Peter Abelard (1079–1142 ce) was the most wide‐ranging philosopher of the twelfth century. He quickly established himself as a leading teacher of logic in and near Paris shortly after 1100. After his affair with Heloise, and his subsequent castration, Abelard became a monk, but he returned to teaching in the Paris schools until 1140, when his work was condemned by a Church Council at Sens. His logical writings were based around discussion of the “Old Logic”: Porphyry's Isagoge, aristotle'S Categories and (...) On Interpretation and boethius'S textbook on topical inference. They comprise a freestanding Dialectica (“Logic”; probably c.1116), a set of commentaries (known as the Logica [Ingredientibus], c. 1119) and a later (c. 1125) commentary on the Isagoge (Logica Nostrorum Petititoni Sociorum or Glossulae). In a work Abelard called his Theologia, issued in three main versions (between 1120 and c.1134), he attempted a logical analysis of trinitarian relations and explored the philosophical problems surrounding God's claims to omnipotence and omniscience. The Collationes (“Debates,” also known as “Dialogue between a Christian, a Philosopher and a Jew”; probably c.1130) present a rational investigation into the nature of the highest good, in which the Christian and the Philosopher (who seems to be modeled on a philosopher of pagan antiquity) are remarkably in agreement. The unfinished Scito teipsum (“Know thyself,” also known as the “Ethics”; c.1138) analyses moral action. (shrink)

We present our personal view on W.J. Blok's contribution to modal logic.

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates. BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our ’learner’ discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the (...) relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system. (shrink)

Background: Although genetic research into Alzheimer disease (AD) is increasing, the ethical aspects of this kind of research and the differences between ethical issues related to genetic and non-genetic research into AD have not yet received much attention. Objectives: (1) To identify and compare the five ethical issues considered most important by surveyed expert panellists in non-genetic and genetic AD research and (2) to compare our empirical findings with ethical issues in genetic research in general as described in the literature. (...) Method: A modified Delphi study in two rounds Results: Genetic and non-genetic research into AD generated an approximately equal number of topics with a considerable overlap. Different priorities in the ethics of both types of research were found. Genetic research raised new topics such as “confidentiality of genetic information” and “implications of research for relatives” which changes the impact and application of existing ethical topics such as “informed consent” and is judged to have more impact on both individuals and society. A difference with the results of more theoretical approaches on ethical aspects related to AD research was also found. Conclusions: Different priorities are given to ethical issues in genetic and non-genetic research. These arise partly because genetic research causes unique and new questions, mostly related to the position of family members and the status of and access to genetic information. Differences found between the results of our empirical study and the more theoretical literature, suggest an additional value for empirical research in medical ethics. (shrink)

ABSTRACT Global biodiversity declines are increasingly recognized as profound ecological and social crises. In areas subject to colonialization, these declines have advanced in lockstep with settler colonialism and imposition of centralized resource management by settler states. Many have suggested that resurgent Indigenous-led governance systems could help arrest these trends while advancing effective and socially just approaches to environmental interactions that benefit people and places alike. However, how dominant management and conservation approaches might be decolonized (i.e., how their underlying colonial structure (...) might be addressed, transformed, and replaced) is not always clear. Here, we describe a ‘Decolonial Model of Environmental Management and Conservation’ as an alternative paradigm to dominant approaches of conservation and management. The tenets of the model describe characteristics that might be expected of decolonized management, contrasted with those of dominant state-led approaches such as those embedded in the North American Model of Wildlife Conservation. The model does not prescribe how Indigenous governments or communities ought to govern their own territories, but instead offers insights into how external management and conservation agencies and practitioners might support (or stop impeding) Indigenous-led governance. We illustrate the model with a conservation ‘bright spot’: grizzly bear stewardship in the area now referred to as the Great Bear Rainforest in British Columbia, Canada, with a focus on work led by or in collaboration with, and within the territories of, the Haíɫzaqv, Kitasoo/xai’xais, Nuxalk, and Wuikinuxv First Nations. While acknowledging the important context-specific variability among place-based management and conservation applications, we also discuss the model’s broader applicability. (shrink)