Anydomainofscientificresearchhasitssustainingorthodoxy. Thatis, research on a problem, whether in astronomy, physics, or biology, is con- ducted against a backdrop of broadly shared assumptions. It is these as- sumptionsthatguideinquiryandprovidethecanonofwhatisreasonable-- of what "makes sense." And it is these shared assumptions that constitute a framework for the interpretation of research results. Research on the problem of how we see is likewise sustained by broadly shared assump- tions, where the current orthodoxy embraces the very general idea that the business of the visual system is to (...) create a detailed replica of the visual world, and that it accomplishes its business via hierarchical organization and by operatingessentiallyindependently of other sensorymodalitiesas well as independently of previous learning, goals, motor planning, and motor execution. (shrink)

In this review, we describe some of the central philosophical issues facing origins-of-life research and provide a targeted history of the developments that have led to the multidisciplinary field of origins-of-life studies. We outline these issues and developments to guide researchers and students from all fields. With respect to philosophy, we provide brief summaries of debates with respect to (1) definitions (or theories) of life, what life is and how research should be conducted in the absence of an accepted theory (...) of life, (2) the distinctions between synthetic, historical, and universal projects in origins-of-life studies, issues with strategies for inferring the origins of life, such as (3) the nature of the first living entities (the “bottom up” approach) and (4) how to infer the nature of the last universal common ancestor (the “top down” approach), and (5) the status of origins of life as a science. Each of these debates influences the others. Although there are clusters of researchers that agree on some answers to these issues, each of these debates is still open. With respect to history, we outline several independent paths that have led to some of the approaches now prevalent in origins-of-life studies. These include one path from early views of life through the scientific revolutions brought about by Linnaeus (von Linn.), Wöhler, Miller, and others. In this approach, new theories, tools, and evidence guide new thoughts about the nature of life and its origin.We also describe another family of paths motivated by a” circularity” approach to life, which is guided by such thinkers as Maturana & Varela, Gánti, Rosen, and others. These views echo ideas developed by Kant and Aristotle, though they do so using modern science in ways that produce exciting avenues of investigation. By exploring the history of these ideas, we can see how many of the issues that currently interest us have been guided by the contexts in which the ideas were developed. The disciplinary backgrounds of each of these scholars has influenced the questions they sought to answer, the experiments they envisioned, and the kinds of data they collected. We conclude by encouraging scientists and scholars in the humanities and social sciences to explore ways in which they can interact to provide a deeper understanding of the conceptual assumptions, structure, and history of origins-of-life research. This may be useful to help frame future research agendas and bring awareness to the multifaceted issues facing this challenging scientific question. (shrink)

Most studies on Nietzsche seldom associate him with the dialectic method. We readily think of Socrates, Hegel, and Marx when we hear of dialectic, but very rarely, if at all, of Nietzsche. To date, very few studies on Nietzsche have claimed that one of the German philosopher's underpinning philosophical methodologies in his literary oeuvre is the dialectic. This paper thus intends to show that Nietzsche has been employing the dialectic throughout his writings, especially in his treatment of the "free spirits"-a (...) recurring subject in his different compositions. To do this, I will first revisit the meaning of dialectic in Socrates, Hegel, and Marx and subsequently argue that in Nietzsche, a type of dialectic akin to Hegel's permeates his writings. In the next parts of this paper, I will discuss in-depth how for Nietzsche, the incarnation of the free spirits involves not just one, but a continuum of triple dialectic. I will argue that to become a free spirit, one must constantly apply the dialectics of (1) criticality and openness, (2) unlearning and relearning, and (3) overcoming and becoming. These dialectics, in my view, are the necessary conditions for any individual to be truly free. In this paper, I will importantly highlight that these dialectics run through Nietzsche's works starting from the early up to the final period of his literary productivity. (shrink)

