Miracle-dz/UniFAR-FTUs huggingface dataset:
Angular Anisotropies in the Cosmic Gamma-Ray Background as a Probe of Its Origin

Notwithstanding the advent of the Gamma-ray Large Area Space Telescope, theoretical models predict that a significant fraction of the cosmic γ-ray background (CGB), at a level of 20% of the currently measured value, will remain unresolved. The angular power spectrum of intensity fluctuations of the CGB contains information on its origin. We show that probing the latter on scales from a few tens of arcminutes to several degrees, together with complementary GLAST observations of γ-ray emission from galaxy clusters and the blazar luminosity function, can discriminate between a background that originates from unresolved blazars or cosmic rays accelerated at structure formation shocks.
Refining Susceptibility Loci of Chronic Obstructive Pulmonary Disease with Lung eqtls

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of mortality worldwide. Recent genome-wide association studies (GWAS) have identified robust susceptibility loci associated with COPD. However, the mechanisms mediating the risk conferred by these loci remain to be found. The goal of this study was to identify causal genes/variants within susceptibility loci associated with COPD. In the discovery cohort, genome-wide gene expression profiles of 500 non-tumor lung specimens were obtained from patients undergoing lung surgery. Blood-DNA from the same patients were genotyped for 1,2 million SNPs. Following genotyping and gene expression quality control filters, 409 samples were analyzed. Lung expression quantitative trait loci (eQTLs) were identified and overlaid onto three COPD susceptibility loci derived from GWAS; 4q31 (HHIP), 4q22 (FAM13A), and 19q13 (RAB4B, EGLN2, MIA, CYP2A6). Significant eQTLs were replicated in two independent datasets (n = 363 and 339). SNPs previously associated with COPD and lung function on 4q31 (rs1828591, rs13118928) were associated with the mRNA expression of HHIP. An association between mRNA expression level of FAM13A and SNP rs2045517 was detected at 4q22, but did not reach statistical significance. At 19q13, significant eQTLs were detected with EGLN2. In summary, this study supports HHIP, FAM13A, and EGLN2 as the most likely causal COPD genes on 4q31, 4q22, and 19q13, respectively. Strong lung eQTL SNPs identified in this study will need to be tested for association with COPD in case-control studies. Further functional studies will also be needed to understand the role of genes regulated by disease-related variants in COPD.
Prenatal Alcohol Use and Fetal Alcohol Spectrum Disorder in Indiana

Maternal alcohol use during pregnancy can have deleterious effects. Alcohol in the mother’s blood passes through the placenta to the embryo and fetus via the umbilical cord, and may cause numerous problems, including developmental delays, growth impairment, and a variety of behavioral changes [1]. Compared to all other substances of abuse, including heroin, cocaine, and marijuana, alcohol produces by far the most serious neurobehavioral effects in the fetus [2]. In 2005, the U.S. Department of Health and Human Services’ Office of the Surgeon General released an advisory to warn pregnant women and women who may become pregnant to abstain from drinking alcohol to eliminate the risk of alcohol-related birth defects. The advisory was an update from the 1981 release which initially only suggested that pregnant women limit the amount of alcohol they drink [3]. The update was issued because based on the most current research, no amount of alcohol consumption can be considered safe during pregnancy, and damages to the fetus can occur during any gestational stage. Drinking increases the risk of alcohol-related growth deficiencies and birth defects, including facial abnormalities and central nervous system impairment. In addition, drinking during pregnancy has been linked to behavioral disorders and impaired intellectual development in the child; these cognitive deficits and behavioral problems are lifelong [3, 4]. This has also been substantiated by Healthy People 2020, which designated the prevention of alcohol-exposed pregnancies a public health priority, urging women of childbearing age (ages 15 to 44) to abstain from drinking alcoholic beverages [5]. Since there is no safe time to consume alcohol during pregnancy, women should not drink alcohol if they are planning to become pregnant or are sexually active and do not use effective birth control [4]. Consumption of alcohol during pregnancy can cause the infant to be born with a fetal alcohol spectrum disorder (FASD). FASD is not a diagnosis, but an umbrella term that describes a group of conditions associated with prenatal alcohol exposure, including fetal alcohol syndrome (FAS) [6]. FAS is the most severe and widely known type of FASD. Jones et al. (1973) were the first to coin the term “FAS” and systematically describe the pattern of malformations in children of mothers who drank significant amounts of alcohol during pregnancy [7, 8]. In addition to FASD, prenatal alcohol consumption can also lead to other complications such as miscarriages, preterm births, and stillbirths [9, 10]. Since FASD and all other alcohol-related outcomes are the result of maternal drinking during pregnancy, these consequences are completely preventable.
Stability of Software Defect Prediction in Relation to Levels of Data Imbalance

