A critical issue in executive control is how the nervous system exerts flexibility to inhibit a prepotent response and adapt to sudden changes in the environment. In this study, force measurement was used to capture “partial” unsuccessful trials that are highly relevant in extending the current understanding of motor inhibition processing. Moreover, a modified version of the stop-signal task was used to control and eliminate potential attentional capture effects from the motor inhibition index. The results illustrate that the non-canceled force (...) and force rate increased as a function of stop-signal delay, offering new objective indices for gauging the dynamic inhibitory process. Motor response was a function of delay in the presentation of novel/infrequent stimuli. A larger lateralized readiness potential amplitude in go and novel stimuli indicated an influence of the novel stimuli on central motor processing. Moreover, an early N1 component reflects an index of motor inhibition in addition to the N2 component reported in previous studies. Source analysis revealed that the activation of N2 originated from inhibitory control associated areas: the right inferior frontal gyrus, pre-motor cortex, and primary motor cortex. Regarding partial responses, LRP and error-related negativity were associated with error correction processes, whereas the N2 component may indicate the functional overlap between inhibition and error correction. In sum, the present study has developed reliable and objective indices of motor inhibition by introducing force, force-rate and electrophysiological measures, further elucidating our understandings of dynamic motor inhibition and error correction. (shrink)

In the Middle Age it was tried to show that índex of five predicables that Porfirio proposes in Isagoge was suitable and complete. More recently it is affirmed that chis índex is incomplete, and thal can add a new predicable that also Aristotle would have considered: the accidents per se.

di 1 juan. Shi lun juan -- di 2 juan. Fan chou juan -- di 3 juan. Men lei juan.

The use of black box algorithms in medicine has raised scholarly concerns due to their opaqueness and lack of trustworthiness. Concerns about potential bias, accountability and responsibility, patient autonomy and compromised trust transpire with black box algorithms. These worries connect epistemic concerns with normative issues. In this paper, we outline that black box algorithms are less problematic for epistemic reasons than many scholars seem to believe. By outlining that more transparency in algorithms is not always necessary, and by explaining that (...) computational processes are indeed methodologically opaque to humans, we argue that the reliability of algorithms provides reasons for trusting the outcomes of medical artificial intelligence. To this end, we explain how computational reliabilism, which does not require transparency and supports the reliability of algorithms, justifies the belief that results of medical AI are to be trusted. We also argue that several ethical concerns remain with black box algorithms, even when the results are trustworthy. Having justified knowledge from reliable indicators is, therefore, necessary but not sufficient for normatively justifying physicians to act. This means that deliberation about the results of reliable algorithms is required to find out what is a desirable action. Thus understood, we argue that such challenges should not dismiss the use of black box algorithms altogether but should inform the way in which these algorithms are designed and implemented. When physicians are trained to acquire the necessary skills and expertise, and collaborate with medical informatics and data scientists, black box algorithms can contribute to improving medical care. (shrink)

Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations :483–496, 2009; Morrison in Philos Stud 143:33–57, 2009), the nature of computer data Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Durán, Arnold Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and the explanatory power of (...) computer simulations :277–292, 2008; Durán in Int Stud Philos Sci 31:27–45, 2017). The aim of this article is to show that these authors are right in assuming that results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of epistemic opacity, the article elaborates extensively on computational reliabilism, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of successful implementations, and the role of expert knowledge in simulations. (shrink)

This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...) related to the general practice of computer simulations. (shrink)

This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation model and the (...) results of the simulation. I also argue that our epistemic gain goes beyond the unificationist account, encompassing a practical dimension as well. (shrink)

In this full review paper, the recent emerging trends in Computing Structures, Software Science, and System Applications have been reviewed and explored to address the recent topics and contributions in the era of the Software and Computing fields. This includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art, framework, implemented approaches and techniques research projects in the areas of Software Technology & Automation, Networking, Systems, Computing Sciences and Software Engineering, Big Data and E-learning. Based on this systematic (...) review, we have put some recommendations and suggestions for researchers, practitioners and scholars to improve their research quality in this area. (shrink)

Many philosophical accounts of scientific models fail to distinguish between a simulation model and other forms of models. This failure is unfortunate because there are important differences pertaining to their methodology and epistemology that favor their philosophical understanding. The core claim presented here is that simulation models are rich and complex units of analysis in their own right, that they depart from known forms of scientific models in significant ways, and that a proper understanding of the type of model simulations (...) are fundamental for their philosophical assessment. I argue that simulation models can be distinguished from other forms of models by the many algorithmic structures, representation relations, and new semantic connections involved in their architecture. In this article, I reconstruct a general architecture for a simulation model, one that faithfully captures the complexities involved in most scientific research with computer simulations. Furthermore, I submit that a new methodology capable of conforming such architecture into a fully functional, computationally tractable computer simulation must be in place. I discuss this methodology—what I call recasting—and argue for its philosophical novelty. If these efforts are heading towards the right interpretation of simulation models, then one can show that computer simulations shed new light on the philosophy of science. To illustrate the potential of my interpretation of simulation models, I briefly discuss simulation-based explanations as a novel approach to questions about scientific explanation. (shrink)

