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We spell out the paradigm of exact conditioning as an intuitive and powerful way of conditioning on observations in probabilistic programs. This is contrasted with likelihood-based scoring known from languages such as Stan. We study exact conditioning in the cases of discrete and Gaussian probability, presenting prototypical languages for each case and giving semantics to them. We make use of categorical probability (namely Markov and CD categories) to give a general account of exact conditioning, which avoids limits and measure theory, instead focusing on restructuring dataflow and program equations. The correspondence between such categories and a class of programming languages is made precise by defining the internal language of a CD category. [ABSTRACT FROM AUTHOR]

Background: Happiness is crucial for human wellbeing. Nursing students encounter distinct challenges such as stress, burnout, and emotional exhaustion, which can negatively impact their mental health. Cultural and societal factors also influence happiness. Objective: This study conducted a comparative analysis of Big Five personality traits and emotional regulation (ER) as predictors of happiness among nursing students in Saudi Arabia and Jordan. Methods: This cross‐sectional study included 739 nursing students from Jordan and Saudi Arabia who were selected using a multistage sampling technique. The instruments utilized in this study were the short version of the Big Five Inventory for assessing personality, Oxford Happiness Inventory for measuring happiness levels, and Emotional Regulation Questionnaire for evaluating ER. To identify the predictors of student happiness, stepwise regression analysis was conducted, and cross‐country comparisons were made using a "pool analysis" method. Results: The findings indicated that 62.1% of the participants reported moderate levels of happiness, whereas 36.0% reported high levels. There were significant differences in happiness levels between Jordan and Saudi Arabia (p = 0.003), with Jordanian students reporting lower happiness levels. In Saudi Arabia, there were significant variations based on age (p = 0.049) and academic year (p = 0.013). Multiple regression analysis revealed that higher agreeableness, extraversion, and conscientiousness were positively associated with happiness while openness had a weak association. Conversely, higher Neuroticism, being in Jordan, and being male were negatively associated with happiness. Nominal regression analysis indicated that extraversion and agreeableness are significant predictors of higher levels of happiness, whereas neuroticism is associated with lower levels of happiness. Furthermore, males and non‐Saudis were more likely to report lower levels of happiness. Conclusion: This study revealed notable determinants of happiness among nursing students in Saudi Arabia and Jordan. ER, Big Five personality traits, and demographic factors play influential roles. Overall, the robust regression model emphasized the dependability of these findings, providing valuable insights for nursing education and interventions aimed at improving student wellbeing. From a practical standpoint, these findings can guide the development of personalized mental health support programs and interventions designed to enhance the happiness and wellbeing of nursing students. [ABSTRACT FROM AUTHOR]

Renewable energy sources–based power systems are increasing rapidly every year with higher chances of destabilization and low power quality due to harmonics, subharmonics, and interharmonics. The elimination of the root causes of these harmonics is difficult because harmonics are generated at different levels due to various electronic components. However, the accurate estimation of power signal harmonic can be done and eliminated with a counter signal. Therefore, in this paper, the evolutionary mating heuristic is implied to accurately estimate the parameters of power signal harmonics. The proposed heuristic was tested under multiple scenarios to accurately estimate the phase and amplitude parameters of power signal harmonics at various noise levels. The tuning of the evolutionary mating heuristic is carried out for encountering predator probability and crossover probability Epp <0.8, Cp <0.9. The simulation analysis depicts that the best fitness achieved by the proposed heuristic for noise levels (no) 104, 78, 52, 26, and 13 dB are 2.8169e−11, 9.6969e−09, 3.7703e−06, 1.3501e−03, and 2.8624e−02, respectively, for iteration I = 1249. The comparative analysis shows that the proposed heuristic performance is significantly better than other heuristics. [ABSTRACT FROM AUTHOR]

In opportunistic network, the regular connectivity of nodes and their individual conditions significantly influence message transmission. To address this, we propose an improved spray and wait routing algorithm based on stable transmission capacity evaluation of nodes (referred to as STCESW), which is derived from traditional Prophet and spray and wait algorithms but surpasses them. STCESW incorporates network models that consider node connection stability and transmission capacity, aiming to enhance the update and punishment formulas for node delivery probability. Furthermore, it combines the residual message buffer size of nodes with the angle between motion directions of nodes to determine more efficient and extensive message spraying in the network. The simulation results clearly indicate that STCESW significantly outperforms the other three enhanced algorithms in both SPMBM and RWP. It demonstrates its robust performance in terms of delivery probability, showing an increase ranging from 2% to 87% across diverse node buffer sizes or simulation time intervals. Additionally, it compromises slightly on delivery latency while maintaining relatively stable message latency and buffer time. [ABSTRACT FROM AUTHOR]

Differential evolution (DE) has attracted widespread attention due to its outstanding optimization performance and ease of operation, but it cannot avoid the dilemmas of premature convergence or stagnation when faced with complex optimization problems. To reduce the probability of such difficulties for DE, we sort out the factors that influence the balance between global exploration and local exploitation in the DE algorithm, and we design a novel DE variant (abbreviated as PISRDE) by integrating the corresponding influence factors through a periodic intervention mechanism and a systematic regulation mechanism. The periodic intervention mechanism divides the optimization operations of PISRDE into routine operation and intervention operation, and it balances global exploration and local exploitation at the macro level by executing the two operations alternately. The systematic regulation mechanism treats the involved optimization strategies and parameter settings as an organic system for targeted design, to balance global exploration and local exploitation at the meso or micro level. To evaluate and verify the optimization performance of PISRDE, we employ seven DE variants with excellent optimization performance to conduct comparison experiments on the IEEE CEC 2014 and IEEE CEC 2017 benchmarks. The comparison results indicate that PISRDE outperforms all competitors overall, and its relative advantage is even more significant when dealing with high-dimensional and complex optimization problems. Schematic design philosophy of PISRDE [ABSTRACT FROM AUTHOR]

Background: Cochlear synaptopathy is a disorder where auditory perceptual impairments, such as speech perception in noise and tinnitus, may not be accurately reflected by audiometric thresholds, even if the audiogram appears normal. It is proposed that the connections between hair cells and the auditory nerve are more susceptible to sound and aging damage than the cochlea's hair cells. Cochlear synaptopathy can be present in ears with normal audiograms and undamaged hair cells, leading to hidden hearing loss. This study aims to construct electrophysiological and behavioral auditory parameters associated with persons exposed to loudness and having normal audiograms and auditory complaints to identify hidden hearing loss. Results: A case–control study was done with forty participants with a documented history of exposure to loud sounds and various auditory complaints, compared to a control group of forty persons who had all been confirmed to have normal audiograms. The chosen behavioral core tests comprised the speech intelligibility in noise test (SPIN), gaps detection in noise (GIN test), and pitch pattern sequence test (PPS). The electrophysiological measures utilized in the study were the auditory brainstem response test (ABR) and electrocochleography (ECochG). The SPIN, PPS, and GIN test results demonstrated statistically significant disparities between the control and case groups. The amplitude ratio of wave I to wave V in ABR and the ratio of EcochG AP to SP demonstrated a statistically significant variance between the two groups. The SPIN test exhibited the highest AUC, signifying its superior diagnostic capability in identifying hidden hearing loss. Conclusion: The present study has shown that the SPIN, as a behavioral test, and the EcochG AP amplitude measure, as an electrophysiological test, provide the greatest auditory diagnostic capability for identifying cochlear synaptopathy. Wave I amplitude in the auditory brainstem response (ABR) and the SP/AP ratio in electrocochleography (EcochG) are promising non-behavioral measures of cochlear synaptopathy or hidden hearing loss. [ABSTRACT FROM AUTHOR]

