Commentators have long remarked the influence of Lévi-Strauss on Lacan, yet they have largely ignored important philosophical parallels between Lacan and Emile Durkheim, Lévi-Strauss's predecessor in the French anthropological tradition. I suggest that we are better served by understanding Lacan as heir to Durkheim rather than Lévi-Strauss, especially when Lévi-Strauss is seen as the ambassador of a new "scientific" method ("structural anthropology") modeled on structural linguistics. Lacan's reference to linguistics is, I maintain, a red herring that has misled interpreters. Instead, (...) Durkheim's ideas offer a more fruitful interpretive lens to understand the paradigm shift that defines Lacan's mature thought: a renewed understanding of the primacy of collective categories over individual experience and of the importance of the social and "symbolic" status of the human environment as opposed to its grounding in biological or physical reality. (shrink)

One of the chief virtues of Gutting’s book is its ambition to tell the “relatively self-contained and coherent story” (xi) of French philosophy in this century, not just the parts of the story that American academics have seized upon as distinctive and interesting. Alongside analyses of well-known philosophers like Sartre, Merleau-Ponty, Foucault, and Derrida (a 30-40 page chapter is devoted to each), Gutting provides excellent chronological summaries of early figures like Félix Ravaisson, Jules Lachelier, Léon Brunschvicg, Henri Bergson, and Gaston (...) Bachelard who are infrequently read or discussed in English. (shrink)

Kate Kirkpatrick's provocative interdisciplinary study argues that Sartre's conception of nothingness in Being and Nothingness (BN) can be fruitfully understood as an iteration of the Christian doctrine of original sin, "nothingness" being synonymous with sin and evil in the Augustinian tradition. Hence, Sartre in BN presents us with "a phenomenology of sin from a graceless position" (10). For readers used to understanding Sartre through the lens of German phenomenology, this will come as a surprise. However, the book should be welcomed (...) by all readers as it breathes life into the field of Sartre studies, offering a fresh perspective from which to judge the magnum opus of French existentialism. (shrink)

Glucagon-like peptide-1 (GLP-1) receptor agonists, such as semaglutide, and dual GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptor agonists, such as tirzepatide, have been found to be effective for treating obesity and diabetes, significantly reducing weight and the risk or predicted risk of adverse cardiovascular events. There is a global shortage of these medications that could last several years and raises questions about how limited supplies should be allocated. We propose a fair-allocation framework that enables evaluation of the ethics of current (...) practices and could guide governments, professional societies, and physicians in allocation decisions. (shrink)

The truth of every human being is the end his life with death, and this leads to leaving assets and funds for those after him and can lead to hate between the heirs, it has made a point of Islamic law on all aspects of life, including the subject of the inheritance of the deceased. The main problem is how to get the knowledge of the basics of inheritance. This paper reviews work done in the use of expert system software (...) to calculate inheritance in Islam. A proposed expert system was designed and developed using CLIPS language to calculate the inheritance in Islam. (shrink)

Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...) used in this study comprises chicken images of three different diseases: Newcastle disease, avian influenza, and infectious bursal disease. The proposed method achieved an overall F1-score of 99.04% in classifying the chicken diseases. The results demonstrate the effectiveness of using CNN in classifying chicken diseases and provide a promising approach for early detection and diagnosis of poultry diseases. (shrink)

Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...) a vital role in supporting human well-being and the health of our planet. . Fishes have a lots of types such that: Red Mullet, Sea Bass, Striped Red Mullet and Shrimp. Each of them has its own shape and characteristics that differ from other types. We proposed a system that recognize nine types of fishes using deep learning. We trained the model with a dataset that contain 9000 images that were slit into 6300 images for training, 1350 for validation and 1350 for testing. The proposed model achieved accuracy (99.68%), precision (99.69%), recall (99.68%), and f1-score (99.68%). This indicates that our proposed model can effectively predicate and classify different types of fish with very high accuracy. (shrink)

