Article
History & Philosophy Of Science
Mark Alfano
Summary: In the age of the Internet, while people have increased access to information, there is also a need to sift through accurate sources from online spammers and liars. To address this issue, one can explore the relationship between individual dispositions and network topologies.
Article
Physics, Fluids & Plasmas
E. S. Nani, Britta Nestler
Summary: The asymptotic analysis of multi-phase-field models is often not rigorously performed, and the justification for certain model assumptions is usually heuristic. The transition from an initial filling to a state characterized by separated bulk phases is rarely addressed, and there is a lack of detailed numerical studies on the predicted asymptotic laws.
Article
History & Philosophy Of Science
Cayla Clinkenbeard
Summary: The author argues that the collective responsible for disinformation campaigns is a diffuse network, contrary to Jennifer Lackey's view. This deception involves misleading scientific knowledge, rather than group belief. Taking tobacco industry disinformation campaigns as an example, the author argues that corporate groups needed an epistemically authoritative network of sources, including scientists, doctors, and reputable publishers, to create and spread disinformation to make a skeptical view of scientific knowledge appear credible. Therefore, the author concludes that a network is epistemically responsible for this deception.
Article
Chemistry, Medicinal
Martin Floor, Kengjie Li, Miquel Estevez-Gay, Luis Agullo, Pau Marc Munoz-Torres, Jenn K. Hwang, Silvia Osuna, Jordi Villa-Freixa
Summary: Conventional MD simulations face challenges in obtaining converged results, leading to the widespread use of structure-based models (SBMs) as an alternative. SBMs simplify and focus on relevant aspects of physical processes, allowing for modification of force field definitions and parameters to cater to specific biophysical simulations.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Multidisciplinary Sciences
Nathalie Mathern, Johanna Sandmann, Thorsten Sichtermann, Hani Ridwan, Alexander Riabikin, Andrea Stockero, Omid Nikoubashman, Martin Wiesmann, German Stroke School Group
Summary: This study compared silicone models and computer simulators and evaluated their impact on the subjective self-confidence of operators. Training on computer simulators was considered more realistic and important before patient contact. Participants showed better self-assessment of their abilities and felt more prepared for patient care after the course.
Article
Computer Science, Information Systems
Jie Wang, Zheng Yan, Haiguang Wang, Tieyan Li, Witold Pedrycz
Summary: This paper provides a comprehensive survey and evaluation of the recent advances in trust models in HetNets, filling the gap in the research field and proposing future research directions to advance the research on trustworthy HetNets.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2022)
Article
Social Sciences, Interdisciplinary
Ozge Dilaver, Nigel Gilbert
Summary: This paper aims to improve the transparency of agent-based social simulation (ABSS) models by proposing a framework that captures their conceptual anatomy. It also examines the transparency or opacity of ABSS in the literature on the epistemology of computer simulations and argues that neither opacity nor transparency is intrinsic to ABSS, but depends on research habitus. The paper discusses how thinking about the conceptual anatomy of ABSS can improve its transparency.
JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION
(2023)
Article
History & Philosophy Of Science
Valentin Lageard, Cedric Paternotte
Summary: The high reliability of Wikipedia is attributed to a diverse group of contributors as well as factors like elite contributors and the platform's policies. However, threats to reliability come from disruptive agents like disinformers and trolls, and can only be offset by a combination of factors such as administrative control and the ability to revert entries instantly. Pluralist explanations involving different types of factors are necessary to understand Wikipedia's reliability.
Article
History & Philosophy Of Science
Claus Beisbart
Summary: This paper explores the opacity of simulations and proposes an explication of opacity. The author argues for a broader definition of opacity, suggesting that the resistance to knowledge and understanding is a key factor in determining the opacity of a method. The proposal allows for comparison between different methods regarding opacity and emphasizes the importance of epistemic access in scientific work with simulations.
Article
Chemistry, Multidisciplinary
Martin G. C. Lewis, Maurice R. Yeadon, Mark A. King
Summary: This study compared the accuracy of single-joint and two-joint torque generator representations in whole-body simulations, finding that the two-joint model better matched actual jump performances, especially for dynamic tasks requiring large joint torques and near-maximal joint velocities.
APPLIED SCIENCES-BASEL
(2021)
Article
History & Philosophy Of Science
Hein Duijf
Summary: The paper discusses the conditions under which it is rational to trust and defer to experts, and when it may be rational to refrain from doing so. The author emphasizes that trust in experts depends on their competence and alignment of interests, but it can be difficult to determine these factors.
Article
History & Philosophy Of Science
Keith Raymond Harris
Summary: This paper argues that fears of an epistemic catastrophe caused by deepfake technology are exaggerated. The evidential power of video is not solely dependent on its content, but also on its source, and appropriate patterns of trust can mitigate the epistemic threat posed by deepfakes. Additionally, focusing solely on deepfakes intended to deceive may overlook the psychological impact and harm that this technology can have, even if the audience does not believe the content to be true.
Article
Green & Sustainable Science & Technology
Michael Binns, Hafiz Muhammad Uzair Ayub
Summary: Various modeling approaches have been suggested for gasification processes, including complex models and simpler models like thermodynamic equilibrium and empirical models. This study develops linear and quadratic expressions based on gasifier input parameters using linear regression, and identifies significant parameters with a LASSO shrinkage method for simpler models with reasonable accuracy.
Article
Behavioral Sciences
Y. B. Eisma, P. A. Hancock, J. C. F. de Winter
Summary: In this paper, we review the sampling models described in John Senders's doctoral thesis on visual sampling processes. We present, clarify, and expand these models through computer simulation and visual illustrations.
Article
Computer Science, Information Systems
Abhishek Kesarwani, Pabitra Mohan Khilar
Summary: This paper proposes a subjective trust model based on the behavior of users and service providers to calculate trust values through fuzzy logic in cloud computing. Parameters like performance and elasticity are used for trust evaluation of resources, and fuzzy C-means clustering is applied for evaluating trust values of users.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Public, Environmental & Occupational Health
Stephanie Harvard, Eric Winsberg, John Symons, Amin Adibi
Summary: This paper examines a COVID-19 vaccination model through the lens of philosophical literature, highlighting the social and ethical value judgments in health-oriented modelling. The research emphasizes the importance of making value judgements in health-oriented models explicit and inviting public engagement in the process.
SOCIAL SCIENCE & MEDICINE
(2021)
Article
History & Philosophy Of Science
John Symons, Ramon Alvarado
Summary: Technologies that utilize data science methods can cause epistemic harms which can be unjust. It is important to recognize and address these harms. Through examples from the criminal justice system, workplace hierarchies, and educational contexts, we explain the types of epistemic injustices that can result from common uses of data science technologies.
Article
Philosophy
John Symons
Summary: Meaningfulness is the dimension of importance in adjudicating between competing normative reasons, where an agent's ranking of values reflects their understanding of meaningfulness. While some agents may not engage in such deliberation, their actions can still be prudentially valuable, aesthetically pleasing, and morally praiseworthy. Actions may be good in various ways yet still lack meaning.
