Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliability of thermal quantitative sensory testing of the hand in a cohort of young, healthy adults

Introduction: The reliability of thermal quantitative sensory testing (QST) has yet to be fully established. In this study we investigated intra‐ and interrater reliability of thermal QST in a blinded manner. Methods: Two investigators recorded thermal detection and pain thresholds on the hand of 22 volunteers, twice on two occasions. Results were analyzed using descriptive statistics, intraclass correlation coefficients (ICCs), and coefficients of variation (CVs). Results: Mean intraindividual differences were small for all measures except cold pain thresholds. ICC values for intra‐ and interrater reliability were: cold detection, 0.27–0.55; warm detection, 0.33–0.69; and heat pain, 0.39–0.86. Cold pain yielded high ICC values (0.87–0.94), but also high CV (84.9–90.2%). Conclusions: In young, healthy adults, thermal detection and heat pain thresholds of the hand demonstrated good reliability for group comparisons and individual analyses. Cold pain threshold measures may be suitable for group comparisons, but a large variance in the data limits individual analyses. Muscle Nerve, 2011
Learning from Private Information in Noisy Repeated Games

We study the perfect type-contingently public ex-post equilibrium (PTXE) of repeated games where players observe imperfect public signals of the actions played, and both the payoff functions and the map from actions to signal distributions depend on an unknown state. The PTXE payoffs when players are patient are determined by the solutions to a family of linear programming problems. Using this characterization, we develop conditions under which play can be as if the players have learned the state. We provide a sufficient condition for the folk theorem, and a characterization of the PTXE payoffs in games with a known monitoring structure.
SyMGiza++: A tool for parallel computation of symmetrized word alignment models

SyMGiza++ - a tool that computes symmetric word alignment models with the capability to take advantage of multi-processor systems - is presented. A series of fairly simple modifications to the original IBM/Giza++ word alignment models allows to update the symmetrized models between each iteration of the original training algorithms. We achieve a relative alignment quality improvement of more than 17% compared to Giza++ and MGiza++ on the standard Canadian Hansards task, while maintaining the speed improvements provided by MGiza++'s capability of parallel computations.
General Tooth Boundary Conditions for Equation Free Modeling

We are developing a framework for multiscale computation which enables models at a “microscopic” level of description, for example, lattice Boltzmann, Monte Carlo, or molecular dynamics simulators, to perform modeling tasks at “macroscopic” length scales of interest. The plan is to use the microscopic rules restricted to small “patches” of the domain, the “teeth,” using interpolation to bridge the “gaps. ” Here we explore general boundary conditions coupling the widely separated “teeth” of the microscopic simulation that achieve high order accuracy over the macroscale. We present the simplest case when the microscopic simulator is the quintessential example of a PDE. We argue that classic high order interpolation of the macroscopic field provides the correct forcing in whatever boundary condition is required by the microsimulator. Such interpolation leads to tooth boundary conditions, which achieve arbitrarily high order consistency. The high order consistency is demonstrated on a class of linear PDEs in two ways: first through the eigenvalues of the scheme for selected numerical problems, and second using the dynamical systems approach of holistic discretization on a general class of linear PDEs. Analytic modeling shows that, for a wide class of microscopic systems, the subgrid fields and the effective macroscopic model are largely independent of the tooth size and the particular tooth boundary conditions. When applied to patches of microscopic simulations these tooth boundary conditions promise efficient macroscale simulation. We expect the same approach will also accurately couple patch simulations in higher spatial dimensions.
Comparison of the kinetic properties of the lipid- and protein-kinase activities of the p110α and p110β catalytic subunits of class-Ia phosphoinositide 3-kinases

