Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNA-145 Increases the Apoptosis of Activated Hepatic Stellate Cells Induced by TRAIL through NF-κB Signaling Pathway

During the liver fibrosis recovery stage tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) can effectively induce apoptosis of activated hepatic stellate cells (HSCs). Normal hepatic stellate cells are resistant to TRAIL cytotoxicity. Therefore, enhancing the sensitivity of TRAIL-induced apoptosis of HSCs may be useful to treat hepatic fibrogenesis. Here, we demonstrated that miR-145 and TRAIL were down-regulated in both liver fibrosis tissue samples and transforming growth factor-β1 induced HSCs, concomitant with increased the expression of ZEB2. In addition, we found that mimics-mediated over-expression of miR-145 led to resistance to the ZEB2 expression and up-regulation of the TRAIL-induced apoptosis after treatment of LX-2 cells with TRAIL. Furthermore, ZEB2-siRNA transfected LX-2 cells showed the increased sensitivity to TRAIL-induced apoptosis. Whereas, opposite results were obtained in miR-145-inhibitor group or ZEB2 plasmid group. Moreover, miR-145 regulated ZEB2 gene expression by specifically interacting with the 3′-UTR of ZEB2 mRNA to inhibit the expression of ZEB2. Further studies showed that the over-expression of ZEB2 could inhibit TRAIL-induced apoptosis via inhibiting nuclear factor-κB (NF-κB) signaling pathway in LX-2 cells. Collectively, our data suggest that up-regulation of miR-145 can down-regulate ZEB2 expression, consequently promoting TRAIL-induced apoptosis in LX-2 cells through NF-κB signaling pathway, which facilitates the resolution of liver fibrosis.
Young Learners

The Early Literacy Knowledge and Skills (ELKS) instrument was informed by the work of Ferreiro and Teberosky based on the notion that young children could be differentiated according to levels of sophistication in their understanding of the rules of written language. As an initial step to evaluate the instrument for teaching purposes, the present study examines its psychometric properties in terms of internal consistency reliability, model-data fit, item discrimination, match between item difficulty and ability range in the sample, and item difficulty according to Ferreiro and Teberosky’s theory of early literacy development. Overall, the ELKS instrument showed good psychometric properties in these areas, although two items in particular may require further investigation and possible revision according to the model-data fit index. Future directions to investigate the potential classroom application of the instrument are suggested.
Reframing Professional Development for South African Schools

Often research on the professional development (PD) of staff is framed within a problem-based context that focuses on the PD-related problems experienced by staff. This study pursued a different approach by using the appreciative inquiry (AI) theoretical perspective to study the positive experiences of staff in respect of PD and their desire to improve the practice of PD even further. A qualitative study was carried out among four schools with maximum variance. The findings reveal the main aim of continuing PD, the changing attitudes engendered by PD, the prominent role of the principal and the requirements for effective PD programs including the selection of facilitators, appropriate venues and the timing and duration of workshops, as well as feedback on workshops. The study provides evidence that an AI approach may be used as a basis for identifying guidelines on improving PD practice. The article concludes with implications of the findings for principals of schools.
BUILD-IT : an intuitive simulation tool for multi-expert layout processes

BUILD-IT is a planning tool based on intuitive computer vision technology, supporting complex planning and configuration tasks. It allows a group of people, seated around a table, to move virtual objects with a real brick as interaction handler. With this tool, object manipulation and image display take place within the very same working area. Hence new aspects of interaction and direct response have been added to the computer-based planning process. Together with the image displayed on the table, a perspective view of the situation is projected on a vertical screen. This system offers all kinds of users access to state-of-the-art computing and visualisation, requiring little computer literacy. It offers a new way of interaction, facilitating team-based evaluation of alternative layouts. A connection to the simulation package SIMPLE++ has been realised. Hence, each alternative can be simulated and displayed using the visualisation capabilities of BUILD-IT.
Are Deep Learning Methods Better for Twitter Sentiment Analysis

