In this book, Michael Arbib, a researcher in artificial intelligence and brain theory, joins forces with Mary Hesse, a philosopher of science, to present an integrated account of how humans 'construct' reality through interaction with the social and physical world around them. The book is a major expansion of the Gifford Lectures delivered by the authors at the University of Edinburgh in the autumn of 1983. The authors reconcile a theory of the individual's construction of reality as a network (...) of schemas 'in the head' with an account of the social construction of language, science, ideology and religion to provide an integrated schema-theoretic view of human knowledge. The authors still find scope for lively debate, particularly in their discussion of free will and of the reality of God. The book integrates an accessible exposition of background information with a cumulative marshalling of evidence to address fundamental questions concerning human action in the world and the nature of ultimate reality. (shrink)

To commemorate 40 years since the founding of the Journal of Business Ethics, the editors in chief of the journal have invited the editors to provide commentaries on the future of business ethics. This essay comprises a selection of commentaries aimed at creating dialogue around the theme Business versus Ethics?. The authors of these commentaries seek to transcend the age-old separation fallacy :409–421, 1994) that juxtaposes business and ethics/society, posing a forced choice or trade off. Providing a contemporary take on (...) the classical question “if it’s legal is it ethical?”, David Hess explores the role of the law in promoting or hindering stakeholder-oriented purpose and governance structure. Jeffrey Harrison encourages scholars to move beyond the presupposition that businesses are either strategic or ethical and explore important questions at the intersection of strategy and ethics. The proposition that business models might be inherently ethical or inherently unethical in their design is developed by Sheila Killian, who examines business systems, their morality, and who they serve. However, the conundrum that entrepreneurs are either lauded for their self-belief and risk-taking, or loathed for their self-belief and risk-taking, is discussed by M. Tina Dacin and Julia Roloff using the metaphor of taboos and totems. These commentaries seek to explore positions that advocate multiplicity and tensions in which business ethics is not either/or but both. (shrink)

Recent application of theories of embodied or grounded cognition to the recognition and interpretation of facial expression of emotion has led to an explosion of research in psychology and the neurosciences. However, despite the accelerating number of reported findings, it remains unclear how the many component processes of emotion and their neural mechanisms actually support embodied simulation. Equally unclear is what triggers the use of embodied simulation versus perceptual or conceptual strategies in determining meaning. The present article integrates behavioral research (...) from social psychology with recent research in neurosciences in order to provide coherence to the extant and future research on this topic. The roles of several of the brain's reward systems, and the amygdala, somatosensory cortices, and motor centers are examined. These are then linked to behavioral and brain research on facial mimicry and eye gaze. Articulation of the mediators and moderators of facial mimicry and gaze are particularly useful in guiding interpretation of relevant findings from neurosciences. Finally, a model of the processing of the smile, the most complex of the facial expressions, is presented as a means to illustrate how to advance the application of theories of embodied cognition in the study of facial expression of emotion. (shrink)

This essay explores the validity of Gregory Boyd’s open theistic account of the nature of the future. In particular, it is an investigation into whether Boyd’s logical square of opposition for future contingents provides a model of reality for free will theists that can preserve both bivalence and a classical conception of omniscience. In what follows, I argue that it can.

Evolutionary models of human cooperation are increasingly emphasizing the role of reputation and the requisite truthful “gossiping” about reputation-relevant behavior. If resources were allocated among individuals according to their reputations, competition for resources via competition for “good” reputations would have created incentives for exaggerated or deceptive gossip about oneself and one’s competitors in ancestral societies. Correspondingly, humans should have psychological adaptations to assess gossip veracity. Using social psychological methods, we explored cues of gossip veracity in four experiments. We found that (...) simple reiteration increased gossip veracity, but only for those who found the gossip relatively uninteresting. Multiple sources of gossip increased its veracity, as did the independence of those sources. Information that suggested alternative, benign interpretations of gossip decreased its veracity. Competition between a gossiper and her target decreased gossip veracity. These results provide preliminary evidence for psychological adaptations for assessing gossip veracity, mechanisms that might be used to assess veracity in other domains involving social exchange of information. (shrink)