Growth factors regulate a wide range of cellular processes via activation of the class-Ia phosphoinositide 3-kinases (PI 3-kinases). We directly compared kinetic properties of lipid- and protein-kinase activities of the widely expressed p110alpha and p110beta isoforms. The lipid-kinase activity did not display Michaelis-Menten kinetics but modelling the kinetic data demonstrated that p110alpha has a higher V(max) and a 25-fold higher K(m) for PtdIns than p110beta. A similar situation occurs with PtdIns(4,5)P(2), because at low concentration of PtdIns(4,5)P(2) p110beta is a better PtdIns(4,5)P(2) kinase than p110alpha, although this is reversed at high concentrations. These differences suggest different functional roles and we hypothesize that p110beta functions better in areas of membranes containing low levels of substrate whereas p110alpha would work best in areas of high substrate density such as membrane lipid rafts. We also compared protein-kinase activities. We found that p110beta phosphorylated p85 to a lower degree than did p110alpha. We used a novel peptide-based assay to compare the kinetics of the protein-kinase activities of p110alpha and p110beta. These studies revealed that, like the lipid-kinase activity, the protein-kinase activity of p110alpha has a higher K(m) (550 microM) than p110beta (K(m) 8 microgM). Similarly, the relative V(max) towards peptide substrate of p110alpha was three times higher than that of p110beta. This implies differences in the rates of regulatory autophosphorylation in vivo, which are likely to mean differential regulation of the lipid-kinase activities of p110alpha and p110beta in vivo.
Investigating the applicability of the evidence-based paradigm to software engineering

Context: The success of the evidence-based paradigm in other domains, especially medicine, has raised the question of how this might be employed in software engineering.Objectives: To report the research we are doing to evaluate problems associated with adopting the evidence-based paradigm in software engineering and identifying strategies to address these problems.Method: Currently the experimental paradigms used in a selected set of domains are being examined along with the experimental protocols that they employ. Our aim is to identify those domains that have generally similar characteristics to software engineering and to study the strategies that they employ to overcome the lack of rigorous empirical protocols. We are also undertaking a series of systematic literature reviews to identify the factors that may limit their applicability in the software engineering domain.Conclusions: We have identified two domains that experience problems with experimental protocols that are similar to those occurring for software engineering, and will investigate these further to assess whether the approaches used to aggregate evidence in these domains can be adapted for use in software engineering. Our experiences from performing systematic literature reviews are positive, but reveal infrastructure problems caused by poor indexing of the literature.
Active and passive smoking in relation to lung cancer incidence in the Women's Health Initiative Observational Study prospective cohort.

BACKGROUND Lung cancer is the leading cause of worldwide cancer deaths. While smoking is its leading risk factor, few prospective cohort studies have reported on the association of lung cancer with both active and passive smoking. This study aimed to determine the relationship between lung cancer incidence with both active and passive smoking (childhood, adult at home, and at work). PATIENTS AND METHODS The Women's Health Initiative Observational Study (WHI-OS) was a prospective cohort study conducted at 40 US centers that enrolled postmenopausal women from 1993 to 1999. Among 93 676 multiethnic participants aged 50-79, 76 304 women with complete smoking and covariate data comprised the analytic cohort. Lung cancer incidence was calculated by Cox proportional hazards models, stratified by smoking status. RESULTS Over 10.5 mean follow-up years, 901 lung cancer cases were identified. Compared with never smokers (NS), lung cancer incidence was much higher in current [hazard ratio (HR) 13.44, 95% confidence interval (CI) 10.80-16.75] and former smokers (FS; HR 4.20, 95% CI 3.48-5.08) in a dose-dependent manner. Current and FS had significantly increased risk for all lung cancer subtypes, particularly small-cell and squamous cell carcinoma. Among NS, any passive smoking exposure did not significantly increase lung cancer risk (HR 0.88, 95% CI 0.52-1.49). However, risk tended to be increased in NS with adult home passive smoking exposure ≥30 years, compared with NS with no adult home exposure (HR 1.61, 95% CI 1.00-2.58). CONCLUSIONS In this prospective cohort of postmenopausal women, active smoking significantly increased risk of all lung cancer subtypes; current smokers had significantly increased risk compared with FS. Among NS, prolonged passive adult home exposure tended to increase lung cancer risk. These data support continued need for smoking prevention and cessation interventions, passive smoking research, and further study of lung cancer risk factors in addition to smoking. CLINICALTRIALS.GOV: NCT00000611.
Gatekeepers or Intermediaries? The Role of Clinicians in Commercial Genomic Testing

