Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict effect of oxygen consumption of thylakoid membranes (chloroplasts) from spinach after inhibition. A number of factors were identified that may affect of oxygen consumption of thylakoid membranes from spinach. Factors such as curve, herbicide, dose, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some (...) inhibition of photosynthesis in farms. The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the effect of oxygen consumption of thylakoid membranes (chloroplasts) from spinach after inhibition with 100% accuracy. (shrink)

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities (...) on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes. (shrink)

Researchers of different calibres from phenomenology to posthumanism and beyond have outlined the processuality of the body and the environment (Alaimo 2010; Gendlin 2017), stressing the importance of changing the ontological presuppositions of the body-environment bond (Schoeller and Duanetz 2018: 131), since the existing models facilitate the alienation and intangibility of the environment, thus, leading to reduced societal awareness of the importance of environmental issues (Neimanis, Åsberg, Hedrén 2015: 73–74). In this article, I argue that in questions relating to food, (...) product-oriented ideologies dominate over process-oriented ethicality, in part, due to an embodied and lived ideology that can be best described via the concept of reactive nihilism and substance ontology. The article aims to demonstrate a necessity to rethink and recontextualize situated practices as alternatives to the prevalent ontogenealogies of the Global North. By problematizing the complimentary axis of reactive nihilism in food contexts and the genealogy of contemporary pop food “ethics”, I argue for a shift away from product-oriented ideologies and supplementation of the ontologies-we-live-by with situated alternative models. In the first part of the article, I use a genealogical approach, tracing the predominant meaning cluster encapsulated in Feuerbach’s famous expression “Man is what he eats” (Feuerbach 1846-1866, X: 5) in today’s contexts. To illustrate the leading discourses, I follow a Deleuzian understanding of the concept of “reactive nihilism” and contextualize food choices with the dominant understanding of the body in the Global North. With this discussion, I hope to provide context for the need to reconsider local ontologies as knowledge resources for the future. In the second part of the article, the framework present in the Global North is then complemented by a discussion of some local factors, to suggest ways in which global food philosophy and, particularly, lifestyle choices of food consumption could benefit from acknowledging the knowledge embedded in food consumption trends in Latvia. (shrink)

This study examined the degree to which students indulge in six prominent misconducts in Distance Education Institutions (DEIs). The study also quantified how class size, instructional delivery and institutional policies predict students’ indulgence in sharp practices using a general linear modelling approach. A sample of 871 participants was drawn from 1,742 final-year students across two DEIs in Nigeria. A structured questionnaire was used for data collection. The questionnaire had acceptable psychometric estimates of dimensionality, content and construct validity, as well as (...) reliability. Sharp practices such as cheating, plagiarism, falsification, impersonation, and arm-twisting were more prevalent in large classes, whereas only inducement was higher in small classes. Class size influenced students’ indulgence in sharp practices in DEIs. Instructional delivery and institutional policies negatively predicted students’ indulgence in the six sharp practices. Almost all the six sharp practices correlated positively and significantly, except for impersonation and inducement. Therefore, distance education students who cheat, plagiarize, arm-twist, falsify records, induce lecturers, and promote impersonation are more likely to indulge in other forms of sharp practices. It was concluded that large class sizes, poor instructional delivery, and poorly implemented institutional policies promote sharp practices among distance education students. Based on this conclusion, key policy and research implications are discussed. (shrink)

In this chapter I investigate the kinds of changes that psychiatric kinds undergo when they become explanatory targets of areas of sciences that are not “mature” and are in the early stages of discovering mechanisms. The two areas of science that are the targets of my analysis are cognitive neuroscience and cognitive neurobiology.

