Miracle-dz/UniFAR-FTUs huggingface dataset:
Does the Eye of the Beholder Construct Beauty? Contributions of Self-Efficacy Factors to Divergent Thinking Traits

The study initiated a project exploring a contribution of creative perception to creative behavior. This study investigated the factors in creative self-perception contributing to creative potential. Creative potential was operationalized as divergent thinking and measured by the Abbreviated Torrance Test for Adults. Creative self-perception was operationalized as creative self-efficacy and assessed by Khatena-Torrance Creative Perception Inventory. Undergraduate college students’ creative self-efficacy was found to make a reliable and measurable contribution to their divergent thinking performance. Specifically, fluency was predicted by initiative and intellectuality, originality—by initiative, and flexibility—by environmental sensitivity and self-strength. These findings suggested that in addition to process, product, person, place, persuasion, and potential perspectives, creativity construct could be evaluated from a standpoint of creative perception.
Hand motion identification of grasp-and-lift task from electroencephalography recordings using recurrent neural networks

People who suffer from neuromuscular disorders and amputated limbs require prosthetic devices that are maneuvered through brain computer interfaces. Electroencephalography is a method to record the activity of the brain that is used for inputs for a brain computer interface. In this paper we propose a method for predicting hand motion phases in grasp-and-lift task from electroencephalography recordings using recurrent networks. Various architectures of recurrent neural networks are compared in terms of performance. For consistent prediction, moving average is applied.
Uniform stability analysis for time-varying systems applying homogeneity

The uniform stability notion for a class of nonlinear time-varying systems is studied using the homogeneity framework. It is assumed that the system is weighted homogeneous considering the time variable as a constant parameter, then several conditions of uniform stability for such a class of systems are formulated. The results are applied to the problem of adaptive estimation for a linear system.
Measuring the Effectiveness of Mentoring as a Knowledge Translation Intervention for Implementing Empirical Evidence: A Systematic Review

Background Mentoring as a knowledge translation (KT) intervention uses social influence among healthcare professionals to increase use of evidence in clinical practice. Aim To determine the effectiveness of mentoring as a KT intervention designed to increase healthcare professionals’ use of evidence in clinical practice. Methods A systematic review was conducted using electronic databases (i.e., MEDLINE, CINAHL), grey literature, and hand searching. Eligible studies evaluated mentoring of healthcare professionals responsible for patient care to enhance the uptake of evidence into practice. Mentoring is defined as (a) a mentor more experienced than mentee; (b) individualized support based on mentee's needs; and (c) involved in an interpersonal relationship as indicated by mutual benefit, engagement, and commitment. Two reviewers independently screened citations for eligibility, extracted data, and appraised quality of studies. Data were analyzed descriptively. Results Of 10,669 citations from 1988 to 2012, 10 studies were eligible. Mentoring as a KT intervention was evaluated in Canada, USA, and Australia. Exposure to mentoring compared to no mentoring improved some behavioral outcomes (one study). Compared to controls or other multifaceted interventions, multifaceted interventions with mentoring improved practitioners’ knowledge (four of five studies), beliefs (four of six studies), and impact on organizational outcomes (three of four studies). There were mixed findings for changes in professionals’ behaviors and impact on practitioners’ and patients’ outcomes: some outcomes improved, while others showed no difference. Linking Evidence to Action Only one study evaluated the effectiveness of mentoring alone as a KT intervention and showed improvement in some behavioral outcomes. The other nine studies that evaluated the effectiveness of mentoring as part of a multifaceted intervention showed mixed findings, making it difficult to determine the added effect of mentoring. Further research is needed to identify effective mentoring as a KT intervention.
Context-specific miRNA regulation network predicts cancer prognosis

MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context).
Ergodic properties of polygonal billiards with strongly contracting reflection laws

We consider convex polygonal billiards with a reflection law that contracts the reflection angle towards the normal. Polygonal billiards with orthogonal reflections are called slap maps. For polygons without parallel sides facing each other, the slap map has a finite number of ergodic absolutely continuous invariant probability measures. We show that any billiard with a strongly contracting reflection law has the same number of ergodic SRB measures with the same mixing periods as the ergodic absolutely continuous invariant probabilities of its corresponding slap map. The case of billiards in regular polygons and triangles is studied in detail.
Interactive Reservoir Geomodelling from Uncertainty

