Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional muscle and adipose tissue amino acid metabolism in lean and obese women.

The effect of obesity on regional skeletal muscle and adipose tissue amino acid metabolism is not known. We evaluated systemic and regional (forearm and abdominal subcutaneous adipose tissue) amino acid metabolism, by use of a combination of stable isotope tracer and arteriovenous balance methods, in five lean women [body mass index (BMI) <25 kg/m(2)] and five women with abdominal obesity (BMI 35.0-39.9 kg/m(2); waist circumference >100 cm) who were matched on fat-free mass (FFM). All subjects were studied at 22 h of fasting to ensure that the subjects were in net protein breakdown during this early phase of starvation. Leucine rate of appearance in plasma (an index of whole body proteolysis), expressed per unit of FFM, was not significantly different between lean and obese groups (2.05 +/- 0.18 and 2.34 +/- 0.04 micromol x kg FFM(-1) x min(-1), respectively). However, the rate of leucine release from forearm and adipose tissues in obese women (24.0 +/- 4.8 and 16.6 +/- 6.5 nmol x 100 g(-1) x min(-1), respectively) was lower than in lean women (66.8 +/- 10.6 and 38.6 +/- 7.0 nmol x 100 g(-1) x min(-1), respectively; P < 0.05). Approximately 5-10% of total whole body leucine release into plasma was derived from adipose tissue in lean and obese women. The results of this study demonstrate that the rate of release of amino acids per unit of forearm and adipose tissue at 22 h of fasting is lower in women with abdominal obesity than in lean women, which may help obese women decrease body protein losses during fasting. In addition, adipose tissue is a quantitatively important site for proteolysis in both lean and obese subjects.
Microstructural aspects of rolling deformation in ultrafine-grained copper

Abstract Ultrafine-grained (UFG) copper produced by severe plastic deformation demonstrates an unusual combination of high strength and rather high ductility at room temperature. To obtain the UFG microstructure, the equal channel angular extrusion technique was used in the current work. The microstructure, crystallographic texture and grain boundary distributions were studied in as received and cold-rolled samples. The microstructures and textures generated by rolling of the UFG sample were compared with those formed in identically rolled conventional coarse-grained copper. Rolling to 83° resulted in drastic changes of all microstructural parameters owing to the transformation of the microstructure with initially equiaxed grains into a banded microstructure with mainly elongated and subdivided grains having orientations typical of a rolling texture. Additional rolling led to the strengthening of the main texture components. The emergence of cube oriented {001}(100) grains was distinguished in the rolled .
Cosmic String Loops, Large and Small

We extend our earlier model of the small-scale structure of cosmic string networks through an improved treatment of the separation of long and short scales. We find that the production of small loops (at the gravitational radiation scale) is a robust feature of string networks, in addition to a population of loops near the horizon scale. We obtain quantitative agreement with the scaling of loop production functions as found in simulations by two groups.
Localized Support Vector Machine and Its Efficient Algorithm

Nonlinear Support Vector Machines employ sophisticated kernel functions to classify data sets with complex decision surfaces. Determining the right parameters of such functions is not only computationally expensive, the resulting models are also susceptible to overfitting due to their large VC dimensions. Instead of fitting a nonlinear model, this paper presents a framework called Localized Support Vector Machine (LSVM), which builds multiple linear SVM models from the training data. Since each model is designed to classify a particular test example, it has high computational cost. To overcome this limitation, we propose an efficient implementation of LSVM, termed Profile SVM (PSVM). PSVM partitions the training examples into clusters and builds a separate linear SVM model for each cluster. Our empirical results show that (1) Both LSVM and PSVM outperform nonlinear SVM on the majority of the evaluated data sets; and (2) PSVM achieves comparable accuracy as LSVM but with significant computational savings.
Health Behaviors and Racial Disparity in Blood Pressure Control in the National Health and Nutrition Examination Survey

Minorities have a higher prevalence of hypertension, a major risk factor for cardiovascular disease, which contributes to racial/ethnic disparities in morbidity and mortality in the United States. Many modifiable health behaviors have been associated with improved blood pressure control, but it is unclear how racial/ethnic differences in these behaviors are related to the observed disparities in blood pressure control. Cross-sectional analyses were conducted among 21 489 US adults aged >20 years participating in the National Health and Nutrition Examination Survey from 2001 to 2006. Secondary analyses were conducted among those with a self-reported diagnosis of hypertension. Blood pressure control was defined as systolic values <140 mm Hg and diastolic values <90 mm Hg (or <130 mm Hg and <80 mm Hg among diabetics, respectively). In primary analyses, non-Hispanic blacks had 90% higher odds of poorly controlled blood pressure compared with non-Hispanic whites after adjustment for sociodemographic and clinical characteristics (P<0.001). In secondary analyses among hypertensive subjects, non-Hispanic blacks and Mexican Americans had 40% higher odds of uncontrolled blood pressure compared with non-Hispanic whites after adjustment for sociodemographic and clinical characteristics (P<0.001). For both analyses, the racial/ethnic differences in blood pressure control persisted even after further adjustment for modifiable health behaviors, which included medication adherence in secondary analyses (P<0.001 for both analyses). Although population-level adoption of healthy behaviors may contribute to reduction of the societal burden of cardiovascular disease in general, these findings suggest that racial/ethnic differences in some health behaviors do not explain the disparities in hypertension prevalence and control.
LINE-1 Endonuclease-Dependent Retrotranspositional Events Causing Human Genetic Disease: Mutation Detection Bias and Multiple Mechanisms of Target Gene Disruption

LINE-1 (L1) elements are the most abundant autonomous non-LTR retrotransposons in the human genome. Having recently performed a meta-analysis of L1 endonuclease-mediated retrotranspositional events causing human genetic disease, we have extended this study by focusing on two key issues, namely, mutation detection bias and the multiplicity of mechanisms of target gene disruption. Our analysis suggests that whereas an ascertainment bias may have generally militated against the detection of autosomal L1-mediated insertions, autosomal L1 direct insertions could have been disproportionately overlooked owing to their unusually large size. Our analysis has also indicated that the mechanisms underlying the functional disruption of target genes by L1-mediated retrotranspositional events are likely to be dependent on several different factors such as the type of insertion (L1 direct, L1 trans-driven Alu, or SVA), the precise locations of the inserted sequences within the target gene regions, the length of the inserted sequences, and possibly also their orientation.
Effects of composite viscosity and adhesive curing mode on marginal sealing of restorations

Abstract Objectives: Evaluate the influence of composite viscosity, adhesive systems curing mode and artificial aging on marginal sealing of composite resin restorations. Methods: 240 cavities were prepared in bovine incisors. Teeth were divided in two groups: GR – GrandioSO (Voco), conventional viscosity and GF – GrandioSO Heavy Flow (Voco), low viscosity. Each group was divided into 6 subgroups: FM – Futura Bond M (Voco), FDCL and FDCC – Futura Bond DC (Voco), light and chemical cured, CS – Clearfil S3 Bond (Kuraray), CDCL and CDCC – Cleafil DC (Kuraray), light and chemical cured. Half of all specimens were subjected to mechanical (300.000) and thermal cycling (1.000). Marginal gap was measured in an optical microscope. For microleakage, specimens were stained in 50% ammoniacal silver nitrate. Results: For marginal gap mean (μm), significant differences were shown for all factors (p = 0.000). Results for resin were GR: 28.1 and GF: 40.6; for adhesive CDCC: 28.67, CDCL: 32.25, CS: 34.12, FDCL: 36.10, FM: 36.50 and FDCC: 38.46; and for artificial aging WITHOUT: 29.05 and WITH: 39.65. For microleakage mean (mm), there were also differences for all factors (p = 0.000). Results for resin were GR: 2.68 and GF: 3.46; for adhesive FM: 2.85, CDCC: 3.00, FDCL: 3.08, CDCL: 3.15, CS: 3.16 and FDCC: 3.19; and for artificial aging WITHOUT: 2.66 and WITH: 3.48. Conclusion: Composite with conventional viscosity resulted in narrower marginal gaps and less microleakage. CDCC showed less marginal gap formation. The presence of thermo-mechanical cycling increased the values of gap and microleakage.
Discontinuous Statistical Machine Translation with Target-Side Dependency Syntax

For several languages only potentially non-projective dependency parses are readily available. Projectivizing the parses and utilizing them in syntax-based translation systems often yields particularly bad translation results indicating that those translation models cannot properly utilize such information. We demonstrate that our system based on multi bottom-up tree transducers, which can natively handle discontinuities, can avoid the large translation quality deterioration, achieve the best performance of all classical syntax-based translation systems, and close the gap to phrase-based and hierarchical systems that do not utilize syntax.
Edward: A library for probabilistic modeling, inference, and criticism

Probabilistic modeling is a powerful approach for analyzing empirical information. We describe Edward, a library for probabilistic modeling. Edward's design reflects an iterative process pioneered by George Box: build a model of a phenomenon, make inferences about the model given data, and criticize the model's fit to the data. Edward supports a broad class of probabilistic models, efficient algorithms for inference, and many techniques for model criticism. The library builds on top of TensorFlow to support distributed training and hardware such as GPUs. Edward enables the development of complex probabilistic models and their algorithms at a massive scale.
Intelligent Methods of Fusing the Knowledge During Incremental Learning via Clustering in A Distributed Environment

One of the ways of learning from the data which is physically distributed over multiple locations is to have a common learning mechanism at each of the source and knowledge of each of the learnt concepts has to be transmitted to a centralized location for assimilation. In this research, clustering is employed as a mechanism of learning and a cluster is viewed as a concept which is described by a set of variables. The set of variables which describes each of the clusters is being referred to as a knowledge packet (KP). As histograms have the generic ability to characterize any type of data, a histogram based regression line has been used as one of the variable to describe a KP. For online monitoring of the progression in learning apart from achieving computational ease and efficacy, the KPs at the centralized location are fused incrementally to get the overall knowledge. If learning mechanisms employed are data sequence sensitive, different combinations of merging the thus generated KP s may result in altogether a different overall knowledge. Further, the distance measure employed to find distance between the KPs in obtaining the optimal sequence of merging, may also result in a different overall knowledge. This phenomenon is being referred to as the problem of order effect. To minimize or avoid the order effect , a density based spatial clustering of applications with noise (DBSCAN) algorithm, which is insensitive to the order of presentation of data samples is used to learn from the data chunks and a novel methodology of finding the distance between the batches of data and there by finding the more optimal sequence of merging the KPs is presented. A specially designed distance measure for histogram based objects (histo-objects) is employed to find distance between the KPs and the nearest KPs are merged incrementally till certain conditions are satisfied. The proposed methods provide a robust mechanism of avoiding order effects. Since it is difficult to get the real distributed datasets, effectiveness of the proposed approaches is demonstrated with a carefully designed synthetic dataset. Some of the bench mark datasets were modified to simulate the distributed environment and experimentations with some of them show an accuracy of up to 100%.
A randomized controlled educational intervention on emergency contraception among drugstore personnel in southern Thailand.

OBJECTIVE to document the effectiveness of an educational intervention in improving knowledge of and practice in dispensing emergency contraception (EC) among drugstore personnel in Thailand. METHODS Sixty of 120 drugstores in Hat Yai, a city in Southern Thailand, were randomly selected, and half of them were randomly assigned to participate in an educational program. Well-trained "secret" shoppers went into each store before the intervention and at 1 and 3 months after the program to assess the knowledge of and practice in dispensing EC among the drugstore personnel. RESULTS Dispensing practices at baseline were poor to fair and knowledge was fair in both groups. Sellers in the intervention group improved significantly in choice of drug, advice provided, and knowledge of the time limit for initiating EC, but those in the control group did not. However, proper history taking on the time of intercourse and menstrual cycle was poor in both groups at all study periods. CONCLUSION All drugstore personnel should be educated on the importance of history taking and on the time limit for initiating EC.
TLR4–MD-2 complex is negatively regulated by an endogenous ligand, globotetraosylceramide

Although endogenous ligands for Toll-like receptor (TLR)4–myeloid differentiation factor 2 (MD2) have not been well-understood, we here report that a globo-series glycosphingolipid, globotetraosylceramide (Gb4), attenuates the toxicity of lipopolysaccharides (LPSs) by binding to TLR4–MD-2. Because α1,4-galactosyltransferase (A4galt)-deficient mice lacking globo-series glycosphingolipids showed higher sensitivity to LPS than wild-type mice, we examined mechanisms by which globo-series glycosphingolipids attenuate LPS toxicity. Cultured endothelial cells lacking A4galt showed higher expression of LPS-inducible genes upon LPS treatment. In turn, introduction of A4galt cDNA resulted in the neo expression of Gb4, leading to the reduced expression of LPS-inducible genes. Exogenous Gb4 induced similar effects. As a mechanism for the suppressive effects of Gb4 on LPS signals, specific binding of Gb4 to the LPS receptor TLR4–MD-2 was demonstrated by coprecipitation of Gb4 with recombinant MD-2 and by native PAGE. A docking model also supported these data. Taken together with colocalization of TLR4–MD-2 with Gb4 in lipid rafts after LPS stimulation, it was suggested that Gb4 competes with LPS for binding to TLR4–MD-2. Finally, administration of Gb4 significantly protected mice from LPS-elicited mortality. These results suggest that Gb4 is an endogenous ligand for TLR4–MD-2 and is capable of attenuating LPS toxicity, indicating the possibility for its therapeutic application in endotoxin shock.
Fault resilient physical neural networks on a single chip

Device scaling engineering is facing major challenges in producing reliable transistors for future electronic technologies. With shrinking device sizes, the total circuit sensitivity to both permanent and transient faults has increased significantly. Research for fault tolerant processors has primarily focused on the conventional processor architectures. Neural network computing has been employed to solve a wide range of problems. This paper presents a design and implementation of a physical neural network that is resilient to permanent hardware faults. To achieve scalability, it uses tiled neuron clusters where neuron outputs are efficiently forwarded to the target neurons using source based spanning tree routing. To achieve fault resilience in the face of increasing number of permanent hardware failures, the design proactively preserves neural network computing performance by selectively replicating performance critical neurons. Furthermore, the paper presents a spanning tree recovery solution that mitigates disruption to distribution of neuron outputs caused by failed neuron clusters. The proposed neuron cluster design is implemented in Verilog. We studied the fault resilience performance of the described design using a RBM neural network trained for classifying handwritten digit images. Results demonstrate that our approach can achieve improved fault resilience performance by replicating only 5% most important neurons.
Flow aggregation for enhanced TCP over wide-area wireless

Throughout the world, GSM cellular mobile networks are being upgraded to support the "always-on" General Packet Radio Service (GPRS). Despite the apparent availability of levels of bandwidth not dissimilar to that provided by conventional fixed-wire telephone modems, the user experience using GPRS is currently considerably worse. In this paper we examine the performance of TCP and HTTP over GPRS, and show how certain network characteristics interact badly with TCP to yield problems such as: link under-utilization for short-lived flows, excess queueing for long-lived flows, ACK compression, poor loss recovery, and gross unfairness between competing flows. We present the design and implementation of a transparent TCP proxy that mitigates many of these problems without requiring any changes to the TCP implementations in either mobile or fixed-wire end systems. The proxy transparently splits TCP connections into two halves, the wired and wireless sides. Connections destined for the same mobile host are treated as an aggregate due to their statistical dependence. We demonstrate packet scheduling and flow control algorithms that use information shared between the connections to maximise performance of the wireless link while inter-working with unmodified TCP peers. We also demonstrate how fairness between flows and response to loss is improved, and that queueing and hence network latency is reduced. We conclude that installing such a proxy into GPRS network would be of significant benefit to users.
Do we really need 24-h observation for patients with minimal brain injury and small intracranial bleeding? The Bernese Trauma Unit Protocol

Background Traumatic brain injury is one of the most common reasons for admission to hospital emergency departments. However, optimal diagnosis and treatment protocols remain controversial. The aim of this study is to assess whether a specific group of patients can be discharged from the hospital without 24-h neurological observation. Methods Retrospective analysis was performed for 1078 patients with a minor isolated head injury admitted to the authors' Emergency Department for 24-h observation. Exclusion criteria included intracranial bleeds with maximum diameter above 5 mm or multiple (>1) bleeds, a history of inherited coagulopathy or anticoagulant therapy, platelet aggregation inhibitor therapy, intoxication or multiple associated injuries. Furthermore, patients who had no-one to observe them at home or who lived more than 1 h away were excluded from the study. Results 110 patients presented with an isolated small intracranial bleed (<5 mm) with a Glasgow Coma Scale (GCS) of 13–15. Of these patients, 46% exhibited small intracerebral haematomas, 23% traumatic subarachnoid haematomas, 9% epidural haematomas and 7% subdural haematomas. Nine patients presented with a GCS of 13/15, 30 patients with a GCS 14/15 and 71 patients with a GCS 15/15. 85% of all patients regained GCS 15/15 within 1 h after admission and 15% within 2 h after admission. All patients maintained their GCS 15/15 over the 24-h period. Conclusions Standard 24-h observation may not be required for adult patients with single intracranial bleeds with maximum diameter less than 5 mm, without a history of inherited coagulopathy or anticoagulant therapy, platelet aggregation inhibitor therapy, intoxication or multiple associated injuries. The decision for discharging patients may be made from the clinical picture. This might help to spare hospital resources and reduce unnecessary hospitalisations.
Predicting Medication Persistence to Buprenorphine Transdermal System

Persistence, the duration a patient remains on therapy, in chronic, symptomatic conditions plays an important role in therapy effectiveness. Understanding the duration and patient factors associated with prescribed medication persistence is, therefore, an important step toward better treatment and health outcomes for patients. In the following study, an analysis of such factors associated with buprenorphine transdermal system (BTDS) persistence was conducted utilizing a large US private practitioner and pharmacy claims database and is herein reported.
Efficient Processing of Nested Fuzzy SQL Queries in a Fuzzy Database

In a fuzzy relational database where a relation is a fuzzy set of tuples and ill-known data are represented by possibility distributions, nested fuzzy queries can be expressed in the Fuzzy SQL language. Although it provides a very convenient way for users to express complex queries, a nested fuzzy query may be very inefficient to process with the naive evaluation method based on its semantics. In conventional databases, nested queries are unnested to improve the efficiency of their evaluation. In this paper, we extend the unnesting techniques to process several types of nested fuzzy queries. An extended merge-join is used to evaluate the unnested fuzzy queries. As shown by both theoretical analysis and experimental results, the unnesting techniques with the extended merge-join significantly improve the performance of evaluating nested fuzzy queries.
Agility and Quality Attributes in Open Source Software Projects Release Practices

Context: The need to accelerate software delivery, supporting faster time-to-market and frequent community developers/ users feedback are issues that have lead to relevant changes in software development practices. Many Open Source Software (OSS) projects have engaged to achieve this through the adoption of agile practices in software release practices. Problem: There is no secondary study in the literature discussing evidences of the influence of agile approaches in OSS projects release practices. Goal: Identify published reports in the literature that characterize to which extent agility has influenced release approaches in OSS projects. Method: The characterization of studies followed a fivephase process to present a panoramic view of software releases practices in the context of OSS projects. Results: The overall data collected from 14 studies published from January 2006 to January 2016 depicted the following scenario: nine issues that characterize the advantages/influence of agility in OSS release approaches; four challenge issues in this approach; three possibilities of implementation and two main motivations towards the adoption of software release approaches through agility; and finally three main strategies to implement it. Conclusion: This study provides an up-to-date and structured understanding of the influence of agility on OSS projects release approaches based on findings systematically collected from a list of relevant references in the last decade.