Miracle-dz/UniFAR-FTUs huggingface dataset:
Obesity and Subtypes of Incident Cardiovascular Disease

Background Obesity is a risk factor for various subtypes of cardiovascular disease (CVD), including coronary heart disease (CHD), heart failure (HF), and stroke. Nevertheless, there are limited comparisons of the associations of obesity with each of these CVD subtypes, particularly regarding the extent to which they are unexplained by traditional CVD mediators. Methods and Results We followed 13 730 participants in the Atherosclerosis Risk in Communities (ARIC) study who had a body mass index ≥18.5 and no CVD at baseline (visit 1, 1987–1989). We compared the association of higher body mass index with incident HF, CHD, and stroke before and after adjusting for traditional CVD mediators (including systolic blood pressure, diabetes mellitus, and lipid measures). Over a median follow‐up of 23 years, there were 2235 HF events, 1653 CHD events, and 986 strokes. After adjustment for demographics, smoking, physical activity, and alcohol intake, higher body mass index had the strongest association with incident HF among CVD subtypes, with hazard ratios for severe obesity (body mass index ≥35 versus normal weight) of 3.74 (95% CI 3.24–4.31) for HF, 2.00 (95% CI 1.67–2.40) for CHD, and 1.75 (95% CI 1.40–2.20) for stroke (P<0.0001 for comparisons of HF versus CHD or stroke). Further adjustment for traditional mediators fully explained the association of higher body mass index with CHD and stroke but not with HF (hazard ratio 2.27, 95% CI 1.94–2.64). Conclusions The link between obesity and HF was stronger than those for other CVD subtypes and was uniquely unexplained by traditional risk factors. Weight management is likely critical for optimal HF prevention, and nontraditional pathways linking obesity to HF need to be elucidated.
Selection of a MCMC simulation strategy via an entropy convergence criterion

In MCMC methods, such as the Metropolis-Hastings (MH) algorithm, the Gibbs sampler, or recent adaptive methods, many different strategies can be proposed, often associated in practice to unknown rates of convergence. In this paper we propose a simulation-based methodology to compare these rates of convergence, grounded on an entropy criterion computed from parallel (i.i.d.) simulated Markov chains coming from each candidate strategy. Our criterion determines on the very first iterations the best strategy among the candidates. Theoretically, we give for the MH algorithm general conditions under which its successive densities satisfy adequate smoothness and tail properties, so that this entropy criterion can be estimated consistently using kernel density estimate and Monte Carlo integration. Simulated examples are provided to illustrate this convergence criterion.
Community of Suffering and Struggle: Women, Men, and the Labor Movement in Minneapolis, 1915-1945

Elizabeth Faue traces the transformation of the American labor movement from community forms of solidarity to bureaucratic unionism. Arguing that gender is central to understanding this shift, Faue explores women's involvement in labor and political organizations and the role of gender and family ideology in shaping unionism in the twentieth century. Her study of Minneapolis, the site of the important 1934 trucking strike, has broad implications for labor history as a whole. Initially the labor movement rooted itself in community organizations and networks in which women were active, both as members and as leaders. This community orientation reclaimed family, relief, and education as political ground for a labor movement seeking to re-establish itself after the losses of the 1920s. But as the depression deepened, women -- perceived as threats to men seeking work -- lost their places in union leadership, in working-class culture, and on labor's political agenda. When unions exchanged a community orientation for a focus on the workplace and on national politics, they lost the power to recruit and involve women members, even after World War II prompted large numbers of women to enter the work force. In a pathbreaking analysis, Faue explores how the iconography and language of labor reflected ideas about gender. The depiction of work and the worker as male; the reliance on sport, military, and familial metaphors for solidarity; and the ideas of women's place -- these all reinforced the representation of labor solidarity as masculine during a time of increasing female participation in the labor force. Although the language of labor as male was not new in the depression, the crisis of wage-earning -- as a crisis of masculinity -- helped to give psychological power to male dominance in the labor culture. By the end of the war, women no longer occupied a central position in organized labor but a peripheral one.
ENSEIGNEMENT DE L'ÉCONOMIE EN UTILISANT L'APPROCHE DE L'APPRENTISSAGE COOPÉRATIF: LA PERFORMANCE ET L'ATTITUDE DES ÉTUDIANTS EN COMPTABILITÉ

Using experimental and post experimental setting, this study examines whether different learning approach influence students' behaviour. Specifically, this study examines whether using cooperative learning approach could improve students' performance in economics course better than the conventional approach. This study also examines the students' attitude towards economics subject, communication skill and social skill upon reliance on the learning approach used in the experiment. Sixty one undergraduate accounting students in a public university in Malaysia participated in this study. The results show that although there is a difference in performance between students using cooperative learning approach and students using conventional approach, the result is not significant. However, the students' attitude toward economic subject, communication skill and social skill is more positive among the cooperation learning approach group compared to the conventional approach group. The findings of this study provide some understanding to academics
Successes in Logic