Abstract Heart Attack is the Cardiovascular Disease (CVD) which causes the most deaths among CVDs. We collected a dataset from Kaggle website. In this paper, we propose an ANN model for the predicting whether a patient has a heart attack or not that. The dataset set consists of 9 features with 1000 samples. We split the dataset into training, validation, and testing. After training and validating the proposed model, we tested it with testing dataset. The proposed model (...) reached an accuracy of 98.01% on the Heart Disease Dataset. (shrink)

In the quest to discover the neural bases of cognition, rigorous behavioral tools are equally as important as sophisticated tools for neural intervention. This paper evaluates several episodes in the development of a novel behavioral tool for rodent cognitive testing, the rodent touchscreen operant chamber. Using conceptual tools on offer in the philosophical literature on exploratory experimentation and control, I illuminate how optimization of this behavioral tool and an understanding of the causal knowledge it may be used to generate historically (...) has involved dynamic interplay between community-driven exploratory practices operating in parallel with causal hypothesis-driven research. (shrink)

Many neurodegenerative and neuropsychiatric diseases and other brain disorders are accompanied by impairments in high-level cognitive functions including memory, attention, motivation, and decision-making. Despite several decades of extensive research, neuroscience is little closer to discovering new treatments. Key impediments include the absence of validated and robust cognitive assessment tools for facilitating translation from animal models to humans. In this review, we describe a state-of-the-art platform poised to overcome these impediments and improve the success of translational research, the Mouse Translational Research (...) Accelerator Platform (MouseTRAP), which is centered on the touchscreen cognitive testing system for rodents. It integrates touchscreen-based tests of high-level cognitive assessment with state-of-the art neurotechnology to record and manipulate molecular and circuit level activity in vivo in animal models during human-relevant cognitive performance. The platform also is integrated with two Open Science platforms designed to facilitate knowledge and data-sharing practices within the rodent touchscreen community, touchscreencognition and mousebytes. Touchscreencognition includes the Wall, showcasing touchscreen news and publications, the Forum, for community discussion, and Training, which includes courses, videos, SOPs, and symposia. To get started, interested researchers simply create user accounts. We describe the origins of the touchscreen testing system, the novel lines of research it has facilitated, and its increasingly widespread use in translational research, which is attributable in part to knowledge-sharing efforts over the past decade. We then identify the unique features of MouseTRAP that stand to potentially revolutionize translational research, and describe new initiatives to partner with similar platforms such as McGill’s M3 platform. (shrink)

Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict temperature in the surrounding environment. A number of factors were identified that may affect temperature or humidity. Factors such as the nature of the surrounding place, proximity or distance from water surfaces, the influence of vegetation, and the level of rise or fall below sea level, among others, as input variables for the ANN model. A model based on multi-layer concept topology (...) was developed and trained using data from several regions in the surrounding environment. The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the temperature with 100% accuracy. (shrink)

Slippery slope arguments are frequently dismissed as fallacious or weak arguments but are nevertheless commonly used in political and bioethical debates. This paper gives an overview of different variants of the argument commonly found in the literature and addresses their argumentative strength and the interrelations between them. The most common variant, the empirical slippery slope argument, predicts that if we do A, at some point the highly undesirable B will follow. I discuss both the question which factors affect likelihood of (...) slippage and the relation between the strength of the prediction and the justificatory power of the argument. (shrink)

Fan culture has grown immensely over the past few years. People are constantly looking up to celebrities and personalities as role models for their fashion, identity, and success. During the stage of adolescence, it is normal for teenagers to admire well- known people and form fan attachments as part of their identity formation. However, this admiration of a specific media figure can be associated with one's personality, cognitive processes, and psychological well-being. Thus, the current study aims to investigate the correlation (...) between celebrity admiration and the self-esteem of 238 Filipino male teenagers. The research instruments, namely Celebrity Attitude Scale (CAS) and Rosenberg Self-Esteem Scale (RSES) were both utilized through google forms. Results have shown high scores on celebrity admiration and the normal range of self-esteem of the participants. Using Pearson’s r correlation coefficient, it was found that celebrity admiration and self-esteem of Filipino male teenagers have a significant relationship that exists in a negative direction. (shrink)

