Miracle-dz/UniFAR-FTUs huggingface dataset:
The Ribonucleotide Reductase R1 Subunits of Herpes Simplex Virus 1 and 2 Protect Cells against Poly(I · C)-Induced Apoptosis

ABSTRACT We recently provided evidence that the ribonucleotide reductase R1 subunits of herpes simplex virus types 1 and 2 (HSV-1 and -2) protect cells against tumor necrosis factor alpha- and Fas ligand-induced apoptosis by interacting with caspase 8. Double-stranded RNA (dsRNA) is a viral intermediate known to initiate innate antiviral responses. Poly(I · C), a synthetic analogue of viral dsRNA, rapidly triggers caspase 8 activation and apoptosis in HeLa cells. Here, we report that HeLa cells after HSV-1 and HSV-2 infection were quickly protected from apoptosis caused by either extracellular poly(I · C) combined with cycloheximide or transfected poly(I · C). Cells infected with the HSV-1 R1 deletion mutant ICP6Δ were killed by poly(I · C), indicating that HSV-1 R1 plays a key role in antiapoptotic responses to poly(I · C). Individually expressed HSV R1s counteracted caspase 8 activation by poly(I · C). In addition to their binding to caspase 8, HSV R1s also interacted constitutively with receptor-interacting protein 1 (RIP1) when expressed either individually or with other viral proteins during HSV infection. R1(1-834)-green fluorescent protein (GFP), an HSV-2 R1 deletion mutant protein devoid of antiapoptotic activity, did not interact with caspase 8 and RIP1, suggesting that these interactions are required for protection against poly(I · C). HSV-2 R1 inhibited the interaction between the Toll/interleukin-1 receptor domain-containing adaptor-inducing beta interferon (IFN-β) (TRIF) and RIP1, an interaction that is essential for apoptosis triggered by extracellular poly(I · C) plus cycloheximide or TRIF overexpression. TRIF silencing reduced poly(I · C)-triggered caspase 8 activation in mock- and ICP6Δ-infected cells, confirming that TRIF is involved in poly(I · C)-induced apoptosis. Thus, by interacting with caspase 8 and RIP1, HSV R1s impair the apoptotic host defense mechanism prompted by dsRNA.
Learn to Load the Dishwasher

We develop an algorithm to enable a personal robot to conduct one of the common tasks in our daily life – moving the objects to a specific place. One typical application scenario of this algorithm is to load a variety of kitchen items such as the plates, mugs, and bowls etc. into a dishwasher. For newly seen objects and their destination container (e.g. the dishwahser), our algorithm features a supervised learning procedure to decide both the position to grasp the objects and the locations to place them. The input of the algorithm includes the image captured by a camera and the point cloud data collected by a depth sensor. A few placing positions and the corresponding object’s placing orientations are selected by the trained SVM. Finally our method runs the point-based rigid-body simulation for each of the position/orientation candidates to pick the best placing strategy and proposes an placing order if multiple objects are considered.
Applying Game Design Elements in the Workplace

Gamification, whereby users are engaged in pre-assigned activities induced by game elements, is gaining interest among researchers and practitioners. While it has been touted that enterprise gamified information systems (ISs) can successfully tempt users, ensuring sustainable user engagement has been identified as a major challenge for organizations that have adopted the gamification ideas. Despite the proliferation of enterprise social media with gamified applications, little research has empirically examined how gamification ideas generate practical values in the workplace. To fill this gap, drawing on cognitive evaluation theory and the theory of aesthetic experience, this study develops a theoretical model that explains how game dynamics influence an employee’s work engagement within an enterprise gamified IS. On the basis of the results of model test, we can discuss how different game dynamics (i.e., rewardbased and aesthetic-based dynamics) jointly influence users’ intrinsic motivation (enjoyment) to engage in work-related activities.
Enhanced intracellular calcium concentration during poliovirus infection

The infection of human fibroblasts by poliovirus leads to a notable increase in the intracellular calcium concentration, [Ca2+]i, measured by microfluorimetry or by flow cytometry. [Ca2+]i increases from 2 to 3 h postinfection, and by the fifth hour there is a 5- to 10-fold increase in [Ca2+]i. At this time postinfection there is active viral protein synthesis. The modifications in [Ca2+]i are not observed in the presence of cycloheximide, guanidine, or Ro 09-0179, indicating that virus gene expression is required for the increase in [Ca2+]i. Attempts to identify the source of the intracellular Ca2+ by using different inhibitors of calcium fluxes suggest that calcium enters from the culture medium through voltage-sensitive calcium channels.
Adult Born Olfactory Bulb Dopaminergic Interneurons: Molecular Determinants and Experience-Dependent Plasticity