Many applications based on sentiment analysis on social media, such as Twitter, have been developed by researchers. Recently, during the Unites States presidential election of 2016, politicians, including president-elect Donald J. Trump, have been using Twitter as a mean of communicating with the public, drawing tremendous attention to Twitter. It is known that sentiment analysis on tweets still fall behind it on traditional texts, such as movie reviews and product reviews, while it has achieved tangible progress since the popularity of deep learning and the availability of large training datasets (distant supervised by emoticons and hashtags). However, previous sentiment analysis studies on tweets usually carried out in an experimental setting, i.e., their training/validation/test datasets only have two types of global polarities (i.e., positive and negative). What makes it worse, the judgments made by systems are not consciously linked to the designated evaluation objects, i.e., they just mathematically fit features extracted from tweets to their true polarities as simple document classification does. These experimental settings are basically unpractical for real-world systems. First, the tweets that are passed to systems in a production environment unavoidably contain three types of polarities (i.e., positive, negative and neutral), since we cannot pick out positive and negative tweets from a large collection of tweets by any kind of automated tweet filtering beforehand. Second, the global polarity of a tweet is defined as author’s attitude to a specific evaluation object (topic) in it. We cannot decide the global polarity of a tweet without given an evaluation object, especially for tweets containing multiple topics and complex contexts. For example, in the following tweet, there are two topics (i.e., #windows8 and #skype). This tweet could be a positive tweet (regarding Windows 8) or a neutral tweet (regarding Skype).
Study of the Role of Personality Factors in Organizational Citizenship Behaviors

Organizational citizenship behavior (OCB) as a non-mandatory cooperation with others significantly influences an organization’s performance and social capital. In this paper it has been attempted to study the role of personality traits based on the Big Five model namely, extraversion, agreeableness, conscientiousness, openness to experience and neuroticism in the performing of organizational citizenship behavior, while Altruism, civic virtue, organizational conscientiousness, courtesy and sportsmanship were regarded as the main OCB dimensions. Correlation analysis on data from 56 employees of “Bank Mellat” of Tehran, revealed that there was a significant relationship between personality characteristics and OCB. The present study suggests that conscientiousness, agreeableness and emotional stability positively affect OCB. Also according to the regression model conscientiousness is the best factor to predict OCB. The current research demonstrates that neuroticism is negatively related to OCB, since it diminishes a person's ability to avoid complaining while facing organizational problems.
Effects of Exposure to Nanoparticle-rich Diesel Exhaust on Pregnancy in Rats

Abstract Pollutants from burning of diesel fuel are hazardous to human health. Nanoparticles in diesel exhaust potentially have profound impact on fetal development and maternal endocrine function during pregnancy due to their ability to penetrate deeply into the body. To investigate the effects of nanoparticle-rich diesel exhaust (NR-DE) on pregnancy, pregnant rats were exposed to NR-DE, filtered diesel exhaust (F-DE) or clean air for 19 days of gestation. Relative weights of maternal liver and spleen to body weight were significantly lower in the NR-DE and F-DE groups than those in the control group. The serum concentration of maternal progesterone was significantly lower, while those of luteinizing hormone (LH) and corticosterone were significantly higher in the NR-DE and F-DE groups than those in the control group. The serum concentration of estradiol-17β was significantly higher in the F-DE group than that in the control group. The levels of cytochrome P450 side-chain cleavage enzyme, 3β-hydroxysteroid dehydrogenase and LH receptor mRNA in the corpus luteum were significantly lower in the NR-DE and F-DE groups than those in the control. In fetuses, body weight and crown-rump length were significantly greater and shorter, respectively, in both males and females in the NR-DE and F-DE groups than those in the control group. These results demonstrate that exposure of pregnant rats to NR-DE and F-DE suppresses the function of corpora lutea and stimulates the function of the adrenal cortex, suggesting a risk of spontaneous abortion associated with maternal hormonal changes.
Should Simulation Products use Software Engineering Techniques or Should they Reuse Products of Software Engineering? -- Part 1