Background Many commentators on “direct-to-consumer” genetic risk information have raised concerns that giving results to individuals with insufficient knowledge and training in genomics may harm consumers, the health care system, and society. In response, several commercial laboratories offering genomic risk profiling have shifted to more traditional “direct-to-provider” (DTP) marketing strategies, repositioning clinicians as the intended recipients of advertising of laboratory services and as gatekeepers to personal genomic information. Increasing popularity of next generation sequencing puts a premium on ensuring that those who are charged with interpreting, translating, communicating and managing commercial genomic risk information are appropriately equipped for the job. To shed light on their gatekeeping role, we conducted a study to assess how and why early clinical users of genomic risk assessment incorporate these tools in their clinical practices and how they interpret genomic information for their patients. Methods and Findings We conducted qualitative in-depth interviews with 18 clinicians providing genomic risk assessment services to their patients in partnership with DNA Direct and Navigenics. Our findings suggest that clinicians learned most of what they knew about genomics directly from the commercial laboratories. Clinicians rely on the expertise of the commercial laboratories without the ability to critically evaluate the knowledge or assess risks. Conclusions DTP service delivery model cannot guarantee that providers will have adequate expertise or sound clinical judgment. Even if clinicians want greater genomic knowledge, the current market structure is unlikely to build the independent substantive expertise of clinicians, but rather promote its continued outsourcing. Because commercial laboratories have the most “skin in the game” financially, genetics professionals and policymakers should scrutinize the scientific validity and clinical soundness of the process by which these laboratories interpret their findings to assess whether self-interested commercial sources are the most appropriate entities for gate-keeping genomic interpretation.
Downside Correlation and Expected Stock Returns

If investors are more averse to the risk of losses on the downside than of gains on the upside, investors ought to demand greater compensation for holding stocks with greater downside risk. Downside correlations better capture the asymmetric nature of risk than downside betas, since conditional betas exhibit little asymmetry across falling and rising markets. We find that stocks with high downside correlations with the market, which are correlations over periods when excess market returns are below the mean, have high expected returns. Controlling for the market beta, the size effect, and the book-to-market effect, the expected return on a portfolio of stocks with the greatest downside correlations exceeds the expected return on a portfolio of stocks with the least downside correlations by 6.55% per annum. We find that part of the profitability of investing in momentum strategies can be explained as compensation for bearing high exposure to downside risk.
Cognitive effects of risperidone in children with autism and irritable behavior.

OBJECTIVE The objective of this research was to explore the effects of risperidone on cognitive processes in children with autism and irritable behavior. METHOD Thirty-eight children, ages 5-17 years with autism and severe behavioral disturbance, were randomly assigned to risperidone (0.5 to 3.5 mg/day) or placebo for 8 weeks. This sample of 38 was a subset of 101 subjects who participated in the clinical trial; 63 were unable to perform the cognitive tasks. A double-blind placebo-controlled parallel groups design was used. Dependent measures included tests of sustained attention, verbal learning, hand-eye coordination, and spatial memory assessed before, during, and after the 8-week treatment. Changes in performance were compared by repeated measures ANOVA. RESULTS Twenty-nine boys and 9 girls with autism and severe behavioral disturbance and a mental age >or=18 months completed the cognitive part of the study. No decline in performance occurred with risperidone. Performance on a cancellation task (number of correct detections) and a verbal learning task (word recognition) was better on risperidone than on placebo (without correction for multiplicity). Equivocal improvement also occurred on a spatial memory task. There were no significant differences between treatment conditions on the Purdue Pegboard (hand-eye coordination) task or the Analog Classroom Task (timed math test). CONCLUSION Risperidone given to children with autism at doses up to 3.5 mg for up to 8 weeks appears to have no detrimental effect on cognitive performance.
Comparison of Self- and Proxy Report of Mental Health Symptoms in People With Intellectual Disabilities