We propose the linearly adaptive cross entropy loss function. This is a novel measure derived from the information theory. In comparison to the standard cross entropy loss function, the proposed one has an additional term that depends on the predicted probability of the true class. This feature serves to enhance the optimization process in classification tasks involving one-hot encoded class labels. The proposed one has been evaluated on a ResNet-based model using the CIFAR-100 dataset. Preliminary results show that the proposed one consistently outperforms the standard cross entropy loss function in terms of classification accuracy. Moreover, the proposed one maintains simplicity, achieving practically the same efficiency to the traditional cross entropy loss. These findings suggest that our approach could broaden the scope for future research into loss function design. [ABSTRACT FROM AUTHOR]

We examine the gender gap in faculty promotion at the University of Geneva. After building a new measure of research quality that has no gender bias (i.e. men and women have, on average, the same level of research quality after we control for disciplines), we find that conditional on research quality, discipline and place where the PhD was obtained, women are 11 percent less likely to get promoted. The gender gap is almost three times larger for promotion from assistant to associate professor, suggesting that the mechanism at play is stronger for junior faculty. The gender gap is explained by the fact that an equal increase in research quality leads to a smaller increase in women's probability of promotion. [ABSTRACT FROM AUTHOR]

This paper studies the bounded confidence model on growing fully-mixed populations. In this model, in addition to the usual opinion clusters, significant secondary clusters of smaller size appear systematically, while those secondary clusters appear erratically and include much fewer agents when the population is fixed. Through simulations, we derive the bifurcation diagram of the growing population model and compare it to the diagram obtained with an evolving probability density instead of agents, and with their equivalent having a fixed population. Our tests, when changing the usual bounded confidence function into a smooth bounded confidence function, suggest that these secondary clusters are mainly generated by a different mechanism when the population is growing than when it is fixed. [ABSTRACT FROM AUTHOR]

Background: In recent years, limited studies have evaluated the development of cultural awareness, sensitivity, skills, communication and competence among nursing students using different models and curricula. Objectives: This study aimed to evaluate the effectiveness of a new internationally developed curriculum for transcultural nursing education. Methods: This mixed methods study was conducted on nursing students (n = 83) who attended a transcultural nursing course from 2021 to 2022 during the fall semester. A paired samples test was used to compare total scores, and the related-samples Wilcoxon signed-rank test was used to compare subscale scores. Results: The vast majority (94.0%) of the participants mentioned Islam as their religion. Turkish was the mother tongue of 91.6% of them, while 10.8% were able to speak English and 6.0% were able to speak Kurdish fluently. The mean score for the achievement of cultural competence subdimension posttest was significantly greater (p < 0.001). Posttest mean scores for challenges and barriers in providing culturally competent care subdimensions were significantly lower (p = 0.003). The mean score on the culturally sensitive communication subdimension pretest was 21.00 ± 4.76, and the mean score on the posttest increased to 23.02 ± 6.05, which was a statistically significantly greater difference (p = 0.024). According to the qualitative results of our study, five main themes were analyzed: transcultural nursing as an opportunity, transcultural nursing as a didactic process, transcultural nursing as a professional field, transcultural care as a safe environment, and transcultural care as an obligation. Conclusions: In this study, after a semester of continuing education, nursing students developed respect for cultural diversity, cultural competence, and culturally sensitive communication. [ABSTRACT FROM AUTHOR]

Background: Osteoporosis is a common condition that increases the risk of fracture and mortality. In Taiwan, clinical guidelines recommend pharmaceutical therapy for patients with a T-score of ≤ − 2.5; however, Taiwan's National Health Insurance (NHI) only covers these medications for those with a history of fragility fractures. This gap in coverage necessitates a discussion of out-of-pocket treatment options. To address this, we provided an integrated care program with patient education and shared decision-making by nurse case managers specializing in osteoporosis. We evaluated whether education by nurse case managers influences patients with a T-score ≤ − 2.5, who are not covered by the NHI, to choose out-of-pocket pharmaceutical therapy. Methods: We retrospectively reviewed medical records of patients who underwent bone density scanning at our hospital between January 2014 and December 2021. We identified 4,462 patients with a T-score of ≤ − 2.5 who were ineligible for NHI-covered anti-osteoporotic therapy and analyzed trends in out-of-pocket medication use. Since the integrated care program began in 2018, we evaluated whether education by nurse case managers between 2018 and 2021 influenced patients' decisions to pay out-of-pocket for therapy. After the implementation of the integrated care program, we identified 2,910 patients with a T-score ≤ -2.5 who were ineligible for NHI-covered anti-osteoporotic therapy. Of these, 640 opted for out-of-pocket treatment, while 2,270 chose conservative care. After a 1:1 propensity score match based on age and sex, logistic regression was used to analyze the impact of nurse case manager education on these decisions. Results: Between 2014 and 2021, 888 of the 4,462 patients chose out-of-pocket pharmaceutical therapy. Before the implementation of the integrated care program and patient education by nurse case managers (2014–2017), 16% of the patients opted to pay out-of-pocket for anti-osteoporotic therapy. After the program was implemented (2018–2021), the rate increased significantly to 22% (P < 0.001). A multivariate logistic regression model showed that a history of osteoarthritis (adjusted odds ratio = 1.576; P = 0.009) and education provided by the nurse case managers (adjusted odds ratio = 5.044; P < 0.001) were significantly associated with choosing out-of-pocket therapy. Conclusions: Education from nurse case managers significantly increased the likelihood of patients choosing out-of-pocket anti-osteoporotic therapy in our hospital, thereby bridging the gap between clinical guidelines and NHI reimbursement criteria. [ABSTRACT FROM AUTHOR]

To investigate the potential lane‐changing collision risks that may arise between vehicles during lane changes and those in the original lane, a model for vehicle lane‐changing collision risk is constructed specifically for this scenario, and a research analysis is conducted. First, based on vehicle trajectory data, a sample set capturing the relationships between vehicles traveling in a straight line and those changing lanes laterally is extracted and built. Interpolation methods are then applied to fill in missing values, outliers are eliminated, and data noise is smoothed during preprocessing. After preprocessing, a total of 468 vehicle pairs and 265,392 data points are obtained. Second, a real‐time collision time model is established based on the preprocessed data, and collision risk probabilities are calculated accordingly. Then, the collision risks are classified into four levels based on whether the vehicle on the side actually changes lanes and the severity of the collision risks. Finally, a light gradient boosting machine (LightGBM) learning method is adopted to predict the risk levels and analyze the main factors that significantly impact the severity of collision risks. The results indicate that the longitudinal distance between the target vehicle and the preceding vehicle is the most critical influencing factor, followed by the speed of the target vehicle itself, and then the speed difference between the target vehicle and the preceding vehicle. The influence of other factors is relatively similar and does not have a significant impact. [ABSTRACT FROM AUTHOR]