Software defect prediction is recognized as one of the most important ways to reach software development efficiency. The majority of costs during software development is spent on software defect detection activities, but their ability to guarantee software reliability is still limited. The analyses performed by [Andersson and Runeson 2007; Fenton and Ohlsson 2000; Galinac Grbac et al. 2013], in the environment of a large scale industrial software with high focus on reliability shows that faults are distributed within the system according to the Pareto principle. They prove that the majority of faults are concentrated in just small amount of system modules, and that these modules do not compose a majority of system size. This fact implies that software defect prediction would really bring benefits if a well performing model is applied. The main motivating idea is that if we were able to predict the location of software faults within the system, then we could plan defect detection activities more efficiently. This means that we would be able to concentrate defect detection activities and resources into critical locations within the system and not on the entire system. Numerous studies have already been performed aiming to find the best general software defect prediction model [Hall et al. 2012]. Unfortunately, a well performing solution is still absent. Data in software defect prediction are very complex, and do not follow in general any particular probability distribution that could provide a mathematical model. Data distributions are highly skewed, which is connected to the popular data imbalance problem, thus making standard machine learning approaches inadequate. Therefore, a significant research has recently been devoted to cope with this problem.
Technical Perspective:: Toward Building Entity Matching Management Systems

Entity matching (EM) has been a long-standing challenge in data management. Most current EM works focus only on developing matching algorithms. We argue that far more efforts should be devoted to building EM systems. We discuss the limitations of current EM systems, then describe Magellan, a new kind of EM system. Magellan is novel in four important aspects. (1) It provides how-to guides that tell users what to do in each EM scenario, step by step. (2) It provides tools to help users execute these steps; the tools seek to cover the entire EM pipeline, not just blocking and matching as current EM systems do. (3) Tools are built into the Python open-source data science ecosystem, allowing Magellan to borrow a rich set of capabilities in data cleaning, IE, visualization, learning, etc. (4) Magellan provides a powerful scripting environment to facilitate interactive experimentation and quick "patching" of the system. We describe research challenges and present extensive experiments that show the promise of the Magellan approach.
Haematological, Biochemical and Histopathological Alterations Induced by Abamectin and Bacillus Thuringiensis in Male Albino Rats

The renal- and hepato-toxicity induced by abamectin pesticide (Vertimec) and a commercial form of a bio-insecticide Bacillus thuringiensis (Agerin) in male albino rats were evaluated. Blood picture and blood glucose level were investigated. Male albino rats were administered dietary doses each equivalent to 1/10 or 1/100 of the LD_50 values of each toxicant for 30 consecutive days. Abamectin was found to pose risks of renal- and hepato-toxicity in rats, since the biochemical parameters of liver function (i.e. aspartate aminotransferase activity, alanine aminotransferase activity, acid phosphatase activity, albumin, and total protein levels) and kidney function (uric acid and creatinine concentration) were severely affected. These effects were verified by histopathological examination of liver and kidney tissues. Likewise, some haematological indices (i.e. erythrocyte count, leukocyte count and haemoglobin concentration) were also influenced; in addition abamectin might cause hypoglycaemia. On the other hand, the above-mentioned lesions were less pronounced in the case of Bacillus thuringiensis -treated rats.
Extracellular Ca2+ modulates leukocyte function-associated antigen-1 cell surface distribution on T lymphocytes and consequently affects cell adhesion

