Miracle-dz/UniFAR-FTUs huggingface dataset:
Factor Structure and Gender Stability in the Multidimensional Condom Attitudes Scale

Sexually transmitted infections continue to trouble the United States and can be attenuated through increased condom use. Attitudes about condoms are an important multidimensional factor that can affect sexual health choices and have been successfully measured using the Multidimensional Condom Attitudes Scale (MCAS). Such attitudes have the potential to vary between men and women, yet little work has been undertaken to identify if the MCAS accurately captures attitudes without being influenced by underlying gender biases. We examined the factor structure and gender invariance on the MCAS using confirmatory factor analysis and item response theory, within-subscale differential item functioning analyses. More than 770 participants provided data via the Internet. Results of differential item functioning analyses identified three items as differentially functioning between the genders, and removal of these items is recommended. Findings confirmed the previously hypothesized multidimensional nature of condom attitudes and the five-factor structure of the MCAS even after the removal of the three problematic items. In general, comparisons across genders using the MCAS seem reasonable from a methodological standpoint. Results are discussed in terms of improving sexual health research and interventions.
Borrowing on the Wrong Credit Card: Evidence from Mexico

We study how consumers allocate debt across credit cards they already hold using new data on credit card activity for a representative sample of consumers with two homogeneous cards in Mexico. We find that relative prices are a very weak predictor of the allocation of debt, purchases, and payments. On average, consumers pay 31% above their minimum financing cost. Evidence on cross-card debt elasticities with respect to interest rates and credit limits show no substitution in the price margin. Our findings offer evidence against the cost-minimizing hypothesis and provide support to behavioral explanations.
Conditional Convolutional Neural Network for Modality-Aware Face Recognition

Faces in the wild are usually captured with various poses, illuminations and occlusions, and thus inherently multimodally distributed in many tasks. We propose a conditional Convolutional Neural Network, named as c-CNN, to handle multimodal face recognition. Different from traditional CNN that adopts fixed convolution kernels, samples in c-CNN are processed with dynamically activated sets of kernels. In particular, convolution kernels within each layer are only sparsely activated when a sample is passed through the network. For a given sample, the activations of convolution kernels in a certain layer are conditioned on its present intermediate representation and the activation status in the lower layers. The activated kernels across layers define the sample-specific adaptive routes that reveal the distribution of underlying modalities. Consequently, the proposed framework does not rely on any prior knowledge of modalities in contrast with most existing methods. To substantiate the generic framework, we introduce a special case of c-CNN via incorporating the conditional routing of the decision tree, which is evaluated with two problems of multimodality - multi-view face identification and occluded face verification. Extensive experiments demonstrate consistent improvements over the counterparts unaware of modalities.
Observational Constraints on the Ages of Molecular Clouds and the Star Formation Timescale: Ambipolar-Diffusion-controlled or Turbulence-induced Star Formation?

We revisit the problem of the star formation timescale and the ages of molecular clouds. The apparent overabundance of star-forming molecular clouds over clouds without active star formation has been thought to indicate that molecular clouds are "short-lived" and that star formation is "rapid. " We show that this statistical argument lacks self-consistency and, even within the rapid star formation scenario, implies cloud lifetimes ≈10 Myr. We discuss additional observational evidence from external galaxies that indicate lifetimes of molecular clouds and a timescale of star formation of ≈107. These long cloud lifetimes, in conjunction with the rapid (≈1 Myr) decay of supersonic turbulence, present severe difficulties for the scenario of turbulence-controlled star formation. By contrast, we show that all 31 existing observations of objects for which the line width, the size, and the magnetic field strength have been reliably measured are in excellent quantitative agreement with the predictions of the ambipolar-diffusion theory. Within the ambipolar-diffusion-controlled star formation theory, the line widths may be attributed to large-scale nonradial cloud oscillations (essentially standing large-amplitude, long-wavelength Alfvén waves), and the predicted relation between the line width, the size, and the magnetic field is a natural consequence of magnetic support of self-gravitating clouds.
Understanding Soft Skills Requirements for Mobile Applications Developers

The development of smart phone software industry has brought high demands for mobile developers. The skills of developers have a great influence on the quality of software product and the success of software projects. It is necessary to examine what soft skills are important for mobile applications development while it remains unknown. In this article, based on related mobile application development advertisements, we obtained a classification of soft skills requirements of mobile developers, which includes 13 categories, by text mining (word segmentation, similarity calculation and clustering analysis). We also compared our results with that for traditional software development. Communication and teamwork are considered the most important two skills under both of two development fields. However, mobile developers should have a stronger ability of fast learning. Additionally, mobile developers should pay attention to four soft skills (responsibility, initiative in meeting challenging work, positive attitude to work and coding habit) that have not identified before.
Supplementation with vitamin D3 during pregnancy protects against lipopolysaccharide-induced neural tube defects through improving placental folate transportation.

