Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Terrestrial Water Storage and Flood Potential Using GRACE Data in the Yangtze River Basin, China

Floods have caused tremendous economic, societal and ecological losses in the Yangtze River Basin (YRB) of China. To reduce the impact of these disasters, it is important to understand the variables affecting the hydrological state of the basin. In this study, we used Gravity Recovery and Climate Experiment (GRACE) satellite data, flood potential index (FPI), precipitation data (Tropical Rainfall Measuring Mission, TRMM 3B43), and other meteorological data to generate monthly terrestrial water storage anomalies (TWSA) and to evaluate flood potential in the YRB. The results indicate that the basin contained increasing amounts of water from 2003 to 2014, with a slight increase of 3.04 mm/year in the TWSA. The TWSA and TRMM data exhibit marked seasonal characteristics with summer peaks and winter dips. Estimates of terrestrial water storage based on GRACE, measured as FPI, are critical for understanding and predicting flooding. The 2010 flood (FPI ~ 0.36) was identified as the most serious disaster during the study period, with discharge and precipitation values 37.95% and 19.44% higher, respectively, than multi-year average values for the same period. FPI can assess reliably hydrological extremes with high spatial and temporal resolution, but currently, it is not suitable for smaller and/or short-term flood events. Thus, we conclude that GRACE data can be effectively used for monitoring and examining large floods in the YRB and elsewhere, thus improving the current knowledge and presenting potentially important political and economic implications.
Rev. Latino-am. Enfermagem Original Article Quality of Life in the Workplace for Nursing Staff at Public Healthcare Institutions 1

Objective: to determine the quality of life in the workplace for nursing staff at public institutions in We used a probabilistic sample of 345 nurses with data collected in 2013 using an instrument created by the authors to gather bio-socio-demographic data and the CVT–GOHISALO instrument with a Cronbach's alpha of 0.95. SPSS 15 was used to analyze the data. A Kolmogorov-Smirnov test was used to calculate the normality of the data; the medians were compared using the Mann-Whitney U test and Kruskal-Wallis test with the significance level set at 0.05. Results: the average overall quality of life in the workplace for nursing staff was 207.31 (DE 41.74), indicating a moderate level. The quality of life in the workplace was higher for people with permanent contracts (p=0.007) who did not engage in other remunerative activities (p=0.046). Differences in the quality of life in the workplace were observed depending on the institution where the subjects worked (p=0.001). Conclusion: the nursing staff perceives itself as having a moderate-level quality of life in the workplace. This level was determined in the statistical analysis based on the type of contract, whether the person performed other remunerated activities, and the institution where the person worked. Introduction Quality of life in the workplace is a multidimensional concept that applies when the employee is able to cover the following personal necessities through employment or his or her own ventures: institutional support, security and integration into his or her role at work and satisfaction related to this role, a sense of wellbeing obtained through his or her work and the personal development achieved, and the management of his or her free time (1). This concept has been used with increasing frequency to describe certain environmental and humanistic values that are neglected by industrial societies in their pursuit of technological advancement, productivity, and economic growth (2). Among healthcare professionals, quality of life in the workplace ought to meet the highest standards because these professionals appear to have the knowledge and the means necessary to avoid risks and perform self-care activities in all areas. However, various studies underscore that this ideal is far from the reality. Convincing evidence exists that healthcare professionals are faced with various problems. In the specific case of nursing, employees have developed pathologies including Burnout Syndrome, workplace stress, conflicts related to violence within healthcare institutions (directed at both clients and the nursing staff itself), indices of poor …
L1-L1 norms for face super-resolution with mixed Gaussian-impulse noise

In real world surveillance application, the captured faces are often low resolution (LR) and corrupted by mixed Gaussian-impulse noise during the acquisition and transmission processes. In this paper, we propose an effective patch-based face super-resolution method to reconstruct a high resolution (HR) face image given an LR observation that is corrupted by mixed Gaussian-impulse noise. To represent the corrupted image patches, a sparse regularization combined with an l\ data fitting term is proposed. In the proposed model, both the patch reconstruction term and the regularization term are in the l\ norm form. As a result, the model is called norms. In addition, since image pixels have nonnegative intensities, we further add a nonnegative constraint to the patch representation model. Experimental results demonstrate that the proposed norms based method can achieve superior face super-resolution performance over several state-of-the-art approaches based on the objective results in terms of P-SNR, as well as the visual perceptual quality.
Grammatical Evolution for the Multi-Objective Integration and Test Order Problem

