Miracle-dz/UniFAR-FTUs huggingface dataset:
Ovarian Hormone Deprivation Reduces Oxytocin Expression in Paraventricular Nucleus Preautonomic Neurons and Correlates with Baroreflex Impairment in Rats

The prevalence of cardiovascular diseases including hypertension increases dramatically in women after menopause, however the mechanisms involved remain incompletely understood. Oxytocinergic (OTergic) neurons are largely present within the paraventricular nucleus of the hypothalamus (PVN). Several studies have shown that OTergic drive from PVN to brainstem increases baroreflex sensitivity and improves autonomic control of the circulation. Since preautonomic PVN neurons express different types of estrogen receptors, we hypothesize that ovarian hormone deprivation causes baroreflex impairment, autonomic imbalance and hypertension by negatively impacting OTergic drive and oxytocin levels in pre-autonomic neurons. Here, we assessed oxytocin gene and protein expression (qPCR and immunohistochemistry) within PVN subnuclei in sham-operated and ovariectomized Wistar rats. Conscious hemodynamic recordings were used to assess resting blood pressure and heart rate and the autonomic modulation of heart and vessels was estimated by power spectral analysis. We observed that the ovarian hormone deprivation in ovariectomized rats decreased baroreflex sensitivity, increased sympathetic and reduced vagal outflows to the heart and augmented the resting blood pressure. Of note, ovariectomized rats had reduced PVN oxytocin mRNA and protein expression in all pre-autonomic PVN subnuclei. Furthermore, reduced PVN oxytocin protein levels were positively correlated with decreased baroreflex sensitivity and negatively correlated with increased LF/HF ratio. These findings suggest that reduced oxytocin expression in OTergic neurons of the PVN contributes to the baroreflex dysfunction and autonomic dysregulation observed with ovarian hormone deprivation.
DAiSEE: Towards User Engagement Recognition in the Wild.

We introduce DAiSEE, the first multi-label video classification dataset comprising of 9068 video snippets captured from 112 users for recognizing the user affective states of boredom, confusion, engagement, and frustration in the wild. The dataset has four levels of labels namely - very low, low, high, and very high for each of the affective states, which are crowd annotated and correlated with a gold standard annotation created using a team of expert psychologists. We have also established benchmark results on this dataset using state-of-the-art video classification methods that are available today. We believe that DAiSEE will provide the research community with challenges in feature extraction, context-based inference, and development of suitable machine learning methods for related tasks, thus providing a springboard for further research. The dataset is available for download at this https URL
Design and Performance Analysis of the Exponentially Weighted Moving Average Mean Estimate for Processes Subject to Random Step Changes

The exponentially weighted moving average (EWMA) is a well-known and popular statistic used for smoothing and forecasting time series and as a process mean estimator, due to its simplicity and ability to capture nonstationarity. The EWMA statistic has been shown to be an optimal mean estimator for a certain disturbance process and an effective estimator for various other processes. In this article we focus on a practical disturbance process—relatively small random step changes that are difficult to distinguish from white noise and usually overlooked by practitioners. We propose an optimal EWMA parameter for step-change disturbance processes, as well as methodologies to identify and estimate the process models. The EWMA estimator's performance is then evaluated analytically. We demonstrate that a well-designed EWMA control scheme can effectively reduce the process variation even for processes subject to infrequent, small step changes. A semiconductor process example illustrates the design and analysis.
Pulmonary diffuse alveolar septal amyloidosis.

Picture 2. High-resolution computed tomography of the chest, showing interlobular septal thickening and random distribution of small nodules with calcification. Picture 3. Histopathologic findings of the transbronchial biopsy specimens from the right lung: (a) Alveolar septa were thickened with acellular eosinophilc homogeneous materials (arrows) (Hematoxylin and Eosin staining, original magnification ×200). (b) Multifocal thickening of alveolar septa with Congo red positive materials were observed (arrows). Congo red positive materials also deposited in the bronchiolar wall and adjacent alveolar region (Congo red stain, original magnification ×200). (c) The amyloid materials were covered on both sides with keratin-positive alveolar lining epithelial cells. Thus, amyloid depositions were confirmed in the alveolar septa in these places (arrows) (AE1/AE3 immunostain, original magnification ×200). □ PICTURES IN CLINICAL MEDICINE □
Status of Cognitive Testing of Adults in India

The assessment of cognitive function is a challenging yet an integral component of psychological, psychiatric, and neurological evaluation. Cognitive assessment tools either can be administered quickly for screening for neurocognitive disorders or can be comprehensive and detailed to identify cognitive deficits for the purpose of localization, diagnosis, and rehabilitation. This article is a comprehensive review of published research that discusses the current challenges for cognitive testing in India, available tools used for the assessment of cognitive function in India, and future directions for cognitive testing in India.
Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.
Heterogeneity of Cerebral Blood Flow: a Fractal Approach

