Miracle-dz/UniFAR-FTUs huggingface dataset:
Attributes that Predict which Features to Fix: Lessons for App Store Mining

Requirements engineering is assessed as the most important phase of the software development process. This process is especially challenging for app developers, who tend to gather crowd-based feedback after releasing their apps. This feedback is often voluminous, posing prioritization challenges for developers identifying features to fix or add. While previous work has identified frequently mentioned features, and some effort has been dedicated towards providing various prioritization and classification techniques, these do not quite address the prioritization challenge faced by app developers given voluminous app reviews. In fact, there is also need to assess the scale of app reviews' usefulness. We use content analysis and regression to contribute towards this cause by exploring the usefulness of app reviews, and the attributes that predict which app features to fix, respectively. Our outcomes show that reviews tended to either provide information of little value (i.e., no actionable information) or highlighted problems that may directly affect the functionality of app features. For two different apps, we also observe that features that were mentioned the most (the feature frequency attribute) in lower ranked reviews provided by users had the strongest predictive power for identifying severely broken features (as perceived by a developer). However, the ordering did not match with the frequency with which reports were made by users. There were also variances in the attributes that predict which features to fix, for the reviews of different apps. Review mining and prioritization challenges remain given variances in app reviews' content and structure. These findings also point to the need to redesign app review interfaces to consider how reviews are captured.
Effect Modification of Chronic Kidney Disease on the Association of Circulating and Imaging Cardiac Biomarkers With Outcomes

Background Cardiac troponin T and brain natriuretic peptide (BNP) are elevated in >50% of dialysis patients and are associated with poor outcomes. Few data investigated these associations in earlier chronic kidney disease (CKD). Methods and Results We studied whether CKD modified associations of elevated BNP, N‐terminal‐pro‐BNP, high‐sensitivity cardiac troponin T, coronary artery calcification, and left ventricular hypertrophy with all‐cause death and cardiovascular death/events in 3218 multiethnic individuals followed for 12.5 years, and whether biomarkers added prognostic information to traditional cardiovascular risk factors in CKD. Of the cohort, 279 (9%) had CKD. There were 296 deaths and 218 cardiovascular deaths/events. Of non‐CKD individuals, 7% died and 6% had cardiovascular death/event versus 32% and 30% of CKD participants, P<0.001 for both. The interaction between BNP and CKD on death was significant (P=0.01): the adjusted hazard ratio in CKD was 2.05, 95% CI (1.34, 3.14), but not significant in non‐CKD, 1.04 (0.76, 1.41). CKD modified the association of high‐sensitivity cardiac troponin T with cardiovascular death/event, adjusted hazard ratio 3.34 (1.56, 7.18) in CKD versus 1.65 (1.16, 2.35) in non‐CKD, interaction P=0.09. There was an interaction between N‐terminal‐pro‐BNP and CKD for death in those without prior cardiovascular disease. Addition of each biomarker to traditional risk factors improved risk prediction, except coronary artery calcification was not discriminatory for cardiovascular death/event in CKD. Conclusions Cardiac biomarkers, with the exception of coronary artery calcification, prognosticated outcomes in early‐stage CKD as well as, if not better than, in non‐CKD individuals, even after controlling for estimated glomerular filtration rate, and added to information obtained from traditional cardiovascular risk factors alone.
Factors of Interpersonal Behavior and Judgment in Social Groups

This study explored dimensions which are used to describe persons within closely-knit social groups. Ss in the group were similar in socio-economic status and used two independent dimensions in describing one another: another's positive and negative reinforcing quality. The sociometric questionnaire which yielded these two factors is a potentially useful device for characterizing an individual within any social organization according to a four-fold classification: positively and negatively reinforcing to others, positively but not negatively reinforcing to others, negatively but not positively reinforcing, and neither positively nor negatively reinforcing. Correlations among the sociometric measures, personality measures, and sex showed that males were less affiliative and were judged as more negatively reinforcing than females.
Learning Asynchronous-Time Information Diffusion Models and its Application to Behavioral Data Analysis over Social Networks