Several reports demonstrated that maternal lipopolysaccharide (LPS) exposure at middle gestational stage caused neural tube defects (NTDs). This study investigated the effects of supplementation with vitamin D3 (VitD3) during pregnancy on LPS-induced NTDs. Pregnant mice except controls were ip injected with LPS (25 μg/kg) daily from gestational day (GD)8 to GD12. In LPS+VitD3 group, pregnant mice were orally administered with VitD3 (25 μg/kg) before LPS injection. As expected, a 5-day LPS injection resulted in 62.5% (10/16) of dams and 20.3% of fetuses with NTDs. Additional experiment showed that a 5-day LPS injection downregulated placental proton-coupled folate transporter (pcft) and reduced folate carrier 1 (rfc1), 2 major folate transporters in placentas. Consistent with downregulation of placental folate transporters, folate transport from maternal circulation into embryos was disturbed in LPS-treated mice. Interestingly, VitD3 not only inhibited placental inflammation but also attenuated LPS-induced downregulation of placental folate transporters. Correspondingly, VitD3 markedly improved folate transport from maternal circulation into the embryos. Importantly, supplementation with VitD3 during pregnancy protected mice from LPS-induced NTDs. Taken together, these results suggest that supplementation with VitD3 during pregnancy prevents LPS-induced NTDs through inhibiting placental inflammation and improving folate transport from maternal circulation into the embryos.
Associations between body mass index and serum levels of C-reactive protein

C-reactive protein (CRP) (an acute phase protein) has been thought to be synthesised in the liver, with a plasma half-life of 18 hours.1 However, the extrahepatic expression of CRP has been detected in macrophages and smooth-muscle cells from atherosclerotic plaques.2 It plays an important role in the inflammatory process and is recognised as a useful biochemical marker of inflammation. Increasing epidemiological evidence supports the notion that low-grade inflammation, as reflected by elevated levels of CRP, is associated with glucose intolerance3 and various vascular diseases4-7 including atherosclerosis, stroke, ischaemic heart disease, and peripheral vascular disease. Evidence-based systemic reviews have suggested that elevated CRP is related to an increased risk of stroke and cognitive impairment.8 There is evidence for the presence of CRP in human adipose tissue9,10 and growing evidence that adipose tissue can induce chronic low-grade inflammation by producing proinflammatory cytokines such as interleukin-6.11 Overweight or obese individuals have an increased risk of developing cardiovascular diseases12 and insulin resistance.13 A certain degree of inflammatory process in subjects with obesity could be suspected, but data examining the direct association between body mass index (BMI) and CRP is sparse. This study aimed to evaluate whether higher BMI and central obesity are associated with low-grade systemic inflammation as measured by serum CRP levels, using data from the National Health and Nutrition Examination Survey (NHANES), 1999 2002.
How many degrees of freedom can be achieved for mutually interfering MIMO broadcast channels?

In this paper, we consider homogeneous mutually interfering multiple-input multiple-output broadcast channels(MI-MIMO-BC). It is investigated that maximally achievable spatial degrees of freedom(DoF) for MI-MIMO-BC with constant channel coefficients. Assuming that there are two base station(BS) M transmit antennas, and each mobile stations(MS) has N receive antennas, it is shown that maximally min(M + N − 1, 2M) DoF can be achieved. We formulate zero intra- and inter-cell interference equations as function of the precoders and decoders. By checking solvability of these equations as multivariate polynomial equations, an achievable DoF upper bound can be obtained. To achieve the DoF upper bound, at least M + N − 1 MSs in each cell when M + N is an even number or equation MSs when M + N is an odd number are required. Our analysis is verified by numerical results.
Performance of case definitions used for influenza surveillance among hospitalized patients in a rural area of India.

OBJECTIVE To assess case definitions for influenza in a rural community in India. METHODS Residents of the study area who were hospitalized for any acute medical condition for at least one night between May 2009 and April 2011 were enrolled. Respiratory specimens were collected and tested for influenza viruses in a reverse-transcription polymerase chain reaction (PCR). The PCR results were taken as the "gold standard" in evaluating the performance of several case definitions. FINDINGS Of the 3179 patients included in the final analysis, 21% (665) were PCR-positive for influenza virus, 96% reported fever and 4% reported shortness of breath. The World Health Organization (WHO) case definition for severe acute respiratory illness had a sensitivity of 11% among patients aged < 5 years and of 3% among older patients. When shortness of breath was excluded from the definition, sensitivities increased (to 69% and 70%, respectively) and corresponding specificities of 43% and 53% were recorded. Among patients aged ≥ 5 years, WHO's definition of a case of influenza-like illness had a sensitivity of 70% and a specificity of 53%. The addition of "cough and reported or measured fever" increased sensitivity to 80% but decreased specificity to 42%. CONCLUSION The inclusion of shortness of breath in WHO's case definition for severe acute respiratory illness may grossly underestimate the burden posed by influenza in hospitals. The exclusion of shortness of breath from this definition or, alternatively, the inclusion of "cough and measured or reported fever" may improve estimates of the burden.
On Synchronizability of Kleinberg Small World Networks

In this paper, the impact of edge-adding probability on both synchronizability and average path length of Klein berg small world networks is investigated. It could be seen from the analysis that two dimensional Klein berg small world networks have similar properties as NW small world networks but Klein berg small world network is more general, that is, the synchronizability becomes stronger as the edge-adding probability increases. Moreover, the average path length of Klein berg small world network decreases with the increasing edge-adding probability. And this phenomenon is verified by numerical simulations on a network of Lorenz oscillators. Then, it could be deduced from the phenomenon observed that compared with the small probabilities of longer distance of the edge-adding, the large probabilities of shorter distance of the edge-adding could achieve better synchronizability. This means the probabilities of the edge-adding play more important than the length of edge-adding to enhance the synchronizability of the small world network.
Multi-Locus Sequence Typing of Bartonella henselae Isolates from Three Continents Reveals Hypervirulent and Feline-Associated Clones

Bartonella henselae is a zoonotic pathogen and the causative agent of cat scratch disease and a variety of other disease manifestations in humans. Previous investigations have suggested that a limited subset of B. henselae isolates may be associated with human disease. In the present study, 182 human and feline B. henselae isolates from Europe, North America and Australia were analysed by multi-locus sequence typing (MLST) to detect any associations between sequence type (ST), host species and geographical distribution of the isolates. A total of 14 sequence types were detected, but over 66% (16/24) of the isolates recovered from human disease corresponded to a single genotype, ST1, and this type was detected in all three continents. In contrast, 27.2% (43/158) of the feline isolates corresponded to ST7, but this ST was not recovered from humans and was restricted to Europe. The difference in host association of STs 1 (human) and 7 (feline) was statistically significant (P≤0.001). eBURST analysis assigned the 14 STs to three clonal lineages, which contained two or more STs, and a singleton comprising ST7. These groups were broadly consistent with a neighbour-joining tree, although splits decomposition analysis was indicative of a history of recombination. These data indicate that B. henselae lineages differ in their virulence properties for humans and contribute to a better understanding of the population structure of B. henselae.
Direct and indirect effects of paliperidone extended-release tablets on negative symptoms of schizophrenia

Direct and indirect effects of the new psychotropic paliperidone extended-release (paliperidone ER) tablets on negative symptom improvement in schizophrenia were investigated using path analysis. A post hoc analysis of pooled data from three 6-week, double-blind, placebo-controlled studies of paliperidone ER in patients experiencing acute exacerbation was conducted. Regression analysis explored relationships between baseline/study characteristics and negative symptoms. Change in Positive and Negative Syndrome Scale (PANSS) negative factor score at endpoint was the dependent variable; explanatory variables included demographic and clinical characteristics. Path analysis determined direct and indirect effects of treatment on negative symptom change. Indirect mediators of negative symptom change in the model included changes in positive symptoms, anxiety/depression symptoms and movement disorders. Path analysis indicated that up to 33% of negative symptom improvement was a direct treatment effect. Indirect effects on negative symptoms were mediated through changes in positive symptoms (51%) and anxiety/depression symptoms (18%), whereas changes in movement disorders had a 2.1% inverse effect. Path analysis indicated that paliperidone ER has a direct effect on negative symptoms. Negative symptom improvement also was indirectly mediated via changes in positive and depressive symptoms.
Tensor Networks : Deep Learning and Logical Reasoning from Data and Knowledge ⋆

We proposereal logic: a uniform framework for integrating automatic learning and reasoning. Real logic is defined on a full first-o der language where formulas have truth-value in the interval [0,1] and semanti cs defined concretely on the domain of real numbers. Logical constants are interpr eted as (feature) vectors of real numbers. Real logic promotes a well-founded int egration of deductive reasoning on knowledge-bases with efficient, data-dri ven relational machine learning. We show how Real Logic can be implemented in deep Te nsor Neural Networks with the use of Google’s T ENSORFLOW primitives. The paper concludes with experiments on a simple but representative exam ple of knowledge completion.
Connection Between the Passivity Index and Conic Systems

