nils-herrmann/clean_scirepeval huggingface dataset:
Friction Coefficient Variation with Sliding Velocity in Copper with Copper Contact

In this paper, by applying analytical method and using experimental method data, the effect of sliding velocity on friction coefficient for contact of copper with copper is investigated. Some equations for obtaining friction coefficient as a function of sliding velocity for contact of copper with copper by applying second analytical method and using experimental method data are achieved. The results have shown, for each duration of rubbing, the existence of an exclusive equation for friction coefficient. The friction coefficient functions that are achieved by second analytical method are shown as a curve that indicates specific friction coefficient for each sliding velocity. Friction coefficient can be used to obtain friction force and stress in contact region of materials. In order to have a suitable design, the amounts of stress and friction force in contact region are required.
Nonlinear residual minimization by iteratively reweighted least squares
Venue: Comput. Optim. Appl.

In this paper we address the numerical solution of minimal norm residuals of nonlinear equations in finite dimensions. We take particularly inspiration from the problem of finding a sparse vector solution of phase retrieval problems by using greedy algorithms based on iterative residual minimizations in the \ell _p$$lp norm, for $1 \le p \le 2$$1<=p<=2. Due to the mild smoothness of the problem, especially for $p \rightarrow 1$$p 1, we develop and analyze a generalized version of iteratively reweighted least squares (IRLS) This simple and efficient algorithm performs the solution of optimization problems involving non quadratic possibly non convex and non smooth cost functions, which can be transformed into a sequence of common least squares problems. The latter can be tackled eventually by more efficient numerical optimization methods. While its analysis has been by now developed in many different contexts (e.g. for sparse vector, low rank matrix optimization, and for the solution of PDE involving p Laplacians) when the model equation is linear, no results are up to now provided in case of nonlinear ones. We address here precisely the convergence and the rate of error decay of IRLS for such nonlinear problems. The analysis of the convergence of the algorithm is based on its reformulation as an alternating minimization of an energy functional. In fact its main variables are the competitors to solutions of the intermediate reweighted least squares problems and their weights. Under a specific condition of coercivity often verified in practice and assumptions of local convexity, we are able to show convergence of IRLS to minimizers of the nonlinear residual problem. For the case where we are lacking the local convexity, we propose an appropriate convexification by quadratic perturbations. Eventually we are able to show convergence of this modified procedure to at least a very good approximation of stationary points of the original problem. In order to illustrate the theoretical results we conclude the paper with several numerical experiments. We first compare IRLS with standard Matlab optimization functions for a simple and easily presentable example. Furthermore we numerically validate our theoretical results in the more complicated framework of phase retrieval problems, which are our main motivation. Finally we examine the recovery capability of the algorithm in the context of data corrupted by impulsive noise where the sparsification of the residual is desired.
Retrospective analysis of Suomi NPP VIIRS radiometric bias for reflective solar bands due to operational calibration changes

A comprehensive analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) radiometric bias relative to Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 data has been performed since early 2012 for selected reflective solar bands. The study suggests that VIIRS bias trends changes over time mainly due to calibration updates and anomalies. Results show nearly consistent biases of 1.7% for M5 (0.672 um) and 2% for M7 (0.865 um) throughout the mission. However, M1 (0.412 um) and M4 (0.555 um) biases are less consistent. While biases for both M1 and M4 fluctuates mostly around 0% M1 shows most frequent short term changes in bias trends, as high as 4% When the bias trends are compared with VIIRS on board calibration based gain trends, there exists a high correlation. In addition, the operational VIIRS data product of NOAA and the reprocessed NASA Land Product Evaluation and Test Element (PEATE) data were compared by trending the radiance ratio. The ratio trends show calibration differences that agree well with bias trends. The comparison of bias with F factors and ratio trends indicates that the frequent changes observed in VIIRS bias trends are primarily caused by calibration updates and anomalies in VIIRS operational calibration. The study suggests that even though the operational VIIRS data archive meets the specification of 2% radiometric uncertainty, reprocessing can improve data quality needed for rigorous scientific applications.
ISOLATION OF STAPHYLOCOCUS AUREUS AND COAGULASE NEGATIVE STAPHYLOCOCCIFORM BOVINE SUBCLINICAL MASTITIS AND THEIR IMPACT ON THE CHEMICAL COMPONENTS OF MILK