“Probably Peirce’s best-known works are the first two articles in a series of six that originally were collectively entitled Illustrations of the Logic of Science and published in Popular Science Monthly from November 1877 through August 1878. The first is entitled ‘The Fixation of Belief’ and the second is entitled ‘How to Make Our Ideas Clear.’ In the first of these papers Peirce defended, in a manner consistent with not accepting naive realism, the superiority of the scientific method over other (...) methods of overcoming doubt and ‘fixing belief.’” — Robert Burch, “Charles Sanders Peirce,” entry in the Stanford Encyclopedia of Philosophy (2021 revision) -/- “Pragmatist epistemologies often explore how we can carry out inquiries in a self-controlled and fruitful way. (Where much analytic epistemology centres around the concept of knowledge, considered as an idealised end-point of human thought, pragmatist epistemology centres around the concept of inquiry, considered as the process of knowledge-seeking and how we can improve it.) So pragmatists often provide rich accounts of the capacities or virtues that we must possess in order to inquire well, and the rules or guiding principles that we should adopt. A canonical account is Peirce’s classic early paper ‘The Fixation of Belief‘. Here Peirce states that inquiry is a struggle to replace doubt with “settled belief“, and that the only method of inquiry that can make sense of the fact that at least some of us are disturbed by inconsistent beliefs, and will subsequently reflect upon which methods of fixing belief are correct is the Method of Science, which draws on the Pragmatic Maxim described above. This contrasts with three other methods of fixing belief: i) refusing to consider evidence contrary to one’s favored beliefs (the Method of Tenacity), ii) accepting an institution’s dictates (the Method of Authority), iii) developing the most rationally coherent or elegant-seeming belief-set (the A Priori Method).“ — Catherine Legg, “Pragmatism,” entry in the Stanford Encyclopedia of Philosophy (2021 revision). (shrink)

The problem of other minds has a distinguished philosophical history stretching back more than two hundred years. Taken at face value, it is an epistemological question: it concerns how we can have knowledge of, or at least justified belief in, the existence of minds other than our own. In recent decades, philosophers, psychologists, neuroscientists, anthropologists and primatologists have debated a related question: how we actually go about attributing mental states to others (regardless of whether we ever achieve knowledge or rational (...) justification in this domain). Until the mid-nineties, the latter debate – which sometimes goes under the name of the “mindreading” debate – was characterized by a fairly clear-cut opposition between two theoretical outlooks: “theory-theory” (TT) and “simulation theory” (ST). Theory-theorists typically argued that we attribute mental states to others on the basis of a “theory of mind” that is either constructed in early infancy and subsequently revised and modified (Gopnik 1996), or else is the result of maturation of innate mindreading “modules” (Baron-Cohen 1995). (shrink)

Iberian repertorios de los tiempos stemmed from Medieval almanacs and calendars. During the sixteenth century significant editorial, conceptual and material changes in repertorios incorporated astronomy, geography, chronology and natural philosophy. From De Li’s Repertorio (1492) to Zamorano’s Cronología (1585), the genre evolved from simple almanacs to more complex cosmological works which circulated throughout the Iberian-American world. This article claims that repertorios are a form of syncretic knowledge rather than “popular science” by relying on the concept of “knowledge in transit”. Elaborating (...) on this perspective, I present how repertorios ended up delivering a worldview from existing materials, a fact so far unnoticed by scholarship. At the same time, repertorios should not be considered an exclusively Iberian phenomenon, but the full scope of their nature as a form of syncretic knowledge should include their networks with migrants, indigenous, mestizos, and criollos across the Atlantic. In this sense, I try to trace the paths connecting productions in the Americas with Iberian repertorios. (shrink)

David Lewis presented Convention as an alternative to the conventionalism characteristic of early-twentieth-century analytic philosophy. Rudolf Carnap is well known for suggesting the arbitrariness of any particular linguistic convention for engaging in scientific inquiry. Analytic truths are self-consistent, and are not checked against empirical facts to ascertain their veracity. In keeping with the logical positivists before him, Lewis concludes that linguistic communication is conventional. However, despite his firm allegiance to conventions underlying not just languages but also social customs, he (...) pioneered the view that convening need not require any active agreement to participate. Lewis proposed that conventions arise from “an exchange of manifestations of a propensity to conform to a regularity” (87–8). In reasserting the conventional quality of languages and other practices resting on mutual expectations, Lewis comfortably works within the analytic tradition. Yet he also deviates from his predecessors because his conventionalist approach is comprehensively grounded in instrumentalism. Lewis adopts an extension of David Hume's desire-belief psychology articulated in rational choice theory. He develops his philosophy of convention relying on the highly formal mid-twentieth-century expected utility and game theories. This attempt to account for language and social customs wholly in terms of instrumental rationality has the implication of reducing normativity to preference satisfaction. Lewis’ approach continues in the trend of undermining normative political philosophy because institutions and practices arise spontaneously, without the deliberate involvement of agents. Perhaps Lewis’ Convention is best seen as a resurgent form of analytic philosophy, characterized by “a style of argument, hostility to [ambitious] metaphysics, focus on language, and the dominance of logic and formalization” that solves the dilemma of “combining the analytic inheritance…with normative concerns” by reducing normativity to individuals’ preference fulfillment consistent with the axioms of rational choice. (shrink)

