Coronavirus is a viral irresistible sickness brought about by SARS- COV2. Its clinical signs and side effects are on an expansive range going from asymptomatic to serious confusions like multi-organ disappointment, thromboembolism, and extreme pneumonia with respiratory disappointment. More awful results and higher death rates have been accounted for in the old, individuals with co-morbidities, and malnourished people. Sustenance is central to acceptable wellbeing and safe capacity. It frames an essential segment of therapy modalities for different intense and persistent infections, (...) particularly where a causative therapy isn't yet perceived. Despite the fact that reviews tending to the part of explicit supplements in COVID-19 are still at a beginning phase, accessible proof recommends that addressing the necessities of a variety of large scale and miniature supplements (energy, proteins, fats, nutrients A, D, E, C, B nutrients, iron, selenium, zinc, and so forth) Additionally, supplements are Immune System Might Promote Recovery for Mild COVID-19 Patients Impact of Coronavirus on Education in India Review 466 determinants of the sythesis of the gut microbiota that thusly impacts the attributes of safe reactions in the body. (shrink)

A letter replying to Bayne et al. "Tests for consciousness in humans and beyond", 2024, arguing that the search for consciousness "beyond" healthy adult humans should begin with other animals.

Abstract: The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) is fundamentally transforming how organizations approach recruitment, performance management, and employee engagement. This paper explores the multifaceted impact of AI on HR practices, highlighting its role in enhancing efficiency, reducing bias, and driving strategic decision-making. Through an in-depth analysis of AI-driven recruitment tools, performance management systems, and personalized employee engagement strategies, this study examines both the opportunities and challenges associated with AI in HRM. Ethical considerations, including data privacy, (...) algorithmic bias, and the potential displacement of human jobs, are critically discussed to provide a balanced perspective on the adoption of AI technologies in the HR domain. By presenting case studies of organizations successfully leveraging AI, this paper offers insights into the future trajectory of HRM in an increasingly AI-driven world. Ultimately, the findings underscore the need for HR professionals to adapt and innovate in response to the growing influence of AI, ensuring a harmonious balance between technological advancement and the human element in the workplace. (shrink)

How can we have a sense of the presence of ordinary three-dimensional objects (e.g., an apple on my desk, a partially occluded cat behind a picket fence) when we are only presented with some parts of objects perceived from a particular egocentric viewpoint (e.g., the facing side of the apple, the unoccluded parts of the cat)? This paper presents and defends a novel answer to this question by incorporating insights from two prominent contemporary theories of perception, naïve realism and sensorimotor (...) theory. Naïve realism is the view that perception is fundamentally a matter of obtaining a relation of ‘acquaintance’ with some mind-independent entities (e.g., objects, properties, events). Sensorimotor theory holds that perception involves implicit practical understanding or ‘anticipation’ of the covariance between movements and sensory changes. I argue that perceptual presence is best accounted for in terms of the combination of our direct ‘acquaintance’ with some parts of perceived objects and sensorimotor ‘anticipations’ of how the objects would look different depending on some movements and actions. (shrink)

In het spoor van de moord op George Floyd door een politieagent in Minneapolis, vinden er wereldwijd ‘Black Lives Matter’ protesten plaats. De beeldenstorm in ons land sluit hierbij aan. Acties van fanatici, of hebben ze een punt dat we liever niet onder ogen zien? Beelden van dubieuze nationale helden horen in museum thuis, niet op straat.

