Miracle-dz/UniFAR-FTUs huggingface dataset:
The dependence of aerosol effects on clouds and precipitation on cloud‐system organization, shear and stability

Precipitation suppression due to an increase of aerosol number concentration in stratiform cloud is well-known. It is not certain whether the suppression applies for deep convection. Recent studies have suggested increasing precipitation from deep convection with increasing aerosols under some, but not all, conditions. Increasing precipitation with increasing aerosols can result from strong interactions in deep convection between dynamics and microphysics. High cloud liquid, due to delayed autoconversion, provides more evaporation, leading to more active downdrafts, convergence fields, condensation, collection of cloud liquid by precipitable hydrometeors, and precipitation. Evaporation of cloud liquid is a primary determinant of the intensity of the interactions. It is partly controlled by wind shear modulating the entrainment of dry air into clouds and transport of cloud liquid into unsaturated areas. Downdraft-induced convergence, crucial to the interaction, is weak for shallow clouds, generally associated with low convective available potential energy ( CAPE). Aerosol effects on cloud and precipitation can vary with CAPE and wind shear. Pairs of idealized numerical experiments for high and low aerosol cases were run for five different environmental conditions to investigate the dependence of aerosol effect on stability and wind shear. In the environment of high CAPE and strong wind shear, cumulonimbus- and cumulus-type clouds were dominant. Transport of cloud liquid to unsaturated areas was larger at high aerosol, leading to stronger downdrafts. Because of the large vertical extent of those clouds, strong downdrafts and convergence developed for strong interactions between dynamics and microphysics. These led to larger precipitation at high aerosol. Detrainment of cloud liquid and associated evaporation were less with lower CAPE and wind shear, where dynamically weaker clouds dominated. Transport of cloud liquid to unsaturated areas was not as active as in the environment of high CAPE and strong shear. Also, evaporatively driven differences in downdrafts at their level of initial descent were not magnified in clouds with shallow depth as much as in deep convective clouds as they accelerated to the surface over shorter distances. Hence the interaction between dynamics and microphysics was reduced, leading to precipitation suppression at high aerosol. These results demonstrate that increasing aerosol can either decrease or increase precipitation for an imposed large-scale environment supporting cloud development. The implications for larger-scale aspects of the hydrological cycle will require further study with larger-domain models and cumulus parameterizations with advanced microphysics. (Less)
The relationship between prosocial and antisocial behaviors in sport, general self-efficacy and academic self-efficacy: Study in department of physical education and sport teacher education

The aim of this study was to examine the relationship between prosocial and antisocial behaviors in sport, general self-efficacy and academic self-efficacy beliefs of students studying in physical education and sport teacher education department. 118 students in department of physical education and sport teacher education at Mugla Sitki Kocman University voluntarily participated in the study. 31 of the participants were national athletes while 87 of them were non-national athletes. 50 of the participant were females while 68 of them were males. Prosocial and Antisocial Behavior in Sport Scale (PABSS) was used to determine the behaviors of students whether prosocial or antisocial. General self-efficacy scale was used to determine the self-efficacy beliefs of participants. Academic Self-Efficacy scale was used to determine academic self-efficacy beliefs of students. Positive correlations have been found between age and prosocial opponent. Positive correlations have been found between general self-efficacy and prosocial teammate, prosocial opponent. Positive correlations have been found between academic self-efficacy and prosocial teammate, prosocial opponent, general-self-efficacy. Consequently, students having high level of self-efficacy beliefs in physical education and sport teacher education department can adopt prosocial behaviors.
THE RELATIONSHIP BETWEEN LEARNING STYLE, SELF-EFFICACY BELIEFS, AND ACADEMIC FIELDS IN HIGH SCHOOL STUDENTS

The main prupose of this study was to investigate the relationship between learning styles, self-efficacy beliefs and academic fields in high school students. In this research, we have been seeking to find whether there is significant relationship between the element of study field and learning style, between the elements of self-efficacy belief and field of study, and the elements of gender and self-efficacy. Self-efficacy consists of the beliefs a person has toward his abilities in order to organize the phenomenon to reach his desired state with suitable behavior and act (Mortazavi, 2005). Studies indicated that the amount of self-efficacy beliefs is differing based on the people’s age and gender. And self-efficacy belief increases with the increase in age in both genders and it is higher in men (Tuckman, and others 1987). Learning styles refer to beliefs and behaviors that people use to help them in learning in a specific situation (Hohen, 1999). The studies about learning styles have indicated that the various learning styles differ with gender, academic field and education 1 M. A. in Educational Psychology
Modeling and Forecasting Stock Market Volatility by Gaussian Processes based on GARCH , EGARCH and GJR Models