Search techniques have been successfully applied for solving different software testing problems. However, choosing, implementing and configuring a search technique can be hard tasks. To reduce efforts spent in such tasks, this paper presents an offline hyper-heuristic named GEMOITO, based on Grammatical Evolution (GE). The goal is to automatically generate a Multi-Objective Evolutionary Algorithm (MOEA) to solve the Integration and Test Order (ITO) problem. The MOEAs are distinguished by components and parameters values, described by a grammar. The proposed hyper-heuristic is compared to conventional MOEAs and to a selection hyper-heuristic used in related work. Results show that GEMOITO can generate MOEAs that are statistically better or equivalent to the compared algorithms.
Fabrication and Characterization of AISI 420 Stainless Steel Using Selective Laser Melting

Selective laser melting (SLM) offers great possibilities to fabricate metal tools with a complex geometry, but there are limitations regarding some materials. This work focuses on the fabrication of AISI 420 stainless steel using SLM for the application of plastic injection mold. The melt characteristic of the powders was firstly concluded, and then the microstructure, phase composition, and hardness were characterized using scanning electron microscopy, X-ray diffraction, and Rockwell hardness test, respectively. The results showed that cellular microstructure was observed along the direction of the maximum heat flow. The proportion of the phases varies with the change of SLM processing parameters, which directly affects on the hardness of the parts. The relative density over 99% was obtained and the highest hardness presents 50.7 HRC, which meets the requirement of plastic injection molding application.
Planning Bike Lanes based on Sharing-Bikes' Trajectories

Cycling as a green transportation mode has been promoted by many governments all over the world. As a result, constructing effective bike lanes has become a crucial task for governments promoting the cycling life style, as well-planned bike paths can reduce traffic congestion and decrease safety risks for both cyclists and motor vehicle drivers. Unfortunately, existing trajectory mining approaches for bike lane planning do not consider key realistic government constraints: 1) budget limitations, 2) construction convenience, and 3) bike lane utilization. In this paper, we propose a data-driven approach to develop bike lane construction plans based on large-scale real world bike trajectory data. We enforce these constraints to formulate our problem and introduce a flexible objective function to tune the benefit between coverage of the number of users and the length of their trajectories. We prove the NP-hardness of the problem and propose greedy-based heuristics to address it. Finally, we deploy our system on Microsoft Azure, providing extensive experiments and case studies to demonstrate the effectiveness of our approach.
Exploiting correlations among channels in distributed compressive sensing with convolutional deep stacking networks

This paper addresses the compressive sensing with Multiple Measurement Vectors (MMV) problem where the correlation amongst the different sparse vectors (channels) are used to improve the reconstruction performance. We propose the use of Convolutional Deep Stacking Networks (CDSN), where the correlations amongst the channels are captured by a moving window containing the "residuals" of different sparse vectors. We develop a greedy algorithm that exploits the structure captured by the CDSN to reconstruct the sparse vectors. Using a natural image dataset, we compare the performance of the proposed algorithm with two types of reconstruction algorithms: Simultaneous Orthogonal Matching Pursuit (SOMP) which is a greedy solver and the model-based Bayesian approaches that also exploit correlation among channels. We show experimentally that our proposed method outperforms these popular methods and is almost as fast as the greedy methods.
Lower bounds for Auslander's representation dimension