Summary Constructing structurally complex reservoir models at the appraisal stage is a complex task, with a high-degree of uncertainty. The lack of an intuitive set of modeling and visualization tools that support expert visual interpretation from geophysicists and geologists significantly increases the challenge. We present a set of interactive software tools to reservoir modeling in the appraisal stage. Our project use sketch-based modeling tools to allow the users to guide the model process with his/her expertise intuitively and quickly. We propose two different approaches that depend on the input data. The first approach is to create “what if” scenarios and start with no data or sparse data. The second one is to edit horizons which will form the horizon and fault network, and start using the seismic volume and a pre-extracted horizon.
Agent-Based Control for Object Manipulation with Modular Self-reconfigurable Robots

We demonstrate multiagent control of modular self-reconfigurable (MSR) robots for object manipulation tasks and show how it provides a useful programming abstraction. Such robots consist of many modules that can move relative to each other and change their connectivity, thereby changing the robot's overall shape to suit different tasks. We illustrate this approach through simulation experiments of the TeleCube MSR robot system.
Prevalence of type 2 diabetes mellitus among inland residents in China (2000–2014): A meta‐analysis

Besides the aging population in China, the following have become serious public health problems: increasing urban population, lifestyle changes and diabetes. We assessed the epidemiology of type 2 diabetes mellitus in China between 2000 and 2014, and analyzed time trends to better determine the prevalence status of diabetes in China and to provide a basis for prevention and decision‐making.
Increased Expression of Forkhead Box M1 Is Associated with Aggressive Phenotype and Poor Prognosis in Estrogen Receptor-Positive Breast Cancer

Fox transcription factors play a critical role in the regulation of a variety of biological processes. While FoxM1 behaves like the oncogenic transcription factor, FoxO3a is known as a tumor suppressor by inhibiting FoxM1. This study aimed to investigate the clinicopathological significance of FoxM1 and FoxO3a expression in breast cancer. Expression of FoxM1 and FoxO3a were analyzed by immunohistochemical staining on tissue microarray sections from 236 breast cancer patients, and correlated with various clinicopathological characteristics. Overexpression of FoxM1 correlated with adverse clinicopathological features, such as larger tumor size, lymph node metastasis, advanced tumor stage, and lymphovascular invasion. The Kaplan-Meier survival curves revealed no prognostic significance of FoxM1 expression. However, in subgroup analyses with patients of estrogen receptor (ER) positive breast cancers, FoxM1 overexpression associated with poor disease free and overall survival. No association was found between FoxO3a and FoxM1 expression. Regarding clinicopathological variables, the only association between histologic grade and FoxO3a was observed. In conclusion, FoxM1 overexpression was significantly associated with aggressive phenotypes and poor prognosis of ER-positive breast cancer. These findings suggest the possible role of FoxM1 as a prognostic biomarker and putative target of anti-cancer therapy. Graphical Abstract
Endocrine responses to short-term feed deprivation in weanling pigs.

The study objective was to assess endocrine and tIssue responses to feed deprivation in weaned pigs. In experiment 1, eight crossbred castrated male pigs were either fed on a continual basis (CON; n=4) or were feed deprived for 24 h and then re-fed until 30 h (FD; n=4). Relative serum concentrations of ghrelin tended to be lower in FD pigs at 12 h (P=0.08) when compared with CON pigs, but was higher at 24 h and 30 h compared with 12 h (P<0.05). Serum IGF-I was lower in FD pigs from 12 to 30 h as compared with CON pigs (P<0.05) and increased following re-feeding (P<0.06). Experiment 2 consisted of 32 pigs that were either fed for 72 or 96 h (CON72 and CON96; n=16), feed deprived for 72 h (FD72; n=8), or FD72 and then re-fed from 72-96 h (FD72/RF24; n=8). Ghrelin in the FD72 and FD72/RF24 groups was lower at 12 h (P<0.03) compared with CON pigs, but then increased from 12 h to 36 h (P<0.01). Serum IGF-I and leptin decreased following feed deprivation (P<0.001) and remained low until re-feeding. Cortisol was elevated from 12 h to 72 h during feed deprivation (P<0.01) but was not different from CON96 pigs following refeeding (P>0.88). Expression of ghrelin mRNA tended to be lower in the FD72 pigs' stomachs, pituitary glands, and hypothalami (P=0.06, 0.07, and 0.08 respectively) compared with CON pigs. These results provide evidence that feed deprivation is accompanied by multiple changes in the endocrine and neuroendocrine axis which influences feed intake, somatotropic response, and hypothalamic-pituitary-adrenal axis hormone concentrations.
A combined index of structure and function for staging glaucomatous damage.

