Miracle-dz/UniFAR-FTUs huggingface dataset:
Resveratrol modulates the inflammatory response via an estrogen receptor-signal integration network

Resveratrol has beneficial effects on aging, inflammation and metabolism, which are thought to result from activation of the lysine deacetylase, sirtuin 1 (SIRT1), the cAMP pathway, or AMP-activated protein kinase. In this study, we report that resveratrol acts as a pathway-selective estrogen receptor-α (ERα) ligand to modulate the inflammatory response but not cell proliferation. A crystal structure of the ERα ligand-binding domain (LBD) as a complex with resveratrol revealed a unique perturbation of the coactivator-binding surface, consistent with an altered coregulator recruitment profile. Gene expression analyses revealed significant overlap of TNFα genes modulated by resveratrol and estradiol. Furthermore, the ability of resveratrol to suppress interleukin-6 transcription was shown to require ERα and several ERα coregulators, suggesting that ERα functions as a primary conduit for resveratrol activity. DOI: http://dx.doi. org/10.7554/eLife.02057. 001
School Counselors' Experiences Working with Digital Natives: A Qualitative Study

To better understand school counselors' experiences related to students' use of social media, the authors conducted a qualitative study, utilizing a phenomenological approach, with eight practicing high school counselors. Three major themes emerged from the study: “the digital cultural divide,” “frustration and fear,” and “embracing change. ” This article presents implications for school counseling practice and research.
Multiple Acoustical Holography Method for Localization of Objects in Broad Range using Audible Sound

This paper describes a new acoustic localization method using audible sound, which can be applied over a broader range of search directions. In the field of robotics, most conventional indoor localization systems based on sonar range finders use ultrasound to obtain a highly accurate distance. Because ultrasound has high directivity, many measurements are required to localize objects in a large space. To achieve localization with one-time measurement, we use audible sounds. We then calculate an intensity field of the reflection sound to estimate object positions. Although acoustical holography (AH) is a well-known technique to do this, it has problems in that it generates false images. We propose multiple AH (MAH) to solve this problem. The method is used to divide a measurement plane into sub-planes and to apply AH to each sub-plane. By integrating the results of applying AH to the sub-planes, false images can be suppressed because the positions of the false images differ depending on the position of the sub-plane. In addition, we use multiple frequencies to advance an accuracy of the localization based on MAH in a real environment. We constructed a localization system with only one speaker and a microphone array. In both simulation and actual experiments, we confirmed that MAH was effective method for the suppression of false image and could be used within the range of an angle view of 120 deg
Neuropathic Pain Memory Is Maintained by Rac1-Regulated Dendritic Spine Remodeling after Spinal Cord Injury

Localized increases in synaptic strength constitute a synaptic basis for learning and memory in the CNS and may also contribute to the maintenance of neuropathic pain after spinal cord injury (SCI) through the de novo formation or elaboration of postsynaptic dendritic structures. To determine whether SCI-induced dendritic spine remodeling contributes to neuronal hyperexcitability and neuropathic pain, we analyzed spine morphometry, localization, and functional influence in dorsal horn (DH) neurons in adult rats 1 month after sham surgery, contusion SCI, and SCI treated with a selective inhibitor of Rac1 activation, NSC23766. After SCI, DH neurons located in lamina IV–V exhibited increased spine density, redistributed spines, and mature spines compared with control neurons, which was associated with enhancement of EPSCs in computer simulations and hyperexcitable responsiveness to innocuous and noxious peripheral stimuli in unit recordings in vivo. SCI animals also exhibited symptoms of tactile allodynia and thermal hyperalgesia. Inhibition of the small GTP-binding protein Rac1 ameliorated post-SCI changes in spine morphology, attenuated injury-induced hyperexcitability of wide-dynamic range neurons, and progressively increased pain thresholds over a 3 d period. This suggests that Rac1 is an important intracellular signaling molecule involved in a spinal dendritic spine pathology associated with chronic neuropathic pain after SCI. Our report provides robust evidence for a novel conceptual bridge between learning and memory on the one hand, and neuropathic pain on the other.
A Retrieval Method Based on Language Model Considering Neighboring Contents