The notion of representation dimension of a finite dimensional algebra has been introduced by Auslander. He has shown that an algebra is of finite representation type if and only if its representation dimension is at most two. He has expected that the representation dimension of a representation infinite algebra should measure how far this algebra is from being representation finite. In many cases, and, thanks to Iyama, also in general, upper bounds for the representation dimension are known. However there are non-trivial lower bounds only for two (similarly constructed) series of algebras. In this thesis new lower bounds for Auslander’s representation dimension are constructed, and more general methods are developed. First we consider group algebras of elementary abelian groups. We show that their representation dimension is greater than the rank of the group. This leads to a proof of a conjecture of Benson concerning the Loewy length of blocks of group algebras. Then a notion of dimension of a module category is introduced. This notion enables us to find better lower bounds for the representation dimension. In particular it allows us for the first time to determine the value of the representation dimension of non-self-injective algebras of representation dimension greater than three. Finally we give a general criterion for finding lower bounds for Auslander’s representation dimension: Suppose there is a family of modules, such that sufficiently many members of the family have certain d-extensions. Then the representation dimension of the algebra is at least d + 2. We illustrate how this criterion is applied on some interesting families of algebras. It turns out that the lower bound is often the precise value of the representation dimension.
Some Graphical Aids for Deciding When to Stop Testing Software

It is noted that the developers of large software systems must decide how much software should be tested before releasing it. An explicit tradeoff between the costs of testing and releasing is considered. The former may include the opportunity cost of continued testing, and the latter may include the cost of customer dissatisfaction and of fixing faults found in the field. Exact stopping rules were obtained by Dalal and Mallows (J. Amer., Statist. Assoc., vol.83, p.872, 1988), under the assumption that the distribution of the fault finding rate is known. Here, two important variants where the fault finding distribution is not completely known are considered. They are (i) the distribution is exponential with unknown mean and (ii) the distribution is locally exponential with the rate changing smoothly over time. New procedures for both cases are presented. In case (i) it is shown how to incorporate information from related projects and subjective inputs. Several novel graphical procedures which are easy to implement are proposed, and these are illustrated for data from a large telecommunications software system. >
Temperature Thresholds and Thermal Requirements for the Development of the Rice Leaf Folder, Cnaphalocrocis medinalis

Abstract The rice leaf folder, Cnaphalocrocis medinalis Guenée (Lepidoptera: Pyralidae) is a predominant foliage feeder in all the rice ecosystems. The objective of this study was to examine the development of leaf folder at 7 constant temperatures (18, 20, 25, 30, 32, 34, 35° C) and to estimate temperature thresholds and thermal constants for the forecasting models based on heat accumulation units, which could be developed for use in forecasting. The developmental periods of different stages of rice leaf folder were reduced with increases in temperature from 18 to 34° C. The lower threshold temperatures of 11.0, 10.4, 12.8, and 11.1° C, and thermal constants of 69, 270, 106, and 455 degree days, were estimated by linear regression analysis for egg, larva, pupa, and total development, respectively. Based on the thermodynamic non-linear optimSSI model, intrinsic optimum temperatures for the development of egg, larva, and pupa were estimated at 28.9, 25.1 and 23.7° C, respectively. The upper and lower threshold temperatures were estimated as 36.4° C and 11.2° C for total development, indicating that the enzyme was half active and half inactive at these temperatures. These estimated thermal thresholds and degree days could be used to predict the leaf folder activity in the field for their effective management.
Cell Fusion Activity of Hepatitis C Virus Envelope Proteins