This paper introduces a new probability distribution called the mixture symmetric gamma (MSG) distribution, which is defined as a mixture of two symmetric gamma distributions. Its statistical properties and applications are explored. We first examine its mathematical properties, including the possible shapes of the corresponding probability density function, as well as the moments, and the moment‐generating function. We then look at parameter estimation using various frequentist and Bayesian methods, such as moment estimation, maximum likelihood method, least‐squares method, and Bayesian approaches. In addition, the prediction of future observations under the MSG model is extensively covered, considering both frequentist and Bayesian perspectives, including median prediction, best unbiased prediction, and Bayesian prediction. A comprehensive simulation study is conducted to evaluate the performance of the proposed estimation and prediction techniques. Finally, the practical applicability of the MSG model is demonstrated through the analysis of four real‐world datasets. It is shown to outperform several well‐known competing models in terms of goodness‐of‐fit. The results highlight the inherent simplicity, efficiency, robustness, and intuitive interpretability of the MSG distribution, making it a compelling choice for modeling data with a symmetric pattern, with potential applications in diverse domains. [ABSTRACT FROM AUTHOR]

Background: This study aims to analyze the historical trends of inflammatory bowel disease (IBD) burden in the elderly from 1990 to 2021 and forecast future trends up to 2051. Methods: Data from the Global Burden of Disease Study 2021 were utilized. Age-standardized rates (ASR) for incidence, prevalence, mortality, and disability-adjusted life years (DALYs) were calculated. Estimated annual percentage changes (EAPCs) were computed to quantify temporal trends. A Bayesian Age-Period-Cohort model was employed to project future trends. Results: From 1990 to 2021, the global number of elderly IBD increased from 573,500 to 1,278,190. The age-standardized incidence rate (ASIR) rose from 8.01 to 8.77 per 100,000, while the age-standardized prevalence rate (ASPR) slightly decreased from 118.14 to 117.29 per 100,000. Death number increased from 14,400 to 33,490, but the age-standardized mortality rate decreased from 3.21 to 2.84 per 100,000. DALYs increased from 324,100 to 683,750, with the age-standardized DALYs rate declining from 68.78 to 60.88 per 100,000. Significant geographical variations were observed, with high Socio-demographic Index regions showing the highest burden. Projections suggest that by 2051, elderly IBD prevalence number may reach 2,316,000, with ASIR and ASPR potentially rising after 2035 and 2042, respectively. Deaths and DALYs are projected to increase to 75,000 and 1,401,000 respectively, despite continued declines in ASRs. Conclusion: The absolute burden of IBD in the elderly population is projected to increase substantially by 2051, despite decreasing ASRs. These findings underscore the need for tailored healthcare strategies and resource allocation to address the growing challenge of elderly IBD globally. [ABSTRACT FROM AUTHOR]

Background: Research to date suggests that physical activity (PA) can buffer menopausal symptoms and support well-being, but there is limited evidence on the link between PA and menopausal symptoms in the United Kingdom, and no study has assessed how PA affects well-being through menopausal symptoms and three psychosomatic factors (i.e. depression, anxiety and stress). Objectives: This study investigated whether PA affects well-being through menopausal symptoms and psychosomatic factors. This study focuses on how PA influences working women with menopause. Design: A cross-sectional design based on the STROBE (i.e. Strengthening the Reporting of Observational Studies in Epidemiology) checklist was adopted. Methods: The participants were 324 working women in England. An online self-reported questionnaire was utilised to gather data through Qualtrics. The data were analysed with path analysis through structural equation modelling, and sensitivity analyses were performed to avoid or reduce statistical bias. Results: PA had a negative effect on menopausal symptoms (β = −0.21; p < 0.001) but a positive effect on well-being (β = 0.19; p < 0.001). Menopausal symptoms had a negative indirect effect on well-being, but PA had a positive indirect effect on well-being through menopausal symptoms and the three psychosomatic factors. Conclusion: PA was positively associated with well-being but negatively associated with menopausal symptoms. Menopausal symptoms may lower well-being through anxiety, depression and stress, but PA can be associated with better well-being through depression, anxiety and stress. Plain language summary: The influence of physical activity on well-being through menopausal symptoms, depression, anxiety, and stress Why was the study done? Studies have assessed the potential influence of physical activity on menopausal symptoms among women, but no study in the United Kingdom has examined this relationship. Although the positive effect of physical activity on well-being is well researched and documented, no study has explored how it is mediated by menopausal symptoms and psychosomatic factors (i.e. stress, anxiety, and depression). Evaluation of this potential mediation is needed to improve stakeholders' understanding of the best ways to manage menopause at work. What did the researchers do? The researchers designed an online survey and used Qualtrics to distribute it among 324 working women with menopause in England. They used the appropriate statistical analysis technique to ascertain how the effect of physical activity on well-being is mediated by menopausal symptoms and the psychosomatic factors. What did the researchers find? Women who reported higher physical activity experienced fewer menopausal symptoms. Women with higher physical activity reported better well-being through fewer menopausal symptoms and lower stress, anxiety, and depression. Physical activity may help to improve well-being among working menopausal women by lowering menopausal symptoms, stress, anxiety, and depression. What do the findings mean? Working women can maintain well-being and experience less menopausal symptoms, stress, anxiety, and depression if they participate in physical activities. Organizations can manage menopause by rolling out workplace programmes encouraging employees to regularly participate in physical activities. [ABSTRACT FROM AUTHOR]

Bayesian inference gets its name from Bayes's theorem , expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function. But Bayesian inference uses all of probability theory, not just Bayes's theorem. Many hypotheses of scientific interest are composite hypotheses , with the strength of evidence for the hypothesis dependent on knowledge about auxiliary factors, such as the values of nuisance parameters (e.g., uncertain background rates or calibration factors). Many important capabilities of Bayesian methods arise from use of the law of total probability, which instructs analysts to compute probabilities for composite hypotheses by marginalization over auxiliary factors. This tutorial targets relative newcomers to Bayesian inference, aiming to complement tutorials that focus on Bayes's theorem and how priors modulate likelihoods. The emphasis here is on marginalization over parameter spaces—both how it is the foundation for important capabilities, and how it may motivate caution when parameter spaces are large. Topics covered include the difference between likelihood and probability, understanding the impact of priors beyond merely shifting the maximum likelihood estimate, and the role of marginalization in accounting for uncertainty in nuisance parameters, systematic error, and model misspecification. [ABSTRACT FROM AUTHOR]

In this work, we analyze the local certification of unitary quantum channels, which is a natural extension of quantum hypothesis testing. A particular case of a quantum channel operating on two systems corresponding to product states at the input, is considered. The goal is to minimize the probability of the type II error, given a specified maximum probability of the type I error, considering assistance through entanglement with auxiliary systems. Our result indicates connection of the local certification problem with a product numerical range of unitary matrices. We show that the optimal local strategy does not need usage of auxiliary systems and requires only single round of one-way classical communication. Moreover, we compare local and global certification strategies and show that typically local strategies are optimal, yet in some extremal cases, where global strategies make no errors, local ones may fail miserably. Finally, some application for local certification of von Neumann measurements are discussed as well. [ABSTRACT FROM AUTHOR]

Large language models have demonstrated impressive capabilities in many domains. But they sometimes generate irrelevant or nonsensical text, or produce outputs that deviate from the provided input, an occurrence commonly referred to as hallucination. To mitigate this issue, we introduce a novel decoding method that incorporates both factual and hallucination prompts (DFHP). It applies contrastive decoding to highlight the disparity in output probabilities between factual prompts and hallucination prompts. Experiments on both multiple-choice and text generation tasks show that our approach significantly improves factual accuracy of large language models without additional training. On the TruthfulQA dataset, the DFHP method significantly improves factual accuracy of the LLaMA model, with an average improvement of 6.4% for the 7B, 13B, 30B, and 65B versions. Its high accuracy in factuality makes it an ideal choice for high reliability tasks like medical diagnosis and legal cases. [ABSTRACT FROM AUTHOR]