Abstract: Ensuring the proactive detection of transaction risks is paramount for financial institutions, particularly in the context of managing credit scores. In this study, we compare different machine learning algorithms to effectively and efficiently. The algorithms used in this study were: MLogisticRegressionCV, ExtraTreeClassifier,LGBMClassifier,AdaBoostClassifier, GradientBoostingClassifier,Perceptron,RandomForestClassifier,KNeighborsClassifier,BaggingClassifier, DecisionTreeClassifier, CalibratedClassifierCV, LabelPropagation, Deep Learning. The dataset was collected from Kaggle depository. It consists of 164 rows and 8 columns. The best classifier with unbalanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%,Recall100.0% and the F1-score (...) 100.0%. However, the best classifier with balanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%, Recall 100.0% and the F1-score 100.0%. (shrink)

Abstract: Classifying sea animals is an important problem in marine biology and ecology as it enables the accurate identification and monitoring of species populations, which is crucial for understanding and protecting marine ecosystems. This paper addresses the problem of classifying 19 different sea animals using convolutional neural networks (CNNs). The proposed solution is to use a pretrained MobileNetV2 model, which is a lightweight and efficient CNN architecture, and fine-tune it on a dataset of sea animals. The results of the study (...) show that the fine-tuned MobileNetV2 model is able to achieve an accuracy of 85% on the classification task, which is competitive with the state-of-the-art methods. Additionally, the study also found that data augmentation and regularization techniques such as dropout were important for preventing overfitting and improving the performance of the model. This study demonstrates the potential of using pretrained models and efficient CNN architectures for classifying sea animals, and it provides insights into the challenges and best practices for solving this important problem in marine biology and ecology. (shrink)

Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected from Kaggle which (...) is part from the Plant Village dataset. We generate a comprehensive training dataset using techniques such as image filtering, compression, and generation. Our model achieves impressive accuracy scores for all classes, with an overall accuracy of 99.93% on a dataset of 10,000 labeled images . (shrink)

Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has been (...) proposed. The aim of this paper is to diagnose tomato diseases based on a dataset containing 11000 picture and 11 classes. The model gave the final accuracy test with Accuracy (99.87%), F1-score (99.87%), Recall (99.87%), and Precision (99.88%) in an estimated time 1.36 second, as with these results it proved its effectiveness and good ability in the classification of the testing data. (shrink)

Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...) Watch institute. Discovery and classification depend on human experience and effort, so the error in the results of this process can lead to forest fires and disasters. Therefore, deep learning algorithms from artificial intelligence and machine learning sciences have been applied to help specialists avoid false or inaccurate diagnoses when detecting Forest fires in images using a pre-trained convolutional neural network called VGG16. The model was customized to fit the Forest fires classification and then applied to a dataset consisting of (14,000) of the Forests collected from the Kaggle depository. We trained, validated, and tested the modified VGG16 model. The proposed VGG16 model obtained Precision (99.96%), Recall (99.96%), and F1-Score (99.96%). (shrink)

Academic excellence and intelligence are commonly lauded as commendable attributes synonymous with success. However, a disconcerting trend has surfaced within educational institutions, challenging the prevailing narrative of scholastic accomplishment—smart shaming. This research delves into the increasing concern of smart shaming within educational settings, particularly at Immaculate Conception College of Balayan, Inc., questioning the predominant emphasis on academic excellence and intelligence. A qualitative case study design, along with judgmental sampling, was employed to examine fifteen (15) student leaders who had experienced smart (...) shaming on campus. Thematic analysis revealed that sarcastic remarks including "edi wow," "Okay ikaw na matalino," "bidabida," and "sipsip" were a prevalent manifestation of smart shaming, adversely affecting emotional well-being, academic and leadership prowess, mental health, and self-perception. Coping mechanisms, predominantly centered around ignoring and focusing on goals, were identified. The findings underscore the imperative for educators to remain vigilant regarding instances of smart shaming in classrooms, promoting open communication to ensure student well-being. Additionally, guidance counselors play a pivotal role in aiding students in effectively navigating the repercussions of smart shaming. This study advocates for proactive programs and interventions to address and alleviate the deleterious effects of smart shaming on students. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...) it addresses challenges such as data privacy, technology adoption barriers, and the ethical implications of AI in farming. By integrating AI into agricultural practices, the industry can achieve greater efficiency and sustainability, paving the way for future advancements. (shrink)

The co-evolutionary concept of Three-modal stable evolutionary strategy of Homo sapiens is developed. The concept based on the principle of evolutionary complementarity of anthropogenesis: value of evolutionary risk and evolutionary path of human evolution are defined by descriptive (evolutionary efficiency) and creative-teleological (evolutionary correctly) parameters simultaneously, that cannot be instrumental reduced to others ones. Resulting volume of both parameters define the trends of biological, social, cultural and techno-rationalistic human evolution by two gear mechanism ˗ gene-cultural co-evolution and techno- humanitarian balance. (...) The resultant each of them can estimated by the ratio of socio-psychological predispositions of humanization/dehumanization in mentality. Explanatory model and methodology of evaluation of creatively teleological evolutionary risk component of NBIC technological complex is proposed. Integral part of the model is evolutionary semantics (time-varying semantic code, the compliance of the biological, socio-cultural and techno-rationalist adaptive modules of human stable evolutionary strategy). (shrink)

The study aimed at identifying responsive flexibility and its role in improving service quality, from the point of view of the internal beneficiary in non-governmental hospitals in Gaza Strip. The study relied on the descriptive and analytical approach, and the questionnaire was designed as a tool to collect data, and the researchers used the comprehensive survey method, and the number of the study population was (536) single, where (434) questionnaires were retrieved, and the recovery rate was (80.97%). The study showed (...) many results, the most important of which were: The presence of moderate degree of approval by the study sample on the responsive flexibility, as it was evident through the response flexibility field obtaining a relative weight (60.50%), and the results of the study indicated that there is a high degree of approval by the members of the study sample. On the quality of service, as it was evident through the field of service quality obtaining a relative weight (79.90%). The results of the study revealed a statistically significant relationship between responsive flexibility and service quality in non-governmental hospitals in Gaza Strip, with a correlation coefficient of 0.418, and the results of the study revealed a statistically significant effect between responsive flexibility and service quality in non-governmental hospitals in Gaza Strip. The study reached many recommendations, the most important of which were: Finding mechanisms by which stored information can be used to enhance the decision-making process, and setting up an effective system to receive patients' complaints in a manner that ensures rapid response and treatment, to achieve continuous communication between patients and the hospital management, and to notify patients of abuse With the complaints that they submit, and working to provide all medical and health specialties in the hospitals under study, by making use of the medical delegations that visit Gaza Strip, involving them in the treatment processes, bringing in doctors and specialists from abroad, and updating the standards related to measuring the services provided to patients continuously, based on On patients' suggestions and complaints, developing facilities in hospitals, as well as updating medical devices and equipment used in hospitals periodically. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting AI, such (...) as data privacy concerns, integration issues, and the need for skilled personnel. The paper concludes with recommendations for effectively implementing AI solutions to maximize their benefits while navigating potential pitfalls. (shrink)

E-money systems have revolutionized global business transactions through digital payment methods. This quantitative correlational study aimed to assess the awareness and acceptance of e-money among individuals in Balayan, Batangas. Employing quota and purposive sampling, 100 participants aged 21 to 70 completed a survey questionnaire. Statistical analysis revealed that consumers were aware of e-money but lacked comprehensive knowledge. They acknowledged the convenience of e-money for online shopping and expense tracking. Age significantly influenced acceptance, while gender did not exhibit a similar effect. (...) Significant differences were observed in awareness and acceptance levels. Recommendations for improving acceptance include administrator-led campaigns, business incentives, consumer education, financial institution partnerships, and integration into student curricula. The study underscores the need for targeted strategies to translate e-money knowledge into practical use. Future research should explore adoption trends over time, barriers, and the impact of regulations on e-money utilization. (shrink)

