natural sciences
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Development ◽  
2022 ◽  
Vol 149 (2) ◽  
Stefan Galander

Mansi Srivastava is a John L. Loeb Associate Professor of the Natural Sciences at Harvard University. This year, she was awarded the Elizabeth D. Hay New Investigator Award by the Society of Developmental Biology, which recognizes new group leaders who have performed outstanding research in developmental biology during the early stages of their independent career. Mansi's research focusses on investigating wound response and stem cell biology during regeneration in an evolutionary context. We talked to Mansi to discover how she feels about receiving this award, and about her career and her activities outside of the lab.

2022 ◽  
pp. 1-20
Noah Stemeroff

Abstract Perspectival realists often appeal to the methodology of science to secure a realist account of the retention and continued success of scientific claims through the progress of science (e.g. Massimi, 2016). However, in the context of modern physics, the retention and continued success of scientific claims is typically only definable within a mathematical framework. In this paper, I argue that this concern leaves the perspectivist open to Cassirer’s (1910) neo-Kantian critique of the applicability of mathematics in the natural sciences. To support this criticism, I present a case study on the conservation of energy in modern physics.

2022 ◽  
Rosemary Claire Hastings ◽  
Krishma Labib ◽  
Iris Lechner ◽  
Lex Bouter ◽  
Guy Widdershoven ◽  

There is little research on how guidance provided in the European Code of Conduct for Research Integrity (ALLEA code) compares with recommendations developed by European discipline-specific learned societies. We identified, and conducted a content analysis of, 58 guideline documents from 245 societies. Less than 25% of societies in any discipline provide guidance and there are notable disciplinary differences. Recommendations not reflected in the ALLEA code relate primarily to research culture and environment. Medical and Health Sciences societies often focus on regulatory and procedural aspects of research, whereas Natural Sciences societies emphasize the importance of accurate and appropriate dissemination of results. Humanities and Social Sciences societies’ recommendations are more heterogenous and relate to the nature of specific sub-disciplines. Our results reflect differences in epistemological approaches as well as the specific role and responsibilities of societies as membership organizations. We recommend that societies develop, or endorse, appropriate research integrity guidance.

2022 ◽  
Olivier Pourret ◽  
Dasapta Erwin Irawan ◽  
Najmeh Shaghaei ◽  
Elenora M. van Rijsingen ◽  
Lonni Besançon

Science's success and effect measures are built on a system that prioritizes citations and impact factors. These measurements are inaccurate and biased against already under-represented groups, and they fail to convey the range of individuals' significant scientific contributions, especially open science. We argue for a transition in this out-of-date value system that promotes science by promoting diversity, equity, and inclusion. To achieve systemic change, it will necessitate a concerted effort led by academic leaders and administrators.

2022 ◽  
Gaëlle Pontarotti ◽  
Antoine C. Dussault ◽  
Francesca Merlin

2022 ◽  
Vol 21 ◽  
pp. 055-080
Frank Griffel

Preserved in what seems to be a unique manuscript at the Bodleian Library, al-Nafs wa-l-rūḥ wa-sharḥ quwāhumā (The Soul and the Spirit together with an Explanation of Their Faculties) of Fakhr al-Dīn al-Rāzī (d. 606/1210) is a curious book. At the beginning, the author decribes the text as part of the philosophical sciences (as opposed to the religious ones) and clarifies that it deals with ʿilm al-akhlāq, meaning Aristotelian virtue ethics. The text is divided into two parts, the first explaining subjects of philosophical psychology, such as the nature of the soul, its faculties, and its survival after the death of the body. The second part explains how one can “treat” or “heal” the soul from certain negative character traits or vices. In both parts, the book makes liberal use of quotations from the Qur’an, from prophetical ḥadīth, and from sayings by other prophets and sages. This is quite unlike any other “book on philosophy” that Fakhr al-Dīn al-Rāzī wrote.The article explains the distinction between philosophical and non-philosophical books in Fakhr al-Dīn al-Rāzī and what it means for a book to belong to the former group. Al-Rāzī’s works in the theoretical fields of philosophy (logic, the natural sciences, metaphysics, and theology) do not use evidence derived from revelation and hardly ever refer to it. The relationship between revelation and the practical disciplines of philosophy (among them ethics), however, is different from the relation between revelation and theoretical philosophy. This difference leads in Avicenna to an almost complete abandonment of the practical disciplines. In authors who follow Avicenna in his Farabian approach to the relationship between philosophy and revelation, it leads to hybrid works such as al-Nafs wa-l-rūḥ wa-sharḥ quwāhumā that follow a philosophical agenda but employ means and strategies that mimic and imitate revelation.

2022 ◽  
Hiroto Saigo ◽  
K.C. Dukka Bahadur ◽  
Noritaka Saito

Abstract In classical machine learning, regressors are trained without attempting to gain insight into the mechanism connecting inputs and outputs. Natural sciences, however, are interested in finding a robust interpretable function for the target phenomenon, that can return predictions even outside of the training domains. This paper focuses on viscosity prediction problem in steelmaking, and proposes Einstein-Roscoe regression (ERR), which learns the coefficients of the Einstein-Roscoe equation, and is able to extrapolate to unseen domains. Besides, it is often the case in the natural sciences that some measurements are much more expensive than the others due to physical constraints. To this end, we employ a transfer learning framework based on Gaussian process, which allows us to estimate the regression parameters using the auxiliary measurements available in a reasonable cost. In experiments using the viscosity measurements in high temperature slag system, ERR is compared favorably with various machine learning approaches in interpolation settings, while outperformed all of them in extrapolation settings. Furthermore, after estimating parameters using the auxiliary dataset obtained at room temperature, increase in accuracy is observed in the high temperature dataset, which corroborates the effectiveness of the proposed approach.

2022 ◽  
Vol 10 (1) ◽  
pp. 63-83
Wei Xiao ◽  
Jin Liu ◽  
Li Li

Recent years have witnessed a growing interest in research article (RA thereafter) introductions. Most previous studies focused on the macro structures, rhetorical functions and linguistic realizations of RA introductions, but few intended to investigate the information content distribution from the perspective of information theory. The current study conducted an entropy-based study on the distributional patterns of information content in RA introductions and their variations across disciplines (humanities, natural sciences, and social sciences). Three indices, that is, one-, two-, and three-gram entropies, were used to analyze 120 RA introductions (40 introductions from each disciplinary area). The results reveal that, first, in RA introductions, the information content is unevenly distributed, with the information content of Move 1 being the highest, followed in sequence by Move 3 and Move 2; second, the three entropy indices may reflect different linguistic features of RA introductions; and, third, disciplinary variations of information content were found. In Move 1, the RA introductions of natural sciences are more informative than those of the other two disciplines, and in Move 3 the RA introductions of social sciences are more informative as well. This study has implications for genre-based instruction in the pedagogy of academic writing, as well as the broadening of the applications of quantitative corpus linguistic methods into less touched fields.

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