Research on the relationship between context and facial expressions generally assumes a unidirectional effect of context on expressions. However, according to the model of the meaning of emotion expressions in context the effect should be bidirectional. The present research tested the effect of emotion expression on the interpretation of scenes. A total of 380 participants either rated facial expressions with regard to the likely appraisal of the eliciting situation by the emoter, appraised the scenes alone or appraised scenes shown (...) together with the expressions they supposedly elicited. The findings strongly supported the MEEC. When a scene was combined with an expression signalling a situation that is undesirable, or high in locus of control or sudden, the participants appraised the scene correspondingly. Thus, the meaning of scenes is malleable and affected by the way that people are seen to react to them. (shrink)

Powerful transformer models based on neural networks such as GPT-4 have enabled huge progress in natural language processing. This paper identifies three challenges for computer programs dealing with metaphors. First, the phenomenon of Twice-Apt-Metaphors shows that metaphorical interpretations do not have to be triggered by syntactical, semantic or pragmatic tensions. The detection of these metaphors seems to involve a sense of aesthetic pleasure or a higher-order theory of mind, both of which are difficult to implement into computer programs. Second, the (...) contexts relative to which metaphors are interpreted are not simply given but must be reconstructed based on pragmatic considerations that can involve presuppositional pretence. If computer programs cannot produce or understand such a form of pretence, they will have problems dealing with certain metaphors. Finally, adequately interpreting and reacting to some metaphors seems to require the ability to have internal, first-personal experiential and affective states. Since it is questionable whether computer programs have such mental states, it can be assumed that they will have problems with these kinds of metaphors. (shrink)

The term information has become a universal and omnipresent keyword in almost all areas of our modern world—be it in science or society in general. This is not only obvious from the naming of whole scientific branches like Information Theory, Information Science or Informatics but even more from common speaking—characterising our present time and society as information age viz. information society. However, what information might mean, is by no means clear and there is a wide range of interpretations covering, among (...) others, its technical, communicational, educational, mental, and scientific aspects. But is the use of the same term justified when adopted in Biology, Physics, Archaeology, Law, Communication Technology, and Informatics (to list just a few of the involved scientific branches) or do its different uses at least have some common characteristics—some sort of common denominator? Is information natural, e.g. manifesting itself as a material phenomenon residing in organisms, stars, atoms, or genes, or is it just a cultural product of human communication, thinking, and interpretation? In this article, we try to clarify some of the most important interpretations, discuss and contrast them with the Informatics point of view. Interpretations range from taking information as material, transferable signals (following Shannon’s Information Theory or the genetic approaches), treating it as a sign (following a semiotic approach), as a commercial product (now common in Web-based Information Business) to considering it a pure mental phenomenon bound to humans or human-like individuals or even to groups and societies. Based on these interpretations, we shall throw a critical glance on current trends in human science and society—focusing on the now popular concept of information society —and then derive some theses and guidelines for further research escorting the growth and dispersal of information technology. As it will turn out, an information society which defines itself through the number of computers, internet connections and network links is based on a very narrow, techno-centric concept of information. However, a reflection on the educational and cultural aspects of information might lead to a better-qualified society consisting of responsible and critical citizens. (shrink)

The topic of the article is St. Anselm’s ontological argument. This is not, however, an attempt to interpret or evaluate the proof itself, but rather to place it in a broader theoretical context. The proper aim of the article is to present a proposal of a theory of metaphysics within which this proof could be considered and acknowledged as correct. This proposal is presented in two steps: in the first the author presents a sketch of a formal theory of being (...) and properties; in the second he offers a sketch of a model that is appropriate for this theory. His intention is also that the proposed theory be as close as possible to Anselm’s theory as it is found in his writings. He also considers Anselm’s position in the matter of universals and the suggested nominalist interpretation of his metaphysics. The final part of the article shows Anselm’s originality, especially as regards his method of reasoning. (shrink)