One of the interesting and important problems of information diffusion over a large social network is to identify an appropriate model from a limited amount of diffusion information. There are two contrasting approaches to model information diffusion: a push type model known as Independent Cascade (IC) model and a pull type model known as Linear Threshold (LT) model. We extend these two models (called AsIC and AsLT in this paper) to incorporate asynchronous time delay and investigate 1) how they differ from or similar to each other in terms of information diffusion, 2) whether the model itself is learnable or not from the observed information diffusion data, and 3) which model is more appropriate to explain for a particular topic (information) to diffuse/propagate. We first show there can be variations with respect to how the time delay is modeled, and derive the likelihood of the observed data being generated for each model. Using one particular time delay model, we show the model parameters are learnable from a limited amount of observation. We then propose a method based on predictive accuracy by which to select a model which better explains the observed data. Extensive evaluations were performed. We first show using synthetic data with the network structures taken from real networks that there are considerable behavioral differences between the AsIC and the AsLT models, the proposed methods accurately and stably learn the model parameters, and identify the correct diffusion model from a limited amount of observation data. We next apply these methods to behavioral analysis of topic propagation using the real blog propagation data, and show there is a clear indication as to which topic better follows which model although the results are rather insensitive to the model selected at the level of discussing how far and fast each topic propagates from the learned parameter values.
Sumatriptan Nasal Spray (20 Mg/Dose) in the Acute Treatment of Cluster Headache

Subcutaneous injection of sumatriptan is an effective treatment for attacks of cluster headache with a short onset of action. This open, randomized study evaluates whether sumatriptan nasal spray at its highest commercially available dose (20 mg/dose) is equally effective. In 26 patients, four consecutive attacks were treated alternately with nasal spray and subcutaneous injection. Treatment was given within 5 min of onset of pain, and the time interval for the start and completeness of pain relief, provided these occurred within 15 min of administration, were recorded by the patient. After completion of the study, the patients were also asked to indicate which treatment they preferred, based on efficacy, side effects, and handling of the preparation. Forty-nine of the 52 treatments with injection resulted in complete relief of pain within 15 min, with a mean of 9.6 min. The remaining three attacks were reduced by a mean of 86.7% at 15 min. Only 7 of the 52 treatments with nasal spray in the nostril ipsilateral to pain resulted in complete relief within this time period, with a mean of 13.0 min. In 18 of these treatments pain was reduced by a mean of 42.2% at 15 min, whereas no effect on pain was obtained at this time in the remaining 27 treatments. The effect was almost identical when the nasal spray was administered in the nostril on the non-painful side. As an overall judgement, only 2 of the 26 patients preferred nasal spray to injection. We conclude that sumatriptan nasal spray 20 mg/dose is less effective than subcutaneous injection in relieving pain in the great majority of cluster headache sufferers.
Fabrication and Analysis of 150-mm-Aperture Nb3Sn MQXF Coils

The U.S. LHC Accelerator Research Program (LARP) and CERN are combining efforts for the HiLumi-LHC upgrade to design and fabricate 150-mm-aperture interaction region quadrupoles with a nominal gradient of 130 T/m using Nb3Sn. To successfully produce the necessary long MQXF triplets, the HiLumi-LHC collaboration is systematically reducing risk and design modification by heavily relying upon the experience gained from the successful 120-mm-aperture LARP HQ program. First-generation MQXF short (MQXFS) coils were predominately a scaling up of the HQ quadrupole design, allowing comparable cable expansion during Nb3Sn formation heat treatment and increased insulation fraction for electrical robustness. A total of 13 first-generation MQXFS coils were fabricated between LARP and CERN. Systematic differences in coil size, coil alignment symmetry, and coil length contraction during heat treatment are observed and likely due to slight variances in tooling and insulation/cable systems. Analysis of coil cross sections indicate that field-shaping wedges and adjacent coil turns are systematically displaced from the nominal location and the cable is expanding less than nominally designed. A second-generation MQXF coil design seeks to correct the expansion and displacement discrepancies by increasing insulation and adding adjustable shims at the coil pole and midplanes to correct allowed magnetic field harmonics.
Promoting Entrepreneurship in the Welfare State

Entrepreneurship is largely ignored or treated in a highly simplified way in endogenous growth theory. Still, it is now widely recognized that the supply of entrepreneurial talent is likely to be important for economic growth, innovation and job creation. In this study we provide an in-depth examination of how the supply of productive entrepreneurship is likely to be affected by the kind of tax and welfare arrangements that may prevail in a mature welfare state. Sweden, allegedly the most extensive of all welfare states, is the object of the empirical analysis. It is argued that the Swedish welfare state early on chose a specific “Swedish Model” of trying to combine ambitious welfare programs and a high tax burden with good opportunities for economic growth. This particular view rested heavily on the assumption that innovative activity was best performed in large established firms and that entry of new firms was less important. Consequently, policy and institutions were geared to promoting certain types of activities which could deliver growth if scale economies are important and intrapreneurship can substitute for entrepreneurship. However, in an environment where entry, exit and turnover of firms are important for growth, and where scale-economies are less important, this kind of model may be more problematic. Both aggregate economic performance and data on firm growth and direct measures of entrepreneurial activity are broadly consistent with the identified structure of payoffs. A number of measures that can be implemented to strengthen entrepreneurial incentives within extensive welfare states are discussed, but the fact still remains that an entrepreneurial culture and a welfare state are very remotely related. As a result, the respective cultures are unlikely to be promoted by a similar set of institutions.
Sparse estimation of self-exciting point processes with application to LGN neural modeling

