Miracle-dz/UniFAR-FTUs huggingface dataset:
Accuracy, Memory, and Speed Strategies in GPU-Based Finite-Element Matrix-Generation

This letter presents strategies on how to optimize graphics processing unit (GPU)-based finite-element matrix-generation that occurs in the finite element method (FEM) using higher-order curvilinear elements. The goal of the optimization is to increase the speed of evaluation and assembly of large finite-element matrices on a single GPU while maintaining the accuracy of numerical integration at the desired level. For this reason, the choice of the optimal Gaussian quadratures for curvilinear finite elements focused on accuracy, memory usage, and runtime of numerical integration is discussed. Moreover, we show how to efficiently utilize symmetry of local mass and stiffness matrices on a GPU in the numerical integration step. The performance results, obtained on a workstation equipped with one Tesla C2075, indicate that the proposed strategies retain the accuracy of computations, allow generation of larger sparse linear systems, and provide 2.5-fold acceleration of GPU-based finite-element matrix-generation.
Norepinephrine Modulates Myelopoiesis After Experimental Thermal Injury With Sepsis

ObjectiveTo determine whether thermal injury and sepsis cause an increase in bone marrow norepinephrine release and whether such a release influences bone marrow monocytopoiesis. Summary Background DataThe authors previously demonstrated enhanced bone marrow monocytopoiesis after burn with sepsis. They also showed that physiologic stress and bacterial challenge without injury could lead to a dynamic release of norepinephrine from the bone marrow compartment. In this study, they sought to determine the potential cause-and-effect relationship of bone marrow norepinephrine release on increased monocytopoiesis after burn sepsis. MethodsNorepinephrine release from bone marrow was determined by traditional pulse-chase methods. Tissue and bone marrow norepinephrine content was ablated by chemical sympathectomy with 6-hydroxydopamine treatment. Clonogenic potential in response to colony-stimulating factors was determined in total nucleated bone marrow cells. Dual color flow cytometry was used to document the distribution pattern of monocyte progenitors. ResultsBurn sepsis induced increased norepinephrine release in bone marrow, spleen, and heart. Colony-forming assays demonstrated an increase in responsive colonies, which was significantly attenuated when norepinephrine content was reduced in animals before burn sepsis. Flow cytometric analysis of early and late monocyte progenitors showed a significantly altered distribution profile of monocyte progenitors in norepinephrine-depleted mice compared with norepinephrine-intact mice. Abrogation of bone marrow norepinephrine content resulted in a 62% survival rate in burn septic mice compared with no survivors in norepinephrine-intact mice. ConclusionsThese data suggest that enhanced bone marrow norepinephrine release after burn sepsis may play a role in bone marrow monocytopoiesis, thus contributing to the sustenance of inflammation.
Association of the Asp1312Gly Thyroglobulin Gene Polymorphism with Susceptibility to Differentiated Thyroid Cancer in an Iranian Population

Background and aim: While the causes of thyroid cancer in most patients remain largely unknown, it has recently been reported that there may be links to particular chromosome regions. In particular, polymorphisms (SNPs) in the thyroglobulin (TG) gene could be susceptibility factors. Methods: In this case-control study, any association of the Asp1312Gly single nucleotide polymorphism (SNP) in the TG gene (rs2069556) with susceptibility to differentiated thyroid cancer (DTC) was investigated among 103 Iranian patients and 100 controls who had no history of any type of cancer. Genomic DNA was extracted from the whole blood by salting out procedure. High Resolution Melting (HRM) technique was used to detect this SNP. Results: Data were analyzed with SPSS software and the results showed that the recessive GG genotype was associated with an increased risk of differentiated thyroid carcinoma when compared to the AA+AG genotypes (OR: 2.06; CI: 1.09-3.89; P-value: 0.025). Conclusion: Although our study demonstrated that differentiated thyroid cancer is significantly associated with this polymorphism, further studies with larger populations are required to confirm our findings.
Quantifying dimensions in autism: a factor-analytic study.

