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New waves in philosophy of science
\"This book captures the diverse array of issues in the rapidly developing area of philosophy of science by bringing together a pool of talented young philosophers from across the globe to debate the field and show where it's heading\"--Provided by publisher.
Book
Dynamic Matching in Overloaded Waiting Lists
This paper introduces a stylized model to capture distinctive features of waiting list allocation mechanisms. First, agents choose among items with associated expected wait times. Waiting times serve a similar role to that of monetary prices in directing agents’ choices and rationing items. Second, the expected wait for an item is endogenously determined and randomly fluctuates over time. We evaluate welfare under these endogenously determined waiting times and find that waiting time fluctuations lead to misallocation and welfare loss. A simple randomized assignment policy can reduce misallocation and increase welfare.
Journal Article
AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization
We here present AutoGrow4, an open-source program for semi-automated computer-aided drug discovery. AutoGrow4 uses a genetic algorithm to evolve predicted ligands on demand and so is not limited to a virtual library of pre-enumerated compounds. It is a useful tool for generating entirely novel drug-like molecules and for optimizing preexisting ligands. By leveraging recent computational and cheminformatics advancements, AutoGrow4 is faster, more stable, and more modular than previous versions. It implements new docking-program compatibility, chemical filters, multithreading options, and selection methods to support a wide range of user needs. To illustrate both de novo design and lead optimization, we here apply AutoGrow4 to the catalytic domain of poly(ADP-ribose) polymerase 1 (PARP-1), a well characterized DNA-damage-recognition protein. AutoGrow4 produces drug-like compounds with better predicted binding affinities than FDA-approved PARP-1 inhibitors (positive controls). The predicted binding modes of the AutoGrow4 compounds mimic those of the known inhibitors, even when AutoGrow4 is seeded with random small molecules. AutoGrow4 is available under the terms of the Apache License, Version 2.0. A copy can be downloaded free of charge from
http://durrantlab.com/autogrow4
.
Journal Article
Monopoly without a Monopolist
Bitcoin provides its users with transaction-processing services which are similar to those of traditional payment systems. This article models the novel economic structure implied by Bitcoin’s innovative decentralized design, which allows the payment system to be reliably operated by unrelated parties called miners. We find that this decentralized design protects users from monopoly pricing. Competition among service providers within the platform and free entry imply no entity can profitably affect the level of fees paid by users. Instead, a market for transaction-processing determines the fees users pay to gain priority and avoid transaction-processing delays. The article (i) derives closed-form formulas of the fees and waiting times and studies their properties, (ii) compares pricing under the Bitcoin Payment System to that under a traditional payment system operated by a profit-maximizing firm, and (iii) suggests protocol design modifications to enhance the platform’s efficiency. The Appendix describes and explains the main attributes of Bitcoin and the underlying blockchain technology.
Journal Article
Intrinsic ecological dynamics drive biodiversity turnover in model metacommunities
Turnover of species composition through time is frequently observed in ecosystems. It is often interpreted as indicating the impact of changes in the environment. Continuous turnover due solely to ecological dynamics—species interactions and dispersal—is also known to be theoretically possible; however the prevalence of such autonomous turnover in natural communities remains unclear. Here we demonstrate that observed patterns of compositional turnover and other important macroecological phenomena can be reproduced in large spatially explicit model ecosystems, without external forcing such as environmental change or the invasion of new species into the model. We find that autonomous turnover is triggered by the onset of ecological structural instability—the mechanism that also limits local biodiversity. These results imply that the potential role of autonomous turnover as a widespread and important natural process is underappreciated, challenging assumptions implicit in many observation and management tools. Quantifying the baseline level of compositional change would greatly improve ecological status assessments.
Change in ecological communities can be driven by extrinsic forces, but the degree to which intrinsic population dynamics drive turnover has remained unclear. Here the authors use metacommunity modelling to show that biodiversity change previously attributed to external drivers can be explained based on intrinsic ecosystem dynamics.
Journal Article
Deductive Qualitative Analysis: Evaluating, Expanding, and Refining Theory
Although qualitative research is often equated with inductive analysis, researchers may also use deductive qualitative approaches for certain types of research questions and purposes. Deductive qualitative research allows researchers to use existing theory to examine meanings, processes, and narratives of interpersonal and intrapersonal phenomena. Deductive qualitative analysis (DQA; Gilgun, 2005, 2019) is one form of deductive qualitative research that is suited to theory application, testing, and refinement. Within DQA, researchers combine deductive and inductive analysis to examine supporting, contradicting, refining, and expanding evidence for the theory or conceptual model being examined, resulting in a theory that better fits the present sample and accounts for increased diversity in the phenomenon being studied. This paper acts as a primer on DQA and presents two worked examples of DQA studies. Our discussion focuses on the five primary components of DQA: selecting a research question and guiding theory, operationalizing theory, collecting a purposive sample, coding and analyzing data, and theorizing. We highlight different ways of operationalizing theory as sensitizing constructs or as working hypotheses and discuss common pitfalls in theory operationalization. We divide the coding and analyzing process into two sections for parsimony: early analysis, focused on familiarity with the data, code generation, and identification of negative cases, and middle analysis, focused on developing a thorough understanding of evidence related to the guiding theory and negative cases that depart from the guiding theory. Theorizing occurs throughout as researchers consider ways in which the theory being examined is supported, refuted, refined, or expanded. We also discuss strengths and limitations of DQA and potential difficulties researchers may experience when utilizing this methodology.
Journal Article