This two-part article addresses the issues concerning the building of new simulation software by either reusing existing general purpose software products and frameworks or by writing the simulation software from scratch. As a means of discussing the use of existing software, this first part describes a selected list of such existing software: the Eclipse IDE as graphical user front-end, Maven for the management and building of projects, Bonita for supporting simulation workflows, Ruby on Rails and its Hobo extension to provide online persistence, and the Fractal Component Model for supporting the popular Component-Based Modeling & Simulation approach. The second part, to be published in the next issue of M&S Magazine, will further explore some interesting features found in the selected software solutions, and discuss their benefits when applied to simulation.
An integrated network motif based approach to identify colorectal cancer related genes

Identifying colorectal cancer related genes is crucial to diagnose and treat this disease. Many conventional approaches based on gene expression data have been developed to identify disease genes through patterns of gene activity. These approaches usually ignore other heterogeneous information, for example, gene-gene interactions, epigenomic data and gene expression data. We propose a novel integrated approach based on network motif to identify colorectal cancer related genes, which considered the network topological characteristic and coordinated changed pattern characteristic of gene expression data, epigenomic data. Screened network motifs and motif's genes are respectively used as classification features to distinguish colorectal cancer samples from normal samples. Result shows they achieve almost the same accuracy in classification as the known cancer marker genes. Functional enrichment analysis reveals that the genes of the screened motifs are annotated to important biological process. Most of them can be validated to highly associate with the development of colorectal cancer based on previous studies. We not only provide a method for identification of disease related genes but also add a new perspective to integrate heterogeneous data and mine subgraph with significant biological characteristics pattern.
Designing a Call Center with Impatient Customers

The most common model to support workforce management of telephone call centers is theM/ M/ N/ B model, in particular its special casesM/ M/ N (Erlang C, which models out busy signals) andM/ M/ N/ N (Erlang B, disallowing waiting). All of these models lack a central prevalent feature, namely, that impatient customers might decide to leave (abandon) before their service begins.In this paper, we analyze the simplest abandonment model, in which customers' patience is exponentially distributed and the system's waiting capacity is unlimited ( M/ M/ N +M). Such a model is both rich and analyzable enough to provide information that is practically important for call-center managers. We first outline a method for exact analysis of theM/ M/ N +M model, that while numerically tractable is not very insightful. We then proceed with an asymptotic analysis of theM/ M/ N +M model, in a regime that is appropriate for large call centers (many agents, high efficiency, high service level). Guided by the asymptotic behavior, we derive approximations for performance measures and propose "rules of thumb" for the design of large call centers. We thus add support to the growing acknowledgment that insights from diffusion approximations are directly applicable to management practice.
Social Ties and Emotions: Evidence from Social Media

The social connections, or ties, individuals create affect their life outcomes, for example, by providing novel information that leads to new jobs or career opportunities. A host of socioeconomic and cognitive factors are believed to affect social interactions, but few of these factors have been empirically validated. In this research work, we extracted a large corpus of data from a popular social media platform that consists of geo-referenced messages, or tweets, posted from a major US metropolitan area. We linked these tweets to US Census data through their locations. This allowed us to measure emotions expressed in tweets posted from a specific area, and also use that area's socioeconomic and demographic characteristics in the analysis. We extracted the structure of social interactions from the people mentioned in tweets from that area. We find that at an aggregate level, areas where social media users engage in stronger, less diverse online social interactions are those where they express more negative emotions, like sadness and anger. With respect to demographics, these areas have larger numbers of Hispanic residents, lower mean household income, and lower education levels. Conversely, areas with weaker, more diverse online interactions are associated with happier, more positive feelings and also have better educated, younger and higher-earning residents. Our work highlights the value of linking social media data to traditional data sources, such as US Census, to drive novel analysis of online behavior.
Effects of Individual Differences on the Perceived Job Relatedness of a Cognitive Ability Test and a Multimedia Situational Judgment Test