This thesis is about perceptual experience, its subjective character, and how it is essentially structured. It focuses specifically on how the nature of perception is shaped not only by our acquaintance with the world but also by the very structure of experience itself. My central claim is that perceptual consciousness incorporates different aspects, some of which constitute the very way in which experiences are organized, sustained, and structured. Over the course of this thesis, I develop and defend an original account (...) of the nature of perceptual experience by integrating naïve realism, a prominent contemporary Anglophone theory of perception, with insights and ideas from the Phenomenological tradition. In particular, I argue that there are fruitful grounds for combining naïve realism and a phenomenologically grounded account of the essential structural features of experience (‘minimal self’, ‘temporality’, ‘anticipation’). Naïve realism holds that perception is fundamentally a matter of being in direct contact with some mind-independent entities. Proponents of naïve realism often emphasize the ‘object-dependent’ nature of perception. The appeal to the structural features of experience offers us a promising way to delineate the oft-overlooked ‘subject-dependent’ nature of perception and capture the phenomenological richness of our conscious experiential life. This thesis offers a rich, phenomenologically informed account of the nature of perception which in turn places us in a better position to understand the nature of hallucination. The integration of naïve realism and the structural approach to consciousness I develop in this thesis yields a novel solution to the problem of hallucination: structural disjunctivism. According to this view, the ‘partially overlapping’ psychological nature of perception and hallucination is accounted for in terms of their structural similarities and differences. I seek to show how detailed analyses and reflections on the structures of perceptual experience pave the way to reconceive the phenomenological basis of naïve realism. (shrink)

Po svoji uèinkovitosti pri spodbujanju éustev glede pripadnosti oz. nepripadnosti je morda edino religija sposobna tekmovati z domoljubjem. Morda tudi samo religija lahko tekmuje z domoljubjem v svoji sposobnosti, da spodbuja in neguje pripadnost milijonov, da bi dosegla niz ciljev povezanih z zvestobo. Vendar paje, kotje opazil John Kleinig (2014: 5), 'domoljubna in verska zvestoba, kljub vsem svojim vznemirjujoèim lastnostim, pogosto pristranska, izkljuóujoéa in celo teroristiéna'. Ince se posamezniki nekritiéno identificirajo z narodom, njegovimi ideali, zgodovino, institucijami in voditelji, ima domoljub (...) nagnjenost delovati, braniti, napadati in celo imeti tujce za manjvredne. (shrink)

Over the past 45 years there has been increasing vocal opposition to religious schools, particularly in Western Europe. Only some of this opposition is related to the perception that some religious schools might be excluding the less fortunate. Much of the opposition rests on the conviction that it is no longer tenable to fund and support so many religious schools when the number of persons professing religious belief has sharply declined. This argument, buttressed by the belief that Europe has undergone (...) a profound “secularization,” maintains that religious schools are but an obsolete cultural relic to be discarded in favor of nondenominational alternatives. Relatedly, religious schools are believed to contribute to segregation and “divisiveness”: Rather than maintain a system in which persons are drawn to schools that reflect their own cultural or religious background, children ought to attend the same schools, learning from – and not only about – each other through substantive interaction. Underneath this argument lies a concern with fostering the skills and dispositions necessary for citizenship. It remains unclear, however, whether religious schools are more guilty of segregation than nonreligious schools. Nor is it clear why attending a religious school would make one less capable of cultivating the skills and dispositions necessary for citizenship than nonreligious alternatives. (shrink)

This paper traces two contradicting beliefs about death and immortality in the writings of Rabbi Hayyim Hirschensohn, and examines these opposing beliefs in his Halakhic ruling, in the case of Autopsies. The paper opens by conceptualizing two possible attitudes regarding the relation between this-world and the ʽother-world’, and by analyzing two main beliefs regarding death and immortality in their relation to the body-spirit distinction (the naturalistic and the spiritualistic approach). It demonstrates how Hirschensohn was holding these two different views. The (...) paper then moves to examine whether his halakhic ruling may help us in understanding which approach was Hirschensohn’s favorable belief, by investigating his halakhic ruling regarding autopsies. Hirschensohn permits to perform such surgeries, however subject to some halakhic limitations. The paper concludes that the naturalistic belief regarding death appears to be the more dominant one in his thought. Finally, I point out a few consequences of this paper, for addressing some contemporary ethical dilemmas regarding human corpses. (shrink)

The current study is conducted to examine the following research questions: 1) How is the residential proximity to the coast during childhood, and nature connectedness, associated with peace of mind when visiting the coast? 2) Does the residential proximity to the coast during childhood moderate the relationship between nature connectedness and peace of mind when visiting the coast? 3) How is the peace of mind associated with improved thinking when visiting the coast?