This article explores the negative framing of environmental concern in the context of food procurement and consumption, through the lens of the myth of Eden considering the ontological and genealogical aspects of the experienced exile from nature. The article first considers the theoretical context of the negative framing of food ethics. Demonstrating the consequences of the experience of food as abject, the article then goes on to discuss the exile from Eden as an explanatory myth for the perceptual inbetweenness of (...) humankind. The aim of the article is to outline the genealogical markers of the negative framing of food ethics via the discussion of the exile from Eden. In the context of a new materialist understanding of the nature–culture continuum, the article depicts the exile as a perceptual rather than ontological divide that does not reflect a factual human inbetweenness but mirrors the objectification of nature by stripping the flesh of its spirit. Such reenvisioning is thought to be a pivotal aspect for mitigating the affectual abjectivity of food and recapturing the factual entanglement of body–environment to enable affirmative environmental ethics. (shrink)

It seems like people have character traits that explain a good deal of their behavior. Call a theory character realism just in case it vindicates this folk assumption. Recently, Christian Miller has argued that the way to reconcile character realism with decades of psychological research is to adopt metaphysical reductivism about character traits. Some contemporary psychological theories of character and virtue seem to implicitly endorse such reductivism; others resist reduction of traits to finer-grained mental components or processes; and still others (...) remain silent on the metaphysics of traits. In this paper we argue that character realists do not have to, and in fact should not, be reductivists. We introduce a theoretical dilemma for reductivist character realism. Then we explain how nonreductivists can meet the standards for empirical adequacy laid out by Miller and others. Further, we argue, hylomorphic nonreductivism avoids the theoretical dilemma that threatens reductivism. It also fits nicely the major commitments of recent models of virtue in psychology. Thus, character realists should not be reductivists. (shrink)

In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases in (...) hospitals. The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the birth weight with 100% accuracy. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [BOU 99]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in [AMB 07], make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information (for a first outline [CHA 76, SCH 01]). The first section 1 introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two 2 discusses the intermediary but central notion of models. Section three 3, more exploratory, introduces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, (...) philosophers of science have started analyzing scientific representations in terms of fictionalization strategies. Many arguments center on a dyadic relation between the model and its target system, focusing on structural resemblances and “as if” scenarios. This chapter provides a different approach. It looks more closely at model building to analyze the interpretative strategies dealing with the representational limits of models. How do we interpret ambiguous elements in models? Moreover, how do we determine the validity of model-based inferences to information that is not an explicit part of a representational structure? I argue that the problem of ambiguous inference emerges from two features of representations, namely their hybridity and incompleteness. To distinguish between fictional and non-fictional elements in scientific models my suggestion is to look at the integrative strategies that link a particular model to other methods in an ongoing research context. To exemplify this idea, I examine protein modeling through X-ray crystallography as a pivotal method in biochemistry. (shrink)

As analysis of Kant’s account of virtue in the Lectures on Ethics shows that Kant thinks of virtue as a form of moral self-mastery or self-command that represents a model of self-governance he compares to an autocracy. In light of the fact that the very concept of virtue presupposes struggle and conflict, Kant insists that virtue is distinct from holiness and that any ideal of moral perfection that overlooks the fact that morality is always difficult for us fails to (...) provide an appropriate model of human virtue. No matter how morally good we are or become, virtue remains a disposition to do one’s duty from duty, out of necessitation by practical reason. Yet, even though finite rational beings require a power of self-constraint in accordance with the commands of duty to comply with the law (which we obey reluctantly), the virtuous agent displays a unified soul that is at peace. This picture of virtue uncovered from the Lectures on Ethics thus reveals the way in which Kant’s conception of virtue accords with his foundational commitments in his moral theory, while at the same time representing a more complex theory of moral character and a life lived in accordance with practical reason. (shrink)