Digital multi-beam synthesis technology is generally used in the on-orbit satellite-based Automatic Dependent Surveillance–Broadcast (ADS-B) system. However, the probability of successfully detecting aircraft with uneven surface distribution is low. An adaptive digital beamforming method is proposed to improve the efficiency of aircraft detection probability. The current method has the problem of long operation time and is not suitable for on-orbit operation. Therefore, this paper proposes an adaptive beamforming method for the ADS-B system based on a fully connected neural network (FCNN). The simulation results show that the calculation time of this method is about 2.6 s when more than 15,000 sets of data are inputted, which is 15–80% better than the existing methods. Its detection success probability is 10% higher than those of existing methods, and it has better robustness against large amounts of data. [ABSTRACT FROM AUTHOR]

Defensive traits are hypothesized to benefit prey by reducing predation risk from a focal predator but come at a cost to the fitness of the prey. Variation in the expression of defensive traits is seen among individuals within the same population, and in the same individual in response to changes in the environment (i.e., phenotypically plastic responses). It is the relative magnitude of the cost and benefit of the defensive trait that underlies the defensive trait expression and its consequences to the community. However, whereas the cost has received much attention in ecological research, the benefit is seldom examined. Even in a defensive trait as extensively studied as vigilance, there are few studies of the purported benefit of the behavior, namely that vigilance enhances survival. We examined whether prey vigilance increased survival and quantified that benefit in a natural system, with white‐tailed deer (Odocoileus virginianus) experiencing unmanipulated levels of predation risk from Florida panther (Puma concolor coryi). Deer that spent more time vigilant (as measured by head position using camera trap data) had a higher probability of survival. Indeed, an individual deer that was vigilant 75% of the time was more than three times as likely to be killed by panthers over the course of a year than a deer that was vigilant 95% of the time. Our results therefore show that within‐population variation in the expression of a defensive trait has profound consequences for the benefit it confers. Our results provide empirical evidence supporting a long‐held but seldom‐tested hypothesis, that vigilance is a behavior that reduces the probability of predation and quantifies the benefit of this defensive trait. Our work furthers an understanding of the net effects of a trait on prey fitness and predator–prey interactions, within‐population variation in traits, and predation risk effects. [ABSTRACT FROM AUTHOR]

Background: The Universal Infant Free School Meal (UIFSM) policy was introduced in 2014/15 in England and Scotland for schoolchildren aged 4–7 years, leading to an increase in school meal uptake. UK school meals are known to be healthier and less industrially processed than food brought from home (packed lunches). However, the impact of the UIFSM policy on the quantity of ultra-processed food (UPF) consumed at school during lunchtime is unknown. This study aimed to evaluate the impact of the UIFSM policy on lunchtime intakes of UPF in English and Scottish schoolchildren. Methods: Data from the UK National Diet and Nutrition Survey (2008–2019) were used to conduct a difference-in-difference (DID) natural experiment. Outcomes included school meal uptake and the average intake of UPF (% of total lunch in grams (%g) and % total lunch in Kcal (%Kcal)) during school lunchtime. The change in the outcomes before and after the introduction of UIFSM (September 2014 in England, January 2015 in Scotland) in the intervention group (4–7 years, n = 835) was compared to the change in an unexposed control group (8–11 years, n = 783), using linear regression. Inverse probability weights were used to balance characteristics between intervention and control groups. Results: Before UIFSM, school meal uptake and consumption of UPFs were similar in the intervention and control groups. The DID model showed that after UIFSM, school meal uptake rose by 25%-points (pp) (95% CI 14.2, 35.9) and consumption of UPFs (%g) decreased by 6.8pp (95% CI -12.5,-1.0). Analyses indicated this was driven by increases in minimally processed dairy and eggs, and starchy foods, and decreases in ultra-processed salty snacks, bread and drinks. The differences were larger in the lowest-income children (-19.3 UPF(%g); 95% CI -30.4,-8.2) compared to middle- and high-income children. Analyses using UPF %Kcal had similar conclusions. Conclusions: This study builds on previous evidence suggesting that UIFSM had a positive impact on dietary patterns, showing that it reduced consumption of UPFs at school lunchtime, with the greatest impact for children from the lowest-income households. Universal free school meals could be an important policy for long term equitable improvements in children's diet. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for solving the first-passage time probability problem of nonlinear stochastic dynamic systems. The safe domain boundary is exactly imposed into the radial basis function neural network (RBF-NN) architecture such that the solution is an admissible function of the boundary-value problem. In this way, the neural network solution can automatically satisfy the safe domain boundaries and no longer requires adding the corresponding loss terms, thus efficiently handling structure failure problems defined by various safe domain boundaries. The effectiveness of the proposed method is demonstrated through three nonlinear stochastic examples defined by different safe domains, and the results are validated against the extensive Monte Carlo simulations (MCSs). [ABSTRACT FROM AUTHOR]

We introduce a robust likelihood approach to inference for paired multiple binary endpoints data. One can easily implement the methodology without dealing with the model that incorporates a large number of joint probabilities of no direct relevance to the inference of interest. We present the robust score test statistic for testing the equality of two treatment effects to exemplify the utility and simplicity of the method. Our novel technique is applicable when patients have different numbers of endpoints and for unpaired endpoints. The extension of our robust approach to multiple endpoints data with more categories is straightforward. We use simulations and real data analysis to highlight the efficacy of our robust procedure. [ABSTRACT FROM AUTHOR]

This paper solves the finite-time extended dissipative fault estimate problem for discrete-time Markov jump neural networks based on an event-triggered approach in fully/partially known transition probability cases. Firstly, the systems are expanded into new systems treating sensor faults as states. Based on the proposed event-triggered scheme and an intermediate variable, an event-triggered intermediate observer is designed to estimate states, faults of actuator and sensor, and the intermediate variable, simultaneously. Next, the finite-time stability of error systems with extended dissipativity is analyzed, and the observer gains are shown in fully/partially known transition probability case, respectively, whose existence conditions are given. Finally, an example is given to illustrate the feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

Objectives. To assess the relationship between doula utilization and health outcomes of females enrolled in Medicaid-affiliated plans in the United States. Methods. In this retrospective, observational cohort study, we used Medicaid claims data from a national health insurer to compare health outcomes between females who used and who did not use a doula (2014–2023). We conducted propensity score matching using a 1:1 case‒control match, without replacement, and fit logistic regressions to analyze the relative risks for maternal health outcomes. Results. The study population included 722 matched pairs with and without a doula. Results indicate females with doulas had a 47% lower risk of cesarean delivery and a 29% lower risk of preterm birth, and were 46% more likely to attend a postpartum checkup (all differences P <.05). Conclusions. Doula care is associated with improved health outcomes among Medicaid enrollees. Public Health Implications. Doulas have garnered increasing interest from policymakers as a strategy to address increasing trends in maternal morbidity and persistent health disparities. This study provides evidence from Medicaid enrollees across the United States that doula care can improve maternal health. (Am J Public Health. 2024;114(11):1275–1285. https://doi.org/10.2105/AJPH.2024.307805) [ABSTRACT FROM AUTHOR]