Transition of leukocyte function-associated antigen-1 (LFA-1), from an inactive into an activate state depends on the presence of extracellular Mg2+ and/or Ca2+ ions. Although Mg2+ is directly involved in ligand binding, the role of Ca2+ in LFA-1 mediated adhesion remained obscure. We now demonstrate that binding of Ca2+, but not Mg2+, directly correlates with clustering of LFA-1 molecules at the cell surface of T cells, thereby facilitating LFA-1-ligand interaction. Using a reporter antibody (NKI-L16) that recognizes a Ca(2+)-dependent epitope on LFA-1, we found that Ca2+ can be bound by LFA-1 with different strength. We noticed that weak binding of Ca2+ is associated with a dispersed LFA-1 surface distribution on T cells and with non- responsiveness of these cells to stimuli known to activate LFA-1. In contrast, stable binding of Ca2+ by LFA-1 correlates with a patch-like surface distribution and vivid ligand binding after activation of LFA- 1. Mg(2+)-dependent ligand binding does not affect binding of Ca2+ by LFA-1 as measured by NKI-L16 expression, suggesting that Mg2+ binds to a distinct site, and that both cations are important to mediate adhesion. Only Sr2+ ions can replace Ca2+ to express the L16 epitope, and to induce clustering of LFA-1 at the cell surface. We conclude that Ca2+ is involved in avidity regulation of LFA-1 by clustering of LFA-1 molecules at the cell surface, whereas Mg2+ is important in regulation of the affinity of LFA-1 for its ligands.
A socio-perceptual/ecological approach to lexical development: affordances of the communicative context

Basic assumptions crucial to the innatist position influence researchers to ignore the source of language input, its characteristics, and its impact on language development. However, a key assumption of the socio-perceptual/ecological approach is the idea that the emergence of language depends on the dynamic structure of the social-interactive environment in which the infant develops. To support and illustrate this perspective, evidence from a series of studies examining the social and perceptual bases of the emergence of the lexicon is marshalled to support and illustrate this perspective. Parallel arguments can and ought to be constructed to explain other aspects of language learning.
Electronic Helping Behavior: The Virtual Presence of Others Makes a Difference

Years of research have demonstrated that the physical presence of others can reduce the tendency to help individuals needing assistance. This study examined whether the diffusion of responsibility phenomenon extends beyond face-to-face environments and helps explain the lack of responsiveness often demonstrated by Internet users who receive e-mail requests sent to multiple people simultaneously. Participants were sent an e-mail message requesting assistance with an online library search task. Each person received the message along with an indication that 0, 1, 14, or 49 others were also contacted. The results demonstrated partial support for the study hypothesis. As expected, the virtual presence of many others significantly reduced e-mail responsiveness; however, nonresponse did not directly increase in proportion with group size.
Adaptive Skinning for Interactive Hair-Solid Simulation

Reduced hair models have proven successful for interactively simulating a full head of hair strands, building upon a fundamental assumption that only a small set of guide hairs are needed for explicit simulation, and the rest of the hair move coherently and thus can be interpolated using guide hairs. Unfortunately, hair-solid interactions is a pathological case for traditional reduced hair models, as the motion coherence between hair strands can be arbitrarily broken by interacting with solids. In this paper, we propose an adaptive hair skinning method for interactive hair simulation with hair-solid collisions. We precompute many eligible sets of guide hairs and the corresponding interpolation relationships that are represented using a compact strand-based hair skinning model. At runtime, we simulate only guide hairs; for interpolating every other hair, we adaptively choose its guide hairs, taking into account motion coherence and potential hair-solid collisions. Further, we introduce a two-way collision correction algorithm to allow sparsely sampled guide hairs to resolve collisions with solids that can have small geometric features. Our method enables interactive simulation of more than 150 K hair strands interacting with complex solid objects, using 400 guide hairs. We demonstrate the efficiency and robustness of the method with various hairstyles and user-controlled arbitrary hair-solid interactions.
Golden Eggs and Hyperbolic Discounting

