The main purpose of this paper is to explore Pierre Bourdieu’s conception of social science. To this end, the paper sheds light on the main epistemological presuppositions that undergird Bourdieu’s defence of reflexive sociology as a scientific endeavour. The predominant view in the literature is that, in most of his writings,Bourdieu has a tendency to embrace a positivist conception of social science. When examining Bourdieu’s conception of social science in more detail, however, it becomes clear that the assumption that he (...) remains trapped in a positivist paradigm does not do justice to the complexity of his multifaceted account of social science. In order to illustrate the complexity of Bourdieu’s conception of social science, the following analysis scrutinises ten epistemological tensions which can be found in Bourdieu’s writings on the nature of knowledge production. In view of these epistemological tensions, a more fine-grained picture emerges which demonstrates that Bourdieu invites,and indeed compels, us to reflect upon the complexity of the various tension-laden tasks posed by the pursuit of a critical social science. (shrink)

In this paper we argue that dissociative identity disorder (DID) is best interpreted as a causal model of a (possible) post-traumatic psychological process, as a mechanical model of an abnormal psychological condition. From this perspective we examine and criticize the evidential status of DID, and we demonstrate that there is really no good reason to believe that anyone has ever suffered from DID so understood. This is so because the proponents of DID violate basic methodological principles of good causal modeling. (...) When every ounce of your concentration is fixed upon blasting a winged pig out of the sky, you do not question its species' ontological status. James Morrow, City of Truth (1990). (shrink)

With regards to the inefficiencies and uncompromising situations within the humanities and social sciences field in Iran, the challenge of problematizing these sciences is inevitable. So far, numerous research analyzing humanities and social sciences’ problems in the Iranian academic system have been published. Considering the important role of humanities and social sciences in the modern Iranian society, we attempt to suggest a theoretical framework for the problematization of humanities and social sciences in Iran. The exploration of the main challenges facing (...) humanities and social sciences in Iran from the community, academy and administration point of view, sparks three hypotheses. First, humanities and social sciences’ theories and teachings are not applied accurately. Second, the humanities and social sciences’ schools of thought are not chosen properly according to Iranian circumstances. And third, there are metaphysical differences between axioms and presupposition of humanities and social sciences having western origins and those with Islamic-Iranian culture. (shrink)

A evolução da seleção genética de aves e suínos proporcionou aumento no crescimento muscular e no desempenho produtivo, bem como na produção intensiva. Os premixes proporcionam ingredientes, como vitaminas e minerais que são essenciais para o crescimento muscular, redução do estresse, eficiência de diversos metabolismos e o bem-estar animal, contribuindo para uma produção mais sustentável. Deste modo, os premixes desempenham um papel fundamental na otimização do desempenho produtivo e reprodutivo de aves, equinos e suínos. Para formular uma dieta balanceada é (...) necessária a inclusão de vitaminas e minerais, os quais são inseridos em baixas concentrações, em função disto é necessário incluí-los por meio de premix para garantir uma boa homogeneidade dos microingredientes na ração. Os premixes podem ser classificados como: ➢ Vitamínicos, ➢ Minerais e ➢ Minerais-vitamínicos ➢ e conter aminoácidos, antibióticos ou enzimas. (shrink)

Along with inefficiencies of mainstream sciences to find solutions for world problems, and besides the unpleasant difficulties in human lives due to such matters as poverty and economic gap, environmental pollution and climate change, the question raised is whether alternative sciences are contingent, which could preserve mainstream sciences’ potencies and avoid inefficiencies. Along this, religious incentives also seek ways to compromise sciences with divine learnings. To answer this question and benefit from alternative sciences, the contingency of heterodox sciences has to (...) be discussed. The article Starts by an introduction to efforts made towards Islamization of science, then contingency of heterodox sciences is analyzed from the metaphysics of science point of view. The pioneer inquiry in this regard is a less-known essay of Immanuel Kant titled Metaphysical Foundations of Natural Science. This article touches topics such as the relation of metaphysics to science, the contingency of metaphysics of science, the contingency of different metaphysics, and metaphysical foundations of social sciences. And later explains the contingency conditions of heterodox sciences and some advantages of metaphysical approach to these sciences. (shrink)

In order to analyze e-commerce from the perspective of theories of the philosophy of technology, first the characteristics of e-commerce are examined and then analyzed from the viewpoint of the philosophy of technology. In the first section of the article, topics such as definitions and models of e-commerce, electronic contracts, electronic payments, and electronic customs are investigated. In the second section, topics including the technology of e-commerce, requirements of e-commerce, ethics and e-commerce, identity and e-commerce, virtual reality of e-commerce, and (...) the power of aggregation in e-commerce are analyzed. (shrink)