Definição de IPP da vaca A idade ao primeiro parto (IPP) da vaca, como o próprio nome indica, é a idade em que a vaca tem o seu primeiro parto e, portanto, o seu bezerro(a). Representa o início do retorno econômico do investimento realizado na criação de novilhas. É o ponto de partida onde a vaca começa a produzir descendentes para venda ou reposição e leite para venda, sendo as duas fontes de renda na pecuária de duplo propósito ou dupla (...) aptidão, com criação de raças produtoras de carne e leite. Qual deve ser a IPP da vaca? Para as condições tropicais, espera-se que o primeiro parto da novilha ocorra entre: 29 – 35 meses, o que seria possível se os animais atingissem a gestação aos 20-26 meses de idade. Em condições tropicais, foram relatados valores de idade ao primeiro parto em bovinos mestiços de duplo propósito entre 32 e 48 meses (Aranguren et al., 1993; Rosendo et al., 1993). Isto mostra que existe um amplo valor de melhoria que parece ser basicamente influenciado pela componente nutricional. (shrink)

The current study is conducted to examine the following research questions: 1) How are gender, age, and income associated with trying space tourism? 2) How are gender, age, and income associated with the intention to try space tourism when conditional on the level of immersiveness in information on social media?

The current study is conducted to examine the following research questions: 1) How are coastal activities enabling close connections to nature associated with the mental health condition of the visitors in the previous year? 2) How are coastal activities that have close connections to nature associated with the perceived general health condition of the visitors in the previous year?

Nếu như năm 2022, Truyện ngụ ngôn Bói Cá bản tiếng Anh hoàn tất và đến được quầy hàng, thì năm 2023, bài viết có nguồn gốc suy nghĩ từ ngụ ngôn, kèm theo chương trình nghiên cứu về môi trường, biến đổi khí hậu với bóng dáng Bói Cá hiện diện rõ nét, cũng ra đời.

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

The current study is conducted to examine the following research question: How are the temperature and population density associated with the countries’ cultural values of embeddedness and hierarchy cultural values?

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

The current study is conducted to examine the following research question: How are healthy eating information-seeking ability and e-health literacy associated with healthy eating intention?

The current study is conducted to examine the following research question: How are the temperature and rainfall associated with the countries’ cultural values of embeddedness and hierarchy cultural values?

The current study is conducted to examine the following research questions: 1) How are health information-seeking ability and e-health literacy associated with illness response capability? 2) How are health information-seeking ability and e-health literacy associated with the frequency of health checkups?

The current study is conducted to examine the following research questions: 1) How is engaging children with nature associated with their environmental awareness? 2) How is engaging children with nature associated with their environmental protection participation?

Abstract: Lemons are an important fruit that have a wide range of uses and benefits, from culinary to health to household and beauty applications. Deep learning techniques have shown promising results in image classification tasks, including fruit quality detection. In this paper, we propose a convolutional neural network (CNN)-based approach for detecting the quality of lemons by analysing visual features such as colour and texture. The study aims to develop and train a deep learning model to classify lemons based on (...) their quality, evaluate the model's performance, compare it to traditional machine learning approaches, and identify key factors that affect the model's performance. The dataset used in the study consists of approximately 2533 images of lemons and an empty surface, divided into training, test, and validation data, and includes images of both good and bad quality lemons under different lighting conditions. The deep learning model achieved an accuracy of 99.74% on the test dataset and outperformed traditional machine learning approaches. The developed model has the potential to improve efficiency and accuracy in lemon quality control in the agriculture and food industry. (shrink)

The challenges and opportunities associated with the education of immigrants predate modern school systems, though it certainly can be said that support for public schooling grew—for example, in Canada and the United States—as dominant (read White, Anglo-Saxon, Protestant) groups came to see the importance of integrating masses of disparate origin. Educational responses to the children of immigrants over time have been varied, and many responses are indistinguishable from efforts to address other minority groups. In North America, the rapid expansion of (...) immigration encompassing immigrant and refugee populations from around the world, particularly since the 1960s, has led to a number of structural and curricular changes in schools, only some of which were explicitly aimed at immigrants. One example of a policy aimed at the children of immigrants was bilingual education, and as this increasingly fell out of favor, ESL (English as a second language) classrooms became more common. However, with few exceptions, neither has been a very effective instrument for addressing the interests or concerns of immigrants themselves. Nevertheless, most parents strongly prefer that their children learn to master the dominant language, as a means of getting ahead. (shrink)

