Ethical Reductionism

Ethical reductionism is the best version of naturalistic moral realism. Reductionists regard moral properties as identical to properties appearing in successful scientific theories. Nonreductionists, including many of the Cornell Realists, argue that moral properties instead supervene on scientific properties without identity. I respond to two arguments for nonreductionism. First, nonreductionists argue that the multiple realizability of moral properties defeats reductionism. Multiple realizability can be addressed in ethics by identifying moral properties uniquely or disjunctively with properties of the special sciences. Second, nonreductionists argue that irreducible moral properties explain empirical phenomena, just as irreducible special-science properties do. But since irreducible moral properties don't successfully explain additional regularities, they run the risk of being pseudoscientific properties. Reductionism has all the benefits of nonreductionism, while also being more secure against anti-realist objections because of its ontological simplicity

Beyond model answers: learners’ perceptions of self-assessment materials in e-learning applications

The importance of feedback as an aid to self‐assessment is widely acknowledged. A common form of feedback that is used widely in e‐learning is the use of model answers. However, model answers are deficient in many respects. In particular, the notion of a ‘model’ answer implies the existence of a single correct answer applicable across multiple contexts with no scope for permissible variation. This reductive assumption is rarely the case with complex problems that are supposed to test students’ higher‐order learning. Nevertheless, the challenge remains of how to support students as they assess their own performance using model answers and other forms of non‐verificational ‘feedback’. To explore this challenge, the research investigated a management development e‐learning application and investigated the effectiveness of model answers that followed problem‐based questions. The research was exploratory, using semi‐structured interviews with 29 adult learners employed in a global organisation. Given interviewees’ generally negative perceptions of the model‐answers, they were asked to describe their ideal form of self‐assessment materials, and to evaluate nine alternative designs. The results suggest that, as support for higher‐order learning, self‐assessment materials that merely present an idealised model answer are inadequate. As alternatives, learners preferred materials that helped them understand what behaviours to avoid (and not just ‘do’), how to think through the problem (i.e. critical thinking skills), and the key issues that provide a framework for thinking. These findings have broader relevance within higher education, particularly in postgraduate programmes for business students where the importance of prior business experience is emphasised and the profile of students is similar to that of the participants in this research

Lustre, Hadoop, Accumulo

Data processing systems impose multiple views on data as it is processed by the system. These views include spreadsheets, databases, matrices, and graphs. There are a wide variety of technologies that can be used to store and process data through these different steps. The Lustre parallel file system, the Hadoop distributed file system, and the Accumulo database are all designed to address the largest and the most challenging data storage problems. There have been many ad-hoc comparisons of these technologies. This paper describes the foundational principles of each technology, provides simple models for assessing their capabilities, and compares the various technologies on a hypothetical common cluster. These comparisons indicate that Lustre provides 2x more storage capacity, is less likely to loose data during 3 simultaneous drive failures, and provides higher bandwidth on general purpose workloads. Hadoop can provide 4x greater read bandwidth on special purpose workloads. Accumulo provides 10,000x lower latency on random lookups than either Lustre or Hadoop but Accumulo's bulk bandwidth is 10x less. Significant recent work has been done to enable mix-and-match solutions that allow Lustre, Hadoop, and Accumulo to be combined in different ways.Comment: 6 pages; accepted to IEEE High Performance Extreme Computing conference, Waltham, MA, 201

New Water in Old Buckets: Hypothetical and Counterfactual Reasoning in Mach’s Economy of Science

Ernst Mach’s defense of relativist theories of motion in Die Mechanik involves a well-known criticism of Newton’s theory appealing to absolute space, and of Newton’s “bucket” experiment. Sympathetic readers (Norton 1995) and critics (Stein 1967, 1977) agree that there’s a tension in Mach’s view: he allows for some constructed scientific concepts, but not others, and some kinds of reasoning about unobserved phenomena, but not others. Following Banks (2003), I argue that this tension can be interpreted as a constructive one, springing from Mach’s approach to scientific reasoning. Mach’s “economy of science” allows for a principled distinction to be made, between natural and artificial hypothetical reasoning, and Mach defends a division of labor between the sciences in a 1903 paper for The Monist, “Space and Geometry from the Point of View of Physical Inquiry”. That division supports counterfactual reasoning in Mach’s system, something that’s long been denied is possible for him

Homologous Pairing between Long DNA Double Helices

Molecular recognition between two double stranded (ds) DNA with homologous sequences may not seem compatible with the B-DNA structure because the sequence information is hidden when it is used for joining the two strands. Nevertheless, it has to be invoked to account for various biological data. Using quantum chemistry, molecular mechanics, and hints from recent genetics experiments I show here that direct recognition between homologous dsDNA is possible through formation of short quadruplexes due to direct complementary hydrogen bonding of major groove surfaces in parallel alignment. The constraints imposed by the predicted structures of the recognition units determine the mechanism of complexation between long dsDNA. This mechanism and concomitant predictions agree with available experimental data and shed light upon the sequence effects and the possible involvement of topoisomerase II in the recognition.Comment: 10 pages, 7 figures, Includes Supplemental Material. To appear in Phys. Rev. Let

Possible history

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