Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Nursing Students Handwashing Knowledge, Beliefs, and Attitudes on Their Handwashing Compliance

Information regarding current status of handwashing knowledge, beliefs, attitudes and compliance with handwashing practice in nursing students in Jordan is limited. This study aims to explore handwashing knowledge, beliefs, attitudes, and self-reported compliance and to examine significant variables predicting compliance with handwashing practice among nursing students. The study used a cross-sectional survey design. Results found a statistically significant relationship between nursing students’ handwashing compliance and their handwashing knowledge, attitudes, and beliefs (r = 0.68, 0.65, 0.58, P < 0.05), respectively. Also, results revealed three statistically significant predictors. Namely, handwashing knowledge was the strongest predictor (β = 0.423, P = 0.000), followed by attitudes (β = 0.322, P = 0.000), and beliefs (β = 0.171, P = 0.027). Specific handwashing training courses integrated in nursing education curriculum are recommended. These courses need to consider nursing students’ handwashing attitudes and beliefs in conjunction with handwashing knowledge.
Pain and Emotion: Effects of Affective Picture Modulation

Objective and Methods Two experiments examined the impact of viewing unpleasant, pleasant, and neutral photographic slides on cold-pain perception in healthy men and women. In each experiment, participants viewed one of three slide shows (experiment 1 = fear, disgust, or neutral; experiment 2 = erotic, nurturant, or neutral) immediately before a cold-pressor task. Skin conductance and heart rate were recorded during the slide shows, whereas visual analog scale ratings of pain intensity and unpleasantness thresholds and pain tolerance were recorded during the cold-pressor task. Results Viewing fear and disgust slides decreased pain intensity and unpleasantness thresholds, but only the fear slides decreased pain tolerance. In contrast, viewing erotic, but not nurturant, slides increased pain intensity and unpleasantness threshold ratings on the visual analog scale in men, whereas neither nurturant nor erotic slides altered pain tolerance. Conclusions These results are consistent with a motivational priming model that predicts that unpleasant affective states should enhance pain and that pleasant affective states should attenuate it.
Dissipation via particle production in scalar field theories.

We study the nonequilibrium evolution of the expectation value of a scalar field in the broken and unbroken symmetry cases. We find that the particles produced by parametric amplification give rise to dissipative behavior for this mode. However, a {Gamma} {center_dot}{phi} type of term {ital cannot} account for the dissipational dynamics. We are able to show clearly that perturbation theory breaks down at late times, so that dissipation in field theories can only be understood nonperturbatively. When Goldstone bosons are present we find infrared divergences that require a nonperturbative resummation to describe the long-time dynamics. We use the Hartree factorization and the large {ital N} approximation to the O({ital N}) linear {sigma} model to numerically as well as analytically understand the long-time behavior of the zero mode as well as that of the produced particles. The O({ital N}) model case is extremely interesting since, in the spontaneously broken case, the radial mode dissipates all of its energy into production of long-wavelength Goldstone modes. The minima of the effective action (determined by the final value of the expectation value of the scalar field) depend on the initial conditions.
VLBA DETERMINATION OF THE DISTANCE TO NEARBY STAR-FORMING REGIONS. III. HP TAU/G2 AND THE THREE-DIMENSIONAL STRUCTURE OF TAURUS