OBJECTIVE The objective of this study was to determine whether the phenotypic variation in autism and the related pervasive developmental disorders (PDDs) is a unitary construct or whether it is composed of distinct dimensions of autistic symptoms and measures of level of functioning. METHOD One hundred twenty-nine children with autism and other forms of PDD from two samples with different inclusion criteria were assessed with the Vineland Adaptive Behavior Scales to measure level of functioning and the Autism Diagnostic Interview to measure severity of autistic behaviors. A factor analysis with varimax rotation was performed on each sample, separately and combined. RESULTS Two factors emerged; one representing autistic symptoms and another representing level of functioning. The factor structure was remarkably similar and robust to variations in ascertainment and inclusion criteria between the samples. The validity of the distinction was supported by differences between males and females on the symptom factor, but not on the level of functioning factor. IQ was modestly correlated with level of functioning, but not with symptoms. CONCLUSIONS The phenotypic variation seen in autism/PDD is composed of at least two different dimensions of autistic symptoms and level of functioning. The implications of this dimensional heterogeneity for research, classification, and clinical practice are discussed.
Visual cues for data mining

This paper describes a set of visual techniques, based on principles of human perception and cognition, which can help users analyze and develop intuitions about tabular data. Collections of tabular data are widely available, including, for example, multivariate time series data, customer satisfaction data, stock market performance data, multivariate profiles of companies and individuals, and scientific measurements. In our approach, we show how visual cues can help users perform a number of data mining tasks, including identifying correlations and interaction effects, finding clusters and understanding the semantics of cluster membership, identifying anomalies and outliers, and discovering multivariate relationships among variables. These cues are derived from psychological studies on perceptual organization, visual search, perceptual scaling, and color perception. These visual techniques are presented as a complement to the statistical and algorithmic methods more commonly associated with these tasks, and provide an interactive interface for the human analyst.
Lifetime risk of suicide for affective disorder, alcoholism and schizophrenia

Background The lifetime risks of suicide are generally quoted as 15% for affective disorder and alcoholism and 10% for schizophrenia, based on data from 1921–1975 and on calculations performed before computerised modelling techniques became available. This study recalculates the risk using contemporary data and modern techniques. Method Twenty-seven mortality studies provided data for affective disorder, 27 for alcohol dependence and 29 for schizophrenia. The proportion of the cohort who had died was plotted against the proportion of deaths from suicide. Modelling techniques fitted curves through the data points extrapolating them to cohort extinction, thus estimating the lifetime risk of suicide for each disorder. Results The lifetime risk was estimated at 6% for affective disorder, 7% for alcohol dependence and 4% for schizophrenia. Conclusions The lifetime suicide risk figures often quoted in the literature appear to be too high.
Modeling of cooling process under critical conditions due to liquid evaporation

The model of heat exchange process in the flat plate, which surface during the fist stage dissipates heat only due to convection, but when temperature becomes critical, the liquid is supplied on the surface of the plate, and evaporating cools the plate, has been built. The solution of the model problem has been found by the numerical method. The analysis of transient changes of the temperature fields have been made.
Gender differences in depression: a study of older unlike-sex twins

Gender differences in depressive symptoms, in the diagnosis of major/minor depression, and in the use of antidepressant medication were investigated. The sample included 249 pairs of unlike-sex twins, who were between 70 and 80 years of age at the initial, baseline assessment. A follow-up, in which both members of 145 twin pairs participated, was carried out four years later. Participants completed the Centre for the Epidemiologic Studies Depression Scale (CES-D) for depressive symptoms. Current use of antidepressant medicine was assessed. Medical records of major/minor depression from the period 1985–1998, including a summary of those diagnoses in earlier years, were gathered from several sources. Women had a higher frequency of depressive symptoms and depression diagnoses than their twin brothers. Depressive symptoms and diagnosis of depression increased over time, slightly more among men. The gender difference and increase over time in the depressive symptoms were related to differences in socio-economic status and physical functioning in men and women. No gender difference was found in the use of antidepressant medication.
EVs charging and discharging model consisted of EV users behaviour

