Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting NBA Player Performance

Predicting the outcomes of sporting events and the performances of athletes represents a natural application for machine learning. Major, professional sports such as the NBA, NFL, and MLB contain a significant amount of easily accessible data whose outcomes and player performances tend to be randomly distributed and offer attractive data to predict. The NBA is particularly well suited for machine learning applications because the performance of NBA players across different positions can be measured using the same set of statistics. This is unlike the NFL, for instance, where different positions are measured using different metrics (e.g. QB’s are measured based on how many TDs they throw while linebackers are measured based on how many people they sack/tackle).
Herpes Virus Fusion and Entry: A Story with Many Characters

Herpesviridae comprise a large family of enveloped DNA viruses all of whom employ orthologs of the same three glycoproteins, gB, gH and gL. Additionally, herpesviruses often employ accessory proteins to bind receptors and/or bind the heterodimer gH/gL or even to determine cell tropism. Sorting out how these proteins function has been resolved to a large extent by structural biology coupled with supporting biochemical and biologic evidence. Together with the G protein of vesicular stomatitis virus, gB is a charter member of the Class III fusion proteins. Unlike VSV G, gB only functions when partnered with gH/gL. However, gH/gL does not resemble any known viral fusion protein and there is evidence that its function is to upregulate the fusogenic activity of gB. In the case of herpes simplex virus, gH/gL itself is upregulated into an active state by the conformational change that occurs when gD, the receptor binding protein, binds one of its receptors. In this review we focus primarily on prototypes of the three subfamilies of herpesviruses. We will present our model for how herpes simplex virus (HSV) regulates fusion in series of highly regulated steps. Our model highlights what is known and also provides a framework to address mechanistic questions about fusion by HSV and herpesviruses in general.
The Effects of Behavioral Parent Training With Adjunctive Social Skills Training for a Preadolescent Girl With ADHD and Borderline Personality Features

Girls with attention deficit hyperactivity disorder (ADHD) are at high risk of a range of social–emotional difficulties, including peer rejection, suicide attempts, and borderline personality disorder (BPD), which are associated with serious, long-term impairment and have not emerged as clearly in samples of boys with ADHD. BPD is a particularly concerning long-term outcome of ADHD in girls, given the high risk for suicidality and long-lasting relationship difficulties. Very little research has focused on treatment for the interpersonal impairments of girls with ADHD, or on addressing risk for developing BPD. This case study describes the use of behavioral parent training (BPT) with adjunctive social skills training (SST) to address the social–emotional difficulties of a 9-year-old girl, “Violet,” who was diagnosed with ADHD Combined Presentation and was being treated with medication for anxiety. Violet presented with many social difficulties, including low self-esteem, emotional dysregulation, and unstable relationships, which were conceptualized as borderline personality features (BPF). Treatment was associated with improvements in parent functioning, including reductions in caregiver strain and inconsistent discipline, as well as improvements in child functioning, including reductions in ADHD symptoms, a range of impairments, and BPF. This case study illustrates the benefit of a brief psychosocial intervention in reducing multiple indices of interpersonal impairment, including BPF, for a girl with ADHD.
The Effect of L-Thyroxine Treatment on Hypothyroid Symptom Scores and Lipid Profile in Children with Subclinical Hypothyroidism

Objective: To evaluate i) the frequency of typical hypothyroidism symptoms in children with subclinical hypothyroidism (SH), ii) to evaluate the association of SH with lipoproteins and iii) to investigate possible improving effects of L-thyroxine (LT4) treatment on these findings. Methods: Twenty-seven children with SH who had elevated thyroid-stimulating hormone (TSH: >4.94 µIU/L) but normal free T4 levels and healthy euthyroid children of similar age and sex were enrolled in the study. Anthropometric and laboratory (lipid profile and thyroid function tests) measurements were performed at diagnosis and six months after euthyroidism was achieved. All children were also subjected to a questionnaire on hypothyroid symptoms at diagnosis. The SH patients were subjected to the questionnaire also following treatment. Pre-treatment data were compared with those of controls and post-treatment measurements. Results: Anthropometric and laboratory parameters of the groups were not statistically different except for higher TSH levels in the SH group. Serum lipoprotein levels and dyslipidemia frequency were similar between the groups. Compared to the controls, hypothyroidism symptom score was significantly higher in the SH group. Six months after euthyroidism was achieved, a significant reduction in the hypothyroid symptom score was obtained in the SH group. Except for significantly higher serum TSH values, no significant differences regarding demographic characteristics, symptom scores and lipid parameters were present between patients with Hashimoto’s thyroiditis and the remaining SH patients. Conclusion: The results of this study showed that in children with SH i) the hypothyroidism symptom score was significantly higher than in euthyroid children, ii) LT4 treatment improved the hypothyroidism symptom score and iii) SH does not seem to be associated with dyslipidemia.
Evaluating and Improving Inference-rules via Crowdsourcing