In this paper we study how to verify that a pure Prolog program has solutions for a given query. The detailed analysis of the fail-ure/success behaviour of a program is necessary when dealing with transformation and veriication of pure Prolog programs. In a previous work 10] we deened the class of noFD programs and queries which are characterized statically. We proved that a noFD query cannot have nitely failing derivations in a noFD program. Now, by introducing the concept of a set of exhaustive tests, we deene the larger class of successsful predicates. We prove that a noFD terminating query for successful predicates have at least one successful derivation. Moreover we propose some techniques based on program transformations for simplifying the veriication of the successful condition.
Design of an antagonistically counter-balancing parallel mechanism

Much attention has not been paid to analysis of the open-loop stability for gravity counter-balancing of parallel mechanisms or closed-chain mechanisms. The open-loop stability is crucial especially in passively counter-balanced mechanisms where no actuators are involved. Passive hands-on device is such an example. A general stiffness model is derived for general closed-chain mechanism including counter-weight model. As a measure of the open-loop stability, we employ the determinant of the stiffness matrix. A parallel mechanism having 3 translational DOF (degree of freedom) is employed as an exemplary device. An antagonistically counter-balancing is found the most stable method. We conduct dynamic simulation and experiment to confirm the open-loop stability of the system.
Enabling enterprise-scale systems using cloud-based personal media

Personal cloud services are emerging as a disruptive technology for tools and services that use digital media assets. As the shift to a bring-your-own-device and app workplace becomes commonplace, the opportunity exists to leverage these personal services to create enterprise scale approaches. However, a key limiting feature is the ability to provide private and secure assets, whether they are photos, videos, audio and text in a unified way layered on top of personal cloud services. We discuss an approach to support this shift and illustrate its feasibility using a prototype secure email service that is layered on top of a popular unsecured cloud service. One of the primary benefits of our approach is that companies can create secure enterprise services on top of a third party cloud used by individuals alleviating the need for a complex IT infrastructure for digital media assets. These solutions are particularly relevant for emerging markets.
Robust Low-Rank Regularized Regression for Face Recognition with Occlusion

Recently, regression analysis based classification methods are popular for robust face recognition. These methods use a pixel-based error model, which assumes that errors of pixels are independent. This assumption does not hold in the case of contiguous occlusion, where the errors are spatially correlated. Observing that occlusion in a face image generally leads to a low-rank error image, we propose a low-rank regularized regression model and use the alternating direction method of multipliers (ADMM) to solve it. We thus introduce a novel robust low-rank regularized regression (RLR3) method for face recognition with occlusion. Compared with the existing structured sparse error coding models, which perform error detection and error support separately, our method integrates error detection and error support into one regression model. Experiments on benchmark face databases demonstrate the effectiveness and robustness of our method, which outperforms state-of-the-art methods.
Acquisition of Humoral Transplantation Tolerance upon De Novo Emergence of B Lymphocytes

A major obstacle to transplantation tolerance is humoral immunity. In this paper, we demonstrate that the intrinsic developmental propensity of the B lymphocyte compartment for acquisition of self-tolerance can be harnessed to induce humoral unresponsiveness to transplanted alloantigens. In the current study, when transitional B cells developed in the presence of donor lymphoid cells, the mature B lymphocyte compartment failed to mount a donor-specific alloantibody response to an organ transplant—despite unrestrained acute T cell-mediated allograft rejection. Specifically, we generated an experimental system wherein a B6 strain B cell compartment developed de novo in the presence of F1 (B6xBALB/c) lymphoid cells and in a T cell-deficient setting. Following establishment of a steady-state B cell compartment, these B6 mice were transplanted with heterotopic cardiac allografts from allogeneic BALB/c donors. The mice were then inoculated with purified syngeneic B6 T cells. As expected, all cardiac allografts were acutely rejected. However, the B lymphocyte compartment of these mice was completely inert in its capacity to form a BALB/c-specific alloantibody response. Using an alloantigen-specific Ig transgenic system, we demonstrated that this profound degree of humoral tolerance was caused by clonal deletion of alloreactive specificities from the primary B cell repertoire. Thus, de novo B cell compartment development at the time of transplantation is of critical importance in recipient repertoire “remodeling” to a humoral tolerant state.
Towards better integration of semantic predictors in statistical language modeling

