Distribution of endothelial cell protein C/activated protein C receptor (EPCR) during mouse embryo development.

The endothelial cell protein C receptor (EPCR) augments protein C activation by the thrombomodulin.thrombin complex. Deletion of the EPCR gene in mice has been reported to lead to embryonic lethality before embryonic day 10 (E10.0). To identify potential mechanisms responsible for this lethality, we performed an immunohistological analysis of EPCR distribution during mouse embryogenesis. EPCR was detected in the trophoblast giant cells at the feto-maternal boundary from E7.5 and at later time points in the trophoblasts of the placenta, suggesting a role in the haemostatic regulation of the maternal blood that irrigates these surfaces. In the embryo, EPCR was weakly detected in aortic endothelial cells from E13.5. Thereafter, EPCR levels increased in certain large blood vessels endothelial cells suggesting that the specificity of EPCR to large vessels is conferred in utero. However, not until postnatal day 7 did the intensity and distribution of EPCR staining mimic that observed in adult mice

Macroscopic theory of giant magnetoresistance in magnetic granular metals

A macroscopic theory of giant magnetoresistance in granular magnetic materials is developed to improve on that of Rubinstein [Phys. Rev. B 50, 3830 (1994)]. By using a self-consistent method and introducing a useful parametrization, we show the magnetotransport in granular systems to be between those for currents in the plane of layers and currents perpendicular to the plane of the layers in multilayers. The theoretical result in the local limit is found to be in agreement with the observed singular dependence of the giant magnetoresistance on annealing temperature.published_or_final_versio

Sequence tutor: Conservative fine-tuning of sequence generation models with KL-control

This paper proposes a general method for improving the structure and quality of sequences generated by a recurrent neural network (RNN), while maintaining information originally learned from data, as well as sample diversity. An RNN is first pre-trained on data using maximum likelihood estimation (MLE), and the probability distribution over the next token in the sequence learned by this model is treated as a prior policy. Another RNN is then trained using reinforcement learning (RL) to generate higher-quality outputs that account for domain-specific incentives while retaining proximity to the prior policy of the MLE RNN. To formalize this objective, we derive novel off-policy RL methods for RNNs from KL-control. The effectiveness of the approach is demonstrated on two applications; 1) generating novel musical melodies, and 2) computational molecular generation. For both problems, we show that the proposed method improves the desired properties and structure of the generated sequences, while maintaining information learned from data

GaN micro-light-emitting diode arrays with monolithically integrated sapphire microlenses

A microdisk light emitting diode (micro-LED) with a monolithically integrated microlens array was demonstrated. The capability of the lenses in concentrating light emitted from microdisk LEDs was also demonstrated. The focal lengths of the microlenses were determined to be around 44 νm. The emission pattern of the LED emitters was found to be altered by the optical properties of the microlenses. The light emitted by the hybrid device was also found to be less divergent than a broad-area device.published_or_final_versio

Dimension reduction for systems with slow relaxation

We develop reduced, stochastic models for high dimensional, dissipative dynamical systems that relax very slowly to equilibrium and can encode long term memory. We present a variety of empirical and first principles approaches for model reduction, and build a mathematical framework for analyzing the reduced models. We introduce the notions of universal and asymptotic filters to characterize `optimal' model reductions for sloppy linear models. We illustrate our methods by applying them to the practically important problem of modeling evaporation in oil spills.Comment: 48 Pages, 13 figures. Paper dedicated to the memory of Leo Kadanof

Cell genesis and dendritic plasticity: a neuroplastic pas de deux in the onset and remission from depression

Brain neuroplasticity is increasingly considered to be an important component of both the pathology and treatment of depressive spectrum disorders. Recent studies shed light on the relevance of hippocampal cell genesis and cortico-limbic dendritic plasticity for the development and remission from depressive-like behavior. However, the neurobiological significance of neuroplastic phenomena in this context is still controversial. Here we summarize recent developments in this topic and propose an integrative interpretation of data gathered so far

Evolution in the number of authors of computer science publications

This article analyses the evolution in the number of authors of scientific publications in computer science (CS). This analysis is based on a framework that structures CS into 17 constituent areas, proposed by Wainer et al. (Commun ACM 56(8):67–63, 2013), so that indicators can be calculated for each one in order to make comparisons. We collected and mined over 200,000 article references from 81 conferences and journals in the considered CS areas, spanning a 60-year period (1954–2014). The main insights of this article are that all CS areas witness an increase in the average number of authors, in every decade, with just one slight exception. We ordered the article references by number of authors, in ascending chronological order and grouped them into decades. For each CS area, we provide a perspective of how many groups (1-author papers, 2-author papers and so on) must be considered to reach certain proportions of the total for that CS area, e.g., the 90th and 95th percentiles. Different CS areas require different number of groups to reach those percentiles. For all 17 CS areas, an analysis of the point in time in which publications with n+1 authors overtake the publications with n authors is presented. Finally, we analyse the average number of authors and their rate of increase.This work was supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013

Measuring Invisible Particle Masses Using a Single Short Decay Chain

We consider the mass measurement at hadron colliders for a decay chain of two steps, which ends with a missing particle. Such a topology appears as a subprocess of signal events of many new physics models which contain a dark matter candidate. From the two visible particles coming from the decay chain, only one invariant mass combination can be formed and hence it is na\"ively expected that the masses of the three invisible particles in the decay chain cannot be determined from a single end point of the invariant mass distribution. We show that the event distribution in the $\log(E_{1T}/E_{2T})$ vs. invariant mass-squared plane, where $E_{1T}$, $E_{2T}$ are the transverse energies of the two visible particles, contains the information of all three invisible particle masses and allows them to be extracted individually. The experimental smearing and combinatorial issues pose challenges to the mass measurements. However, in many cases the three invisible particle masses in the decay chain can be determined with reasonable accuracies.Comment: 45 pages, 32 figure

Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo

Emotional intelligence buffers the effect of physiological arousal on dishonesty

We studied the emotional processes that allow people to balance two competing desires: benefitting from dishonesty and keeping a positive self-image. We recorded physiological arousal (skin conductance and heart rate) during a computer card game in which participants could cheat and fail to report a certain card when presented on the screen to avoid losing their money. We found that higher skin conductance corresponded to lower cheating rates. Importantly, emotional intelligence regulated this effect; participants with high emotional intelligence were less affected by their physiological reactions than those with low emotional intelligence. As a result, they were more likely to profit from dishonesty. However, no interaction emerged between heart rate and emotional intelligence. We suggest that the ability to manage and control emotions can allow people to overcome the tension between doing right or wrong and license them to bend the rules