To improve oneself and grow professionally, career development has been found to be crucial, as it serves as a roadmap for the professional growth of employees. However, a barrier, known as the glass ceiling, hinders the progress of employees, especially those in the LGBTQIA+ community. This study explores the impact of the glass ceiling on the career development of selected LGBTQIA+ individuals, shedding light on the barriers faced by this community in the workplace. The researchers used a qualitative multiple-case study (...) and selected ten (10) LGBTQIA+ participants from large enterprises via the judgmental sampling technique. Through thematic analysis, psychological impact, workplace discomfort, lack of recognition, and career progress challenges emerged as the impacts of the glass ceiling on the participants. Strategies for overcoming glass ceiling barriers, such as resilience, self-reflection, and community support, are identified. Thus, the study found that glass ceilings are really evident in the context of businesses. With this, the proposed advocacy plan in the study suggests interventions like workplace inclusion training, mentorship networks, and seminars on employee rights. Furthermore, it emphasizes the call for ongoing research and advocacy efforts to dismantle barriers and cultivate workplaces that not only embrace diversity but also provide equitable opportunities for career growth. (shrink)

Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in dvance regarding: on-going construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. In (...) our proposed system we propose a new forecasting method that uses a Convolutional Neural Network monthly rainfall for a selected location. In our proposed system we are going to forecast the rainfall result based on the mean square error, mean absolute error and root mean square error, which we get in train and test of the dataset based deep learning technique. (shrink)

De burgemeester van Etterbeek liet tijdens de afgelopen periode van vrieskou daklozen van straat halen. Soms tegen hun wil in. Omdat het soms nodig is om mensen tegen zichzelf te beschermen.

Abstract: Vegetables are an essential component of a healthy diet and play a critical role in promoting overall health and well- being. Vegetables are rich in important vitamins and minerals, including vitamin C, folate, potassium, and iron. They also provide fiber, which helps maintain digestive health and prevent chronic diseases. We are proposing a deep learning model for the classification of vegetables. A dataset was collected from Kaggle depository for Vegetable with 15000 images for 15 different classes. The data was (...) preprocessed, normalized and split into three sets (train, valid, test). The proposed model was trained and validated using the train and valid sets and accuracy of both training and validation was very high. For the evaluation of the proposed model we utilized these metrics: accuracy, F1-score, precision, Recall and time required for testing. We then tested the proposed model using the test set. The result of the testing was accuracy (99.95%), F1-score (99.95%), precision (99.95%), Recall (99.95%) and time required for testing the test set was 1.38 seconds. (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)

Identification of factors that predict recurrent antisocial behavior is integral to the social sciences, criminal justice procedures, and the effective treatment of high-risk individuals. Here we show that error-related brain activity elicited during performance of an in- hibitory task prospectively predicted subsequent rearrest among adult offenders within 4 y of release (N =96). The odds that an offender with relatively low anterior cingulate activity would be rearrested were approximately double that of an offender with high activity in this region, holding (...) constant other observed risk factors. These results suggest a potential neurocognitive biomarker for persistent antisocial behavior. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into educational technology has revolutionized learning through Intelligent Tutoring Systems (ITS). These systems harness AI to deliver personalized, adaptive instruction that caters to individual student needs, thereby enhancing learning outcomes and engagement. This paper explores the evolution and impact of ITS, highlighting key AI technologies such as machine learning, natural language processing, and adaptive algorithms that underpin their functionality. By examining various case studies and applications, the paper illustrates how ITS have transformed traditional (...) educational practices and identifies the challenges and limitations associated with their implementation, including data privacy concerns and system biases. The discussion also extends to future directions in ITS development, emphasizing emerging trends and potential advancements. Ultimately, this paper aims to provide a comprehensive understanding of how ITS leverage AI to enhance educational experiences and propose pathways for future research in this dynamic field. (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)

Abstract: As artificial intelligence (AI) technologies become increasingly integrated into various sectors, ethical considerations surrounding their development and deployment have become paramount. This paper explores the multifaceted ethical landscape of AI, focusing on key challenges such as bias, transparency, privacy, and accountability. It examines how these issues manifest in AI systems and their impact on society. The paper also evaluates current approaches and solutions aimed at mitigating these ethical concerns, including regulatory frameworks, ethical guidelines, and best practices for AI design. (...) By providing a comprehensive analysis of these challenges and solutions, this paper aims to contribute to the ongoing discourse on responsible AI development and implementation, advocating for a balance between technological innovation and ethical integrity. (shrink)