Abstract: Smoke detectors are critical devices for early fire detection and life-saving interventions. This research paper explores the application of Artificial Neural Networks (ANNs) in smoke detection systems. The study aims to develop a robust and accurate smoke detection model using ANNs. Surprisingly, the results indicate a 100% accuracy rate, suggesting promising potential for ANNs in enhancing smoke detection technology. However, this paper acknowledges the need for a comprehensive evaluation beyond accuracy. It discusses potential challenges, such as overfitting, dataset size, (...) and class imbalance, and presents strategies employed to address these issues. Additionally, the paper emphasizes the importance of alternative evaluation metrics, including precision, recall, and F1-score, to assess the model's performance comprehensively. Detailed information regarding the model architecture, data preprocessing, and hyperparameter tuning is provided to enhance the reproducibility of the research. The study also discusses ethical considerations and the implications of false positives and false negatives in smoke detection applications. While achieving 100% accuracy is a notable accomplishment, this paper calls for cautious interpretation and further validation in real-world settings. It concludes by highlighting areas for future research and improvement in smoke detection technology, emphasizing the need for practical deployment and the reduction of false alarms. (shrink)

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying the (...) presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies. (shrink)

Committing to contribute to promoting the 11th progressive cultural element – environmental-healing value – and building the eco-surplus culture for sustainable development, the AISDL Team (represented by Drs. Minh-Hoang Nguyen and Quan-Hoang Vuong) has collaborated with Discover Sustainability to launch “Environmental Sustainability Needs Humanities” Topical Collection. In contributing to the generation of knowledge that aids the social transitions toward an eco-surplus utopia, the Topical Collection welcomes various types of articles across disciplines, including Research, Reviews, Perspectives, Comments, Brief Communications, Case Studies, (...) Registered Reports, and Data Notes that are related but not limited to these issues: - Socio-cultural and economic issues that help mitigate and adapt to climate change and prevent biodiversity loss - Socio-cultural and economic issues that support the development and implementation of nature-based solutions and artificial technologies for achieving environmental sustainability - Factors that help restore the connection between nature and humans, such as science, art, literature, and lived experiences - The psychology towards climate change, biodiversity loss, social transition, and technological transformation - The roles of creativity, serendipity, and knowledge management in sustainability transformation - Sustainable financing mechanism for climate change mitigation and adaptation as well as biodiversity conservation - The roles of urban and rural humans in addressing climate change and biodiversity loss - Global agreement, national commitments, and local actions for addressing climate change and biodiversity loss. (shrink)

The current study is conducted to examine the following research questions: -/- - What are the consequences of blockage, vandalism, and harassment activities for the cause of climate change mitigation? - What kind of environmental activism leads to the escalation of violence? - Which pathways (e.g., survival threats) do the activism lead to violence escalation? -/- The findings from this study are expected to provide insights into the effectiveness and appropriateness of strategies to raise public awareness and support and contribute (...) to the societal transitions to address climate change. (shrink)

Abstract: The Spotify Status Dataset is a valuable resource that provides real-time insights into the operational status and performance of Spotify, a popular music streaming platform. This dataset contains a wide array of information related to server uptime, user activity, service disruptions, and more, serving as a critical tool for both Spotify's internal monitoring and the broader data analysis community. As digital services like Spotify continue to play a central role in music consumption, understanding the platform's status becomes crucial for (...) ensuring a seamless user experience. This dataset offers numerous research and analysis opportunities, whether you're interested in exploring service availability trends or investigating user behavior patterns during service disruptions. This study highlights the significance of the Spotify Status Dataset, its potential applications, and the valuable insights it can offer to various stakeholders, from Spotify engineers working to enhance service reliability to researchers studying the effects of downtime on user engagement. It invites readers on a journey through this dataset to uncover the secrets of Spotify's operational status and its impact on music enthusiasts worldwide. (shrink)

“Only those who have lived among the birds could truly appreciate the magic of their singing. At daybreak, the bushes and the alley corners would all be drenched in a vibrant chorus of birdsongs. The whole scene is exhilarating, exuding the mysterious vibes of a major orchestra.” -/- —In “Conductor”; The Kingfisher Story Collection [1].

Abstract Alzheimer's disease has spread insanely throughout the world. Early detection and intervention are essential to improve the chances of a positive outcome. This study presents a new method to predict a person's likelihood of developing Alzheimer's using a neural network model. The dataset includes 373 samples with 10 features, such as Group,M/F,Age,EDUC, SES,MMSE,CDR ,eTIV,nWBV,Oldpeak,ASF.. A four-layer neural network model (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 98.10% and an average error (...) of 0.01. This study provides a valuable tool for early detection and intervention of Alzheimer's, thus contributing to the field of health and medicine. (shrink)

“[…] To alleviate the boredom, after catching a fish, Kingfisher would press all three buttons before swallowing the fish. Pressing the buttons has gradually become somewhat of a new technological ritual.” -/- —In “Innovation”; The Kingfisher Story Collection [1].

Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader reviews (...) influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

Family members can provide crucial support to individuals participating in clinical trials. In research on the “newest frontier” of Deep Brain Stimulation (DBS)—the use of DBS for psychiatric conditions—family member support is frequently listed as a criterion for trial enrollment. Despite the significance of family members, qualitative ethics research on DBS for psychiatric conditions has focused almost exclusively on the perspectives and experiences of DBS recipients. This qualitative study is one of the first to include both DBS recipients and their (...) family members as interview participants. Using dyadic thematic analysis—an approach that takes both the individuals and the relationship as units of analyses—this study analyzes the complex ways in which family relationships can affect DBS trial participation, and how DBS trial participation in turn influences family relationships. Based on these findings, we propose ways to improve study designs to better take family relationships into account, and better support family members in taking on the complex, essential roles that they play in DBS trials for psychiatric conditions. (shrink)

The study aims to identify the efficiency of the university education performance from the perspective of postgraduate and undergraduate students in international and Palestinian universities. The analytical descriptive approach was used for this purpose and the questionnaire was used as a main tool for data collection. The study community consists of: post graduate students, (23850) graduate students and (146355) undergraduate students. The sample of the study was 378 graduate students and 383 undergraduate students. The random stratified sample was used. The (...) Statistical Package of Social Sciences (SPSS) was also used for data analysis. The study reached a number of results, the most important of which are: The level of efficiency of educational performance in Palestinian and international universities from the point of view of postgraduate and undergraduate students was high. And that there are significant differences between the average views of the sample of the study on the efficiency of educational performance in Palestinian and international universities attributed to the University and to the benefit of international universities. The study concluded many recommendations, the most important of which is the necessity of continuing to develop e-learning strategies that affect the efficiency of educational performance and research commensurate with the university's position in the local and international community, which puts it on the best classification between local and international universities through e-learning. (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)

Brain tumors pose significant challenges in modern healthcare, with accurate and timely diagnosis crucial for determining appropriate treatment strategies. Artificial intelligence has made significant advancements in recent years. Rule-based expert systems (if-then rule-based systems) have emerged as a promising approach for clinical decision-making in brain tumor diagnosis. In this paper, we present "A CLIPS-Based Expert System for Brain Tumor Diagnosis," which leverages a set of 14 if-then rules to diagnose brain tumors with three possible outcomes: 1) Confirm the diagnosis of (...) a brain tumor, 2) Consider the possibility of a brain tumor that has metastasized, and 3) Consider the possibility of a brain tumor. Our expert system offers a user-friendly interface, enabling users to select symptoms and receive a diagnosis based on the provided information. This paper discusses the expert system's development, implementation, and evaluation, highlighting its potential to facilitate brain tumor diagnosis and decision-making in clinical settings. Additionally, we provide a literature review that contextualizes our expert system within the broader landscape of rule-based expert systems for brain tumor diagnosis, examining their effectiveness, limitations, and challenges. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

Mouth ulcers, also known as canker sores, are a common oral health issue affecting a significant portion of the population. Early and accurate diagnosis of mouth ulcers is crucial for effective treatment and prevention of complications. This paper presents an expert system developed using CLIPS (C Language Integrated Production System) to diagnose mouth ulcer disease. The expert system utilizes a rule-based approach, incorporating a comprehensive knowledge base consisting of symptoms, risk factors, and medical literature related to mouth ulcers. By employing (...) an inference engine, the system evaluates patient input against the rules and generates a diagnosis based on the matching symptoms and relevant factors. The system also provides detailed explanations and recommendations for each diagnosis, aiding healthcare professionals and patients in understanding the condition and selecting appropriate treatment options. The development and validation of the expert system involved a multi-step process, including knowledge acquisition, rule formulation, and testing against a diverse dataset of mouth ulcer cases. The system's performance was evaluated by comparing its diagnoses with those made by medical professionals, demonstrating a high level of accuracy and consistency. The implementation of an expert system for diagnosing mouth ulcer disease offers several advantages, including the ability to provide timely and accessible healthcare services, reduce misdiagnosis rates, and assist healthcare professionals in decision-making processes. Moreover, it empowers individuals to make informed decisions about their health and seek appropriate medical intervention. This paper contributes to the field of medical expert systems by showcasing the practical application of CLIPS in the diagnosis of mouth ulcer disease. The results demonstrate the potential of expert systems as valuable tools for healthcare professionals and patients alike, enhancing the efficiency and accuracy of diagnosis in oral health care. (shrink)