ABSTRACTAccording to Nietzsche, both modern individuals and societies are pathologically fragmented. In this paper, I examine how he proposes we combat this affliction in his Untimely Meditations. I argue that he advocates a dual struggle involving both instrumental domination and eradication. On these grounds, I claim the following: 1. pace a growing number of commentators, we cannot categorise the species of conflict he endorses in the Untimely Meditations as agonistic; and 2. this conflict is better understood as analogous to the (...) species of struggle that Schopenhauer describes in his account of purposive organisation. (shrink)

Daoism and Environmental Philosophy explores ethics and the philosophy of nature in the Daodejing, the Zhuangzi, and related texts to elucidate their potential significance in our contemporary environmental crisis. This book traces early Daoist depictions of practices of embodied emptying and forgetting and communicative strategies of undoing the fixations of words, things, and the embodied self. These are aspects of an ethics of embracing plainness and simplicity, nourishing the asymmetrically differentiated yet shared elemental body of life of the myriad (...) things, and being responsively attuned in encountering and responding to things. These critical and transformative dimensions of early Daoism provide exemplary models and insights for cultivating a more expansive ecological ethos, environmental culture of nature, and progressive political ecology. This work will be of interest to students and scholars interested in philosophy, environmental ethics and philosophy, religious studies, and intellectual history. (shrink)

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)

Genes are thought to have evolved from long-lived and multiply-interactive molecules in the early stages of the origins of life. However, at that stage there were no replicators, and the distinction between interactors and replicators did not yet apply. Nevertheless, the process of evolution that proceeded from initial autocatalytic hypercycles to full organisms was a Darwinian process of selection of favourable variants. We distinguish therefore between Neo-Darwinian evolution and the related Weismannian and Central Dogma divisions, on the one hand, (...) and the more generic category of Darwinian evolution on the other. We argue that Hull’s and Dawkins’ replicator/interactor distinction of entities is a sufficient, but not necessary, condition for Darwinian evolution to take place. We conceive the origin of genes as a separation between different types of molecules in a thermodynamic state space, and employ a notion of reproducers. (shrink)

One critique of the early Daoist texts associated with Laozi and Zhuangzi is that they neglect the human and lack a proper sense of ethical personhood in maintaining the primacy of an impersonal dehumanizing “way.” This article offers a reconsideration of the appropriateness of such negative evaluations by exploring whether and to what extent the ethical sensibility unfolded in the Zhuangzi is aporetic, naturalistic, and/or religious. As an ethos of cultivating life and free and easy wandering by performatively enacting (...) openness and responsiveness to things in an immanent this-worldly context, the Zhuangzi is oriented toward the relational attunement of disposition and practice rather than toward metaphysics or religion in a transcendent sense. It consequently suggests an immanent anarchic ethics without principles while neither forgetting nor reifying the sacred and the mundane in its playful illumination of the biospiritual dynamics of cultivating life. (shrink)

Cognitive penetration of perception, broadly understood, is the influence that the cognitive system has on a perceptual system. The paper shows a form of cognitive penetration in the visual system which I call ‘architectural’. Architectural cognitive penetration is the process whereby the behaviour or the structure of the perceptual system is influenced by the cognitive system, which consequently may have an impact on the content of the perceptual experience. I scrutinize a study in perceptual learning that provides empirical evidence that (...) cognitive influences in the visual system produce neural reorganization in the primary visual cortex. The type of cognitive penetration can be synchronic and diachronic. (shrink)