Abstract: In this research, the Artificial Neural Network (ANN) model was developed and tested to predict the rate of treatment expenditure on an individual or family in a country. A number of factors have been identified that may affect treatment expenses. Factors such as age, grade level such as primary, preparatory, secondary or college, sex, size of disability, social status, and annual medical expenses in fixed dollars excluding dental and outpatient clinics among others, as input variables for the ANN (...) model. A model based on the multi-layer Perceptron topology was developed and trained using data on 5574 cases. The evaluation of the test data shows that the ANN model is capable of predicting correctly Medical Expenses. (shrink)

This essay proposes that Socrates practiced various spiritual exercises, including meditation, and that this Socratic practice of meditation was habitual, aimed at cultivating emotional self-control and existential preparedness. Contemporary research in neurobiology supports the view that intentional mental actions, including meditation, have a profound impact on brain activity, neuroplasticity, and help engender emotional self-control. This impact on brain activity is confirmed via technological developments, a prime example of how technology benefits humanity. Socrates attains the balanced emotional self-control that Alcibiades describes (...) in the Symposium because of the sustained mental effort he exerts that directly impacts his brain and his emotional and philosophical life. The essay concludes that Socratic meditative practices aimed at manifesting true dignity as human beings within the complexities of a technological world offer a promising model of self-care worthy of embracing today. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict (...) MPG_City with 97.50 % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

A recent and growing discussion in philosophy addresses the construction of models and their use in scientific reasoning by comparison with fiction. This comparison helps to explore the problem of mediated observation and, hence, the lack of an unambiguous reference of representations. Examining the usefulness of the concept of fiction for a comparison with non-denoting elements in science, the aim of this paper is to present reasonable grounds for drawing a distinction between these two kinds of representation. In particular, my (...) account will suggest a demarcation between fictional and non-fictional discourse as involving two different ways of interpreting representations. This demarcation, leading me to distinguish between fictional and non-fictional forms of enquiry, will provide a useful tool to explore to what extent the descriptions given by a model can be justified as making claims about the world and to what degree they are a consequence of the model’s particular construction. (shrink)

Abstract: In this paper an Artificial Neural Network (ANN) model, for predicting the Letters from twenty dissimilar fonts for each letter. The character images were, initially, based on twenty dissimilar fonts and each letter inside these twenty fonts was arbitrarily distorted to yield a file of 20,000 distinctive stimuli. Every stimulus was transformed into 16 simple numerical attributes (arithmetical moments and edge amounts) which were then ascended to be suitable into a range of numeral values from 0 to 15. (...) We naturally chose, arbitrarily, 1,000 distinctive stimuli for this research. We made certain that the scattering remnants the similar after selecting the one thousand stimuli. In this research, a neural network tool (Just NN) was used for the purpose of predicting to classify every of a huge number of black and white four-sided pixel displays as one of the 26 capital letters in the English language. (shrink)

Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict efficiency of antibiotics in treating various bacteria types. Attributes that were taken in account are: organism name, specimen type, and antibiotic name as input and susceptibility as an output. A model based on one input, one hidden, and one output layers concept topology was developed and trained using a data from Queensland government's website. The evaluation shows that the ANN model is (...) capable of correctly predicting the susceptibility of organisms to the antibiotics with 98% accuracy. -/- . (shrink)

Biomedical science has been remarkably successful in explaining illness by categorizing diseases and then by identifying localizable lesions such as a virus and neoplasm in the body that cause those diseases. Not surprisingly, researchers have aspired to apply this powerful paradigm to addiction. So, for example, in a review of the neuroscience of addiction literature, Hyman and Malenka (2001, p. 695) acknowledge a general consensus among addiction researchers that “[a]ddiction can appropriately be considered as a chronic medical illness.” Like other (...) diseases, “Once addiction has taken hold, it tends to follow a chronic course.” (Koob and La Moal 2006, p. ?). Working from this perspective, much effort has gone into characterizing the symptomology of addiction and the brain changes that underlie them. Evidence for involvement of dopamine transmission changes in the ventral tegmental area (VTA) and nucleus accumbens (NAc) have received the greatest attention. Kauer and Malenka (2007, p. 844) put it well: “drugs of abuse can co-opt synaptic plasticity mechanisms in brain circuits involved in reinforcement and reward processing”. Our goal in this chapter to provide an explicit description of the assumptions of medical models, the different forms they may take, and the challenges they face in providing explanations with solid evidence of addiction. <br>. (shrink)

