the increased reliance on computer imaging; how analog and digital technologies condition behaviors that shape the object and beholder; the cultural significance of humanoid robots; the erosion of scientific quality in experimentation; and the effect of computers on prediction at the expense of explanation. -/- Whether these events represent a historic break in scientific theory, practice, and methodology is disputed. What they do offer is an important occasion for philosophical analysis of the epistemic, institutional and moral questions affecting current and future scientific pursuits. (shrink)

Recent work has assumed that the normativity associated with assertion differs from the normativity of morality, practical rationality, etiquette, and legality. That is, whether an assertion “should” be made is not merely a function of these other familiar sorts of normativity and is especially connected to truth. Some researchers have challenged this assumption of distinctive normativity. In this paper I report two experiments that test the assumption. Participants read a brief story, judged whether an assertion should be made, and rated (...) several other qualities of the assertion, including its truth value, morality, rationality, etiquette, legality, and folly. Of these qualities, truth value most strongly predicted assertability. The findings support the assumption of distinctive normativity and provide further evidence that the norm of our social practice of assertion is factive. (shrink)

In this paper I set out to solve the problem of how the world as we experience it, full of colours and other sensory qualities, and our inner experiences, can be reconciled with physics. I discuss and reject the views of J. J. C. Smart and Rom Harré. I argue that physics is concerned only to describe a selected aspect of all that there is – the causal aspect which determines how events evolve. Colours and other sensory qualities, lacking causal (...) efficacy, are ignored by physics and cannot be predicted by physical theory. Even though physics is silent about sensory qualities, they nevertheless exist objectively in the world – in one sense of “objective” at least. (shrink)