The role of social support and social identification on challenge and threat cognitive appraisals, perceived stress, and life satisfaction in workplace employees

There is an emergent literature highlighting the positive role of social support and social identification in buffering against the deleterious effects of psychological stressors. Yet, we have limited understanding of how exactly these social factors fit within contemporary stress and coping theory. To advance and gain a greater understanding of these social factors, we explore the associations of social support and social identification on individuals’ challenge and threat cognitive appraisals and how this then relates to perceived stress, life satisfaction, turnover intentions, and job performance. A total of 412 workplace employees from private and public sector occupations completed state measures around a recent most stressful experience at work. Results revealed atemporal associations between cognitive resource appraisals with both social support and social identification. Specifically, greater identification with colleagues and lower threat were related to less perceived stress, while having greater social identification (with colleagues and organisation), social support, and lower threat, were related to greater life satisfaction. Greater perceived stress, and lower social identification and life satisfaction, were also related to greater turnover intentions. While greater identification with the organisation and life satisfaction, along with lower perceived stress were related to greater job performance. Taken together, this research provides evidence that social support and social identification play a positive role when trying to promote more adaptive responses to stressful situations

Laser frequency noise characterisation using high-finesse plano-concave optical microresonators

Characterising laser frequency noise is essential for applications including optical sensing and coherent optical communications. Accurate measurement of ultranarrow linewidth lasers over a wide frequency range using existing methods is still challenging. Here we present a method for characterising the frequency noise of lasers using a high finesse plano-concave optical microresonator (PCMR) acting as frequency discriminator. To enable noise measurements at a wide range of laser frequencies, an array of PCMRs was produced with slight variations of thickness resulting in a series of discriminators operating at a series of periodical frequencies. This method enables measuring the frequency noise over a wide linewidth range (15Hz to <100MHz) over the 1440nm-1630nm wavelength range. To assess the performance of the method, four different lasers were characterised, and the results were compared to the estimations of a commercial frequency noise analyser

Inadequate reporting of research ethics review and informed consent in cluster randomized trials : review of random sample of published trials

Peer reviewedPublisher PD

Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning

Quantum machine learning (QML) is emerging as an application of quantum computing with the potential to deliver quantum advantage, but its realisation for practical applications remains impeded by challenges. Amongst those, a key barrier is the computationally expensive task of encoding classical data into a quantum state, which could erase any prospective speed-ups over classical algorithms. In this work, we implement methods for the efficient preparation of quantum states representing encoded image data using variational, genetic and matrix product state based algorithms. Our results show that these methods can approximately prepare states to a level suitable for QML using circuits two orders of magnitude shallower than a standard state preparation implementation, obtaining drastic savings in circuit depth and gate count without unduly sacrificing classification accuracy. Additionally, the QML models trained and evaluated on approximately encoded data display an increased robustness to adversarially generated input data perturbations. This partial alleviation of adversarial vulnerability, possible due to the "drowning out" of adversarial perturbations while retaining the meaningful large-scale features of the data, constitutes a considerable benefit for approximate state preparation in addition to lessening the requirements of the quantum hardware. Our results, based on simulations and experiments on IBM quantum devices, highlight a promising pathway for the future implementation of accurate and robust QML models on complex datasets relevant for practical applications, bringing the possibility of NISQ-era QML advantage closer to reality.Comment: 14 pages, 8 figure

How to develop, externally validate, and update multinomial prediction models

Multinomial prediction models (MPMs) have a range of potential applications across healthcare where the primary outcome of interest has multiple nominal or ordinal categories. However, the application of MPMs is scarce, which may be due to the added methodological complexities that they bring. This article provides a guide of how to develop, externally validate, and update MPMs. Using a previously developed and validated MPM for treatment outcomes in rheumatoid arthritis as an example, we outline guidance and recommendations for producing a clinical prediction model using multinomial logistic regression. This article is intended to supplement existing general guidance on prediction model research. This guide is split into three parts: 1) Outcome definition and variable selection, 2) Model development, and 3) Model evaluation (including performance assessment, internal and external validation, and model recalibration). We outline how to evaluate and interpret the predictive performance of MPMs. R code is provided. We recommend the application of MPMs in clinical settings where the prediction of a nominal polytomous outcome is of interest. Future methodological research could focus on MPM-specific considerations for variable selection and sample size criteria for external validation

Salinity and temperature affect the symbiont profile and host condition of Florida USA blue crabs Callinectes sapidus

Subtropical Florida blue crabs, Callinectes sapidus, exhibit differing life history traits compared to their temperate counterparts, likely influencing symbiont infection dynamics. Little information exists for Florida C. sapidus symbiont profiles, their distribution among various habitats, and influence on crab condition. Using histopathology, genomics, and transmission electron microscopy, we describe the first symbiont profiles for Florida C. sapidus occupying freshwater to marine habitats. Twelve symbiont groups were identified from 409 crabs including ciliophorans, digenean, microsporidian, Haplosporidia, Hematodinium sp., Nematoda, filamentous bacteria, gregarine, Callinectes sapidus nudivirus, Octolasmis sp., Cambarincola sp., and putative microcell. Overall, 78% of C. sapidus were documented with one or more symbiont groups demonstrating high infection rates in wild populations. Environmental variables water temperature and salinity explained 48% of the variation in symbiont groups among Florida habitats, and salinity was positively correlated with C. sapidus symbiont diversity. This suggests freshwater C. sapidus possess fewer symbionts and represent healthier individuals compared to saltwater populations. Crab condition was examined using the reflex action mortality predictor (RAMP) to determine if reflex impairment could be linked to symbiont prevalence. Symbionts were found positively correlated with crab condition, and impaired crabs were more likely to host symbionts, demonstrating symbiont inclusion may boost predictive ability of the RAMP application. The microsporidian symbiont group had a particularly strong effect on C. sapidus reflex response, and impairment was on average 1.57 times higher compared to all other symbiont groups. Our findings demonstrate the importance of considering full symbiont profiles and their associations with a spatially and temporally variable environment to fully assess C. sapidus population health.</p

Совершенствование ценообразования на предприятии

Выпускная квалификационная работа 105 с., 7 рис., 29 табл., 22 источника. Цель работы - экономическое обоснование оптимальной цены на продукцию. В процессе исследования проводились статистические исследования. В результате исследования была разработана оптимальная цена на продукцию. Основные технологические и управленческие характеристики: организационная структура является линейной, списочная численность предприятия - 150 человек.Final qualifying work 105 p., 7 Fig., 29 tab., 22 source. Purpose - the economic rationale for the optimal prices for the products. During the study, carried out statistical studies. The study developed the optimal price for the products. Basic technological and managerial characteristics: organizational structure is linear, the headcount of the enterprise - 150 people

An Antimethanogenic Nutritional Intervention in Early Life of Ruminants Modifies Ruminal Colonization by Archaea

The aim of this work was to study whether feeding a methanogen inhibitor from birth of goat kids and their does has an impact on the archaeal population colonizing the rumen and to what extent the impact persists later in life. Sixteen goats giving birth to two kids were used. Eight does were treated (D+) with bromochloromethane after giving birth and over 2 months. The other 8 goats were not treated (D−). One kid per doe in both groups was treated with bromochloromethane (k+) for 3 months while the other was untreated (k−), resulting in four experimental groups: D+/k+, D+/k−, D−/k+, and D−/k−. Rumen samples were collected from kids at weaning and 1 and 4 months after (3 and 6 months after birth) and from does at the end of the treating period (2 months). Pyrosequencing analyses showed a modified archaeal community composition colonizing the rumen of kids, although such effect did not persist entirely 4 months after; however, some less abundant groups remained different in treated and control animals. The different response on the archaeal community composition observed between offspring and adult goats suggests that the competition occurring in the developing rumen to occupy different niches offer potential for intervention

Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques

IntroductionThis study considers the prediction of the time until two survival outcomes have both occurred. We compared a variety of analytical methods motivated by a typical clinical problem of multimorbidity prognosis.MethodsWe considered five methods: product (multiply marginal risks), dual-outcome (directly model the time until both events occur), multistate models (msm), and a range of copula and frailty models. We assessed calibration and discrimination under a variety of simulated data scenarios, varying outcome prevalence, and the amount of residual correlation. The simulation focused on model misspecification and statistical power. Using data from the Clinical Practice Research Datalink, we compared model performance when predicting the risk of cardiovascular disease and type 2 diabetes both occurring.ResultsDiscrimination was similar for all methods. The product method was poorly calibrated in the presence of residual correlation. The msm and dual-outcome models were the most robust to model misspecification but suffered a drop in performance at small sample sizes due to overfitting, which the copula and frailty model were less susceptible to. The copula and frailty model's performance were highly dependent on the underlying data structure. In the clinical example, the product method was poorly calibrated when adjusting for 8 major cardiovascular risk factors.DiscussionWe recommend the dual-outcome method for predicting the risk of two survival outcomes both occurring. It was the most robust to model misspecification, although was also the most prone to overfitting. The clinical example motivates the use of the methods considered in this study

Halogen effects on the solid-state packing of phenylalanine derivatives and the resultant gelation properties

Phenylalanine is an important amino acid both biologically, essential to human health, and industrially, as a building block of artificial sweeteners. Our interest in this particular amino acid and its derivatives lies with its ability to form gels in a number of solvents. We present here the studies of the influence of halogen addition to the aromatic ring on the gelation properties and we analyse the crystal structures of a number of these materials to elucidate the trends in their behaviour based on the halogen addition to the aromatic group and the interactions that result