In this paper, we propose a framework for fostering argumentative skills in a systematic way in Philosophy and Ethics classes. We start with a review of curricula and teaching materials from the German-speaking world to show that there is an urgent need for standards for the teaching and learning of argumentation. Against this backdrop, we present a framework for such standards that is intended to tackle these difficulties. The spiral-curricular model of argumentative competences we sketch helps teachers introduce the (...) relevant concepts and skills to students early on in their school career. The focus is on secondary schools, but the proposal can also be of use for learning and teaching in universities, especially in introductory classes. (shrink)

In the last decade alone, a growing body of preliminary evidence suggests that classic psychedelics (CPs) can rapidly and durably ameliorate symptoms and cognitive deficits associated with depression. However, the mechanisms by which CPs work in the brain are not well understood. Rodent translational research, in which experimental findings from rodents are translated to humans, is fundamental in achieving this goal. This chapter focuses on a representative subset of human and rodent studies investigating CPs for depression, including the various lines (...) of research that have been initiated to understand how they work. Our aim is to show that in addition to epistemic challenges that scientists face in translating findings from rodents to humans, there is also mismatch between experimental approaches used to investigate CPs in humans and rodents. We thus show current experimental practices are not conducive to mechanistic discovery. We end with a set of positive proposals to expedite the drive to translate CPs into effective treatments for depression. -/- Keywords: classic psychedelics, psychiatry, clinical trials, collaboration, extrapolation, major depressive disorder, open science, philosophy of science, rodent models, scientific practice, translation, validity . (shrink)

Crime is a serious social problem, but its causes are not exclusively social. There is growing consensus that explaining and preventing it requires interdisciplinary research efforts. Indeed, the landscape of contemporary criminology includes a variety of theoretical models that incorporate psychological, biological and sociological factors. These multi-disciplinary approaches, however, have yet to radically advance scientific understandings of crime and shed light on how to manage it. In this paper, using conceptual tools on offer in the philosophy of science in combination (...) with theoretical work represented in this special volume of Psychology, Crime and Law, I provide some perspective on why explanatory progress in criminology has remained elusive and evaluate some positive proposals for attaining it. -/- . (shrink)

Complex systems like literacy and numeracy emerge through multigenerational interactions of brains, behaviors, and material forms. In such systems, material forms – writing for language and notations for numbers – become increasingly refined to elicit specific behavioral and psychological responses in newly indoctrinated individuals. These material forms, however, differ fundamentally in things like semiotic function: language signifies, while numbers instantiate. This makes writing for language able to represent the meanings and sounds of particular languages, while notations for numbers are semantically (...) meaningful without phonetic specification. This representational distinction is associated with neurofunctional and behavioral differences in what neural activity and behaviors like handwriting contribute to literacy and numeracy. In turn, neurofunctional and behavioral differences place written representations for language and numbers under different pressures that influence the forms they take and how those forms change over time as they are transmitted across languages and cultures. (shrink)

We discuss two models of virtue cultivation that are present throughout the Republic: the self-mastery model and the harmony model. Schultz (2013) discusses them at length in her recent book, Plato’s Socrates as Narrator: A Philosophical Muse. We bring this Socratic distinction into conversation with two modes of intentional regulation strategies articulated by James J. Gross. These strategies are expressive suppression and cognitive reappraisal. We argue that that the Socratic distinction helps us see the value in cognitive reappraisal (...) and that the contemporary neurological research supports the wide range of attitudes toward the value of emotional experience that mirror those found in the Republic. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [Boulnois 1999]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in chapter 4, make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information. The first section introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two discusses the intermediary but central notion of models. Section three, more exploratory, intro-duces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