The importance of inference rules to semantic applications has long been recognized, and extensive work has been carried out to automatically acquire inference-rule resources. However, despite their potential, the utilization of inference rule resources is currently somewhat limited, in part due to the considerable number of rules which are in fact invalid. A possible solution to this problem is to enhance the quality of these resources by computing an estimate of the accuracy of its rules. Unfortunately, evaluating such resources has turned out to be a non-trivial task, leading to slow progress in the field. In this study, we demonstrate how the quality of an inference-rule resource can be enhanced using rule annotations. For this purpose we propose a framework for evaluating inference-rules using crowdsourcing. Our framework simplifies a previously proposed ‘instance-based evaluation’ method which evaluates a rule, based on a sample of its applications. The new framework eliminates the need for the substantial annotator training previously required, making it suitable for crowdsourcing. We show that our method produces a large amount of annotations with a kappa of 0.78 (considered as ‘substantial agreement’) between the online annotators and our manual annotations, without requiring training expert annotators. Two use cases are presented to demonstrate the utilization of the annotations gathered using the proposed crowdsourcing framework. The first demonstrates how the crowdsourcing framework can be used to evaluate the quality of an inference-rule resource, either by its developers or by potential users of the resource. The second use case sets out to accomplish the main goal of this work, improving the quality of an inference-rule resource, by combing the score given by the rule-learning algorithm with the accuracy according to the crowdsourced rule application annotations.
beta-Catenin associates with the actin-bundling protein fascin in a noncadherin complex

Catenins were first characterized as linking the cytoplasmic domains of cadherin cell-cell adhesion molecules to the cortical actin cytoskeleton. In addition to their essential role in modulating cadherin adhesivity, catenins have more recently been indicated to participate in cell and developmental signaling pathways. beta-Catenin, for example, associates directly with at least two receptor tyrosine kinases and transduces developmental signals within the Wnt pathway. Catenins also complex with the tumor suppressor protein adenomatous polyposis coli (APC), which appears to have a role in regulating cell proliferation. We have used the yeast two-hybrid method to reveal that fascin, a bundler of actin filaments, binds to beta-catenin's central Armadillo repeat domain. Western blotting of immunoprecipitates from cell line and mouse and rat brain extracts indicate that this interaction exists in vivo. Fascin and beta-catenin's association was further substantiated in vitro using purified proteins isolated from recombinant bacterial and baculoviral sources. Immunoprecipitation analysis indicates that fascin additionally binds to plakoglobin, which is highly homologous to beta-catenin but not to p120cas, a newly described catenin which contains a more divergent Armadillo-repeat domain. Immunoprecipitation, in vitro competition, and domain-mapping experiments demonstrate that fascin and E-cadherin utilize a similar binding site within beta-catenin, such that they form mutually exclusive complexes with beta-catenin. Immunofluorescence microscopy reveals that fascin and beta-catenin colocalize at cell-cell borders and dynamic cell leading edges of epithelial and endothelial cells. In addition to cell-cell borders, cadherins were unexpectedly observed to colocalize with fascin and beta-catenin at cell leading edges. It is conceivable that beta-catenin participates in modulating cytoskeletal dynamics in association with the microfilament-bundling protein fascin, perhaps in a coordinate manner with its functions in cadherin and APC complexes.
Finding an optimum edit script between an XML document and a DTD

Finding an optimum edit script between data plays an important role in data retrieval and data transformation. Many methods for finding an optimum edit script between two XML documents have been proposed so far, but few studies on finding an optimum edit script between an XML document and a DTD have been made. In this paper, we first show a polynomial-time algorithm that finds an optimum edit script between an XML document (modeled as an ordered tree) and a DTD. We next prove that, if the cost of an operation on a node in a tree may depend on the other nodes, then the corresponding decision problem becomes strongly NP-complete.
Loss Model Approximations and Sensitivity Computations for Wireless Network Design