We introduce a number of techniques designed to help integrate semantic knowledge with N-gram language models for automatic speech recognition. Our techniques allow us to integrate Latent Semantic Analysis (LSA), a word-similarity algorithm based on word co-occurrence information, with N-gram models. While LSA is good at predicting content words which are coherent with the rest of a text, it is a bad predictor of frequent words, has a low dynamic range, and is inaccurate when combined linearly with N-grams. We show that modifying the dynamic range, applying a per-word conﬁdence metric, and using geometric rather than linear combinations with N-grams produces a more robust language model which has a lower perplexity on a Wall Street Journal test-set than a baseline N-gram model.
The effect of cross-sex hormonal treatment on gender dysphoria individuals’ mental health: a systematic review

Cross-sex hormonal treatment represents a main aspect of gender dysphoria health care pathway. However, it is still debated whether this intervention translates into a better mental well-being for the individual and which mechanisms may underlie this association. Although sex reassignment surgery has been the subject of extensive investigation, few studies have specifically focused on hormonal treatment in recent years. Here, we systematically review all studies examining the effect of cross-sex hormonal treatment on mental health and well-being in gender dysphoria. Research tends to support the evidence that hormone therapy reduces symptoms of anxiety and dissociation, lowering perceived and social distress and improving quality of life and self-esteem in both male-to-female and female-to-male individuals. Instead, compared to female-to-male individuals, hormone-treated male-to-female individuals seem to benefit more in terms of a reduction in their body uneasiness and personality-related psychopathology and an amelioration of their emotional functioning. Less consistent findings support an association between hormonal treatment and other mental health-related dimensions. In particular, depression, global psychopathology, and psychosocial functioning difficulties appear to reduce only in some studies, while others do not suggest any improvement in these domains. Results from longitudinal studies support more consistently the association between hormonal treatment and improved mental health. On the contrary, a number of cross-sectional studies do not support this evidence. This review provides possible biological explanation vs psychological explanation (direct effect vs indirect effect) for the hormonal treatment-induced better mental well-being. In conclusion, this review indicates that gender dysphoria-related mental distress may benefit from hormonal treatment intervention, suggesting a transient reaction to the nonsatisfaction connected to the incongruent body image rather than a stable psychiatric comorbidity. In this perspective, timely hormonal treatment intervention represents a crucial issue in gender dysphoria individuals’ mental health-related outcome.
Fair allocation of utilities in multirate multicast networks: a framework for unifying diverse fairness objectives

We study fairness in a multicast network. We assume that different receivers of the same session can receive information at different rates. We study a fair allocation of utilities, where the utility of a bandwidth is an arbitrary function of the bandwidth. The utility function is not strictly increasing, nor continuous in general. We discuss fairness issues in this general context. Fair allocation of utilities can be modeled as a nonlinear optimization problem. However, nonlinear optimization techniques do not terminate in a finite number of iterations in general. We present an algorithm for computing a fair utility allocation. Using specific fairness properties, we show that this algorithm attains global convergence and yields a fair allocation in polynomial number of iterations.
Genetic Population Structure of Local Populations of the Endangered Saltmarsh Sesarmid Crab Clistocoeloma sinense in Japan

During recent decades, over 40% of Japanese estuarine tidal flats have been lost due to coastal developments. Local populations of the saltmarsh sesarmid crab Clistocoeloma sinense, designated as an endangered species due to the limited suitable saltmarsh habitat available, have decreased accordingly, being now represented as small remnant populations. Several such populations in Tokyo Bay, have been recognised as representing distributional limits of the species. To clarify the genetic diversity and connectivity among local coastal populations of Japanese Clistocoeloma sinense, including those in Tokyo Bay, mitochondrial DNA analyses were conducted in the hope of providing fundamental information for future conservation studies and an understanding of metapopulation dynamics through larval dispersal among local populations. All of the populations sampled indicated low levels of genetic diversity, which may have resulted from recent population bottlenecks or founder events. However, the results also revealed clear genetic differentiation between two enclosed-water populations in Tokyo Bay and Ise-Mikawa Bay, suggesting the existence of a barrier to larval transport between these two water bodies. Since the maintenance of genetic connectivity is a requirement of local population stability, the preservation of extant habitats and restoration of saltmarshes along the coast of Japan may be the most effective measures for conservation of this endangered species.
Altered methylation of specific DNA loci in the liver of Bhmt‐null mice results in repression of Iqgap2 and F2rl2 and is associated with development of preneoplastic foci