The objective of this paper is to discuss the relationship between the functional properties and information-processing modes of the human brain and the evolution of scientific thought. Science has emerged as a tool to carry out predictive operations that exceed the accuracy, temporal scale, and intrinsic operational limitations of the human brain. Yet the scientific method unavoidably reflects some fundamental characteristics of the information-acquisition and -analysis modes of the brain, which impose a priori boundary conditions upon how science can develop (...) and how the physical universe can be “understood.” A brief description of physical and biological interactions is given, with emphasis on the defining role played by the concept of information. Current views on the information-processing and information-generating mechanisms of the human brain are briefly reviewed. It is shown how some particular features of superstition, natural philosophy, physical thought, and intuition can be linked to certain characteristic information-processing modes of the brain. A discussion is given of how greatly expanded knowledge of brain functions might affect the future of science and technology. (shrink)

Moral identity and moral dissonance in business ethics have explored tensions relating to moral self-identity and the pressures for identity compartmentalization in the workplace. Yet, the connection between these streams of scholarship, spirituality at work, and business ethics is under-theorized. In this paper, we examine the Quaker tradition to explore how Quakers’ interpret moral identity and negotiate the moral dissonance associated with a divided self in work organizations. Specifically, our study illuminates that while Quakers’ share a tradition-specific conception of “Quaker (...) morality” grounded in Quaker theology and the Quaker testimonies to truth, integrity, peace, equality, and simplicity, they often foreground the pursuit of an undivided self through seeking work that enables an expression of Quaker moral identity, or by resigning from work organizations that do not. In most cases, however, Quakers’ face moral dissonance at work and engage in either identity compartmentalization and draw upon the metaphor of a ‘spiritual journey’ as a form of self-justification, or reframe, compartmentalize and engage in work tasks that are both subjectively moral and meaningful. We present a model that elaborates these negotiation processes and invite further research that examines how the spiritual traditions influence moral identity construction at work. (shrink)

In this paper l deal with the substantiva! theory of space and time and I examine its consequences with respect to the problem of the differentiation of indiscernible particulars (the so called "problem of individuation"). I distinguish two versions: the "standard" theory and the "substratist" theory. According to the "standard" theory, space and time ( or spacetime) are substances made of points and instants (or point-instants) which hold a contingent relation with the physical substances which occupy those points and instants. (...) According to the "substratist" theory, which may be attributed to D.M. Armstrong, space and time ( or spacetime) are also substances made of points and instants (or point-instants), but those points and instants hold a necessary relation with the physical objects which "occupy" them. This is so because those points (or point-instants) are, as substrata, essential constituents of physical objects, which support and hold together their properties. I argue that in these theories we cannot appeal to the difference in spaciotemporal position in order to ground the numerical diversity of indiscernible particulars and, in this sense, they dont allow us to use space and time as "principies of individuation". (shrink)

Various authors have recently expressed doubts about the public relevance of philosophy. These doubts target both academic philosophy in general and particular subfields of philosophy. This paper investigates whether these doubts are justified through two tests in which the lack of public relevance of a philosophical paper is operationalized as the degree to which that paper is isolated. Both tests suggest that academic philosophy in general is more isolated from the broader public than it should be, and confirm the hypothesis (...) that some subfields of philosophy are more isolated than others. We argue that this lack of public relevance is caused by the incentive structure of academic philosophy and discuss a range of individual-level and incentive-level solutions. (shrink)

In this article I examine Michel Serres’s seminal study of Leibniz: Le Système de Leibniz et ses modèles mathématiques, a book which, in spite of its significance, has never been dis...

When one wants to use citizen input to inform policy, what should the standards of informedness on the part of the citizens be? While there are moral reasons to allow every citizen to participate and have a voice on every issue, regardless of education and involvement, designers of participatory assessments have to make decisions about how to structure deliberations as well as how much background information and deliberation time to provide to participants. After assessing different frameworks for the relationship between (...) science and society, we use Philip Kitcher's framework of Well-Ordered Science to propose an epistemic standard on how citizen deliberations should be structured. We explore what potential standards follow from this epistemic framework focusing on significance versus scientific and engineering expertise. We argue that citizens should be tutored on the historical context of why scientific questions became significant and deemed scientifically and socially valuable, and if citizens report that they are capable of weighing in on an issue then they should be able to do so. We explore what this standard can mean by looking at actual citizen deliberations tied to the 2014 NASA ECAST Asteroid Initiative Citizen forums. We code different vignettes of citizens debating alternative approaches for Mars exploration based upon what level of information seemed to be sufficient for them to feel comfortable in making a policy position. The analysis provides recommendations on how to design and assess future citizen assessments grounded in properly conveying the historical value context surrounding a scientific issue and trusting citizens to seek out sufficient information to deliberate. (shrink)