Using multiepoch Very Long Baseline Array (VLBA) observations, we have measured the trigonometric parallax of the weak-line T Tauri star HP Tau/G2 in Taurus. The best fit yields a distance of 161.2 ± 0.9 pc, suggesting that the eastern portion of Taurus (where HP Tau/G2 is located) corresponds to the far side of the complex. Previous VLBA observations have shown that T Tau, to the south of the complex, is at an intermediate distance of about 147 pc, whereas the region around L1495 corresponds to the near side at roughly 130 pc. Our observations of only four sources are still too coarse to enable a reliable determination of the three-dimensional structure of the entire Taurus star-forming complex. They do demonstrate, however, that VLBA observations of multiple sources in a given star-forming region have the potential not only to provide a very accurate estimate of its mean distance, but also to reveal its internal structure. The proper motion measurements obtained simultaneously with the parallax allowed us to study the kinematics of the young stars in Taurus. Combining the four observations available so far, we estimate the peculiar velocity of Taurus to be about 10.6 km s−1 almost completely in a direction parallel to the Galactic plane. Using our improved distance measurement, we have refined the determination of the position on the H–R diagram of HP Tau/G2, and of two other members of the HP Tau group (HP Tau itself and HP Tau/G3). Most pre-main-sequence evolutionary models predict significantly discrepant ages (by 5 Myr) for those three stars—expected to be coeval. Only in the models of Palla & Stahler do they fall on a single isochrone (at 3 Myr).
Review On Expectancy Disconfirmation Theory (EDT) Model In B2C E-Commerce

This study focuses on a review of “Expectancy Disconfirmation Theory” (EDT) as a famous theory in measuring customer’s satisfaction. In today’s competitive e-marketplace, e-businesses that determine an efficient strategic think behind their e-commerce activities involve designing a qualified website and presenting good quality of products and services will be more successful in attracting customer satisfaction. These points emphasize on the importance of attracting customer’s satisfaction for the vita of e-businesses. That’s why measuring customer’s satisfaction by an empowerment tool that has ability to cover and make relationship among all concepts that are explained above is imperative. “Expectancy Disconfirmation Theory” (EDT) which is defined as an theory for measuring customer satisfaction from perceived quality of products or services is reviewed in this research for measuring customers satisfaction. Evolution of “EDT” shown this theory is able to measure quality of services and information which provided by B2C E-commerce from customer’s point of view. Moreover, review on EDT measurement methods and their strengths and weaknesses in accuracy of the results shown that Additive Difference Model (ADM) and Direct Effects Model (DEM) worked well across both standards involve customer‘s expectation and desire. Between DEM and ADM methods, when managers need information about desires and expectations DEM appears to be a good choice but it does not provide a distinct measure of the disconfirmation of customer‘s expectation and desire. In versus ADM provide a distinct measure of the disconfirmation of customer‘s expectation and desire. That’s why it is concerned by managerial issues.
Light Element Depletion in Contracting Brown Dwarfs and Pre-Main-Sequence Stars

We present an analytic calculation of the thermonuclear depletion of the light elements lithium, beryllium, and boron in fully convective, low-mass stars. Under the presumption that the pre-main-sequence star is always fully mixed during contraction, we find that the burning of these rare light elements can be computed analytically, even when the star is degenerate. Using the effective temperature as a free parameter, we constrain the properties of low-mass stars from observational data, independently of the uncertainties associated with modeling their atmospheres and convection. Our results are in excellent agreement with the detailed calculations of D'Antona & Mazzitelli and Chabrier, Baraffe, & Plez. Our analytic solution explains the dependence of the age at a given level of elemental depletion on the stellar effective temperature, nuclear cross sections, and chemical composition. These results are also useful as benchmarks to those constructing full stellar models. Most importantly, our results allow observers to translate lithium nondetections in young cluster members into a model-independent minimum age for that cluster. Using this procedure, we have found lower limits to the ages of the Pleiades (100 Myr) and Alpha Persei (60 Myr) clusters. Dating an open cluster using low-mass stars is also independent of techniques that fit upper main-sequence evolution. Comparison of these methods provides crucial information on the amount of convective overshooting (or rotationally induced mixing) that occurs during core hydrogen burning in the 5-10 M☉ stars typically at the main-sequence turnoff for these clusters. We also discuss beryllium depletion in pre-main-sequence stars. Recent experimental work on the low-energy resonance in the 10B(p, α)7Be reaction has greatly enhanced estimates of the destruction rate of 10B, making it possible for stars with M ≳ 0.1 M☉ to deplete both 10B and 11B before reaching the main sequence. Moreover, there is an interesting range of masses, 0.085 M☉ ≲ M ≲ 0.13 M☉, where boron depletion occurs on the main sequence in less than a Hubble time, providing a potential "clock" for dating low-mass stars.
MicroRNA-590 is an EMT-suppressive microRNA involved in the TGFβ signaling pathway

