Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcription Factors and microRNA-Co-Regulated Genes in Gastric Cancer Invasion in Ex Vivo

Aberrant miRNA expression abnormally modulates gene expression in cells and can contribute to tumorigenesis in humans. This study identified functionally relevant differentially expressed genes using the transcription factors and miRNA-co-regulated network analysis for gastric cancer. The TF-miRNA co-regulatory network was constructed based on data obtained from cDNA microarray and miRNA expression profiling of gastric cancer tissues. The network along with their co-regulated genes was analyzed using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Transcriptional Regulatory Element Database (TRED). We found eighteen (17 up-regulated and 1 down-regulated) differentially expressed genes that were co-regulated by transcription factors and miRNAs. KEGG pathway analysis revealed that these genes were part of the extracellular matrix-receptor interaction and focal adhesion signaling pathways. In addition, qRT- PCR and Western blot data showed an increase in COL1A1 and decrease in NCAM1 mRNA and protein levels in gastric cancer tissues. Thus, these data provided the first evidence to illustrate that altered gene network was associated with gastric cancer invasion. Further study with a large sample size and more functional experiments is needed to confirm these data and contribute to diagnostic and treatment strategies for gastric cancer.
Loss of Mrap2 is associated with Sim1 deficiency and increased circulating cholesterol

Melanocortin receptor accessory protein 2 (MRAP2) is a transmembrane accessory protein predominantly expressed in the brain. Both global and brain-specific deletion of Mrap2 in mice results in severe obesity. Loss-of-function MRAP2 mutations have also been associated with obesity in humans. Although MRAP2 has been shown to interact with MC4R, a G protein-coupled receptor with an established role in energy homeostasis, appetite regulation and lipid metabolism, the mechanisms through which loss of MRAP2 causes obesity remains uncertain. In this study, we used two independently derived lines of Mrap2 deficient mice (Mrap2tm1a/tm1a) to further study the role of Mrap2 in the regulation of energy balance and peripheral lipid metabolism. Mrap2tm1a/tm1a mice have a significant increase in body weight, with increased fat and lean mass, but without detectable changes in food intake or energy expenditure. Transcriptomic analysis showed significantly decreased expression of Sim1, Trh, Oxt and Crh within the hypothalamic paraventricular nucleus of Mrap2tm1a/tm1a mice. Circulating levels of both high-density lipoprotein and low-density lipoprotein were significantly increased in Mrap2 deficient mice. Taken together, these data corroborate the role of MRAP2 in metabolic regulation and indicate that, at least in part, this may be due to defective central melanocortin signalling.
Machine Learned Machines: Adaptive co-optimization of caches, cores, and On-chip Network

Modern multicore architectures require runtime optimization techniques to address the problem of mismatches between the dynamic resource requirements of different processes and the runtime allocation. Choosing between multiple optimizations at runtime is complex due to the non-additive effects, making the adaptiveness of the machine learning techniques useful. We present a novel method, Machine Learned Machines (MLM), by using Online Reinforcement Learning (RL) to perform dynamic partitioning of the last level cache (LLC), along with dynamic voltage and frequency scaling (DVFS) of the core and uncore (interconnection network and LLC). We show that the co-optimization results in much lower energy-delay product (EDP) than any of the techniques applied individually. The results show an average of 19.6% EDP and 2.6% execution time improvement over the baseline.
Understanding eHealth Literacy From a Privacy Perspective: eHealth Literacy and Digital Privacy Skills in American Disadvantaged Communities

Despite the importance of eHealth literacy in the eHealth domain, studies on the antecedents of eHealth literacy, especially through a privacy lens, are still limited. Using a door-to-door paper-and-pencil household census of public housing communities in a major American city, this study examines how eHealth literacy varies by digital privacy skills that go beyond frequency of Internet activities among members of such disadvantaged communities. Results show that proficiency in digital privacy skills plays a positive and direct role in influencing levels of eHealth literacy. In addition, proficiency in digital privacy skills mediates the positive relationship between frequency of Internet activities and levels of eHealth literacy. This study offers a refined understanding of eHealth literacy from a privacy perspective.
Are Humans Like Ants? -- Analyzing Collective Opinion Formation in Online Discussions

Web 2.0 platforms give people more power over the way they share information and exchange opinions. The increase in social interactivity leads to the emerging of self-organized communities where members form their opinions via social swarming. This paper introduces a new approach which enables predicting and explaining the process of collective opinion formation by social swarming. A computational model for simulating collective opinion formation is derived from the ant colony meta-heuristic and applied to an exemplary online community where the members' opinions are identified via text mining. For validation purposes, this approach is compared to three other approaches.
ITCA: Inter-task Conflict-Aware CPU Accounting for CMPs