ABSTRACT To examine the cell fusion activity of hepatitis C virus (HCV) envelope proteins (E1 and E2), we have established a sensitive cell fusion assay based on the activation of a reporter gene as described previously (O. Nussbaum, C. C. Broder, and E. A. Berger, J. Virol. 68:5411–5422, 1994). The chimeric HCV E1 and E2 proteins, each consisting of the ectodomain of the E1 and E2 envelope protein and the transmembrane and cytoplasmic domains of the vesicular stomatitis virus G glycoprotein, were expressed on the cell surface. Cells expressing the chimeric envelope proteins and T7 RNA polymerase were cocultured with the various target cell lines transfected with a reporter plasmid encoding the luciferase gene under the control of the T7 promoter. After cocultivation, the cell fusion activity was determined by the expression of luciferase in the cocultured cells. The induction of cell fusion requires both the chimeric E1 and E2 proteins and occurs in a low-pH-dependent manner. Although it has been shown that HCV E2 protein binds human CD81 (P. Pileri, Y. Uematsu, S. Campagnoli, G. Galli, F. Falugi, R. Petracca, A. J. Weiner, M. Houghton, D. Rosa, G. Grandi, and S. Abrignani, Science 282:938–941, 1998), the expression of human CD81 alone is not sufficient to confer susceptibility to cell fusion in the mouse cell line. Treatment of the target cells with pronase, heparinase, or heparitinase reduced the cell fusion activity induced by the chimeric envelope proteins. These results suggest (i) that both HCV E1 and E2 proteins are responsible for fusion with the endosomal membrane after endocytosis and (ii) that certain protein molecules other than human CD81 and some glycosaminoglycans on the cell surface are also involved in the cell fusion induced by HCV.
Hyperinsulinemia and Macrosomia in the Fetus of the Diabetic Mother

OBJECTIVE To determine 1) whether macrosomia in the fetus of the diabetic mother is related to fetal hyperinsulinemia and 2) whether hyperinsulinemia and macrosomia are related to maternal metabolic control. RESEARCH DESIGN AND METHODS Normal pregnant women (n = 95) were compared with insulin-treated pregnant women (n = 155), who were subdivided according to White's class, hypertension, and mode of delivery. All women were treated to achieve optimal metabolic control. HbA1c was determined at each visit. At delivery, umbilical plasma was analyzed for glucose, insulin antibodies, total insulin, free insulin, C-peptide, proinsulin components, and total and individual amino acids. RESULTS Macrosomia, defined as <2 standard deviation units (97.75%), was found in 10–27% of the diabetic groups. It was not related to maternal mass or size, but was significantly correlated with umbilical total insulin, free insulin, and C-peptide. Proinsulin components were not different among groups. Amino acids also were not different. Glycosylated hemoglobin was a weak predictor of birth weight and fetal hyperinsulinism. CONCLUSIONS Macrosomia in the fetus of the diabetic mother remains inadequately explained. In a large population of pregnant women with strict metabolic control, macrosomia was mainly independent of glycosylated hemoglobin. Nevertheless, fetal hyperinsulinism remains the driving force for excessive fetal growth. The stimulus for fetal insulin excess in humans remains to be defined.
Analysis of somatic mutations in kappa transgenes

We have examined the nature and localization of somatic mutations in three kappa transgenes cloned from IgG-secreting hybridomas. All of the mutations identified were single base substitutions. Mutations were localized to the variable (V) region and its flanking sequences. In every case, the nuclear matrix association region, kappa enhancer, and C gene were spared. These data indicate that the rearranged kappa gene contains the necessary sequences for targeting of the mutation process, and suggest that the observed localization of mutations to the V region reflects the inherent specificity of this mutation process.
Prevalence of distal renal tubular acidosis in primary Sjögren's syndrome.

OBJECTIVES Our objectives were to analyse the prevalence of distal renal tubular acidosis (dRTA) in primary SS (pSS) and to compare a novel urinary acidification test with furosemide and fludrocortisone (FF) with the gold standard ammonium chloride (NH4Cl) to detect dRTA. METHODS Urinary acidification was assessed in 57 pSS patients using NH4Cl and FF. A urinary acidification defect was defined as an inability to reach a urinary pH of <5.3 after NH4Cl. RESULTS The prevalence of complete dRTA (urinary acidification defect with acidosis) was 5% (3/57). All three patients had positive SSA/Ro and SSB/La autoantibodies and impaired kidney function. The prevalence of incomplete dRTA (urinary acidification defect without acidosis) was 25% (14/57). Compared with patients without dRTA, patients with incomplete dRTA had significantly lower venous pH and serum bicarbonate and higher urinary pH. SSB/La antibodies were more prevalent in the dRTA groups (P < 0.05). Compared with NH4Cl, the positive and negative predictive values of FF were 46% and 82%, respectively. Vomiting occurred more often during the urinary acidification test with NH4Cl than with FF (9 vs 0, P < 0.05). CONCLUSION Incomplete dRTA is common in pSS and causes mild acidaemia and higher urinary pH, which may contribute to bone demineralization and kidney stone formation. FF cannot replace NH4Cl in testing urinary acidification in pSS, but may be considered as a screening tool, given its reasonable negative predictive value and better tolerability.
A Study on Biocompatibility of Three Endodontic Sealers: Intensity and Duration of Tissue Irritation