Summary Aim: We demonstrate the heterogeneity of regional cerebral blood flow using a fractal approach and singlephoton emission computed tomography (SPECT). Method: Tc-99m-labelled ethylcysteine dimer was injected intravenously in 10 healthy controls and in 10 patients with dementia of frontal lobe type. The head was imaged with a gamma camera and transaxial, sagittal and coronal slices were reconstructed. Two hundred fifty-six symmetrical regions of interest (ROIs) were drawn onto each hemisphere of functioning brain matter. Fractal analysis was used to examine the spatial heterogeneity of blood flow as a function of the number of ROIs. Results: Relative dispersion (= coefficient of variation of the regional flows) was fractal-like in healthy subjects and could be characterized by a fractal dimension of 1.17 ± 0.05 (mean ± SD) for the left hemisphere and 1.15 ± 0.04 for the right hemisphere, respectively. The fractal dimension of 1.0 reflects completely homogeneous blood flow and 1.5 indicates a random blood flow distribution. Patients with dementia of frontal lobe type had a significantly lower fractal dimension of 1.04 ± 0.03 than in healthy controls. Conclusion: Within the limits of spatial resolution of SPECT, the heterogeneity of brain blood flow is well characterized by a fractal dimension. Fractal analysis may help brain scientists to assess age-, sex- and laterality-related anatomic and physiological changes of brain blood flow and possibly to improve precision of diagnostic information available for patient care.
An IL-7 Fusion Protein That Shows Increased Thymopoietic Ability1

The role of IL-7 during thymopoiesis has led to it being the focus of a number of therapeutic interventions. However, its small size and pleiotropic nature present problems for thymus-directed therapies. We have created a fusion molecule between the extracellular N-terminal domain of CCR9 and IL-7, which has the potential to overcome these difficulties. This novel fusion protein retains the thymopoietic activity of IL-7 and the ligand-binding ability of CCR9. As a thymopoietic agent, compared with IL-7, it shows an enhanced retention in the thymus, increased de novo T cell production, and increased thymic output. Old mice receiving the fusion protein show improved CD8 T cell responses and reduced viral load after infection with influenza virus compared with those receiving IL-7. This chimeric molecule offers a novel therapeutic strategy that may result in the production of an effective immunorestorative agent.
Temperature sensing probe integrated with an SU-8 flexible ribbon cable for heart surgery application

This paper presents a silicon probe designed with three polysilicon resistance temperature detectors (RTDs) for heart temperature sensing in open-heart surgery. Via an integrated SU-8/Cu flexible ribbon cable for signal transmission to the instrument reader outside human body, the probe with a 40° tip angle can provide ∼0.9°C sensing accuracy and sustain a 4N buckling load large enough for the probe to easily penetrate pig's myocardium. The device characteristics have shown the potential for clinical heart temperature sensing applications
Cross-Validation and Mean-Square Stability

A popular practical method of obtaining a good estimate of the error rate of a learning algorithm is k-fold cross-validation. Here, the set of examples is flrst partitioned into k equal-sized folds. Each fold acts as a test set for evaluating the hypothesis learned on the other ki1 folds. The average error across the k hypotheses is used as an estimate of the error rate. Although widely used, especially with small values of k (such as 10), the cross-validation method has heretofore resisted theoretical analysis due to the fact that the k distinct estimates have inherent correlations between them. With only sanity-check bounds known, there is no compelling reason to use the k-fold cross-validation estimate over a simpler holdout estimate. Conventional wisdom is that the averaging in cross-validation leads to a tighter concentration of the estimate of the error around its mean. In this paper, we show that the conventional wisdom is essentially correct. We analyze the reduction in variance of the gap between the cross-validation estimate and the true error rate, and show that for a large family of stable algorithms cross-validation achieves a near optimal variance reduction factor of (1 + o(1))k. In these cases, the k difierent estimates are essentially independent of each other. To proceed with the analysis, we deflne a new measure of algorithm stability, called mean-square stability. This measure is weaker than most stability notions described in the literature, and encompasses a large class of algorithms including bounded SVM regression and regularized least-squares regression. For slightly less stable algorithms such as t-nearest-neighbor, we show that cross-validation leads to an O(1 p k) reduction in the variance of the generalization error.
Phonon engineering for hot-carrier solar cells