Kidney stones pose a significant health concern, and early detection can lead to timely intervention and improved patient outcomes. This research endeavours to predict the presence of kidney stones based on urine analysis, utilizing a neural network model. A dataset of 552 urine specimens, comprising six essential physical characteristics (specific gravity, pH, osmolarity, conductivity, urea concentration, and calcium concentration), was collected and prepared. Our proposed neural network architecture, featuring three layers (input, hidden, output), was trained and validated, achieving an impressive (...) accuracy of 98.67% and an average error of 0.012. In addition to model performance, feature importance analysis was conducted to determine the most influential factors in predicting kidney stone presence. The findings underscore the significance of urea concentration, specific gravity, calcium concentration, conductivity, osmolarity, and pH as key indicators. This research contributes to the early diagnosis of kidney stones and demonstrates the potential of neural networks in medical diagnostics. The clinical implications of these findings are discussed, emphasizing the importance of timely intervention in managing kidney stone-related health issues. (shrink)

heart attack analysis & prediction dataset is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 304 samples with 11 features, such as age, sex, chest pain type, Trtbps, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, and HeartDisease. (...) A neural network model with four layers (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 88% and an average error of 0078296. The most influential factors in heart failure prediction were found to be oldpeak, ST_Slope, sex, fastingBS, chestPainType, exerciseAngina, cholesterol, restingBP, maxHR, restingBP, and age. This study provides a valuable tool for early detection and intervention of heart failure, thereby contributing to the field of health and medicine. (shrink)

The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in (...) other areas of the natural sciences have been successfully overcome by developing and using common ontologies. This White Paper presents the authors’ rationale for the use of ontologies with computable semantics for the improvement of clinical data quality and EHR usability formulated for researchers with a stake in clinical and translational science and who are advocates for the use of information technology in medicine but at the same time are concerned by current major shortfalls. This White Paper outlines pitfalls, opportunities, and solutions and recommends increased investment in research and development of ontologies with computable semantics for a new generation of EHRs. (shrink)

Abstract: The emergence of the novel coronavirus (COVID-19) in 2019 has presented the world with an unprecedented global health crisis. The rapid and widespread transmission of the virus has strained healthcare systems, disrupted economies, and challenged societies. In response to this monumental challenge, the intersection of technology and healthcare has become a focal point for innovation. This research endeavors to leverage the capabilities of Artificial Neural Networks (ANNs) to develop an advanced predictive model for forecasting the spread of COVID-19. It (...) involves the collection, analysis, and integration of diverse datasets encompassing epidemiological, clinical, and social factors that influence the virus's dissemination. (shrink)

The aim of this study was to identify the obstacles facing the application of knowledge management and its impact on performance at Palestine Technical University-Kadoorei from the point of view of employees and to detect the differences between the average views of the study sample on the subject of the study according to some variables such as (gender, nature of work, Education Level, specialization, years of experience). The study followed the descriptive analytical method and the questionnaire as a tool for (...) study. It was distributed to 74 employees. After the questionnaire was distributed, the data was collected and coded and entered into the computer and processed statistically using the SPSS program. The study found that the percentage of approval of the obstacles to the application of knowledge management at Palestine Technical University-Kadoorei differed between few and large, and the relative weight of the axis was complete (68.2). The degree of awareness of the workers of the reality of performance excellence at the University of Palestine Technical-Kadoorei was between medium and very large. There is an impact of the constraints of the application of knowledge management on performance excellence at Palestine Technical University-Kadoorei. In light of the results of the previous study, the researchers recommended that the importance of knowledge management should be taken into account in order to raise the university's reputation and reputation at home and abroad and improve its services to students and the local community. And to promote the exchange of experiences and knowledge with local, regional and international universities in order to enhance the knowledge and preserve it and provide modern and sophisticated scientific techniques and use them in administrative and academic work at the university. (shrink)

The article entitled “Cultural evolution in Vietnam’s early 20th century: A Bayesian networks analysis of Hanoi Franco-Chinese house designs” investigates how diverse cultures and religious creeds influenced the architecture of Hanoi in the early 20th century.

Aristotle’s dialogue Protrepticus is not only his earliest work of ethics but also the root of all his subsequent investigations into ethics. Here we explore the various ways Aristotle retained in memory the contents of the Protrepticus and redeployed them in the Eudemian Ethics, including the common books. Since Aristotle himself does not explicitly acknowledge the foundational significance of the Protrepticus to his later works, our exploration must proceed on the basis of our knowledge of the earlier work, which can (...) then related to comparable passages in the treatises. But the Protrepticus is a lost work, unlike the EE and the EN, in the sense that no medieval manuscripts of it have survived. And so it first needs to be reconstructed on the basis of the streams of reception that deposited information in surviving works by later ancient authors. We begin in part 1 by reviewing the surviving evidence of the Protrepticus before presenting our wider reconstruction and conception of the work as a dialogue in part 2. In part 3, we discuss ideas and arguments in the reconstructed dialogue that are retained and redeployed in the Eudemian Ethics, focussing on the account of intellectual virtues in EE v and the introduction and methodological framework in EE i-ii.1. (shrink)