We would like to thank the authors of the commentaries for their critical appraisal of our feature article, Who is afraid of black box algorithms?1 Their comments, suggestions and concerns are various, and we are glad that our article contributes to the academic debate about the ethical and epistemic conditions for medical Explanatory AI. We would like to bring to attention a few issues that are common worries across reviewers. Most prominently are the merits of computational reliabilism —in particular, when (...) promoted as an alternative to transparency—and CR as necessary but not sufficient for delivering trust. We finalise our response by addressing concerns about the place and role of artificial intelligence in medical decision-making and the physician’s responsibilities. We understand the concerns and reservations that some of the reviewers express regarding the epistemic merits of CR. We believe that, in part, this is due to a practice too deeply rooted in transparency. But on …. (shrink)

A chronicled approach to the notion of computer simulations shows that there are two predominant interpretations in the specialized literature. According to the first interpretation, computer simulations are techniques for finding the set of solutions to a mathematical model. I call this first interpretation the problem-solving technique viewpoint. In its second interpretation, computer simulations are considered to describe patterns of behavior of a target system. I call this second interpretation the description of patterns of behavior viewpoint of computer simulations. This (...) article explores these two interpretations of computer simulations from three different angles. First, I collect a series of definitions of computer simulation from the historical record. I track back definitions to the early 1960s and show how each viewpoint shares similar interpretations of computer simulations—ultimately clustering into the two viewpoints aforementioned. This reconstruction also includes the most recent literature. Second, I unpack the philosophical assumptions behind each viewpoint, with a special emphasis on their differences. Third, I discuss the philosophical implications of each viewpoint in the context of the recent discussion on the logic of scientific explanation for computer simulations. (shrink)

A chronicled approach to the notion of computer simulations shows that there are two predominant interpretations in the specialized literature. According to the first interpretation, computer simulations are techniques for finding the set of solutions to a mathematical model. I call this first interpretation the problem-solving technique viewpoint. In its second interpretation, computer simulations are considered to describe patterns of behavior of a target system. I call this second interpretation the description of patterns of behavior viewpoint of computer simulations. This (...) article explores these two interpretations of computer simulations from three different angles. First, I collect a series of definitions of computer simulation from the historical record. I track back definitions to the early 1960s and show how each viewpoint shares similar interpretations of computer simulations—ultimately clustering into the two viewpoints aforementioned. This reconstruction also includes the most recent literature. Second, I unpack the philosophical assumptions behind each viewpoint, with a special emphasis on their differences. Third, I discuss the philosophical implications of each viewpoint in the context of the recent discussion on the logic of scientific explanation for computer simulations. (shrink)

This article asks the question, ``what is reliable machine learning?'' As I intend to answer it, this is a question about epistemic justification. Reliable machine learning gives justification for believing its output. Current approaches to reliability (e.g., transparency) involve showing the inner workings of an algorithm (functions, variables, etc.) and how they render outputs. We then have justification for believing the output because we know how it was computed. Thus, justification is contingent on what can be shown about the algorithm, (...) its properties, and its behavior. In this paper, I defend computational reliabilism (CR). CR is a computationally-inspired off-shoot of process reliabilism that does not require showing the inner workings of an algorithm. CR credits reliability to machine learning by identifying reliability indicators external to the algorithm (validation methods, knowledge-based integration, etc.). Thus, we have justification for believing the output of machine learning when we have identified the appropriate reliability indicators. CR is advanced as a more suitable epistemology for machine learning. The main goal of this article is to lay the groundwork for CR, how it works, and what we can expect as a justificatory framework for reliable machine learning. (shrink)

In this volume, scientists, historians, and philosophers join to examine computer simulations in scientific practice. One central aim of the volume is to provide a multiperspective view on the topic. Therefore, the text includes philosophical studies on computer simulations, as well as case studies from simulation practice, and historical studies of the evolution of simulations as a research method.

Riben Jiuzhou da xue tu shu guan cang you gu xie Huizhou ben "Zhuzi yu lei" yi bai si shi juan. Huizhou ben shang cheng "Chi lu", xia qi li bian, zai yu lu dao yu lei de xing cheng guo cheng zhong chu yu guan jian de di wei, dui xue jie yan jiu zhu xi si xiang de xing cheng guo cheng, Zhu Xi men ren de qing kuang, jin ben "Zhuzi yu lei" de xing cheng guo (...) cheng yi ji zhong gu shi qi gu Han yu bai hua, ti gong le xin de cai liao he xin de shi ye. (shrink)