Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Video Game Content Matter? An Examination of Two Competing Ideas

Does Video Game Content Matter? An Examination of Two Competing Ideas Nathan J. Smith School of Family Life, BYU Doctor of Philosophy The current paper addresses the associations between video game content (i.e., physically aggressive, relationally aggressive, and prosocial) and physical aggression, relational aggression, and prosocial behavior in two distinct developmental periods. The purpose of the paper is to test whether playing video games with a particular type of content influences behaviors over time, or whether individuals who have higher levels of physical aggression, relational aggression, or prosocial behavior prefer to play games with similar content. Two theories will be simultaneously examined and tested in order to determine the relative merit in using each in research examining the relationships between video game content and positive and negative behaviors. More specifically, this paper will address the General Aggression Model/General Learning Model (GAM/GLM) and the Uses and Gratification Theory. The GAM/GLM, at their core, predict that exposure to video game content will build a cognitive schema which will guide how an individual should behave when confronted with a later social encounter (Anderson & Bushman, 2002). Contrarily, Uses and Gratification would suggest that a person chooses to play video games with a particular type of content, and that video games should not influence behavior. Specifically, according to the theory, individuals should seek out video games in order to fulfill their inward feelings and motivations (e.g., an individual with aggressive tendencies would play games with more violent and aggressive content) (Katz, Blumler, & Gurevitch, 1973; Whiting & Williams, 2013). A careful analysis showed a significant relationship between each type of video game content and its’ corresponding behavior among adolescents, which supports the assumptions of the GAM and GLM. There was no relationship between video game content and behavior among preschoolers. With the exception of relational aggression of physically aggressive content, there was no support for Uses and Gratification Theory, in that preschoolers’ and adolescents’ levels of physical aggression, relational aggression, and prosocial behavior were not related to the preference for video games with different types of content. The analysis adds significantly to the current literature by showing a relationship between video game content and behavior over a four year period.
Classification of Potentially Unwanted Programs Using Supervised Learning

Malicious software authors have shifted their focus from illegal and clearly malicious software to potentially unwanted programs (PUPs) to earn revenue. PUPs blur the border between legitimate and illegitimate programs and thus fall into a grey zone. Existing anti-virus and anti-spyware software are in many instances unable to detect previously unseen or zero-day attacks and separate PUPs from legitimate software. Many tools also require frequent updates to be effective. By predicting the class of particular piece of software, users can get support before taking the decision to install the software. This Licentiate thesis introduces approaches to distinguish PUP from legitimate software based on the supervised learning of file features represented as n-grams. The overall research method applied in this thesis is experiments. For these experiments, malicious software applications were obtained from anti-malware industrial partners. The legitimate software applications were collected from various online repositories. The general steps of supervised learning, from data preparation (n-gram generation) to evaluation were, followed. Different data representations, such as byte codes and operation codes, with different configurations, such as fixed-size, variable-length, and overlap, were investigated to generate different n-gram sizes. The experimental variables were controlled to measure the correlation between n-gram size, the number of features required for optimal training, and classifier performance. The thesis results suggest that, despite the subtle difference between legitimate software and PUP, this type of software can be classified accurately with a low false positive and false negative rate. The thesis results further suggest an optimal size of operation code-based n-grams for data representation. Finally, the results indicate that classification accuracy can be increased by using a customized ensemble learner that makes use of multiple representations of the data set. The investigated approaches can be implemented as a software tool with a less frequently required update in comparison to existing commercial tools.
Comparing programming paradigms: an evaluation of functional and object-oriented programs

