Predicting continuous conflict perception with Bayesian Gaussian processes

Conflict is one of the most important phenomena of social life, but it is still largely neglected by the computing community. This work proposes an approach that detects common conversational social signals (loudness, overlapping speech, etc.) and predicts the conflict level perceived by human observers in continuous, non-categorical terms. The proposed regression approach is fully Bayesian and it adopts Automatic Relevance Determination to identify the social signals that influence most the outcome of the prediction. The experiments are performed over the SSPNet Conflict Corpus, a publicly available collection of 1430 clips extracted from televised political debates (roughly 12 hours of material for 138 subjects in total). The results show that it is possible to achieve a correlation close to 0.8 between actual and predicted conflict perception

Improved single-swab sample preparation for recovering bacterial and phage DNA from human skin and wound microbiomes.

BackgroundCharacterization of the skin and wound microbiome is of high biomedical interest, but is hampered by the low biomass of typical samples. While sample preparation from other microbiomes (e.g., gut) has been the subject of extensive optimization, procedures for skin and wound microbiomes have received relatively little attention. Here we describe an improved method for obtaining both phage and microbial DNA from a single skin or wound swab, characterize the yield of DNA in model samples, and demonstrate the utility of this approach with samples collected from a wound clinic.ResultsWe find a substantial improvement when processing wound samples in particular; while only one-quarter of wound samples processed by a traditional method yielded sufficient DNA for downstream analysis, all samples processed using the improved method yielded sufficient DNA. Moreover, for both skin and wound samples, community analysis and viral reads obtained through deep sequencing of clinical swab samples showed significant improvement with the use of the improved method.ConclusionUse of this method may increase the efficiency and data quality of microbiome studies from low-biomass samples

The effect of abstract versus concrete framing on judgments of biological and psychological bases of behavior

Human behavior is frequently described both in abstract, general terms and in concrete, specific terms. We asked whether these two ways of framing equivalent behaviors shift the inferences people make about the biological and psychological bases of those behaviors. In five experiments, we manipulated whether behaviors are presented concretely (i.e. with reference to a specific person, instantiated in the particular context of that person’s life) or abstractly (i.e. with reference to a category of people or behaviors across generalized contexts). People judged concretely framed behaviors to be less biologically based and, on some dimensions, more psychologically based than the same behaviors framed in the abstract. These findings held true for both mental disorders (Experiments 1 and 2) and everyday behaviors (Experiments 4 and 5) and yielded downstream consequences for the perceived efficacy of disorder treatments (Experiment 3). Implications for science educators, students of science, and members of the lay public are discussed

Nano-photocatalysts in microfluidics, energy conversion and environmental applications

Extensive studies have been carried out on photocatalytic materials in recent years as photocatalytic reactions offer a promising solution for solar energy conversion and environmental remediation. Currently available commercial photocatalysts still lack efficiency and thus are economically not viable for replacing traditional sources of energy. This article focuses on recent developments in novel nano-photocatalyst materials to enhance photocatalytic activity. Recent reports on optofluidic systems, new synthesis of photocatalytic composite materials and motile photocatalysts are discussed in this article.Postprint (published version

Competing by Saving Lives: How Pharmaceutical and Medical Device Companies Create Shared Value in Global Health

This report looks at how pharmaceutical and medical device companies can create shared value in global health by addressing unmet health needs in low- and middle-income countries. Companies have already begun to reap business value and are securing competitive advantages in the markets of tomorrow

A Learning Based Approach to Control Synthesis of Markov Decision Processes for Linear Temporal Logic Specifications

We propose to synthesize a control policy for a Markov decision process (MDP) such that the resulting traces of the MDP satisfy a linear temporal logic (LTL) property. We construct a product MDP that incorporates a deterministic Rabin automaton generated from the desired LTL property. The reward function of the product MDP is defined from the acceptance condition of the Rabin automaton. This construction allows us to apply techniques from learning theory to the problem of synthesis for LTL specifications even when the transition probabilities are not known a priori. We prove that our method is guaranteed to find a controller that satisfies the LTL property with probability one if such a policy exists, and we suggest empirically with a case study in traffic control that our method produces reasonable control strategies even when the LTL property cannot be satisfied with probability one

Centralized trading of corporate bonds

In the post-crisis period, increased regulation of financial intermediaries led to a significant decline in corporate bond market liquidity. In order to stabilize these markets, policy makers recently proposed that the trading of corporate bonds should be more centralized. In this paper, we show that a centralization of corporate bond markets always leads to an inferior outcome when compared with the initial over-the-counter structure. The regulator may achieve a superior allocation only if it is feasible for him to also affect market liquidity, by either increasing or decreasing it

Searching for Dark Photons with Maverick Top Partners

In this paper, we present a model in which an up-type vector-like quark (VLQ) is charged under a new $U(1)_d$ gauge force which kinetically mixes with the SM hypercharge. The gauge boson of the $U(1)_d$ is the dark photon, $\gamma_d$. Traditional searches for VLQs rely on decays into Standard Model electroweak bosons $W,Z$ or Higgs. However, since no evidence for VLQs has been found at the Large Hadron Collider (LHC), it is imperative to search for other novel signatures of VLQs beyond their traditional decays. As we will show, if the dark photon is much less massive than the Standard Model electroweak sector, $M_{\gamma_d}\ll M_Z$, for the large majority of the allowed parameter space the VLQ predominately decays into the dark photon and the dark Higgs that breaks the $U(1)_d$ . That is, this VLQ is a `maverick top partner' with nontraditional decays. One of the appeals of this scenario is that pair production of the VLQ at the LHC occurs through the strong force and the rate is determined by the gauge structure. Hence, the production of the dark photon at the LHC only depends on the strong force and is largely independent of the small kinetic mixing with hypercharge. This scenario provides a robust framework to search for a light dark sector via searches for heavy colored particles at the LHC.Comment: 40 pages and 11 figure