I consider the intertextuality between Chinese and Western thought by exploring how images, metaphors, and ideas from the texts associated with Zhuangzi and Laozi were appropriated in early twentieth-century German philosophy. This interest in “Lao-Zhuang Daoism” encompasses a diverse range of thinkers including Buber and Heidegger. I examine how the problematization of utility, usefulness, and “purposiveness” in Zhuangzi and Laozi becomes a key point for their German philosophical reception; how it is the poetic character of the Zhuangzi that hints (...) at an appropriate response to the crisis and loss of meaning that characterizes technological modernity and its instrumental technological rationality; that is, how the “poetic” and “spiritual” world perceived in Lao-Zhuang thought became part of Buber's and Heidegger's critical encounter and confrontation with technological modernity; and how their concern with Zhuangzi does not signify a return to a dogmatic religiosity or otherworldly mysticism; it anticipates a this-worldly spiritual or poetic way of dwelling immanently within the world. (shrink)

På mange måter er dette en bok som blir utgitt alt for sent. Det er den første antologien av sitt slag, og retter fokus på kvinnelige metafysikere som virket i den tidlige moderne perioden (16. og tidlig 17. århundre). Redaktør Emily Thomas skriver i introduksjonen at til tross for at flere antologier om moderne metafysikk allerede finnes, er kvinnelige filosofer fortsatt underrepresentert og den filosofiske kanon mannsdominert. De ni filosofene som blir omtalt i totalt 13 kapitler var alle originale og (...) velkjente tenkere i sin samtid, men har blitt glemt i filosofihistoriens løp. (shrink)

Breast cancer remains a significant health concern worldwide, necessitating the development of effective diagnostic tools. In this study, we employ a neural network-based approach to analyze the Wisconsin Breast Cancer dataset, sourced from Kaggle, comprising 570 samples and 30 features. Our proposed model features six layers (1 input, 1 hidden, 1 output), and through rigorous training and validation, we achieve a remarkable accuracy rate of 99.57% and an average error of 0.000170 as shown in the image below. Furthermore, our investigation (...) identifies the most influential features in breast cancer diagnosis, shedding light on the key determinants of malignancy. Notably, we find that factors such as fractal dimension_se, symmetry worst, compactness_worst, symmetry_se, and smoothness_se play pivotal roles in distinguishing between benign and malignant cases. This research contributes to the ongoing efforts to enhance breast cancer diagnosis, providing valuable insights into feature importance and showcasing the potential of neural networks in medical applications. Our findings have implications for improving early detection and treatment strategies, ultimately contributing to improved patient outcomes. (shrink)

This essay examines the development of Reformed treatments of the affections in the period of early orthodoxy (ca. 1565-1640). I argue that discussion of the affections during this period grew within the broad framework of the Aristotelian psychology and certain polemical concerns initially established by early Reformed theologians. With the advent of Protestant universities and academies, Reformed ethicists and theologians treated the affections in greater detail, with a majority drawing on a generally Thomistic approach to the nature and (...) division of the affections, although not without a dissenting Scotistic minority. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with (...) a heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors (...) in identifying PD. Previous research with regards to predict the presence of the PD has shown accuracy rates up to 93% [1]; however, accuracy of prediction for small classes is reduced. The proposed design of the neural network system causes a significant increase of robustness. It is also has shown that networks recognition rates reached 100%. (shrink)

Carine Defoort, Mario Wenning, and Kai Marchal offer three ways of engaging with Chinese and Buddhist Philosophy in Early Twentieth-Century German Thought and the philosophical, hermeneutical, and historical issues it attempted to articulate and address.1 This work is historical with a contemporary philosophical intent: to reexamine a tumultuous contested epoch of philosophy’s past in order to reconsider its existing limitations and alternative possibilities. One dimension of this book is the investigation of constellations and entanglements of historical forces and concepts (...) for the sake of articulating critical models and alternatives for the present.2 In the book, I contested the modern self-image of philosophy... (shrink)

Archytas of Tarentum, a contemporary and associate of Plato, was a famous Pythagorean, mathematician, and statesman of Tarentum. Although his works are lost and most of the fragments attributed to him were composed in later eras, they nevertheless contain valuable information about his thought. In particular, the fragments of On Law and Justice are likely based on a work by the early Peripatetic biographer Aristoxenus of Tarentum. The fragments touch on key themes of early Greek ethics, including: written (...) and unwritten laws; freedom and self-sufficiency; moderation of the emotions and cultivation of virtues; equality and the competence of the majority to participate in government; criticism of “rule by an individual”; a theory of the ideal “mixed constitution”; distributive and corrective justice and punishment, and of the rule of law. The fragments also contain one of the only positive accounts of democracy in ancient Greek philosophy. (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)