Asymmetrical probability models are helpful for analyzing skewed data sets since they allow you to describe the form of the distribution and anticipate the chance of extreme events. This article defines a novel approach to continuous moment exponential distribution called the exponentiated generalized moment exponential model. The extension has two additional parameters accounting for the distribution's shape. We extend this distribution probability density, cumulative distribution, hazard rate, and survival functions and establish different key statistical properties. Parameter estimation is obtained using different procedures, notably maximum likelihood estimation, least square, and Bayesian methods. A Monte Carlo simulation experiment is conducted to assess parameter performance and indicator risk measures. This article examines two distinct actual data sets in order to highlight the significance of the proposed model as well as its application in a variety of settings. The new model is compared to a large number of well-known extensions that were developed by other businesses. [ABSTRACT FROM AUTHOR]

Background Single-legged hop tests have been widely used to assess performance-based outcomes after anterior cruciate ligament (ACL) reconstruction. Traditional single, triple, or 6-meter (6m) timed hop tests only measure distance or time as the principal variables, neglecting other variables, such as individual hop distances within a series of hops, flight time, and stance time. The development of portable instrumented pressure walkways has made it possible to collect parameters such as hop velocity, flight time, stance time, distance, and pressure outside of a laboratory setting. However, the reliability of instrumented pressure walkways in measuring spatial and temporal variables during single-legged hop tests is unknown. This study aimed to determine if the Zeno walkway can reliably measure spatiotemporal (ST) characteristics of hop tests. Study Design Cross-Sectional Study Methods Individuals (n=38) in this cross-sectional study performed single, triple, and 6m hop tests on a pressure-sensitive Zeno walkway. Twenty-one participants completed follow-up testing between one and 14 days later. Intraclass correlation coefficients (ICC(3,k)) were used to assess test-retest reliability of ST variables. The accuracy of vertical jump height and 6m hop timing were also measured. Results All ST variables demonstrated excellent test-retest reliability (ICC > 0.86) with small minimal detectable change (MDC) values during single-legged hop tests. Six-meter hop time and jump height during a bilateral drop jump were also accurately measured by the walkway. Conclusion An instrumented pressure walkway is a novel tool to reliably assess non-traditional parameters of clinically relevant hop and jump tests such as flight time, stance time, and jump height after lower extremity injury, surgery, and rehabilitation. Level of Evidence 3b [ABSTRACT FROM AUTHOR]

The modeling and analysis of epidemic processes in networks have attracted much attention over the past few decades. A major underlying assumption is that the recovery process and infection process are homogeneous, allowing the associated theoretical studies to be conducted in a convenient manner. However, the recovery and infection processes usually exhibit heterogeneous rates in the real world, which makes it difficult to characterize the general relations between the dynamics and the underlying network structure. In this work, we focus on the susceptible–infected–susceptible (SIS) epidemic process with heterogeneous recovery rates in a finite-size complete graph. Specifically, we study the metastable-state statistical properties of SIS epidemic dynamics with two different nodal recovery rates in complete graphs. We propose approximate solutions to the metastable-state expectation and the variance in the number of infected nodes within the framework of the mean-field approximation method. We also derive several upper and lower bounds of the steady-state probability that a node is in the infected state. We verify the proposed approximate solutions of the mean and variance via simulations. This work provides insights into the fluctuations in the statistical properties of epidemic processes with complex dynamical behaviors in networks. [ABSTRACT FROM AUTHOR]

This paper presents a cognitive radio (CR)-enabled symbiotic ambient backscatter communication (AmBC) system with the help of a zero-energy reconfigurable intelligent surface (zeRIS). An adaptive transmission (AT) strategy for the zeRIS is devised based on the amount of harvested energy. Specifically, when energy reserve is insufficient, the zeRIS merely reflects signals without any phase adjustments (PAs), whereas under sufficient energy conditions, it reflects signals following precise PAs. Moreover, a segmented zeRIS is adopted by taking primary transmission (PT) and backscatter transmission (BT) into account. Following this, the coexistence outage probability and ergodic capacity are derived to assess the reliability and effectiveness of the proposed model, respectively. Their asymptotic performance is analyzed to gain insightful observations. Finally, simulation results are provided to verify the accuracy of the theoretical analysis, confirming that AT offers improved reliability, system rate, and energy efficiency over non-adaptive transmission. Furthermore, CR-aided AT demonstrates superior energy efficiency compared to non-CR-assisted AT. It is also crucial to note that the allocation of reflective elements between PT and BT must be reasonably managed to satisfy specific system requirements. [ABSTRACT FROM AUTHOR]

With the development of high-speed analog-to-digital converter (ADC)-based wireline receivers, the Mueller–Muller clock and data recovery (MM-CDR) circuit has garnered increasing attention. But in the design stage, evaluating the loop performance of MM-CDR circuits in ADC-based wireline receivers is challenging due to the absence of a linearized model for a Mueller–Muller phase detector (MMPD). In this paper, a linearized model of the MMPD is proposed by analyzing the output probability of the MMPD in different transition patterns with random jitter injection, and the model is combined with an entire MM-CDR system to analyze the performance of the MM-CDR loop. Analysis of the linearized model and corresponding simulations indicate that when the reference voltage level in the MMPD is set equal to the amplitude of the average crossing voltage at the intersection of 011 and 110 patterns, the MMPD can obtain the maximum gain, which is determined by jitter, and the jitter transfer function and jitter tolerance can achieve optimum performance. [ABSTRACT FROM AUTHOR]

An outlier probability is the probability that an observation is an outlier. Typically, outlier detection algorithms calculate real-valued outlier scores to identify outliers. Converting outlier scores into outlier probabilities increases the interpretability of outlier scores for domain experts and makes outlier scores from different outlier detection algorithms comparable. Although several transformations to convert outlier scores to outlier probabilities have been proposed in the literature, there is no common understanding of good outlier probabilities and no standard approach to evaluate outlier probabilities. We require that good outlier probabilities be sharp, refined, and calibrated. To evaluate these properties, we adapt and propose novel measures that use ground-truth labels indicating which observation is an outlier or an inlier. The refinement and calibration measures partition the outlier probabilities into bins or use kernel smoothing. Compared to the evaluation of probability in supervised learning, several aspects are relevant when evaluating outlier probabilities, mainly due to the imbalanced and often unsupervised nature of outlier detection. First, stratified and weighted measures are necessary to evaluate the probabilities of outliers well. Second, the joint use of the sharpness, refinement, and calibration errors makes it possible to independently measure the corresponding characteristics of outlier probabilities. Third, equiareal bins, where the product of observations per bin times bin length is constant, balance the number of observations per bin and bin length, allowing accurate evaluation of different outlier probability ranges. Finally, we show that good outlier probabilities, according to the proposed measures, improve the performance of the follow-up task of converting outlier probabilities into labels for outliers and inliers. [ABSTRACT FROM AUTHOR]

The article considers the Monte Carlo method as one of the possible techniques for calculating the error of a measuring system, which consists of several elements, each of which measures some quantity with its own independent error. Due to its features, the method can be extended to modeling any process affected by random variables. The simplicity of application and the calculation algorithm makes it possible to easily calculate the total error of the system and the probability of its occurrence, while avoiding inflated and unlikely values. The article substantiates the application of the Monte Carlo method for calculating the error of the measuring system, reveals the nature of the distribution of errors, and calculates the value of the error depending on the probability of its occurrence. It is shown that with probability of 0.95 the total error of the system can be taken to be 3 times smaller than the maximum possible error. References 8, figures 2, table 1. [ABSTRACT FROM AUTHOR]