Introduction: Several studies have evaluated the inflammatory reaction triggered by Epiphany (EPH), a contemporary endodontic sealer. However, they used conventional parameters, which need additional analysis to better understand the reactions induced by this sealer compared to other traditional sealers. Methods and Materials: The intensity and time span of tissue irritations for three endodontic sealers were assessed by inflammatory reactions, fibrous capsule measurement and mast cell counts. Tubes containing freshly mixed EPH, AH plus (AHP) and Endofill (ENF) were subcutaneously implanted into the backs of 28 Wistar rats. The side wall of the tube was used as the control. At 14, 21, 42 and 60 days, the connective tissue surrounding the implants (n=7) was stained for histopathological analysis. The Friedman test was applied to compare the results. The level of significance was set at 0.05. Results: At days 14 and 21, a significant difference among the groups was observed, with the ENF showing the worst tissue response (P<0.001). ENF remained the most aggressive sealer at 42 and 60 days, compared with EPH (P<0.05). No differences were found for the fibrous capsule thicknesses among the groups in each period. The number of mast cells per field did not show difference among the sealers at 21 and 60 days. Conclusions: EPH and AHP elicited similar patterns of irritation, as demonstrated by the inflammatory scores and fibrous capsule thicknesses. ENF caused the highest degree of tissue damage. The increase in mast cell counts observed during the early and late periods shows the possibility of late hypersensitivity to the test materials.
Desmocollin 3-mediated Binding Is Crucial for Keratinocyte Cohesion and Is Impaired in Pemphigus*

Desmocollin (Dsc) 1–3 and desmoglein (Dsg) 1–4, transmembrane proteins of the cadherin family, form the adhesive core of desmosomes. Here we provide evidence that Dsc3 homo- and heterophilic trans-interaction is crucial for epidermal integrity. Single molecule atomic force microscopy (AFM) revealed homophilic trans-interaction of Dsc3. Dsc3 displayed heterophilic interaction with Dsg1 but not with Dsg3. A monoclonal antibody targeted against the extracellular domain reduced homophilic and heterophilic binding as measured by AFM, caused intraepidermal blistering in a model of human skin, and a loss of intercellular adhesion in cultured keratinocytes. Because autoantibodies against Dsg1 are associated with skin blistering in pemphigus, we characterized the role of Dsc3 binding for pemphigus pathogenesis. In contrast to AFM experiments, laser tweezer trapping revealed that pemphigus autoantibodies reduced binding of Dsc3-coated beads to the keratinocyte cell surface. These data indicate that loss of heterophilic Dsc3/Dsg1 binding may contribute to pemphigus skin blistering.
Video object segmentation by motion-based sequential feature clustering

Segmentation of video foreground objects from background has many important applications, such as human computer interaction, video compression, multimedia content editing and manipulation. Most existing methods work on image pixels or color segments which are computationally expensive. Some methods require extensive manual inputs, static cameras, and/or rigid scenes. In this paper we propose a fully automatic foreground segmentation method based on sequential clustering of sparse image features. The sparseness makes the method computationally efficient. We use both edge and corner points extracted from each video frame. A joint spatio-temporal linear regression method is developed to compute sparse motion layers of M consecutive frames jointly under the temporal consistency constraint. Once the sparse motion layers have been identified for each frame, the corresponding dense motion layers are created using the Markov Random Field (MRF) model. The MRF model assigns the rest of the image pixels to the motion layers by considering both the color attributes and the spatial relations between each pixel and its surrounding edge/corner points. Experimental evaluations on videos taken by webcams show the effectiveness of the proposed method.