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Accurate forecasting of photovoltaic optimal points and efficiency using advanced hybrid machine learning models
Abstract Accurate forecasting of photovoltaic performance is essential for improving solar energy management, optimizing operational schedules, and supporting investment decisions. This study proposes a structured data-driven forecasting framework that integrates standalone learners with a hybrid boosting–aggregation strategy to predict two critical photovoltaic performance indicators: the optimal peak operating time (NOPT) and the power conversion efficiency (PCE). The methodology involves systematic data preprocessing, feature normalization, model training using both single and hybrid learners, and performance validation under identical experimental conditions. Multiple data-driven algorithms were examined using comprehensive statistical metrics, including R², RMSE, and U95. Among all models, the hybrid XGBA framework demonstrated superior predictive performance, achieving R 2 values of 0.9954 for NOPT and 0.9970 for PCE, and consistently low errors across all evaluation criteria. Model robustness and generalization were further assessed through uncertainty-based evaluation metrics. Sensitivity analyses highlight key influential parameters such as Emin Emax , and Ap , revealing their substantial contributions to model outputs. The proposed hybrid model provides a robust and highly accurate predictive tool that can reduce operational uncertainties, enhance energy yield, and support data-driven decision-making for photovoltaic plant operators and energy sector stakeholders.
Optimal power flow of hybrid wind/solar/thermal energy integrated power systems considering renewable energy uncertainty via an enhanced weighted mean of vectors algorithm
The rising global energy demand, along with the growth of electric power transmission and distribution systems, has intensified the need to incorporate renewable energy sources to foster sustainable development. However, achieving optimal operation within such systems poses significant challenges due to the stochastic nature of renewable energy generation. As a result, the optimal power flow (OPF) problem becomes increasingly complex when addressing the inherent uncertainty of renewable inputs. This study presents a new approach to addressing the OPF problem through the implementation of a hybrid Weighted Mean of Vectors Optimization Algorithm (INFO) based on artificial rabbits optimization (ARO) called ARINFO technique. The proposed ARINFO algorithm aims to reach an exploration-exploitation balance to improve search efficiency. To effectively manage the uncertainty associated with renewable energy output, modifications are implemented on standard test systems: in the IEEE 30-bus system (consisting of 30 buses, 6 thermal generators, and 41 branches), three thermal units are substituted with two wind turbines and one solar photovoltaic (PV) generator; a similar modification is made to the IEEE 57-bus system (which includes 57 buses, 7 thermal generators, and 80 branches) and large scale test system (IEEE 118-bus system). The stochastic characteristics of wind and solar power are modeled using Weibull and lognormal distributions, respectively. Their impact on the OPF problem is examined by incorporating reserve and penalty costs for overestimating and underestimating power output. Load demand variability is also assessed through standard probability density functions (PDF) to capture its uncertainty. Furthermore, operational constraints of thermal generators, such as ramp rate limits, are considered. The performance of the ARINFO algorithm is rigorously evaluated through 23 benchmark functions and the CEC-2022 test suite, with its effectiveness compared against nine established optimization methods. The results demonstrate that ARINFO achieved 1st rank overall on both the CEC-2017 and CEC-2022 test suites. When applied to the modified IEEE 30-bus system, ARINFO achieved a minimum generation cost of 781.1538 $/h, reduced emissions to 0.0922140 t/h, and minimized power losses to 1.734974 MW. For the larger IEEE 57-bus system, it attained a total cost of 20193.270 $/h, confirming its scalability and superior performance in managing the OPF problem under uncertainty in both generation and demand scenarios.