Identity in the philosophical literature has until recently be confined mostly to ruminations on the self: as soul in Plato; rationality connected to, but not coterminous with, the body in Descartes; uninterrupted consciousness in Locke; a stream of experiences which a thing has in relation to itself in Hume; an emotive life in Rousseau; as noumenal self about which we can know little in Kant; as will in Schopenhauer; as an elusive but nonspecific something in Wittgenstein; and as the continuous, (...) purposive struggle of creative power against an historically contingent concatenation of social, political, and cultural forces in Nietzsche and Foucault. Yet what follows is not a summary of metaphysics or philosophy of mind. There also is not sufficient space here to examine identity in each of the separate disciplines. Instead, what follows are some prefatory discursive remarks about identity; then, owing to the dominance of psychological theories on identity, a brief overview of some of its salient themes will be adumbrated; this will be followed by a discussion on identity formation and maintenance both in political philosophy and philosophy of education. (shrink)

Phenomenology gives rise to certain ontological considerations that have far-reaching implications for standard conceptions of patient autonomy in medical ethics, and, as a result, the obligations of and to patients in clinical decision-making contexts. One such consideration is the phenomenological reduction in classical phenomenology, a core feature of which is the characterisation of our primary experiences as immediately and inherently meaningful. This paper builds on and extends the analyses of the phenomenological reduction in the works of Husserl, Heidegger, and Merleau-Ponty (...) in order to identify and explain its implications for our current understanding of the principle of respect for patient autonomy and the norms of clinical decision making. (shrink)

Abstract: The Knowledge-Based System for Diagnosing Breast Cancer aims to support medical students in enhancing their education regarding diagnosis and counseling. The system facilitates the analysis of biopsy images under a microscope, determination of tumor type, selection of appropriate treatment methods, and identification of disease-related questions. According to the Ministry of Health's annual report in Gaza, there were 7,069 cases of breast cancer between 2009 and 2014, with 1,502 cases reported in 2014. In an era dominated by visual information, where (...) 65% of the population are visual learners, the Knowledge-Based System serves as an effective tool to aid long-term information retention by utilizing visual and textual resources. The system features a user-friendly interface, enabling students to diagnose the disease and expand their understanding. Furthermore, it can be accessed via smartphones. The Knowledge-Based System comprises three primary components: Firstly, it provides specific patient-oriented questions to familiarize students with the questioning process. Secondly, it facilitates the analysis of biopsy sample images to determine their integrity and identify potential infections. Lastly, the system incorporates animated videos illustrating various approaches for treating breast cancer. (shrink)

The traditional use of conventional media by businesses for audience targeting has shifted with the rise of influencer marketing, notably on platforms like TikTok, posing challenges in content adaptation and technological adaptation. Albert Bandura's Social Cognitive Theory examines factors shaping purchasing behavior, particularly relevant for young professionals. A quantitative correlational study focused on young professionals engaging with TikTok and influenced by Filipino TikTok creators, revealing education level as a key determinant of purchasing behavior. Extended TikTok engagement positively correlates with increased (...) purchasing likelihood. Filipino TikTok influencers significantly impact young professionals' purchasing decisions, emphasizing the need for tailored marketing strategies targeting this demographic. Recommendations were provided for effective influencer and digital marketing strategies targeting young professionals. (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: 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: Fast food refers to quick, convenient, and ready-to-eat meals that are usually sold at chain restaurants or take-out establishments. Fast food is often criticized for its unhealthy ingredients, such as high levels of salt, sugar, and unhealthy fats, and its contribution to the growing obesity epidemic. Despite this, fast food remains popular due to its affordability, convenience, and widespread availability. Many fast food chains have attempted to respond to these criticisms by offering healthier options, such as salads and grilled (...) chicken sandwiches, and by using more natural and locally sourced ingredients. The aim in this paper to propose a deep learning model for the classification of fast food dishes. The proposed model, Xception, was trained on natural images and was fine-tuned to make up the fast food meals. The researchers collected the Fast Food V2 dataset from Kaggle depository, the dataset, contained 20,000 images. The dataset has ten labels of food images comprised of Baked Potato, Burger, Crispy Chicken, Donut, Fries, Hot Dog, Pizza, Sandwich, Taco, and Taquito. The dataset was split into three sets: training, validation and testing. The accuracy, F1-score, recall, precision on the separate test set showed that classification of fast food was accuracy (95.13%), Precision (95.34%), Recall (95.13%), and F1-Score (95.14%). (shrink)