This report covers open-loop conditions that guarantee closed-loop stability of a feedback interconnection of two systems. The traditional solutions for this problem are passivity theory and the small gain theorem. These approaches can be shown to be part of a larger design framework. Two such larger frameworks are the conic systems framework and the passivity index framework. This report shows that these two actually reduce to the same open-loop conditions on the two systems in the interconnection. This connection is shown for the purpose of applying this generalized framework to switched systems. The recent application of passivity to switched systems gives one method of guaranteeing that the feedback interconnection of two switched systems is stable. However, a more general framework is presented in this report that is based on passivity theory but can show stability for the feedback interconnection of systems that aren’t necessarily passive or even stable.
Harmonic tracking using sequential monte carlo

This paper extends our previous work about individual frequencies detection and tracking to the extraction of harmonic components from multicomponent signals. Once harmonic components are detected, we study their time evolution applying statistical filtering to track them in the time-frequency plane. A nonlinear observation model based on spectrogram is defined and a state-of-the-art particle filtering algorithm is developed. Applications are mainly audio signals
Exploiting global priors for RGB-D saliency detection

Inspired by the effectiveness of global priors for 2D saliency analysis, this paper aims to explore those particular to RGB-D data. To this end, we propose two priors, which are the normalized depth prior and the global-context surface orientation prior, and formulate them in the forms simple for computation. A two-stage RGB-D salient object detection framework is presented. It first integrates the region contrast, together with the background, depth, and orientation priors to achieve a saliency map. Then, a saliency restoration scheme is proposed, which integrates the PageRank algorithm for sampling high confident regions and recovers saliency for those ambiguous. The saliency map is thus reconstructed and refined globally. We conduct comparative experiments on two publicly available RGB-D datasets. Experimental results show that our approach consistently outperforms other state-of-the-art algorithms on both datasets.
Software piracy: A time-series Analysis

Software piracy is a global problem that costs businesses billions of dollars each year. This study presents the first time series analysis looking at what influences software piracy. It includes data for 85 countries associating economic, cultural, and temporal variables with national software piracy rates. Some of the variables included coincide with those in previous studies (GDP, collectivism and power indexes) while others are new to this study (time, high tech exports, IT expenditures). The results show that the aforementioned variables are significantly associated with software piracy rates and that more specific influences can be investigated by looking at breakpoints in GDP. This knowledge is important to several areas both within and outside academia such as future policy formation aimed at curbing software piracy, the creation of preventive and deterrent controls for software piracy, and future research of the phenomenon discussed.
H3 Domain of Syntaxin 1A Inhibits KATP Channels by Its Actions on the Sulfonylurea Receptor 1 Nucleotide-Binding Folds-1 and -2*

The ATP-sensitive potassium (KATP) channel in pancreatic islet beta cells consists of four pore-forming (Kir6.2) subunits and four regulatory sulfonylurea receptor (SUR1) subunits. In beta cells, the KATP channel links intracellular metabolism to the dynamic regulation of the cell membrane potential that triggers insulin secretion. Syntaxin 1A (Syn-1A) is a SNARE protein that not only plays a direct role in exocytosis, but also binds and modulates voltage-gated K+ and Ca2+ channels to fine tune exocytosis. We recently reported that wild type Syn-1A inhibits rat islet beta cell KATP channels and binds both nucleotide-binding folds (NBF-1 and NBF-2) of SUR1. However, wild type Syn-1A inhibition of rat islet beta cell KATP channels seems to be mediated primarily via NBF-1. During exocytosis, Syn-1A undergoes a conformational change from a closed form to an open form, which would fully expose its active domain, the C-terminal H3 domain. Here, we show that the constitutively open form Syn-1A mutant (L165A/E166A) has a similar affinity to NBF-1 and NBF-2 as wild type Syn-1A and was equally effective in inhibiting the KATP channels of rat pancreatic beta cells and a cell line (BA8) stably expressing SUR1/Kir6.2. Although dialysis of NBF-1 into BA8 and islet beta cells effectively blocked wild type and open form Syn-1A inhibition of the KATP current, NBF-2 was also effective in blocking the open form Syn-1A inhibition. This prompted us to examine the specific domains within Syn-1A that would mediate its action on the KATP channels. The C-terminal H3 domain of Syn-1A (Syn-1A-H3), but not the N-terminal HABC domain (Syn-1A-HABC), binds the SUR1 protein of BA8 cells, causing an inhibition of KATP currents, and this inhibition was mediated via both NBF-1 and NBF-2. It therefore appears that the H3 domain of Syn-1A is the putative domain, which binds SUR1, but its distinct actions on the NBFs may depend on the conformation of Syn-1A occurring during exocytosis.