The study determined the chemical composition and acceptability of organic bath soap among students in Yaba College of Technology, Yaba, Lagos State, Nigeria. The study was guided by two research questions. Mixed method research design was used for the study. Population was 46 which comprised all Home Economics students from the Department of Vocational Education. In-home use questionnaire was used for data collection. The study produced two samples of turmeric bath soap. Findings showed that the chemical compositions of the turmeric (...) soap samples are in accordance with the specifications of the Standard Organization of Nigeria (SON) with toilet soap specifications of pH ranging from 9 to 11, total fatty matter ranging from 60-75 gm and total free caustic soda ranging from 0.05 to 0.08 %. Findings showed that the sensory evaluation attributes for colour, smell, consistency foam ability and skin sensitivity were accepted after use for three months as the samples were skin friendly, safe to use without side effects. It was recommended that turmeric body soap and turmeric face gel can be produced in large quantities for commercial purpose as a form of income generation for unemployed graduates. (shrink)

This discussion treats a set of familiar social derelictions as consequences of the perversion of a universalistic moral theory in the service of an ill-considered or insufficiently examined personal agenda.The set includes racism, sexism, anti-Semitism, homophobia, and class elitism, among other similar pathologies, under the general heading of discrimination. The perversion of moral theory from which these derelictions arise, I argue, involves restricting its scope of application to some preferred subgroup of the moral community of human beings. -/- The following (...) analysis of higher-order discrimination suggests that we often select the individuals who constitute such subgroups for reasons that we ourselves would reject on moral grounds were we to examine them carefully, but that we choose instead to put our rational resources in the service of avoiding any such examination at all costs. The implication is that arguments that truncate the scope of moral theory in fact justify bestowing the gift of moral treatment on a select few who deserve it no more than the many from whom we withhold it. Therefore, it would be precipitous to conclude that universalistic moral theory can be legitimately restricted in its practical scope of application in any way at all. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into leadership practices is transforming organizational dynamics and This decision-making processes. paper explores how AI can enhance leadership effectiveness by providing data-driven insights, optimizing decision-making, and automating routine tasks. It also examines the challenges leaders face in adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to provide a comprehensive overview of the (...) opportunities AI presents for effective leadership and the strategies required to address its associated challenges. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing organizational dynamics by reshaping both structures and processes. This paper explores how AI-driven innovations are transforming organizational frameworks, from hierarchical adjustments to decentralized decision-making models. It examines the impact of AI on various processes, including workflow automation, data analysis, and enhanced decision support systems. Through case studies and empirical research, the paper highlights the benefits of AI in improving efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges associated with AI (...) integration, such as resistance to change, ethical concerns, and data security issues. The paper concludes by offering insights into future trends and implications for organizations navigating the evolving landscape of AI-driven change. (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.

Heart failure 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 918 samples with 11 features, such as age, sex, chest pain type, resting blood pressure, 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 and 1 output) was trained on the dataset and achieved an accuracy of 90% and an average error of 0.009. 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)

My aim in this discussion is to argue, not only that government should provide funding for the arts, but a fortiori that it should provide funding for unconventional, disruptive works of art.

Indian and Classical Greek philosophical traditions both recommend that we structure our lives around the performance of certain kinds of actions as daily and regular habits. Under some circumstances and for some individuals, this means merely doing what comes naturally. For others, it requires varying degrees of self-control. For yet others, adhering to these practices is impossible or unimportant, beyond the scope of their interests or abilities. I want to take issue with one familiar answer to the question of why (...) this is, and to suggest a different one. (shrink)

This essay represents a novel contribution to Nietzschean studies by combining an assessment of Friedrich Nietzsche’s challenging uses of “truth” and the “eternal return” with his insights drawn from Indian philosophies. Specifically, drawing on Martin Heidegger’s Nietzsche, I argue that Nietzsche’s critique of a static philosophy of being underpinning conceptual truth is best understood in line with the Theravada Buddhist critique of “self ” and “ego” as transitory. In conclusion, I find that Nietzsche’s “eternal return” can be understood as a (...) direct inversion of “nirvana”: Nietzsche celebrates profound attachment to each and every moment, independent from its pleasurable or distasteful registry. (shrink)