The World Wide Web (WWW) has a massive number of Web pages, so that it is difficult for users to get useful information. In recent years, however, it is said that the probabilistic language model can help to improve retrieval accuracies of some kinds of search engines. The probabilistic language model has statistical background and can adapt previous text information retrieval model. However, we cannot directly adapt the probabilistic language model to Web search engines, because data on the Web has a hyperlink environment while the probabilistic language model can only text information on it. In this paper, we propose a novel approach for searching Web pages considering a Web page as well as its neighboring oneson the hyperlink environment.
Extended Validation of an Optimal Estimation Cloud Property Retrieval Algorithm

Results are presented which illustrate the evaluation of the retrieval using in situ data collected during the March 2000 Cloud Intensive Observation Period (IOP) and the incorporation of these observations into the retrieval algorithm. The observations are used to modify the a priori estimates of cloud properties used in the retrieval, and the influence of the modified a priori data are evaluated for a number of liquid cloud cases. The retrieval algorithm is further evaluated using observations over the yearlong period following the Cloud IOP. Finally, the extensibility of the retrieval algorithm is illustrated by incorporating microwave radiometer (MWR) observations to augment the MMCR and VOD inputs. Two cases are examined to evaluate the influence of the liquid water path constraints from the MWR on the retrieval results. Performance of the retrieval algorithm is evaluated in terms of bias and scatter of modeled radiative fluxes versus observations. The inclusion of VOD reduces scatter in all the modeled radiative fluxes in comparison to those obtained using only MMCR observations. The reductions range from 5% to over 50%. For shortwave fluxes, the inclusion of cloud optical depth information reduces both the top-ofatmosphere flux bias and the surface flux bias, while effects on the longwave biases are slight. Overall, the results suggest that the retrievals that include cloud optical depth information provide improved cloud microphysical properties in comparison with radar-only retrievals.
DIAGNOSIS OF THE JAUNDICE USING FUZZY EXPERT SYSTEM

The objective of our study is to design fuzzy expert system to diagnose the jaundice. To diagnose the jaundice both Mamdani and Sugeno fuzzy expert system is used. The symptoms of the jaundice are fed as inputs of fuzzy inference system and the outputs, i.e. grade of disease, is obtained. The grade is obtained using the fuzzy tool in MATLAB R2007a software. Ten patients of different ages and genders are taken into our study.
Mining Association Rules in Geographic Information Systems using Intelligent Agents

A geographical information system (GIS) is a framework capable to assemble, keep, process and display specific information, identified by geographical location, which can combines layers of information to give the user a better understanding about that location. Intelligent agents prove to be a useful tool for data mining in geographical distributed knowledge bases. In this paper we present a method of using intelligent agents for discovering association rules in geographical datasets.
Hierarchical Multiclass Object Classification

Humans can use similarity between objects in order to recognize rare objects. They also make many abstract concepts when they see some objects very often. Interestingly, a large part of brain is associated with common classes like faces rather than rare objects like Ostrich. In our work we want to propose a model that has four mentioned characteristics. 1. Use more resources for categories that have many examples and less resources for categories that have few examples , 2. Has the ability recognize objects that it has never seen before, but can be synthesized by combining previously seen objects, 3. Objects with few examples can borrow statistical strength from similar objects with many examples, 4. Models that have lot of sharing between model parameters of different classes should be favored.
Research of multi-factors heuristics tasks scheduling model and its algorithms in grid environment

The tasks scheduling model is established based on multi-factors that include communication abilities between any two sites, process ability of the site and the reliability of site in complex and dynamic environment. The Target heuristic function is constructed combined minimum executing time and reliability of site. Simulation result demonstrates the factors concern with task scheduling model accord actual situations and its can be satisfied task scheduling demand in complex grid environment. It can be found optimization value of the local target heuristic function combined minimum executing time and reliability of site.
Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.
New Results on Stability of Discrete-Time Systems With Time-Varying State Delay

This note is concerned with the stability analysis of discrete-time systems with time-varying state delay. By defining new Lyapunov functions and by making use of novel techniques to achieve delay dependence, several new conditions are obtained for the asymptotic stability of these systems. The merit of the proposed conditions lies in their less conservativeness, which is achieved by circumventing the utilization of some bounding inequalities for cross products between two vectors and by paying careful attention to the subtle difference between the terms Sigmam=k-dk k-1(middot) and Sigma m=k-dM k-1(middot), which is largely ignored in the existing literature. These conditions are shown, via several examples, to be much less conservative than some existing result
A Theory of Conflict as a Coordination Failure in Anarchic Environments

