Systematic Study of Electron Localization in an Amorphous Semiconductor

We investigate the electronic structure of gap and band tail states in amorphous silicon. Starting with two 216-atom models of amorphous silicon with defect concentration close to the experiments, we systematically study the dependence of electron localization on basis set, density functional and spin polarization using the first principles density functional code Siesta. We briefly compare three different schemes for characterizing localization: information entropy, inverse participation ratio and spatial variance. Our results show that to accurately describe defect structures within self consistent density functional theory, a rich basis set is necessary. Our study revealed that the localization of the wave function associated with the defect states decreases with larger basis sets and there is some enhancement of localization from GGA relative to LDA. Spin localization results obtained via LSDA calculations, are in reasonable agreement with experiment and with previous LSDA calculations on a-Si:H models.Comment: 16 pages, 11 Postscript figures, To appear in Phys. Rev.

Modulation of Neutrophil Function by Recombinant Human IgG1 Fc Hexamer in the Endogenous K/BxN Mouse Model of Rheumatoid Arthritis.

INTRODUCTION Neutrophils are a pivotal cell type in the K/BxN mouse model of rheumatoid arthritis and play an essential role in the progression of the arthritis. They are readily activated by immune complexes (ICs) via their FcγRs to release IL-1β in addition to other cytokines, which are inducing cartilage destruction. Neutrophils also release neutrophil-active chemokines to recruit themselves in an autocrine manner to perpetuate tissue destruction. FcγR-expression on neutrophils is of crucial importance for the recognition of ICs. METHODS In this study, due to its high avidity for binding to FcγRs, we investigated the potential anti-inflammatory effect of a recombinant IgG1 Fc hexamer (rFc-µTP-L309C) on neutrophils in the K/BxN mouse model of endogenously generated chronic arthritis. 200 mg/kg rFc-µTP-L309C and human serum albumin (HSA), used as controls, were administered subcutaneously every other day. Mouse ankle joints were monitored daily to generate a clinical score. Immunohistology was used to evaluate neutrophil infiltration and TUNEL to assess apoptosis. ELISA was used to measure IL-1β. RESULTS Treatment with rFc-µTP-L309C, but not HSA, was able to significantly ameliorate the arthritis in the K/BxN mice. Significant neutrophil infiltration into the ankle joint was found, but treatment with rFc-µTP-L309C resulted in significantly less neutrophil infiltration. There was no significant influence of rFc-µTP-L309C on neutrophil death or apoptosis. Less neutrophil infiltration could not be correlated to chemokine-mediated migration. Significantly less IL-1β was measured in mice treated with rFc-µTP-L309C. CONCLUSION In the endogenous K/BxN mouse model of rheumatoid arthritis, amelioration can be explained in part by inhibition of neutrophil infiltration into the joints as well as inhibition of IL-1β production. Given the observed inhibitory properties on neutrophils, rFc-µTP-L309C may be a potential therapeutic candidate to treat autoimmune and inflammatory conditions in which neutrophils are the predominant cell type involved in pathogenesis

Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring

Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl-D-aspartate receptor (NMDAR)–mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia

Patients with pulmonary arterial hypertension with and without cardiovascular risk factors: Results from the AMBITION trial

Background: The purpose of this study was to compare patients with pulmonary arterial hypertension enrolled in the AMBITION trial with (excluded from the primary analysis set [ex-primary analysis set]) and without (primary analysis set) multiple risk factors for left ventricular diastolic dysfunction. Methods: Treatment-naive patients with pulmonary arterial hypertension were randomized to once-daily ambrisentan and tadalafil combination therapy, ambrisentan monotherapy, or tadalafil monotherapy. The primary end point was time from randomization to first adjudicated clinical failure event. Results: Primary analysis set patients (n = 500), compared with ex-primary analysis set patients (n = 105), were younger (mean, 54.4 vs 62.1 years) with greater baseline 6-minute walk distance (median, 363.7 vs 330.5 meters) and fewer comorbidities (e.g., hypertension and diabetes). Treatment effects of initial combination therapy vs pooled monotherapy were directionally the same for both populations, albeit of a lower magnitude for ex-primary analysis set patients. Initial combination therapy reduced the risk of clinical failure compared with pooled monotherapy in primary analysis set patients (hazard ratio, 0.50; 95% confidence interval, 0.35-0.72), whereas the effect was less clear in ex-primary analysis set patients (hazard ratio, 0.70; 95% confidence interval, 0.35-1.37). Overall, primary analysis set patients had fewer clinical failure events (25% vs 33%), higher rates of satisfactory clinical response (34% vs 24%), and lower rates of permanent study drug withdrawal due to adverse events (16% vs 31%) than ex-primary analysis set patients. Conclusions: Efficacy of initial combination therapy vs pooled monotherapy was directionally similar for primary analysis set and ex-primary analysis set patients. However, ex-primary analysis set patients (with multiple risk factors for left ventricular diastolic dysfunction) experienced higher rates of clinical failure events and the response to combination therapy vs monotherapy was attenuated. Tolerability was better in primary analysis set than ex-primary analysis set patients