This study was conducted to isolate Staphylococcus aureus and Coagulase Negative Staphylococci (CNS) from bovine subclinical mastitis cases and study their effect on chemical composition of milk. A total of 152 milk samples were collected from apparently normal cows from Basrah province, subclinical mastitis (SCM) was detected in 51.97% of tested samples by using California mastitis test (CMT) Staphylococcus aureus and CNS were isolated from 20.25% and 16.45% cases of tested SCM respectively. The affected samples with SCM have high concentrations of fat and protein, the difference from normal samples was statistically highly significant (P <0.001) for fat; lactose was lower in affected samples. The pH of affected samples was higher than that of normal, however, pH of samples containing S. aureus was the highest (7.8375) and the difference was statistically significant (P< 0.05) Antimicrobial susceptibility assay revealed that all isolates were susceptible to chloramphenicol, ciprofloxacin, gentamycin and vancomycin. However, the resistance to oxacillin and penicillin exhibited by CNS and S. aureus were 76.9% 84.6% 62.5% and 68.75% respectively. It have been concluded that, subclinical mastitis caused by Staphylococci(in particular S. aureus) which carried resistance to antibioticsused in human medicine represents a big problem.However, the changes caused by S. aureus and other staphylococci in pH and chemical composition of mastitic milk may reduce the shelf life and processing of the products.
Metabolomic Approaches to Explore Chemical Diversity of Human Breast Milk, Formula Milk and Bovine Milk
Venue: International journal of molecular sciences

Although many studies have been conducted on the components present in human breast milk (HM) research on the differences of chemical metabolites between HM, bovine milk (BM) and formula milk (FM) is limited. This study was to explore the chemical diversity of HM, BM and FM by metabolomic approaches. GC TOFMS and UPLC QTOFMS were applied to investigate the metabolic compositions in 30 HM samples, 20 FM samples and 20 BM samples. Metabolite profiling identified that most of the non esterified fatty acids, which reflected the hydrolysis of triglycerides, were much more abundant in HM than those in FM and BM, except for palmitic acid and stearic acid. The levels of tricarboxylic acid (TCA) intermediates were much higher in FM and BM than those in HM. Each type of milk also showed its unique composition of free amino acids and free carbohydrates. In conclusion, higher levels of non esterified saturated fatty acids with aliphatic tails <16 carbons, monounsaturated fatty acids and polyunsaturated fatty acids and lower levels of TCA intermediates are characteristic of HM, as compared with FM and BM. The content of non esterified fatty acids may reflect the hydrolysis of triglycerides in different milk types.
Botanical drugs in Ayurveda and Traditional Chinese Medicine.
Venue: Journal of ethnopharmacology

ETHNOPHARMACOLOGICAL RELEVANCE China and India have a long history in the therapeutic application of botanical drugs in traditional medicine. Traditional Chinese Medicine (TCM) and Ayurveda are considered as two of the most ancient systems of medicine, with history of more than two millennia. Medicinal plants are the principal medicinal materials used in both these systems.  This review discusses about the histories of Ayurveda and TCM, the common medicinal plants species, the drug processing strategies used, and the current statuses of these traditional systems of medicine (TSM) Through the views presented in this article, we aim to provide a new perspective to herbal drug researchers for expanding and improving the utilization of botanical drugs and their therapeutic applications.  A bibliographic investigation of Chinese and Indian pharmacopoeias, monographs and official websites was performed. Furthermore, information was obtained from scientific databases on ethnobotany and ethno medicines.  The review of Ayurveda and TCM ethno medicine indicates that both these systems have many medicinal materials in common. The studies carried out by the authors for comparison of plants from same genus from both these TSM's have been discussed to further bring focus to the utilization of "qualitatively" similar species which can be utilized and substituted for endangered or economically valued species. The overview of ancient literature and scientific findings for drugs in both these systems suggests that, the botanical drugs used in common and their processing methods can be explored further for extensive utilization in traditional medicine.  This review describes the histories, common medicinal plant species, their processing methods and therapeutic applications in Ayurveda and TCM. The insights provided through this article may be used by herbal drug researchers and pharmacologists for further exploration of botanical drugs from these two traditional systems of medicine.
Tratamiento con solucion salina hipertonica en lactantes hospitalizados con bronquiolitis aguda

