Miracle-dz/UniFAR-FTUs huggingface dataset:
Resorting to Internet: A look at university students’ problematic Internet use through meaning in life, self-efficacy and self-esteem

Internet can be used in a maladaptive way to escape from or compensate perceived inadequacies or the problems experiencing in daily life. In relation to this, in this study the relationship of meaning in life, self-efficacy and self-esteem to problematic Internet use was examined. Furthermore, the role of meaning in life, self-efficacy and self-esteem in predicting problematic Internet use was investigated. The study was carried out 410 university students (280 females and 130 males) attending the different grades of various departments in a school of education in Rize, Turkey. In the study, Sociodemographic Data Form, Problematic Internet Use Scale, Meaning in Life Questionnaire, General Self-Efficacy Scale and Rosenberg Self-Esteem Scale were used as data collection instruments. The data were analyzed through SPSS 15.0 version and descriptive statistics, Pearson product-moment correlation coefficient and multiple linear regression analysis were utilized in the analysis. Results showed that presence of meaning in life (r=-.26, p<.01), self-efficacy (r=-.36, p<.01) and self-esteem (r=-.29, p<.01) are negatively and significantly correlated to problematic Internet use, on the contrary, search for meaning’s relationship was found in a positive way (r=.21, p<.01). Besides, presence of meaning in life, search for meaning in life and self-efficacy emerged as significant predictors of problematic Internet use. By discussing these results in line with the relevant literature, directions were given for further studies.
The difference PDF of 21-cm fluctuations: a powerful statistical tool for probing cosmic reionization

A new generation of radio telescopes are currently being built with the goal of tracing the cosmic distribution of atomic hydrogen at redshifts 6-15 through its 21-cm line. The observations will probe the large-scale brightness fluctuations sourced by ionization fluctuations during cosmic reionization. Since detailed maps will be difficult to extract due to noise and foreground emission, efforts have focused on a statistical detection of the 21-cm fluctuations. During cosmic reionization, these fluctuations are highly non-Gaussian and thus more information can be extracted than just the one-dimensional function that is usually considered, i.e. the correlation function. We calculate a two-dimensional function that if measured observationally would allow a more thorough investigation of the properties of the underlying ionizing sources. This function is the probability distribution function (PDF) of the difference in the 21-cm brightness temperature between two points, as a function of the separation between the points. While the standard correlation function is determined by a complicated mixture of contributions from density and ionization fluctuations, we show that the difference PDF holds the key to separately measuring the statistical properties of the ionized regions.
A radio-emitting outflow in the quiescent state of A0620−00: implications for modelling low-luminosity black hole binaries

Deep observations with the Very Large Array of A0620-00, performed in 2005 August, resulted in the first detection of radio emission from a black hole binary at X-ray luminosities as low as 10-8.5 times the Eddington limit. The measured radio flux density, of 51 +/- 7 ? Jy at 8.5 GHz, is the lowest reported for an X-ray binary system so far, and is interpreted in terms of partially self-absorbed synchrotron emission from outflowing plasma. Making use of the estimated outer accretion rate of A0620-00 in quiescence, we demonstrate that the outflow kinetic power must be energetically comparable to the total accretion power associated with such rate, if it was to reach the black hole with the standard radiative efficiency of 10 per cent. This favours a model for quiescence in which a radiatively inefficient outflow accounts for a sizable fraction of the missing energy, and, in turn, substantially affects the overall dynamics of the accretion flow. Simultaneous observations in the X-ray band, with Chandra, confirm the validity of a non-linear radio/X-ray correlation for hard state black hole binaries down to low quiescent luminosities, thereby contradicting some theoretical expectations. Taking the mass term into account, the A0620-00 data lie on the extrapolation of the so-called Fundamental Plane of black hole activity, which has thus been extended by more than two orders of magnitude in radio and X-ray luminosity. With the addition of the A0620-00 point, the plane relation provides an empirical proof for the scale invariance of the jet-accretion coupling in accreting black holes over the entire parameter space observable with current instrumentation.
The Utility of an Interferon Gamma Release Assay for Diagnosis of Latent Tuberculosis Infection and Disease in Children: A Systematic Review and Meta-analysis