This paper proposes a new approach for forecasting the coordinated Electric Vehicles (EVs) charging and discharging that minimizes the EVs charging cost, based on the day-ahead electricity price (DAEP) subject to the EVs state of charge (SOC) limits, the EVs maximum power charger, the EVs batteries full charging at the end of the charging period. Besides, the EVs initial state of charge (SOC0) has been calculated based on the EVs daily driving mileage, while Latin Hypercube Sampling (LHS) has been applied to deal with the EVs arrival, departure time and SOC0 uncertainties. The proposed optimal strategy enables EVs users to make a profit of 14.79€ while they need 2.17€ to charge their EVs in the uncoordinated scenario. Furthermore, the comparison between the real and the estimated results show that the charging cost based on the real SOC0 values is 2.88% and 27% higher than the charging cost based on the estimated SOC0 values for coordinated and uncoordinated scenarios respectively.
Online environmental adaptation of CNN-based acoustic models using spatial diffuseness features

We propose a new concept for adapting CNN-based acoustic models using spatial diffuseness features as auxiliary information about the acoustic environment: the spatial diffuseness features are simultaneously employed as acoustic-model input features and to estimate environmental cues for context adaptation, where one convolutional layer is factorized into several sub-layers to represent different acoustic conditions. This context-adaptive CNN-based acoustic model facilitates an online environmental adaptation and is experimentally verified for the real-world recordings provided by the CHiME-3 task. The best performing setup reduces the average word error rate scores achieved by the baseline system (without using spatial diffuseness features) from 19.4% to 15.9% and 12.2% to 10.7% considering two experimental setups with and without front-end signal enhancement, respectively.
Sigma-1 Receptor Plays a Negative Modulation on N-type Calcium Channel

The sigma-1 receptor is a 223 amino acids molecular chaperone with a single transmembrane domain. It is resident to eukaryotic mitochondrial-associated endoplasmic reticulum and plasma membranes. By chaperone-mediated interactions with ion channels, G-protein coupled receptors and cell-signaling molecules, the sigma-1 receptor performs broad physiological and pharmacological functions. Despite sigma-1 receptors have been confirmed to regulate various types of ion channels, the relationship between the sigma-1 receptor and N-type Ca2+ channel is still unclear. Considering both sigma-1 receptors and N-type Ca2+ channels are involved in intracellular calcium homeostasis and neurotransmission, we undertake studies to explore the possible interaction between these two proteins. In the experiment, we confirmed the expression of the sigma-1 receptors and the N-type calcium channels in the cholinergic interneurons (ChIs) in rat striatum by using single-cell reverse transcription-polymerase chain reaction (scRT-PCR) and immunofluorescence staining. N-type Ca2+ currents recorded from ChIs in the brain slice of rat striatum was depressed when sigma-1 receptor agonists (SKF-10047 and Pre-084) were administrated. The inhibition was completely abolished by sigma-1 receptor antagonist (BD-1063). Co-expression of the sigma-1 receptors and the N-type calcium channels in Xenopus oocytes presented a decrease of N-type Ca2+ current amplitude with an increase of sigma-1 receptor expression. SKF-10047 could further depress N-type Ca2+ currents recorded from oocytes. The fluorescence resonance energy transfer (FRET) assays and co-immunoprecipitation (Co-IP) demonstrated that sigma-1 receptors and N-type Ca2+ channels formed a protein complex when they were co-expressed in HEK-293T (Human Embryonic Kidney -293T) cells. Our results revealed that the sigma-1 receptors played a negative modulation on N-type Ca2+ channels. The mechanism for the inhibition of sigma-1 receptors on N-type Ca2+ channels probably involved a chaperone-mediated direct interaction and agonist-induced conformational changes in the receptor-channel complexes on the cell surface.
Laboratory Tests for the Diagnosis of Thrombotic Disorders