Background: A bean is the seed of one of several genera of the flowering plant family Fabaceae, which are used as vegetables for human or animal food. They can be cooked in many different ways, including boiling, frying, and baking, and are used in many traditional dishes throughout the world. Beans are one of the longest-cultivated plants. Broad beans, also called fava beans, in their wild state the size of a small fingernail, were gathered in Afghanistan and the Himalayan foothills. (...) In a form improved from naturally occurring types, Beans were an important source of protein throughout old and new world history, and still are today. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help farmers and those interested in agriculture in diagnosing many of the Bean diseases such as Fusarium wilt, Charcoal rot or ashy stem blight, Bacterial leaf spot and blight, Mung bean yellow mosaic virus, Cercospora leaf spot. The proposed expert system presents an overview of Bean diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Bean diseases diagnosis expert system was evaluated by Agricultural experts and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (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)

Abstract: Context: grapevine leaves are an important agricultural product that is used in many Middle Eastern dishes. The species from which the grapevine leaf originates can differ in terms of both taste and price. Method: In this study, we build a deep learning model to tackle the problem of grape leaf classification. 500 images were used (100 for each species) that were then increased to 10,000 using data augmentation methods. Convolutional Neural Network (CNN) algorithms were applied to build this model (...) specifically using the pre-trained model on top of the VGG16 architecture. Then, dense layers were added to classify the output of the Convolutional layers and classify outputs to the five classes (species) the leaf belonged to. Results: It was found that feature extraction without fine-tuning the convolutional layers yielded poor results, about 86% accuracy, while training the whole network along with some data preprocessing gave the best results, about 99.45% accuracy on the testing dataset. Conclusions: The proposed CNN model is an effective one for the problem of classification of grape leaf species. (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)

Risk Management Strategies and Investment Behaviors are considered important factors in the investing activities of the retail investors. This study seeks to determine the relationship between Risk Management Strategies and Investment Behavior of Generation Z retail investors. The study is a correlational research and purposive sampling was used to select the respondents for this study. Cochran’s formula was utilized to determine the total sample size or total number of respondents. Spearman’s Rank-Order Correlation was employed to assess the significant relationship of (...) Risk Management Strategies and Investment Behaviors. Based on the results, it showed that risk management strategies have a significant relationship with one or more of the investment behaviors. Risk avoidance has a significant relationship with confirmation bias. Risk reduction has a significant relationship with all of the investment behaviors such as overconfidence, loss-aversion, recency bias, and confirmation bias. Risk transfer shows a significant relationship with only loss-aversion and confirmation bias. And lastly, risk acceptance also has a significant relationship with all of the investment behaviors. This study recommends exploring other types of behavioral biases under cognitive bias and emotional bias to determine their correlation with risk management strategies. Also, broadening the sample size, demographic scope, and geographic scope of the study can improve the generalizability of the study and provide a more comprehensive understanding of the relationship between investment behavior and risk management strategies. The researchers also recommend to utilize interviews and focus group discussions to gain an in-depth understanding of the underlying values and attitudes concerning investment behavior. (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)

Corruptionism is the view that following physical death, the human being ceases to exist but their soul persists in the afterlife. Survivalism holds that both the human being and their soul persist in the afterlife, as distinct entities, with the soul constituting the human. Each position has its defenders, most of whom appeal both to metaphysical considerations and to the authority of St Thomas Aquinas. Corruptionists claim that survivalism violates a basic principle of any plausible mereology, while survivalists tend to (...) reject the principle, though without as much detail as one would like. In this paper I examine both the key exegetical issues and the mereological question, arguing that Aquinas cannot be shown to have supported the principle in question, and that the principle should be rejected on independent grounds. If correct, some key planks in support of survivalism are established, with others to await further examination. (shrink)

Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI has brought to the (...) field. However, the integration of AI also raises concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a comprehensive overview of these developments, offering insights into the future potential of AI in revolutionizing healthcare while addressing the ethical considerations that must accompany its adoption. The findings suggest that while AI holds the promise of transforming healthcare delivery, careful consideration of its implications is essential to ensure equitable and effective implementation. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into medical imaging represents a transformative shift in healthcare, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. This paper explores the application of AI technologies in the analysis of medical images, focusing on techniques such as convolutional neural networks (CNNs) and deep learning models. We discuss how these technologies are applied to various imaging modalities, including X-rays, MRIs, and CT scans, to enhance disease detection, image segmentation, and diagnostic support. Additionally, the (...) paper addresses the challenges faced in AI-driven medical imaging, including data quality, model interpretability, and ethical considerations. By examining recent advancements and real-world case studies, this paper provides insights into the current state of AI in medical imaging and its potential future directions. The findings highlight the ongoing evolution of AI technologies and their crucial role in advancing medical diagnostics and treatment strategies. (shrink)

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid (...) sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios. (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)

It has long been thought that observing distinctive traces of quantum gravity in a laboratory setting is effectively impossible, since gravity is so much weaker than all the other familiar forces in particle physics. But the quantum gravity phenomenology community today seeks to do the (effectively) impossible, using a challenging novel class of `tabletop' Gravitationally Induced Entanglement (GIE) experiments, surveyed here. The hypothesized outcomes of the GIE experiments are claimed by some (but disputed by others) to provide a `witness' of (...) the underlying quantum nature of gravity in the non-relativistic limit, using superpositions of Planck-mass bodies. We inspect what sort of achievement it would possibly be to perform GIE experiments, as proposed, ultimately arguing that the positive claim of witness is equivocal. Despite various sweeping arguments to the contrary in the vicinity of quantum information theory or given low-energy quantum gravity, whether or not one can claim to witness the quantum nature of the gravitational field in these experiments decisively depends on which out of two legitimate modelling paradigms one finds oneself in. However, by situating GIE experiments in a tradition of existing experiments aimed at making gravity interestingly quantum in the laboratory, we argue that, independently of witnessing or paradigms, there are powerful reasons to perform the experiments, and that their successful undertaking would indeed be a major advance in physics. (shrink)

Many profess a belief in the importance of school integration. In this essay I argue that the evidence tells against the sincerity of this belief.

Early Confucian “moral psychology” developed in the context of undoing reactive emotions in order to promote relationships of reciprocal recognition. Early Confucian texts diagnose the pervasiveness of reactive emotions under specific social conditions and respond with the ethical-psychological mandate to counter them in self-cultivation. Undoing negative affects is a basic element of becoming ethically noble, while the ignoble person is fixated on limited self-interested concerns and feelings of being unrecognized. Western ethical theory typically accepts equality and symmetry as conditions of (...) disentangling resentment; yet this task requires the asymmetrical recognition of others. Confucian ethics integrates a nuanced and realistic moral psychology with the normatively oriented project of self-cultivation necessary for dismantling complex negative emotions in promoting a condition of humane benevolence that is oriented toward others and achieved through self-cultivation. (shrink)

The critique of philosophical foundations of neoclassical economics is significant, because of its hegemony on economic education and research programs in Iran and worldwide academies. Due to an epistemological fallacy, methodological individualism plays a prominent role in the philosophy of economic; since the ontological aspects of economy are reduced to methodological considerations. Accordingly, critique of methodological individualism is regarded as the main entry for philosophical analysis of neoclassical economics. This article aims to analyze and appraise the methodological individualism from critical (...) realism’s point of view. Critical realism is taken as a stand for criticizing methodological individualism, because critical realism and neoclassical economics as a positive approach to economics, both share a realistic worldview. The critical realism’ critique of methodological individualism is bases on analyzing the concepts of formalism, syllogism, social atomism, isolation and reduction. From critical realism’ point of view because of unrealistic postulations of methodological individualism, neoclassical economics is turned to an abstract and deductive science such as mathematics with a low potentiality of explanation. (shrink)