A quantitative evaluation of the functional and object-oriented paradigms is presented. The aim of this project is to investigate whether the quality of code produced using a functional language is significantly different from that produced using an object-oriented language. 12 sets of algorithms are developed, together with a number of utility functions, in both Standard ML (SML) and C++. Strict constraints are imposed during the development cycle to improve the reliability of the results. The statistical tests do not reveal any significant differences for direct measures of the development metrics used which are associated with quality, such as the number of known errors, the number of modification requests, a subjective complexity assessment, etc. However, significant differences are found for an indirect measure, the number of known errors per thousand non-comment source lines, and for various code metrics, including the number of distinct functions called, the number of distinct library functions called, and the ratio of these, which is a measure of code reuse. A difference is also found for the time taken to test the programs, due to different compilation techniques and a difference in the number of test cases executed.
Potential of Start Codon Targeted (SCoT) Markers to Estimate Genetic Diversity and Relationships among Chinese Elymus sibiricus Accessions

Elymus sibiricus as an important forage grass and gene pool for improving cereal crops, that is widely distributed in West and North China. Information on its genetic diversity and relationships is limited but necessary for germplasm collection, conservation and future breeding. Start Codon Targeted (SCoT) markers were used for studying the genetic diversity and relationships among 53 E. sibiricus accessions from its primary distribution area in China. A total of 173 bands were generated from 16 SCoT primers, 159 bands of which were polymorphic with the percentage of polymorphic bands (PPB) of 91.91%. Based upon population structure analysis five groups were formed. The cluster analysis separated the accessions into two major clusters and three sub-clusters, similar to results of principal coordinate analysis (PCoA). The molecular variance analysis (AMOVA) showed that genetic variation was greater within geographical regions (50.99%) than between them (49.01%). Furthermore, the study also suggested that collecting and evaluating E. sibiricus germplasm for major geographic regions and special environments broadens the available genetic base and illustrates the range of variation. The results of the present study showed that SCoT markers were efficient in assessing the genetic diversity among E. sibiricus accessions.
Evidence for Classifying Metathesis Patterns as Subsequential

This paper presents a computational analysis of metathesis patterns that distinguishes three categories of metathesis that differ in their computational complexity. These categories are local metathesis, bounded long distance metathesis, and unbounded long distance metathesis. Using the formalism of finite state automata, it is established that the first two categories are subsequential, while the third category is not (in fact, it is not even regular). These terms will be discussed in more detail below, but the overall distinction is one of complexity: the subsequential class is more restrictive than the regular class. Assigning a pattern to the subsequential class then identifies it as less complex than a pattern that is non-regular. Furthermore, the patterns identified as subsequential are robustly attested in the world’s languages, whereas the non-regular patterns are much less common and in fact only attested diachronically. Thus this result suggests an upper bound for how complex a synchronic phonological pattern can be. The outline of this paper is as follows. Section 2 presents the Chomsky Hierarchy of language patterns and discusses recent findings and hypotheses for where to classifying phonological patterns on the hierarchy. Section 3 defines subsequential FSTs and demonstrates how they can be used to describe phonological patterns. Section 4 presents the computational analysis of metathesis patterns. Section 5 discusses the typological implications of the analysis, as well as the implications for learning. Section 6 indicates directions for future work and concludes. 2. The Chomsky Hierarchy and the Subregular Hypothesis Chomsky (1956) presents a means to classify languages and language patterns based on their degree of complexity or how expressive they are. This hierarchy is shown in Figure 1.
ERP Implementation: A multi-stakeholder analysis of critical success factors

Enterprise Resource Planning systems aim at integrating and streamlining organisational processes. Their adoption, coupled with an attempt to adhere to industry best practice, often bring to light much needed organisational transformation, the social dimensions of which are often sidelined. This latter dimension is also often found to have a strong bearing on success. In a drive to identify the needs for successful Enterprise Resource Planning implementation, this paper aims to categorise known critical success factors and to subsequently present these to multiple stakeholder groups for acceptance. Index Terms
Pericellular Ca2+ recycling potentiates thrombin-evoked Ca2+ signals in human platelets