Socioeconomic status refers to the family's social and economic standing in society. It is measured by combining an individual or group's economic and social position, which is often based on income, education, and occupation. It significantly affects academic performance and even one's health status. The pandemic changed the educational system, causing a huge transition from traditional learning methods to online learning. This shift resulted in confusion, burden, and difficulty among students from different walks of life. This study was conducted to (...) determine the academic stress on online learning among nursing students in relation to their economic status and their ability to access technology. The study utilized a quantitative-correlational method aided by a standard questionnaire. Two hundred thirty-six University of Bohol nursing students enrolled in the second semester of SY 2021–2022 were included in the study by random selection. Data revealed a significant correlation between economic status and the level of stress related to academic expectations and a significant correlation between economic status and access to technology after being subjected to the Spearman rho test of correlation. However, no significant correlation was found between access to technology and the respondents' level of academic stress. (shrink)

Many academics and researchers who publish scholarly articles on Plato’s philosophy of education claim that the ultimate educational goal for Plato is simply the acquisition of virtues. While such a claim may not be entirely incorrect, it is nevertheless substantially wanting; for although the acquisition of virtue is no doubt paramount, for Plato it primarily serves as a means to another end. In this paper, I aim to show that, for Plato, the final summit of all educational enterprise is not (...) really to become virtuous but rather to attain the state of becoming like God, and that is, homoiōsis theōi. -/- . (shrink)

This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to enhance (...) model generalizability. (shrink)

Human nature, values, and human existence and development are all intertwined in the notion of Maqāṣid al-Sharīʽah, which supports the well-being of humans, including those with mental health concerns. The high degree of mental health difficulties among students, such as severe stress and depressive symptoms, not only impact their academic performance but also lead to self-injurious behaviour and suicidal attempts. With the COVID-19 pandemic affecting Malaysian university students’ mental health, this article aims to explore the situation from a Maqāṣid al-Sharīʽah (...) perspective and positive psychology. The study employed a mixed-method approach. Firstly, a quantitative descriptive analysis was done to assess students’ overall mental health symptoms to provide a rudimentary assessment of their core psychological problems. Questionnaires were accompanied by an open-ended question to triangulate respondents’ experiences and were analysed qualitatively through a thematic analysis. A DASS-21 survey was given to 87 undergraduate IIUM students (n = 81) aged 19 to 27 years. Based on the maqāṣid framework, the study could be utilised to prioritise strategies to treat mental health concerns at various levels that will ensure the preservation of human life. The ultimate purpose of this research is to provide future implications for a multidimensional framework of psychological well-being based on Maqāṣid al-Sharīʽah principles. This is consistent with the Sustainable Development Goals (SDG) that calls for action to protect humanity and to ensure that all individuals are living in peace and prosperity. (shrink)

Life expectancy prediction, a pivotal facet of public health and policy formulation, has witnessed remarkable advancements owing to the integration of neural network models and comprehensive datasets. In this research, we present an innovative approach to forecasting life expectancy in diverse countries. Leveraging a neural network architecture, our model was trained on a dataset comprising 22 distinct features, acquired from Kaggle, and encompassing key health indicators, socioeconomic metrics, and cultural attributes. The model demonstrated exceptional predictive accuracy, attaining an impressive 99.27% (...) and an average error of 0.0034, underscoring the potency of deep learning in tackling complex, real-world challenges. Furthermore, our study delved into feature importance analysis, identifying critical determinants such as HIV/AIDS prevalence, income composition of resources, and socioeconomic status that significantly influence life expectancy. These findings provide actionable insights for healthcare policymakers and practitioners, emphasizing the importance of addressing health disparities, promoting economic development, and implementing targeted interventions. This research bridges the gap between data-driven methodologies and global health, offering a robust predictive tool and enriching our understanding of the multifaceted dynamics that shape life expectancy across nations. (shrink)

Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

Recent empirical work on the concept of intentionality suggests that people’s assessments of whether an action is intentional are subject to uncertainty. Some researchers have gone so far as to claim that different people employ different concepts of intentional action. These possibilities have motivated a good deal of work in the relatively new field of experimental philosophy. The findings from this empirical research may prove to be relevant to medical ethics. In this article, we address this issue head on. We (...) first describe a study we conducted on intention ascription. Drawing on recent work in experimental philosophy, we investigated the possibility that the ascription of intentions to clinical actors in clinical settings is influenced by prior judgments about the goodness or badness of the consequences of the action in question. Our study was modeled on experimental studies in other contexts that have shown that people, when presented with a range of scenarios, are more likely to classify a side effect of an action as intended if the side effect is negative or reflects poorly on the actor than if it is positive or reflects well on the actor. We investigated whether this asymmetry in intention ascriptions was also present among physicians who were asked to ascribe intentions to clinical actors in certain well-defined clinical scenarios. After describing the study and its results, we discuss its implications for medical ethics. (shrink)