OBJECTIVES To present and evaluate a new combined index of structure and function (CSFI) for staging and detecting glaucomatous damage. METHODS Observational study including 333 glaucomatous eyes (295 with perimetric glaucoma and 38 with preperimetric glaucoma) and 330 eyes of healthy subjects. All the eyes were tested with standard automated perimetry and spectral domain optical coherence tomography within 6 months. Estimates of the number of retinal ganglion cells (RGCs) were obtained from standardautomated perimetry and spectral domain optical coherence tomography and a weighted averaging scheme was used to obtain a final estimate of the number of RGCs for each eye. The CSFI was calculated as the percent loss of RGCs obtained by subtracting estimated from expected RGC numbers. The performance of the CSFI for discriminating glaucoma from normal eyes and the different stages of disease was evaluated by receiver operating characteristic curves. RESULTS The mean CSFI, representing the mean estimated percent loss of RGCs, was 41% and 17% in the perimetric and preperimetric groups, respectively (P.001). They were both significantly higher than the mean CSFI in the healthy group (P.001). The CSFI had larger receiver operating characteristic curve areas than isolated indexes of structure and function for detecting perimetric and preperimetric glaucoma and differentiating among early, moderate, and advanced stages of visual field loss. CONCLUSION An index combining structure and function performed better than isolated structural and functional measures for detection of perimetric and preperimetric glaucoma as well as for discriminating different stages of the disease.
Finite-Sample Analysis of LSTD

In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-difference (LSTD) learning algorithm. We report a finite-sample analysis of LSTD. We first derive a bound on the performance of the LSTD solution evaluated at the states generated by the Markov chain and used by the algorithm to learn an estimate of the value function. This result is general in the sense that no assumption is made on the existence of a stationary distribution for the Markov chain. We then derive generalization bounds in the case when the Markov chain possesses a stationary distribution and is β-mixing.
Recent Progress in Modelling Deterioration of Reinforced Concrete Structures

The main purpose of this paper is to give an overview of some recent progress made in modelling of deterioration of reinforced concrete structures. The review is not claimed to be complete. It is based on some of the author’s contributions in this research area especially the papers Thoft-Christensen [1] and Thoft-Christensen, Svensson & Frandsen [2]. In the paper, corrosion of reinforced concrete structures is discussed from the point of view of corrosion products. The different types of corrosion products are presented and the important diffusion coefficient is discussed. Modelling of corrosion initiation, corrosion propagation, corrosion cracking and corrosion crack opening is presented.
Enhancing physicality in touch interaction with programmable friction

Touch interactions have refreshed some of the 'glowing enthusiasm' of thirty years ago for direct manipulation interfaces. However, today's touch technologies, whose interactions are supported by graphics, sounds or crude clicks, have a tactile sameness and gaps in usability. We use a Large Area Tactile Pattern Display (LATPaD) to examine design possibilities and outcomes when touch interactions are enhanced with variable surface friction. In a series of four studies, we first confirm that variable friction gives significant performance advantages in low-level targeting activities. We then explore the design space of variable friction interface controls and assess user reactions. Most importantly, we demonstrate that variable friction can have a positive impact on the enjoyment, engagement and sense of realism experienced by users of touch interfaces.
GaBoDS: the Garching-Bonn Deep Survey. III. Lyman-break galaxies in the Chandra Deep Field South

We present first results of our search for high-redshift galaxies in deep CCD mosaic images. As a pilot study for a larger survey, very deep images of the Chandra Deep Field South (CDFS), taken with WFI@MPG/ESO2.2m, are used to select large samples of 1070 U-band and 565 B-band dropouts with the Lyman-break method. The data of these Lyman-break galaxies are made public as an electronic table. These objects are good candidates for galaxies at z ∼ 3a ndz ∼ 4 which is supported by their photometric redshifts. The distributions of apparent magnitudes and the clustering properties of the two populations are analysed, and they show good agreement to earlier studies. We see no evolution in the comoving clustering scale length from z ∼ 3t oz ∼ 4. The techniques presented here will be applied to a much larger sample of U-dropouts from the whole survey in near future.
Socio-economic factors Affected the Recent Fertility Decline in Iran and Some Comparison with other MENA Countries

Human fertility has declined in all of the Middle East and North African (MENA) countries in the recent years, Iran had the largest decline, however. What factors have affected the fertility decline in Iran, and as compared with other MENA countries, is the question of this paper. Fertility, higher education, and other measures were used for comparison. Regression analysis was also carried out to estimate the effects of education on fertility decline in Iran. Estimated results showed that education and women’s age of marriage reduce fertility that is consistent with other studies. The results of this study should be used with cautious.
An axiomatic definition of divergence for intuitionistic fuzzy sets

An axiomatic definition of divergence measure for intuitionistic fuzzy sets (IFSs, for short) is presented in this work, as a particular case of dissimilarity between IFSs. As the concept of divergence measure is more restrictive, it has particular properties which are studied. Furthermore, the relationships among IF-divergences, dissimilarities and distances are studied. We also provide some methods for building divergence measure for IFSs. They will allow us to conclude this work with a classification of the usual functions used in the literature for measuring the dierence between intuitionistic fuzzy sets in two classes: which are divergence measures between IFSs and which are not.
DNA polymorphisms in the ACE gene, serum ACE activity and the risk of nephropathy in insulin-dependent diabetes mellitus.