The olfactory bulb (OB) is a highly plastic brain region involved in the early processing of olfactory information. A remarkably feature of the OB circuits in rodents is the constitutive integration of new neurons that takes place during adulthood. Newborn cells in the adult OB are mostly inhibitory interneurons belonging to chemically, morphologically and functionally heterogeneous types. Although there is general agreement that adult neurogenesis in the OB plays a key role in sensory information processing and olfaction-related plasticity, the contribution of each interneuron subtype to such functions is far to be elucidated. Here, we focus on the dopaminergic (DA) interneurons: we highlight recent findings about their morphological features and then describe the molecular factors required for the specification/differentiation and maintenance of the DA phenotype in adult born neurons. We also discuss dynamic changes of the DA interneuron population related to age, environmental stimuli and lesions, and their possible functional implications.
Approximation Algorithm for the Shortest Approximate Common Superstring Problem

The Shortest Approximate Common Superstring (SACS) problem is : Given a set of strings f={w1, w2, . , wn}, where no wi is an approximate substring of wj, i ≠ j, find a shortest string Sa, such that, every string of f is an approximate substring of Sa. When the number of the strings n>2, the SACS problem becomes NP-complete. In this paper, we present a greedy approximation SACS algorithm. Our algorithm is a 1/2-approximation for the SACS problem. It is of complexity O(n2*(l2+log(n))) in computing time, where n is the number of the strings and l is the length of a string. Our SACS algorithm is based on computation of the Length of the Approximate Longest Overlap (LALO). Keywords—Shortest approximate common superstring, approximation algorithms, strings overlaps, complexities.
Physical Layer Security Scheme Based on Base Station Cooperation in Dense Heterogeneous Networks

For preventing the leakage of confidential messages sent to a marcocell user in dense heterogeneous networks, a physical layer security scheme based on base station cooperation is proposed in the paper. To improve transmission rate of confidential messages and make the downlink signals of other legitimate users interfere with eavesdroppers, the beamforming vectors at a macrocell base station and femtocell base stations are jointly optimized. The problem of maximizing the secrecy rate is modeled under the limitations of quality of service(QoS) and base station power. Due to the intractability, this problem is recast into a convex SemiDefinite Program(SDP) problem using the SemiDefinite Relaxation(SDR) technique and the successive convex approximation(SCA) algorithm. Simulation results validate the efficacy and the security of the scheme.
Stop-Loss Orders and Price Cascades in Currency Markets

In this paper, I provide evidence that currency stop-loss orders contribute to rapid, self-reinforcing price movements, or "price cascades. " Stop-loss orders, which instruct a dealer to buy (sell) a certain amount of currency at the market rate once the rate has risen (fallen) to a prespecified level, generate positive-feedback trading. Theoretical research on the 1987 stock market crash suggests that such trading can cause price discontinuities, which would manifest themselves as price cascades. ; My analysis of high-frequency exchange rates offers three main results that provide empirical support for the hypothesis that stop-loss orders contribute to price cascades: (1) Exchange rate trends are unusually rapid when rates reach exchange rate levels at which stop-loss order have been documented to cluster. (2) The response to stop-loss orders is larger than the response to take-profit orders, which generate negative-feedback trading and are therefore unlikely to contribute to price cascades. (3) The response to stop-loss orders lasts longer than the response to take-profit orders. Most results are statistically significant for hours, although not for days. Together, these results indicate that stop-loss orders propagate trends and are sometimes triggered in waves, contributing to price cascades. Stop-loss propagated price cascades may help explain the well-known "fat tails" of the distribution of exchange rate returns, or equivalently the high frequency of large exchange rate moves. The paper also provides evidence that exchange rates respond to noninformative order flow.
Implicit vs. explicit resource allocation in SMT processors

In a simultaneous multithreaded (SMT) architecture, the front end of a superscalar is adapted in order to be able to fetch from several threads while the back end is shared among the threads. In this paper, we describe different resource sharing models in SMT processors. We show that explicit resource allocation can improve SMT performance. In addition, it enables SMTs to solve other QoS requirements, not realizable before.
Similarity Search in Biological and Engineering Databases

Similarity search is an important task in a wide range of scie ntific database applications. Besides being used directly, it is also used as a basic operation for many da ta mining algorithms. Example applications which are presented in this article are functional classific ation of proteins in biological databases and the similarity search of CAD parts in engineering environme ts. It turns out that the general concept of set-based similarity measures can be successfully applied to both of these diverse application domains.
PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations

We propose position-velocity encoders (PVEs) which learn---without supervision---to encode images to positions and velocities of task-relevant objects. PVEs encode a single image into a low-dimensional position state and compute the velocity state from finite differences in position. In contrast to autoencoders, position-velocity encoders are not trained by image reconstruction, but by making the position-velocity representation consistent with priors about interacting with the physical world. We applied PVEs to several simulated control tasks from pixels and achieved promising preliminary results.
Clustering For Demand Response A Theory to Break the ‘ Curse of Dimensionality ’

The advent of smart meters and advanced communication infrastructures catalyzes numerous smart grid applications such as dynamic demand response, and paves the way to solve challenging research problems in sustainable energy consumption. The space of solution possibilities are restricted primarily by the huge amount of generated data requiring considerable computational resources and efficient algorithms. To overcome this Big Data challenge, data clustering techniques have been proposed. Current approaches however do not scale in the face of the “increasing dimensionality” problem where a cluster point is represented by the entire customer consumption time series. To overcome this aspect we first rethink the way cluster points are created and designed, and then design an efficient online clustering technique for demand response (DR) in order to analyze high volume, high dimensional energy consumption time series data at scale, and on the fly. Our online algorithm is randomized in nature, and provides optimal performance guarantees in a computationally efficient manner. Unlike prior work we (i) study the consumption properties of the whole population simultaneously rather than developing individual models for each customer separately, claiming it to be a ‘killer’ approach that breaks the “curse of dimensionality” in online time series clustering, and (ii) provide tight performance guarantees in theory to validate our approach. Our insights are driven by the field of sociology, where collective behavior often emerges as the result of individual patterns and lifestyles.
Solving Factored MDPs with Hybrid State and Action Variables

Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automated decision support systems. In this paper, we describe a novel hybrid factored Markov decision process (MDP) model that allows for a compact representation of these problems, and a new hybrid approximate linear programming (HALP) framework that permits their efficient solutions. The central idea of HALP is to approximate the optimal value function by a linear combination of basis functions and optimize its weights by linear programming. We analyze both theoretical and computational aspects of this approach, and demonstrate its scale-up potential on several hybrid optimization problems.
The role of estrogen in the regulation of erythropoietin production.

Low doses of estradiol benzoate (2.5-10.0 μg/day X 5) inhibited the production of erythropoietin (Ep) in female rats exposed to various intensities of hypoxia. This was not attributable to the presence of either residual estradiol, or an inhibitor of Ep in plasma samples, since these plasmas had no inhibitory effect on Ep simultaneously injected into assay mice. Although normal females produced less Ep in response to hypoxia than normal males, ovariectomized rats showed a response equal to males. Estradiol treatment of ovariectomized animals lowered their Ep response to hypoxia down to the level of intact females. Only the largest dose employed (10.0 μ/day) had some inhibitory effect on Ep production in hypoxic males. (Endocrinology 92: 358, 1973)
Neural Word Representations from Large-Scale Commonsense Knowledge

There has recently been a surge of research on neural network-inspired algorithms to produce numerical vector representations of words, based on contextual information. In this paper, we present an approach to improve such word embeddings by first mining cognitively salient word relationships from text and then using stochastic gradient descent to jointly optimize the embeddings to reflect this information, in addition to the regular contextual information captured by the word2vec CBOW objective. Our findings show that this new training regime leads to vectors that better reflect commonsense information about words.
Augmenting Paper-Based Reading Activities with Mobile Technology to Enhance Reading Comprehension

We present in this paper a developing project attempting to integrate the strengths of mobile technology into paper-based reading activities to enhance learners’ reading comprehension. While conventional print text provides very limited information in fostering learners’ comprehension, integrating mobile technology with paper prints is a possible way to offer learners essential content-related resources to make sense of the text. We explored the possibility of this integration, and to verify the practicability of such a system in an English reading practice.
The role of vascular endothelial growth factor leading to vascular leakage in children with dengue virus infection

Abstract Increased vascular permeability is the main aetiology for hypovolaemic shock and circulatory failure in dengue haemorrhagic fever (DHF). Aim: To investigate the role of vascular endothelial growth factor (VEGF) in the pathogenesis of DHF. Methods: Serum samples from 41 patients [15 dengue fever (DF), 26 DHF] with serologically confirmed dengue virus infection during the febrile, toxic, convalescent stages and at follow-up were analysed for VEGF. Plasma samples from an additional 27 children (16 DF and 11 DHF) during the febrile, toxic stages and at 4-week follow-up and from eight healthy controls were analysed for VEGF. Results: Serum and plasma VEGF levels were not elevated during the febrile or toxic stages of dengue virus infection and did not differ between patients with DF and DHF. Conclusion: Plasma leakage in patients with DHF cannot be explained by elevation of VEGF during the toxic stage of the illness.
Implémentation et évaluation d'un programme de promotion de la santé au sein de clubs sportifs "Promouvoir l'Activité Physique des Adolescents"