We develop and evaluate a new method for estimating various performance metrics of multi-hop wireless networks, including MANETs. The estimates depend implicitly on network design parameters, and therefore the method can form the basis for designing such networks so as to achieve predictable performance bounds. Explicit simulation models for large wireless networks are too complex and can not be used for analysis and design of wireless networks in realistic settings. We introduce a simple approximate (throughput) loss model that couples the physical, MAC and routing layers. The model provides quantitative statistical relations between the loss parameters used to characterize multiuser interference and physical path conditions on the one hand and traffic rates between origin-destination pairs on the other. We use a fixed point approach together with recently proposed models for the MAC layer to find a consistent solution satisfying all equations in the set. The result is an implicit model of performance metrics, such as throughput, packet loss, delay, parameterized by design variables, such as path routing probabilities, power levels, noise levels. We next apply Automatic Differentiation (AD) to these implicit performance models, and develop a methodology for design and parameter selection/tuning of wireless protocols.
One decade of environmental education research in Brazil: trajectories and trends in three national scientific conferences (ANPEd, ANPPAS and EPEA)

Abstract This article discusses the scientific research work on environmental education presented during the last decade in three Brazilian conferences: the meetings of the National Association of Graduate Research on Education (Associação Nacional de Pós-Graduação e Pesquisa em Educação, ANPEd), the National Association of Graduate Research on Environment and Society (Associação Nacional de Pós-Graduação e Pesquisa em Ambiente e Sociedade, ANPPAS), and the Environmental Education Research Meetings (Encontros de Pesquisa em Educação Ambiental, EPEA). It analyzes the authors, institutions, and regions whence the studies came from, as well as their main research subjects. Our findings indicate the prevalence of women in all academic degree segments; of PhD holders and candidates; of professors in public higher education institutions located in the Brazilian Southwest and South regions; and of environmental education in formal teaching as the main subject in all three conferences. Based on these results, we discuss how this body of research relates to the development of Brazilian academic and educational policies, and indicate some of the challenges involved in building a research tradition in this field, in close dialogue with the arduous political and pedagogical path of environmental education in Brazilian schools.
A Class of Fast Exact Bayesian Filters in Dynamical Models With Jumps

We address the statistical filtering problem in dynamical models with jumps. When a particular application is adequately modeled by linear and Gaussian probability density functions with jumps, a usual method consists in approximating the optimal Bayesian estimate [in the sense of the minimum mean square error (MMSE)] in a linear and Gaussian jump Markov state space system (JMSS). Practical solutions include algorithms based on numerical approximations or on sequential Monte Carlo (SMC) methods. In this paper, we propose a class of alternative methods which consists in building statistical models which, locally, similarly model the problem of interest, but in which the computation of the MMSE estimate can be be computed exactly (without numerical nor SMC approximations) and at a computational cost which is linear in the number of observations.
RESEARCH OUTPUTS / RÉSULTATS DE RECHERCHE

The problem of managing inconsistencies within and between models is omnipresent in software engineering. Over the years many different inconsistency management approaches have been proposed by the research community. Because of their large diversity of backgrounds and the diversity of models being considered, it is difﬁcult to pinpoint what these approaches have in common and what not. As a result, researchers encounter difﬁculties when positioning and comparing their work with existing state-of-the-art, or when collaborating on or combining different approaches. Also, end-users have a hard time making informed decisions to select the most appropriate approach. To address these problems, we present a unifying conceptual framework of deﬁnitions and terminology, independent of any concrete inconsistency management approach or (modelling) language. The contribution is a formal framework providing a common understanding of what (in)consistency means, what inconsistency management involves and what assumptions are commonly made by existing approaches. The formalisation is also illustrated with four instantiations taken from different research ﬁelds.
Bi-grappin: bipartite graph based protein-protein interaction network similarity search

We propose an algorithm, called BI-GRAPPIN, to search for similarities across PPI networks. The technique core consists in computing a maximum weight matching of bipartite graphs to compare the neighborhoods of pairs of proteins in different PPI networks. The idea is that proteins belonging to different networks should be matched look- ing not only at their own sequence similarity, but also at the similarity of proteins they "strongly" interact with, ei- ther directly or indirectly. We implemented the method and tested it on both real and synthetic data, showing its effec- tiveness in solving ambiguous situations and in individuat- ing functionally related proteins. Differently from previous work, the presented algorithm allows to take into account both quantitative and reliability information possibly avail- able about interactions.
A SKYPE ML DATASETS VALIDATION AND DETECTION MECHANISM USING MACHINE LEARNING APPROACH

A bstract— Internet traffic classification is an area of current research interest. Identification of real time applications such as Skype has gained more attention in the last few years. Skype traffic classification is challenging because Skype uses encrypted traffic and uses no well-known port number. Several methods which used both signature-based and statistical approaches were proposed. However, the training and testing datasets validation have not been formally addressed. This work highlights the problem of machine learning (ML) datasets validation and proposes a mechanism based on ML statistical approach to identify Skype traffic. Two different networks environment are considered for Skype traffic to gain insight into the statistical features of Skype traffic. Ten algorithms within Weka are used to examine the best algorithm for the given datasets. Random Forest was found to be the best resulting in more than 99.8% accuracy.
Composite annotations with inter-type declarations in aspect-oriented programming

