We agree with Ainslie's general approach to intertemporal choices and self-control. However, we argue that a concept of “will” is superfluous in explaining tradeoffs between SS (smaller and sooner) and LL (larger and later) rewards in a framework of temporal goal setting and goal aggregation. We provide an alternative framework of reference point-dependent tradeoffs between SS and LL options.

Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases, and extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. A community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the OBO Foundry principles. OHMI leverages established (...) ontologies to create logically structured representations of microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and associated study protocols and types of data analysis and experimental results. (shrink)

© 2017. The American Astronomical Society. All rights reserved.We present new observations of the low-mass companion to HD 984 taken with the Gemini Planet Imager as a part of the GPI Exoplanet Survey campaign. Images of HD 984 B were obtained in the J and H bands. Combined with archival epochs from 2012 and 2014, we fit the first orbit to the companion to find an 18 au orbit with a 68% confidence interval between 14 and 28 au, an eccentricity (...) of 0.18 with a 68% confidence interval between 0.05 and 0.47, and an inclination of 119°with a 68% confidence interval between 114°and 125°. To address the considerable spectral covariance in both spectra, we present a method of splitting the spectra into low and high frequencies to analyze the spectral structure at different spatial frequencies with the proper spectral noise correlation. Using the split spectra, we compare them to known spectral types using field brown dwarf and low-mass star spectra and find a best-fit match of a field gravity M6.5 ±1.5 spectral type with a corresponding temperature of K. Photometry of the companion yields a luminosity of log=2.88 ± 0.07 dex with DUSTY models. Mass estimates, again from DUSTY models, find an age-dependent mass of 34 ±1 to 95 ±4 M Jup. These results are consistent with previous measurements of the object. (shrink)

Data science, and the related field of big data, is an emerging discipline involving the analysis of data to solve problems and develop insights. This rapidly growing domain promises many benefits to both consumers and businesses. However, the use of big data analytics can also introduce many ethical concerns, stemming from, for example, the possible loss of privacy or the harming of a sub-category of the population via a classification algorithm. To help address these potential ethical challenges, this paper maps (...) and describes the main ethical themes that were identified via systematic literature review. It then identifies a possible structure to integrate these themes within a data science project, thus helping to provide some structure in the on-going debate with respect to the possible ethical situations that can arise when using data science analytics. (shrink)

Neural network models have recently made striking progress in natural language processing, but they are typically trained on orders of magnitude more language input than children receive. What can these neural networks, which are primarily distributional learners, learn from a naturalistic subset of a single child's experience? We examine this question using a recent longitudinal dataset collected from a single child, consisting of egocentric visual data paired with text transcripts. We train both language-only and vision-and-language neural networks and analyze the (...) linguistic knowledge they acquire. In parallel with findings from Jeffrey Elman's seminal work, the neural networks form emergent clusters of words corresponding to syntactic (nouns, transitive and intransitive verbs) and semantic categories (e.g., animals and clothing), based solely on one child's linguistic input. The networks also acquire sensitivity to acceptability contrasts from linguistic phenomena, such as determiner-noun agreement and argument structure. We find that incorporating visual information produces an incremental gain in predicting words in context, especially for syntactic categories that are comparatively more easily grounded, such as nouns and verbs, but the underlying linguistic representations are not fundamentally altered. Our findings demonstrate which kinds of linguistic knowledge are learnable from a snapshot of a single child's real developmental experience. (shrink)

Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting (...) brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data. (shrink)

This new selection of Thoreau’s essays traces his trajectory as a writer for the outlets of his day—the periodical press, newspapers, and compendiums—and as a frequent presenter on the local lecture circuit. By arranging the writings chronologically, the volume re-creates the experience of Thoreau’s readers as they followed his developing ideas over time. Jeffrey S. Cramer, award-winning editor of six previous volumes of works by Thoreau, offers the most accurate text available for each essay and provides convenient on-page annotations. (...) He establishes context and guides the reader through unfamiliar allusions and references, plumbing the depths of Thoreau’s writings with unprecedented insight. Among the essays in this book: · The Last Days of John Brown · Resistance to Civil Government [Civil Disobedience] · Thomas Carlyle and His Works · Natural History of Massachusetts · and many more. (shrink)

This new selection of Thoreau’s essays traces his trajectory as a writer for the outlets of his day—the periodical press, newspapers, and compendiums—and as a frequent presenter on the local lecture circuit. By arranging the writings chronologically, the volume re-creates the experience of Thoreau’s readers as they followed his developing ideas over time. Jeffrey S. Cramer, award-winning editor of six previous volumes of works by Thoreau, offers the most accurate text available for each essay and provides convenient on-page annotations. (...) He establishes context and guides the reader through unfamiliar allusions and references, plumbing the depths of Thoreau’s writings with unprecedented insight. Among the essays in this book: · The Last Days of John Brown · Resistance to Civil Government [Civil Disobedience] · Thomas Carlyle and His Works · Natural History of Massachusetts · and many more. (shrink)