Aborda a descrição do sistema digestivo dos não-ruminantes e suas particularidades, o aproveitamento e importância da água e demais nutrientes para o desenvolvimento das aves, suínos, equinos, peixes, cães e gatos. Como os nutrientes e a energia é aproveitada pelos Não-Ruminantes. São descritos o conceito de aditivos e sua importância a ser adicionado nas rações destes animais, e como as rações são formuladas para o atendimento mínimo dos nutrientes e energia, além da formulação do suplemento vitamínico e mineral.

As these opening quotes acknowledge, the Prisoner’s Dilemma (PD) represents a core puzzle within the formal mathematics of game theory.3 Its rise in conspicuity is evident figure 2.1 above demonstrating a relatively steady rise in incidences of the phrase’s usage between 1960 to 1995, with a stable presence persisting into the twenty first century. This famous two-person “game,” with a stock narrative cast in terms of two prisoners who each independently must choose whether to remain silent or speak, each advancing (...) self-interest at the expense of the other and thereby achieving a mutually suboptimal outcome, mires any social interaction it is applied to into perplexity. The logic of this game proves the inverse of Adam Smith’s invisible hand: individuals acting on self interest will achieve a mutually suboptimal outcome. However, as this chapter illuminates, the assumptions underlying game theory drive this conclusion. (shrink)

There are three questions associated with Simpson’s Paradox (SP): (i) Why is SP paradoxical? (ii) What conditions generate SP?, and (iii) What should be done about SP? By developing a logic-based account of SP, it is argued that (i) and (ii) must be divorced from (iii). This account shows that (i) and (ii) have nothing to do with causality, which plays a role only in addressing (iii). A counterexample is also presented against the causal account. Finally, the causal and logic-based (...) approaches are compared by means of an experiment to show that SP is not basically causal. (shrink)

In the first chapter of his Knowledge and Lotteries, John Hawthorne argues that thinkers do not ordinarily know lottery propositions. His arguments depend on claims about the intimate connections between knowledge and assertion, epistemic possibility, practical reasoning, and theoretical reasoning. In this paper, we cast doubt on the proposed connections. We also put forward an alternative picture of belief and reasoning. In particular, we argue that assertion is governed by a Gricean constraint that makes no reference to knowledge, and that (...) practical reasoning has more to do with rational degrees of belief than with states of knowledge. (shrink)

Traditionally, the investigation of truth has been anchored in a priori reasoning. Cognitive science deviates from this tradition by adding empirical data on how people understand and use concepts. Building on psychophysics and machine learning methods, we introduce conceptual scaling, an approach to map people's understanding of abstract concepts. This approach, allows computing participant-specific conceptual maps from obtained ordinal comparison data, thereby quantifying perceived similarities among abstract concepts. Using this approach, we investigated individual's alignment with philosophical theories on truth and (...) the predictive capacity of conceptual maps. The obtained results indicated that, while people's understanding of truth is multifaceted and encapsulates notions of coherence and authenticity, alignment is best for the correspondence theory of truth. Furthermore, conceptual maps allowed predicting individual outcomes with an accuracy of roughly 70%. This research demonstrates that conceptual scaling offers accurate descriptions of individual's understanding of abstract concepts, behavioral predictions, and quantification of alignment with theoretical perspectives. (shrink)

Virtues and reasons are two of the most fruitful and important concepts in contemporary moral philosophy. Many writers have commented upon the close connection between virtues and reasons, but no one has done full justice to the complexity of this connection. It is generally recognized that the virtues not only depend upon reasons, but also sometimes provide them. The essays in this volume shed light on precisely how virtues and reasons are related to each other and what can be learned (...) by exploring this relationship. Virtue’s Reasons is divided into three sections, each of them devoted to a general issue regarding the relationship between virtues and reasons. The first section analyzes how the virtues may be related to, or linked with, normative reasons in ways that improve our understanding of what constitutes virtuous character and ethical agency. The second section explores the reasons moral agents have for cultivating the virtues and how the virtues impact moral responsiveness or development. The final section examines how reasons can be employed in understanding the nature of virtue, and how specific virtues, like modesty and practical wisdom, interact with reasons. This book will be of major interest to scholars working on virtue theory, the nature of moral character, and normative ethics. (shrink)