This paper discusses problem of repeating annotations' clones in the code that is considered bad smell in annotations' usage. Composite annotations compose a repeating group of annotations into a single one so that can be used instead of the repeating group. We propose a new approach to composite annotations implementation using aspect-oriented programming. We discuss the options for composite annotations available in the AspectJ language, explain the benefits of using our approach over the existing solutions, and identify AspectJ shortcomings that hamper full potential of AOP for composite annotations. The approach is presented on examples and includes guidelines for implementing composite annotations in AspectJ.
SURVEY DATA COLLECTION METHODOLOGY FOR ELECTION MISSIONS: HOW PROFESSIONAL FORM DESIGN HELPS TO CONTROL A SURVEY

The present case study discusses some difficulties in applying survey methodology to the observation of elections by international observers. In election missions data collected through observation forms should justify general statements on the freedom and the fairness of the election observed. The paper focuses on observations of the voting during visits to polling stations and the observation forms used to collect the information gained in these visits. Important differences between election observation surveys and regular self-administered surveys are, to varying degrees, lack of control over (a) sampling, (b) what is to be observed and reported, and (c) data processing and analysis due to time pressure and logistic circumstances. It is shown what progress has been made on points (b) and (c) between the 1995 Russian State Duma Elections and the 1996 Russian Presidential Elections. The whole statistical process was reviewed, various experts were consulted, and redesigned forms were tested. The resulting new forms in general conformed to the Jenkins and Dillman (1997) principles referring to (o) form content, (1) instructions and explanations, (2) form compositon, and (3) guidance through the form. Theoretical and empirical evidence asserts that professional form design helps to optimize response rates, increase reporting accuracy, and decrease processing times. In our study, form return rates increased from ca. 50 percent to ca. 90 percent, data quality improved, and preliminary results were available within 48 hours. Correspondence to Statistics Netherlands (SutNeth), P.O. Box 4481, 6401 CZ Heerlen, The Netherlands; on questionnaire design methodology to Dr. J. C. Akkerboom, Questionnaire Design Resource Centre, Department of Data Collection Methodology (GWM), and on election monitoring methodology to J. J. G. Schmeets, Department of Social-Cultural Surveys (KPE), E-mail: HAKM@CBS.NL and HSHS@CBS.NL The views and opinions expressed in this piper are those of the authors and do not necessarily reflect official Statistics Netherlands (SutNeth) policies. We would like to acknowledge Jan de Looff, graphic design and desktop publishing specialist at SutNeth, for his invaluable contributions to the design of voting and counting forms. His ideas very much shaped form (re-)design as discussed here. © World Association for Public Opinion Research 1998 258 INTERNATIONAL JOURNAL OF PUBLIC OPINION RESEARCH
Alternating proximal algorithm for blind image recovery

We consider a variational formulation of blind image recovery problems. A novel iterative proximal algorithm is proposed to solve the associated nonconvex minimization problem. Under suitable assumptions, this algorithm is shown to have better convergence properties than standard alternating minimization techniques. The objective function includes a smooth convex data fidelity term and nonsmooth convex regularization terms modeling prior information on the data and on the unknown linear degradation operator. A novelty of our approach is to bring into play recent nonsmooth analysis results. The pertinence of the proposed method is illustrated in an image restoration example.
Elastic traces for fast and accurate system performance exploration

As computer systems become increasingly complex, the need for fast and accurate simulation tools increases. Accurate but slow processor core models are often substituted with simple trace players to achieve faster memory-system simulation. However, existing trace-driven simulation techniques are limited in their applicability and availability. In this work, we capture elastic traces containing out-of-order core dependencies and effects of speculative execution, which overcome limitations of existing work. Additionally, we make our capture and replay modelling available in the gem5 simulator. Our trace-driven CPU achieves a speed-up of 6-8x compared to the reference core and predicts the performance with less than 1% error on average when the memory-system is changed.
MySearchView: a customized metasearch engine generator

In this paper, we describe MySearchView, a system for assembling search engines into metasearch engines. With this system, any user can create a metasearch engine by simply letting the system know the URLs of the search engines the user wants to be included and the metasearch engine will be built fully automatically. In this paper, the main steps of building metasearch engines will be sketched. We will also outline our plan to demonstrate all the features of MySearchView.