Matilal's Metaethics

Bimal Krishna Matilal (1935-1991) was a Harvard-educated Indian philosopher best known for his contributions to logic, but who also wrote on wide variety of topics, including metaethics. Unfortunately, the latter contributions have been overlooked. Engaging with Anglo-American figures such as Gilbert Harman and Bernard Williams, Matilal defends a view he dubs ‘pluralism.’ In defending this view he draws on a wide range of classical Indian sources: the Bhagavad-Gītā, Buddhist thinkers like Nāgārjuna, and classical Jaina concepts. This pluralist position is somewhere between relativism and absolutist realism. Unlike the relativist, he argues that there is a genuinely universal morality; unlike the absolutist, he argues that there are multiple, but often conflicting and incommensurable, moral frameworks and ideals. This paper will explain his objections to relativism, as well as flesh out his suggestive remarks about his own pluralistic account

Novel functional imaging approaches for investigating brain plasticity in multiple sclerosis and Parkinson\u2019s disease: from research to clinical applications

Neuronal plasticity, as the capacity of the brain to respond to external demands or to injury, has emerged as a crucial mechanism to preserve, at least in part, an adequate behavioral functioning after an injury and as the process underlying improvements in disability during rehabilitation. Brain plasticity can be detected with both structural and functional magnetic resonance imaging and more and more processing techniques have been developed to better capture the occurring changes and to better define the potential plasticity. Gait and balance are affected in patients with multiple sclerosis since the early stages of the disease with sensory deficits playing a major role in determining both balance and gait impairment. Moreover, gait disorders are one of the major causes of disability in patients with Parkinson\u2019s disease, in particular if suffering from freezing of gait. With this work we aimed at i) investigating the functional reorganization occurring in multiple sclerosis at both early and late stages of the disease, ii) characterizing the functional pattern underlying sensory impairment in patients with early multiple sclerosis and iii) verifying the neural correlates of action observation of gait in patients with Parkinson\u2019s disease. These different studies fit into a larger framework where neuroimaging techniques, in particular functional imaging, would support the clinicians in identifying tailored rehabilitation treatments and the patients who would better benefit from them. We found that patients with early multiple sclerosis showed a higher brain functional flexibility, expressed in terms of blood oxygen level dependent signal variability, which correlated to clinical disability, representing a possible compensatory mechanism. In patients with early multiple sclerosis we also observed subtle position sense deficits, not detectable with a standard neurological examination, and which affected still standing balance. Moreover, these deficits were related to a structural damage at the level of the corpus callosum and to functional activity patterns mainly involving the frontoparietal regions. On the contrary, patients with multiple sclerosis at the progressive stages presented with more subtle changes in the resting state functional connectivity which, nonetheless, were related to clinical disability. Lastly, the presence of freezing of gait in patients with Parkinson disease influenced the neural activation underpinning the action observation of walking. Altogether, these results offer an better insight into the pathophysiological mechanisms underlying disability in patients with multiple sclerosis and constitute a groundwork for the enhancement of rehabilitation protocols to improve gait and balance in both multiple sclerosis and Parkinson\u2019s disease, supporting the embracing of new strategies such as sensory integration and action observation training

A General Approach for Predicting the Behavior of the Supreme Court of the United States

Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time evolving random forest classifier which leverages some unique feature engineering to predict more than 240,000 justice votes and 28,000 cases outcomes over nearly two centuries (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve 70.2% accuracy at the case outcome level and 71.9% at the justice vote level. More recently, over the past century, we outperform an in-sample optimized null model by nearly 5%. Our performance is consistent with, and improves on the general level of prediction demonstrated by prior work; however, our model is distinctive because it can be applied out-of-sample to the entire past and future of the Court, not a single term. Our results represent an important advance for the science of quantitative legal prediction and portend a range of other potential applications.Comment: version 2.02; 18 pages, 5 figures. This paper is related to but distinct from arXiv:1407.6333, and the results herein supersede arXiv:1407.6333. Source code available at https://github.com/mjbommar/scotus-predict-v

The Khache Phalu: A Translation and Interpretation

A translation and analysis of a short ethical treatise written in Tibet in the late 18th or early 19th century. The Khache Phalu includes references to both Buddhist and Islamic thought in providing ethical and spiritual advice. The analysis gives an overview of the secondary literature in both Tibetan and English that is accessible to non-specialists and defends the claim that many passages are deliberately ambiguous. The translation was done with Tenzin Norbu Nangsal and also includes the full Tibetan text

Developmental windows of susceptibility to inorganic arsenic: a survey of current toxicologic and epidemiologic data

Epigenetic reprogramming may underlie adverse health outcomes linked to in utero and early life iAs exposure

On the Stability of Community Detection Algorithms on Longitudinal Citation Data

There are fundamental differences between citation networks and other classes of graphs. In particular, given that citation networks are directed and acyclic, methods developed primarily for use with undirected social network data may face obstacles. This is particularly true for the dynamic development of community structure in citation networks. Namely, it is neither clear when it is appropriate to employ existing community detection approaches nor is it clear how to choose among existing approaches. Using simulated data, we attempt to clarify the conditions under which one should use existing methods and which of these algorithms is appropriate in a given context. We hope this paper will serve as both a useful guidepost and an encouragement to those interested in the development of more targeted approaches for use with longitudinal citation data.Comment: 17 pages, 7 figures, presenting at Applications of Social Network Analysis 2009, ETH Zurich Edit, August 17, 2009: updated abstract, figures, text clarification