We have previously demonstrated that Na+/Ca2+ exchangers (NCXs) potentiate Ca2+ signaling evoked by thapsigargin in human platelets, via their ability to modulate the secretion of autocoids from dense granules. This link was confirmed in platelets stimulated with the physiological agonist, thrombin, and experiments were performed to examine how Ca2+ removal by the NCX modulates platelet dense granule secretion. In cells loaded with the near‐membrane indicator FFP‐18, thrombin stimulation was observed to elicit an NCX‐dependent accumulation of Ca2+ in a pericellular region around the platelets. To test whether this pericellular Ca2+ accumulation might be responsible for the influence of NCXs over platelet function, platelets were exposed to fast Ca2+ chelators or had their glycocalyx removed. Both manipulations of the pericellular Ca2+ rise reduced thrombin‐evoked Ca2+ signals and dense granule secretion. Blocking Ca2+‐permeable ion channels had a similar effect, suggesting that Ca2+ exported into the pericellular region is able to recycle back into the platelet cytosol. Single cell imaging with extracellular Fluo‐4 indicated that thrombin‐evoked rises in extracellular [Ca2+] occurred within the boundary described by the cell surface, suggesting their presence within the open canalicular system (OCS). FFP‐18 fluorescence was similarly distributed. These data suggest that upon thrombin stimulation, NCX activity creates a rise in [Ca2+] within the pericellular region of the platelet from where it recycles back into the platelet cytosol, acting to both accelerate dense granule secretion and maintain the initial rise in cytosolic [Ca2+].
Bregmanized Nonlocal Regularization for Deconvolution and Sparse Reconstruction

Bregman methods introduced in [S. Osher, M. Burger, D. Goldfarb, J. Xu, and W. Yin, Multiscale Model. Simul. , 4 (2005), pp. 460-489] to image processing are demonstrated to be an efficient optimization method for solving sparse reconstruction with convex functionals, such as the $\ell^1$ norm and total variation [W. Yin, S. Osher, D. Goldfarb, and J. Darbon, SIAM J. Imaging Sci., 1 (2008), pp. 143-168; T. Goldstein and S. Osher, SIAM J. Imaging Sci., 2 (2009), pp. 323-343]. In particular, the efficiency of this method relies on the performance of inner solvers for the resulting subproblems. In this paper, we propose a general algorithm framework for inverse problem regularization with a single forward-backward operator splitting step [P. L. Combettes and V. R. Wajs, Multiscale Model. Simul. , 4 (2005), pp. 1168-1200], which is used to solve the subproblems of the Bregman iteration. We prove that the proposed algorithm, namely, Bregmanized operator splitting (BOS), converges without fully solving the subproblems. Furthermore, we apply the BOS algorithm and a preconditioned one for solving inverse problems with nonlocal functionals. Our numerical results on deconvolution and compressive sensing illustrate the performance of nonlocal total variation regularization under the proposed algorithm framework, compared to other regularization techniques such as the standard total variation method and the wavelet-based regularization method.
Forecasting Volatility in Financial Markets: A Review

Financial market volatility is an important input for investment, option pricing, and financial market regulation. The emphasis of this review article is on forecasting instead of modelling; it compares the volatility forecasting findings in 93 papers published and written in the last two decades. Provided in this paper as well are volatility definitions, insights into problematic issues of forecast evaluation, data frequency, extreme values and the measurement of "actual" volatility. We compare volatility forecasting performance of two main approaches; historical volatility models and volatility implied from options. Forecasting results are compared across different asset classes and geographical regions.
Evaluation of successful practices that lead to resiliency, grit, and growth mindsets among at-risk students

The United States is losing millions of students from its educational systems each year, leading researchers to exclaim that reducing the dropout rate is the top priority for educators throughout the country. As educators wrestle with the charge to educate and prepare every child to be successful in a global society, they seek answers about those students who are faced with serious adverse conditions leaving them statistically at risk of failure. While the national statistics for high school dropouts are high and deserve much concern, there are many students who are conquering the challenges that have caused many to dropout, and instead, are succeeding in their educational endeavors. The intent of this study is to share with professionals in the educational community effective strategies that will foster resiliency, grit, and growth mindsets in at-risk students. This study uses research and real life experiences of at-risk students succeeding in school to provide effective strategies for fostering resilience with students in danger of failing school. This mixed-methods study identified effective strategies and programs that fostered resiliency in at-risk students who were academically successful in high school. The qualitative and quantitative data indicated that schools can become havens for implementing strategies and programs that will support at-risk students overcome the adverse conditions that they experience. The study identified protective factors that are both external and internal to the individual at-risk student, and when fostered, lead to academic success. The four major themes that emerged as critical to the development of resilience, grit, and growth mindsets in at-risk students are involvement, high expectations, positive reinforcement, and fortitude. When these critical components are effectively nurtured, at-risk students have shown to overcome the challenges they face, and attain academic achievement.
Prevention of malnutrition in older people during and after hospitalisation: results from a randomised controlled clinical trial.

OBJECTIVE to prevent the occurrence of weight loss during hospitalisation and following discharge by daily oral supplementation. DESIGN in a prospective, randomised, controlled study of 80 patients aged 75 or more, and at risk of undernutrition based on their initial Mini Nutritional Assessment score, patients were randomised into a control group or one receiving oral supplementation. The intervention was a prescription of 200 ml sweet or salty sip feed twice daily (500 kcal, 21 g protein per day) throughout hospitalisation and convalescence. Nutritional status was assessed at baseline and after 2 months using Mini Nutritional Assessment and body weight record. RESULTS compliance with oral supplementation was good and daily extra energy intake was 407+/-184 kcal. On day 60, significant weight loss from upon admission was observed in the control group (-1.23+/-2.5 kg; P=0.01), but not in the supplemented group (0.28+/-3.8 kg; NS). At the end of the study, Mini Nutritional Assessment scores were higher in the supplemented group than in the control group (23.5+/-3.9 versus 20.8+/-3.6; P<0.01). CONCLUSION use of daily oral supplementation during and after hospitalisation maintains body weight and increases Mini Nutritional Assessment score in patients at risk of undernutrition.
Developing a Conceptual Framework for Life Skills Interventions Ψ

The purpose of the article is to outline a comprehensive conceptual framework for life skills interventions by integrating aspects of Basic Needs Theory (BNT) and Life Development Intervention (LDI). In particular, we advocate the integration of (a) the three basic psychological needs of autonomy, competence, and relatedness and (b) the needs-supportive motivationalclimate from BNT with the LDI framework. When these basic psychological needs are satisfied, people experience positive psychological development and optimal psychological well-being—the stated outcome goals of most life skills programs. Without the development of a conceptual framework, it is difficult to determine whether individual life skills interventions achieve optimal psychological well-being. By developing this framework, we seek to identify and articulate the key underlying psychological mechanisms (i.e., basic needs of autonomy, competence, and relatedness) that contribute to optimal human functioning and positive psychosocial development in all life skill programs. The implications for counseling psychologists’ research and practice are also considered.
Liver Methylazoxymethanol-induced DNA Methylation in Rat Colon Metabolism of Methylazoxymethanol and on in Vitro and in Vivo Effects of Chronic Dietary Ethanol on Updated Version