In this paper, the performance of ℓ1-regularized Maximum-Likelihood estimator is investigated in sparse estimation of self-exciting processes. The underlying model includes a Generalized Linear Model (GLM) with Poisson observations and a parameter which is related to the covariates through a log-link. Kolmogorov-Smirnov and autocorrelation function tests are used as statistical goodness-of-fit measures. Results have shown a better performance of the regularized estimator both in the statistical sense and in the error norm. Application of the proposed algorithm to the LGN neuron firing data has successfully recovered the neurons' intrinsic frequencies.
New Constructions of Optimal Locally Recoverable Codes via Good Polynomials

In recent literature, a family of optimal linear locally recoverable codes (LRC codes) that attain the maximum possible distance (given code length, cardinality, and locality) is presented. The key ingredient for constructing such optimal linear LRC codes is the so-called <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>-good polynomials, where <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> is equal to the locality of the LRC code. However, given a prime <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>, known constructions of <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>-good polynomials over some extension field of <inline-formula> <tex-math notation="LaTeX">$\mathbb {F}_{p}$ </tex-math></inline-formula> exist only for some special integers <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>, and the problem of constructing optimal LRC codes over small field for any given locality is still open. In this paper, by using function composition, we present two general methods of designing good polynomials, which lead to three new constructions of <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>-good polynomials. Such polynomials bring new constructions of optimal LRC codes. In particular, our constructed polynomials as well as the power functions yield optimal <inline-formula> <tex-math notation="LaTeX">$(n,k,r)$ </tex-math></inline-formula> LRC codes over <inline-formula> <tex-math notation="LaTeX">$\mathbb {F}_{q}$ </tex-math></inline-formula> for all positive integers <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> as localities, where <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> is near the code length <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>.
A retrospective case-control study of modifiable risk factors and cutaneous markers in Indian patients with young coronary artery disease

Objective Indians have the highest risk rates for coronary artery disease (CAD) among all ethnic groups. There is a paucity of data on the risk factors and clinical markers associated with premature CAD. We aimed to determine whether young CAD is due to preventable lifestyle-related factors and cutaneous clinical markers are useful in identifying at-risk patients. Design Single-centre retrospective study. Setting Tertiary care center. Participants A total of 292 patients (age ≤40 years) who presented with acute CAD between January 2005 and June 2009 and 92 age, and gender-matched controls. Major outcome measures Details of smoking, family history of premature CAD, waist size, blood sugar and lipid profile. Clinical evidence of arcus juvenilis, premature greying of hair and premature baldness sought. Results Dyslipidaemia (91%), smoking (74.3%), low high-density lipoprotein cholesterol (HDL-C) (68.9%), central obesity (47.7%) and greying of hair (34.9%) were the most commonly associated factors. Compared with male patients, females had greater prevalence of dyslipidaemia, low HDL-C, central obesity, hypertension, diabetes and family history of premature CAD. The presence of cutaneous markers was significantly associated with premature CAD. Conclusions CAD in young Indian people is multifactorial; dyslipidaemia, low HDL-C, smoking, hypertension, central obesity and family history of premature CAD are the most common risk factors. Smoking in men and central obesity in women are the most prevalent factors. Clinicians should be highly suspicious of patients with presence of cutaneous markers, and they should be followed intensively for lifestyle modifications.
Genetic Variation in the Vascular Endothelial Growth Factor Gene is Associated With Biliary Atresia

Background and Goals: Biliary atresia (BA) is a chronic inflammatory disease of the bile ducts resulting in biliary cirrhosis. Vascular endothelial growth factor (VEGF) has been implicated in cell-mediated inflammatory reactions. We aimed to study the relationship between genetic variations of the VEGF gene and susceptibility to BA using both case-control and family-based methodologies. Study: A total of 45 Taiwanese children with BA, 160 ethnically matched healthy controls, and 40 families (consisting of parents, affected children, and unaffected siblings) were studied. Three functional VEGF polymorphisms (−2578 A/C, −634 G/C, and +936 C/T) were assessed by using TaqMan assay. Results: The +936 CC genotype [odds ratio (OR) 3.51, 95% confidence interval 1.54-8.01, Pc=0.006] and C allele (OR 3.19, 95% confidence interval 1.48-6.90, Pc=0.004) were significantly associated with increased risk of BA. The association of the +936 C allele with BA was also confirmed in a family-based association study (OR 5.7, χ2=9.8, Pc=0.005). None of the haplotypes studied significantly influenced the risk to BA in either the case-control or family data sets. Conclusions: The VEGF +936 C/T polymorphism and particularly the C allele are associated with BA, possibly conferring increased susceptibility to the disease.
Job embeddedness versus traditional models of voluntary turnover: A test of voluntary turnover prediction.