Over the last few decades, the epithelial-to-mesenchymal transition (EMT) has been identified as being involved in a number of aspects of physiological processes and various pathological events, including embryonic development and renal fibrosis. Transforming growth factor-β receptor 2 (TGFβR2) is a widely studied gene, which fulfils a vital role in the TGFβ signaling pathway and exerts a crucial function in the progression of EMT. Previous studies demonstrated that the dysregulation of microRNAs (miRNAs) is considered to be associated with the EMT process. However, the precise functional involvement of miRNAs in EMT remains to be fully elucidated. In the present study, the level of miR-590 was decreased in an EMT model in vitro and in vivo. Furthermore, the overexpression of miR-590 inhibited EMT by upregulating the epithelial marker, E-cadherin, and downregulating the mesenchymal markers, laminin, α-smooth muscle actin (α-SMA) and collagen, in the human kidney 2 (HK2) cell line. Furthermore, TGFβR2 was negatively regulated by miR-590. In addition, performing a knockdown of TGFβR2 with small-interfering RNA had an effect similar to miR-590 on EMT in the HK2 cell line, whereas the transfection of pCMV-tag2B-TGFβR2 reversed the effect of miR-590 on EMT in HK2 cells. Taken together, the present study demonstrated that miR-590 is a novel EMT-suppressive microRNA, which targets TGFβR2.
Identification of Sparse Linear Operators

We consider the problem of identifying a linear deterministic operator from its response to a given probing signal. For a large class of linear operators, we show that stable identifiability is possible if the total support area of the operator's spreading function satisfies Δ ≤ 1/2. This result holds for an arbitrary (possibly fragmented) support region of the spreading function, does not impose limitations on the total extent of the support region, and, most importantly, does not require the support region to be known prior to identification. Furthermore, we prove that stable identifiability of almost all operators is possible if Δ <; 1. This result is surprising as it says that there is no penalty for not knowing the support region of the spreading function prior to identification. Algorithms that provably recover all operators with Δ ≤ 1/2, and almost all operators with Δ <; 1 are presented.
A Type-based Trace Analysis for Java

The intersection type discipline ( ITD) is a well established one in the field of the Lambda Calculus ( LC) and the functional programming paradigm. It has also been extended to Term Rewriting Systems ( TRS) and more recently to object calculi and sequent calculi. We continue this trend by applying the techniques o f ITD to the analysis of the (class based) object-oriented ( OO) programming paradigm: specifically, we study a small core calculus f or Java which is a restriction of Featherweight Java by removing cas ts, for which usingITD we define an intersection type system that traces method and field calls. Type assignment in this system is closed under reduction and expansion, allowing for a type-based semantics for program s. The main contribution of this paper is an approximation result f or this programming model, linking approximation semantics with t race semantics, which we achieve by defining a notion of reduction on type derivations that is strongly normalising (as for LC and TRS). This result demonstrates a direct correspondence between a trace semantics for programs and their types, and opens up the poss ibility of both abstract interpretation and detailed type-based an alyses for OO. We show how the approximation result facilitates one such analysis a characterisation of normalisation and termina tio . In order to demonstrate that our framework constitutes a pra ctical approach to program analysis, we define a restriction o f our type system which is essentially equivalent to Curry’s syst em for the Lambda Calculus (functional programming), and show tha t a principal typings property holds. We show that our system is expressive by giving an encoding of Combinatory Logic (and the reby, indirectly, the Lambda Calculus) into our calculus which pr eserves type assignment. The definition of principal typings for thi s system leads straightforwardly to a decidable type inference algo rithm, for which we have a reference implementation in ML.
An Effort Based Model of Software Usability

