nils-herrmann/clean_scirepeval huggingface dataset:
Girls' and boys' problem talk: Implications for emotional closeness in friendships.
Venue: Developmental psychology

This research highlights the critical role of gender in the context of problem talk and social support in adolescents' friendships. Early and middle adolescents' (N 314 friend dyads; Ms 13.01 and 16.03 years) conversations about problems were studied using observation and a short term longitudinal design. Mean level gender differences emerged in that girls participated in problem talk more than boys and responded in a more positive and engaged manner to friends' statements about problems (e.g. by saying something supportive, asking a question) than did boys. Interestingly, boys used humor during problem talk more than girls. Despite mean level differences, there were not gender differences in the functional significance of participating in problem talk and positive engaged responses in that these behaviors predicted increased friendship closeness for both boys and girls. In contrast, humor during problem talk predicted increased closeness only for boys, highlighting an understudied pathway to closeness in boys' friendships.
Wave Dispersion and Basic Concepts of Peridynamics Compared to Classical Nonlocal Damage Models

The spectral approach is used to examine the wave dispersion in linearized bond based and state based peridynamics in one and two dimensions, and comparisons with the classical nonlocal models for damage are made. Similar to the classical nonlocal models, the peridynamic dispersion of elastic waves occurs for high frequencies. It is shown to be stronger in the state based than in the bond based version, with multiple wavelengths giving a vanishing phase velocity, one of them longer than the horizon. In the bond based and state based, the nonlocality of elastic and inelastic behaviors is coupled, i.e. the dispersion of elastic and inelastic waves cannot be independently controlled. In consequence, the difference between: (1) the nonlocality due to material characteristic length for softening damage, which ensures stability of softening damage and serves as the localization limiter, and (2) the nonlocality due to material heterogeneity cannot be distinguished. This coupling of both kinds of dispersion is unrealistic and similar to the original 1984 nonlocal model for damage which was in 1987 abandoned and improved to be nondispersive or mildly dispersive for elasticity but strongly dispersive for damage. With the same regular grid of nodes, the convergence rates for both the bond based and statebased versions are found to be slower than for the finite difference methods. It is shown that there exists a limit case of peridynamics, with a micromodulus in the form of a Delta function spiking at the horizon. This limit case is equivalent to the unstabilized imbricate continuum and exhibits zero energy periodic modes of instability. Finally, it is emphasized that the node skipping force interactions, a salient feature of peridynamics, are physically unjustified (except on the atomic scale) because in reality the forces get transmitted to the second and farther neighboring particles (or nodes) through the displacements and rotations of the intermediate particles, rather than by some potential permeating particles as on the atomic scale.
Down regulation of cell adhesion via rho associated protein kinase (ROCK) pathway promotes tumor cell migration on laminin 511.
Venue: Experimental cell research

Epithelial cells, both normal and precancerous, stably anchor to basement membranes, whereas malignant tumors pass through them to achieve metastasis. Of basement membrane components, laminin 511 (a5, b1, g1; LM 511) has been found to be a major isoform in many adult basement membranes. Several studies have shown that LM 511 promotes not only cell adhesion but also tumor cell migration. Thus, LM 511 can be viewed like two distinct molecules in normal vs. tumor cells; tumor cells seem to be able to alter their response (adhesive vs. migratory) to LM 511. In this study we examined the effects of biologically active molecules on A549 lung adenocarcinoma cell adhesion to LM 511. Of them, phorbol 12 myristate 13 acetate (PMA) induced transition to a rounded cell shape and significantly promoted cell migration on LM 511. The attachment of PMA treated A549 cells to LM 511 was weaker than that of control cells. PMA stimulated signaling pathway reduced the binding of integrin a3b1 to LM 511. Cell migration assays using inhibitors for signal transduction and cytoskeletal organization showed that suppression of cell adhesion via the rho associated protein kinase (ROCK) pathway promoted tumor cell migration on LM 511. Our results suggest that the ROCK pathway is involved in the transition from static to migratory cell behaviors on LM 511.
Approach for performance optimization of switched reluctance generator in variable speed wind generation system

