Miracle-dz/UniFAR-FTUs huggingface dataset:
Web-based Grid PSE for MD Simulations using Grid PSE Builder

In large-scale scientific simulations, we sometimes have access to supercomputers and largescale cluster systems of appropriate computer centers at remote sites as a way of obtaining large scale computer resources. In this case, some difficulties in using such resources due to differences in rules and job execution at each computer center have been found. Differences among remote sites to be accessed might contribute a delay in research and development, since it takes time for the application-side researcher to get to know a new computer environment well. In order to provide a common environment to users, we have constructed an MD Portal or a web-based PSE for parallel MD simulations using Grid PSE Builder, a portal construction tool for PSE developers on the Grid. Users can obtain common “look and feel” interfaces to carry out their MD simulations through a Grid PSE, regardless of differences in computer resources. Multi-site computer environments are obscured from user's eyes. The MD Portal has two components; one is an MD kernel component using the parallel MD Web-based Grid PSE for MD Simulations using Grid PSE Builder Naotaka Yamamoto, Futoshi Shimizu, Mitsuo Yokokawa, Satoshi Sekiguchi, Hideo Kaburaki, Motoyoshi Kurokawa, and Ryutaro Himeno Naotaka Yamamoto, Futoshi Shimizu, Mitsuo Yokokawa, Satoshi Sekiguchi, Hideo Kaburaki, Motoyoshi Kurokawa, Ryutaro Himeno Web-based Grid PSE for MD Simulations using Grid PSE Builder 60 Stencil library, and the other is an image generator component for drawing snapshots of the results of MD simulations. Users can submit their jobs with their own parameters, check job status, and manage result files from their jobs through a web browser with secure connections. The image generator provides an animation of the results. We have confirmed the effectiveness of the Grid PSE by applying it to an MD simulation for calculating the intrinsic transformation of the vacancy dislocation loop in copper crystal. Keyword: Grid, Grid PSE, Grid Portal, Molecular Dynamics
Polymorphisms of microRNA Sequences or Binding Sites and Lung Cancer: A Meta-Analysis and Systematic Review

Objective Functional single nucleotide polymorphisms (SNPs) of microRNA (miRNA) sequences or binding sites (miRNA-SNPs) are associated with lung cancer risk and survival. The objective of this study was to systematically review genetic association studies about miRNA-SNPs in lung cancer. Methods Eligible genetic association studies were retrieved from databases of PubMed, EMBASE, China National Knowledge Infrastructure and SinoMed. Two investigators selected related studies and assessed methodological quality independently. Quantitative data synthesis was conducted for common SNPs of miRNA (miRNA-196a2 rs11614913, miRNA146a rs2910164, miRNA149 rs2292832, miRNA-605 rs2043556 and miRNA499 rs3746444). GRADE profiler was used to grade the quality of evidence for each miRNA-SNP. Results 15 eligible studies and 27 miRNA-SNPs were retrieved and 10 miRNA-SNPs were reported with a significant association with susceptibility to or survival of lung cancer. Methodological quality of eligible studies was adequate with an average score of 8.5. miRNA-196a2 rs11614913 polymorphism was associated with increased lung cancer risk (homozygote comparison, OR = 1.299, 95% CI: 1.096–1.540; dominant model, OR = 1.217, 95% CI: 1.041–1.421) and decreased survival. And according to GRADE profiler, quality of evidence was moderate for MYCL1 rs3134615, while quality of the other significant associations was low. Conclusions Based on this first systematic review about miRNA-SNPs in lung cancer, quality of evidence was low for most genetic association studies. Polymorphisms of miRNA-196a2 rs11614913 and MYCL1 rs3134615 could be potential biomarkers of lung cancer.
Tomographic Spectral Imaging with Multivariate Statistical Analysis: Comprehensive 3D Microanalysis