Comparison of general anesthesia versus no anesthesia in elective transjugular intrahepatic portosystemic shunt (TIPS): Procedural and hemodynamic parameters
Transjugular intrahepatic portosystemic shunt (TIPS) is an established treatment for complications of portal hypertension; yet the influence of anesthesia modality on procedural performance and hemodynamics remains insufficiently characterized. This retrospective single-center study compared radiation exposure, procedural parameters, and portal hemodynamics between procedures performed with and without general anesthesia (GA). A total of 84 patients were identified, of whom 62 were age- and sex-matched into two equal groups: group 1 (GA, n = 31) and group 2 (no GA, n = 31). Evaluated parameters included length of hospital stay, dose area product (DAP), fluoroscopy time (FT), contrast volume, number of digital subtraction angiography series, procedure duration, and pre- and post-TIPS measurements of portal venous pressure, central venous pressure (CVP), and portosystemic pressure gradient (PPG). Non-parametric statistical tests were applied. Patients in group 1 had significantly shorter postoperative hospital stay (median 6 days; interquartile range (IQR): 4–7) than those in group 2 (8 days; IQR 6–8; p = 0.006). Radiation dose was significantly lower in group 1, with a median DAP of 127.1 Gy*cm 2 (IQR 64.6–201.8) compared to 325 Gy*cm 2 (IQR 162.3–393.7; p = 0.02) in group 2. FT was also reduced under GA (12.2 minutes; IQR 9.6–15.9 vs. 16.0 minutes; IQR 11.5–25.9; p = 0.01), as was contrast volume (75 ml; IQR 60–100 vs. 90 mL; IQR 60–110; p = 0.01). PPG reduction was achieved in both groups, despite higher CVP under GA. These findings suggest that GA may facilitate more stable procedural conditions during TIPS, reducing radiation dose and contrast use without compromising hemodynamic effectiveness.
Prospective Evaluation of Antibody Response post COVID-19 vaccination in older persons ≧ 60 years old (PEARL 60): A longitudinal 15-months study in a tertiary centre in Malaysia
Older adults exhibit heterogeneous immune responses to COVID-19 vaccination, yet the relative contributions of age, comorbidity, vaccine platform, and infection history to antibody durability remain incompletely defined. Understanding these determinants is essential to inform booster strategies in ageing populations. We conducted a longitudinal observational study of 300 participants (250 aged ≥60 years and 50 younger controls) followed for up to 15 months. Anti-spike (anti-S) antibody responses were assessed at four event-anchored timepoints: ≤ 3 months post-primary vaccination (TP1), ~ 3 months post-first booster (TP2), 6–9 months post-first booster capturing waning immunity (TP3), and ≤3 months post-second booster where available (TP4). Multivariable log-linear regression models were used to identify independent determinants of antibody levels, with additional analyses stratified by infection status and vaccine platform. Among older adults, 78.8% had moderate-to-severe comorbidity burden, 40.0% were pre-frail, and only 16.8% received a second booster. At TP3, older age was associated with lower antibody levels in univariable analysis (GMR 0.81, 95% CI 0.68–0.97) but not after adjustment (aGMR 0.78, 95% CI 0.51–1.22, p = 0.279). Independent predictors of higher TP3 antibody levels included female sex (aGMR 1.24, 95% CI 1.02–1.51, p = 0.028), prior SARS-CoV-2 infection (aGMR 1.39, 95% CI 1.14–1.71, p = 0.001), and mRNA (aGMR 5.16, 95% CI 3.57–7.47, p=<0.001) or viral vector boosters (aGMR 6.05, 95% CI 4.03–9.08, p=<0.001), while renal disease was associated with lower responses (aGMR 0.71, 95% CI 0.54–0.94, p = 0.017). Similar associations were observed at TP4. Frailty and sarcopenia were not independently associated with antibody levels. Neutralising antibodies against Omicron were absent after primary vaccination and detected in only 25.9% of infection-naïve older adults after the first booster. Sustained humoral immunity following COVID-19 vaccination is driven primarily by vaccine platform and immune history rather than chronological age or geriatric syndromes alone. Waning immunity unmasks vulnerability in older adults, while low uptake of second boosters highlights a critical gap between immunological risk and vaccine utilisation. These findings support targeted, equity-focused booster strategies prioritising highly immunogenic platforms and high-risk older adults.