In this paper, algorithms are proposed to get optimal parameters of a switched reluctance generator (SRG) when applied in variable speed wind generation systems. The driver's parameters affect power generated, torque ripples, iron losses, and electric losses. Therefore, the optimal values of the drive activation must be defined for SRG's operation in a wide speed range. Thus, knowing the operating points of the wind turbine (speed and power) algorithms that perform dynamic simulations of the operation at low and high speed were developed. Driver's parameters of the SRG are obtained through cost functions, which are defined such that the balance between torque ripples, iron losses, and electric losses are maintained. With simulations results, the cost functions were minimized to get SRG's optimal firing angles according to the operating speed. Simulation and experimental tests were performed emulating a wind turbine system. The results confirmed the efficiency of the methodology proposed in this paper.
Analyse numerique et equations differentielles

Cet ouvrage est un cours d'introduction a la theorie des equations differentielles ordinaires, accompagne d'un expose detaille de differentes methodes numeriques permettant de les resoudre en pratique. La premiere partie presente quelques techniques importantes de l'analyse numerique interpolation polynomiale, methodes d'integration numerique, methodes iteratives pour la resolution d'equations. Suit un expose rigoureux des resultats de base sur l'existence, l'unicite et la regularite des solutions des equations differentielles, incluant une etude detaillee des equations usuelles du premier et du second ordre, des equations et systemes differentiels lineaires, de la stabilite des solutions et leur dependance par rapport aux parametres. Une place substantielle est accordee a la description des methodes numeriques a un pas ou multi pas, avec une etude comparative de la stabilite et du cout en temps de calcul. Agremente de nombreux exemples concrets, le texte propose des exercices et des problemes d'application a la fin de chaque chapitre.
Management de l'innovation et nouvelle ere numerique Enjeux et perspectives

Qui n'a pas entendu parler de la transformation numerique L'avenement d'Internet et des nouvelles technologies numeriques ont bouleverse les usages et modes de fonctionnement des individus mais aussi des organisations. Cette mutation acceleree annoncee en 2011 par le sommet de l'e G8 souligne le role preponderant joue par Internet dans la croissance economique et sa capacite a transformer le monde. En effet, le developpement des nouvelles technologies mobiles (comme le reseau 4G et le cloud computing) et de ses nouveaux terminaux (smartlets) des objets connectes (internet of things) l'essor des medias sociaux (Facebook, Twitter, etc. et des nouvelles plateformes collaboratives (gaming, crowdsourcing, etc. ainsi que le phenomene de multiplication des donnees comme nouvelle matiere premiere (big data, open data, etc. montre que la transformation numerique est a son apogee. Cette nouvelle ere numerique transforme chaque aspect de la vie
Analyse numerique et equations differentielles

Link to this book Analyse numerique et equations differentielles Nouvelle edition avec exercices corriges Jean Pierre Demailly La reference francaise sur les equations differentielles et leurs resolutions numeriques Cet ouvrage est la quatrieme edition d'un livre devenu aujourd'hui un classique sur la theorie des equations differentielles ordinaires. Le cours theorique de base est accompagne d'un expose detaille des methodes numeriques qui permettent de resoudre ces equations en pratique.
La transparence l'utopie du numerique

Cet article interroge la notion de transparence en partant du principe que celle ci a ete portee a son paroxysme par les technologies de l'information et de la communication, par l'utopie du numerique. Nous chercherons a comprendre si la transparence a l'ere du numerique ne releverait pas in fine d'une mise en scene, et ne serait finalement que l'exacerbation de la metaphore du theatre de Goffman.
Litteraties et creacollage numerique