Folate B12–dependent remethylation of homocysteine is important, but less is understood about the importance of the alternative betaine‐dependent methylation pathway—catalyzed by betaine‐homocysteine methyltransferase (BHMT)—for establishing and maintaining adequate DNA methylation across the genome. We studied C57Bl/6J Bhmt (betaine‐homocysteine methyltransferase)‐null mice at age 4, 12, 24, and 52 wk (N = 8) and observed elevation of S‐adenosylhomocysteine concentrations and development of preneoplastic foci in the liver (increased placental glutathione S‐transferase and cytokeratin 8–18 activity; starting at 12 wk). At 4 wk, we identified 63 differentially methylated CpGs (DMCs; false discovery rate < 5%) proximal to 81 genes (across 14 chromosomes), of which 18 were differentially expressed. Of these DMCs, 52% were located in one 15.5‐Mb locus on chromosome 13, which encompassed the Bhmt gene and defined a potentially sensitive region with mostly decreased methylation. Analyzing Hybrid Mouse Diversity Panel data, which consisted of 100 inbred strains of mice, we identified 97 DMCs that were affected by Bhmt genetic variation in the same region, with 7 overlapping those found in Bhmt‐null mice (P < 0.001). At all time points, we found a hypomethylated region mapping to Iqgap2 (IQ motif‐containing GTPase activating protein 2) and F2rl2 (proteinase‐activated receptor‐3), 2 genes that were also silenced and underexpressed, respectively. —Lupu, D. S. , Orozco, L. D. , Wang, Y. , Cullen, J. M. , Pellegrini, M. , Zeisel, S. H. Altered methylation of specific DNA loci in the liver of Bhmt‐null mice results in repression of Iqgap2 and F2rl2 and is associated with development of preneoplastic foci. FASEB J. 31, 2090–2103 (2017). www.fasebj. org
Learning the Meaning and Usage of Time Phrases from a Parallel Text-Data Corpus

We present an empirical corpus study of the meaning and usage of time phrases in weather forecasts; this is based on a novel corpus analysis technique where we align phrases from the forecast text with data extracted from a numerical weather simulation. Previous papers have summarised this analysis and discussed the substantial variations we discovered among individual writers, which was perhaps our most surprising finding. In this paper we describe our analysis procedure and results in considerably more detail, and also discuss our current work on using parallel text-data corpora to learn the meanings of other types of words.
Atomistic Simulations of Flash Memory Materials Based on Chalcogenide Glasses

In this chapter, by using ab-initio molecular dynamics, we introduce the latest simulation results on two materials for flash memory devices: Ge2Sb2Te5 and Ge-Se-Cu-Ag. This chapter is a review of our previous work including some of our published figures and text in Cai et al. (2010) and Prasai & Drabold (2011) and also includes several new results.
Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance.
Bots increase exposure to negative and inflammatory content in online social systems

Significance Social media can deeply influence reality perception, affecting millions of people’s voting behavior. Hence, maneuvering opinion dynamics by disseminating forged content over online ecosystems is an effective pathway for social hacking. We propose a framework for discovering such a potentially dangerous behavior promoted by automatic users, also called “bots,” in online social networks. We provide evidence that social bots target mainly human influencers but generate semantic content depending on the polarized stance of their targets. During the 2017 Catalan referendum, used as a case study, social bots generated and promoted violent content aimed at Independentists, ultimately exacerbating social conflict online. Our results open challenges for detecting and controlling the influence of such content on society. Societies are complex systems, which tend to polarize into subgroups of individuals with dramatically opposite perspectives. This phenomenon is reflected—and often amplified—in online social networks, where, however, humans are no longer the only players and coexist alongside with social bots—that is, software-controlled accounts. Analyzing large-scale social data collected during the Catalan referendum for independence on October 1, 2017, consisting of nearly 4 millions Twitter posts generated by almost 1 million users, we identify the two polarized groups of Independentists and Constitutionalists and quantify the structural and emotional roles played by social bots. We show that bots act from peripheral areas of the social system to target influential humans of both groups, bombarding Independentists with violent contents, increasing their exposure to negative and inflammatory narratives, and exacerbating social conflict online. Our findings stress the importance of developing countermeasures to unmask these forms of automated social manipulation.
A new dynamic tool to perform assembly of expressed sequence tags (ESTs)

MOTIVATION Expressed Sequence Tags (ESTs) are short single-pass DNA sequences obtained from either ends of cDNA clones. To exploit these sequences efficiently, a dynamic Web-tool has been developed which uses these data to perform fast virtual cloning of cDNAs. RESULTS Starting with a query sequence, the user is able to identify related ESTs and extend the sequence of interest step by step, possibly to a full-length transcript. Graphical views of the clustering are used to monitor the progress of a particular 'cloning' project. Potential open reading frames are detected by positional base preference, and hyperlinks to other Worldwide Web sites allows the user to retrieve information relevant to each EST in a cluster (e.g. sequence traces, clone size, plate position). Apart from cDNA cloning, this tool also provides a mechanism for collating gene families and polymorphism sites.