Technologies for the automated collection of heat stress data in sheep

The automated collection of phenotypic measurements in livestock is becoming increasingly important to both researchers and farmers. The capacity to non-invasively collect real-time data, provides the opportunity to better understand livestock behaviour and physiology and improve animal management decisions. Current climate models project that temperatures will increase across the world, influencing both local and global agriculture. Sheep that are exposed to high ambient temperatures experience heat stress and their physiology, reproductive function and performance are compromised. Body temperature is a reliable measure of heat stress and hence a good indicator of an animals’ health and well-being. Non-invasive temperature-sensing technologies have made substantial progress over the past decade. Here, we review the different technologies available and assess their suitability for inferring ovine heat stress. Specifically, the use of indwelling probes, intra-ruminal bolus insertion, thermal imaging and implantable devices are investigated. We further evaluate the capacity of behavioural tracking technology, such as global positioning systems, to identify heat stressed individuals based on the exhibition of specific behaviours. Although there are challenges associated with using real-time thermosensing data to make informed management decisions, these technologies provide new opportunities to manage heat stress in sheep. In order to obtain accurate real-time information of individual animals and facilitate prompt intervention, data collection should be entirely automated. Additionally, for accurate interpretation on-farm, the development of software which can effectively collect, manage and integrate data for sheep producer’s needs to be prioritised. Lastly, understanding known physiological thresholds will allow farmers to determine individual heat stress risk and facilitate early intervention to reduce the effects in both current and subsequent generations

Transiting Exoplanet Studies and Community Targets for JWST's Early Release Science Program

The James Webb Space Telescope will revolutionize transiting exoplanet atmospheric science due to its capability for continuous, long-duration observations and its larger collecting area, spectral coverage, and spectral resolution compared to existing space-based facilities. However, it is unclear precisely how well JWST will perform and which of its myriad instruments and observing modes will be best suited for transiting exoplanet studies. In this article, we describe a prefatory JWST Early Release Science (ERS) program that focuses on testing specific observing modes to quickly give the community the data and experience it needs to plan more efficient and successful future transiting exoplanet characterization programs. We propose a multi-pronged approach wherein one aspect of the program focuses on observing transits of a single target with all of the recommended observing modes to identify and understand potential systematics, compare transmission spectra at overlapping and neighboring wavelength regions, confirm throughputs, and determine overall performances. In our search for transiting exoplanets that are well suited to achieving these goals, we identify 12 objects (dubbed "community targets") that meet our defined criteria. Currently, the most favorable target is WASP-62b because of its large predicted signal size, relatively bright host star, and location in JWST's continuous viewing zone. Since most of the community targets do not have well-characterized atmospheres, we recommend initiating preparatory observing programs to determine the presence of obscuring clouds/hazes within their atmospheres. Measurable spectroscopic features are needed to establish the optimal resolution and wavelength regions for exoplanet characterization. Other initiatives from our proposed ERS program include testing the instrument brightness limits and performing phase-curve observations.(Abridged)Comment: This is a white paper that originated from an open discussion at the Enabling Transiting Exoplanet Science with JWST workshop held November 16 - 18, 2015 at STScI (http://www.stsci.edu/jwst/science/exoplanets). Accepted for publication in PAS

Untangling a Web of Lies: Exploring Automated Detection of Deception in Computer-Mediated Communication

Safeguarding organizations against opportunism and severe deception in computer-mediated communication (CMC) presents a major challenge to CIOs and IT managers. New insights into linguistic cues of deception derive from the speech acts innate to CMC. Applying automated text analysis to archival email exchanges in a CMC system as part of a reward program, we assess the ability of word use (micro-level), message development (macro-level), and intertextual exchange cues (meta-level) to detect severe deception by business partners. We empirically assess the predictive ability of our framework using an ordinal multilevel regression model. Results indicate that deceivers minimize the use of referencing and self-deprecation but include more superfluous descriptions and flattery. Deceitful channel partners also over structure their arguments and rapidly mimic the linguistic style of the account manager across dyadic e-mail exchanges. Thanks to its diagnostic value, the proposed framework can support firms’ decision-making and guide compliance monitoring system development

Ultra-fast yttrium hydride chemistry at high pressures via non-equilibrium states induced by x-ray free electron laser

Controlling the formation and stoichiometric content of desired phases of materials has become a central interest for the study of a variety of fields, notably high temperature superconductivity under extreme pressures. The further possibility of accessing metastable states by initiating reactions by x-ray triggered mechanisms over ultra-short timescales is enabled with the development of x-ray free electron lasers (XFEL). Utilizing the exceptionally high brilliance x-ray pulses from the EuXFEL, we report the synthesis of a previously unobserved yttrium hydride under high pressure, along with non-stoichiometric changes in hydrogen content as probed at a repetition rate of 4.5\,MHz using time-resolved x-ray diffraction. Exploiting non-equilibrium pathways we synthesize and characterize a hydride with yttrium cations in an \textit{A}15 structure type at 125\,GPa, predicted using crystal structure searches, with a hydrogen content between 4.0--5.75 hydrogens per cation, that is enthalpically metastable on the convex hull. We demonstrate a tailored approach to changing hydrogen content using changes in x-ray fluence that is not accessible using conventional synthesis methods, and reveals a new paradigm in metastable chemical physics

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives