Miracle-dz/UniFAR-FTUs huggingface dataset:
A Static Malware Detection System Using Data Mining Methods

A serious threat today is malicious executables. It is designed to damage computer system and some of them spread over network without the knowledge of the owner using the system. Two approaches have been derived for it i.e. Signature Based Detection and Heuristic Based Detection. These approaches performed well against known malicious programs but cannot catch the new malicious programs. Different researchers have proposed methods using data mining and machine learning for detecting new malicious programs. The method based on data mining and machine learning has shown good results compared to other approaches. This work presents a static malware detection system using data mining techniques such as Information Gain, Principal component analysis, and three classifiers: SVM, J48, and Naive Bayes. For overcoming the lack of usual anti-virus products, we use methods of static analysis to extract valuable features of Windows PE file. We extract raw features of Windows executables which are PE header information, DLLs, and API functions inside each DLL of Windows PE file. Thereafter, Information Gain, calling frequencies of the raw features are calculated to select valuable subset features, and then Principal Component Analysis is used for dimensionality reduction of the selected features. By adopting the concepts of machine learning and data-mining, we construct a static malware detection system which has a detection rate of 99.6%.
Emotional Self-Regulation in Adults With Attention-Deficit / Hyperactivity Disorder ( ADHD ) : The Relative Contributions of Emotional Impulsiveness and ADHD Symptoms to Adaptive Impairments in Major Life Activities

Background: Recent reviews have argued that emotional impulsiveness (EI) and deficient emotional selfregulation are central components in attention-deficit/hyperactivity disorder (ADHD), not merely associated features or the consequence of comorbidity. Objectives: Our study has 2 aims: (1) to determine the frequency/severity of EI in adults with ADHD relative to these control groups; and (2) to evaluate the degree to which EI contributed to impairment in various domains of major life activities beyond that made by severity of the traditional 2 dimensions of ADHD (inattention, hyperactivity-impulsivity). Methods: We examined the frequency and severity of problems with EI in 3 groups: adults with ADHD (n = 146), clinical-control adults not diagnosed with ADHD (n = 97), and a community-control group (n = 109). Selfand other ratings of EI were utilized. Results: Results indicated that adults with ADHD had significantly more EI than either clinical or community controls, whether by selfor other reports, and whether symptoms were studied individually or in total. We also evaluated the extent to which EI contributed to the prediction of global ratings of selfand other rated impairments in 10 different domains beyond the contribution made by the traditional 2 dimensions of ADHD symptoms. EI uniquely contributed to 6 of 10 domains and overall impairment. We then evaluated this issue using more detailed measures of occupational impairment, educational history, criminal history, adverse driving outcomes, marital satisfaction, parenting stress, and offspring severity of ADHD, oppositional defiant disorder, and conduct disorder. Severity of EI independently contributed to most measures of impairment beyond severity of the 2 ADHD symptom dimensions and, in many cases, was the only predictor of some impairments. Conclusions: Our results indicate that EI is as central a component of ADHD as are its 2 traditional symptom dimensions. EI severity is not merely redundant with the other ADHD symptom dimensions, but adds additional explanatory and predictive power to understanding various forms of adult impairment. (J ADHD Relat Disord. 2010;1[4]:5–28) © 2010 Excerpta Medica.
Transactivation of EGFR mediates insulin-stimulated ERK1/2 activation and enhanced cell migration in human corneal epithelial cells.

PURPOSE Insulin activates phosphatidylinositol 3-kinase (PI3K) and extracellular signal-regulated kinase (ERK)-1/2 in human corneal epithelial cells. These events have been shown to be involved in wound healing. However, the mechanism of insulin-induced ERK pathway is not clear during corneal wound healing. In this study, the effect of insulin associated with epidermal growth factor receptor (EGFR) on wound healing in transformed human corneal epithelial cells was investigated to determine the signaling mechanism involved. METHODS SV40-immortalized human corneal epithelial (THCE) cells were cultured on a diluted Matrigel matrix that resembled the basement membrane of the corneal epithelium. A wound was introduced with a micropipette tip, and closure of the scratch wound was photographed 12 h after exposure to insulin. Activation of EGFR was analyzed by immunoprecipitation, and cytoskeletal rearrangements were visualized with rhodamine-conjugated phalloidin. RESULTS Exposure of corneal epithelial cells to insulin induced phosphorylation of EGFR. Inhibition of EGFR activation by AG1478 or the MMP inhibitor, GM6001, reduced phosphorylation of insulin-induced ERK in the presence of insulin and delayed wound closure. In addition, cells exposed to insulin contained stress fibers and their submembranous cortical actin was depleted. These effects were inhibited by AG1478. CONCLUSIONS Inhibition of EGFR activity decreases cell migration involved in insulin-induced wound repair, an effect that mimics inhibition of MMP activation. Inhibition of MMP activity leads to decreased EGFR phosphorylation. Our data show that insulin stimulates wound healing in the corneal epithelium by activating EGFR, and point to a novel insulin signaling pathway that acts during corneal wound healing.
Shifting priorities

We investigated whether partners in newly developing romantic relationships adjust their goals when they experience conflict with the goals of their partner, and the consequences of goal conflict and goal adjustment. Fifty-nine newly dating couples (N = 118) reported on their goals at an initial session and again 3 months later. Multilevel models indicated that when people reported higher conflict between a goal and their partner’s goals, they were more likely to stop pursuing as well as to devalue the importance of that particular goal over time. Furthermore, goal devaluing was associated with increases in relationship commitment over time but decreases in women’s relationship satisfaction when their partners devalued conflicting goals. Overall levels of goal conflict were associated with marginal decreases in relationship satisfaction. These results indicate that romantic partners try to adjust their goals to reduce goal conflict even in developing relationships, and that these adjustments have consequences for relationship satisfaction and commitment.
Method for Assessing Software Quality Using Source Code Analysis

Software systems and products are widely used in our personal daily life, business activities, hospitals, aviation and many other fields. These software products should not only satisfy the requirements of their intended users but also should be able to compete with other similar software products available in the market. Assessment of software product quality can be achieved by analyzing and specifying the quality characteristics which is defined in software quality models and standards, based on the quality reports defined by the stakeholders. However, assessment of software quality is not an easy task and as time passes, the characteristic of new software systems and products will change. In this research, a quality assessment method is proposed based on the latest software quality standard ISO/IEC 25010. This method performs code analysis using two perspectives (structural and rule violation-based quality measure metrics) to analyse four quality characteristics (i.e., performance, security, maintainability and reliability). The code analysis process is done by extracting structural elements and tracking defects which prevent a software system to have good architectural and coding practices. An automated tool is developed to facilitate and support the code analysis and software quality assessment.
A Proto-Architecture for Innate Directionally Selective Visual Maps

Self-organizing artificial neural networks are a popular tool for studying visual system development, in particular the cortical feature maps present in real systems that represent properties such as ocular dominance (OD), orientation-selectivity (OR) and direction selectivity (DS). They are also potentially useful in artificial systems, for example robotics, where the ability to extract and learn features from the environment in an unsupervised way is important. In this computational study we explore a DS map that is already latent in a simple artificial network. This latent selectivity arises purely from the cortical architecture without any explicit coding for DS and prior to any self-organising process facilitated by spontaneous activity or training. We find DS maps with local patchy regions that exhibit features similar to maps derived experimentally and from previous modeling studies. We explore the consequences of changes to the afferent and lateral connectivity to establish the key features of this proto-architecture that support DS.
Deep Ranking for Person Re-Identification via Joint Representation Learning

This paper proposes a novel approach to person re-identification, a fundamental task in distributed multi-camera surveillance systems. Although a variety of powerful algorithms have been presented in the past few years, most of them usually focus on designing hand-crafted features and learning metrics either individually or sequentially. Different from previous works, we formulate a unified deep ranking framework that jointly tackles both of these key components to maximize their strengths. We start from the principle that the correct match of the probe image should be positioned in the top rank within the whole gallery set. An effective learning-to-rank algorithm is proposed to minimize the cost corresponding to the ranking disorders of the gallery. The ranking model is solved with a deep convolutional neural network (CNN) that builds the relation between input image pairs and their similarity scores through joint representation learning directly from raw image pixels. The proposed framework allows us to get rid of feature engineering and does not rely on any assumption. An extensive comparative evaluation is given, demonstrating that our approach significantly outperforms all the state-of-the-art approaches, including both traditional and CNN-based methods on the challenging VIPeR, CUHK-01, and CAVIAR4REID datasets. In addition, our approach has better ability to generalize across datasets without fine-tuning.
Physical influences on forest types and deer habitat, northern Fiordland, New Zealand

Forest types of the Wapiti, Doon and Glaisnock catchments, ranked in order of proportion of preferred food species for deer, paralleled a gradient of landform stability. Seral forests and low altitude silver beech forests were preferred deer habitat because they contained the largest proportions of highly preferred species. They often occurred on unstable landforms such as debris cones, colluvial sideslopes, and terraces with recent and compound soils, assumed to be of high nutrient status. In contrast, mountain beech and high altitude silver beech forests supported lower proportions of highly preferred food species and were poor deer habitat. They occurred on more stable landforms such as bedrock sideslopes, ridges and benches with poorlydrained, infertile soils. The Wapiti/Doon catchments contained a greater abundance of more stable landforms than the Glaisnock and therefore provided poorer deer habitat in the predominant mountain beech forests.
Human Infant Faces Provoke Implicit Positive Affective Responses in Parents and Non-Parents Alike

Human infants' complete dependence on adult caregiving suggests that mechanisms associated with adult responsiveness to infant cues might be deeply embedded in the brain. Behavioural and neuroimaging research has produced converging evidence for adults' positive disposition to infant cues, but these studies have not investigated directly the valence of adults' reactions, how they are moderated by biological and social factors, and if they relate to child caregiving. This study examines implicit affective responses of 90 adults toward faces of human and non-human (cats and dogs) infants and adults. Implicit reactions were assessed with Single Category Implicit Association Tests, and reports of childrearing behaviours were assessed by the Parental Style Questionnaire. The results showed that human infant faces represent highly biologically relevant stimuli that capture attention and are implicitly associated with positive emotions. This reaction holds independent of gender and parenthood status and is associated with ideal parenting behaviors.
Crossing borders: the lived experiences of Brazilians on the move

Starting from the observation that Brazilian history has led to the development of a very distinct system of race relations, this paper focuses on the (re)creation of ethnic divisions in a new city, Palmas, the capital of the Brazilian state Tocantins. Because the city was only founded in 1990, internal migration has heavily influenced the composition of the city’s population. The research shows that residential proximity and interaction between whites and non-whites is largely limited to the poor neighbourhoods of the city. Subtle racism continues to exist, deriving from a way of thinking that naturalises the racial hierarchy. The absence of clearly defined racial categories and the centrality of miscegenation to the Brazilian identity complicate the further dismantling of this racist culture.
Genetic interactions between protein phosphatases CaPtc2p and CaPph3p in response to genotoxins and rapamycin in Candida albicans.