Do credit rating agencies (CRAs) learn from the options market? We examine this question by exploring the relation between options trading activity and credit rating accuracy. We find that as options trading volume increases, credit ratings become more responsive to expected credit risk and exhibit greater ability to predict future defaults. We also find that CRAs rely more on the options market as a source of ratings-related information when firm default risk is higher, options trading is more informative, manager-provided information is of lower quality, and firm uncertainty is higher. Our results are robust to a number of sensitivity tests, including alternative measures of options trading and credit rating accuracy. We reach similar inferences using various approaches to address endogeneity issues, including difference-in-difference analyses and an instrumental variables approach. Overall, our findings are consistent with the view that CRAs incorporate unique information from the options market into their rating decisions which, in turn, improves credit rating accuracy. This paper was accepted by Brian Bushee, accounting. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.4980. [ABSTRACT FROM AUTHOR]

The study of specific physiological processes from the perspective of network physiology has gained recent attention. Modeling the global information integration among the separated functionalized modules in structural and functional brain networks is a central problem. In this article, the preferentially cutting-rewiring operation (PCRO) is introduced to approximatively describe the above physiological process, which consists of the cutting procedure and the rewiring procedure with specific preferential constraints. By applying the PCRO on the classical Erdös-Rényi random network (ERRN), three types of isolated nodes are generated, based on which the common leaves (CLs) are formed between the two hubs. This makes the initially homogeneous ERRN experience drastic changes and become heterogeneous. Importantly, a statistical analysis method is proposed to theoretically analyze the statistical properties of an ERRN with a PCRO. Specifically, the probability distributions of these three types of isolated nodes are derived, based on which the probability distribution of the CLs can be obtained easily. Furthermore, the validity and universality of our statistical analysis method have been confirmed in numerical experiments. Our contributions may shed light on a new perspective in the interdisciplinary field of complexity science and biological science and would be of great and general interest to network physiology. [ABSTRACT FROM AUTHOR]

In association football, predicting the likelihood and outcome of a shot at a goal is useful but challenging. Expected goal (xG) models can be used in a variety of ways including evaluating performance and designing offensive strategies. This study proposed a novel framework that uses the events preceding a shot, to improve the accuracy of the expected goals (xG) metric. A combination of previously explored and unexplored temporal features is utilized in the proposed framework. The new features include; "advancement factor", and "player position column". A random forest model was used, which performed better than published single-event-based models in the literature. Results further demonstrated a significant improvement in model performance with the inclusion of preceding event information. The proposed framework and model enable the discovery of event sequences that improve xG, which include; opportunities built up from the sides of the 18-yard box, shots attempted from in front of the goal within the opposition's 18-yard box, and shots from successful passes to the far post. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation is a growing epidemic in Africa. Anticoagulation, considered the backbone for non-valvular atrial fibrillation (NVAF) management, is limited to warfarin as the mainstay of available anticoagulation therapy in most low- and middle-income countries (LMIC). The optimal time in the therapeutic range (TTR) while on warfarin is essential to avoid bleeding and thromboembolic complications. This study assessed anticoagulation control in patients with NVAF on warfarin in Johannesburg, South Africa. Methods: We conducted a cross-sectional retrospective study on patients with NVAF managed in the Division of Cardiology, at a tertiary-level academic centre in Johannesburg, South Africa, between 1 January 2015 and 31 December 2019. Anticoagulation control for patients with NVAF was assessed by calculating the TTR using the Rosendaal method. Results: The study population comprised 177 patients diagnosed with NVAF. The mean age was 65.0 ± 13.1 years. The median TTR among patients with NVAF was 46% [interquartile range (IQR): 8.7–86.0], and 63 (35.6%) patients with NVAF had a TTR ≥ 70% (optimal anticoagulation control). Patients with poor anticoagulation control (TTR < 70%) were on warfarin for a shorter duration compared with those with optimal anticoagulation control [56 days (IQR: 43–84) vs. 70 days (IQR: 56–140), p = 0.0013]. The mean CHA2DS2-VASc score was 4 ± 1.5, and it did not differ between patients with poor or optimal anticoagulation control. Among the 175 patients with available HAS-BLED scores, 21 (12.0%), 112 (64.0%) and 42 (24.0%) were at a low, moderate, and high risk for bleeding, respectively. Of the 21 patients in the HAS BLED low-risk category, only 4 (19.0%) had a TTR < 70% (p < 0.001). Warfarin toxicity was documented in 13 (7.3%) patients. Conclusion: In our study, a TTR ≥ 70%, suggesting optimal anticoagulation control, was found in only 35.6% of patients with NVAF on warfarin. [ABSTRACT FROM AUTHOR]

Introduction: Although intensive care units (ICUs) are where severe and complicated cases are managed, there is limited evidence on treatment outcomes in Ethiopia. Therefore, this study is aimed at assessing the magnitude and associated factors of mortality among patients with sepsis admitted to ICUs at southern Amhara public hospitals, Ethiopia. Methods: A total of 547 medical records of patients with sepsis admitted to the ICUs at Injibara, Debre Markos, and Debre Tabor hospitals in the past 3 years were retrieved from August 10–31, 2022. Multivariable logistic regression analyses were conducted and adjusted odds ratios (AOR) with a 95% confidence interval (CI) were reported, and a p value < 0.05 was set to declare the significance of the association. Results: In this study, 46.2% (95% CI: 41.7%–50.3%) of patients with sepsis died during their ICU stay. Respiratory, gastrointestinal, and urinary tract infections contributed to 32.3%, 25.8%, and 9.6% of mortality, respectively. Individuals aged 60 and above (AOR: 4.07; 95% CI: 2.23–7.44), those with a Glasgow Coma Scale ≤ 10 at admission (AOR: 11.27; 95% CI: 4.64–27.37), respiratory site of infection (AOR: 5.38; 95% CI: 2.94–9.86), creatinine level > 1.1 mg/dL (AOR: 4.20; 95% CI: 2.33–7.60), vasopressor use (AOR: 3.13; 95% CI:1.66–5.95), initiation of antibiotics 1–3 h after admission (AOR: 2.80; 95% CI: 1.64–4.76), and a hospital stay of more than 20 days (AOR: 3.44; 95% CI: 1.40–8.46) were significantly associated with mortality. Conclusion: Overall, the mortality rate among patients with sepsis admitted to ICUs in southern Amhara public hospitals was high. Mainly, death was attributed to respiratory infections. Elderly patients and those with deteriorated clinical conditions at admission were at higher risk. Therefore, special attention is needed for elderly patients admitted with respiratory infections, antibiotics should be initiated as early as possible, and interventions must be designed to shorten the length of stay in ICUs. [ABSTRACT FROM AUTHOR]

This research validates tropical cyclone (TC) forecasts from the National Centre for Hydro‐Meteorological Forecasting of Vietnam, the Regional Specialized Meteorological Center (RSMC) Tokyo, and global models (the Japanese Meteorological Agency [JMA], global spectral model [GSM], the National Centers for Environmental Prediction [NCEP], Global Forecast System [GFS], and the European Centre for Medium‐Range Weather Forecasts [ECMWF] Integrated Forecasting System [IFS]) for 72 activated TCs over the Bien Dong Sea. The best quality track forecasts come from the IFS and then GFS and GSM, while the GFS provides a good intensity forecast compared to IFS and GSM. The official guidance and model track forecast tend to be slower and leftward compared to observations (negative biases of along and cross‐track errors). Regarding the ECMWF's ensemble track forecast, the strike probability forecast is quite overforecast/overconfident, especially for a lead time of 72 h and at high probabilities. [ABSTRACT FROM AUTHOR]