Although there is a growing number of publications concerning applicant reactions to different selection instruments, the relationships between individual differences and applicant reactions have largely remained unexplored. The aim of the present study was to examine the effects of several testing-related and general individual differences (anxiety, self-evaluations, and personality) on the most commonly studied dimension of applicant reactions, namely the perceived job relatedness of selection instruments. Participants were 153 psychology students, who completed a cognitive ability test and a multimedia situational judgment test as part of their educational program. Our results indicated that computer anxiety negatively affected perceived job relatedness and core self-evaluations, subjective well-being, agreeableness, emotional stability, and openness to experience positively affected perceived job relatedness. Openness to experience was the most consistent predictor of perceived job relatedness. The results of our study suggest that certain individuals may be more predisposed to react positively to selection instruments. Therefore, we concluded that the nature of the applicant pool should be carefully considered when designing interventions to improve applicant reactions.
Signal-mediated retrieval of a membrane protein from the Golgi to the ER in yeast

The Saccharomyces cerevisiae Wbp1 protein is an endoplasmic reticulum (ER), type I transmembrane protein which contains a cytoplasmic dilysine (KKXX) motif. This motif has previously been shown to direct Golgi-to-ER retrieval of type I membrane proteins in mammalian cells (Jackson, M. R., T. Nilsson, and P. A. Peterson. 1993. J. Cell Biol. 121: 317-333). To analyze the role of this motif in yeast, we constructed a SUC2-WBP1 chimera consisting of the coding sequence for the normally secreted glycoprotein invertase fused to the coding sequence of the COOH terminus (including the transmembrane domain and 16-amino acid cytoplasmic tail) of Wbplp. Carbohydrate analysis of the invertase-Wbp1 fusion protein using mannose linkage-specific antiserum demonstrated that the fusion protein was efficiently modified by the early Golgi initial alpha 1,6 mannosyltransferase (Och1p). Subcellular fractionation revealed that > 90% of the alpha 1,6 mannose-modified fusion protein colocalized with the ER (Wbp1p) and not with the Golgi Och1p-containing compartment or other membrane fractions. Amino acid changes within the dily sine motif (KK-->QK, KQ, or QQ) did not change the kinetics of initial alpha 1,6 mannose modification of the fusion protein but did dramatically increase the rate of modification by more distal Golgi (elongating alpha 1,6 and alpha 1,3) mannosyltransferases. These mutant fusion proteins were then delivered directly from a late Golgi compartment to the vacuole, where they were proteolytically cleaved in a PEP4-dependent manner. While amino acids surrounding the dilysine motif played only a minor role in retention ability, mutations that altered the position of the lysines relative to the COOH terminus of the fusion protein also yielded a dramatic defect in ER retention. Collectively, our results indicate that the KKXX motif does not simply retain proteins in the ER but rather directs their rapid retrieval from a novel, Och1p-containing early Golgi compartment. Similar to observations in mammalian cells, it is the presence of two lysine residues at the appropriate COOH-terminal position which represents the most important features of this sorting determinant.
Specific HIV Protease Inhibitors Inhibit the Ability of Hpv16 E6 to Degrade P53 and Selectively Kill E6-Dependent Cervical Carcinoma Cells In Vitro