In Saccharomyces cerevisiae cells, both of the two PP2C protein phosphatases ScPtc2p and ScPtc3p and the PP4 protein phosphatase ScPph3 are responsible for ScRad53p dephosphorylation after the DNA methylation agent methylmethane sulfonate (MMS)-induced DNA damage. In this study, we show that CaPtc2p is not required for the CaRad53p dephosphorylation during the recovery from DNA damage, as is CaPph3p in Candida albicans. However, deletion of CaPPH3 has an additive effect on the sensitivity of C. albicans cells lacking CaPTC2 to MMS and the DNA synthesis inhibitor hydroxyurea (HU). In addition, deletion of CaPPH3 promotes in vitro filamentation of C. albicans cells. Furthermore, mutation of CaPTC2 is epistatic to that of CaPPH3 in the sensitivity of C. albicans cells to rapamycin. Therefore, CaPtc2p and CaPph3p might play a role in the target of rapamycin (TOR) signaling in C. albicans cells.
Giftedness and evidence for reproducibly superior performance: an account based on the expert performance framework

Giftedness researchers have long debated whether there is empirical evidence to support a distinction between giftedness and attained level of achievement. In this paper we propose a general theoretical framework that establishes scientific criteria for acceptable evidence of superior reproducible performance, which any theory of exceptional performance must explain. We review evidence for superior reproducible performance, generally emerging only after extended periods of deliberate practice that result in subsequent physiological adaptations and complex cognitive mechanisms. We also apply this framework to examine proposed evidence for innate talents. With the exception of fixed genetic factors determining body size and height, we were unable to find evidence for innate constraints to the attainment of elite achievement for healthy individuals.
Detection of significant patterns by compression algorithms: the case of approximate tandem repeats in DNA sequences

MOTIVATION Compression algorithms can be used to analyse genetic sequences. A compression algorithm tests a given property on the sequence and uses it to encode the sequence: if the property is true, it reveals some structure of the sequence which can be described briefly, this yields a description of the sequence which is shorter than the sequence of nucleotides given in extenso. The more a sequence is compressed by the algorithm, the more significant is the property for that sequence. RESULTS We present a compression algorithm that tests the presence of a particular type of dosDNA (defined ordered sequence-DNA): approximate tandem repeats of small motifs (i.e. of lengths < 4). This algorithm has been experimented with on four yeast chromosomes. The presence of approximate tandem repeats seems to be a uniform structural property of yeast chromosomes.
Decision-making in opioid-dependent individuals using the Iowa Gambling Task

Decision-making impairments have been highlighted in opioid-dependent individuals using the Iowa Gambling Task (IGT). The objective of this study was to assess decision-making under uncertainty in opioid-dependent subjects. The sample included 64 abstinent opioid-dependent individuals under treatment and 48 control subjects. Group equivalence was analyzed considering age, gender and educational variables. In both groups, most subjects showed borderline performance, followed by disadvantageous performance and advantageous performance. Both groups showed a preference for low punishment frequency decks (B and D). In both groups, education and gender do not account for IGT performance, and learning differences in the IGT could be in part attributable to cognitive functions as assessed by the MoCA. Opioid- dependent individuals and the control group showed no significant differences in performance
Hybrid spamicity score approach to web spam detection

Web spamming refers to actions intended to mislead search engines and give some pages higher ranking than they deserve. Fundamentally, Web spam is designed to pollute search engines and corrupt the user experience by driving traffic to particular spammed Web pages, regardless of the merits of those pages. Recently, there is dramatic increase in amount of web spam, leading to a degradation of search results. Most of the existing web spam detection methods are supervised that require a large set of training web pages. The proposed system studies the problem of unsupervised web spam detection. It introduces the notion of spamicity to measure how likely a page is spam. Spamicity is a more flexible measure than the traditional supervised classification methods. In the proposed system link and content spam techniques are used to determine the spamicity score of web page. A threshold is set by empirical analysis which classifies the web page into spam or non spam.
Lexical standards for expository writing at Grade 3:The transition from early literacy to academic literacy

This article reports on an investigation of vocabulary thresholds across four standards of writing quality for grade 3 children. An expository prompt was used to elicit first draft writing from 222 students. A quota sampling strategy was used to create a learner corpus of 80 papers. Online lexical profiling tools were used to generate indices of lexical richness. Distinct differences in vocabulary use were noted between quality standards, in particular the ability to access low frequency words among the samples judged of excellent quality. Pedagogical implications emerge for classroom practitioners to address the language learning needs of linguistically vulnerable youngsters. Key words: expository prose, writing, transitional literacy, vocabulary profiling
A Combinatorial Searching Method for Detecting a Set of Interacting Loci Associated with Complex Traits