BACKGROUND To determine the relationship between DNA polymorphisms in the angiotensin I converting enzyme (ACE) gene, serum ACE activity and the risk of diabetic nephropathy. METHODS A case-control study was carried out in a population of Jewish insulin-dependent diabetes mellitus (IDDM) patients. Cases (77 IDDM patients with diabetic nephropathy) and controls (89 IDDM patients with normoalbuminuria) were genotyped with PCR protocols for detecting two DNA polymorphisms in the ACE gene: one in intron 7 detected with the restriction enzyme PstI and the other in intron 16 identified as an insertion/deletion (I/D). RESULTS The risk of nephropathy was increased only in patients homozygous for the allele with the PstI site. These homozygotes had a nephropathy risk that was 2.3 times (95% C.I.: 1.2-4.5) that of the other genotypes. Furthermore, these individuals did not have elevated serum ACE activity. CONCLUSIONS The results of this study are evidence that the risk of diabetic nephropathy in IDDM is influenced by genetic variability at the ACE locus, but the responsible variant is not the I/D polymorphism in intron 16. Our findings require further studies in other populations.
Protein Function Prediction with Incomplete Annotations

Automated protein function prediction is one of the grand challenges in computational biology. Multi-label learning is widely used to predict functions of proteins. Most of multi-label learning methods make prediction for unlabeled proteins under the assumption that the labeled proteins are completely annotated, i.e., without any missing functions. However, in practice, we may have a subset of the ground-truth functions for a protein, and whether the protein has other functions is unknown. To predict protein functions with incomplete annotations, we propose a Protein Function Prediction method with Weak-label Learning (ProWL) and its variant ProWL-IF. Both ProWL and ProWL-IF can replenish the missing functions of proteins. In addition, ProWL-IF makes use of the knowledge that a protein cannot have certain functions, which can further boost the performance of protein function prediction. Our experimental results on protein-protein interaction networks and gene expression benchmarks validate the effectiveness of both ProWL and ProWL-IF.
DISCOUNTING AND AUGMENTATION OF DISPOSITIONAL AND CAUSAL ATTRIBUTIONS

This article investigates whether and how discounting and augmentation of dispositional and causal attributions differ between each other. In three experiments, the strength of a causal or dispositional attribution to a target actor (or object) was varied by manipulating the number of observations (i.e., sample size) of an alternative actor (or object). The results of Experiments 1 and 2 indicated that a greater sample size of the alternative actor (or object) resulted in greater discounting or augmentation of the target, and that this effect was alike for causal and dispositional attributions. This effect of sample size on discounting and augmentation cannot be explained by current algebraic attribution models, but is consistent with predictions from a connectionist framework. In Experiment 3, the extraction of information was made more difficult, and the effect of sample size on discounting and augmentation remained robust for causal attributions, whereas it disappeared for dispositional attributions. This failure for dispositional attributions was not predicted by any theoretical model. The discussion focuses on some potential explanations for this unexpected finding.
Fostering Authentic Problem Seeking: A Step Toward Social Justice Engagement

Because of these learners’ potential as future leaders, it is imperative that educators develop gifted students’ ability to identify and solve complex social justice problems. Nourishing students’ affective traits, including empathy for others, understanding of themselves, and the ability to connect to others in local and global society, will help students to recognize and seek out authentic problems. This article examines the nuances around the creative problem-solving process and how educators can infuse the curriculum with opportunities to develop and strengthen the skills students need to become engaged, real-world problem seekers, as we call it, and problem solvers. Through the combination of social justice issues and creative problem seeking, students can be motivated to engage with the community and promote positive change in the world.
Support Vector Machines in High Energy Physics

This lecture will introduce the Support Vector algorithms for classification and regression. They are an application of the so called kernel trick, which allows the extension of a certain class of linear algorithms to the non linear case. The kernel trick will be introduced and in the context of structural risk minimization, large margin algorithms for classification and regression will be presented. Current applications in high energy physics will be discussed.