Voluntary turnover has historically been a problem for today's organizations. Traditional models of turnover continue to be utilized in a number of ways in both academia and industry. A newer model of turnover, job embeddedness, has recently been developed in an attempt to better predict voluntary turnover than existing models. Job embeddedness consists of organizational fit, organizational sacrifice, and organizational links. The purpose of this study is to two fold. First, psychometric analyses were conducted on the job embeddedness model. Exploratory factor analyses were conducted on the dimensions of job embeddedness, which revealed a combined model consisting of five factors. This structure was then analyzed using confirmatory factor analysis, assessing a 1, 3, and 5 factor model structure. The confirmatory factor analysis established the use of the 5 factor model structure in subsequent analysis in this study. The second purpose of this study is to compare the predictive power of the job embeddedness model versus that of the traditional models of turnover. The traditional model of turnover is comprised of job satisfaction, organizational commitment, and perceived job alternatives. In order to compare the predictive power of the job embeddedness and traditional model of voluntary turnover, a series of structural equation model analyses were conducting using LISREL. The job embeddedness model, alone, was found to be the best fit with the sample data. This fit was improved over the other two models tested (traditional model and the combination of the traditional and job embeddedness model). In addition to assessing which model better predicts voluntary turnover, it was tested which age group and gender is a better fit with the job embeddedness model. It was found that the job embeddedness model better predicts turnover intention for older respondents and males.
Understanding the Factors Affecting Users' Like Intentions in Social Network Services: A Multi-dimensional Value Perspective

Social network service (SNS) has become a widely used social communication platform which is well integrated in the daily routines of many people. The Like button has become a popular interactive function in SNS in recent years but the research on the underlying mechanism about why individuals use the Like button (termed as Like behavior in this study) is rarely examined. To fill this research gap, based on a multi-dimensional value perspective, we propose a research model to investigate the factors influencing users' Like behaviors. The proposed model is empirically tested through an online survey of 479 users in the context of WeChat, one of the most popular SNS in China. The results of this study suggest that social value, entertainment value and cognitive value are the key determinants of users' Like intention. Theoretical and practical implications as well as limitations of the study are discussed finally.
Nicotinic transmission at functionally distinct synapses in descending reflex pathways of the rat colon

Abstract We examined descending reflex pathways in the rat colon using intracellular recording techniques. Inhibitory junction potentials (IJPs) were recorded from circular smooth muscle when descending pathways were excited by combined mucosal compression and distension. IJPs were reduced to 71% of control when synaptic transmission was blocked in the oral stimulation chamber of a divided organ bath suggesting that two reflex pathways exist, the one involving descending sensory neurones and the other involving descending interneurones. Hexamethonium (200 μmol L−1) in the recording chamber abolished reflexly evoked IJPs, while in the stimulation chamber, it was as effective as synaptic blockade. When hexamethonium was added to a chamber lying between the stimulation and recording chambers, it again sharply depressed IJPs to 27% of control; an extent similar to synaptic blockade. A P2 receptor antagonist did not reveal any purinergic neurotransmission. Either granisetron (5‐HT3 receptor antagonist, 1 μmol L−1) or SB204070 (5‐HT4 receptor antagonist, 1 μmol L−1) in the stimulation chamber significantly decreased IJPs; these decreases were not additive. We conclude that some sensory neurones and interneurones in rat colon have long anally projecting axons and that acetylcholine, acting via nicotinic receptors, is the primary neurotransmitter from sensory neurones, to inhibitory motor neurones and between interneurones.
Using trust for detecting deceitful agents in artificial societies

Trust is one of the most important concepts guiding decision-making and contracting in human societies. In artificial societies, this concept has been neglected until recently. The inherent benevolence assumption implemented in many multiagent systems can have hazardous consequences when dealing with deceit in open systems. The aim of this paper is to establish a mechanism that helps agents to cope with environments inhabited by both selfish and cooperative entities. This is achieved by enabling agents to evaluate trust in others. A formalization and an algorithm for trust are presented so that agents can autonomously deal with deception and identify trustworthy parties in open systems. The approach is twofold: agents can observe the behavior of others and thus collect information for establishing an initial trust model. In order to adapt quickly to a new or rapidly changing environment, one enables agents to also make use of observations from other agents. The practical relevance of these ideas is demonstrated by means of a direct mapping from a scenario to electronic commerce.