A fundamental claim associated with parallel distributed processing theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts, that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned (...) in connectionist models and neural coding in brain and often dismiss localist theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models. (shrink)

This paper argues that the notion of value has been overly simplified and narrowed to focus on economic returns. Stakeholder theory provides an appropriate lens for considering a more complex perspective of the value that stakeholders seek as well as new ways to measure it. We develop a four-factor perspective for defining value that includes, but extends beyond, the economic value stakeholders seek. To highlight its distinctiveness, we compare this perspective to three other popular performance perspectives. Recommendations are made regarding (...) performance measurement for both academic researchers and practitioners. The stakeholder perspective on value offered in this paper draws attention to those factors that are most closely associated with building more value for stakeholders, and in so doing, allows academics to better measure it and enhances managerial ability to create it. (shrink)

The stakeholder perspective has provided a rich forum for a variety of debates at the intersection of business and society. Scholars gathered for two consecutive years, first in North America, and then in Europe, to discuss the major issues surrounding what has come to be known as stakeholder theory, to attempt to find common ground, and to uncover areas in need of further inquiry. Those meetings led to a list of “tensions” and a call for papers for this special issue (...) to help address them. In this article, we introduce the resulting articles and provide some brief commentary on their importance. We end with a few of our own observations about the stakeholder perspective and stakeholder research. (shrink)

Stakeholder theory focuses on how more value is created if stakeholder relationships are governed by ethical principles such as integrity, respect, fairness, generosity and inclusiveness. However, it has not adequately addressed strategies that stakeholders perceive as harmful to their interests and how this perception can even lead some stakeholders to view the firm’s strategies as unethical. To fill the void, this paper directly addresses strategies that stakeholders perceive as harmful to their interests, or what we refer to as harmful stakeholder (...) strategies. Specifically, it identifies factors associated with stakeholder perceptions of harm that are likely to cause them to consider a strategy unethical, examines the negative implications for firms that pursue such strategies in terms of likely stakeholder responses and damage to stakeholder relationships, and provides theory to help explain how firms are likely to respond to stakeholder claims that a strategy is unethical, based on factors such as the strategic importance of the claim to the firm, how long the strategy has been in use, the costs of remediation, the risk of stakeholder mobilization or new regulation, and whether firms can reasonably rationalize their actions. Assessing harm allows a firm to make a more accurate estimate of the costs of a strategy and can assist managers in allocating resources intended to reduce or remediate harm. (shrink)

In this article, we discuss a hypothesis to explain the preferential synthesis of the superoxide sensitive form of aconitase in mitochondria and the phenotype observed in manganese superoxide dismutase mutant mice, which show a gross over accumulation of stored fat in liver. The model proposes that intermediary metabolism is redox regulated by mitochondrial superoxide generated during mitochondrial respiration. This regulates the level of reducing equivalents (NADH) entering the electron transport chain (ETC) through the reversible inactivation of mitochondrial aconitase. This control (...) mechanism has a dual function; firstly, it regulates levels of superoxide generated by the ETC and, secondly, it fine‐tunes metabolism by channeling citrate either for the production of NADH for energy metabolism or diverting it for the synthesis of fats. In this setting, the mitochondrial redox state influences metabolic decisions via a superoxide–aconitase rheostat. BioEssays 26:894–900, 2004. © 2004 Wiley Periodicals, Inc. (shrink)

The aim of this paper is to examine the usefulness of the Machamer, Darden, and Craver (2000) mechanism approach to gaining an understanding of explanation in cognitive neuroscience. We argue that although the mechanism approach can capture many aspects of explanation in cognitive neuroscience, it cannot capture everything. In particular, it cannot completely capture all aspects of the content and significance of mental representations or the evaluative features constitutive of psychopathology.

Sibley et al. (2008) report a recurrent neural network model designed to learn wordform representations suitable for written and spoken word identification. The authors claim that their sequence encoder network overcomes a key limitation associated with models that code letters by position (e.g., CAT might be coded as C‐in‐position‐1, A‐in‐position‐2, T‐in‐position‐3). The problem with coding letters by position (slot‐coding) is that it is difficult to generalize knowledge across positions; for example, the overlap between CAT and TOMCAT is lost. Although we (...) agree this is a critical problem with many slot‐coding schemes, we question whether the sequence encoder model addresses this limitation, and we highlight another deficiency of the model. We conclude that alternative theories are more promising. (shrink)

Recent perspectives on community investments suggest that they are opportunities for firms to create value for shareholders and other stakeholders. However, many corporate managers are still influenced by a widely held belief that such investments erode profits and are therefore unjustifiable from an agency perspective. In this paper, we refine and test theory regarding countervailing forces that influence community-based firm performance. We hypothesize that high levels of available slack will be associated with higher community-based performance, but that this relationship will (...) be moderated by three important governance variables: board independence, investment fund ownership, and CEO ownership. We find support for our hypotheses in longitudinal study of a large sample of U.S. corporations. (shrink)