Miracle-dz/UniFAR-FTUs huggingface dataset:
Implications of Conformal Invariance in Field Theories for General Dimensions

Abstract The requirements of conformal invariance for two- and three-point functions for general dimension d on flat space are investigated. A compact group theoretic construction of the three-point function for arbitrary spin fields is presented and it is applied to various cases involving conserved vector operators and the energy momentum tensor. The restrictions arising from the associated conservation equations are investigated. It is shown that there are, for general d, three linearly independent conformal invariant forms for the three-point function of the energy momentum tensor, although for d = 3 there are two and for d = 2 only one. The form of the three-point function is also demonstrated to simplify considerably when all three-points lie on a straight line. Using this the coefficients of the conformal invariant three-point functions are calculated for free scalar and fermion theories in general dimensions and for abelian vector fields when d = 4. Ward identities relating three- and two-point functions are also discussed. This requires careful analysis of the singularities in the short distance expansion and the method of differential regularisation is found convenient. For d = 4 the coefficients appearing in the energy momentum tensor three-point function are related to the coefficients of the two possible terms in the trace anomaly for a conformal theory on a curved space background.
The impact of a three-year teacher professional development course on quality of teaching: strengths and limitations of the dynamic approach

Abstract The dynamic approach (DA) suggests that professional development should be differentiated to meet teachers’ individual needs while engaging participants into systematic and guided critical reflection. Previous experimental studies demonstrated that one-year interventions based on the DA have a positive impact on teacher effectiveness. The study reported here investigates the impact that a long-term programme based on the DA can have on quality of teaching. In-service primary school teachers were randomly allocated into two groups. The first group received a three-year programme based on the DA whereas the second acted as the control group. Pre- and post-measurement of teaching skills was performed each year. Offering the DA for a longer period resulted in bigger effects on improving teaching skills but no change in the skills of the control group was observed. Differential effects for teachers situated at different levels are also reported. Implications of findings are drawn.
MAFIA: a maximal frequent itemset algorithm

We present a new algorithm for mining maximal frequent itemsets from a transactional database. The search strategy of the algorithm integrates a depth-first traversal of the itemset lattice with effective pruning mechanisms that significantly improve mining performance. Our implementation for support counting combines a vertical bitmap representation of the data with an efficient bitmap compression scheme. In a thorough experimental analysis, we isolate the effects of individual components of MAFIA including search space pruning techniques and adaptive compression. We also compare our performance with previous work by running tests on very different types of data sets. Our experiments show that MAFIA performs best when mining long itemsets and outperforms other algorithms on dense data by a factor of three to 30.
Word sequences as features in text-learning

Dunja Mladeni c & Marko Grobelnik J.Stefan Institute Jamova 39, 1000 Ljubljana, Slovenia Dunja.Mladenic@ijs.si, Marko.Grobelnik@ijs.si Abstract This paper proposes an e cient algorithm for the generation of new features that enrich the known bagof-words document representation. New features are generated based on word sequences of di erent length. Learning is performed using Naive Bayesian classi er on feature-vectors, where only highly scored features are used. The performance of enriched document representation is evaluated on the problem of automatic document categorization using Yahoo text hierarchy. Our experiments show that using word sequences of length up to 3 instead of using only single words improves the performance, while longer sequences in average have no in uence to the performance.
The Rise of Competition in Syntax: A Synopsis

Syntactic theories differ with respect to how they determine the wellformedness or illformedness of a given sentence Si in a given language. One possibility is that the decision of whether Si is grammatical or not can be made by exclusively considering properties of Si ; properties of other sentences S j , Sk , . are irrelevant. Another possibility is that properties of other sentences S j , Sk , . do play a role in deciding whether Si is grammatical or not in addition to Si ’s own properties. The first possibility, which we may call a local approach, can arguably be viewed as the standard one; this strategy is pursued in, e.g., most versions of government and binding theory (principles and parameters theory), head-driven phrase structure grammar, lexical-functional grammar (until recently), and in certain versions of the minimalist program. The second possibility presupposes a competition of sentences; hence, we will refer to it as a competition-based approach. This strategy is the one that this book is about; it is chosen in certain versions of the minimalist program (in particular, in earlier manifestations), in theories that incorporate the Blocking Principle (the Elsewhere Condition), and, last but not least, in optimalitytheoretic syntax. In what follows, we will illustrate fundamental differences between and points of convergence among local and competition-based approaches by considering government and binding theory (section 2) and its development into the minimalist program (section 3), blocking syntax (section 4), and optimality-theoretic syntax (section 5).
Develop yourself, develop others? How coaches and clients benefit from train-the-coach courses