Background: The utility of interferon gamma release assays (IGRAs) has been assessed in adults, but remains unclear in children. We reviewed the literature on the use of a commercial IGRA in immunocompetent children for the diagnosis of both latent tuberculosis infection (LTBI) and TB disease. Methods: We searched PubMed for studies published before January 2010 on the diagnosis of TB in children using an IGRA. We compared the specificity and sensitivity of the tuberculin skin test (TST) and the IGRA for LTBI and conducted a random effects meta-analysis on sensitivity of the IGRA for TB disease. Results: Of 68 studies identified, 20 were included in this review. There was increased specificity of the IGRA for LTBI in children compared with TST, but varying sensitivities. Sensitivity of the IGRA in detecting TB disease in children also varied when compared with TST (mean &kgr; score, 0.57). For all TB cases, the pooled sensitivity was 66% (95% confidence interval [CI], 53%–78%) with heterogeneity (I2 = 74.8%). Stratification by background TB incidence highlighted a significantly reduced IGRA sensitivity of 55% (95% CI, 37%–73%) in high incidence settings when compared with low incidence settings, 70% (95% CI, 53%–84%). Conclusions: There was no clear evidence that IGRAs should replace TST for detecting LTBI in children. Sensitivity of the IGRA for TB disease was no different from TST, and a significantly reduced IGRA sensitivity was found in high-burden TB settings compared with low-burden TB settings. Further studies are needed to determine the value of IGRAs in LTBI and TB disease diagnosis in children.
A personalized recommendation algorithm via biased random walk

With the rapid development of Internet, Recommender Systems can help us efficiently find the useful objects in the information era. Generally, the traditional random walk algorithm has high accuracy but low personality and diversity. In this paper, we propose an improved random walk algorithm by depressing the influence of large-degree objects. Experimental results on MovieLens and Netflix data sets show that this algorithm can effectively improve not only the accuracy (improved by 5.5% and 5.9%, respectively) but also the diversity.
Software engineering by source transformation - experience with TXL

Many tasks in software engineering can be characterized as source to source transformations. Design recovery, software restructuring, forward engineering, language translation, platform migration and code reuse can all be understood as transformations from one source text to another. TXL, the Tree Transformation Language, is a programming language specifically designed to support rule-based source to source transformation. Originally conceived as a tool for exploring programming language dialects, TXL has evolved into a general purpose software transformation system that has proven well suited to a wide range of software maintenance and reengineering tasks, including the design recovery, analysis and automated reprogramming of billions of lines of commercial Cobol, PL/I and RPG code for the Year 2000. The authors introduce the basic features of modern TXL and its use in a range of software engineering applications, with an emphasis on how each task can be achieved by source transformation.
Advances in Bio-Tactile Sensors for Minimally Invasive Surgery Using the Fibre Bragg Grating Force Sensor Technique:A Survey

The large interest in utilising fibre Bragg grating (FBG) strain sensors for minimally invasive surgery (MIS) applications to replace conventional electrical tactile sensors has grown in the past few years. FBG strain sensors offer the advantages of optical fibre sensors, such as high sensitivity, immunity to electromagnetic noise, electrical passivity and chemical inertness, but are not limited by phase discontinuity or intensity fluctuations. FBG sensors feature a wavelength-encoding sensing signal that enables distributed sensing that utilises fewer connections. In addition, their flexibility and lightness allow easy insertion into needles and catheters, thus enabling localised measurements inside tissues and blood. Two types of FBG tactile sensors have been emphasised in the literature: single-point and array FBG tactile sensors. This paper describes the current design, development and research of the optical fibre tactile techniques that are based on FBGs to enhance the performance of MIS procedures in general. Providing MIS or microsurgery surgeons with accurate and precise measurements and control of the contact forces during tissues manipulation will benefit both surgeons and patients.
The Role of Aspirations and Obligations in Explaining the Relationship between Identity Discrepancies and Psychological Distress

Using a national sample of adults, we examine the relationship between identity discrepancies and mental health in spouse and worker identities. Building on previous research, we predict that discrepancies between how individuals want to be with respect to a particular identity (aspirations) and perceptions of how others view them in that identity (reflected appraisals) will be associated with depressive symptoms. Alternatively, discrepancies between how individuals feels they should be (obligations) and reflected appraisals will be associated with anxiety symptoms. We further examine whether identity salience moderates the relationship between discrepancies and distress. We find aspiration discrepancies are associated with depression as predicted in the spouse identity but not for the worker identity. With respect to obligation discrepancies, we find evidence for the predicted relationships for the spouse and worker identity only when identities are considered salient. We discuss the implications of our findings for the development of identity models of distress.
3-Year-Olds’ Perseveration on the DCCS Explained: A Meta-Analysis

ABSTRACT The Dimensional Change Card Sort (DCCS) task is a widely used measure of preschoolers’ executive function. We combined data for 3,290 3-year-olds from 37 unique studies reporting 130 experimental conditions. Using raw pass/fail counts, we computed the pass rates and chi-squared value for each against chance (50/50) performance. We grouped data according to DCCS variants and computed the standard pass rate and chi-squared and phi for each variant relative to standard. For all standard versions, the mean pass rate was 36%. We compared all other variants to the standard and found robust improvements in performance for manipulations that involved spatial separation of the conflicting dimensions, use of distraction between pre and post-switch, elimination of all conflict, and extra practice. We also found that negative priming offers a better explanation for 3-year-olds’ perseveration than attentional inertia. The results support a theoretical model of 3-year-olds’ performance based on inhibitory control.
Con-/divergences between postcolonial and critical peace education: towards pedagogies of decolonization in peace education

Abstract This paper focuses on the limitations of the Eurocentric modernist framework that undergirds Freirean theory and critical pedagogy in relation to critical peace education, highlighting in particular the contributions of post-colonial and decolonial thinking. The paper posits that critical approaches to peace education need to consider these limitations in pushing critical peace education to engage more postcolonial and decolonial thinking. A renewal of critical peace education that integrates the critiques of both decolonial and postcolonial perspectives will provide productive possibilities for revitalizing the transformative orientation within critical peace education and decolonizing the work of research and pedagogical praxis in peace education. This means to evoke discourses and practices that move away from the dominant categories of Eurocentric thought and engage explicitly with the ways in which understandings and pedagogies of peace education are implicated in modernity and coloniality.
HMDSAD: Hindi multi-domain sentiment aware dictionary

Sentiment Analysis is a fast growing sub area of Natural Language Processing which extracts user's opinion and classify it according to its polarity into positive, negative or neutral classes. This task of classification is required for many purposes like opinion mining, opinion summarization, contextual advertising and market analysis but it is domain dependent. The words used to convey sentiments in one domain is different from the words used to express sentiments in other domain and it is a costly task to annotate the corpora in every possible domain of interest before training the classifier for the classification. We are making an attempt to solve this problem by creating a sentiment aware dictionary using multiple domain data. The source domain data is labeled into positive and negative classes at the document level and the target domain data is unlabeled. The dictionary is created using both source and target domain data. The words used to express positive or negative sentiments in labeled data has relatedness weights assigned to it which signifies its co-occurrence frequency with the words expressing the similar sentiments in target domain. This work is carried out in Hindi, the official language of India. The web pages in Hindi language is booming very quickly after the introduction of UTF-8 encoding style. The dictionary can be used to classify the unlabeled data in the target domain by training a classifier.
MMDiff : Statistical Testing for ChIP-Seq data sets

ChIP-Seq has rapidly become the dominant experimental technique to determine the location of transcription factor binding sites and histone modifications. Typically, computational peak finders, such as Macs [Zhang et al., 2008], are used to identify potential candidate regions, i.e. regions with significantly enriched read coverage compared to some background. In the following, we will simply call these regions peaks and will assume that their genomic coordinates are provided. Going beyond this basic analysis, it is often of interest to detect a subset of peaks where significant changes of read coverage occur in a treatment experiment relative to a control (see Figure 1). Statistical analysis of ChIP-Seq data however remains challenging, due to the highly structured nature of the data and the paucity of replicates. Current approaches to detect differentially bound regions are mainly borrowed from RNA-Seq data analysis, thus focusing on total counts of fragments mapped to a region, ignoring any information encoded in the shape of the peak profile. Higher order features of ChIP-Seq peak enrichment profiles carry important and often complementary information to total counts, and hence are potentially important in assessing differential binding. We therefore incorporate higher order information into testing for differential binding by adapting recently proposed kernel-based statistical tests to ChIP-Seq data.
Map Polygon-Polygon Objects Spatial Conflicts Solution Using Simulated Annealing

Displaying map data at scales smaller than its source can result in objects that are either too small to be seen or too close to each other to be distinguishable. Furthermore, map conflicts become more likely when certain map symbols are no longer a true scale representation of the feature they represent. Map generalization involves careful examination of the interactions between all map symbols. These interactions may give rise to obvious spatial conflicts of proximity and overlap. Most cases of spatial conflicts can be resolved by displacement, whereas displacement is a very complex operation, which involves the type definitions, constraint conditions, direction and the size of the displacement and so on. As the simulated annealing method has its unique advantages in directing object displacement, in this paper, we guide the displacement of conflicted objects using simulated annealing. It is tested on a number of data sets and the result of experiment shows that the simulated annealing algorithm presented here works well.
Preventing Information Leaks through Shadow Executions