— Probabilistic methods called Gaussian processes have been successfully shown as a powerful tool for modeling time series data and prediction problem as they are a Bayesian approach with kernel based learning. In this paper, the Gaussian processes are applied to model and predict financial volatility based on GARCH, EGARCH and GJR. Five different kernels are used to train each of the proposed volatility models. More precisely, the experimental results show that, the nonlinear hybrid models can capture well symmetric and asymmetric effects of news on volatility and yields better predictive performance than the classic GARCH, EGARCH and GJR approaches.
Fast Downward Cedalion

Cedalion is our algorithm for automatically configuring sequential planning portfolios. Given a parametrized planner and a set of training instances, it iteratively selects the pair of planner configuration and time slice that improves the current portfolio the most per time spent. At the end of each iteration all instances for which the current portfolio finds the best solution are removed from the training set. The algorithm stops when the the total runtime of the added configurations reaches the portfolio time limit (usually 30 minutes) or if the training set becomes empty. Conceptually, Cedalion is similar to Hydra (Xu, Hoos, and Leyton-Brown 2010) in that both use an algorithm configuration procedure (Hutter 2009) to add the most improving configuration to the existing portfolio in each iteration. However, Hydra uses the algorithm selection system SATzilla (Xu et al. 2008) to select a configuration based on the characteristics of a given test instance, and therefore does not have a notion of time slices. In contrast, Cedalion runs all found configurations sequentially regardless of the instance at hand and makes the length of the time slices part of the configuration space. Cedalion is also very similar to the greedy algorithm presented by Streeter, Golovin, and Smith (2007). Given a finite set of solvers and their runtimes on the training set, that algorithm iteratively adds the (solver, time slice) pair that most improves the current portfolio per time spent. In contrast, Cedalion does not rely on a priori runtime data and supports infinite sets of solver configurations by using an algorithm configuration procedure to adaptively gather this data for promising configurations only. In principle, Cedalion could employ any algorithm configuration procedure to select the next (configuration, time slice) pair. Here, we use the model-based configurator SMAC (Hutter, Hoos, and Leyton-Brown 2011) for this task. As a simple standard parallelization method (Hutter, Hoos, and Leyton-Brown 2012), we performed 5 SMAC runs in parallel in every iteration of Cedalion and used the best of the 5 identified (configuration, time slice) pairs. We could have included planners other than Fast Downward in our Cedalion portfolios (even other parameterized planning frameworks, by configuring on the union of all parameter spaces). If portfolios prove to be useful in the learning track setting, this would have almost certainly improved performance, due to the fact that portfolios can exploit the complementary strengths of diverse approaches. Nevertheless, we chose to limit ourselves to Fast Downward in order to quantify the performance gain possible within this framework.
Identifying the Physical Fitness, Anthropometric and Athletic Movement Qualities Discriminant of Developmental Level in Elite Junior Australian Football: Implications for the Development of Talent

Abstract Gaudion, SL, Doma, K, Sinclair, W, Banyard, HG, and Woods, CT. Identifying the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football: implications for the development of talent. J Strength Cond Res 31(7): 1830–1839, 2017—This study aimed to identify the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football (AF). From a total of 77 players, 2 groups were defined according to their developmental level; under 16 (U16) (n = 40, 15.6 to 15.9 years), and U18 (n = 37, 17.1 to 17.9 years). Players performed a test battery consisting of 7 physical fitness assessments, 2 anthropometric measurements, and a fundamental athletic movement assessment. A multivariate analysis of variance tested the main effect of developmental level (2 levels: U16 and U18) on the assessment criterions, whilst binary logistic regression models and receiver operating characteristic (ROC) curves were built to identify the qualities most discriminant of developmental level. A significant effect of developmental level was evident on 9 of the assessments (d = 0.27–0.88; p ⩽ 0.05). However, it was a combination of body mass, dynamic vertical jump height (nondominant leg), repeat sprint time, and the score on the 20-m multistage fitness test that provided the greatest association with developmental level (Akaike's information criterion = 80.84). The ROC curve was maximized with a combined score of 180.7, successfully discriminating 89 and 60% of the U18 and U16 players, respectively (area under the curve = 79.3%). These results indicate that there are distinctive physical fitness and anthropometric qualities discriminant of developmental level within the junior AF talent pathway. Coaches should consider these differences when designing training interventions at the U16 level to assist with the development of prospective U18 AF players.
Mitomycin C Treatment Significantly Reduces Central Damage of Islets in Culture