A Theory of Conﬂict as a Coordination Failure in Anarchic Environments ∗ Sylvain Chassang Massachusetts Institute of Technology Gerard Padr´ i Miquel † o Stanford University Graduate School of Business May 25, 2006 VERY PRELIMINARY – COMMENTS WELCOME Abstract This paper presents a theory of conﬂict in which violence occurs as an outcome of a diﬃcult balancing act between the fear of being attacked and the opportunity cost of breaking peace. We link the propensity of conﬂict to current and future economic conditions and discuss the eﬀects of growth, inequality and military technology on the ability of groups to escape the Security Dilemma. Keywords : Conﬂict, Security Dilemma, Coordination failure, Global Games, Exit Games We wish to thank Jim Fearon, Bob Powell and participants of the Kellogg “conference on cooperation and conﬂict” for many useful comments. Any errors are, of course, our own. Corresponding author : gpadro@stanford.edu
Effects of Individual or Group Training and Anxiety for Youth Basketball Players’ Skill Development

EFFECTS OF INDIVIDUAL OR GROUP TRAINING AND ANXIETY FOR YOUTH BASKETBALL PLAYERS’ SKILL DEVELOPMENT John Ennis, MS George Mason University, 2013 Project Director: Craig Esherick The purpose of this study is to determine, based on experience level, if group or individual training will be more effective for youth and high school basketball players. This research is being conducted because youth basketball is a critical time for players to develop fundamental skills and prepare themselves to make a high school team. This information will be valuable to basketball trainers or coaches as it may contribute to the improvement and success of their own players and teams. Furthermore, the foundation of this research derives from these research questions: How will training in an individual setting affect a player who has little to no experience with basketball? How will training in a group setting affect a player who is already experienced with basketball? The procedural technique for this study is an experimental design with the use of the Sport Competition Anxiety Test. Testing occurred during the first and tenth week and subjects trained once a week for eight weeks in between testing. All subjects were instructed to take the SCAT immediately prior to testing. Tests consist of Mikan series, stationary dribbling, shooting ladder, dribble weave, passing at target, attacking the gaps, lane slides, push-ups, and free throws. The 60 subjects in this study were selected via the probability method of stratified random sampling.
The effect of the state sector on wage inequality in urban China: 1988–2007

This paper examines the effect of the public sector and state-owned enterprises (SOEs) on wage inequality in urban China using China Household Income Project data. It applies quantile regression analysis, the Machado and Mata decomposition to investigate how urban wage inequality was affected by the changes in wage structure and employment shares of the public sector and SOEs. We find that since the radical state sector reforms designed to reduce overstaffing and improve efficiency in the late 1990s, urban wage gaps were narrowed due to the reduction in the employment share of the state sector; the wage premium of the state sector in comparison with the non-state sector increased significantly; and changes in the wage structure of the labour market caused the rise in urban wage inequality.
Collaborative Neighborhoods

Finding relevant research publications is a growing problem for researchers across all fields. Online platforms such as Mendeley and CiteULike have attempted to address this need by providing researchers the ability to share relevant articles with one another. These platforms have further sought to extend their capabilities by recommending articles to users based on the user’s past interactions and preferences. The models that underlie these methods, however, are unable to provide recommendations on an item for which no prior interactions have been observed. To solve this issue, we propose Collaborative Neighborhoods (CN). CN combines elements of Collaborative Topic Regression [0] and Nearest Neighbor Models [1] to provide meaningful recommendations in both the presence and absence of past user interactions with items. We assess the performance of CN on dataset of 129,531 articles sourced from PubMed, and demonstrate that our models provides more accurate recommendations that extant recommendation frameworks.
Embracing Integrative Multiomics Approaches

As “-omics” data technology advances and becomes more readily accessible to address complex biological questions, increasing amount of cross “-omics” dataset is inspiring the use and development of integrative bioinformatics analysis. In the current review, we discuss multiple options for integrating data across “-omes” for a range of study designs. We discuss established methods for such analysis and point the reader to in-depth discussions for the various topics. Additionally, we discuss challenges and new directions in the area.
Upper-bound approximations for dynamic pruning