Chip-MultiProcessor (CMP) architectures are becoming more and more popular as an alternative to the traditional processors that only extract instruction-level parallelism from an application. CMPs introduce complexities when accounting CPU utilization. This is due to the fact that the progress done by an application during an interval of time highly depends on the activity of the other applications it is co-scheduled with. In this paper, we identify how an inaccurate measurement of the CPU utilization affects several key aspects of the system like the application scheduling or the charging mechanism in data centers. We propose a new hardware CPU accounting mechanism to improve the accuracy when measuring the CPU utilization in CMPs and compare it with the previous accounting mechanisms. Our results show that currently known mechanisms lead to a 19 % average error when it comes to CPU utilization accounting. Our proposal reduces this error to less than 1 % in a modeled 4-core processor system.
Examining adults’ participant roles in cyberbullying

Adults’ participant roles in cyberbullying remain unclear. Two hundred and sixty-four (163 female and 87 male) 18- to 74-year-olds from 31 countries completed measures to assess their experiences of, and engagement in, 5 cyberbullying types for up to 9 media. Cluster analysis identified two distinct groups: rarely victim and bully (85%) and frequently victim and occasional bully. Sex and age predicted group membership: Females and older participants were more likely to belong to the rarely victim and bully group, whereas males and younger participants were more likely to belong to the frequently victim and occasional bully group. The findings have implications for anti-cyberbullying interventions and how behaviors are interpreted online.
Regulation of the balance of cytokine production and the signal transducer and activator of transcription (STAT) transcription factor activity by cytokines and inflammatory synovial fluids

The balance between type 1 and 2 T helper cell cytokine production plays an important role in several animal models of autoimmunity, and skewed patterns of cytokine expression have been described in human inflammatory diseases. Many cytokines activate signal transducer and activation of transcription (STAT) transcription factors, which, in turn, activate transcription of inflammatory effector genes. We used mononuclear cell priming cultures and inflammatory synovial fluids (SFs) derived from arthritis patients to examine the regulation of cytokine production and STAT activity by an inflammatory synovial microenvironment. Exposure to SFs during priming resulted in an 81% inhibition of interferon (IFN)-gamma, but not interleukin (IL) 4, production by effector cells generated in priming cultures. SF suppression was mediated by IL-4 and IL-10 and inhibition of IL-12 expression, and it was reversed in a dominant fashion by exogenous IL- 12. SFs blocked the sustained activity of transcription factor Stat1, but not Stat3, during the priming period, and Stat1 activity was differentially regulated by cytokines in parallel with their positive or negative regulation of IFN-gamma production. Active Stat3, but not Stat1, was detected in cells from inflamed joints. These results suggest a role for altered balance of Stat1 and Stat3 transcriptional activity in the regulation of T cell differentiation and in the pathogenesis of inflammatory synovitis.
On weighted local fitting and its relation to the Horvitz-Thompson estimator

Weighting is a largely used concept in many fields of statistics and has frequently caused controversies on its justification and profit. In this paper, we analyze a weighted version of the well-known local polynomial regression estimators, derive their asymptotic bias and variance, and find that the conflict between the asymptotically optimal weighting scheme and the practical requirements has a surprising counterpart in sampling theory, leading us back to the discussion on Basu’s (1971) elephants.
Modeling anchor text and classifying queries to enhance web document retrieval

Several types of queries are widely used on the World Wide Web and the expected retrieval method can vary depending on the query type. We propose a method for classifying queries into informational and navigational types. Because terms in navigational queries often appear in anchor text for links to other pages, we analyze the distribution of query terms in anchor texts on the Web for query classification purposes. While content-based retrieval is effective for informational queries, anchor-based retrieval is effective for navigational queries. Our retrieval system combines the results obtained with the content-based and anchor-based retrieval methods, in which the weight for each retrieval result is determined automatically depending on the result of the query classification. We also propose a method for improving anchor-based retrieval. Our retrieval method, which computes the probability that a document is retrieved in response to the given query, identifies synonyms of query terms in the anchor texts on the Web and uses these synonyms for smoothing purposes in the probability estimation. We use the NTCIR test collections and show the effectiveness of individual methods and the entire Web retrieval system experimentally.
DIAGNOSTICS FOR REDESIGNING SURVEY QUESTIONNAIRES MEASURING WORK IN THE CURRENT POPULATION SURVEY