Objectives We recently reported that mitomycin C (MMC) treatment and subsequent culture of islets significantly prolongs graft survival in allotransplantation and xenotransplantation models. The present study was performed to determine the changes in morphology and signal transduction in pancreatic islets after MMC treatment. Methods Freshly isolated rat islets were treated with 10 &mgr;g/mL MMC for 30 minutes and then cultured for up to 3 days. The samples were processed for immunohistologic studies and electron microscopic examination at various times after treatment. A DNA fragmentation assay was performed to detect apoptotic cell death. Western blotting was performed to determine the effects of MMC on signal transduction. Results As early as 4 hours after culture, the islets showed central damage; most cells were necrotic and stained with anti–high mobility group box 1 antibody, and a few were apoptotic. The ratio of the damaged area to the whole area was significantly decreased after MMC treatment. Western blotting showed that MMC treatment increased the levels of activated forms of p53 and p21waf1, whereas levels of the activated forms of Akt and caspase-3 were unchanged. Conclusions Mitomycin C treatment protects islets from the progression of central damage during culture. The p53–p21waf1 pathway might be involved in these effects. Abbreviations MMC - mitomycin C, HMGB1 - high mobility group box 1
Visualization of parallel modeling of dynamical processes on stochastic Kronecker graphs

This article focuses on the visualization of parallel modeling of dynamic processes on complex networks. The proposed method based on the parallel visualization of each part of parallel algorithm of modeling. This approach is applied to visualization of the stochastic Kronecker graph. The experiments have shown that our approach facilitates the visual analysis and helps to investigate the dynamic processes into network.
A General HIV Incidence Inference Scheme Based on Likelihood of Individual Level Data and a Population Renewal Equation

We derive a new method to estimate the age specific incidence of an infection with a differential mortality, using individual level infection status data from successive surveys. The method consists of a) an SI-type model to express the incidence rate in terms of the prevalence and its derivatives as well as the difference in mortality rate, and b) a maximum likelihood approach to estimate the prevalence and its derivatives. Estimates can in principle be obtained for any chosen age and time, and no particular assumptions are made about the epidemiological or demographic context. This is in contrast with earlier methods for estimating incidence from prevalence data, which work with aggregated data, and the aggregated effect of demographic and epidemiological rates over the time interval between prevalence surveys. Numerical simulation of HIV epidemics, under the presumption of known excess mortality due to infection, shows improved control of bias and variance, compared to previous methods. Our analysis motivates for a) effort to be applied to obtain accurate estimates of excess mortality rates as a function of age and time among HIV infected individuals and b) use of individual level rather than aggregated data in order to estimate HIV incidence rates at times between two prevalence surveys.
A new unsupervised model of action recognition

The hand-craft feature description such as blob detection (SIFT), the gradient of edges (HOG) are widely used in the action recognition, while they are not suitable to all kinds of videos and increase the manual intervention. And the deep learning based on unsupervised method have a lot of parameter tuning and iterations. Our paper proposes a new model of action recognition combine the hand-craft spatiotemporal interest points with unsupervised descriptors. This model uses STIP as the spatiotemporal interest points extractor and improved K-means as the unsupervised learning method to build the descriptor. This K-Means based unsupervised descriptor provides higher accuracy than hand-craft descriptors and lower training time than multi-layer unsupervised learning methods. Moreover, we update the BoF model in recognition framework, which constructs local vocabularies to each category. Experimental results indicate that this proposed framework works well.
YwdL in Bacillus cereus: Its Role in Germination and Exosporium Structure

In members of the Bacillus cereus group the outermost layer of the spore is the exosporium, which interacts with hosts and the environment. Efforts have been made to identify proteins of the exosporium but only a few have so far been characterised and their role in determining spore architecture and spore function is still poorly understood. We have characterised the exosporium protein, YwdL. ΔywdL spores have a more fragile exosporium, subject to damage on repeated freeze-thawing, although there is no evidence of altered resistance properties, and coats appear intact. Immunogold labelling and Western blotting with anti-YwdL antibodies identified YwdL to be located exclusively on the inner surface of the exosporium of B. cereus and B. thuringiensis. We conclude that YwdL is important for formation of a robust exosporium but is not required to maintain the crystalline assembly within the basal layer or for attachment of the hairy nap structure. ΔywdL spores are unable to germinate in response to CaDPA, and have altered germination properties, a phenotype that confirms the expected defect in localization of the cortex lytic enzyme CwlJ in the coat.
Myanmar in Thailand: An Empirical Study of the Relationship among the Job Characteristics Model, Job Satisfaction, Organizational Commitment, and Turnover Intention in Low-skilled Workers

This paper presents new empirical findings in the academically sparse area of low-skilled worker management. Despite their important presence in the labour-intensive sector, a limited amount of research and study has been done regarding low-skilled worker attitude. This empirical paper studied 400 low-skilled Myanmar immigrant workers in the Thai seafood-processing industry to find out the level of their attitude toward job satisfaction, organizational commitment, turnover intention, and job characteristic factors. Descriptive analysis, t-test, ANOVA, correlation, and regression analysis are used in this study. The results reveal a mixture of evidence supportive to that of past literatures and a surprisingly contradictory result in the area of turnover intention. Through this new empirical finding, entrepreneurs and society gain a better understanding of low-skilled workers and understand how to manage and motivate this unique group of employees more effectively and efficiently in the future.
Text classification using word sequence kernel methods