One of the most important hyper-parameters in duration-dependent Markov-switching (DDMS) models is the duration of the hidden states. Because there is currently no procedure for estimating this duration or testing whether a given duration is appropriate for a given data set, an ad hoc duration choice must be heuristically justified. In this paper, we propose and examine a methodology that mitigates the choice of duration in DDMS models when forecasting is the goal. The novelty of this paper is the use of the asymmetric Aranda-Ordaz parametric link function to model transition probabilities in DDMS models, instead of the commonly applied logit link. The idea behind this approach is that any incorrect duration choice is compensated for by the parameter in the link, increasing model flexibility. Two Monte Carlo simulations, based on classical applications of DDMS models, are employed to evaluate the methodology. In addition, an empirical investigation is carried out to forecast the volatility of the S&P500, which showcases the capabilities of the proposed model. [ABSTRACT FROM AUTHOR]

Background and objectives: Observational studies have established a connection between body mass index (BMI) and an increased risk of cognitive decline. However, a comprehensive investigation into the causal relationships between BMI and cognitive function across diverse age groups, as well as the genetic underpinnings of this relationship, has been notably lacking. This study aims to investigate causality and the shared genetic underpinnings of between BMI and cognitive function by conducting a thorough genomewide analysis, thereby provide valuable insights for developing personalized intervention strategies to promote cognitive health. Methods: Genetic associations between BMI and cognitive function were thoroughly investigated through covariate genetic analysis and chained imbalance score regression, utilizing data from genome-wide association studies (GWAS). Bi-directional Mendelian Randomization (MR) was employed to uncover associations and potential functional genes were further scrutinized through Cross-trait meta-analysis and Summary-data-based MR (SMR). Subsequently, a detailed examination of the expression profiles of the identified risk SNPs in tissues and cells was conducted. Results: The study found a significant negative correlation between BMI and cognitive function (b = -0.16, P = 1.76E-05), suggesting a causal linkage where higher BMI values were predictive of cognitive impairment. We identified 5 genetic loci (rs6809216, rs7187776, rs11713193, rs13096480, and rs13107325) between BMI and cognitive function by cross-trait meta-analysis and 5 genetissue pairs were identified by SMR analysis. Moreover, two novel risk genes TUFM and MST1R were shared by both cross-trait analysis and SMR analysis, which had not been observed in previous studies. Furthermore, significant enrichment of single nucleotide polymorphisms (SNPs) at tissue- and cellspecific levels was identified for both BMI and cognitive function, predominantly within the brain. Conclusion: This study uncovers a causal relationship between BMI and cognitive function, with the discovery of TUFM and MST1R as shared genetic factors associated with both conditions. This novel finding offers new insights into the development of preventative strategies for cognitive decline in obese individuals, and further enhances our understanding of the underlying pathophysiology of these conditions. Furthermore, these findings could serve as a guide for the development of innovative therapeutic approaches to address cognitive decline in obese individuals. [ABSTRACT FROM AUTHOR]

Background: It is unclear how rising obesity among people with HIV (PWH) impacts their risk of type 2 diabetes mellitus (diabetes). We examined associations between HIV, prevalent diabetes and adiposity among South African PWH and their peers without HIV (PWOH). Methods: HIV status was ascertained by antibody testing. Diabetes was defined as current use of oral hypoglycemics, insulin, and/or HbA1c ≥6.5%. Adiposity was measured by body mass index (BMI), waist circumference and waist-to-height ratio. Their associations were examined using sex-stratified multivariable fractional polynomial generalized linear models, reporting adjusted prevalence and prevalence ratios (adjPR). Results: The mean age among 1,254 PWH and 4,381 PWOH was 41 years (95%CI 28, 56). The prevalence of diabetes among males was similar between PWH [11.3% (7.1, 15.5)] and PWOH [9.8% (8.5, 11.1); p=0.740]. By contrast, diabetes prevalence was higher among female PWOH [15.7% (14.4, 17.0)] than female PWH [10.5 (8.3, 12.8)%; adjPR: 0.67 (0.51, 0.82); p<0.001]. This difference was accentuated with obesity but reversed with leanness. At BMI ≥25 kg/m2, female PWH had lower diabetes prevalence [adjPR: 0.58 (0.41, 0.76); p<0.001] than female PHIV. In contrast, at BMI <18 kg/m2, female PWH had higher prevalence [adjPR: 1.72 (−1.53, 4.96); p=0.756] than female PWOH. Conclusion: We found sex-specific differences in the relationship between adiposity and diabetes prevalence by HIV serostatus in South Africa. Notably, females living with obesity and HIV had lower prevalence of diabetes than females living with obesity and without HIV, which may have particular implications for diabetes prevention programs in the region. [ABSTRACT FROM AUTHOR]

The mixture cure rate model (MCM) is the most widely used model for the analysis of survival data with a cured subgroup. In this context, the most common strategy to model the cure probability is to assume a generalized linear model with a known link function, such as the logit link function. However, the logit model can only capture simple effects of covariates on the cure probability. In this article, we propose a new MCM where the cure probability is modeled using a decision tree-based classifier and the survival distribution of the uncured is modeled using an accelerated failure time structure. To estimate the model parameters, we develop an expectation maximization algorithm. Our simulation study shows that the proposed model performs better in capturing nonlinear classification boundaries when compared to the logit-based MCM and the spline-based MCM. This results in more accurate and precise estimates of the cured probabilities, which in-turn results in improved predictive accuracy of cure. We further show that capturing nonlinear classification boundary also improves the estimation results corresponding to the survival distribution of the uncured subjects. Finally, we apply our proposed model and the EM algorithm to analyze an existing bone marrow transplant data. [ABSTRACT FROM AUTHOR]

Background: First-year nursing students are at a critical juncture in their education. They are transitioning from laypersons to healthcare professionals, and students are frequently exposed to medical information in academic settings and through personal research. This exposure can sometimes lead to cyberchondria; improving health literacy and managing health anxiety are critical strategies for reducing the incidence of cyberchondria. Aim: Investigate the mediating effect of health anxiety on cyberchondria and health literacy among first-year nursing students. Methods: A cross-sectional correlational research design was used in this study. The study was conducted with 475 students in October 2023 during the first semester of the academic year 2023–2024. Results: Cyberchondria and health literacy levels were both moderate. In addition, the degree of health anxiety among first-year Nursing Students was mild, too. The results showed that the association between Cyberchondria and Health Literacy was partially mediated by health anxiety. Conclusion and implications: This study highlights the sophisticated relationship between cyberchondria, health literacy, and anxiety among first-year nursing students. It demonstrates that lower health literacy can lead to increased health anxiety, which in turn exacerbates cyberchondria. To mitigate these issues, it is essential to enhance health literacy and provide support for managing health anxiety within nursing education programs. By doing so, we can help nursing students navigate online health information effectively and reduce unnecessary health-related anxieties, promoting better educational outcomes and overall well-being. [ABSTRACT FROM AUTHOR]