Robert Nozick, in chapter two of the nature of rationality, proposes two famous problems in decision theory (i.e., Newcomb's problem and Prisoner Dilemma) and two main strategies toward these problems i.e. dominant strategy and dominated or cooperative one. He will try to give a formal principles to calculate the decision values in these situations. In this calculation he goes beyond the standard principle of maximizing expected utility and would try to put forth less ideal and more realistic principles that fit (...) the decision situation in the real world. (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)

One method for preventing the spread of the coronavirus and other contagious diseases is through social distancing. Therefore, creating a tool to measure and quickly discover the precise distance is necessary. In order to prevent physical contact between individuals, this study aimed to detects individuals’ physical distance, through an inaugurated battery-powered device that monitors physical distance through wireless technology. Specifically, in public or crowded areas, to lessen the spread of the virus. This study focuses on detecting people’s physical distance in (...) the region of interest utilizing an Ultrasonic and VL53L0X sensors and determining the significant difference between the two sensors in monitoring physical distance. This study employs an applied experimental research design. The efficiency of both sensors in measuring physical distance was evaluated through analysis. The Ultrasonic and VL53L0X sensors underwent 15 tests. Furthermore, the researchers effectuated a t-test to determine the significant difference between the two sensors. Data gathered revealed that the sensors’ combined mean in terms of measuring physical distance indicates that the ultrasonic sensor performed better than VL53L0X, measuring 134.7 cm, notwithstanding 99.8 cm for the VL53L0X sensor. Complementary to this, the results of the t-test show that the VL53L0X sensor and Ultrasonic sensor have a significant difference in terms of distance precision. (shrink)

This paper argues for global sharing of COVID‐19 treatments during the COVID‐19 pandemic and beyond based on principles of global solidarity. It starts by distinguishing two types of COVID‐19 treatments and models sharing strategies for each in small‐group scenarios, contrasting groups that are solidaristic with those composed of self‐interest maximizers to show the appeal of solidaristic reasoning. It then extends the analysis, arguing that a similar logic should apply within and between nations. To further elaborate global solidarity, the paper distinguishes (...) morally voluntary, sliding‐scale, and mandatory versions. It argues for an all‐hands‐on‐deck approach and gives examples to illustrate. The paper concludes that during the COVID‐19 crisis, global solidarity is a core value, and global sharing of COVID‐19 treatments should be considered a duty of justice, not of charity. (shrink)

Numerous agricultural wastes are impractically discarded every day, and one of these is rice bran. This study investigated the production of a biodegradable straw made of cassava starch and powdered rice bran. It aimed to determine the effectiveness of the different treatments of Cassava Starch-Rice Bran in terms of water resistance, tensile strength, and biodegradability. An experimental design was used in conducting the study. There were three treatments made in making CSRB straws: the first, with more rice bran; the second, (...) with the same cassava starch and rice bran ratio; and the third, with more cassava starch. These treatments produced three replicates each. The straws were placed in a dehydrating machine for 24 hours at a temperature of 60° Celsius. The straws were then coated with beeswax after being removed from their respective molders. The CSRB straws were found to be water resistant due to the beeswax coating applied, although it had a weak tensile strength even with the presence of beeswax. The rate of biodegradability of the CSRB straw was fast due to it being made up of organic materials. The results revealed that straws made from Cassava Starch and Powdered Rice Bran are effective in terms of water resistance and biodegradability. (shrink)

As a contribution to a wider discussion on moral discernment in theological anthropology, this paper seeks to answer the question “What is the impact of mental illness on an individual’s ability to make moral decisions?” Written from a clinical psychiatric perspective, it considers recent contributions from psychology, neuropsychology and imaging technology. It notes that the popular conception that mental illness necessarily robs an individual of moral responsibility is largely unfounded. Most people who suffer from mental health problems do not lose (...) the capacity to make moral decisions, and mental illness on its own rarely explains anti-social or criminal behaviour. Moreover, the assumptions of some scientists, that recent developments in neuropsychology and brain imaging suggest biological determinism, must be treated with caution. (shrink)

This study employs a neural network to analyze the connection between smoking, drinking, and various health-related factors using a dataset of 5148 samples. Achieving an impressive 99.94% accuracy and an average training error of 0.0016, the model identifies influential factors such as serum aminotransferases, serum creatinine, sex, weight, and triglyceride levels. These findings enhance our understanding of lifestyle choices and their impact on health. This research underscores the potential of machine learning in studying complex health phenomena.