ABSTRACT The majority of the numerous train-the-coach courses in the growing coaching market are not evidence-based and evaluate neither the personal development of coaches during these courses nor their effects on clients’ subsequent coaching success. The aim of our study was to investigate the development of coaches’ career-related variables during a train-the-coach course. Furthermore, we explored the effects of these coach variables on clients’ coaching success. Fifty-seven German university students participated in a five-month train-the-coach course and answered questionnaires regarding career-related variables at three points of time during the course. Afterwards, in groups of two or three, they led group coachings for the vocational orientation of secondary school pupils. The pupils (N = 104) answered questionnaires at the beginning, in the middle and at the end of the 10-week coaching process. Results indicated that coaches’ occupational self-efficacy, goal orientation and career adaptability significantly increased during the train-the-coach course. Furthermore, higher levels of coaches’ goal orientation and career adaptability led to stronger increases of clients’ career decision-making self-efficacy during the coaching process. This might be due to coaches’ role modelling behaviour. Our findings suggest that coaches not only gain technical competences during train-the-coach courses, but also improve in important career-related variables. Thus, train-the-coach courses might contribute to the personal development of university students. Additionally, coaches’ career-related variables indeed seem significant for clients’ coaching success and should therefore be encouraged during coach qualification.
Alternating Direction Algorithms for 1-Problems in Compressive Sensing

In this paper, we propose and study the use of alternating direction algorithms for several $\ell_1$-norm minimization problems arising from sparse solution recovery in compressive sensing, including the basis pursuit problem, the basis pursuit denoising problems of both unconstrained and constrained forms, and others. We present and investigate two classes of algorithms derived from either the primal or the dual form of $\ell_1$-problems. The construction of the algorithms consists of two main steps: (1) to reformulate an $\ell_1$-problem into one having blockwise separable objective functions by adding new variables and constraints; and (2) to apply an exact or inexact alternating direction method to the augmented Lagrangian function of the resulting problem. The derived alternating direction algorithms can be regarded as first-order primal-dual algorithms because both primal and dual variables are updated at every iteration. Convergence properties of these algorithms are established or restated when they already exist. Extensive numerical experiments are performed, using randomized partial Walsh-Hadamard sensing matrices, to demonstrate the versatility and effectiveness of the proposed approach. Moreover, we present numerical results to emphasize two practically important but perhaps overlooked points: (i) that algorithm speed should be evaluated relative to appropriate solution accuracy; and (ii) that when erroneous measurements possibly exist, the $\ell_1$-fidelity should generally be preferable to the $\ell_2$-fidelity.
Heparin Elevates Circulating Soluble fms-Like Tyrosine Kinase-1 Immunoreactivity in Pregnant Women Receiving Anticoagulation Therapy

Background— Alterations in circulating levels of pro- and antiangiogenic factors have been associated with adverse pregnancy outcomes. Heparin is routinely administered to pregnant women, but without clear knowledge of its impact on these factors. Methods and Results— We conducted a longitudinal study of 42 pregnant women. Twenty-one women received prophylactic heparin anticoagulation, and 21 healthy pregnant women served as controls. Compared with gestational age-matched controls, heparin treatment was associated with increased circulating levels of soluble fms-like tyrosine kinase-1 (sFlt-1) in the third trimester (P<0.05), in the absence of preeclampsia, placental abruption, or fetal growth restriction. Heparin had no effect on circulating levels of vascular endothelial growth factor, placenta growth factor, or soluble endoglin as assessed by ELISA. In vitro, low-molecular weight and unfractionated heparins stimulated sFlt-1 release from placental villous explants, in a dose- and time-dependent manner. This effect was not due to placental apoptosis, necrosis, alteration in protein secretion, or increased transcription. Western blot analysis demonstrated that heparin induced shedding of the N-terminus of Flt-1 both in vivo and in vitro as indicated by a predominant band of 100–112 kDa. By using an in vitro angiogenesis assay, we demonstrated that serum of heparin-treated cases inhibited both basal and vascular endothelial growth factor-induced capillary-like tube formation. Conclusions— Heparin likely increases the maternal sFlt-1 through shedding of the extracellular domain of Flt-1 receptor. Our results imply that upregulation of circulating sFlt-1 immunoreactivity in pregnancy is not always associated with adverse outcomes, and that heparin's protective effects, if any, cannot be explained by promotion of angiogenesis.
Enhancing the Detection of Metamorphic Malware using Call Graphs

Malware stands for malicious software. It is software that is designed with a harmful intent. A malware detector is a system that attempts to identify malware using Application Programming Interface (API) call graph technique and/or other techniques. API call graph techniques follow two main steps, namely, transformation of malware samples into an API call graph using API call graph construction algorithm, and matching the constructed graph against existing malware call graph samples using graph matching algorithm. A major issue facing malware API call graph construction algorithms is building a precise call graph from information collected about malware samples. On the other hand call graph matching is an NP-complete problem and is slow because of computational complexity . In this study, a malware detection system based on API call graph is proposed. In the proposed system, each malware sample is represented as an API call graph. API call graph construction algorithm is used to transform input malware samples into API call graph by integrating API calls and operating system resource to represent graph nodes. Moreover, the dependence between different types of nodes is identified and represented using graph edges. After that, graph matching algorithm is used to calculate similarity between the input sample and malware API call graph samples that are stored in a database. The graph matching algorithm is based on an enhanced graph edit distance algorithm that simplifies the computational complexity using a greedy approach to select best common subgraphs from the integrating API call graph with high similarity, which helps in terms of detecting metamorphic malware. Experimental results on 514 malware samples demonstrate that the proposed system has 98% accuracy and 0 false positive rates. Detailed comparisons against other detection methods have been carried out and significant improvement over
Semantic Similarity in Biomedical Ontologies

In recent years, ontologies have become a mainstream topic in biomedical research. When biological entities are described using a common schema, such as an ontology, they can be compared by means of their annotations. This type of comparison is called semantic similarity, since it assesses the degree of relatedness between two entities by the similarity in meaning of their annotations. The application of semantic similarity to biomedical ontologies is recent; nevertheless, several studies have been published in the last few years describing and evaluating diverse approaches. Semantic similarity has become a valuable tool for validating the results drawn from biomedical studies such as gene clustering, gene expression data analysis, prediction and validation of molecular interactions, and disease gene prioritization. We review semantic similarity measures applied to biomedical ontologies and propose their classification according to the strategies they employ: node-based versus edge-based and pairwise versus groupwise. We also present comparative assessment studies and discuss the implications of their results. We survey the existing implementations of semantic similarity measures, and we describe examples of applications to biomedical research. This will clarify how biomedical researchers can benefit from semantic similarity measures and help them choose the approach most suitable for their studies. Biomedical ontologies are evolving toward increased coverage, formality, and integration, and their use for annotation is increasingly becoming a focus of both effort by biomedical experts and application of automated annotation procedures to create corpora of higher quality and completeness than are currently available. Given that semantic similarity measures are directly dependent on these evolutions, we can expect to see them gaining more relevance and even becoming as essential as sequence similarity is today in biomedical research.
ASR Using Features With Syllable Units

A system for analyzing fabrication processes, such as analyzing device yield on a substrate. An input accesses fabrication information, where the fabrication information includes at least one of an dependent variable that is associated with substrate location information, and at least one independent variable that is associated with at least one of the fabrication processes. Desired portions of the substrate information are selected, based on at least one of the independent variable and the dependent variable. A substrate profile is produced, based on the desired portions of the fabrication information.
The mediation effect of customer satisfaction in the relationship between service quality, service orientation, and marketing mix strategy to customer loyalty

The purpose of this paper is to investigate the mediation effect of customer satisfaction in the relationship between service quality, service orientation, and marketing mix strategy to customer loyalty, in a study in Telkomsel-Indonesia. The product used in this research will take the telecommunication service product categories with a number of products available in the market. In this research, the telecommunication service products of Telkomsel with various features as the research objects were studied. ,The population of this research is Telkomsel customers who use the products of Halo, As and Simpati, domiciled in Malang, 2016. Since it was impossible to get the exact number of customers, the population in this study is infinite. The study had a sample size of 200 respondents. This research uses the structural equation modeling (SEM) analysis techniques along with AMOS methods. ,The quality of service, service orientation, and strategy marketing mix applied by the company are not all variables can directly affect customer loyalty, but must first going through satisfaction. Which means that companies must first need to understand what the customer needs through variable service quality, service orientation, and marketing mix strategy so that the customers feel loyal when the level of satisfaction is resolved. The service quality provided by the telecommunications industry needs to be improved in order to improve customer satisfaction and loyalty of telecommunications services, especially for Telkomsel in Malang. ,Originality for this paper shows: mediation effect (using the Sobel test) customer satisfaction on the effect of service quality, service orientation and marketing mix strategy to customer loyalty; location of the study (no previous research for this relationship): telecommunication services in Malang, Indonesia.
Lymphocyte activation after exposure to swine dust: a role of humoral mediators and phagocytic cells

Exposure to swine dust causes intense airway inflammation with multifold increase in inflammatory cells and secretion of pro-inflammatory cytokines. This in vitro study focuses on the swine-dust activation of lymphocytes in whole blood, in phagocyte-depleted whole blood and in peripheral blood mononuclear cells (PBMC), in order to investigate whether phagocytic cells and/or soluble mediators are involved in the activation of T-cells following exposure to organic dust from a swine confinement house. T-cell activation was analysed by flow cytometry with double staining for CD3 and the activation marker CD69. Swine dust (50 µg) incubated (24 h) with heparinized whole blood was shown to activate 27.6% of the T-cells, while swine dust incubated with whole blood depleted from phagocytic cells or PBMC only activated 4.5% and 4.8% of the T-cells, respectively. Plasma separated from whole blood preincubated with swine dust for 24 h stimulated as much as 32.4% of PBMC T-cells and contained high levels of interleukin (IL)-12 (14 pg·mL) and interferon (IFN)-γ (2284 pg·mL−1), while plasma from PBMC incubated with swine dust contained low levels of IL-12 (2 pg·mL−1) and IFN-γ (196 pg·mL−1). This study demonstrates that activation of T-cells by organic dust from a swine confinement building seems to require phagocytic cells, most likely acting through the release of soluble mediators. Also, conditioned plasma from swine-dust exposed whole blood, which was capable of activating T-cells, contained high concentrations of interleukin-12 and interferon-γ.
Diagnosis of hepatitis C virus infection in pregnant women in the healthcare system in Poland

AbstractThe hepatitis C virus (HCV) is globally recognized as a serious public health concern. Current statistics indicate that approximately 2% of people worldwide and 1.9% of people in Poland suffer from HCV infection.This study was conducted to assess the anti-HCV seroprevalence in pregnant women in Poland and subsequently provide recommendations on the rationale for obligatory screening.A total of 42,274 women participated in our study, of which 16,130 were pregnant. We were granted access to their health data stored in the form of electronic medical records kept by the network of outpatient clinics throughout Poland.The lowest rate of positive anti-HCV test results was found in women ages 25 to 34 (0.73%); however, younger and older age groups had similar rates (15–24 = 0.86%; 35–44 = 0.84%). Additional analysis of data from the period between 2011 and 2014 revealed a downward trend in the proportion of positive anti-HCV tests among pregnant women (mean positive anti-HCV = −0.001 × year + 1.9451; R2 = 0.7274). Regardless of the gradual increase in the number of female patients undergoing screening between 2004 and 2015, there has been a constant decrease in the rate of positive cases. The rate of pregnant women potentially infected with HCV was twice as lower than that in a control group of women undergoing tests for other medical circumstances: 0.76% vs 1.67% (P < 0.0001). Analysis of real-world data of female patients in Poland provides evidence that screening based on an individual's medical history and behavioral risk factors in clinical circumstances would be more effective than obligatory testing of all pregnant women.
Permuting Sparse Rectangular Matrices into Block-Diagonal Form

We investigate the problem of permuting a sparse rectangular matrix into block-diagonal form. Block-diagonal form of a matrix grants an inherent parallelism for solving the deriving problem, as recently investigated in the context of mathematical programming, LU factorization, and QR factorization. To represent the nonzero structure of a matrix, we propose bipartite graph and hypergraph models that reduce the permutation problem to those of graph partitioning by vertex separator and hypergraph partitioning, respectively. Our experiments on a wide range of matrices, using the state-of-the-art graph and hypergraph partitioning tools MeTiS and PaToH\@, revealed that the proposed methods yield very effective solutions both in terms of solution quality and runtime.
Genome-Wide Screen for Modifiers of Ataxin-3 Neurodegeneration in Drosophila

Spinocerebellar ataxia type-3 (SCA3) is among the most common dominantly inherited ataxias, and is one of nine devastating human neurodegenerative diseases caused by the expansion of a CAG repeat encoding glutamine within the gene. The polyglutamine domain confers toxicity on the protein Ataxin-3 leading to neuronal dysfunction and loss. Although modifiers of polyglutamine toxicity have been identified, little is known concerning how the modifiers function mechanistically to affect toxicity. To reveal insight into spinocerebellar ataxia type-3, we performed a genetic screen in Drosophila with pathogenic Ataxin-3-induced neurodegeneration and identified 25 modifiers defining 18 genes. Despite a variety of predicted molecular activities, biological analysis indicated that the modifiers affected protein misfolding. Detailed mechanistic studies revealed that some modifiers affected protein accumulation in a manner dependent on the proteasome, whereas others affected autophagy. Select modifiers of Ataxin-3 also affected tau, revealing common pathways between degeneration due to distinct human neurotoxic proteins. These findings provide new insight into molecular pathways of polyQ toxicity, defining novel targets for promoting neuronal survival in human neurodegenerative disease.