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)

A new translation and edition of Aristotle's Protrepticus (with critical comments on the fragments) -/- Welcome -/- The Protrepticus was an early work of Aristotle, written while he was still a member of Plato's Academy, but it soon became one of the most famous works in the whole history of philosophy. Unfortunately it was not directly copied in the middle ages and so did not survive in its own manuscript tradition. But substantial fragments of it have been preserved in (...) several works by Iamblichus of Chalcis, a third century A.D. neo-Pythagorean philosopher and educator. On the basis of a close study of Iamblichus' extensive use and excerption of Aristotle's Protrepticus, it is possible to reconstruct the backbone of the lost work, and then to flesh it out with the other surviving reports about the work from antiquity (for example in Alexander of Aphrodisias and other ancient commentators on Aristotle). It is also possible to identify several papyrus fragments of the work, and many references and literary allusions in later authors, especially Cicero, whose own lost dialogue Hortensius was a defense of philosophy modeleld on Aristotle's. (shrink)

Abstract: Alzheimer's disease (AD) is one of the most common types of dementia. Symptoms appear gradually and end with severe brain damage. People with Alzheimer's disease lose the abilities of knowledge, memory, language and learning. Recently, the classification and diagnosis of diseases using deep learning has emerged as an active topic covering a wide range of applications. This paper proposes examining abnormalities in brain structures and detecting cases of Alzheimer's disease especially in the early stages, using features derived from (...) medical images. The entire brain image was passed on through the transmission of Xception learning architectures. The Convolutional Neural Network (CNN) was constructed with the help of separable convolution layers that It can automatically learn general features from imaging data for classification. (shrink)

Richard Baxter, one of the most famous Puritans of the seventeenth century, is generally known as a writer of practical and devotional literature. But he also excelled in knowledge of medieval and early modern scholastic theology, and was conversant with a wide variety of seventeenth-century philosophies. Baxter was among the early English polemicists to write against the mechanical philosophy of René Descartes and Pierre Gassendi in the years immediately following the establishment of the Royal Society. At the same (...) time, he was friends with Robert Boyle and Matthew Hale, corresponded with Joseph Glanvill, and engaged in philosophical controversy with Henry More. In this book, David Sytsma presents a chronological and thematic account of Baxter's relation to the people and concepts involved in the rise of mechanical philosophy in late-seventeenth-century England. -/- Drawing on largely unexamined works, including Baxter's Methodus Theologiae Christianae (1681) and manuscript treatises and correspondence, Sytsma discusses Baxter's response to mechanical philosophers on the nature of substance, laws of motion, the soul, and ethics. Analysis of these topics is framed by a consideration of the growth of Christian Epicureanism in England, Baxter's overall approach to reason and philosophy, and his attempt to understand creation as an analogical reflection of God's power, wisdom, and goodness, understood as vestigia Trinitatis. Baxter's views on reason, analogical knowledge of God, and vestigia Trinitatis draw on medieval precedents and directly inform a largely hostile, though partially accommodating, response to mechanical philosophy. (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)

Marsilius of Inghen’s account of imaginable impossibilities became paradigmatic in logic, semantics, and metaphysics throughout the later Middle Ages and well into the early modern period. The present study focuses on imaginable impossibilities in 14th-century logic, underlining the relevance of Marsilius of Inghen’s innovative approach through a comparison with the semantic accounts proposed by other mid-14th-century Parisian nominalists, namely John Buridan and Albert of Saxony. In particular, this paper tracks the specific issue of the admissibility of absolute impossibilities – (...) such as the chimera – within Marsilius of Inghen’s semantic analysis, proving that there is a sense in which the chimera is indeed treatable. The present study does so by analysing the issues involved in impossibilities on the levels of signification, supposition, and extended reference. In doing so it provides a clearer picture of the problems involved, where they emerge and why, as well as of the significance and range of Marsilius of Inghen’s approach. (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)

We’ll approach the notion of object in Wittgenstein’s Tractatus LogicoPhilosophicus (1921), initially from the so-called “substance argument”. The discourse about necessary conditions for the propositional sense cannot be treated in terms of truth or falsity in the Tractatus without resulting in a infinite regress. Such a situation is avoided by postulating a substance made up of simple objects, thus ensuring the assumed total determination of sense. Passages from the Notebooks (1914-1916) suggest that the idea of simples is given in the (...) ideia of logical analysis and is reached without the necessity of examples for objects. Another early Wittgenstein’s remarks provide examples for objects based on itens of phenomenical nature, such as a point in the visual field. An important analogy for the phenomenical approach for the object, which is found in the aphorisms 2.013-2.0131 of Tractatus, presents a problem for the absolute simplicity. This problem concerns the notion of form, a concept that attributes an ontological dependence to the object given by its essencial capacity of occurrence in atomic facts. The form of the objects results from an appropriation of the Context Principle used by Frege in his Grundlagen der Arithmetik (1884) and differs from the notions of pictorial form and logical form. The dependence assigned to the object through its form contradicts the independent subsistence established by its simplicity. The Tractarian object results from necessary demands for determination of propositional sense, reached by means of an clarificatory analysis which prioritizes the transformative and regressive modes of analysis. Simplicity and Context Principle are, under this perspective, rules of a syntax for a logical or significative use of language, which are reflected in the Tractarian ontology through the ideia that the logico-philosophical investigation of language reveals essencial aspects of the intimate structure of the world. (shrink)

Abstract: Breast cancer is reported to be the most common cancer type among women worldwide and it is the second highest women fatality rate amongst all cancer types. Notwithstanding all the progresses made in prevention and early intervention, early prognosis and survival prediction rates are still not sufficient. In this paper, we propose an ANN model which outperforms all the previous supervised learning methods by reaching 99.57 in terms of accuracy in Wisconsin Breast Cancer dataset. Experimental results on (...) Haberman’s Breast Cancer Survival dataset show the superiority of proposed method by reaching 88.24 % in terms of accuracy. The results are the best reported ones obtained from Artificial Neural Network using JNN environment without any preprocessing of the dataset. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with (...) a heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is used as a (...) technique to produce brain tumor detection and classification models using Magnetic Resonance Imaging (MRI) imaging for rapid and easy detection and identification of brain tumor. In this thesis, some ways and mechanisms will be reviewed to use deep learning techniques to produce a model for brain tumor detection. The goal is to find a good and effective way to detect brain tumor based on MRI to help the brain doctor in making decisions easily, accurately and rapidly. A recent report by the World Health Organization in February 2018 showed that the death rate from brain cancer or central nervous system (CNS) is the highest in the Asian continent. It is important to detect cancer early so that many of these lives can be saved. The model has been designed and implemented, including a dataset which consist of 10,000 images for brain tumor detection through the use of Deep learning algorithms based on neural networks. For testing, we have used our model, Inception, VGG16, MobileNet and ResNet models. The f-score accuracy we got for each model was as follows: Our model was 98.28, VGG16 was 99.86%, ResNet50 was 98.14%, MobileNet was 88,98%, and InceptionV3 was 99.88%. (shrink)

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)

This study sought to investigate the Human Resource and Management (HRM) Program of a preschool hereinafter referred to as the Early Years Learning Center (EYLC) in Mandaluyong City for purposes of this research study. This is a qualitative case study that delved particularly into the issue of employee retention, especially of seasoned teachers and staff of the subject learning center. It used the interview method to generate an in-depth analysis as it revisited its HRM Program. To triangulate the data (...) gathered, documents from websites and social media as well as artifacts were also utilized. There is a dearth of research on the Human Resource and Management Program in preschool education. Most studies are from India and China. In terms of the HRM Program in education, SWOT analysis was frequently used to help improve the program. There were negligible sources that used the balanced scorecard at the preschool level. Hence, a combination of the SWOT analysis and the Balanced Scorecard method were utilized - the SWOT Analysis to determine the problems the learning center faces vis-à-vis its HRM Program, and the balanced scorecard in the search for a solution or strategy to help solve the problem. Based on the study, these combined tools proved to be effective in revisiting the HRM Program of schools. After interviewing the Directress of EYLC, findings disclosed that to be able to improve the retention of employees in the learning center, the focus should be given to the hiring policies and procedures keeping in mind the job security of its targeted employees. This brings forward concerns over advertising schemes utilizing different venues and platforms as well as issues involving the provision of seasoned employees with a retirement package, comprehensive Health Management Organization (HMO), and a continuing professional development program. (shrink)