Hyperbolic discount functions induce dynamically inconsistent preferences, implying a motive for consumers to constrain their own future choices. This paper analyzes the decisions of a hyperbolic consumer who has access to an imperfect commitment technology: an illiquid asset whose sale must be initiated one period before the sale proceeds are received. The model predicts that consumption tracks income, and the model explains why consumers have asset-specific marginal propensities to consume. The model suggests that financial innovation may have caused the ongoing decline in U. S. savings rates, since financial innovation in- creases liquidity, eliminating commitment opportunities. Finally, the model implies that financial market innovation may reduce welfare by providing â€œtoo muchâ€ liquidity.
Mean-Field SDE Driven by a Fractional Brownian Motion and Related Stochastic Control Problem

We study a class of mean-field stochastic differential equations driven by a fractional Brownian motion with Hurst parameter $H\in(1/2,1)$ and a related stochastic control problem. We derive a Pontryagin type maximum principle and the associated adjoint mean-field backward stochastic differential equation driven by a classical Brownian motion, and we prove that under certain assumptions, which generalize the classical ones, the necessary condition for the optimality of an admissible control is also sufficient.
The assessment of surgical competence

Procedural skill forms a large component of surgical practice, and carries a significant influence on patient outcomes. The process of assessing the skill and competence is fraught with complications. With the division of surgical training into ever-smaller segments and the impact of reduced working hours on clinical development, it is becoming important to divide each procedure into its constituent parts. This conforms to Peyton’s model for the teaching of practical skills and leads to faster and more effective education (Krautter et al. 2011), and as each component is ‘‘signed off’’ individually, a trainee can be safely assumed to be able to perform a procedure consisting of previously taught components. Global rating in order to evaluate performance and competence at a specific procedure represents the alternative approach, with the philosophy being that each procedure is more than the mere sum of its parts. It does necessitate that each procedure be evaluated separately. One can argue that the most valuable assessment for a speciality trainee is whether they can safely and competently perform the procedures asked of them. As a summative assessment, it can be valued more than a detailed feedback process. The simplicity of the global rating and its inherent ease of use lend to it a universal appeal, resulting in continued use. The disadvantage is the reduced educational value; a trainee may know that they require further training, but not which area to focus on. Procedural-based assessments [PBAs] have a clear advantage of breaking the procedure into the constituent parts and affording more detailed feedback to the trainee regarding their exact level. The application of PBAs to assessments allows a formative as well as a summative evaluation (Beard et al. 2009). Overcoming the taxing and time consuming workload of PBAs, as well as the volume of information can be achieved by a combination of an understanding trainer, who gives feedback in smaller more digestible portions, and through using the PBA in parts. Performing the entire PBA may not always be appropriate. It is my opinion that these assessments can act to supplement each other, supplementing each other’s strengths and providing cross-cover to overcome weakness. The ideal may be to use PBAs with the addition of a global rating score to give an overall review point, enabling both trainer and trainee to have a handle on the assessment process.
The allergenic relevance of profilin (Ole e 2) from Olea europaea pollen

Many works have dealt with the study of the allergenic relevance of profilin from allergenic extracts, mainly derived from pollens and vegetable foods. Olive pollen extracts also contain a profilin allergen (Ole e 2). This protein has been characterized in detail, so the aminoacid sequence of three isoforms and the structural model of one of them are already known. The prevalence of Ole e 2 for olive allergenic patients has been evaluated by different in vivo and in vitro methods, and the results compared with those obtained for another pollen profilins.
Spontaneous Activity of Solitary Dopaminergic Cells of the Retina

Dopaminergic interplexiform amacrine cells were labeled in transgenic mice with human placental alkaline phosphatase and could therefore be identified after dissociation of the retina and used for whole-cell current and voltage clamp. In absence of synaptic inputs, dopaminergic amacrines spontaneously fired action potentials in a rhythmic pattern. This activity was remarkably robust in the face of inhibition of various voltage-dependent ion channels. It was minimally affected by external cesium or cobalt, suggesting no involvement of either the hyperpolarization-activated cation currentIh or voltage-dependent calcium channels. Inhibiting calcium-activated potassium channels by charybdotoxin or tetraethylammonium slowed the repolarizing phase of the action potentials and eliminated a slow afterhyperpolarization but had a scarce effect on the frequency of spontaneous firing. Voltage-clamp experiments showed that the interspike depolarization leading to threshold results from tetrodotoxin-sensitive sodium channels active at the interspike voltages of −60 to −40 mV. Because dopamine acts on distant targets in the retina, the pacemaker activity of dopaminergic amacrines may be necessary to ensure a tonic release of the modulator from their dendritic tree. Pacemaking is a property that this type of retinal amacrine cell shares with the dopaminergic mesencephalic neurons, but the ionic mechanisms responsible for the spontaneous firing are apparently different.
Dengue Virus Infections among Haitian and Expatriate Non-governmental Organization Workers — Léogane and Port-au-Prince, Haiti, 2012

In October 2012, the Haitian Ministry of Health and the US CDC were notified of 25 recent dengue cases, confirmed by rapid diagnostic tests (RDTs), among non-governmental organization (NGO) workers. We conducted a serosurvey among NGO workers in Léogane and Port-au-Prince to determine the extent of and risk factors for dengue virus infection. Of the total 776 staff from targeted NGOs in Léogane and Port-au-Prince, 173 (22%; 52 expatriates and 121 Haitians) participated. Anti-dengue virus (DENV) IgM antibody was detected in 8 (15%) expatriates and 9 (7%) Haitians, and DENV non-structural protein 1 in one expatriate. Anti-DENV IgG antibody was detected in 162 (94%) participants (79% of expatriates; 100% of Haitians), and confirmed by microneutralization testing as DENV-specific in 17/34 (50%) expatriates and 42/42 (100%) Haitians. Of 254 pupae collected from 68 containers, 65% were Aedes aegypti; 27% were Ae. albopictus. Few NGO workers reported undertaking mosquito-avoidance action. Our findings underscore the risk of dengue in expatriate workers in Haiti and Haitians themselves.
Analysis of learned features for remote sensing image classification

Convolutional neural networks (convnets) have shown excellent results in various image classification tasks. Part of the success can be attributed to good image representations that are extracted using convolutional layers of the network. In this paper we consider convnets from the perspective of feature extraction for remote sensing image classification. We analyze the impact of convolutional feature extraction as well as the role of feature learning on the ability of features to discriminate between land cover classes. The quantitative analysis is based on measuring both classification accuracy and discriminative ability of features. For the latter we use Fisher discriminant analysis and show that features extracted using convolutional layers with random weights have significant discriminative ability and result in a reasonable baseline for remote sensing image classification, which suggests that convolutional feature extraction itself is an important ingredient of feature extraction in convnets. Using learned convnets for feature extraction further improves discriminative ability of features.
Immunoregulation by Mesenchymal Stem Cells: Biological Aspects and Clinical Applications

Mesenchymal stem cells (MSCs) are multipotent cells capable of differentiation into mesenchymal lineages and that can be isolated from various tissues and easily cultivated in vitro. Currently, MSCs are of considerable interest because of the biological characteristics that confer high potential applicability in the clinical treatment of many diseases. Specifically, because of their high immunoregulatory capacity, MSCs are used as tools in cellular therapies for clinical protocols involving immune system alterations. In this review, we discuss the current knowledge about the capacity of MSCs for the immunoregulation of immunocompetent cells and emphasize the effects of MSCs on T cells, principal effectors of the immune response, and the immunosuppressive effects mediated by the secretion of soluble factors and membrane molecules. We also describe the mechanisms of MSC immunoregulatory modulation and the participation of MSCs as immune response regulators in several autoimmune diseases, and we emphasize the clinical application in graft versus host disease (GVHD).