Introduccion El edema de las vias aereas y las secreciones mucosas son caracteristicas patologicas predominantes en lactantes con bronquiolitis aguda (BA) La nebulizacion con solucion salina hipertonica al 3% (SSH) puede reducir los cambios patologicos y disminuir la obstruccion de la via aerea. Objetivos Evaluar en lactantes con bronquiolitis aguda la eficacia del uso de SSH para disminuir dias de internacion y mejoria en el score clinico (SC) Material y Metodos Un total de 106 pacientes (edad media de 5,1 6,4 meses) (rango: 1 14 meses) fueron admitidos y reclutados para recibir tratamiento de BA, en tres hospitales: Catedra de Pediatria del Hospital de Clinicas, Hospital Barrio Obrero, Instituto Privado del Nino. Los pacientes fueron internados en sala de internacion comun. El periodo de estudio fue de mayo del 2011 a julio del 2014. Se realizo un ensayo clinico, aleatorizado, controlado y a doble ciego, divididos en 2 grupos para recibir solucion salina hipertonica (SSH) o solucion salina normal (SSN) con Epinefrina. Resultados Los lactantes del grupo SSH tuvieron importante disminucion en los dias de hospitalizacion 1,7+ 0,76 vs 4,9+ 2,3 del grupo SSN, p<0,001. El SC demostro mejoria significante en el grupo SSH comparando con el grupo SSN p<0,001. Conclusiones La solucion salina al 3% con Epinefrina es mas efectiva que la solucion salina normal con Epinefrina en pacientes moderadamente severos con bronquiolitis aguda.
A transformation based approach to testing concurrent programs using UML activity diagrams
Venue: Softw. Pract. Exp.

Unified Modeling Language (UML) activity diagrams are widely used to model concurrent interaction among multiple objects. In this paper, we propose a transformation based approach to generating scenario oriented test cases for applications modeled by UML activity diagrams. Using a set of transformation rules, the proposed approach first transforms a UML activity diagram specification into an intermediate representation, from which it then constructs test scenarios with respect to the given concurrency coverage criteria. The approach then finally derives a set of test cases for the constructed test scenarios. The approach resolves the difficulties associated with fork and join concurrency in the UML activity diagram and enables control over the number of the resulting test cases. We further implemented a tool to automate the proposed approach and studied its feasibility and effectiveness using a case study. Experimental results show that the approach can generate test cases on demand to satisfy a given concurrency coverage criterion and can detect up to 76.5% of seeded faults when a weak coverage criterion is used. With the approach, testers can not only schedule the software test process earlier, but can also better allocate the testing resources for testing concurrent applications.
Interest in technology based therapies hampered by access: A survey of veterans with serious mental illnesses.
Venue: Psychiatric rehabilitation journal

Computer technology is used in various ways to deliver and enhance health care. It is therefore important to understand technology use patterns among underserved populations such as persons with serious mental illnesses who often experience inequitable care.  A survey was administered to 210 veterans with serious mental illnesses attending programs at a Department of Veterans Affairs community care center, with data collected on demographics, psychiatric diagnoses, access, use, and willingness to use cell phones, smart phones, Internet based online social networking, and computerized therapies. Descriptive and multivariable analyses were conducted to determine utilization and interest in different technologies.  Although 80.4% of the respondents reported owning a cellphone, only 30.3% reported they had a computer and 13.1% reported owning a smartphone. Although 56.7% reported using the Internet and 47.6% indicated they used e mail, 68.6% of respondents reported that they were interested in using computer programs for mental health related problems. Older, less educated veterans, and those with alcohol use disorders were less likely to use the Internet. Veterans who were White or had PTSD diagnoses were less willing to use any computerized therapy.  PRACTICE Lower rates of computer use, Internet, and cell phone technologies were observed among veterans with serious mental illnesses compared to general population surveys. Sociodemographic barriers likely impede access to technology among veterans with serious mental illnesses. Providing financial resources and associated education and training to veterans with serious mental illnesses could increase access to helpful technology based interventions in a population that traditionally experiences service gaps.
The normative feedback approach for energy conservation behavior in the military community

In the field of energy conservation programs, the behavior based method, especially the normative feedback approach, has emerged as a cost effective solution for energy savings. However it remains doubtful whether normative feedback would generate significant energy savings in absence of financial accountability and whether the normative feedback is influenced by the proximity of the comparison groups. Here we test various normative feedback approaches at the Joint Base Andrews in Maryland, with an objective of understanding this approach. We show that the normative feedback approach can lead to 3.4% energy savings, even when residents are not billed for their electricity usage. Through an analysis of covariance, this paper evaluates the effects of different proximities of comparison and concludes that a street level comparison level can generate the highest energy savings of 5.4% Furthermore, this paper also explores and defines the relationship between electricity savings and physical variables including home size, unit type, neighborhood, and the variation of cooling degree days. The study contributes to the understanding of how to realizing the full potential of normative feedback approach in energy savings.
Exploring the effectiveness of social messages on promoting energy conservation behavior in buildings