Between 1986 and 1993, a program of questionnaire design and cognitive research was conducted by the Census Bureau and Bureau of Labor Statistics, to improve labor force measurements in the Current Population Survey (CPS). As part of the research program, diagnostic measures for systematically testing and evaluating alternative questionnaire versions were developed and applied. This article reports results of applying two methods, special follow-up probes and hypothetical vignettes, to the measurement of "work" in the CPS. These measures provided both direct and indirect information about problems of respondent comprehension and reporting errors. In this article, we analyze results using these diagnostic measures to evaluate the effect of questionnaire revisions on reporting of work activities, and we assess the consistency and usefulness of the information provided by alternative diagnostic measures for pretesting and selecting questions.
Audio peer feedback to promote deep learning in online education

We investigated the relation between providing and receiving audio peer feedback with a deep approach to learning within online education. Online students were asked to complete peer feedback assignments. Data through a questionnaire with 108 respondents and 14 interviews were used to measure to what extent deep learning was perceived and why. Results support the view that both providing and receiving audio peer feedback indeed promote deep learning. As a consequence of the peer feedback method, the following student mechanisms were triggered: “feeling personally committed,” “probing back and forth,” and “understanding one's own learning process. ” Particularly important for both providing and receiving feedback is feeling personally committed. Results also show that mechanisms were a stronger predictor for deep learning when providing than when receiving. Given the context in which instructors face an increasing number of students and a high workload, students may be supported by online audio peer feedback as a method to choose a deep approach to learning.
The Influence of Inquiry-Based Multimedia Learning Environment on Scientific Problem-Solving Skills Among Ninth-Grade Students Across Gender Differences

This study investigated the use of inquiry-based multimedia learning environment as a way to increase students’ problem-solving skills, especially female students in a ninth-grade astronomy course. Using a preand posttest design, the study used multiple choice and written essay questions to measure students’ content understanding and problem-solving skills. The results of ANOVA conclude that inquiry-based multimedia learning is viable and effective for improving content understanding and problem-solving skills with all students, especially females.
Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking?

Recently, sparse representation based visual tracking methods have attracted increasing attention in the computer vision community. Although achieve superior performance to traditional tracking methods, however, a basic problem has not been answered yet --- that whether the sparsity constrain is really needed for visual tracking? To answer this question, in this paper, we first propose a robust non-sparse representation based tracker and then conduct extensive experiments to compare it against several state-of-the-art sparse representation based trackers. Our experiment results and analysis indicate that the proposed non-sparse tracker achieved competitive tracking accuracy with sparse trackers while having faster running speed, which support our non-sparse tracker to be used in practical applications.
Caught in the act: A helium-reionizing quasar near the line of sight to Q0302-003

We report the discovery of a quasar at $z=3.050\pm0.003$, closely coincident in redshift with the isolated low-opacity feature seen near $z\simeq 3.056$ in the otherwise black portion of the $\ion{He}{ii}$ Gunn-Peterson absorption trough seen toward the $z=3.286$ background quasar Q0302-003, located $6\farcm5$ away on the sky. We explore plausible models for the $\ion{He}{iii}$ ionization zone created by this neighboring quasar and its interception with the line of sight toward Q0302-003. At its present brightness of $V\simeq 20.5$ and separation of $D_\perp\simeq3.2$ Mpc, the quasar can readily account for the opacity gap in the $\ion{He}{ii}$ absorption spectrum of Q0302-003, provided it has been active for $t_Q\ga 10^7$ y. This is the first clear example of the “transverse” proximity effect and the association of a quasar with its imprint on the intervening absorption detected along an adjacent line of sight.
The effect of first and second language use on question types in English medium instruction science classrooms in Hong Kong

ABSTRACT The role of the first language (L1) in second language (L2) learning has been widely discussed and researched in the second Language Acquisition (SLA) literature. Benefits of L1 use have been found for vocabulary acquisition, and in facilitating comprehension thereby alleviating student anxiety. Many teachers appear to consider L1 use as a necessary option in L2 pedagogy. Disadvantages of L1 use are argued to be that it reduces exposure to the L2 thereby not enabling more implicit forms of L2 acquisition. Considerably less research has been carried out in English medium instruction (EMI) classrooms, surprisingly, as these are predicated on the benefits of massive exposure to the L2. This study investigated the effect of L1 and L2 use on teacher question types and interaction patterns in science lessons in early EMI and late EMI schools in Hong Kong. Our findings show that in late EMI, where there was much greater use of the L1, teachers tended to use higher order questions and were more interactive. In early EMI, despite students having received four more years of greater exposure to English instruction than late EMI students through the use of English as the vehicular language, teachers asked lower order questions and the interaction was more monologic. The implications for policy and pedagogy are discussed.
Towards a gamification of industrial production: a comparative study in sheltered work environments