This paper presents a new effort based model for software usability and reports the results of a set of experiments performed to assess the validity of the model. The model is based on the notion that usability is an inverse function of effort. Physical and mental effort are obtained and inferred from logging physical activity and eye tracking. Using the new model, an objective metric of software usability that facilitates setting measurable requirements and enables the comparison of two or more implementations of the same application is developed. The experiments results show high correlation to learning theory models, strongly support the relationship of effort to usability and demonstrate that operability, learnability, and understandability of software systems can be measured using the effort based metric .
Hypertrophic Scarring and Keloids: Pathomechanisms and Current and Emerging Treatment Strategies

Excessive scars form as a result of aberrations of physiologic wound healing and may arise following any Insult to the deep dermis. By causing pain, pruritus and contractures, excessive scarring significantly affects the patient’s quality of life, both physically and psychologically. Multiple studies on hypertrophic scar and keloid formation have been conducted for decades and have led to a plethora of therapeutic strategies to prevent or attenuate excessive scar formation. However, most therapeutic approaches remain clinically unsatisfactory, most likely owing to poor understanding of the complex mechanisms underlying the processes of scarring and wound contraction. In this review we summarize the current understanding of the pathophysiology underlying keloid and hypertrophic scar formation and discuss established treatments and novel therapeutic strategies.
RDF2Rules: Learning Rules from RDF Knowledge Bases by Mining Frequent Predicate Cycles

Recently, several large-scale RDF knowledge bases have been built and applied in many knowledge-based applications. To further increase the number of facts in RDF knowledge bases, logic rules can be used to predict new facts based on the existing ones. Therefore, how to automatically learn reliable rules from large-scale knowledge bases becomes increasingly important. In this paper, we propose a novel rule learning approach named RDF2Rules for RDF knowledge bases. RDF2Rules first mines frequent predicate cycles (FPCs), a kind of interesting frequent patterns in knowledge bases, and then generates rules from the mined FPCs. Because each FPC can produce multiple rules, and effective pruning strategy is used in the process of mining FPCs, RDF2Rules works very efficiently. Another advantage of RDF2Rules is that it uses the entity type information when generates and evaluates rules, which makes the learned rules more accurate. Experiments show that our approach outperforms the compared approach in terms of both efficiency and accuracy.
Do scores on the HCR-20 and FAM predict frequency of self-harm in females within a secure psychiatric hospital?

Abstract The Historical, Clinical, and Risk Management scales (HCR-20) and the Female Additional Manual (FAM) are violence risk assessment tools. This study aimed to examine whether scores on the HCR-20 and FAM are related to frequency of self-harm. HCR-20 Version 3 and FAM scores and frequency of self-harm across the following year were examined for 89 female patients within a secure psychiatric hospital. The results showed that higher mean total scores on the HCR-20, and also on the Historical and Clinical scales were associated with more frequent self-harm, both with and without the FAM items. The Risk Management scale was not associated. Eight individual items were positively associated with self-harm, and one was negatively associated. The final risk judgement for self-destructive behaviour was also positively associated with self-harm. The HCR-20 and FAM are useful tools for assessing risk of self-harm, particularly the Historical and Clinical scales. However, not all items are independently associated with more frequent self-harm. Final risk judgements are also an accurate indicator of frequency of self-harm, and therefore the process of completing the HCR-20 and FAM may aid accurate self-harm risk assessment.
The weak magnetic field of the O9.7 supergiant ζ Orionis A

We report here the detection of a weak magnetic field of 50-100 G on the O9.7 supergiant ζ Orionis A (ζ Ori A), using spectropolarimetric observations obtained with NARVAL at the 2-m TBernard Lyot atop Pic du Midi (France). ζ Ori A is the third O star known to host a magnetic field (along with θ 1 Ori C and HD 191612), and the first detection on a 'normal' rapidly rotating O star. The magnetic field of ζ Ori A is the weakest magnetic field ever detected on a massive star. The measured field is lower than the thermal equipartition limit (about 100 G). By fitting non-local thermodynamic equilibrium (NLTE) model atmospheres to our spectra, we determined that ζ Ori A is a 40 Mstar with a radius of 25 Rand an age of about 5-6 Myr, showing no surface nitrogen enhancement and losing mass at a rate of about
Deep Neural Networks for Learning Graph Representations

In this paper, we propose a novel model for learning graph representations, which generates a low-dimensional vector representation for each vertex by capturing the graph structural information. Different from other previous research efforts, we adopt a random surfing model to capture graph structural information directly, instead of using the sampling-based method for generating linear sequences proposed by Perozzi et al. (2014). The advantages of our approach will be illustrated from both theorical and empirical perspectives. We also give a new perspective for the matrix factorization method proposed by Levy and Goldberg (2014), in which the pointwise mutual information (PMI) matrix is considered as an analytical solution to the objective function of the skip-gram model with negative sampling proposed by Mikolov et al. (2013). Unlike their approach which involves the use of the SVD for finding the low-dimensitonal projections from the PMI matrix, however, the stacked denoising autoencoder is introduced in our model to extract complex features and model non-linearities. To demonstrate the effectiveness of our model, we conduct experiments on clustering and visualization tasks, employing the learned vertex representations as features. Empirical results on datasets of varying sizes show that our model outperforms other stat-of-the-art models in such tasks.
MCPH1: a window into brain development and evolution

The development of the mammalian cerebral cortex involves a series of mechanisms: from patterning, progenitor cell proliferation and differentiation, to neuronal migration. Many factors influence the development of the cerebral cortex to its normal size and neuronal composition. Of these, the mechanisms that influence the proliferation and differentiation of neural progenitor cells are of particular interest, as they may have the greatest consequence on brain size, not only during development but also in evolution. In this context, causative genes of human autosomal recessive primary microcephaly, such as ASPM and MCPH1, are attractive candidates, as many of them show positive selection during primate evolution. MCPH1 causes microcephaly in mice and humans and is involved in a diverse array of molecular functions beyond brain development, including DNA repair and chromosome condensation. Positive selection of MCPH1 in the primate lineage has led to much insight and discussion of its role in brain size evolution. In this review, we will present an overview of MCPH1 from these multiple angles, and whilst its specific role in brain size regulation during development and evolution remain elusive, the pieces of the puzzle will be discussed with the aim of putting together the full picture of this fascinating gene.
The radio luminosity function from the low-frequency 3CRR, 6CE and 7CRS complete samples

We measure the radio luminosity function (RLF) of steep-spectrum radio sources using three redshift surveys of flux-limited samples selected at low (151 and 178 MHz) radio frequency, low-frequency source counts and the local RLF. The redshift surveys used are the new 7C Redshift Survey (7CRS) and the brighter 3CRR and 6CE surveys totalling 356 sources with virtually complete redshift z information. This yields unprecedented coverage of the radio luminosity versus z plane for steep-spectrum sources, and hence the most accurate measurements of the steep-spectrum RLF yet made. We find that a simple dual-population model for the RLF fits the data well, requiring differential density evolution (with z) for the two populations. The low-luminosity population can be associated with radio galaxies with weak emission lines, and includes sources with both FRI and FRII radio structures; its comoving space density ρ rises by about one dex between z∼0 and 1 but cannot yet be meaningfully constrained at higher redshifts. The high-luminosity population can be associated with radio galaxies and quasars with strong emission lines, and consists almost exclusively of sources with FRII radio structure; its ρ rises by nearly three dex between z∼0 and 2. These results mirror the situation seen in X-ray and optically selected samples of AGN where: (i) low-luminosity objects exhibit a gradual rise in ρ with z that crudely matches the rises seen in the rates of global star formation and galaxy mergers; and (ii) the density of high-luminosity objects rises much more dramatically. The integrated radio luminosity density of the combination of the two populations is controlled by the value of ρ at the low-luminosity end of the RLF of the high-luminosity population, a quantity which has been directly measured at z∼1 by the 7CRS. We argue that robust determination of this quantity at higher redshifts requires a new redshift survey based on a large (∼1000 source) sample about five times fainter than the 7CRS.