ABSTRACT Mental illness, and its assessment and treatment, is a concern for caregivers and professionals working with people with intellectual disability (ID), as well as a cause of distress and disability for people with ID. Research in this area is hindered by difficulties associated with recognizing symptoms of mental illness and tracking their changes. The use of empirically derived and tested tools can improve clinical and research outcomes. This study compares proxy reports of mental health symptoms using the Psychiatric Assessment Schedules for Adults with Developmental Disabilities (PAS-ADD) Checklist to self-reported symptoms using an interview form of the Brief Symptom Inventory (BSI). While the two scales were statistically correlated, clinically they presented very differently. The PAS-ADD identified 23.6% of participants as scoring in the at-risk category of mental health symptoms, while self-rating of symptoms on the BSI resulted in 67.8% of participants scoring above the cutoff. Concerns regarding the use of the BSI for a wide range of people with ID are discussed, as well as the concerns of using proxy report for subjective topics such as mental health symptoms.
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data

In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits model parameters by favoring models that match certain expectation constraints, such as marginal label distributions, on the unlabeled data. This paper shows how to apply generalized expectation criteria to two classes of parametric models: maximum entropy models and conditional random fields. Experimental results demonstrate accuracy improvements over supervised training and a number of other state-of-the-art semi-supervised learning methods for these models.
Analysis of the role of cannabinoid receptors and 2-adrenoceptor subtypes in gastrointestinal functions

s Shujaa, N. , Zadori, Z.S. , Gyires, K. , (2007). Pharmacological analysis of cannabinoid-induced inhibition of gastric mucosal damage and gastric motility. Zeitschrift für Gastroenterologie, 44: 421-452. Shujaa, N. , Zádori, Z.S. , Al-Khrasani, M. , Fürst, S. , Wenger, T. , Gyires, K. , (2007). The role of cannbinoid CB1 receptor agonists in gastric mucosal protection in rats and mice. BMC. Pharmacology, 7 (suppl 2):A47 Aricó, G. , Zádori, Z.S. , Shujaa, N. , Tekes, K. , Gyires, K. , (2007). Endogenous opioids may mediate the centraly-induced
Comparison of HER2 status by fluorescence in situ hybridisation and immunohistochemistry in gastric cancer

Aim of the study To investigate the differences and relevance, and to evaluate the clinical significance of fluorescence in situ hybridisation and immunohistochemistry (IHC) in detecting HER2 in gastric cancer tissues. Material and methods The expression of HER2 protein and the amplification of the HER2 gene in 118 gastric cancer tissues were detected by immunohistochemistry and fluorescence in situ hybridisation, respectively. Results Using IHC, we found that in 40 cases (33.9%) the HER2 expression was at level 0, in 33 cases (28.0%) the HER2 expression was at level 1+, in 16 cases (14%) the HER2 expression was at level 2+, and in 29 cases (25.6%) the HER2 expression was at level 3+, respectively. Using the FISH test, 38 of 118 cases (32.2%) were judged as positive results. The concordance rate between the results of IHC and FISH in all cases was 85.6%. The concordance rate of IHC and FISH was high in cases of HER2 expression at level 0, 1+ and 3+ according to IHC, but low in cases of 2+ according to IHC (43.8%). Conclusions Immunohistochemistry cannot predict HER2 gene amplification accurately. The FISH test should be executed in IHC 2+ cases.
Causality for free!: parametricity implies causality for functional reactive programs