Dynamic pruning strategies for information retrieval systems can increase querying efficiency without decreasing effectiveness by using upper bounds to safely omit scoring documents that are unlikely to make the final retrieved set. Often, such upper bounds are pre-calculated at indexing time for a given weighting model. However, this precludes changing, adapting or training the weighting model without recalculating the upper bounds. Instead, upper bounds should be approximated at querying time from various statistics of each term to allow on-the-fly adaptation of the applied retrieval strategy. This article, by using uniform notation, formulates the problem of determining a term upper-bound given a weighting model and discusses the limitations of existing approximations. Moreover, we propose an upper-bound approximation using a constrained nonlinear maximization problem. We prove that our proposed upper-bound approximation does not impact the retrieval effectiveness of several modern weighting models from various different families. We also show the applicability of the approximation for the Markov Random Field proximity model. Finally, we empirically examine how the accuracy of the upper-bound approximation impacts the number of postings scored and the resulting efficiency in the context of several large Web test collections.
GTgraph : A Synthetic Graph Generator Suite

This document details the characteristics, input parameters and suggested usage of the three graph generators included in this suite. 1 SSCA#2 graph generator This generator produces graphs used in the DARPA HPCS SSCA#2 benchmark [1]. The SSCA#2 graph is directed with integer edge weights, and made up of random-sized cliques, with a hierarchical inter-clique distribution of edges based on a distance metric. An SSCA#2 clique is defined as a maximal set of vertices, where each pair of vertices is connected by directed edges in one or both directions. The following parameters can be specified by the user. The default values of each parameter are also given below. • SCALE: An integer value used to express the rest of the graph parameters. The problem size can be increased by increasing the value of SCALE. • TotVertices: The number of vertices (2) • MaxCliqueSize: The maximum number of vertices in a clique. Clique sizes are distributed uniformly on [1, MaxCliqueSize] ([2]) • ProbUnidirectional: Probability that the connections between two vertices will be unidirectional as opposed to bidirectional (0.2) • MaxParallelEdges: The maximum number of parallel edges from one vertex to another. The actual number is distributed uniformly on [1, MaxParallelEdges] (3) • ProbIntercliqueEdges: Initial probability of an interclique edges (0.5) • MaxIntWeight: Maximum value of integer edge weight. The weights are distributed uniformly on [1, MaxIntWeight] (2) For a detailed description of the intraand inter-clique edge generation algorithms, refer [1].
The acerbity of the social: how to include the social in governmental risk assessments

This paper addresses the expansion of risk practices through a case study of a government led project in Sweden purposed to develop a method to include social events in mandatory risk practices. Social heterogeneity was to be transformed into straightforward causality in order to turn the social into a manageable object. In this regard, the project was quite successful. By inviting social scientists into the process, otherwise often marginalized within risk practice, causality and quantifiable risk factors could be established and the model became a rigorous and legitimate scientific model. Although experts were granted significant autonomy and became experts far beyond their own area of expertise, the success of the model lies rather in allowing experts authority within confined boundaries. Grand narratives and critical perspectives are disregarded as too abstract and if social scientists are to infuse aspects of social critique they must adapt to these circumstances: they must become instrumentalists.
The Tactile Internet – Applications & Challenges

Wireless communications as known today enables to connect devices and people for exchanging content, being multimedia and/or data. The data rates of wireless communications continue to increase, mainly driven by innovation in electronics. An overlooked breakthrough is soon to happen, once the latency of communication systems becomes low enough to enable a round-trip delay from terminals through the network back to terminals of approximately 1ms. This is the response of human tactile to visual feedback control. In this case wireless communications can be the platform for enabling to control and steer real and virtual objects in many situations of our life. Almost no area of economy will be left untouched, with examples being health & care, mobility, education, manufacturing, smart grids, and many more. The Tactile Internet will become a driver for economies and innovation, and will help develop societies to a new level of sophistication.
JACERONG at TASS 2016: An Ensemble Classifier for Sentiment Analysis of Spanish Tweets at Global Level

This paper describes an ensemble-based approach developed to participate in TASS-2016 Task 1 on sentiment analysis of Spanish tweets at global level. Ensembles are built on the combination of systems with the lowest absolute correlation with each other. The systems are able to deal with non-standard lexical forms in tweets, in order to improve the quality of natural language analysis. To support the polarity classification, the approach uses basic features that have proved their discriminative power, as well as word and character n-gram features. Then, outputs from Logistic Regression classifiers, which may be either class labels or probabilities for each class, are used to build ensembles. Experimental results show that the less-correlated combination of 25 systems, which chooses the class with the highest unweighted average probability, is the setting that best suits to the task, achieving an overall accuracy of 62.0% in the six-labels evaluation, and of 70.5% in the fourlabels evaluation.