Mandatory Custody Mediation: The Debate Over its Usefulness Continues

Published in cooperation with the American Bar Association Section of Dispute Resolutio

Counter-intuitive moral judgement following traumatic brain injury

Several neurological patient populations, including Traumatic Brain Injury (TBI), appear to produce an abnormally ‘utilitarian’ pattern of judgements to moral dilemmas; they tend to make judgements that maximise the welfare of the majority, rather than deontological judgements based on the following of moral rules (e.g., do not harm others). However, this patient research has always used extreme dilemmas with highly valued moral rules (e.g., do not kill). Data from healthy participants, however, suggests that when a wider range of dilemmas are employed, involving less valued moral rules (e.g., do not lie), moral judgements demonstrate sensitivity to the psychological intuitiveness of the judgements, rather than their deontological or utilitarian content (Kahane et al., 2011). We sought the moral judgements of 30 TBI participants and 30 controls on moral dilemmas where content (utilitarian/deontological) and intuition (intuitive/counterintuitive) were measured concurrently. Overall TBI participants made utilitarian judgements in equal proportions to controls; disproportionately favouring utilitarian judgements only when they were counterintuitive, and deontological judgements only when they were counterintuitive. These results speak against the view that TBI causes a specific utilitarian bias, suggesting instead that moral intuition is broadly disrupted following TBI

Eigenvector-Based Centrality Measures for Temporal Networks

Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of network data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent networks. In this paper, we introduce a principled generalization of network centrality measures that is valid for any eigenvector-based centrality. We consider a temporal network with N nodes as a sequence of T layers that describe the network during different time windows, and we couple centrality matrices for the layers into a supra-centrality matrix of size NTxNT whose dominant eigenvector gives the centrality of each node i at each time t. We refer to this eigenvector and its components as a joint centrality, as it reflects the importances of both the node i and the time layer t. We also introduce the concepts of marginal and conditional centralities, which facilitate the study of centrality trajectories over time. We find that the strength of coupling between layers is important for determining multiscale properties of centrality, such as localization phenomena and the time scale of centrality changes. In the strong-coupling regime, we derive expressions for time-averaged centralities, which are given by the zeroth-order terms of a singular perturbation expansion. We also study first-order terms to obtain first-order-mover scores, which concisely describe the magnitude of nodes' centrality changes over time. As examples, we apply our method to three empirical temporal networks: the United States Ph.D. exchange in mathematics, costarring relationships among top-billed actors during the Golden Age of Hollywood, and citations of decisions from the United States Supreme Court.Comment: 38 pages, 7 figures, and 5 table

This before That: Causal Precedence in the Biomedical Domain

Causal precedence between biochemical interactions is crucial in the biomedical domain, because it transforms collections of individual interactions, e.g., bindings and phosphorylations, into the causal mechanisms needed to inform meaningful search and inference. Here, we analyze causal precedence in the biomedical domain as distinct from open-domain, temporal precedence. First, we describe a novel, hand-annotated text corpus of causal precedence in the biomedical domain. Second, we use this corpus to investigate a battery of models of precedence, covering rule-based, feature-based, and latent representation models. The highest-performing individual model achieved a micro F1 of 43 points, approaching the best performers on the simpler temporal-only precedence tasks. Feature-based and latent representation models each outperform the rule-based models, but their performance is complementary to one another. We apply a sieve-based architecture to capitalize on this lack of overlap, achieving a micro F1 score of 46 points.Comment: To appear in the proceedings of the 2016 Workshop on Biomedical Natural Language Processing (BioNLP 2016

Alcohol Fuel Cells at Optimal Temperatures

High-power-density alcohol fuel cells can relieve many of the daunting challenges facing a hydrogen energy economy. Here, such fuel cells are achieved using CsH2PO4 as the electrolyte and integrating into the anode chamber a Cu-ZnO/Al2O3 methanol steam-reforming catalyst. The temperature of operation, ~250°C, is matched both to the optimal value for fuel cell power output and for reforming. Peak power densities using methanol and ethanol were 226 and 100 mW/cm^2, respectively. The high power output (305 mW/cm^2) obtained from reformate fuel containing 1% CO demonstrates the potential of this approach with optimized reforming catalysts and also the tolerance to CO poisoning at these elevated temperatures

Polymer solid acid composite membranes for fuel-cell applications

A systematic study of the conductivity of polyvinylidene fluoride (PVDF) and CsHSO4 composites, containing 0 to 100% CsHSO4, has been carried out. The polymer, with its good mechanical properties, served as a supporting matrix for the high proton conductivity inorganic phase. The conductivity of composites exhibited a sharp increase with temperature at 142°C, characteristic of the superprotonic phase transition of CsHSO4. At high temperature (160°C), the dependence of conductivity on vol % CsHSO4 was monotonic and revealed a percolation threshold of ~10 vol %. At low temperature (100°C), a maximum in the conductivity at ~80 vol % CsHSO4 was observed. Results of preliminary fuel cell measurements are presented

Advanced action manipulator system (ADAMS)

Manipulator offers improved performance over other models in its category. It features larger force and reach capabilities and is readily convertible for underwater use. Unique kinematic arrangement provides extremely large working envelope. System has six degrees of motion: azimuth joint, shoulder joint, upper arm rotating joint, elbow joint, wrist pitch, and wrist twist