Creativity is often conceived in terms of insight, innovation, and invention realized through technical mastery and skill. Challenging this individualistic model are “inventions” like writing, something that surely gave no clue to the form it would ultimately take—script—or the ways in which it would reorganize behaviors and brains in the cognitive state known as literacy. Here writing is analyzed as a tool used collectively and collaboratively. Collective, collaborative use enabled the tool to become increasingly effective at eliciting specific behavioral (...) and psychological responses. Collective, collaborative use also subjected the tool to the combined force of the individual variability represented by different user and material combinations over time. Combined variability influenced tool form toward features reflecting both the average behavioral, physiological, and psychological capacities of the tool-using community and points of maximal usability. The result offers a new model of creativity, one based not on the individual but on collective, collaborative use and incremental change in behaviors and brains, materially accumulated and redistributed between generations. The model presents aspects of human innovation that escape the individualistic model by focusing on ordinary tool-using behaviors and sustained use within social groups as the critical elements. (shrink)

The Eleusinian Mysteries are religious rituals that include rites of initiation, purification, and revelation. The high point of these Mysteries is the moment when a priest reveals the secret of the Mysteries to the newly initiated. Plato frequently uses language and motifs from the Mysteries in his dialogues, yet Plato scholars have not paid much attention to this usage, and those who have done so have not found much philosophical significance in it. I argue that in explaining his epistemology in (...) three middle and late period dialogues Plato consciously and systematically uses Eleusinian Mystery motifs to convey the idea of a unique kind of knowledge. This immediate, direct, and incorrigible knowledge bursts upon Plato's initiates after they undergo preparatory processes such as purification through elenchus. I examine the Eleusinian Mystery motifs that Plato employs in the Ladder of Eros at Symposium 209e--212a, in the middle books of the Republic, including the Myth of the Cave at Republic 509a--518d, and in the Myth of the Soul at Phaedrus 246a--253c, and I argue that Plato finds these Mystery elements useful for two reasons. First, in many cases before an individual can come to know a form he must go through certain conditioning and transformatory processes to prepare him for it, and motifs from the Mysteries help Plato to describe these processes. Second, knowledge of a form is different from other kinds of knowledge, and the motif of the visual revelation of the epopteia helps him to express the direct, unmediated contact that constitutes knowledge of a form. ;The structure of the dissertation is as follows. In chapter one I present background information concerning the stages and events of the Mysteries. I consider the purpose and effects of initiation into the Eleusinian Mysteries, paying special attention to the preparatory rituals. In chapter two I present a general discussion of certain aspects of Plato's epistemology and show how Plato employs the five Mystery motifs of progressing through a sequence of stages, purification, being led by a mystagogos, experiencing the epopteia, and achieving eudaimonia in order to explicate these aspects. In chapter three I consider the specifics of Plato's use of Mystery terminology in the Symposium. And finally, in an Appendix, I argue that Plato has a model of knowledge by acquaintance, since I assert in chapters two and three that Plato uses the Mystery theme of an epopteia to express features of this model. (shrink)

To develop rehabilitative treatment programs for persons who have committed crimes, correctional psychologists build theoretical structures that weld theoretical ideas about the causes of criminal behavior, theoretical perspectives about appropriate targets for correctional intervention and normative assumptions about crime and the aims of correctional intervention. To differentiate the tri-partite theoretical structure with which correctional program designers' work, Ward and Durrant (2021) introduce the metatheoretical concept of “practice frameworks”. In this paper, I describe and evaluate this concept, situating my analysis within (...) the broader contexts of philosophical work on scientific theories and models and metatheoretical work on the structure of explanatory and intervention theories in correctional psychology. (shrink)