Background: Nursing aims to rely on the best evidence, yet nurses frequently struggle with statistics, impeding the integration of research into practice. The misuse of statistical significance and p values is a pervasive issue, widely debated across disciplines but often overlooked in nursing. Objective: This study seeks to elucidate key arguments surrounding the misuse of p values, assess their relevance to nursing, and propose recommendations for improvement. Approach: Conducting a critical literature review on the interpretation and reporting of statistical significance and its practical implications among nurses, nursing students, and scholars. Results: The literature reveals widespread misunderstandings of probability concepts in classical statistics, leading to the misuse of p values. Some scholars propose abandoning p values altogether due to these challenges. Rather than dismissing p values, this article provides insights into their historical context and proper application. Recommendations are offered for accurately interpreting results and integrating supplementary metrics. Fostering statistical competencies already at the undergraduate level can enhance statistical literacy and alleviate statistics anxiety among nursing students, a prevalent issue. Early exposure to statistical methods in nursing education empowers nurses to actively engage in research. Additional recommendations include preregistering analysis plans to mitigate publication bias and exploring alternative approaches such as Bayesian methods. Conclusions: While p values serve as a valuable tool for preliminary assessment against randomness in nursing research, their widespread misunderstanding necessitates multiple measures for accurate interpretation and understanding of statistical significance. It is imperative for nurse educators and researchers to incorporate these recommendations into their practices. [ABSTRACT FROM AUTHOR]

We investigate how state “Auto‐IRA” mandates affect firm offerings of employer‐sponsored retirement plans (ESRPs). These policies require firms without ESRPs to facilitate automatic employee contributions to state‐created individual retirement accounts. We find that these policies increase an individual's probability of working for a firm with an ESRP by 6%–9% and of being included in the ESRP by 8%–13%. At the firm level, these policies increase the probability of offering an ESRP by 7%, the probability of establishing a new ESRP by 41%–44%, and the number of ESRP participants by 6 percent. [ABSTRACT FROM AUTHOR]

Objective: This study investigates the associations and mediating pathways between grip strength, cognitive function, and depression in middle-aged and elderly individuals in China. Methods: Utilizing data from the 2011 China Health and Retirement Longitudinal Study (CHARLS), we employed logistic regression and mediation analysis to examine the relationships and mediating factors between grip strength, cognitive function, and depression, while adjusting for potential confounders. Results: The study included 6,841 participants, of whom 1,734 (25.35%) exhibited symptoms of depression. Our findings indicate that weak grip strength is significantly associated with an increased risk of depression (OR: 1.57, 95% CI: 1.32-1.87) among the middle-aged and elderly population. Conversely, good cognitive function was found to be protective against depression (OR: 0.94, 95% CI: 0.93-0.95). Grip strength indirectly affected depression through cognitive function, accounting for 9.4% of the total effect (β = -0.008, 95% CI [-0.013, -0.004]). This mediating effect was 23.8% in men (β = -0.013, 95% CI [-0.020, -0.007]); and 23.2% in those aged 60 years and over (β = -0.015, 95% CI [-0.022, -0.009]). Conclusion: This study highlights that weak grip strength increases risk of depressive symptoms, and adequate cognitive function can mitigate the association between weak grip strength and an increased risk of depression among middle-aged and elderly individuals in China. Psychological care for elder adults with weak grip strength and poor cognitive function should be strengthened. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a global healthcare challenge lacking a simple and affordable detection method. We propose a novel deep learning framework, Eye-AD, to detect Early-onset Alzheimer's Disease (EOAD) and Mild Cognitive Impairment (MCI) using OCTA images of retinal microvasculature and choriocapillaris. Eye-AD employs a multilevel graph representation to analyze intra- and inter-instance relationships in retinal layers. Using 5751 OCTA images from 1671 participants in a multi-center study, our model demonstrated superior performance in EOAD (internal data: AUC = 0.9355, external data: AUC = 0.9007) and MCI detection (internal data: AUC = 0.8630, external data: AUC = 0.8037). Furthermore, we explored the associations between retinal structural biomarkers in OCTA images and EOAD/MCI, and the results align well with the conclusions drawn from our deep learning interpretability analysis. Our findings provide further evidence that retinal OCTA imaging, coupled with artificial intelligence, will serve as a rapid, noninvasive, and affordable dementia detection. [ABSTRACT FROM AUTHOR]

Purpose: We present a probabilistic approach to medical image analysis that requires, and makes use of, explicit prior information provided by a medical expert. Depending on the choice of prior model the method can be used for image enhancement, analysis, and segmentation. Methods: The methodology is based on a probabilistic approach to medical image analysis, that allows integration of 1) arbitrarily complex prior information (for which realizations can be generated), 2) information about a convolution operator of the imaging system, and 3) information about the noise in the reconstructed image into a posterior probability density. The method was demonstrated on positron emission tomography (PET) images obtained from a phantom and a patient with lung cancer. The likelihood model (multivariate log-normal) and the convolution operator were derived from phantom data. Two examples of prior information were used to show the potential of the method. The extended Metropolis-Hastings algorithm, a Markov chain Monte Carlo method, was used to generate realizations of the posterior distribution of the tracer activity concentration. Results: A set of realizations from the posterior was used as the base of a quantitative PET image analysis. The mean and variance of activity concentrations were computed, as well as the probability of high tracer uptake and statistics on the size and activity concentration of high uptake regions. For both phantom and in vivo images, the estimated images of mean activity concentrations appeared to have reduced noise levels, and a sharper outline of high activity regions, as compared to the original PET. The estimated variance of activity concentrations was high at the edges of high activity regions. Conclusions: The methodology provides a probabilistic approach for medical image analysis that explicitly takes into account medical expert knowledge as prior information. The presented first results indicate the potential of the method to improve the detection of small lesions. The methodology allows for a probabilistic measure of the size and activity level of high uptake regions, with possible long-term perspectives for early detection of cancer, aswell as treatment, planning, and follow-up. [ABSTRACT FROM AUTHOR]

Background: Evidence on long COVID symptom clustering patterns among patients with COVID-19 is limited. We summarized long COVID symptoms in clusters defined by number of symptoms co-occurring together, and we assessed Health-Related Quality of Life (HQRoL), Work Productivity and Activity Impairment (WPAI) outcomes across these clusters over time. We assessed associations between the clusters and BNT162b2 vaccination status. Methods: A prospective longitudinal patient-reported outcomes (PRO) study recruited laboratory-confirmed symptomatic COVID-19 patients seeking testing from a national retail pharmacy. Long COVID-19 symptoms were self-reported by participants at 4-week, 3-month and 6-month surveys. Patient classes identified via latent class analysis (LCA) with long COVID-19 symptoms were simplified into clusters based on number of symptoms. HRQoL and WPAI outcomes were collected using EQ-ED-5L and WPAI: GH questionnaires. Mixed models for repeated measures analyses were conducted to examine associations between exposure groups and outcomes. Results: The study included 328 participants that were segmented into three groups of long COVID-19 symptoms based on LCA and then simplified by the number of symptoms (Cluster 1 low, <2; Cluster 2 moderate, 2–6; and Cluster 3 high, >6 symptoms). The number of long COVID-19 symptoms was negatively associated with HRQoL and WPAI, whereby participants with high symptom burden (>6 symptoms) had the lowest HRQoL and WPAI scores assessed by absenteeism, presenteeism, work productivity loss, activity impairment, and hours worked metrics. Compared with those unvaccinated and not up-to-date with COVID-19 vaccination, subjects boosted with BNT162b2 consistently reported less symptom burden during the follow-up, regardless of their symptom-based cluster. Conclusion: Three distinct patient clusters based on frequency of long COVID symptoms experienced different HRQoL and WPAI outcomes over 6 months. The cluster with more concomitant symptoms experienced greater burden than the others. Participants up-to-date with BNT162b2 reported lower symptom burden across all clusters and timeframes. Clinical trial registration: Clinicaltrials.gov NCT05160636. [ABSTRACT FROM AUTHOR]