Using video game elements to improve user experience and user engagement in non-game applications is called "gamification". This method of enriching human-computer interaction has been applied successfully in education, health and general business processes. However, it has not been established in industrial production so far. After discussing the requirements specific for the production domain we present two workplaces augmented with gamification. Both implementations are based on a common framework for context-aware assistive systems but exemplify different approaches: the visualization of work performance is complex in System 1 and simple in System 2. Based on two studies in sheltered work environments with impaired workers, we analyze and compare the systems' effects on work and on workers. We show that gamification leads to a speed-accuracy-tradeoff if no quality-related feedback is provided. Another finding is that there is a highly significant raise in acceptance if a straightforward visualization approach for gamification is used.
The cubic spherical optimization problems

In this paper, the cubic spherical optimization problems, including the cubic one-spherical/two-spherical/three-spherical optimization problems, are discussed. We ﬁrst show that the two-spherical optimization problem is a special case of the three-spherical optimization problem. Then we show that the one-spherical optimization problem and the two-spherical optimization problem have the same optimal value when the tensor is symmetric. In addition, NP-hardness of them are established. For the cubic three-spherical optimization problem, we discuss the conditions under which the problem is polynomial time solvable and if the polynomial time approximation scheme (PTAS) exists. Then we present a relative quality bound by ﬁnding the largest singular values of matrices. Finally, a practical method for solving the cubic three-spherical optimization problem is proposed and preliminary numerical results are reported.
Optimization of parameters in the Menzerath–Altmann law

Four formulas of the Menzerath–Altmann law are tested from the point of view of their applicability and suitability. The accuracy of related approximations of measured data is examined by the least square method at first. Then the accuracy of calculated parameters in the formulas under consideration is compared statistically. The influence of neglecting parameter c is investigated as well. Finally, the obtained results are discussed by means of an illustrative example from quantitative linguistics.
Interfacing network coding with TCP: an implementation

In previous work (`Network coding meets TCP') we proposed a new protocol that interfaces network coding with TCP by means of a coding layer between TCP and IP. Unlike the usual batch-based coding schemes, the protocol uses a TCP-compatible sliding window code in combination with new rules for acknowledging bytes to TCP that take into account the network coding operations in the lower layer. The protocol was presented in a theoretical framework and considered only in conjunction with TCP Vegas. In this paper we present a real-world implementation of this protocol that addresses several important practical aspects of incorporating network coding and decoding with TCP's window management mechanism. Further, we work with the more widespread and practical TCP Reno. Our implementation significantly advances the goal of designing a deployable, general, TCP-compatible protocol that provides the benefits of network coding.
Expression Patterns of GmAP2/EREB-Like Transcription Factors Involved in Soybean Responses to Water Deficit

Soybean farming has faced several losses in productivity due to drought events in the last few decades. However, plants have molecular mechanisms to prevent and protect against water deficit injuries, and transcription factors play an important role in triggering different defense mechanisms. Understanding the expression patterns of transcription factors in response to water deficit and to environmental diurnal changes is very important for unveiling water deficit stress tolerance mechanisms. Here, we analyzed the expression patterns of ten APETALA2/Ethylene Responsive Element Binding-like (AP2/EREB-like) transcription factors in two soybean genotypes (BR16: drought-sensitive; and Embrapa 48: drought-tolerant). According to phylogenetic and domain analyses, these genes can be included in the DREB and ERF subfamilies. We also analyzed a GmDRIP-like gene that encodes a DREB negative regulator. We detected the up-regulation of 9 GmAP2/EREB-like genes and identified transcriptional differences that were dependent on the levels of the stress applied and the tissue type analyzed (the expression of the GmDREB1F-like gene, for example, was four times higher in roots than in leaves). The GmDRIP-like gene was not induced by water deficit in BR16 during the longest periods of stress, but was significantly induced in Embrapa 48; this suggests a possible genetic/molecular difference between the responses of these cultivars to water deficit stress. Additionally, RNAseq gene expression analysis over a 24-h time course indicates that the expression patterns of several GmDREB-like genes are subject to oscillation over the course of the day, indicating a possible circadian regulation.
Evolution of Breaking Directional Spectral Waves in the Nearshore Zone

Methods used in parabolic refraction-diffraction models for computing the evolution of monochromatic waves in the nearshore zone are used to construct a model for spectral wave conditions. The two dimensional spectrum is divided into discrete wave components and the individual wave components are computed simultaneously in the domain using parabolic models for each wave component. Statistical quantities are computed at each forward step in the parabolic scheme and used to construct a statistical wave breaking model. The breaking model is built into the parabolic model equation using an additional breaking term. Model results are compared to available one- or two-dimensional data.