A comprehensive three-dimensional (3D) microanalysis procedure using a combined scanning electron microscope (SEM)/focused ion beam (FIB) system equipped with an energy-dispersive X-ray spectrometer (EDS) has been developed. The FIB system was used first to prepare a site-specific region for X-ray microanalysis followed by the acquisition of an electron-beam generated X-ray spectral image. A small section of material was then removed by the FIB, followed by the acquisition of another X-ray spectral image. This serial sectioning procedure was repeated 10–12 times to sample a volume of material. The series of two-spatial-dimension spectral images were then concatenated into a single data set consisting of a series of volume elements or voxels each with an entire X-ray spectrum. This four-dimensional (three real space and one spectral dimension) spectral image was then comprehensively analyzed with Sandia's automated X-ray spectral image analysis software. This technique was applied to a simple Cu-Ag eutectic and a more complicated localized corrosion study where the powerful site-specific comprehensive analysis capability of tomographic spectral imaging (TSI) combined with multivariate statistical analysis is demonstrated.
Combination of Time Series, Decision Tree and Clustering: A Case Study in Aerology Event Prediction

Predictive systems use historical and other available data to predict an event. In this paper we propose a general framework to predict the Aerology events with time series streams and events stream using combination of K-means clustering algorithm and Decision Tree C5 algorithm. Firstly, we find the closest time series record for any events; therefore, we have gathered different parameters value when an event is occurring. Using K-means we add a field to data set which determines the cluster of each record after that by using C5 algorithm we predict events. C5 Decision Tree Algorithm is one of the well-known Decision Tree Algorithms. This framework and time series model can predict future events efficiently. We gathered 1961 until 2005 data of aerology organization for Tehran Mehrabad Station. This data contains some fields such as wet bulb, relative humidity, amount of cloud, wind speed and etc. This data set includes 17 types of events. Time series models can predict next time series parameters value and by using this Framework the closest event can be predicted. The C5 method is able to predict Events with Correct 74.11 percent and Wrong 25.89 percent. But with the aims of K-means clustering algorithm the prediction increase to 85 percent and wrong to 15 percent. 90 percent of data was used for training set and 10 percent for test set. We use 10-fold cross validation to evaluate our prediction rate. This framework is the first estimation in the area of event prediction for a huge data set of aerology and can be extended in many different data sets in any other environments.
Denoising of human speech using combined acoustic and EM sensor signal processing

Low power EM radar-like sensors have made it possible to measure properties of the human speech production system in real-time, without acoustic interference. This greatly enhances the quality and quantify of information for many speech related applications (see Holzrichter, Burnett, Ng, and Lea, J. Acoustic. Soc. Am. 103 (1) 622 (1998)). By using combined glottal-EM-sensor-and acoustic-signals, segments of voiced, unvoiced, and no-speech can be reliably defined. Real-time de-noising filters can be constructed to remove noise from the user's corresponding speech signal.
Use of Representative Operation Counts in Computational Testing of Algorithms

In the mathematical programming literature, researchers have conducted a large number of computational studies to assess the empirical behavior of various algorithms and have utilized CPU time as the primary measure of performance. CPU time has the following drawbacks as a measure of an algorithm's performance: it is implementation dependent, hard to replicate, and limited in the insight it provides into an algorithm's behavior. In this paper, we illustrate the notion of representative operation counts that can complement the conventional CPU time analysis and can help us (i) to identity the asymptotic bottleneck operations in an algorithm, (ii) to estimate an algorithm's running time for different problem sizes, and (iii) to obtain a fairer comparison of several algorithms. These concepts are easily incorporated into empirical studies and often yield valuable insights into an algorithm's behavior.
Psychopathology Associated with Participant Role among Bullying Situation

MethodsZZIn a cross-sectional study, 490 middle school students completed the Participant Role Questionnaire (PRQ) for classifying the participants’ roles in a bullying situation. The KoreanYouth Self Report (K-YSR), Revised Children’s Manifest Anxiety Scale (RCMAS), Rosenberg SelfEsteem Scale (RSE) and Parent Adolescent Communication Inventory (PACI) were also included to evaluate the psychopathology of the students.
THE ASSESSMENT OF ENTREPRENEURIAL PERSONALITY: THE CURRENT SITUATION AND FUTURE DIRECTIONS

any internationally renowned organisations, such as the Global Entrepreneurship Research Association (GEM, 2015) and the Organisation for Economic Co-operation and Development (OECD, 2014), annually assess entrepreneurial activity in a large number of countries. Currently, governments, organisations, universities and individuals are joining forces to try to understand the process of entrepreneurship, since its promotion is essential for the development of market economies (OECD / The European Commission, 2013). Furthermore, failure as an entrepreneur involves a cost to society in terms of lost opportunities and resources, and it ultimately causes significant consequences for the individual, both economically and psychologically (Zhao, Seibert, & Lumpkin, 2010). It is important to distinguish between entrepreneurship and business ownership, as the latter is confined to the exclusive domain of the company as one specific example of the many possible manifestations of entrepreneurship. Depending on the objectives to be achieved, it is possible to identify at least three types of entrepreneur in terms of the objectives they aim to achieve: extra-entrepreneur, intra-entrepreneur and personal entrepreneur. The extra-entrepreneur is a person whose goal is to develop new external projects related to business creation (Rauch & Frese, 2007b). The intra-entrepreneur is a person who is responsible for creating innovation within a business, improving projects that are already underway (Lumpkin, 2007). The personal entrepreneur is characterised by a high level of personal control and initiative, and is able to handle difficult situations, for example, stressors, unemployment or career changes (Frese & Fay, 2001). A particular case of this type of entrepreneur would be those who are oriented towards volunteer work in the community, in non-governmental organisations, or the researcher who proposes a theory or technique that has not previously been explored. The study of all matters relating to entrepreneurship has grown exponentially in recent years, establishing itself as a multidisciplinary field of research (Rauch & Frese, 2007a; Sánchez, 2011). This consolidation is explained largely by the contribution of models and theories proposed from an economic and sociological approach (Chell, 2008). Psychology has also played a central role in legitimising and even popularising the study of entrepreneurship (Baum, Frese, Baron, & Katz, 2007; Hisrich, Lagan-Fox & Grant, 2007). One possible THE ASSESSMENT OF ENTREPRENEURIAL PERSONALITY: THE CURRENT SITUATION AND FUTURE DIRECTIONS
Perspectivas para el trabajo social en el sistema educativo

In the current context of a functionally differentiated society, as it is proposed by the theory of autopoietic social systems, social work intervention may submit proposals based on the coordination of differences, to guarantee certain levels of equity in the Chilean educational system. The aim of this paper is to propose some guidance on this matter.
Line direction matters: an argument for the use of principal directions in 3D line drawings

While many factors contribute to shape perception, psychological research indicates that the direction of lines on the surface may have an important influence. This is especially the case when other techniques (shading, silhouetting) do not present sufficient shape information. The psychology literature suggests that lines in the principal directions of curvature may communicate surface shape better than lines in other directions. Moreover, principal directions have the quality of geometric invariance so line directions are based on the surface geometry and are viewpoint and light source independent, and the lines do not move above over the surface during animation unless desired. In this work we describe principal direction line drawings which show the flow of curvature over the surface. The technique is presented for arbitrary surfaces represented by either 3D volume data or a polygonal surface mesh. The latter format is common in the field of computer graphics yet thus far has not been widely used for principal direction estimation. The methods offered in this paper can be used alone or in conjunction with other NPR techniques to improve artistic 3D renderings of arbitrary surfaces.
Efficacy of a short-term intense piano training program for cognitive aging: A pilot study

The purpose of this research was to evaluate the efficacy of a short-term intense piano training program on executive functions in healthy older adults. Thirty-four adult participants with little to no formal music training were recruited and completed a battery of standardized cognitive measures at three time points: pre-training, pre-training two (upon completion of a control time period), and post-training. The piano training program included 30 hours of focused music theory, finger dexterity exercises, bimanual coordination exercises, technical exercises, performance duets, and standard piano repertoire. Results of a Repeated Measures MANOVA show significantly enhanced verbal fluency and processing speed, post-training; however, no difference was found in verbal memory performance. Data suggest that a short-term intense piano training program may benefit cognitive performance in areas of verbal fluency and processing speed. Short-term intense music programs may be an appropriate structure for a cognitive training program with the added benefit of increased interest in continued music participation.
Implementing Augmented Reality into the Gaming Industry on a Desktop Display Interface

This project focuses on the use of desktop display interfaces for augmented reality (AR) gaming. With this type of interface, the user is able to look at a screen and see the computer-generated graphics displayed above markers. The desktop display interface alleviates most of the problems associated with head mounted displays (HMDs). The software designed to test the system’s usability is a space station construction game created with ARToolkit, OpenSceneGraph, Maya, and 3ds Max. Using an ARenabled pointing device, the user adds various parts to the station, limited by resources and part requirements.
Cross-lingual and multi-stream posterior features for low resource LVCSR systems

We investigate approaches for large vocabulary continuous speech recognition (LVCSR) system for new languages or new domains using limited amounts of transcribed training data. In these low resource conditions, the performance of conventional LVCSR systems degrade significantly. We propose to train low resource LVCSR system with additional sources of information like annotated data from other languages (German and Spanish) and various acoustic feature streams (short-term and modulation features). We train multilayer perceptrons (MLPs) on these sources of information and use Tandem features derived from the MLPs for low resource LVCSR. In our experiments, the proposed system trained using only one hour of English conversational telephone speech (CTS) provides a relative improvement of 11% over the baseline system.
Bacterial Outer Membrane Ushers Contain Distinct Targeting and Assembly Domains for Pilus Biogenesis

ABSTRACT Biogenesis of a superfamily of surface structures by gram-negative bacteria requires the chaperone/usher pathway, a terminal branch of the general secretory pathway. In this pathway a periplasmic chaperone works together with an outer membrane usher to direct substrate folding, assembly, and secretion to the cell surface. We analyzed the structure and function of the PapC usher required for P pilus biogenesis by uropathogenic Escherichia coli. Structural analysis indicated PapC folds as a β-barrel with short extracellular loops and extensive periplasmic domains. Several periplasmic regions were localized, including two domains containing conserved cysteine pairs. Functional analysis of deletion mutants revealed that the PapC C terminus was not required for insertion of the usher into the outer membrane or for proper folding. The usher C terminus was not necessary for interaction with chaperone-subunit complexes in vitro but was required for pilus biogenesis in vivo. Interestingly, coexpression of PapC C-terminal truncation mutants with the chromosomal fim gene cluster coding for type 1 pili allowed P pilus biogenesis in vivo. These studies suggest that chaperone-subunit complexes target an N-terminal domain of the usher and that subunit assembly into pili depends on a subsequent function provided by the usher C terminus.
Median Based Parallel Steering Kernel Regression for Image Reconstruction

Image reconstruction is a process of obtaining the original image from corrupted data. Applications of image reconstruction include Computer Tomography, radar imaging, weather forecasting etc. Recently steering kernel regression method has been applied for image reconstruction [1]. There are two major drawbacks in this technique. Firstly, it is computationally intensive. Secondly, output of the algorithm suffers form spurious edges (especially in case of denoising). We propose a modified version of Steering Kernel Regression called as Median Based Parallel Steering Kernel Regression Technique. In the proposed algorithm the first problem is overcome by implementing it in on GPUs and multi-cores. The second problem is addressed by a gradient based suppression in which median filter is used. Our algorithm gives better output than that of the Steering Kernel Regression. The results are compared using Root Mean Square Error(RMSE). Our algorithm has also shown a speedup of 21x using GPUs and shown speedup of 6x using multi-cores.
A Model for Damage Load and Its Implications for the Evolution of Bacterial Aging

Deleterious mutations appearing in a population increase in frequency until stopped by natural selection. The ensuing equilibrium creates a stable frequency of deleterious mutations or the mutational load. Here I develop the comparable concept of a damage load, which is caused by harmful non-heritable changes to the phenotype. A damage load also ensues when the increase of damage is opposed by selection. The presence of a damage load favors the evolution of asymmetrical transmission of damage by a mother to her daughters. The asymmetry is beneficial because it increases fitness variance, but it also leads to aging or senescence. A mathematical model based on microbes reveals that a cell lineage dividing symmetrically is immortal if lifetime damage rates do not exceed a threshold. The evolution of asymmetry allows the lineage to persist above the threshold, but the lineage becomes mortal. In microbes with low genomic mutation rates, it is likely that the damage load is much greater than the mutational load. In metazoans with higher genomic mutation rates, the damage and the mutational load could be of the same magnitude. A fit of the model to experimental data shows that Escherichia coli cells experience a damage rate that is below the threshold and are immortal under the conditions examined. The model estimates the asymmetry level of E. coli to be low but sufficient for persisting at higher damage rates. The model also predicts that increasing asymmetry results in diminishing fitness returns, which may explain why the bacterium has not evolved higher asymmetry.
Extracting collective probabilistic forecasts from web games

Game sites on the World Wide Web draw people from around the world with specialized interests, skills, and knowledge. Data from the games often reflects the players' expertise and will to win. We extract probabilistic forecasts from data obtained from three online games: the Hollywood Stock Exchange (HSX), the Foresight Exchange (FX), and the Formula One Pick Six (F1P6) competition. We find that all three yield accurate forecasts of uncertain future events. In particular, prices of so-called "movie stocks" on HSX are good indicators of actual box office returns. Prices of HSX securities in Oscar, Emmy, and Grammy awards correlate well with observed frequencies of winning. FX prices are reliable indicators of future developments in science and technology. Collective predictions from players in the F1 competition serve as good forecasts of true race outcomes. In some cases, forecasts induced from game data are more reliable than expert opinions. We argue that web games naturally attract well-informed and well-motivated players, and thus offer a valuable and oft-overlooked source of high-quality data with significant predictive value.
VRFP: On-the-Fly Video Retrieval Using Web Images and Fast Fisher Vector Products

On-the-fly video retrieval using web images and fast Fisher Vector products (VRFP) is a real-time video retrieval framework based on short text input queries, which obtains weakly labeled training images from the web after the query is known. The retrieved web images representing the query and each database video are treated as unordered collections of images, and each collection is represented using a single Fisher Vector built on CNN features. Our experiments show that a Fisher Vector is robust to noise present in web images and compares favorably in terms of accuracy to other standard representations. While a Fisher Vector can be constructed efficiently for a new query, matching against the test set is slow due to its high dimensionality. To perform matching in real time, we present a lossless algorithm that accelerates the inner product computation between high-dimensional Fisher Vectors. We prove that the expected number of multiplications required decreases quadratically with the sparsity of Fisher Vectors. We are not only able to construct and apply query models in real time, but with the help of a simple reranking scheme, we also outperform state-of-the-art automatic retrieval methods by a significant margin on TRECVID MED13 (3.5%), MED14 (1.3%), and CCV datasets (5.2%). We also provide a direct comparison on standard datasets between two different paradigms for automatic video retrieval: zero-shot learning and on-the-fly retrieval.
A P2P Flow Identification Model Based on Bayesian Network

The fundamental work of managing P2P flow is to identify various P2P flows. In this essay, we constitute a uniform P2P flow identification model-UFIM, and analyze different identification methods. An idea to describe UFIM abstractly utilizing Bayesian network model is advanced. We make 6 measurements to denote identification performance. The contrasting result in theory analysis and experiments shows that UFIM can denote various type of P2P flow identification method abstractly. All these works establish the base of giving new identification method further.