Several quantitative studies (e.g. Kidd & Castano, 2013a; Djikic et al., 2013) have shown a positive correlation between literary reading and empathy. However, the literary nature of the stimuli used in these studies has not been defined at a more detailed, stylistic level. In order to explore the stylistic underpinnings of the hypothesized link between literariness and empathy, we conducted a qualitative experiment in which the degree of stylistic foregrounding was manipulated. Subjects (N = 37) read versions of Katherine Mansfield's (...) 'The Fly', a short story rich in foregrounding, while marking striking and evocative passages of their choosing. Afterwards, they were asked to select three markings and elaborate on their experiences in writing. One group read the original story, while the other read a 'non-literary' version, produced by an established author of suspense fiction for young adults, where stylistic foregrounding was reduced. We found that the non-literary version elicited significantly more (p < 0.05) explicitly empathic responses than the original story. This finding stands in contradiction to widely accepted assumptions in recent research, but can be assimilated in alternative models of literariness and affect in literary reading (e.g. Cupchik et al., 1998). We present an analysis of the data with a view to offering more than one interpretation of the observed effects of stylistic foregrounding. (shrink)

Cet article considère la question de la légitimité du financement public des écoles dites ethnoreligieuses à la lumière du modèle interculturaliste de citoyenneté. La première section dresse un bref portrait historique du débat autour de cette question tel qu’il s’est présenté au Québec. Ensuite, elle explique en quoi cette problématique révèle une tension inhérente aux principes clés de l’interculturalisme. La seconde partie propose une critique de l’approche standard pour aborder l’enjeu du financement public des écoles ethnoreligieuses et défend une approche (...) alternative fondée sur une vision plus globale des finalités politiques de l’interculturalisme. La troisième et dernière section propose, en s’appuyant sur le modèle alternatif défendu, quatre mesures régulatrices visant à répondre aux difficultés que posent les politiques de financement public des écoles ethnoreligieuses. (shrink)

In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases in (...) hospitals. The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the birth weight with 100% accuracy. (shrink)

Four perspectives on numerical origins are examined. The nativist model sees numbers as an aspect of numerosity, the biologically endowed ability to appreciate quantity that humans share with other species. The linguistic model sees numbers as a function of language. The embodied model sees numbers as conceptual metaphors informed by physical experience and expressed in language. Finally, the extended model sees numbers as conceptual outcomes of a cognitive system that includes material forms as constitutive components. If (...) numerical origins are to be found, each perspective must address one or more critical questions that will require working across discipline boundaries. (shrink)

Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases (...) in hospitals. The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the birth weight with 100% accuracy. (shrink)

Cognitive archaeology is a relatively new interdisciplinary science that uses cognitive and psychological models to explain archaeological artifacts like stone tools, figurines, and art. Edited by cognitive archaeologist Karenleigh A. Overmann and psychologist Frederick L. Coolidge, Squeezing Minds From Stones is a collection of essays, from both early pioneers and 'up and coming' newcomers in the field, that addresses a wide variety of cognitive archaeology topics, including the value of experimental archaeology, primate archaeology, the intent of ancient tool makers, and (...) how they may have lived and thought. (shrink)

Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to (...) predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3%. (shrink)

Teachers, who are the most important factor of education, have the great task of inculcating to the learners the knowledge, skill and behavior needed in facing the everchanging society. Thus, the teachers’ task to transmit knowledge requires them to be a highly competent learning facilitators while remaining as a role model soaring with moral integrity. This means that a school must not only have educationally qualified teachers but teachers who are truly dedicated and committed to serve the public specially (...) the learners entrusted to their care. This study is focused to determine teachers’ competency and learners’ performance in English of grade two teachers in Manila particularly in District V. Likewise, the benefits derived from the study hope to provide a springboard to design an intervention scheme towards gearing effort into improving the quality education. (shrink)

Recent empirical work on non-philosophers’ intuitions about epistemic normativity reveals patterns that cannot be fully accounted for by direct epistemic consequentialism. On the basis of these results, one might picture participants as “epistemic deontologists.” We present the results of two new experiments that support a more nuanced picture. We examine intuitions about guesses and hypotheses, and about beliefs. Our results suggest a two-factor model of intuitions, wherein both consequentialist and non-consequentialist considerations affect participants’ judgments about epistemic permissibility.