This thesis deals with fundamental issues related to phonons in hot-carrier solar cells, a third generation photovoltaic technology. This concept aims at extracting photogenerated charge carriers before their reach a thermal equilibrium with the lattice, and exhibits a theoretical efficiency close to thermodynamic limit. One of the main issue is to hinder carrier cooling, which occurs through LO-phonon emission. In addition to the idea of screening the electron-phonon interaction, one approach consists in designing an absorber in which the LO-phonon has an intrinsic lifetime longer than what it is in conventional materials, enhancing the rate of its reabsorption by the carriers. The LO-phonon decay and lifetime is first investigated in semiconductors within density functional perturbation theory. Specific criteria for relevant absorbing materials choosing, from a phonon point of view, are derived. A full study of the LO-phonon lifetime is performed on a singular material, and the possibility to achieve the sufficient phononic requierements is discussed. Secondly, the above-mentioned electron-phonon interaction is modelled in superlattices. The coupling strength is related to the LO-phonon induced macroscopic electric field, which allows to study the directional dependence of the phonon emission. The latter reveals to differently affect the dimensionality of the electronic and phononic interacting populations. This study calls for development of these structure in the framewok of hot-carrier solar cells.
Developers Need Support, Too: A Survey of Security Advice for Software Developers

Increasingly developers are becoming aware of the importance of software security, as frequent high-profile security incidents emphasize the need for secure code. Faced with this new problem, most developers will use their normal approach: web search. But are the resulting web resources useful and effective at promoting security in practice? Recent research has identified security problems arising from Q&A resources that help with specific secure-programming problems, but the web also contains many general resources that discuss security and secure programming more broadly, and to our knowledge few if any of these have been empirically evaluated. The continuing prevalence of security bugs suggests that this guidance ecosystem is not currently working well enough: either effective guidance is not available, or it is not reaching the developers who need it. This paper takes a first step toward understanding and improving this guidance ecosystem by identifying and analyzing 19 general advice resources. The results identify important gaps in the current ecosystem and provide a basis for future work evaluating existing resources and developing new ones to fill these gaps.
Cellulose chain binding free energy drives the processive move of cellulases on the cellulose surface

Processivity is essential for cellulases in their catalysis of cellulose hydrolysis. But what drives the processive move is not well understood. In this work, we use Trichoderma reesei Cel7B as a model system and show that its processivity is directly correlated to the binding free energy difference of a cellulose chain occupying the binding sites −7 to +2 and that occupying sites −7 to −1. Several mutants that have stronger interactions with glycosyl units in sites +1 and +2 than the wild type enzyme show higher processivity. The results suggest that after the release of the product cellobiose located in sites +1 and +2, the enzyme pulls the cellulose chain to fill the vacant sites, which propels its processive move on the cellulose surface. Biotechnol. Bioeng. 2016;113: 1873–1880. © 2016 Wiley Periodicals, Inc.
Threshold quantile autoregressive models

This article studies estimation and asymptotic properties of Threshold Quantile Autoregressive processes. In particular, we show the consistency of the threshold and slope parameter estimators for each quantile and regime, and derive the asymptotic normality of the slope parameter estimators. A Monte Carlo experiment shows that the standard ordinary least squares estimation method is not able to detect important nonlinearities produced in the quantile process. The empirical study concentrates on modelling the dynamics of the conditional distribution of unemployment growth after the second world war. The results show evidence of important heterogeneity associated with unemployment and strong asymmetric persistence of unemployment growth in the higher quantiles.
Suppression of E. multilocularis Hydatid Cysts after Ionizing Radiation Exposure

Background Heavy-ion therapy has an advantage over conventional radiotherapy due to its superb biological effectiveness and dose conformity in cancer therapy. It could be a potential alternate approach for hydatid cyst treatment. However, there is no information currently available on the cellular and molecular basis for heavy-ion irradiation induced cell death in cystic echinococcosis. Methododology/Principal Findings LD50 was scored by protoscolex death. Cellular and ultrastructural changes within the parasite were studied by light and electron microscopy, mitochondrial DNA (mtDNA) damage and copy number were measured by QPCR, and apoptosis was determined by caspase 3 expression and caspase 3 activity. Ionizing radiation induced sparse cytoplasm, disorganized and clumped organelles, large vacuoles and devoid of villi. The initial mtDNA damage caused by ionizing radiation increased in a dose-dependent manner. The kinetic of DNA repair was slower after carbon-ion radiation than that after X-rays radiation. High dose carbon-ion radiation caused irreversible mtDNA degradation. Cysts apoptosis was pronounced after radiation. Carbon-ion radiation was more effective to suppress hydatid cysts than X-rays. Conclusions These studies provide a framework to the evaluation of attenuation effect of heavy-ion radiation on cystic echinococcosis in vitro. Carbon-ion radiation is more effective to suppress E. multilocularis than X-rays.
Saccharomyces cerevisiae BUR6 encodes a DRAP1/NC2alpha homolog that has both positive and negative roles in transcription in vivo