This paper presents a comparison study of two sequence kernels for text classification, namely, all common subsequences and sequence kernel. We consider some variations of the two kernels — kernels based on individual features, linear combination of individual kernels and kernels with a factored representation of features — and evaluate them in text classification by employing them as similarity functions in a support vector machine. A sentence is represented as a sequence of words along with their lemma and part-of-speech tags. Experiments show that sequence kernel has a clear advantage over all common subsequences. Since the main difference between the two kernels lies in the fact that the frequency of words (objects) is considered in sequence kernel but not in all common subsequences, we conclude that the frequency of words is an important factor in the successful application of kernels to text classification.
On social neuroscience methodologies and their applicability to group processes and intergroup relations

Group processes and intergroup relations are one of the most important topics examined by social psychologists. Recent advancements in social neuroscience methodologies provide valuable insight into these processes by allowing researchers to examine different psychological phenomena via neural processes that instantiate them while individuals interact with ingroup and outgroup members. This includes responses that occur outside conscious awareness or are deemed undesirable to overtly express. The purpose of this review is to provide an overview of the different social neuroscience methodologies that afford these possibilities. Specifically, functional magnetic resonance imaging (fMRI), electroencephalography (EEG), functional near infrared spectroscopy (fNIRS), transcranial magnetic stimulation (TMS), and genetic approaches will be discussed. Each section includes a discussion of what the methodology is and how it is used to assess neural function. A secondary goal of the review is to highlight recent studies that have utilized the aforementioned tools to better understand intergroup processes and interactions. Throughout, advantages and limitations of each approach are discussed, particularly with respect to the study of group processes and intergroup relations.
Deletions in the Neuraminidase Stalk Region of H2N2 and H9N2 Avian Influenza Virus Subtypes Do Not Affect Postinfluenza Secondary Bacterial Pneumonia

ABSTRACT We investigated the synergism between influenza virus and Streptococcus pneumoniae, particularly the role of deletions in the stalk region of the neuraminidase (NA) of H2N2 and H9N2 avian influenza viruses. Deletions in the NA stalk (ΔNA) had no effect on NA activity or on the adherence of S. pneumoniae to virus-infected human alveolar epithelial (A549) and mouse lung adenoma (LA-4) cells, although it delayed virus elution from turkey red blood cells. Sequential S. pneumoniae infection of mice previously inoculated with isogenic recombinant H2N2 and H9N2 influenza viruses displayed severe pneumonia, elevated levels of intrapulmonary proinflammatory responses, and death. No differences between the WT and ΔNA mutant viruses were detected with respect to effects on postinfluenza pneumococcal pneumonia as measured by bacterial growth, lung inflammation, morbidity, mortality, and cytokine/chemokine concentrations. Differences were observed, however, in influenza virus-infected mice that were treated with oseltamivir prior to a challenge with S. pneumoniae. Under these circumstances, mice infected with ΔNA viruses were associated with a better prognosis following a secondary bacterial challenge. These data suggest that the H2N2 and H9N2 subtypes of avian influenza A viruses can contribute to secondary bacterial pneumonia and deletions in the NA stalk may modulate its outcome in the context of antiviral therapy.
Research of Security Analysis of ARBAC Policy Based on Intelligence Planning

Aimed at those access control system which support role hierarchy and static mutual exclusion roles (SMER), an intelligent method from intelligent planning, named Graphplan, was imported to perform the security analysis. A complete resolution for reachability problems was designed and presented, including a description model using planning language,the key conception virtual action which was put forward to express the inheritance relation between roles and the modeling steps and processes. The corresponding experiment system was developed and a case was illustrated the application of the analysis process. At last, a complexity result of the modeling process was presented.
Measuring Interpersonal Stress with the Bergen Social Relationships Scale

This study assessed the equivalence of the Bergen Social Relationships Scale (BSRS) across three countries. The six-item BSRS was developed to measure interpersonal stress in close relationships and is grounded in Festinger’s cognitive dissonance theory. In this context, interpersonal stress refers to perceived troubled relationships with significant others who cause stress even when they do not mean to (e.g., inept social support attempts, criticism, demands that are too high). Interpersonal stress is of considerable concern because community-based research indicates that levels of anxiety, depressive symptomatology, and loneliness are significantly associated with levels of interpersonal stress. Structural equation models were used to assess the equivalence of the BSRS linguistic versions used in community-based samples in Norway (n = 328), Romania (n = 581), and Russia (n = 665). Results indicate that the BSRS has satisfactory internal consistency and that the factor structure is invariant across all t.