Diagnosis of thrombotic disorders depends on the performance of a panel of laboratory tests for individual components of the coagulation mechanism. Although genetic tests are simple and accurate, most disorders still require functional or immunologic tests for diagnosis. Tests for the most important thrombotic defects are described. These tests may be significantly altered by pregnancy, hormones, thrombotic events, systemic illness, and anticoagulant therapy. These changes make some thrombotic disorders difficult to diagnose during pregnancy. Testing before pregnancy for women with a personal or family history of thrombosis will simplify the interpretation.
Indoor positioning system based on the improved W-KNN algorithm

With the continuous development of intelligent terminal technology, the demand for Location Based Services (LBS) is also increased. Thus, the research of indoor positioning technology is of great significance. Based on the characteristic of the mobile positioning terminal and the presence of the AP in the indoor positioning environment, the indoor location fingerprint algorithm is the most feasible method due to its stable performance without the need for additional hardware. However, the traditional methods do not take the weight of the composition into consideration, which actually affects the precision of positioning much. In this paper, an improved algorithm based on weighted K-nearest neighbors (W-KNN) is proposed. In the off-line stage, the algorithm filters out invalid data by using data expectation, and selects the mean of RSS and the variance of access points (APs) as the eigenvector. In the on-line stage, according to the variance of APs, the weighted distance is proposed to calculate the similarity. Meanwhile, the nearest main neighbor and (K-1) auxiliary neighbors are obtained by comparing the weighted distance. Using the correlation between main neighbor and (K-1) auxiliary neighbors, the location is derived. Experimental results show that the precision of the proposed algorithm is better than that of using the RSSI location fingerprinting algorithm alone in the indoor environment.
Point Cloud Normal Estimation with Graph-Convolutional Neural Networks

Surface normal estimation is a basic task for many point cloud processing algorithms. However, it can be challenging to capture the local geometry of the data, especially in presence of noise. Recently, deep learning approaches have shown promising results. Nevertheless, applying convolutional neural networks to point clouds is not straightforward, due to the irregular positioning of the points. In this paper, we propose a normal estimation method based on graph-convolutional neural networks to deal with such irregular point cloud domain. The graph-convolutional layers build hierarchies of localized features to solve the estimation problem. We show state-ofthe-art performance and robust results even in presence of noise.
Equilibrium Points in N-Person Games.

One may define a concept of an n -person game in which each player has a finite set of pure strategies and in which a definite set of payments to the n players corresponds to each n -tuple of pure strategies, one strategy being taken for each player. For mixed strategies, which are probability distributions over the pure strategies, the pay-off functions are the expectations of the players, thus becoming polylinear forms …
Improving chemical synthesis using flow reactors

Owing to the competitive nature of the pharmaceutical industry, researchers involved in lead compound generation are under continued pressure to identify and develop promising programmes of research in order to secure intellectual property. The potential of a compound for therapeutic development depends not only on structural complexity, but also on the identification of synthetic strategies that will enable the compound to be prepared on the desired scale. One approach that is of present interest to the pharmaceutical industry is the use of continuous flow reactors, with the flexible nature of the technology being particularly attractive as it bridges the changes in scale required between the initial identification of a target compound and its subsequent production. Based on these factors, a significant programme of research is presently underway into the development of flow reactors as tools for the synthetic chemist, with the transfer of many classes of reaction successfully reported to date. This article focuses on the application of continuous flow methodology to drug discovery and the subsequent production of pharmaceuticals.
Comparison of methods to efficient graph SLAM under general optimization framework

Simultaneous Localization and Mapping(SLAM) algorithms can infer the robot's trajectory as well as the map under unknown environment. Robust and time-efficient optimization methods are important requirements for SLAM. There are many algorithms designed for the graph optimization. However, it is hard to select an appropriate algorithm and corresponding software library, due to the difficulty of evaluating algorithms' adaptabilities under various situations. In this paper, we summarize these algorithms under general optimization framework, conduct several sets of experiments to compare these algorithms in three software libraries, and give some suggestions to choose algorithms.
Risk Status Identification During the Takeover of Conditionally Automated Vehicles