A concern about personal information confidentiality typically arises when any desktop application communicates to the external network, for example, to its producer's server for obtaining software version updates. We address this confidentiality concern of end users by an approach called shadow execution. A key property of shadow execution is that it allows applications to successfully communicate over the network while disallowing any information leaks. We describe the design and implementation of this approach for Windows applications. Experiments with our prototype implementation indicate that shadow execution allows applications to execute without inhibiting any behaviors, has acceptable performance overheads while preventing any information leaks.
Mixed Measurement Dynamic Factor Models

We propose a latent dynamic factor model framework for mixed-measurement mixed-frequency panel data. Time series observations may come from different families of parametric distributions, may be observed at different frequencies, and exhibit common dynamics and cross sectional dependence due to shared exposure to latent dynamic factors. As the main complication, the likelihood does not exist in closed form for this class of models. We therefore present three different approaches to parameter and factor estimation in this framework. First, assuming a factor structure for location parameters yields a parameter driven model that can be cast into state space form. Parameters and factors estimation is then accomplished by Monte-Carlo maximum likelihood based on importance sampling. Second, we propose a less complex observation driven alternative to the parameter driven original model, for which the likelihood exists in closed form. Finally, parameter and factor estimates can be obtained by Markov Chain Monte Carlo. We use the new mixed-measurement framework for the estimation and forecasting of intertwined credit and recovery risk conditions for US Moody’s-rated firms from 1982 - 2008. The joint model allows us to construct predictive (conditional) loss densities for portfolios of bank loans and corporate bonds in the presence of non-standard sources of credit risk such as systematic frailty effects and systematic recovery risk.
A simultaneous localization and mapping algorithm based on Kalman filtering

For automatic navigation of autonomous vehicles, localization in real time is a key issue. In this article, a simultaneous localization and mapping algorithm is proposed for an autonomous vehicle. We use a laser detection and ranging sensor to detect the operating environment. An environment map is plot out using the sensor output data. Then, with an odometer, the vehicle position is located on this map. Finally, these two sensor outputs are merged using a Kalman filter to correct the map as well as the vehicle position.
Robust detection for the uplink of broadband wireless systems with strong ACI levels

This paper considers the uplink of wireless systems using SC-FDE schemes (Single-Carrier with Frequency-Domain Equalization) with OQPSK (Offset Quaternary Phase Shift Keying) modulations. We have an asynchronous scenario where only a coarse synchronization between mobile terminals and the base station is required. We present an iterative frequency-domain receiver for joint equalization, residual carrier synchronization and ACI (Adjacent Channel Interference) suppression. Our performance results show that the proposed receiver is able to cope with strong ACI levels, even with only a coarse synchronization between users.
ISL1 Directly Regulates FGF10 Transcription during Human Cardiac Outflow Formation

The LIM homeodomain gene Islet-1 (ISL1) encodes a transcription factor that has been associated with the multipotency of human cardiac progenitors, and in mice enables the correct deployment of second heart field (SHF) cells to become the myocardium of atria, right ventricle and outflow tract. Other markers have been identified that characterize subdomains of the SHF, such as the fibroblast growth factor Fgf10 in its anterior region. While functional evidence of its essential contribution has been demonstrated in many vertebrate species, SHF expression of Isl1 has been shown in only some models. We examined the relationship between human ISL1 and FGF10 within the embryonic time window during which the linear heart tube remodels into four chambers. ISL1 transcription demarcated an anatomical region supporting the conserved existence of a SHF in humans, and transcription factors of the GATA family were co-expressed therein. In conjunction, we identified a novel enhancer containing a highly conserved ISL1 consensus binding site within the FGF10 first intron. ChIP and EMSA demonstrated its direct occupation by ISL1. Transcription mediated by ISL1 from this FGF10 intronic element was enhanced by the presence of GATA4 and TBX20 cardiac transcription factors. Finally, transgenic mice confirmed that endogenous factors bound the human FGF10 intronic enhancer to drive reporter expression in the developing cardiac outflow tract. These findings highlight the interest of examining developmental regulatory networks directly in human tissues, when possible, to assess candidate non-coding regions that may be responsible for congenital malformations.
Multi-view Clustering of Visual Words Using Canonical Correlation Analysis for Human Action Recognition

In this paper we propose a novel approach for introducing semantic relations into the bag-of-words framework for recognizing human actions. We represent visual words in two different views: the original features and the document co-occurrence representation. The latter view conveys semantic relations but is large, sparse and noisy. We use canonical correlation analysis between the two views to find a subspace in which the words are more semantically distributed. We apply k-means clustering in the computed space to find semantically meaningful clusters and use them as the semantic visual vocabulary. Incorporating the semantic visual vocabulary the features are quantized to form more discriminative histograms. Eventually the histograms are classified using an SVM classifier. We have tested our approach on KTH action dataset and achieved promising results.