Rawls offers three arguments for the priority of liberty in Theory, two of which share a common error: the belief that once we have shown the instrumental value of the basic liberties for some essential purpose (e.g., securing self-respect), we have automatically shown the reason for their lexical priority. The third argument, however, does not share this error and can be reconstructed along Kantian lines: beginning with the Kantian conception of autonomy endorsed by Rawls in section 40 of Theory, we (...) can explain our highest-order interest in rationality, justify the lexical priority of all basic liberties, and reinterpret Rawls’ threshold condition for the application of the priority of liberty. Perhaps unsurprisingly, this Kantian reconstruction will not work within the radically different framework of Political Liberalism. (shrink)

This paper examines how the concepts of utility, impartiality, and universality worked together to form the foundation of Adam Smith's jurisprudence. It argues that the theory of utility consistent with contemporary rational choice theory is insufficient to account for Smith's use of utility. Smith's jurisprudence relies on the impartial spectator's sympathetic judgment over whether third parties are injured, and not individuals' expected utility associated with individuals' expected gains from rendering judgments over innocence or guilt.

Although social scientists have identified diverse behavioral patterns among children from dissimilarly structured families, marketing scholars have progressed little in relating family structure to consumption-related decisions. In particular, the roles played by members of single-mother families—which may include live-in grandparents, mother’s unmarried partner, and step-father with or without step-sibling(s)—may affect children’s influence on consumption-related decisions. For example, to offset a parental authority dynamic introduced by a new stepfather, the work-related constraints imposed on a breadwinning mother, or the imposition of adult-level (...) household responsibilities on children, single-mother families may attend more to their children’s product preferences. -/- Without a profile that includes socio-economic, behavioral, and psychological aspects, efficient and socially responsible marketing to single-mother households is compromised. Relative to dual-parent families, single-mother families tend to have fewer resources and less buying power, children who consume more materialistic and compulsively, and children who more strongly influence decision making for both own-use and family-use products. Timely research would ensure that these and other tendencies now differentiate single-mother from dual-parent families in ways that marketers should address. Hence, our threefold goal is (1) to consolidate and highlight gaps in existing theory applied to studying children’s influence on consumption-related decision making in single-mother families, and (2) to propose a hybrid framework that merges two theories conducive to such research, and (3) to identify promising research propositions for future research. (shrink)

This paper critically engages Philip Mirowki's essay, "The scientific dimensions of social knowledge and their distant echoes in 20th-century American philosophy of science." It argues that although the cold war context of anti-democratic elitism best suited for making decisions about engaging in nuclear war may seem to be politically and ideologically motivated, in fact we need to carefully consider the arguments underlying the new rational choice based political philosophies of the post-WWII era typified by Arrow's impossibility theorem. A distrust of (...) democratic decision-making principles may be developed by social scientists whose leanings may be toward the left or right side of the spectrum of political practices. (shrink)

The paper argues that the moral philosophy of Thomas Hobbes is unified by a complex conception of reason that imposes consistency norms of both rationality and reasonableness. Hobbes’s conceptions of rightness as reciprocity, and moral goodness as sociability belong to an original and attractive moral theory that is neither teleological nor classically deontological, nor as interpreters have variously argued, subjectivist, contractarian, egoist, or dependent on divine command.

This article defends the conclusion that the soccer World Cup in Qatar should not be boycotted by rich countries from the Global North. This conclusion is underpinned by considerations about the economic background conditions in guest workers’ home countries. Three arguments are considered for the view that the World Cup should be boycotted. It is argued that each of these arguments is unsound. Section 7 contains a discussion of an argument for a boycott that centers on the process through which (...) Qatar was awarded the World Cup. This argument is rejected. The article lists several ways in which guest workers in Qatar are wronged, but this fact about how guest workers are treated does not justify a boycott by rich countries from the Global North. (shrink)