Logic, Methodology, and the Philosophy of Science, the Proceedings of the 1960 International Congress at Stanford, is heavily weighted towards technical problems of logic, foundations of mathematics, and the special sciences, especially psychology, economic models, and structural linguistics, with little discussion of general problems of the philosophy of science. Problems about the idealization involved in the relation of theories to the world become problems about probabilistic models at various levels of abstraction ; induction becomes a problem in decision theory ; (...) language becomes the subject-matter of formalized syntactics, and so on. There is nothing in the least undesirable about these inquiries in a Philosophy of Science Congress, but there is a danger that, if they are not balanced by more informal discussions, real points of dispute are missed, or decided over-hastily in the brief preliminaries of formalization. The philosopher's job ought sometimes to be the more irritating one of returning to these points of dispute; a job which is well done in some of the contributions to this volume, but one could wish to find it being done in more. In what follows I shall have to restrict myself to commenting on only a handful of these more philosophical papers. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Remixing the Classroom: Toward an Open Philosophy of Music Education by Randall Everett AllsupJuliet HessRandall Everett Allsup, Remixing the Classroom: Toward an Open Philosophy of Music Education (Bloomington, IN: Indiana University Press, 2016).As a leading voice in music education, Randall Allsup works continually to reconceptualize music education toward democratic and socially just praxis.1 He routinely challenges the field to become self-conscious of practices that limit forward movement, providing (...) powerful critiques2 and urging music education toward open possibilities.3 Remixing the Classroom: Toward an Open Philosophy of Music Education is work that will shift our field. His comprehensive philosophy of music education looks, longs, for moral openings4 through which twenty-first-century music education may become a space of possibility. His writing interweaves stories and theory toward what he calls an "open philosophy," drawing upon the ideas of John Dewey, Maxine Greene, and Roland Barthes. Allsup introduces stories of Dapper Dan, Jiro Ono, Kafka, Atul Gawande, and the Orpheus Orchestra in New York City to illustrate powerful points about current and possible paradigms of music education.Chapter 1, "Toward Open Encounters," discusses the making and breaking of the law (tradition) and explores how tradition and the Master-Apprentice model restrict what is possible in music education. Allsup explores the nature of music education and the limitations it places upon its participants. Chapter 2, "Music-Teacher Quality and Expertise," asks fundamental questions of our field and [End Page 100] explores and challenges the "place and purpose of public schooling in a democratic society."5 Allsup speaks to the function of education and critiques music education. Chapter 3, "learning in laboratories," puts forward a Deweyan laboratory model in which a museum is at the center of the school with learning laboratories situated around it. He explores what this structural fluidity might enable and develops notions of lawmaking and lawbreaking, extending possibilities of the open encounter. The final chapter, "looking, Longing, for Moral Openings," calls on music educators to embrace a more open music education paradigm. Allsup draws upon Greene to challenge music education to move "from the predictable to the possible."6 He puts forward the Orpheus Orchestra, a conductorless orchestra, as one possibility.I situate myself as an anti-racist, anti-colonial, feminist scholar rooted in anti-oppression scholarship.7 locating my review through this framework, I elaborate upon what I see as the major strengths and limitations of this work, drawing upon Judith Butler8 and postcolonial theory. significantly, Allsup's book calls upon music education to "give an account of [it]self" and promotes a self-consciousness crucial for our field in the age of high stakes accountability measures. I contend that he provides a music education philosophy for what stuart Hall terms the "postcolonial moment"9 and ultimately positions music education as a space of possibility. Alongside these strengths, I offer a challenge toward what I view as the open possibilities of closed forms and a critique of his "pedagogy of travel and surprise."Judith Butler points to the impossibility of giving an account of oneself. she notes,I speak as an 'I,' but do not make the mistake of thinking that I know precisely all that I am doing when I speak in that way. I find that my very formation implicates the other and me, that my own foreignness to myself is, paradoxically, the source of my ethical connection with others.10Butler notes the subject's "partial opacity to [her]self."11 In Remixing the Classroom, Allsup calls upon music educators to account for the practices and traditions continually reinscribed in the field. He poses challenging but fundamental questions in the work in music education, asking readers to consider what they do unconsciously. Butler asserts we can never fully account for ourselves. Allsup challenges the field to try, pushing music educators to face hard truths and limitations of what music education is and has been. In chapter 1, for example, he argues:To call a studying musician "unmusical" is to extinguish a light; it is to act as if the future is certain and that human potential is somehow fixed. It is to act [End Page 101... (shrink)