This study investigated the effectiveness of utilizing induced magnetism on the seed germination of radish (Raphanussativus) in terms of growth rate, growth speed, shoot growth, and overall development. This study utilized two groups that consisted of an experimental group where induced magnetism was present one control group where there was an absence of induced magnetism in the seed germination of Radish (Raphanus sativus). Moreover, this study aimed to determine the significant difference between the two in terms growth rate, growth speed, (...) shoot growth, and overall development. Both groups had the same amount of radish (Raphanus sativus) seeds planted in a rectangular wooden container with the same amount of measurement and soil content. This study used an experimental research design by utilizing the functions of an Electromagnetic Induction Device (EID) comprised of a 12v motor battery, light bulb, coiled wire, and switch. The EID was turned on for 10 minutes every day where the electric volts generated by the 12v motor battery were transported through the coiled wire and distributed to the metallic iron screen surrounding the area of the experimental group. The data gathered during the 12-day observation of the growth of radish (Raphanus sativus) were tabulated, analyzed, and evaluated using mean tests, standard deviation, and T-test. Based on the result and analyses of the gathered data, it was found that the experimental group, the one with the presence of induced magnetism, surpassed the control group in terms of growth speed, shoot growth, and overall seed development. However, it was also revealed that in terms of growth rate, there is no significant difference between the control group and experimental group. Therefore, the utilization of Induced Magnetism on the seed germination of radish (Raphanus sativus) is effective in terms of growth speed, shoot growth, and overall development. (shrink)

Climate change temperature prediction plays a crucial role in effective environmental planning. This study introduces an innovative approach that harnesses the power of Artificial Neural Networks (ANNs) within the Just Neural Network (JustNN) framework to enhance temperature forecasting in the context of climate change. By leveraging historical climate data, our model achieves exceptional accuracy, redefining the landscape of temperature prediction without intricate preprocessing. This model sets a new standard for precise temperature forecasting in the context of climate change. Moreover, our (...) research provides valuable insights into the pivotal factors influencing temperature variations, making significant contributions to environmental science and climate mitigation strategies. (shrink)

An interview with Ed Casey where we discuss the intersections of his philosophical work with current political issues, including the Israel-Palestine conflict.

The global water crisis is being exacerbated by climate change, even in the United States. Recycled water is a feasible alternative to alleviate the water shortage, but it is constrained by humans’ perceptions. The current study examines how residents’ water scarcity awareness and climate change belief influence their willingness to use recycled water directly and indirectly. Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of 1831 residents in Albuquerque, New Mexico, an arid inland region in the US. We (...) discovered that residents’ willingness to use direct recycled potable water is positively affected by their awareness of water scarcity, but only if they believe in the impacts of climate change on the water cycle. Meanwhile, the willingness to use indirect recycled potable water is influenced by water scarcity awareness, and the belief in climate change further enhances this effect. These findings implicate that fighting climate change denialism and informing the public of the water scarcity situation in the region can contribute to the effectiveness and sustainability of long-term water conservation and climate change alleviation efforts. (shrink)

In the summer of 2016, the University of Dallas and the Instituto Tecnológico Autónomo de México organized a conference to discuss the topic of the middle class and its continued decline—recognizing that, despite some historical, political and cultural differences, healthy democracies throughout the hemisphere depend upon a strong and prosperous middle class. This volume brings together contributions by nine scholars from both institutions. The chapters reflect diverse disciplinary perspectives that are historical, political, economic, anthropological, and philosophical. Despite this diversity, the (...) volume possesses a conceptual unity that stems from its foundation in Aristotle’s approach to the middle class. On this basis, the topic is given a rigorous study that is both theoretical and data-driven. The chapters include treatments of Aristotle, Montesquieu, Adam Smith and Sir James Steuart, Catholic social teaching, the problem of inequality in the US, the definition and measurement of the middle class in Mexico, as well as its values and political attitudes, the rise of middle-class politics in early-twentieth-century Latin America, and a comparative analysis of healthcare for the middle class in North America. (shrink)

This study was conducted to determine the effectiveness of utilizing the Dual-axis Solar Tracker in harnessing solar energy and storing it in lithium-ion batteries in terms of voltage and milliamps per hour gained. This study utilized two solar panel systems, the Static Solar Panel System and the Dual-Axis Solar Tracker and aimed to prove the significant difference generated by solar panel systems in terms of voltage and milliamps per hour. This study employed an Applied Experimental Research Design utilizing Arduino Uno, (...) light-dependent resistors, micro servos, and solar panels to create the Dual-Axis Solar Tracker. The data gathered from the electric quantities during the seven-day sun exposure were tabulated, analyzed, and computed using mean tests, standard deviation, and T-tests to find the significant difference between the two solar panels. Based on the analyses of the data, it was revealed that the Dual-Axis Solar Tracker was superior in terms of voltage and milliamps per hour generated compared to the Static Solar Panel System. Moreover, computations using the T-test found that in terms of voltage and milliamps per hour generated, there was a significant difference between the Dual-Axis Solar Tracker and the Static Solar Panel System. Based on the findings of the study, it is concluded that the utilization of the Dual-Axis Solar Tracker statistically increases the effectiveness of solar panels in harnessing energy generation. (shrink)