Although HIV protease inhibitor (PI) drugs predominantly target HIV proteases 1 and 2, it is also known that part of their efficacy is due to selective inhibition of the proteasome. The pathogenicity of high-risk human papilloma virus (HPV) is dependent on expression of viral E6 proteins which inappropriately activate the 26S proteasome to degrade p53 and other cellular proteins that are detrimental to viral replication. Comparison of the ability of the PIs indinavir, ritonavir, amprenavir, lopinavir, atazanavir, nelfinavir and saquinavir to inhibit E6-mediated proteasomal degradation of mutant p53 in E6-transfected C33A cells showed that 15μM lopinavir, 1 mM indinavir or 125 μM ritonavir treatment for 24 h produced a stable increase in the level of nuclear p53 in these cells with minimal cell death. After 4 h exposure of HPV16+ve SiHa cells to 15 μM lopinavir, a transient increase in wild-type p53 expression was observed associated with a 7% reduction in the chymotryptic activity of the 20S proteasome and apoptosis after 24 h. Comparison of growth rates of PI treated SiHa, CaSki, C33A, C33A-E6 and non-transformed NIH/3T3 cells showed that SiHa were the most sensitive, whereas NIH/3T3 were least affected. In conclusion, these data show that specific HIV PIs such as lopinavir and possibly indinavir, can induce selective toxicity of HPV-transformed cervical carcinoma cells expressing wild-type p53 and may form the basis of a topically applied alternative to surgery for the treatment of HPV-related premalignant lesions of the cervix.
V5116 Sagittarii, an Eclipsing Supersoft Postoutburst Nova?

V5116 Sgr (Nova Sgr 2005 No. 2), discovered on 2005 July 4, was observed with XMM-Newton in 2007 March, 20 months after the optical outburst. The X-ray spectrum shows that the nova had evolved to a pure supersoft X-ray source, with no significant emission at energies above 1 keV. The X-ray light curve shows abrupt decreases and increases of the flux by a factor ~8. It is consistent with a periodicity of 2.97 hr, the orbital period suggested by Dobrotka and coworkers, although the observation lasted just a little more than a whole period. We estimate the distance to V5116 Sgr to be 11 ± 3 kpc. A simple blackbody model does not fit correctly the EPIC spectra, with χ2ν > 4. In contrast, ONe-rich white dwarf atmosphere models provide a good fit, with NH = (1.3 ± 0.1) × 1021 cm−2, T = (6.1 ± 0.1) × 105 K, and L = (3.9 ± 0.8) × 1037(D/10 kpc)2 ergs s−1 (during the high-flux periods). This is consistent with residual hydrogen burning in the white dwarf envelope. The white dwarf atmosphere temperature is the same both in the low- and the high-flux periods, ruling out an intrinsic variation of the X-ray source as the origin of the flux changes. We speculate that the X-ray light curve may result from a partial coverage by an asymmetric accretion disk in a high-inclination system.
Attitudes and Perceptions of Young Men towards Gender Equality and Violence in Timor-Leste

This article examines attitudes and perceptions of young men toward gender relations and gender-based violence in post-conflict Timor-Leste. A high level of domestic violence is reported and a law against domestic violence has been passed in recent years. In 2013, a research team surveyed almost 500 young men using the Gender-Equitable Men (GEM) Scale in both rural and urban contexts. It was found that young men become less gender equitable as they get older, and the environment they grow up in influences their gender attitudes. Existing contradictions and tensions between national government policy and local customary practices are well-known, and these are reflected in young men’s acceptance of general principles of gender equality, which is unmatched by their willingness to accept more equitable gender relations in their own lives. Of concern was the level of young men’s acceptance of sexual harassment and forced sex. Mechanisms are required to influence young men’s attitudes to gender equality and intimate partner relations in school programs and other arenas as a priority.
A Baseline Learning Genetic Fuzzy Classifier Based on Low Quality Data

Obtaining fuzzy rules from low quality data is a topic that has been recently formalized. This paper contains the first appli- cation of these principles to classification problems. We intend that the classifier proposed here serves as a baseline for future develop- ments in the field. For that reason, we have extended a simple crisp genetic fuzzy classifier to imprecise data, paying special attention to the computational details. In particular, we will discuss some issues about the fuzzy-valued fitness function that is used in our formalism. A synthetic problem, plus two real-world datasets of low and medium complexities are also proposed, and used to evaluate the algorithm.