Le present article s'interesse aux litteraties numerique et informationnelle ainsi qu'aux liens qu'elles entretiennent avec le creacollage numerique. Le modele de creacollage numerique presente fait le rapprochement entre les competences informationnelles, redactionnelles et de referencement documentaire, expliquant comment les strategies de creacollage numerique se retrouvent a toutes les etapes de la creation d'un texte. L'article se termine par un plaidoyer pour la formation des eleves de tous les niveaux scolaires afin que ceux ci puissent developper leurs habiletes liees aux litteraties numerique et informationnelle ainsi que leurs strategies de creacollage numerique pour apprendre a bien rediger leurs travaux scolaires avec integrite intellectuelle.
Reliability of graph analysis of resting state fMRI using test retest dataset from the Human Connectome Project
Venue: NeuroImage

The exploration of brain networks with resting state fMRI (rs fMRI) combined with graph theoretical approaches has become popular, with the perspective of finding network graph metrics as biomarkers in the context of clinical studies. A preliminary requirement for such findings is to assess the reliability of the graph based connectivity metrics. In previous test retest (TRT) studies, this reliability has been explored using intraclass correlation coefficient (ICC) with heterogeneous results. But the issue of sample size has not been addressed. Using the large TRT rs fMRI dataset from the Human Connectome Project (HCP) we computed ICCs and their corresponding p values (applying permutation and bootstrap techniques) and varied the number of subjects (from 20 to 100) the scan duration (from 400 to 1200 time points) the cost and the graph metrics, using the Anatomic Automatic Labelling (AAL) parcellation scheme. We quantified the reliability of the graph metrics computed both at global and regional level depending, at optimal cost, on two key parameters, the sample size and the number of time points or scan duration. In the cost range between 20% to 35% most of the global graph metrics are reliable with 40 subjects or more with long scan duration (14min 24s) In large samples (for instance, 100 subjects) most global and regional graph metrics are reliable for a minimum scan duration of 7min 14s. Finally, for 40 subjects and long scan duration (14min 24s) the reliable regions are located in the main areas of the default mode network (DMN) the motor and the visual networks.
Big Data Approaches for the Analysis of Large Scale fMRI Data Using Apache Spark and GPU Processing: A Demonstration on Resting State fMRI Data from the Human Connectome Project
Venue: Front. Neurosci.

Technologies for scalable analysis of very large datasets have emerged in the domain of internet computing, but are still rarely used in neuroimaging despite the existence of data and research questions in need of efficient computation tools especially in fMRI. In this work, we present software tools for the application of Apache Spark and Graphics Processing Units (GPUs) to neuroimaging datasets, in particular providing distributed file input for 4D NIfTI fMRI datasets in Scala for use in an Apache Spark environment. Examples for using this Big Data platform in graph analysis of fMRI datasets are shown to illustrate how processing pipelines employing it can be developed. With more tools for the convenient integration of neuroimaging file formats and typical processing steps, big data technologies could find wider endorsement in the community, leading to a range of potentially useful applications especially in view of the current collaborative creation of a wealth of large data repositories including thousands of individual fMRI datasets.
Hyperbaric Oxygen Therapy Suppresses Apoptosis and Promotes Renal Tubular Regeneration After Renal Ischemia/Reperfusion Injury in Rats
Venue: Nephro urology monthly

Renal ischemia/reperfusion (I/R) injury remains a major cause of acute kidney injury (AKI) in addition to I/R injury induced tissue inflammation, necrosis and apoptosis. Hyperbaric oxygen therapy (HBO) is defined as a treatment in which a patient is intermittently exposed to 100% oxygen pressurized to a pressure above sea level 2.0 atmospheres absolute (ATA) 1.0 ATA 760 mmHg) It has been used in a number of medical conditions with a proven efficacy in a limited number of disorders. However, the effects of HBO therapy on apoptosis and proliferative activity after I/R injury have not been fully understood.  We studied the possible beneficial effects of HBO therapy on apoptosis and tubular cell regeneration after renal I/R injury in rats.  Sprague Dawley (SD) rats were randomized into three groups: Sham (Sham operated rats) I/R (animals submitted to I/R) and I/R HBO (I/R rats exposed to HBO) Tubular cell apoptosis was confirmed by DNA laddering and the terminal deoxynucleotidyl transferase mediated uridine triphosphate nick end labeling (TUNEL) assay. Cellular proliferation activity was determined using the anti Ki 67 antibody.  A significant decrease in apoptotic cells and increase in proliferative reaction were observed in the I/R HBO group compared to the I/R group.  We demonstrated that HBO suppressed apoptosis, which caused inflammation after renal I/R, and promoted tubular cell regeneration. HBO has protective effects against AKI caused by renal I/R through the inhibition of apoptosis.
Smart Monitoring of Userp s Health at Home: Performance Evaluation and Signal Processing of a Wearable Sensor for the Measurement of Heart Rate and Breathing Rate
Venue: BIOSIGNALS

Nowadays, the monitoring of usersa health status is possible by means of smart sensing devices at low cost and with high measuring capabilities. Wearable devices are able to acquire multiple physiological and physical waveforms and are equipped with on board algorithms to process these signals and extract the required quantities. However, the performance of such processing techniques should be evaluated and compared to different approaches, e.g. processing of the raw waveforms acquired. In this paper, the authors have performed a metrological characterization of a commercial wearable monitoring device for the continuous acquisition of physiological quantities (e.g. Heart Rate HR and Breathing Rate BR) and raw waveforms (e.g. Electrocardiogram ECG) The aim of this work is to compare the performance of the on board processing algorithms for the calculation of HR and BR with a novel approach applied to the raw signals. Results show that the HR values provided by the device are accurate enough 2.1 and 2.8 bpm in static and dynamic tests) without the need of additional processing. On the contrary, the implementation of the dedicated processing technique for breathing waveform allows to compute accurate BR values 2.1 bpm with respect to standard equipment)
Experimental Study on the Ultimate Bearing Capacity of Long Basalt Fiber Reinforced Concrete (BFRC) Filled Steel Tube Columns under Axial Compression

The strength and ductility of core concrete are important factors influencing the bearing capacity of concrete filled steel tube (CFST) structures, and an appropriate mixing amount of basalt fiber can change the toughness index of concrete. To examine the reinforcing effect of basalt fiber on the bearing capacity of long CFST columns, axial compression bearing capacity experiments were conducted on 15 long basalt fiber reinforced concrete (BFRC) filled steel tube columns and 9 long CFST columns to determine the ultimate bearing capacity, load displacement curve, and load strain curve of the experimental columns. A comparative analysis was then performed on the experimental results and experimental characteristics of the bearing capacity to differentiate long fiber CFST columns from long CFST columns. Results revealed that compared with CFST columns, BFRC filled steel tube columns displayed improved ultimate bearing capacities under experimental level. Specifically, for core concrete added with 12 mm basalt fiber, the ultimate bearing capacities of BFRC filled steel tube columns with wall thicknesses of 4, 5, and 6 mm were improved by 9.7% 8.6% and 7.3% respectively. For core concrete filled with 24 mm basalt fiber, the ultimate bearing capacities of long BFRC filled steel tube columns with wall thicknesses of 4, 5, and 6 mm were improved by 7.8% 5.7% and 3.1% respectively. Thus, basalt fiber improves the ductility of CFST columns. The findings of this paper is of important engineering indicate the promising application value of basalt fiber in long CFST columns.
An efficient divide and conquer approach for big data analytics in machine to machine communication
Venue: Neurocomputing