Functional Reactive Programming (FRP) is a model of reactive systems in which signals are time-dependent values, and signal functions are functions between signals. Signal functions are required to be causal, in that output behaviour at time t is only allowed to depend on input behaviour up to time t. In order to enforce causality, many FRP libraries are arrowized, in that they provide combinators for building signal functions, rather than allowing users to write functions directly. In this paper, we provide a definition of deep causality (which coincides with the usual definition on signals of base type, but differs on nested signals). We show that FRP types can be interpreted in System Fomega extended with a kind of time, and show that in this interpretation, a "theorems for free" argument shows that parametric functions are deep causal. Since all System Fomega functions are parametric, this implies that all implementable functions are deep causal. This model is the formal basis of the agda-frp-js FRP library for the dependently typed programming language Agda, which compiles to JavaScript and executes in the browser. Assuming parametricity of Agda, this allows reactive programs to be written as regular functions over signals, without sacrificing causality. All results in this paper have been mechanically verified in Agda.
The interconnected role of strength of brand and interpersonal relationships and user comment valence on brand video sharing behaviour

ABSTRACT This study addresses gaps in our understanding of viral advertising by examining the following questions: (1) how do brand relationships, interpersonal relationships, and user comment valence influence decisions to accept referrals of and re-share online video ads, and (2) how do the roles of each intertwine to influence those decisions. A national sample (N = 405) of 18- to 34-year-old Facebook users participated in a 2 (stronger/weaker brand relationship strength) × 2 (stronger/weaker interpersonal relationship strength) × 2 (positive/negative user comments) experiment. The results show that interpersonal relationships, brand relationships, and valence of user comments play different, but intertwining roles in social networking site users' acceptance of viral video ads and decisions to re-share. Interpersonal relationships most strongly influenced ad referral acceptance while brand relationships and comment valence drove re-sharing. A three-way interaction, however, revealed that positive user comments greatly strengthen the brand's impact on referral acceptance; negative comments strongly negate brand influence.
Bootstrapping Spoken Dialog Systems with Data Reuse

Building natural language spoken dialog systems requires large amounts of human transcribed and labeled speech utterances to reach useful operational service performances. Furthermore, the design of such complex systems consists of several manual steps. The User Experience (UE) expert analyzes and defines by hand the system core functionalities: the system semantic scope (call-types) and the dialog manager strategy which will drive the human-machine interaction. This approach is extensive and error prone since it involves several non-trivial design decisions that can only be evaluated after the actual system deployment. Moreover, scalability is compromised by time, costs and the high level of UE know-how needed to reach a consistent design. We propose a novel approach for bootstrapping spoken dialog systems based on reuse of existing transcribed and labeled data, common reusable dialog templates and patterns, generic language and understanding models, and a consistent design process. We demonstrate that our approach reduces design and development time while providing an effective system without any application specific data.
System electrical parameters and their effects on bearing currents

This paper examines AC motor shaft voltages and resulting bearing currents when operated under pulse width modulation (PWM) voltage source inverters. The paper reviews the electrical characteristics of bearings and motors that cause shaft voltages and bearing currents. A brief review of previous work is presented, including a system model for electrical analysis of bearing currents. Relying on the work of a companion paper, the propensity for electric discharge machining (EDM) is determined by a design equation that is a function of system components. Pertinent machine parameters and their formulae are presented and values calculated for machines from 5 to 1000 hp. The effects of system elements on shaft voltages and bearing currents are evaluated experimentally and the results compared to theory. Finally, the paper presents quantitative results for one solution to the shaft voltage and bearing current problem.
Has twenty-five years of empirical software engineering made a difference?

Our activities in software engineering typically fall into one of three categories, (1) to invent new phenomena, (2) to understand existing phenomena, and (3) to facilitate inspirational education. This paper explores the place of empirical software engineering in the first two of these activities. In this exploration evidence is drawn from the empirical literature in the areas of software inspections and software cost modelling and estimation. This research is then compared with the literature published in the Journal of Empirical Software Engineering. This evidence throws light on aspects of theory derivation, experimental methods and analysis, and also the challenges that we face as empirical software engineering evolves into the future.