This review-essay considers the book by Moshe Halbertal, The Birth of Doubt: Confronting Uncertainty in Early Rabbinic Literature (Brown, 2020), and highlights certain pragmatist trajectories in the book and in its scholarly object - early rabbinic law. Inter alia, the middle rabbinic path between realism and nominalism is discussed.

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)

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)

There are many eye diseases but the most two common retinal diseases are Age-Related Macular Degeneration (AMD), which the sharp, central vision and a leading cause of vision loss among people age 50 and older, there are two types of AMD are wet AMD and DRUSEN. Diabetic Macular Edema (DME), which is a complication of diabetes caused by fluid accumulation in the macula that can affect the fovea. If it is left untreated it may cause vision loss. Therefore, early (...) detection of diseases is a critical importance. Our main goal is to help doctors detect these diseases quickly before reaching a late stage of the disease. In ophthalmology, optical coherence tomography (OCT) is critical for evaluating retinal conditions. OCT is an imaging technique used to capture high-resolution cross-sections of the retinas of patient. In this thesis, we review ways and techniques to use deep learning classification of the optical coherence tomography images of diseases from which a Retinal is suffering. The models used to improve patient care are (VGG-16, MobileNet, ResNet-50, Inception V3, and Xception) to reduce costs and allow fast and reliable analysis in large studies. The obtained results are encouraging, since the best model ResNet-50 reaching 96.21% of testing accuracy, which is very useful for doctors, to diagnose retinal diseases. (shrink)

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)

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality rate, and it induces other diseases. There are no obvious incidental effects during the starting periods of CKD, patients routinely disregard to see the sickness. Early disclosure of CKD enables patients to seek helpful treatment to improve the development of this disease. AI models can effectively assist clinical with achieving this objective on account of their fast and exact affirmation execution. In this appraisal, proposed a (...) Logistic relapse framework for diagnosing CKD. Proposed calculation like NAIVE BAYES , DECISION TREE , KSTAR , LOGISITIC , AND SVM and look at these calculation and get the most noteworthy precision .AI store, which has an enormous number of missing qualities. Missing characteristics are for the most part found, taking everything into account, clinical conditions since patients might miss a couple of assessments for various reasons. By separating the misjudgements delivered by the set up models and proposed a fused model that unites determined backslide and sporadic woods by using perceptron. (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)

This critical edition is the first ever publication of Hale's Of the Law of Nature, which previously existed only in manuscript form. After discussing and defining the law in general, Hale examines the natural law in particular, its discovery and divine origin, and how it relates to both biblical and human laws. Hale's treatise, which was likely written as part of his personal meditations, and was circulated among English lawyers after his death, reveals not only the close relationship between law (...) and theology in his thought, but also the importance of natural law to early modern legal thought. (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)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

Rita Widmaier and Malte-Ludolf Babin have done a valuable scholarly service for studies of the early modern European reception of China in collecting letters from Leibniz's extensive correspondence concerning China and translating them from the original Latin and French into German. This multi-lingual and chronologically organized edition gathers letters to and from Leibniz as well as supplementary texts composed between the years 1694 and 1716. It incorporates helpful clarificatory notes as well as an informative and lucid introduction.This edition focuses (...) on the exchanges between Leibniz and the Jesuit theologian and philosopher Barthélemy Des Bosses S.J. and other Jesuits in Europe who were in... (shrink)

Kim Iryŏp was raised and initially educated in a devout Methodist Christian environment under the strict guidance of her fideistic pastor father and her mother, who believed in female education. Both parents died while she was in her teens, and she questioned her Christian faith at an early age. She was one of the first Korean women to pursue higher education in Korea and Japan. Kim became a prolific poet and essayist, her writings engaging cultural and social issues, and (...) a leading figure of the feminist “new woman” movement in the 1920s, which promoted women’s self-awareness, freedom, and rights in the context of the complex intersection of traditional Korean... (shrink)