Machine to Machine (M2M) communication relies on the physical objects (e.g. satellites, sensors, and so forth) interconnected with each other, creating mesh of machines producing massive volume of data about large geographical area (e.g. living and non living environment) Thus, the M2M is an ideal example of Big Data. On the contrary, the M2M platforms that handle Big Data might perform poorly or not according to the goals of their operator (in term of cost, database utilization, data quality, processing and computational efficiency, analysis and feature extraction applications) Therefore, to address the aforementioned needs, we propose a new effective, memory and processing efficient system architecture for Big Data in M2M, which, unlike other previous proposals, does not require whole set of data to be processed (including raw data sets) and to be kept in the main memory. Our designed system architecture exploits divide and conquer approach and data block wise vertical representation of the database follows a particular petitionary strategy, which formalizes the problem of feature extraction applications. The architecture goes from physical objects to the processing servers, where Big Data set is first transformed into a several data blocks that can be quickly processed, then it classifies and reorganizes these data blocks from the same source. In addition, the data blocks are aggregated in a sequential manner based on a machine ID, and equally partitions the data using fusion algorithm. Finally, the results are stored in a server that helps the users in making decision. The feasibility and efficiency of the proposed system architecture are implemented on Hadoop single node setup on UBUNTU 14.04 LTS core?i5 machine with 3.2GHz processor and 4GB memory. The results show that the proposed system architecture efficiently extract various features (such as River) from the massive volume of satellite data.
An Efficient Multidimensional Big Data Fusion Approach in Machine to Machine Communication
Venue: ACM Trans. Embed. Comput. Syst.

Machine to Machine communication (M2M) is nowadays increasingly becoming a world wide network of interconnected devices uniquely addressable, via standard communication protocols. The prevalence of M2M is bound to generate a massive volume of heterogeneous, multisource, dynamic, and sparse data, which leads a system towards major computational challenges, such as, analysis, aggregation, and storage. Moreover, a critical problem arises to extract the useful information in an efficient manner from the massive volume of data. Hence, to govern an adequate quality of the analysis, diverse and capacious data needs to be aggregated and fused. Therefore, it is imperative to enhance the computational efficiency for fusing and analyzing the massive volume of data. Therefore, to address these issues, this article proposes an efficient, multidimensional, big data analytical architecture based on the fusion model. The basic concept implicates the division of magnitudes (attributes) i.e. big datasets with complex magnitudes can be altered into smaller data subsets using five levels of the fusion model that can be easily processed by the Hadoop Processing Server, resulting in formalizing the problem of feature extraction applications using earth observatory system, social networking, or networking applications. Moreover, a four layered network architecture is also proposed that fulfills the basic requirements of the analytical architecture. The feasibility and efficiency of the proposed algorithms used in the fusion model are implemented on Hadoop single node setup on UBUNTU 14.04 LTS core i5 machine with 3.2GHz processor and 4GB memory. The results show that the proposed system architecture efficiently extracts various features (such as land and sea) from the massive volume of satellite data.
Importance of English communication skills

Communication is a skill which involves systematic and continuous process of speaking, listening and understanding. Most people are born with the physical ability to talk, but we must learn to speak well and communicate effectively. Speaking, listening and our ability to understand verbal and nonverbal cues are the skills by observing other people and modeling our behavior on what we see and perceived. We are also taught some communication skills directly through education. By bringing those skills into practice and getting them evaluated. The face of modern India is changed drastically due to globalization it has brought to India different cultures. In today's world of competition no organizations want to remain local their aim is to expand all over the world.
Regulatory Enhancer Core Promoter Communication via Transcription Factors and Cofactors.
Venue: Trends in genetics TIG

Gene expression is regulated by genomic enhancers that recruit transcription factors and cofactors to activate transcription from target core promoters. Over the past years, thousands of enhancers and core promoters in animal genomes have been annotated, and we have learned much about the domain structure in which regulatory genomes are organized in animals. Enhancer core promoter targeting occurs at several levels, including regulatory domains, DNA accessibility, and sequence encoded core promoter specificities that are likely mediated by different regulatory proteins. We review here current knowledge about enhancer core promoter targeting, regulatory communication between enhancers and core promoters, and the protein factors involved. We conclude with an outlook on open questions that we find particularly interesting and that will likely lead to additional insights in the upcoming years.