We examined the metabolism of "C-labeled methylazoxymethanol (MAM) in male F344 rats pair-fed for 21.0 days either a liquid control diet, an isocaloric liquid diet containing 6.6% ethanol by volume (contin uous ethanol diet), or the ethanol diet for 20.5 days followed by the control diet for 0.5 day (interrupted ethanol diet). Compared to rats fed the control liquid diet, metabolism of |1,2-"C]MAM acetate to exhaled "CO? was inhibited by 25 to 42% in rats fed the continuous ethanol diet, but was initially stimulated by 90% in rats given the interrupted ethanol diet. MAM-induced DNA methylation, as reflected in 7-methylguanine and 06-methylguanine content 24 h after carcinogen administration, was inhibited in the colon mucosae of rats fed the interrupted ethanol diet by 52 to 54%, and an even greater inhibition (71 to 86%) of DNA methyla tion occurred in the colon mucosae of rats fed the continuous ethanol diet. Liver DNA methylation was significantly inhibited (by 32 to 42%) only in those rats fed the continuous ethanol diet. Liver microsomes isolated from rats fed the 3 diets metabolized MAM to formic acid and methanol in vitro, but liver microsomes from rats fed the continuous ethanol diet were 12 to 15 times more active than liver microsomes from rats fed the control diet. Liver microsomes isolated from rats fed the interrupted ethanol diet were only 3 to 5 times more active in MAM metabolism than liver microsomes from rats fed the control diet, indicat ing very rapid turnover of the ethanol-induced enzyme(s) catalyzing the oxidation of MAM. Although chronic ethanol feeding enhanced the activity of liver microsomes for MAM metabolism, ethanol was found to inhibit the reaction competitively. Hepatocytes isolated from rats fed the continuous ethanol diet were considerably more sensitive to MAMinduced unscheduled DNA synthesis than hepatocytes isolated from rats given the control liquid diet, indicating that the stimulation of MAM metabolism by dietary ethanol results in increased DNA damage, observ able in an in vitro system. Thus, the increased metabolic activation of MAM, due to enzyme induction by ethanol which is observed in vitro, is not reflected in increased liver DNA methylation in vivo. In addition, the great degree of similarity between the present observations involving MAM and the results of our previous studies involving azoxymethane and A'-nitrosodimethylamine (O. S. Sohn et al., Cancer Res., 47:31233129, 1987) raises the question of whether all three carcinogens might not be metabolically activated by the same form of ethanol-induced rat liver microsomal enzyme(s).
Regression-based latent factor models

We propose a novel latent factor model to accurately predict response for large scale dyadic data in the presence of features. Our approach is based on a model that predicts response as a multiplicative function of row and column latent factors that are estimated through separate regressions on known row and column features. In fact, our model provides a single unified framework to address both cold and warm start scenarios that are commonplace in practical applications like recommender systems, online advertising, web search, etc. We provide scalable and accurate model fitting methods based on Iterated Conditional Mode and Monte Carlo EM algorithms. We show our model induces a stochastic process on the dyadic space with kernel (covariance) given by a polynomial function of features. Methods that generalize our procedure to estimate factors in an online fashion for dynamic applications are also considered. Our method is illustrated on benchmark datasets and a novel content recommendation application that arises in the context of Yahoo! Front Page. We report significant improvements over several commonly used methods on all datasets.
Syndrome Process of Bronchiolitis Obliterans IL-13 Is Pivotal in the Fibro-Obliterative

Acute allograft rejection is considered to be a predominately type 1 immune mediated response to the donor alloantigen. However, the type 2 immune mediated response has been implicated in multiple ﬁbroproliferative diseases. Based on the ﬁbro-obliterative lesion found during bronchiolitis obliterans syndrome (BOS), we hypothesized that the type 2 immune mediated response is involved in chronic lung allograft rejection. Speciﬁcally, whereas acute rejection is, in part, a type 1 immune response, chronic rejection is, in part, a type 2 immune response. We found the type 2 cytokine, IL-13, to be elevated and biologically active in human bronchoalveolar lavage ﬂuid during BOS. Translational studies using a murine model of BOS demonstrated increased expression of IL-13 and its receptors that paralleled ﬁbro-obliteration. In addition, in vivo neutralization of IL-13 reduced airway allograft matrix deposition and murine BOS, by a mechanism that was independent of IL-4. Furthermore, using IL-13R (cid:1) 2 (cid:2) / (cid:2) mice, we found increased ﬁbro-obliteration. Moreover, anti-IL-13 therapy in combination with cyclosporin A had profound effects on reducing murine BOS. This supports the notion that IL-13 biological axis plays an important role during the pathogenesis of BOS independent of the IL-4 biological axis. The Journal of Immunology, 2007, 178: