Miracle-dz/UniFAR-FTUs huggingface dataset:
Circulating Endothelial Microparticles and Correlation of Serum 1,25-Dihydroxyvitamin D with Adiponectin, Nonesterified Fatty Acids, and Glycerol from Middle-Aged Men in China

The aim of the present study is (1) to determine the correlation between circulating 1,25-dihydroxyvitamin D [25(OH)D] and adiponectin, nonesterified fatty acids (NEFAs), and glycerol and (2) to determine the alterations in circulating endothelial microparticles (EMPs) in Chinese male subjects with increased body mass index (BMI). A total of 45 male adults were enrolled with varied BMI [i.e., lean, overweight (OW), and obese (OB), N = 15 per group]. Blood samples were collected under overnight fasting condition, and plasma was isolated for the measurement of endothelial microparticles (EMPs), total and high-molecular weight (HMW) adiponectin, 25(OH)D, nonesterified fatty acids (NEFAs), and glycerol. Circulating 25(OH)D levels were inversely associated with total adiponectin, NEFA, and glycerol levels. There is no difference for CD62E+ or CD31+/CD42b− EMPs among 3 groups. In Chinese male adults with varied BMI, an inverse correlation existed between 25(OH)D levels and total adiponectin, NEFA, and glycerol levels; and there is no significant difference for CD62E+ or CD31+/CD42b− EMPs among lean, overweight, and obese subjects.
Multi-Period Credit Default Prediction - A Survival Analysis Approach

The book deals with the problem to estimate credit default probabilities under a flexible multi-period prediction horizon. Multi-period predictions are naturally desirable because the maturity of loans usually spans several periods. However, single-period models largely prevail in the literature so far due to their simplicity. Predicting over multiple periods indeed entails certain challenges that do not arise within a single-period view. Among the main contributions of this work to the literature is to show that there are relatively simple solutions to these challenges available. From a methodological point of view, a survival analysis approach is used. In a survival analysis context, the time until default (or lifetime) is the central variable under investigation as opposed to the traditional approach of reducing the information to a binary variable representing the default event. Modeling the time until default has the advantage that both the timing of default events and censored data are utilized. Since both issues gain importance as the prediction horizon grows it is no coincidence that a survival analysis approach is selected for the multi-period prediction problem. The main results of the work are the following. First, a new index for measuring the predictive accuracy of default predictions is proposed and its advantages over commonly used indices are shown both theoretically and by an empirical analysis. This is part of the second chapter which further includes new methods of statistical inference for the new index. In the third chapter, default prediction models for the case of panel datasets with time-varying covariates are dealt with. A new approach is developed that is simpler than the models available in the literature so far. In an empirical study concerning North American public firms, we provide evidence that the proposed approach delivers more accurate predictions than its competitors as well. In the final chapter, the problem of assigning default probability estimates to given rating grades is examined. If default events are rare, standard approaches have certain drawbacks. As an alternative, an empirical Bayes approach is presented that mitigates the effects of data sparseness. The new estimator is applied to a comprehensive sample of sovereign bonds. Among the main findings of the empirical part is that capital requirements for sovereign bonds are likely to be underestimated by using standard approaches but not when using the empirical Bayes estimator.
Personalized movie recommendation

Facing the vast amount of novel production in the movie industry, people are in favor of choosing their favorite candidates quickly and previewing movie contents conveniently so as to decide whether they appeal to their personal taste. To meet this growing need, researchers are paying more attention on Personalization and Recommendation, the new trends of multimedia information retrieval, by integrating content and contextual information. In this paper, we propose a hierarchical framework for personalized movie recommendation. First, movie weekly ranking information is utilized for movie association and recommendation. Then, an integrated graph with both movie content and user preference is constructed to generate dynamic movie synopsis for personalized navigation. The superiorities of the proposed method have two aspects: 1) The prior knowledge independent recommendation scheme is implemented to replace the traditional ranking method for novel information access; 2) Personalized movie synopsis is interactively produced to replace the current movie trailer for preview. The promising results of subjective evaluation indicate that the proposed framework can discover the latent relationship between movies as well as movie highlights and therefore provide personalized movie recommendation to effectively lead movie access in an individualized manner.
Energy efficient routing with mutual information accumulation

We consider minimum-energy routing in a wireless network. We assume the use of ideal rateless codes, so that a node can accumulate transmission rates from the transmission of previous nodes on the routing path. Mutual information accumulation has significant advantages when compared with classical cooperative schemes that use energy accumulation. However, the resource allocation problem becomes more complex, as it involves the determination of 1) Routing path, 2) Transmission duration of each node, and 3) Transmission power of each node. We formulated the problem as an optimization problem, where the objective function is the total energy expenditure and the constraints are minimum mutual information for each node and the maximum total transmission time. We make a slotted-time assumption, and given the routing path and transmission duration, power optimization problem becomes convex. The optimal routing path and transmissions durations are found using a Branch-and-Bound technique. A distributively implementable greedy algorithm is also found and performance are compared by numerical simulations.
A Selenium based approach to automatic test script generation for refactoring JavaScript code

During the development process of Web application, two essential phases are software testing and code refactoring. However, automatic testing script plays an important role in test automation. It has been a hot research topic in Web application. In order to refactor the JavaScript code of Web application more conveniently, an approach to automatic script generation from the defined test case is introduced in this paper. First, it describes the test case using customized XML format. Then, since Selenium platform supports multi-browsers testing, a method to transform XML description into test scripts based on Selenium framework is proposed as the emphasis.
Centralized scheduling for wireless mesh networks with contention-reduced media access

We propose a centralized scheduling approach for wireless mesh networks targeting machine-to-machine applications. Generally centralized scheduling offers good performance comparing with simple distributed schemes such as CSMA/CA which easily arises contention problems due to interference or “back off” wait. This contention problems are prominent when nodes are meshed, and densely deployed. At the same time, however, centralized scheduling requires complex function, or large overhead in both of central and branch nodes. The proposed scheme achieves high efficiency of transmissions and simplicity combining following features. First, our scheme applies sparse coding technology to random access to reduce contention, regarding nodes' transmission requests as a sparse signal. Second, we developed interference-aware node grouping in order to keep both of transmission efficiency and the sparsity of nodes' transmission requests. Finally, our scheme coordinates scheduling and routing by using node group information. Simulation results show that our scheme performs better especially in dense mesh networks.
Performance management in competitive distributed Web search

Distributed heterogeneous search environments are an emerging phenomenon in Web search. We provide a theoretical analysis of the problem and propose a method, utilising reinforcement learning techniques, for automatically managing search engine content. We examine the problem of performance-maximising behaviour for noncooperative specialised search engines in heterogeneous search environments. In particular, we analyse a scenario in which individual search engines compete for queries by choosing which documents to index. We provide game-theoretic analysis of a simplified version of the problem and motivate the use of the concept of "bounded rationality". We then cast our problem as a reinforcement learning task, where the goal of a specialised search engine is to exploit suboptimal behaviour of its competitors to improve own performance.
Implications of Internet Availability of Genomic Information for Public Health Practice

Tensions in the field have emerged over how best to communicate to the public about genomic discoveries in an era of direct-to-consumer (DTC) DNA testing services available through the Internet. Concerns over what the psychological and behavioral response might be to a nuanced, multiplex risk message have spurred some to offer caution in communicating to the public about personalized risk until the necessary research has been completed on how to communicate effectively. The popularization of DTC testing services, along with a spreading Internet culture on transparency for personal data, may make ‘waiting to communicate’ a moot point. To steer communication efforts in the midst of increasing access to personal genomic information, a self-regulation framework is presented. The framework emphasizes the importance of presenting a coherent message in all communiqués about public health genomics. Coherence should be based on an evidence-based model of how the public processes information about health conditions and an emphasis on risk-to-action links. Recommendations from the President’s Council of Advisors for Science and Technology are reviewed as a way of identifying targets of opportunity for structured communications both within the healthcare system and in the broader external ecosystem of publicly available health information technologies.
On-the-fly state space reductions for weak equivalences

On-the-fly verification of concurrent finite-state systems consists in constructing and analysing their underlying state spaces in a demand-driven way. This technique is able to detect errors effectively in large systems; however, its performance can still be increased by reducing the state spaces incrementally in a way compatible with the verification problem. In this paper, we propose algorithms for three on-the-fly reductions of Labeled Transition Systems (LTSs), which preserve weak equivalence relations: Τ-compression (collapsing of strongly connected components made of Τ-transitions), Τ-closure (transitive reflexive closure over Τ-transitions), and Τ-confluence (a form of partial order reduction). Each algorithm is described as a reductor module taking as input the successor function of an LTS and returning the successor function of the reduced LTS. The three reductors were implemented within the CADP toolbox using the generic OPEN/CÆSAR environment, which makes them directly available for any on-the-fly verification tool connected to OPEN/CÆSAR and compatible with the underlying reduction. Our experiments show that these reductors can improve significantly the performance of on-the-fly LTS generation, model checking, and equivalence checking.
An Investigation of Read-Alouds, Classroom Interactions, and Guided Play as Supports for Vocabulary Learning in Preschool.

A large body of research has established the existence of a gap in vocabulary knowledge that occurs largely along socioeconomic lines, is evident prior to age two, and continues to widen as children age. Because research has shown that early vocabulary knowledge supports present and later text comprehension, interventions for supporting preschoolers’ vocabulary development are being explored through research and in classrooms. The present study sought to build upon prior research to explore the impact of two intervention conditions, rich instruction + more rich instruction (RI) and rich instruction + play (+P), on preschoolers’ knowledge of targeted Tier Two vocabulary words selected from read-alouds of children’s literature. The study included 28 preschool students in two full-day, state-funded classrooms, mean age=4.32. A within-subjects design was used to allow all students to experience both conditions by randomly assigning target words to each condition. Findings suggest that participation in both the rich instruction + more rich instruction (RI) and rich instruction +play (+P) conditions increased preschoolers’ learning of targeted Tier Two vocabulary words. Furthermore, students demonstrated deeper word learning in the +P condition as compared to the RI condition. There is some evidence to suggest that preschoolers may have been more engaged in the classroom activities in the +P condition than when they were in the RI condition. Implications for choosing target words for preschool students are also discussed.
The Second Eigenvalue and Random Walks in Random Regular Graphs with Increasing Girth

The goal of this thesis is to upper bound the expected value of the second largest eigenvalue in magnitude of random regular graphs with a given minimum girth. Having a small upper bound implies such random graphs are likely to be expanders and thus have several combinatorial properties useful in various fields of computer science. The best possible upper bound asymptotically on the second eigenvalue has already been proven for random regular graphs without conditions on the girth. Finding this upper bound though required long and complicated analysis due to tangles, which are certain small subgraphs that contain cycles. This thesis thus hypothesizes that specifying a minimum girth large enough will prevent tangles from occurring in random graphs and thus proving an optimal upper bound on the second eigenvalue can avoid the difficult analysis required in order to handle tangles. To find such an upper bound on random regular graphs with specified minimum girth we consider the probability that a random walk in such a random graph returns to the first vertex of the walk in the k-th step of the walk. We prove for 2-regular graphs that the random walk is more likely to visit any given vertex not in the walk than the starting vertex of the walk on the k-th step, and bound how much more likely this event is. We also analyze the d-regular case and we believe our findings will lead to a similar result in this case.
Development and Usability Assessment of a Mobile Application for Neuroanatomy Teaching: A Case Study in Brazil

The teaching of Neuroanatomy presents relevant challenges, such as, restrictions to obtain properly preserved corpses, high cost for anatomy laboratory maintenance, and difficult contextualization. This article describes the development of a mobile application using cumulative tests (retrieval-based learning approach) for neuroanatomy teaching. A case study of usability assessment was conducted with thirty undergraduate Healthy Sciences students. The application received a positive evaluation, based on the System Usability Scale. The results demonstrate that study participants considered the tested application useful for Neuroanatomy Learning.
Pegylated interferon-alfa-2a induces complete hematologic and molecular responses with low toxicity in polycythemia vera.

Interferon-alpha (IFN-alpha) is a nonleukemogenic treatment of polycythemia vera (PV) able to induce cytogenetic remissions. Its use is limited by toxicity, leading to treatment discontinuation in approximately 20% of patients. We completed a phase 2 multicenter study of pegylated IFN-alpha-2a in 40 PV patients. Objectives included evaluation of efficacy, safety, and monitoring of residual disease using JAK2V617F quantification (%V617F). Median follow-up was 31.4 months. At 12 months, all 37 evaluable patients had hematologic response, including 94.6% complete responses (CRs). Only 3 patients (8%) had stopped treatment. After the first year, 35 patients remained in hematologic CR, including 5 who had stopped pegylated IFN-alpha-2a. Sequential samples for %V617F monitoring, available in 29 patients, showed %V617F decrease in 26 (89.6%). Median %V617F decreased from 45% before pegylated IFN-alpha-2a to 22.5%, 17.5%, 5%, and 3% after 12, 18, 24, and 36 months, respectively. Molecular CR (JAK2V617F undetectable) was achieved in 7 patients, lasting from 6(+) to 18(+) months, and persisted after pegylated IFN-alpha-2a discontinuation in 5. No vascular event was recorded. These results show that pegylated IFN-alpha-2a yields high rates of hematologic and molecular response in PV with limited toxicity, and could even eliminate the JAK2 mutated clone in selected cases. Available at www.clinicaltrials. gov as #NCT00241241.
Genome-Wide Association Mapping of Quantitative Traits in Outbred Mice

Recent developments in high-density genotyping and statistical analysis methods that have enabled genome-wide association studies in humans can also be applied to outbred mouse populations. Increased recombination in outbred populations is expected to provide greater mapping resolution than traditional inbred line crosses, improving prospects for identifying the causal genes. We carried out genome-wide association mapping by using 288 mice from a commercially available outbred stock; NMRI mice were genotyped with a high-density single-nucleotide polymorphism array to map loci influencing high-density lipoprotein cholesterol, systolic blood pressure, triglyceride levels, glucose, and urinary albumin-to-creatinine ratios. We found significant associations (P < 10−5) with high-density lipoprotein cholesterol and identified Apoa2 and Scarb1, both of which have been previously reported, as candidate genes for these associations. Additional suggestive associations (P < 10−3) identified in this study were also concordant with published quantitative trait loci, suggesting that we are sampling from a limited pool of genetic diversity that has already been well characterized. These findings dampen our enthusiasm for currently available commercial outbred stocks as genetic mapping resources and highlight the need for new outbred populations with greater genetic diversity. Despite the lack of novel associations in the NMRI population, our analysis strategy illustrates the utility of methods that could be applied to genome-wide association studies in humans.
In vitro and in vivo association of transforming growth factor-beta 1 with hepatic fibrosis

Despite extensive efforts, little progress has been made in identifying the factors that induce hepatic fibrosis. Transforming growth factor- beta (TGF-beta) has been shown to enhance collagen production, therefore its role in hepatic fibrosis was investigated. Treatment of cultured hepatic cells with TGF-beta 1 increased type I procollagen mRNA levels 13-fold due to post-transcriptional gene regulation. When two animal models of hepatic fibrosis, murine schistosomiasis and CCl4- treated rats, were examined, they both exhibited increased levels of TGF-beta 1 gene expression at times that somewhat preceded the increase in collagen synthesis. In contrast, in murine schistosomiasis, mRNA levels of tumor necrosis factor and interleukin-1 peaked early in the fibrogenic process. Immunohistochemical analysis showed TGF-beta 1 to be present in normal mouse liver and to be markedly increased in mice infected with schistosomiasis. TGF-beta 1 appeared in the hepatic parenchyma, primarily in hepatocytes. These findings strongly suggest a role for TGF-beta 1 in a pathophysiological state.
Loss of antiretroviral drug susceptibility at low viral load during early virological failure in treatment-experienced patients

BackgroundClinical studies have demonstrated a correlation between the response to second-line antiretroviral therapy and the number of drugs in the regimen to which the virus is susceptible. These studies have largely been performed in patients with viral loads over 1000 copies/ml. ObjectivesTo examine the evolution of resistance during early virological failure, and the potential role of susceptibility testing in patients with low viral loads (below 1000 copies/ml), in treatment-experienced patients. MethodsDrug susceptibility and genotypes of HIV-1 from indinavir-experienced patients undergoing therapy with nelfinavir, saquinavir, abacavir and either a second nucleoside reverse transcriptase inhibitor (NRTI) or nevirapine were determined. ResultsSixteen subjects were studied. Five of the ten subjects treated with nevirapine, and one of six treated with a second NRTI, achieved and maintained plasma HIV RNA < 500 copies/ml. Virus from the treatment failures lost susceptibility to one or more treatment drugs, including nelfinavir and/or saquinavir, after 4 to 36 weeks of treatment. In six of the ten failures, virus with new reductions in drug susceptibility was detected prior to failure. In five of the six failures who had at least one plasma sample with a viral load between 50 and 1000 copies/ml, reductions in susceptibility to one or more treatment drugs were detected (viral load range: 260 to 630 copies/ml). ConclusionsDrug resistance can be detected at viral loads below 1000 copies/ml which may be predictive of treatment failure. Failure of a second line regimen was typically associated with early evolution of resistance in HIV protease.
Using Tree Diagram Concepts to model Use Case Flows

The level and quality of the abstraction applied during the analysis phase are key factors for the product robustness and project success. There are not so much techniques to organize the abstraction performed. Also, in the software development process, the analysis phase suffers of a lack of formality at the level of the use cases analysis and description. In this paper we present an approach based on the analogy between probabilistic sequential events and the steps of a use case flow. This analogy represents a kind of formalization that supports the use case flows characterization. Using this approach, the use cases analysis can be performed in a methodological way supported by formal fundamentals.