In order to identify the risk status during the takeover from automated driving to manual driving in dangerous traffic situations, this study investigated their performance during the takeover based on PreScan. The experiment invited 38 drivers. They all held a valid driving license. A risk status identification model was proposed based on the information of vehicle status and traffic environment status. According to the rate of electrocardiogram(ECG) and the performance of takeover, the risk status was classified into three levels. Using Pearson correlation coefficient algorithm, seven factors were selected as the feature set. Then, the algorithm of Random Forest (RF) was employed to establish the takeover risk status identification model. The results show that the accuracy of RF is 98.8%, increasing 10.4%, 17.7% and 7.3% compared with Support Vector Machine (SVM), Classification and Regression Tree (CART) and Back Propagation Neural Network, and each risk level has good prediction results. Respectively, the results show that the space headway, longitudinal acceleration and lane departure have a great influence on the risk level, and the space headway has the strongest impact on the degree of danger during the takeover of control in Conditionally Automated Vehicles.
Synthesis, physico-chemical characteristics and cellular behavior of poly (lactic-co-glycolic acid)/ gelatin nanofibrous scaffolds for engineering soft connective tissues

There have been several attempts to synthesis biodegradable polymeric constructs with adequate porous structures for soft connective tissues. In this study, randomly-oriented PLGA-gelatin nanofibrous scaffolds were synthesized by electrospinning method. We offered an appropriate solvent (2, 2, 2-trifluoroethanol) to dissolve both polymers for achieving a homogenous solution without inducing any toxic effects. The results confirmed the formation of high porous and bead free scaffolds, in which an increase in the injection rate slightly decreased the mechanical, swelling ratio and biodegradation behaviors. The modulus and tensile strength for the scaffolds with the injection rate of 0.2 ml/hr were 0.72 ±0.02 and 2.70 ±0.33, respectively. In addition, the evaluation of cell proliferation demonstrated that L929 fibroblast cells spread well on the scaffolds, indicating that they are able to support cell attachment. A possible chemical bond formation has been also suggested for the blending mixture of PLGA and gelatin molecules. Copyright © 2016 VBRI Press.
Development and evaluation of stavudine niosome by ether injection method

Abstract: The main objective of the present study was to encapsulate Stavudine in niosomes for achieving prolonged release & longer duration of action. Niosome are now widely studied as an alternative delivery system to liposome. An increasing number of non ionic surfactant has been found to form vesicles, capable of entrapping hydrophilic and hydrophobic molecules. stavudine drug has shorter half life, Negligible protein binding. This drawback was decreased by formulating it as niosomes. In our present study we incorporated Stavudine into niosome by using ether injection method. In evaluation study the effect of the varying composition of non ionic surfactant and cholesterol on the properties such as zeta potential, drug content, vesicle size and drug release were studied. The result of the physiochemical characterisation and in vitro permeation studies of the prepared vesicles by dialysis membrane to get the idea of drug release. From the present investigation, it can be concluded that the developed niosome formulation of stavudine has shown great potential in the treatment of HIV by providing a prolonged release profile.
Polymer-doped UHF RFID tag for wireless-sensing of humidity

Passive UHF RFID tags, beside item labelling, are also able to exploit capability of sensing the physical state of the tagged object as well as of the surrounding environment. Here a family of polymer-doped tags are proposed and fully characterized for the detection of ambient humidity. A sensitive chemical species based on PEDOT:PSS is used to dope a properly shaped slot carved into a folded-like patch tag. The communication and sensing capabilities of the radio-sensor are investigated by means of simulation and measurements showing how to control and balance above opposite requirements by dosing the quantity of sensitive material. The device could have interesting application in the assessment of the air quality in living and controlled rooms, in the monitoring of the conservation state of foods, in the preservation of walls, and even to monitor the healing degree of wounds.