BUR3 and BUR6 were identified previously by selecting for mutations that increase transcription from an upstream activating sequence (UAS)-less promoter in Saccharomyces cerevisiae. The bur3-1 and bur6-1 mutations are recessive, increase transcription from a suc2 delta uas allele, and cause other mutant phenotypes, suggesting that Bur3p and Bur6p function as general repressors of the basal transcriptional machinery. The molecular cloning and characterization of BUR3 and BUR6 are presented here. BUR3 is identical to MOT1, a previously characterized essential gene that encodes an ATP-dependent inhibitor of the TATA box-binding protein. Cloning and nucleotide sequence analysis reveals that BUR6 encodes a homolog of DRAP1 (also called NC2alpha), a mammalian repressor of basal transcription. Strains that contain a bur6 null allele are viable but grow extremely poorly, demonstrating that BUR6 is critical for normal cell growth in yeast. The Bur6p histone fold domain is required for function; an extensive nonoverlapping set of deletion alleles throughout the histone fold domain impairs BUR6 function in vivo, whereas mutations in the amino- and carboxy-terminal tails have no detectable effect. BUR6 and BUR3/MOT1 have different functions depending on promoter context: although the bur3-1 and bur6-1 mutations increase transcription from delta uas promoters, they result in reduced transcription from the wild-type GAL1 and GAL10 promoters. This transcriptional defect is due to the inability of the GAL10 UAS to function in bur6-1 strains. The similar phenotypes of bur6 and bur3 (mot1) mutations suggest that Bur6p and Mot1p have related, but not identical, functions in modulating the activity of the general transcription machinery in vivo.
A Closed-Form Solution to Retinex with Nonlocal Texture Constraints

We propose a method for intrinsic image decomposition based on retinex theory and texture analysis. While most previous methods approach this problem by analyzing local gradient properties, our technique additionally identifies distant pixels with the same reflectance through texture analysis, and uses these nonlocal reflectance constraints to significantly reduce ambiguity in decomposition. We formulate the decomposition problem as the minimization of a quadratic function which incorporates both the retinex constraint and our nonlocal texture constraint. This optimization can be solved in closed form with the standard conjugate gradient algorithm. Extensive experimentation with comparisons to previous techniques validate our method in terms of both decomposition accuracy and runtime efficiency.
Housing as a Measure for Long-Run Risk in Asset Pricing

I use a non-separable utility function with non-housing consumption and consumption of housing services, which generates an intertemporal composition risk, besides the traditional consumption growth risk. The composition risk has effects for the valuation of cash flow growth fluctuations far into the future due to the persistence of consumption growth and housing services growth. I provide a closed form solution for the valuation function despite the non-separability. This allows me to quantify the price of risk in the long-run with inputs from an indirect inference estimation of the endowment process. I evaluate the different exposure to long-run risk of a cross section of portfolios of securities, and characterize the price of risk for different investment horizons. The model also explains the spread of the returns to different portfolios sorted in book to market and required housing returns, at different investment horizons.
Live demonstration: Unipolar symmetrical variable-capacitance generators for energy harvesting

This demonstration shows a variable-capacitance electrostatic generator made with 3D-printing techniques powering loads through a DC/DC converter. The generator is similar in structure to a microelectromechanical device, and forms an unstable electrostatic generator when connected to a 2-phase diode-capacitor voltage multiplier. As load, a simple bidirectional digital wireless communication system is used.
High-yield production of short GpppA- and 7MeGpppA-capped RNAs and HPLC-monitoring of methyltransfer reactions at the guanine-N7 and adenosine-2′O positions

Many eukaryotic and viral mRNAs, in which the first transcribed nucleotide is an adenosine, are decorated with a cap-1 structure, 7MeG5′-ppp5′-A2′OMe. The positive-sense RNA genomes of flaviviruses (Dengue, West Nile virus) for example show strict conservation of the adenosine. We set out to produce GpppA- and 7MeGpppA-capped RNA oligonucleotides for non-radioactive mRNA cap methyltransferase assays and, in perspective, for studies of enzyme specificity in relation to substrate length as well as for co-crystallization studies. This study reports the use of a bacteriophage T7 DNA primase fragment to synthesize GpppACn and 7MeGpppACn (1 ≤ n ≤ 9) in a one-step enzymatic reaction, followed by direct on-line cleaning HPLC purification. Optimization studies show that yields could be modulated by DNA template, enzyme and substrate concentration adjustments and longer reaction times. Large-scale synthesis rendered pure (in average 99%) products (1 ≤ n ≤ 7) in quantities of up to 100 nmol starting from 200 nmol cap analog. The capped RNA oligonucleotides were efficient substrates of Dengue virus (nucleoside-2′-O-)-methyltransferase, and human (guanine-N7)-methyltransferase. Methyltransfer reactions were monitored by a non-radioactive, quantitative HPLC assay. Additionally, the produced capped RNAs may serve in biochemical, inhibition and structural studies involving a variety of eukaryotic and viral methyltransferases and guanylyltransferases.