Introduction Reza Davari Ardakni, the Iranian contemporary philosopher, distinguishes development from Western modernity; in that it considers modernity as natural and organic changes that Europe has gone through, but sees development as a planned design for implementing modernity in other countries. As a result, the closedness of development concerns only the developing countries, not Western modern ones. Davari emphasizes that the Western modernity has a universality that pertains to a unique reason and a unified world. The only way of thinking (...) in this world is a philosophical thought based on human self-centered reason, and given the pervasiveness of Western civilization. Therefore, Davari does not consider Westernization as mere imitation of Western customs and methods, but rather as a way of existence in the world. Westernization is a subjective view of the world and beings. Westernization is not optional, enabling non-Western people to avoid it. According to the Westernization scenario, the world today is entirely Westernized, and Davari considers Westernization as the inevitable fate of the people of this era, seeing two alternatives for them, both of which ultimately lead to the same destination, which is to embrace development; either they seize the power of science and technology and join the process of global modernization and participate in it, or they become subdued by this process and accept it without participation. Davari regards the first type of Westernization as active and the second type as passive. Problematique Therefore, underdevelopment is not a concept of the ancient world, nor even of a world between the ancient and the modern, or on the threshold of modernization. Underdevelopment is a condition of suspension and timelessness and being exposed to modernization. To escape the paradox of underdevelopment, which is the inevitable historical fate of non-modernized societies, Davari sees no way out other than embracing development. In other words, Westernized societies, which have become confused due to modernization, have no escape route other than turning to development. Therefore, some critics of Davari accuse the theory of Westernization of being a theoretical rupture. M. T. Tabatabaei, by rejecting the theoretical rupture in the theory of Westernization, believes that in the argument of Davari, we are only faced with a shift from a philosophical to an intellectual level. Tabatabaei, by avoiding providing a philosophical response to the critics of the theoretical rupture, believes that the introduction of active Westernization and collaboration in science and technology as a solution to escape from underdevelopment conditions, is only a shift from a philosophical level to an intellectual level and does not involve a rupture. Therefore, it seems that the philosophical issue of how or the possibility of escaping from underdevelopment conditions is still an open non answered problem. In this study, seeking a philosophical answer to this problem, an attempt has been made to summarize Davari's definitions of development, underdevelopment, participation in the world of science, and the role of humanities and social sciences in development, using his writings and speeches. It is proposed that a way to escape from the clesedness of development based on Davari's views, is to make use of analytical method with emphasizing on concepts and theories of the philosophy and metaphysics of science. Argument According to Davari, the social and human sciences that are responsible for development planning in underdeveloped societies must consider the characteristics of underdevelopment in order to facilitate the transition to more favorable conditions. Davari identifies the following conditions for successful development: 1) replacing tradition with science as the organizing and coordinating principle in society, 2) recognizing the universality of philosophy and science of the Western modernity and the impossibility of blindly imitation and adopting it, 3) inevitability of actively engaging and interacting with development, 4) recognizing the internal dynamics of scientific progress and avoiding authoritarian control, and 5) promoting free participation in the scientific paradigms. Therefore, Davari suggests the following steps towards development: 1) recognizing and understanding the problems of society and the local ecosystem, 2) understanding the philosophical and cultural foundations of Western civilization, 3) understanding the historical context and paradigms of science, 4) understanding the philosophical and metaphysical foundations of science, 5) recognizing the intellectual and philosophical capacities of our own community, and 6) reflecting our own philosophical and metaphysical assumptions in the scientific world in a way that is compatible with scientific methods. Given the motivations for change in science at both the global and national levels, including the emergence of heterodox or indigenous sciences, and the inevitable nature of development, Davari points to the possibility of a path between absolute rejecting or accepting the mainstream social and human sciences. However, this path is challenging and contingent upon the aforementioned conditions and steps of transition. Conclusion It is necessary to seek this path within the realm of the philosophy and metaphysics of science, particularly in the origins and foundations of the social and human sciences. Research in the metaphysics and philosophy of the social sciences provides the opportunity for active scientific engagement in the scientific paradigms and a reconsideration of the foundations of science, allowing for different philosophical foundations while are compatible with scientific methods. Successfully finding a path between absolute rejecting or accepting the existing social sciences will lead to an internal transformation within the field of science and, in fact, will advance the boundaries of knowledge. Therefore, it is possible, while adhering to the conditions of transition and actively participating in the world of science and technology, and accepting the unity of modernity and avoiding selectivity and imitation, to search for a way to overcome the closedness of development through a reconsideration of the philosophical and metaphysical foundations of science, while recognizing our own intellectual heritage and critically assessing Western science and technology. (shrink)