Complex diseases are presumed to be the results of the interaction of several genes and environmental factors, with each gene only having a small effect on the disease. Mapping complex disease genes therefore becomes one of the greatest challenges facing geneticists. Most current approaches of association studies essentially evaluate one marker or one gene (haplotype approach) at a time. These approaches ignore the possibility that effects of multilocus functional genetic units may play a larger role than a single‐locus effect in determining trait variability. In this article, we propose a Combinatorial Searching Method (CSM) to detect a set of interacting loci (may be unlinked) that predicts the complex trait. In the application of the CSM, a simple filter is used to filter all the possible locus‐sets and retain the candidate locus‐sets, then a new objective function based on the cross‐validation and partitions of the multi‐locus genotypes is proposed to evaluate the retained locus‐sets. The locus‐set with the largest value of the objective function is the final locus‐set and a permutation procedure is performed to evaluate the overall p‐value of the test for association between the final locus‐set and the trait. The performance of the method is evaluated by simulation studies as well as by being applied to a real data set. The simulation studies show that the CSM has reasonable power to detect high‐order interactions. When the CSM is applied to a real data set to detect the locus‐set (among the 13 loci in the ACE gene) that predicts systolic blood pressure (SBP) or diastolic blood pressure (DBP), we found that a four‐locus gene‐gene interaction model best predicts SBP with an overall p‐value = 0.033, and similarly a two‐locus gene‐gene interaction model best predicts DBP with an overall p‐value = 0.045.
Actin branching in the initiation and maintenance of lamellipodia

Using correlated live-cell imaging and electron tomography we found that actin branch junctions in protruding and treadmilling lamellipodia are not concentrated at the front as previously supposed, but link actin filament subsets in which there is a continuum of distances from a junction to the filament plus ends, for up to at least 1 μm. When branch sites were observed closely spaced on the same filament their separation was commonly a multiple of the actin helical repeat of 36 nm. Image averaging of branch junctions in the tomograms yielded a model for the in vivo branch at 2.9 nm resolution, which was comparable with that derived for the in vitro actin–Arp2/3 complex. Lamellipodium initiation was monitored in an intracellular wound-healing model and was found to involve branching from the sides of actin filaments oriented parallel to the plasmalemma. Many filament plus ends, presumably capped, terminated behind the lamellipodium tip and localized on the dorsal and ventral surfaces of the actin network. These findings reveal how branching events initiate and maintain a network of actin filaments of variable length, and provide the first structural model of the branch junction in vivo. A possible role of filament capping in generating the lamellipodium leaflet is discussed and a mathematical model of protrusion is also presented.
Results from Bilateral Estimations : Eurozone 1999 : Q 1-2006 : Q 1 21 5 Pooled OLS and Panel Estimations : Eurozone 1999 : Q 1-2006 : Q 1 24 6 Instrumental Variables ( IV ) Panel Estimations : Eurozone

The negative correlation between relative consumption growth and real exchange rate changes is a recurrent puzzle in international macroeconomics (Backus and Smith, 1993). Using panel dataset with quarterly observations for all 12 countries from the Eurozone after the introduction of the common currency (1999-2006), this paper demonstrates that the nominal exchange rate is the main source of the puzzle. When nominal exchange rates are eliminated, relative consumption growth is positively correlated with the change in the real exchange rate. Moreover, I contrast this result with alternative samples with flexible nominal exchange rates: while the inflation differential is still positively correlated, the nominal exchange rate change is negatively correlated with relative consumption growth. These findings are robust to alternative regression specifications, estimation methods, and data samples. JEL classification: F31, F41