Cramer et al.'s account of comorbidity comes with a substantive philosophical view concerning the nature of psychological disorders. Although the network account is responsive to problems with extant approaches, it faces several practical and conceptual challenges of its own, especially in cases where the individual differences in network structures require the analysis of intra-individual time-series data.

Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in (...) predicting brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data. (shrink)

Despite the lack of invariance problem (the many‐to‐many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side‐stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real‐world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to (...) provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two‐layer network that borrows one element from ASR, long short‐term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human‐like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR. (shrink)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given (...) that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description—four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity, to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene–environment interactions. We argue that gene–behavior associations can inform cognitive theory with respect to effect size, specificity, and timing. The model demonstrates a means by which researchers can undertake multiscale modeling with respect to cognition and develop highly specific and complex hypotheses across multiple levels of description. (shrink)

In this work, I discuss the role of Husserl’s phenomenology in Paolo Parrini’s positive philosophy. In the first section, I highlight the presence of both empiricist and constructivist elements in Parrini’s anti-foundationalist and anti-absolutist conception of knowledge. In the second section, I stress Parrini’s acknowledgement of the crucial role of phenomenology in investigating the empirical basis of knowledge, thanks to its analysis of the relationship between form and matter of cognition. In the third section, I point out some lines of (...) development of the phenomenological form of empirical realism as revealed in Parrini’s reflection, through a comparison of Husserl’s genetic phenomenology, Mary Hesse’s network model and the tradition of neutral monism. (shrink)

The balance between births and deaths in an age-structured population is strongly influenced by the spatial distribution of sub-populations. Our aim was to describe the demographic process of a fish population in an hierarchical dendritic river network, by taking into account the possible movements of individuals. We tried also to quantify the effect of river network changes (damming or channelling) on the global fish population dynamics. The Salmo trutta life pattern was taken as an example for.We proposed a (...) model which includes the demographic and the migration processes, considering migration fast compared to demography. The population was divided into three age-classes and subdivided into fifteen spatial patches, thus having 45 state variables. Both processes were described by means of constant transfer coefficients, so we were dealing with a linear system of difference equations. The discrete case of the variable aggregation method allowed the study of the system through the dominant elements of a much simpler linear system with only three global variables: the total number of individuals in each age-class. (shrink)

Modeling dynamic networks has attracted much interest in recent years, which helps understand networks’ behavior. Many works have been dedicated to modeling discrete-time networks, but less work is done for continuous-time networks. Point processes as powerful tools for modeling discrete events in continuous time have been widely used for modeling events over networks and their dynamics. These models have solid mathematical assumptions, making them interpretable but decreasing their generalizability for different datasets. Hence, neural point processes were introduced that don’t have (...) strong assumptions on generative functions. However, these models can be impractical in the case of a large number of event types. This research presents a comparative study of different point process models for continuous-time networks. Furthermore, a previously introduced neural point process model is applied for modeling network interactions. In this work, network clustering is used for specifying interaction types. These methods are compared using different synthetic and real-world datasets, and their efficiency is evaluated on these datasets. The experiments represent that each model is appropriate for a group of datasets. In addition, the effect of clustering on results is discussed, and experiments for different clusters are presented. (shrink)

Models of gene regulatory networks have proven useful for understanding many aspects of the highly complex behavior of biological control networks. Randomly generated non-Boolean networks were used in experimental simulations to generate data on dynamic phenotypes as a function of several genotypic parameters. We found that predictive relationships between some phenotypes and quantitative genotypic parameters such as number of network genes, interaction density, and initial condition could be derived depending on the strength of the topological genotype on specific phenotypes. (...) We quantitated the strength of the topological genotype effect on a number of phenotypes in multi-gene networks. For phenotypes with a low influence of topological genotype, derived and empirical relationships using quantitative genotype parameters were accurate in phenotypic outcomes. We found a number of dynamic network properties, including oscillation behaviors, that were largely dependent on genotype topology, and for which no such general quantitative relationships were determinable. It remains to be determined if these results are applicable to biological gene regulatory networks. (shrink)

Mary Hesse's well-known work on models and analogies gives models a creative role to play in science, which rests on developing certain analogical properties considered neutral between the two fields. Case study material from Irving Fisher's work (The Purchasing Power of Money, 1911), in which he used analogies to construct models of monetary relations and the monetary system, highlights certain omissions in Hesse's account. The analysis points to the importance of taking account of the negative properties in the analogies and (...) to certain differences between "ready-made" analogies (models of systems based on existing analogical structures) and "designed" analogies (models built up from separate analogical features). (shrink)

Human cognition is said to be systematic: cognitive ability generalizes to structurally related behaviours. The connectionist approach to cognitive theorizing has been strongly criticized for its failure to explain systematicity. Demonstrations of generalization notwithstanding, I show that two widely used networks (feedforward and recurrent) do not support systematicity under the condition of local input/output representations. For a connectionist explanation of systematicity, these results leave two choices, either: (1) develop models capable of systematicity under local input/output representations; or (2) justify the (...) choice of similarity-based (nonlocal) component representations sufficient for systematicity. (shrink)

Deep neural networks are said to be opaque, impeding the development of safe and trustworthy artificial intelligence, but where this opacity stems from is less clear. What are the sufficient properties for neural network opacity? Here, I discuss five common properties of deep neural networks and two different kinds of opacity. Which of these properties are sufficient for what type of opacity? I show how each kind of opacity stems from only one of these five properties, and then discuss (...) to what extent the two kinds of opacity can be mitigated by explainability methods. (shrink)

It is widely believed that bringing parties with differing opinions together to discuss their differences will help both in securing consensus and also in ensuring that this consensus closely approximates the truth. This paper investigates this presumption using two mathematical and computer simulation models. Ultimately, these models show that increased contact can be useful in securing both consensus and truth, but it is not always beneficial in this way. This suggests one should not, without qualification, support policies which increase interpersonal (...) contact if one seeks to improve the epistemic performance of groups. (shrink)

Air transport is playing an increasing role in the world economy every year. This is facilitated by technological development and the latest developments in the aviation industry, globalization. This paper provides an overview of artificial neural network training methods for airfare predicting. The articles for 2017-2019 were analyzed in order to determine the model with the most accurate prediction. The researchers conducted research on open data collected by themselves and set themselves the goal of creating a model (...) that would advise a user the best time to buy a ticket when the price would be the lowest. The review of the papers by similar themes revealed that the Bagging Regression Tree model has the highest results with an accuracy of 88% and the random forest method has an accuracy of 87%. Civil aviation plays an important role in the economy of each country. Aviation is the best way to cover long distances in comfort in the shortest time. Airlines offer customers a variety of opportunities to travel both within the country and abroad. The main problem of interaction between airlines and customers is the airfare: the former want to sell more at the higher price, and the latter want to buy cheaper. Therefore, companies use their own private algorithms for dynamic pricing and constantly monitor the market situation, responsive to changes in demand and the actions of competitors. This behavior allows them to achieve a balance between the desires of airlines and customers. Scientists are trying to invent a way to predict airfare so that air travelers can buy them at the lowest price. The results of the work in this area provide general rules for the best purchase. For example, according to the article thebest day to buy a ticket by expedia.com for a domestic flight on the United States is Sunday, and the best period is 57 days before departure. This article provides an overview of the works, the authors of which compared the models of machine learning. Achievements in this area are limited to direct flights of a certain domestic market and 88% accuracy of the forecast. The Bagging Regression Tree model described in the article can be considered the best result. This trained model can make predictions based only on two parameters: the number of free cargo and the number of days left before departure and has an accuracy of 88%. (shrink)

Emotion-based sentimental analysis has recently received a lot of interest, with an emphasis on automated identification of user behavior, such as emotional expressions, based on online social media texts. However, the majority of the prior attempts are based on traditional procedures that are insufficient to provide promising outcomes. In this study, we categorize emotional sentiments by recognizing them in the text. For that purpose, we present a deep learning model, bidirectional long-term short-term memory, for emotion recognition that takes into (...) account five main emotions. We use our experimental assessments on the emotion dataset to accomplish the emotion categorization job. The datasets were evaluated and the findings revealed that, when compared to state-of-the-art methodologies, the proposed model can successfully categorize user emotions into several classifications. Finally, we assess the efficacy of our strategy using statistical analysis. This research’s findings help firms to apply best practices in the selection, management, and optimization of policies, services, and product information. (shrink)

Public health care interventions—regarding vaccination, obesity, and HIV, for example—standardly take the form of information dissemination across a community. But information networks can vary importantly between different ethnic communities, as can levels of trust in information from different sources. We use data from the Greater Pittsburgh Random Household Health Survey to construct models of information networks for White and Black communities--models which reflect the degree of information contact between individuals, with degrees of trust in information from various sources correlated with (...) positions in that social network. With simple assumptions regarding belief change and social reinforcement, we use those modeled networks to build dynamic agent-based models of how information can be expected to flow and how beliefs can be expected to change across each community. With contrasting information from governmental and religious sources, the results show importantly different dynamic patterns of belief polarization within the two communities. (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)

Contemporary psycholinguistic models place significant emphasis on the cognitive processes involved in the acquisition, recognition, and production of language but neglect many issues related to the representation of language-related information in the mental lexicon. In contrast, a central tenet of network science is that the structure of a network influences the processes that operate in that system, making process and representation inextricably connected. Here, we consider how the structure found across phonological networks of several languages from different language (...) families may influence language processing as we age and experience diseases that affect cognition during the typical and atypical acquisition of new words, during typical perception and production of speech in adults, and during language change over time. We conclude that the network science approach may not only provide insights into specific language processes but also provide a way to connect the work from these domains, which are becoming increasingly balkanized. (shrink)

The technology, which is implemented with cross platform tools, is proposed for modeling of gesture units of sign language, animation between states of gesture units with a combination of gestures. Implemented technology simulates sequence of gestures using virtual spatial hand model and performs recognition of dactyl items from camera input using trained on collected training dataset set convolutional neural network, based on the MobileNetv3 architecture, and with the optimal configuration of layers and network parameters. On the collected (...) test dataset accuracy of over 98% is achieved. (shrink)

In 1937 Joseph Grinnell founded the University of California’s first biological field station, the Hastings Natural History Reservation. Hastings became a center for field biology on the West Coast, and by 1960 it was serving as a model for the creation of additional U.C. reserves. Today, the U.C. Natural Reserve System is the largest and most diverse network of university-based biological field stations in the world, with 36 sites covering more than 135,000 acres. This essay examines the founding (...) of the Hastings Reservation, and asks how it managed to grow and develop, in the 1940s and 1950s, during a time of declining support for natural history research. It shows how faculty and staff courted the support of key institutional allies, presented themselves as the guardians of a venerable tradition in nature study, and emphasized the station’s capacity to document ecological change and inform environmental policy and management. In the years since, Hastings and other U.C. reserves have played crucial roles in California environmental politics. Biological field stations in the post-war era deserve more attention not only from historians of biology, but also from environmental historians and other scholars interested in the role of science in society. (shrink)

Endothelial cells, when cultured on gelled basement membrane matrix exert forces of tension through which they deform the matrix and at the same time they aggregate into clusters. The cells eventually form a network of cord-like structures connecting cell aggregates. In this network, almost all of the matrix has been pulled underneath the cell cords and cell clusters. This phenomenon has been proposed as a possible model for the growth and development of planar vascular systems in vitro. (...) Our hypothesis is that the matrix is reorganized and the cellular networks form as a result of traction forces exerted by the cells on the matrix and the latter's elasticity. We construct and analyze a mathematical model based on this hypothesis and examine conditions necessary for the formation of the pattern. We show cell migration is not necessary for pattern formation and that isotropic, strain-stimulated traction is sufficient to form the observed patterns. (shrink)

Intersubjectivity refers to one person’s awareness in relation to another person’s awareness. It is key to well-being and human development. From infancy to adulthood, human interactions ceaselessly contribute to the flourishing or impairment of intersubjectivity. In this work, we first describe intersubjectivity as a hallmark of quality dyadic processes. Then, using parent-child relationship as an example, we propose a dyadic active inference model to elucidate an inverse relation between stress and intersubjectivity. We postulate that impaired intersubjectivity is a manifestation (...) of underlying problems of deficient relational benevolence, misattributing another person’s intentions, and neglecting the effects of one’s own actions on the other person. These problems can exacerbate stress due to excessive variational free energy in a person’s active inference engine when that person feels threatened and holds on to his/her invalid beliefs. In support of this dyadic model, we briefly describe relevant neuroimaging literature to elucidate brain networks underlying the effects of an intersubjectivity-oriented parenting intervention on parenting stress. Using the active inference dyadic model, we identified critical interventional strategies necessary to rectify these problems and hereby developed a coding system in reference to these strategies. In a theory-guided quantitative review, we used this coding system to code 35 clinical trials of parenting interventions published between 2016 and 2020, based on PubMed database, to predict their efficacy for reducing parenting stress. The results of this theory-guided analysis corroborated our hypothesis that parenting intervention can effectively reduce parenting stress if the intervention is designed to mitigate the problems of deficient relational benevolence, under-coupling, and over-mentalizing. We integrated our work with several dyadic concepts identified in the literature. Finally, inspired by Arya Nagarjuna’s Buddhist Madhyamaka Philosophy, we described abstract expressions of Dependent Origination as a relational worldview to reflect on the normality, impairment, and rehabilitation of intersubjectivity. (shrink)

As interpersonal, racial, social, and international conflicts intensify in the world, it is important to safeguard the mental health of individuals affected by them. According to a Buddhist notion “if you want others to be happy, practice compassion; if you want to be happy, practice compassion,” compassion practice is an intervention to cultivate conflict-proof well-being. Here, compassion practice refers to a form of concentrated meditation wherein a practitioner attunes to friend, enemy, and someone in between, thinking, “I’m going to help (...) them.” The compassion meditation is based on Buddhist philosophy that mental suffering is rooted in conceptual thoughts that give rise to generic mental images of self and others and subsequent biases to preserve one’s egoism, blocking the ultimate nature of mind. To contextualize compassion meditation scientifically, we adopted a Bayesian active inference framework to incorporate relevant Buddhist concepts, including mind, compassion, aggregates, suffering, reification, conceptual thoughts, and superimposition. In this framework, a person is considered a Bayesian Engine that actively constructs phenomena based on the aggregates of forms, sensations, discriminations, actions, and consciousness. When the person embodies rigid beliefs about self and others’ identities and the resulting ego-preserving bias, the person’s Bayesian Engine malfunctions, failing to use prediction errors to update prior beliefs. To counter this problem, after recognizing the causes of sufferings, a practitioner of the compassion meditation aims to attune to all others equally, friends and enemies alike, suspend identity-based conceptual thoughts, and eventually let go of any identity-grasping belief and ego-preserving bias that obscure reality. We present a brain model for the Bayesian Engine of three components: Relation-Modeling, Reality-Checking, and Conflict-Alarming, which are subserved by the Default-Mode Network, Frontoparietal Network and Ventral Attention Network, and Salience Network, respectively. Upon perceiving conflicts, the strengthening or weakening of ego-preserving bias will critically depend on whether the SN up-regulates the DMN or FPN/VAN, respectively. We propose that compassion meditation can strengthen brain regions that are conducive for suspending prior beliefs and enhancing the attunements to the counterparts in conflicts. (shrink)