Implementation et evaluation d'un programme de promotion de la sante au sein de clubs sportifs : « Promouvoir l'Activite Physique des Adolescents » La pratique sportive est consideree comme benefique pour la sante (OMS, 1995). Malgre ce constat, tous les jeunes ne beneficient pas d'experience sportive positive. Pour encourager ce type d'experience, ce travail doctoral est compose de trois parties : (1) une analyse de la contribution du club sportif a la promotion de la sante, (2) l'evaluation des effets et (3) du processus d'implementation d'une intervention basee sur la theorie de l'autodetermination et la theorie des buts d'accomplissement visant une experience sportive positive et durable : le programme « Promouvoir l'Activite Physique des Adolescents ». Pour apprecier la contribution du club sportif a la promotion de la sante, 2 etudes ont ete realisees. La premiere analyse les representations de 125 educateurs des missions et actions de promotion de la sante des clubs sportifs, concluant que le club pourrait etre plus actif en termes de politique et de pratiques. La seconde, evaluant la contribution de la pratique sportive pour atteindre les recommandations en termes d'activite physique (AP ; OMS, 2010) aupres de 331 jeunes footballeurs, observe que la pratique sportive semble favoriser la pratique d'AP. L'evaluation des effets de l'intervention a ete realisee a l'aide d'une etude controlee randomisee aupres de 617 joueurs (339 du groupe experimental et 278 du groupe experimental). Les resultats montrent qu'en comparaison au groupe controle, les joueurs entraines par un educateur forme ont une evolution plus positive de la perception du climat motivationnel, de la satisfaction du besoin de competence, de leur motivation autodeterminee, de l'estime de soi, et de moindres intentions et un taux d'abandon plus faible. En controlant le niveau au 1er temps de mesure, la formation a un effet sur l'experience sportive mediatisee completement par le climat motivationnel qui est partiellement mediatise par la satisfaction de besoins et la motivation. L'evaluation du processus montre que la formation de formateurs pour delivrer notre intervention est efficace, que l'intervention un taux correct d'implementation. Le taux d'implementation individuel est modere.
Toward a machine learning approach for classifying user goals from user interactions

1 Introduction In this work, we present an evaluation of the utility of collecting and analyzing user-interaction histories to discern information about user intent and user goals. We introduce and compare two techniques for defining the vast space of user goals within a given application. We then offer a supervised, probabilistic approach for mapping series of user interactions into the space of user goals, using collections of goal-classified user-interaction histories as training data. With awareness of user intent, applications may be able to offer tutorial-like advice dynamically, suggesting useful interactions to complete an intended goal. Specifically, we posit that information gained from previous user interactions within a scientific visualization can be leveraged to enhance usability and facilitate scientific discovery: a notion supported by preliminary user-feedback. While interactive visualiza-tion techniques have been shown effective in generating new insight and validating expected hypotheses, we aim to address the lack of attention commonly given to interface usability; an issue that presents a significant roadblock to the widespread adoption of scientific visualizations and workflow systems by domain scientists.
All-Cause Mortality and Progression Risks to Hepatic Decompensation and Hepatocellular Carcinoma in Patients Infected With Hepatitis C Virus.

BACKGROUND A key question in care of patients with chronic hepatitis C virus (HCV) infection is beginning treatment immediately vs delaying treatment. Risks of mortality and disease progression in "real world" settings are important to assess the implications of delaying HCV treatment. METHODS This was a cohort study of HCV patients identified from 4 integrated health systems in the United States who had liver biopsies during 2001-2012. The probabilities of death and progression to hepatocellular carcinoma, hepatic decompensation (hepatic encephalopathy, esophageal varices, ascites, or portal hypertension) or liver transplant were estimated over 1, 2, or 5 years by fibrosis stage (Metavir F0-F4) determined by biopsy at beginning of observation. RESULTS Among 2799 HCV-monoinfected patients who had a qualifying liver biopsy, the mean age at the time of biopsy was 50.7 years. The majority were male (58.9%) and non-Hispanic white (66.9%). Over a mean observation of 5.0 years, 261 (9.3%) patients died and 34 (1.2%) received liver transplants. At 5 years after biopsy, the estimated risk of progression to hepatic decompensation or hepatocellular carcinoma was 37.2% in stage F4, 19.6% in F3, 4.7% in F2, and 2.3% in F0-F1 patients. Baseline biopsy stage F3 or F4 and platelet count below normal were the strongest predictors of progression to hepatic decompensation or hepatocellular carcinoma. CONCLUSIONS The risks of death and progression to liver failure varied greatly by fibrosis stage. Clinicians and policy makers could use these progression risk data in prioritization and in determining the timing of treatment for patients in early stages of liver disease.