Short-time critical dynamics

An introductory review to short-time critical dynamics is given. From the scaling relation valid already in the early stage of the evolution of a system at or near the critical point, one derives power law behaviour for various quantities. By a numerical simulation of the system one can measure the critical exponents and, by searching for the best power law behaviour, one can determine the critical point. Critical slowing down as well as finite size corrections are nearly absent, since the correlation length is still small for times far before equilibrium is reached. By measuring the (pseudo) critical points it is also possible to distinguish (weak) first-order from second-order phase transitions.Comment: Proceedings of the International Workshop on Nonperturbative Methods and Lattice QCD, Guangzho

The Critical Exponent θ′\theta' in Spin Glasses

Short-time dynamic scaling behavior of the 3D $\pm J$ Ising spin glass is studied by Monte Carlo methods. Starting the replicas with independent initial configurations with a small pseudo magnetization, the dynamic evolution of the overlap q(t) between two replicas is measured. The initial increase of the overlap q(t) is observed and the corresponding exponent $\theta'$ is obtained. From the scaling relation $\lambda =d/z-\theta'$, the dynamic exponent z is estimated.Comment: to appear in Mod. Phys. Lett.

The short-time critical behaviour of the Ginzburg-Landau model with long-range interaction

The renormalisation group approach is applied to the study of the short-time critical behaviour of the $d$-dimensional Ginzburg-Landau model with long-range interaction of the form $p^{\sigma} s_{p}s_{-p}$ in momentum space. Firstly the system is quenched from a high temperature to the critical temperature and then relaxes to equilibrium within the model A dynamics. The asymptotic scaling laws and the initial slip exponents $\theta^{\prime}$ and $\theta$ of the order parameter and the response function respectively, are calculated to the second order in $\epsilon=2\sigma-d$.Comment: 18 pages, 4 figures, 1 tabl

Professional decision-making in medicine: Development of a new measure and preliminary evidence of validity

INTRODUCTION: This study developed a new Professional Decision-Making in Medicine Measure that assesses the use of effective decision-making strategies: seek help, manage emotions, recognize consequences and rules, and test assumptions and motives. The aim was to develop a content valid measure and obtain initial evidence for construct validity so that the measure could be used in future research or educational assessment. METHODS: Clinical scenario-based items were developed based on a review of the literature and interviews with physicians. For each item, respondents are tasked with selecting two responses (out of six plausible options) that they would choose in that situation. Three of the six options reflect a decision-making strategy; these responses are scored as correct. Data were collected from a sample of 318 fourth-year medical students in the United States. They completed a 16-item version of the measure (Form A) and measures of social desirability, moral disengagement, and professionalism attitudes. Professionalism ratings from clerkships were also obtained. A sub-group (n = 63) completed a second 16-item measure (Form B) to pilot test the instrument, as two test forms are useful for pre-posttest designs. RESULTS: Scores on the new measure indicated that, on average, participants answered 75% of items correctly. Evidence for construct validity included the lack of correlation between scores on the measure and socially desirable responding, negative correlation with moral disengagement, and modest to low correlations with professionalism attitudes. A positive correlation was observed with a clerkship rating focused on professionalism in peer interactions. CONCLUSIONS: These findings demonstrate modest proficiency in the use of decision-making strategies among fourth-year medical students. Additional research using the Professional Decision-Making Measure should explore scores among physicians in various career stages, and the causes and correlates of scores. Educators could utilize the measure to assess courses that teach decision-making strategies

Estimating the additional costs of living with a disability in the United Kingdom between 2013 and 2016

In the United Kingdom, more than 20% of the population live with a disability. Past evidence shows that being disabled is associated with functional limitations that often cause social exclusion and poverty. Therefore, it is necessary to analyse the connection between disability and poverty. This paper examines whether households with disabled members face extra costs of living to attain the same standard of living as their peers without disabled members. The modelling framework is based on the standard of living approach which estimates the extra income required to close the gap between households with and without disabled members. We apply an ordered logit regression to data from the Family Resources Survey between 2013 and 2016 to analyse the relationship between standard of living, income, and disability, conditional on other explanatory variables. We find that households with disabled members face considerable extra costs that go beyond the transfer payment of the government. The average household with disabled members saw their weekly extra costs continually increase from £293 in 2013 to £326 in 2016 [2020 prices]. Therefore, the government needs to adjust welfare policies to address the problem of extra costs faced by households with disabled members

Preliminary genetic evidence of two different populations of Opisthorchis viverrini in Lao PDR

Opisthorchis viverrini is a major public health concern in Southeast Asia. Various reports have suggested that this parasite may represent a species complex, with genetic structure in the region perhaps being dictated by geographical factors and different species of intermediate hosts. We used four microsatellite loci to analyze O. viverrini adult worms originating from six species of cyprinid fish in Thailand and Lao PDR. Two distinct O. viverrini populations were observed. In Ban Phai, Thailand, only one subgroup occurred, hosted by two different fish species. Both subgroups occurred in fish from That Luang, Lao PDR, but were represented to very different degrees among the fish hosts there. Our data suggest that, although geographical separation is more important than fish host specificity in influencing genetic structure, it is possible that two species of Opisthorchis, with little interbreeding, are present near Vientiane in Lao PDR

A systematic, large-scale comparison of transcription factor binding site models

Background The modelling of gene regulation is a major challenge in biomedical research. This process is dominated by transcription factors (TFs) and mutations in their binding sites (TFBSs) may cause the misregulation of genes, eventually leading to disease. The consequences of DNA variants on TF binding are modelled in silico using binding matrices, but it remains unclear whether these are capable of accurately representing in vivo binding. In this study, we present a systematic comparison of binding models for 82 human TFs from three freely available sources: JASPAR matrices, HT-SELEX-generated models and matrices derived from protein binding microarrays (PBMs). We determined their ability to detect experimentally verified “real” in vivo TFBSs derived from ENCODE ChIP-seq data. As negative controls we chose random downstream exonic sequences, which are unlikely to harbour TFBS. All models were assessed by receiver operating characteristics (ROC) analysis. Results While the area- under-curve was low for most of the tested models with only 47 % reaching a score of 0.7 or higher, we noticed strong differences between the various position-specific scoring matrices with JASPAR and HT-SELEX models showing higher success rates than PBM-derived models. In addition, we found that while TFBS sequences showed a higher degree of conservation than randomly chosen sequences, there was a high variability between individual TFBSs. Conclusions Our results show that only few of the matrix-based models used to predict potential TFBS are able to reliably detect experimentally confirmed TFBS. We compiled our findings in a freely accessible web application called ePOSSUM (http:/mutationtaster.charite.de/ePOSSUM/) which uses a Bayes classifier to assess the impact of genetic alterations on TF binding in user-defined sequences. Additionally, ePOSSUM provides information on the reliability of the prediction using our test set of experimentally confirmed binding sites

Clinical, biochemical and genetic spectrum of 70 patients with ACAD9 deficiency: Is riboflavin supplementation effective?

Background: Mitochondrial acyl-CoA dehydrogenase family member 9 (ACAD9) is essential for the assembly of mitochondrial respiratory chain complex I. Disease causing biallelic variants in ACAD9 have been reported in individuals presenting with lactic acidosis and cardiomyopathy. Results: We describe the genetic, clinical and biochemical findings in a cohort of 70 patients, of whom 29 previously unpublished. We found 34 known and 18 previously unreported variants in ACAD9. No patients harbored biallelic loss of function mutations, indicating that this combination is unlikely to be compatible with life. Causal pathogenic variants were distributed throughout the entire gene, and there was no obvious genotype-phenotype correlation. Most of the patients presented in the first year of life. For this subgroup the survival was poor (50% not surviving the first 2 years) comparing to patients with a later presentation (more than 90% surviving 10 years). The most common clinical findings were cardiomyopathy (85%), muscular weakness (75%) and exercise intolerance (72%). Interestingly, severe intellectual deficits were only reported in one patient and

Exploring perceptions of healthcare technologies enabled by artificial intelligence: An online, scenario-based survey

BACKGROUND: Healthcare is expected to increasingly integrate technologies enabled by artificial intelligence (AI) into patient care. Understanding perceptions of these tools is essential to successful development and adoption. This exploratory study gauged participants\u27 level of openness, concern, and perceived benefit associated with AI-driven healthcare technologies. We also explored socio-demographic, health-related, and psychosocial correlates of these perceptions. METHODS: We developed a measure depicting six AI-driven technologies that either diagnose, predict, or suggest treatment. We administered the measure via an online survey to adults (N = 936) in the United States using MTurk, a crowdsourcing platform. Participants indicated their level of openness to using the AI technology in the healthcare scenario. Items reflecting potential concerns and benefits associated with each technology accompanied the scenarios. Participants rated the extent that the statements of concerns and benefits influenced their perception of favorability toward the technology. Participants completed measures of socio-demographics, health variables, and psychosocial variables such as trust in the healthcare system and trust in technology. Exploratory and confirmatory factor analyses of the concern and benefit items identified two factors representing overall level of concern and perceived benefit. Descriptive analyses examined levels of openness, concern, and perceived benefit. Correlational analyses explored associations of socio-demographic, health, and psychosocial variables with openness, concern, and benefit scores while multivariable regression models examined these relationships concurrently. RESULTS: Participants were moderately open to AI-driven healthcare technologies (M = 3.1/5.0 ± 0.9), but there was variation depending on the type of application, and the statements of concerns and benefits swayed views. Trust in the healthcare system and trust in technology were the strongest, most consistent correlates of openness, concern, and perceived benefit. Most other socio-demographic, health-related, and psychosocial variables were less strongly, or not, associated, but multivariable models indicated some personality characteristics (e.g., conscientiousness and agreeableness) and socio-demographics (e.g., full-time employment, age, sex, and race) were modestly related to perceptions. CONCLUSIONS: Participants\u27 openness appears tenuous, suggesting early promotion strategies and experiences with novel AI technologies may strongly influence views, especially if implementation of AI technologies increases or undermines trust. The exploratory nature of these findings warrants additional research