An integrated statement is made concerning the semantic status of nodes in a propositional semantic network, claiming that such nodes represent only intensions. Within the network, the only reference to extensionality is via a mechanism to assert that two intensions have the same extension in same world. This framework is employed in three application problems to illustrate the nature of its solutions.The formalism used here utilizes only assertional information and no structural, or definitional, information. This restriction corresponds to (...) many of the psychologically motivated network models. Some of the psychological implications of network processes called node merging and node splitting are discussed. Additionally, it is pointed out that both our networks and the psychologically based networks are prone to memory confusions about knowing unless augmented by domain‐specific inference processes, or by structural information. (shrink)

This paper aims to introduce a robust framework for forecasting demand, including data preprocessing, data transformation and standardization, feature selection, cross-validation, and regression ensemble framework. Bagging ), boosting and extreme gradient boosting regression ), and stacking are employed as ensemble models. Different machine learning approaches, including support vector regression, extreme learning machine, and multilayer perceptron neural network, are adopted as reference models. In order to maximize the determination coefficient value and reduce the root mean square error, hyperparameters are set (...) using the grid search method. Using a steel industry dataset, all tests are carried out under identical experimental conditions. In this context, STACK1 and STACK2 models provided better performance than other models. The highest accuracies of R2 of 0.97 and 0.97 are obtained using STACK1 and STACK2, respectively. Moreover, the rank according to performances is STACK1, STACK2, XGBR, GBR, RFR, MLP, ELM, and SVR. As it improves the performance of models and reduces the risk of decision-making, the ensemble method can be used to forecast the demand in a steel industry one month ahead. (shrink)

The self-disorder model provides a phenomenological framework for understanding how the core symptoms of Schizophrenia Spectrum Disorders (SSDs) are rooted in an instability of minimal selfhood. This instability involves a range of “anomalous experiences”: transformations in an individual’s perceptual field and sense of being an agent of action. The explanatory value of this theoretical model can be summarized in two claims about the role of anomalous experiences in self-disorders: (1) anomalous experiences express a common trait-like disturbance that is (...) characteristic of SSDs, and (2) anomalous experiences contribute to explanations regarding how self-disorders progress into SSDs. While hypotheses consistent with the first claim have been substantiated in several studies, hypotheses consistent with the second claim remain underexamined. We argue that attending to this gap in the literature requires considering which methodological strategies are best suited for investigating if and how anomalous experiences contribute to the development of self-disorders into SSDs and psychotic states. Network modeling is discussed as one such strategy suitable for examining the role of anomalies of lived-world in the maintenance of paranoid delusions in SSDs. (shrink)

The contract review process can be a costly and time-consuming task for lawyers and clients alike, requiring significant effort to identify and evaluate the legal implications of individual clauses. To address this challenge, we propose the use of natural language processing techniques, specifically text classification based on deontic tags, to streamline the process. Our research question is whether natural language processing techniques, specifically dense vector embeddings, can help semi-automate the contract review process and reduce time and costs for legal professionals (...) reviewing deontic modalities in contracts. In this study, we create a domain-specific dataset and train both baseline and neural network models for contract sentence classification. This approach offers a more efficient and cost-effective solution for contract review, mimicking the work of a lawyer. Our approach achieves an accuracy of 0.90, showcasing its effectiveness in identifying and evaluating individual contract sentences. (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)

There is widespread belief that connectionist networks are dramatically different from classical or symbolic models. However, connectionists rarely test this belief by interpreting the internal structure of their nets. A new approach to interpreting networks was recently introduced by Berkeley et al. (1995). The current paper examines two implications of applying this method: (1) that the internal structure of a connectionist network can have a very classical appearance, and (2) that this interpretation can provide a cognitive theory that cannot (...) be dismissed as a mere implementation. (shrink)

A fundamental claim associated with parallel distributed processing theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts, that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned (...) in connectionist models and neural coding in brain and often dismiss localist theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models. (shrink)