Buildings could be transformed into interactive living spaces that communicate with their occupants and influence the way occupants behave in buildings. This paper focuses on investigating the effectiveness of incorporating social influence methods in the design of energy saving messages. Specifically, we examined the use of two classic compliance gaining strategies that proved to have great influence on behavior in social psychology: foot in the door and reciprocity and compared them to direct request. One hundred fifty participants were randomly assigned to one of the three experimental groups. Participants in three groups received text based messages that included the same simple energy saving tip. The only difference between the messages was the social influence methods used in framing the messages. Through the use of an immersive virtual environment, we observed the participants' compliance with the messages. Our analysis showed that reciprocity received significantly higher rates of compliance both in the virtual and physical environments. In addition, significant effects were found between the participants' personality traits and their compliance with the messages. We also found carryover effects between the behavior in the virtual part of the experiment and subsequent responses in the physical environment, suggesting participants acted in the same way in both environments.
Prioritizing and scheduling messages for congestion control in vehicular ad hoc networks
Venue: Comput. Networks

Vehicular Ad Hoc Networks (VANets) is considered as a technology which can increase safety and convenience of drivers and passenger. Due to channel congestion in high density situation, VANets' safety applications suffer of degradation of performance. In order to improve performance, reliability, and safety over VANets, congestion control should be taken into account. However, congestion control is a challenging task due to the special characteristics of VANets (e.g. high mobility, high rate of topology change, frequently broken rout, and so on) In this paper, DySch and TaSch strategies are proposed. Those strategies assign priorities to the safety and service messages based on the content of messages (static factor) state of network (dynamic factor) and size of messages. DySch and TaSch strategies schedule the messages dynamically and heuristically, respectively. Their performance is investigated using highway and urban scenarios while the average delay, average throughput, number of packet loss, packet loss ratio, and waiting delay in queues are considered. Simulation results show that DySch and TaSch strategies can significantly improve the performance of VANets in comparison to the best conventional strategies. Employing the proposed strategies to control congestion in VANets helps increase reliability and safety by giving higher priority to the safety messages.
A planar microstrip RF energy harvester 3D cube antenna for multiple frequencies reception
Venue: 2016 Conference on Advances in Signal Processing (CASP)

Energy storage and finding its alternate solution is basic demand in recent years. To resolve this problem we need to use naturally available ambient energy source. This paper focuses on RF energy harvesting by designing 3D antenna for getting efficient RF DC conversion and energy solution by multiple frequency reception. This paper includes mainly 3D cubic patch array design consisting of 4 frequencies 915MHz, 2.4GHz, 2.67 GHZ and 5.8GHz at 4 sides of cube with high RF DC conversion rate and high throughput power as output. In this paper non radiating edge gap coupled rectangular Microstrip antenna is used for the proposed RF energy harvesting system. The software used for processing are HFSS for antenna design and simulation. The substrate used is FR4 with er=4.4, and RT/Duroid 5880 er= 2.2 substrate. The two feeding methods are used Microstrip line feed and inset line feed. At 915 MHz and 2.45 GHz gain obtained is 9 and 12dB. VSWR (Voltage Standing Wave Ratio) is 1.2 and 1.3 respectively. The obtained microwave power is of 56mW.The rectifier model is of 5 stage CMOS model consisting of Schottky diode and rectified under series Skyworks SMS7630 079. This paper combine 4 frequencies in 2 patch array design mainly 4x4 and end fire array design and 2 substrate.
Natural Image Matting Using Deep Convolutional Neural Networks
Venue: ECCV

We propose a deep Convolutional Neural Networks (CNN) method for natural image matting. Our method takes results of the closed form matting, results of the KNN matting and normalized RGB color images as inputs, and directly learns an end to end mapping between the inputs, and reconstructed alpha mattes. We analyze pros and cons of the closed form matting, and the KNN matting in terms of local and nonlocal principle, and show that they are complementary to each other. A major benefit of our method is that it can "recognize" different local image structures, and then combine results of local (closed form matting) and nonlocal (KNN matting) matting effectively to achieve higher quality alpha mattes than both of its inputs. Extensive experiments demonstrate that our proposed deep CNN matting produces visually and quantitatively high quality alpha mattes. In addition, our method has achieved the highest ranking in the public alpha matting evaluation dataset in terms of the sum of absolute differences, mean squared errors, and gradient errors.
Latent Embeddings for Zero Shot Classification
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

We present a novel latent embedding model for learning a compatibility function between image and class embeddings, in the context of zero shot classification. The proposed method augments the state of the art bilinear compatibility model by incorporating latent variables. Instead of learning a single bilinear map, it learns a collection of maps with the selection, of which map to use, being a latent variable for the current image class pair. We train the model with a ranking based objective function which penalizes incorrect rankings of the true class for a given image. We empirically demonstrate that our model improves the state of the art for various class embeddings consistently on three challenging publicly available datasets for the zero shot setting. Moreover, our method leads to visually highly interpretable results with clear clusters of different fine grained object properties that correspond to different latent variable maps.