In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established (...) and trained using data set which its title is “primary tumor” and was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia Test data evaluation shows that the ANN model is able to correctly predict the tumor category with 76.67 % accuracy. (shrink)

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on (...) a dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%. (shrink)

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

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

The objective of Working Group 4 of the COST Action NET4Age-Friendly is to examine existing policies, advocacy, and funding opportunities and to build up relations with policy makers and funding organisations. Also, to synthesize and improve existing knowledge and models to develop from effective business and evaluation models, as well as to guarantee quality and education, proper dissemination and ensure the future of the Action. The Working Group further aims to enable capacity building to improve interdisciplinary participation, to promote knowledge (...) exchange and to foster a cross-European interdisciplinary research capacity, to improve cooperation and co-creation with cross-sectors stakeholders and to introduce and educate students SHAFE implementation and sustainability. To enable the achievement of the objectives of Working Group 4, the Leader of the Working Group, the Chair and Vice-Chair, in close cooperation with the Science Communication Coordinator, developed a template to map the current state of SHAFE policies, funding opportunities and networking in the COST member countries of the Action. On invitation, the Working Group lead received contributions from 37 countries, in a total of 85 Action members. The contributions provide an overview of the diversity of SHAFE policies and opportunities in Europe and beyond. These were not edited or revised and are a result of the main areas of expertise and knowledge of the contributors; thus, gaps in areas or content are possible and these shall be further explored in the following works and reports of this WG. But this preliminary mapping is of huge importance to proceed with the WG activities. In the following chapters, an introduction on the need of SHAFE policies is presented, followed by a summary of the main approaches to be pursued for the next period of work. The deliverable finishes with the opportunities of capacity building, networking and funding that will be relevant to undertake within the frame of Working Group 4 and the total COST Action. The total of country contributions is presented in the annex of this deliverable. (shrink)

Abstract: The sinking of the RMS Titanic in 1912 remains a poignant historical event that continues to captivate our collective imagination. In this research paper, we delve into the realm of data-driven analysis by applying Artificial Neural Networks (ANNs) to predict the chances of survival for passengers aboard the Titanic. Our study leverages a comprehensive dataset encompassing passenger information, demographics, and cabin class, providing a unique opportunity to explore the complex interplay of factors influencing survival outcomes. Our ANN-based predictive (...) model achieved an accuracy rate of 78%, shedding light on the underlying patterns within the data. However, this paper underscores the multifaceted nature of survival prediction and acknowledges several challenges. These include missing data imputation, feature engineering, and the inherent noise within historical datasets. We further discuss the importance of model evaluation metrics, showcasing not only accuracy but also precision, recall, and F1-score as essential indicators of predictive performance. The research paper meticulously outlines the architecture of the ANN model, emphasizing the key hyperparameters, activation functions, and regularization techniques employed in model development. Additionally, we address ethical considerations related to data handling and potential biases within the dataset. While our achieved accuracy is a notable achievement, this study emphasizes the importance of interpreting the results with due caution. It underscores the need for a holistic perspective that considers the practical implications of false positives and false negatives, especially in the context of a disaster scenario. In conclusion, this research contributes to our understanding of survival prediction in historical events like the Titanic disaster using modern machine learning techniques. It calls for further exploration and refinement of predictive models, with a focus on enhancing the interpretability and generalizability of such models to real-world applications. (shrink)

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the (...) dynamics of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network architecture, consisting of three (...) layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)