Information sharing between family and friend carers of older adults and healthcare professionals: Protocol for a systematic review of qualitative studies
Background Population aging worldwide continues to intensify the demand for family and friend carers to support older adults. Informal carers have long identified information gaps as a key challenge in their caregiving role, underscoring the importance of effective communication and collaboration with healthcare professionals (HCPs). Objectives To complete a comprehensive review of qualitative research and to synthesize what is known about the barriers and facilitators to information sharing between carers of older adults and HCPs. Methods This protocol outlines a systematic review that follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and PRISMA-P 2015 guidelines. We searched MEDLINE, EMBASE, CENTRAL, CINAHL, and PsycINFO on May 5, 2025. Our goal is to identify qualitative studies that meet our “PICo” (Population, phenomena of Interest, Context) eligibility criteria. Population includes carers and HCPs. Phenomena of interest is information sharing between the two populations. Context is carers who provide care to older adults aged 60 or above in any care setting. Two reviewers will independently screen titles and abstracts and full texts. We will use Covidence Extraction 2.0 for extraction of data from included records. Qualitative data from included records will be synthesized using Lockwood’s meta-aggregation and Sandelowski’s meta-summary approach to describe the experiences of information sharing reported within the literature. Discussion By comprehensively evaluating barriers and facilitators to information sharing within the literature, this review will offer significant insights into supporting more effective communication between carers and HCPs. Findings will inform the development of new strategies designed to optimize communication processes between carers and HCPs, with the ultimate goal of improving outcomes for older adults requiring caregiving support. This synthesis of current evidence will also identify gaps for further investigation and underscore the need for innovative communication solutions in diverse healthcare contexts. Trial registration PROSPERO CRD420250636906
Association between prognostic nutritional index and long-term mortality in intensive care unit patients with pressure ulcers: A retrospective study
Background The prognostic nutritional index (PNI), an integrated marker of nutritional and immune status, has been proposed as a potential prognostic factor in critically ill patients. This study aimed to investigate the relationship between PNI and long-term mortality in intensive care unit (ICU) patients with pressure ulcers. Methods Individuals with pressure ulcers were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and divided into four categories according to the quartiles of the PNI. Several statistical methods were employed to evaluate the association between PNI and long-term mortality, including Kaplan-Meier survival analysis, multivariable Cox proportional hazards models, restricted cubic splines (RCS), receiver operating characteristic (ROC) curves, and subgroup analyses. Results The median age of the 796 participants was 70.33 years (IQR: 60.91–79.96), with 451 (56.7%) being male. During the follow-up period, 476 patients (59.8%) died within 365 days, and 413 patients (51.9%) died within 180 days. Kaplan-Meier analysis indicated that patients with elevated PNI values had a significantly lower risk of mortality at both 365 and 180 days. After full adjustment for potential confounders, patients in the highest PNI quartile had significantly lower mortality risks compared to those in the lowest quartile (365-day mortality: HR = 0.598, 95% CI: 0.455–0.786, P < 0.001; 180-day mortality: HR = 0.558, 95% CI: 0.414–0.753, P < 0.001). A non-linear L-shaped relationship was identified between PNI and mortality, with threshold values of 28.45 for 365-day mortality and 29.15 for 180-day mortality. Conclusions A lower PNI was significantly associated with increased risk of long-term mortality in ICU patients with pressure ulcers. These findings suggested the potential of PNI as a valuable prognostic biomarker in this population.
Effect of targeted temperature management on neurological and survival outcomes in patients undergoing extracorporeal cardiopulmonary resuscitation
Objectives Targeted temperature management (TTM) has been a fundamental component of post-resuscitation care for patients experiencing cardiac arrest for many years. This study aims to investigate the association between TTM and clinical outcomes in patients undergoing extracorporeal cardiopulmonary resuscitation (ECPR). Methods This retrospective cohort study was conducted at a single tertiary medical center in Taiwan. A total of 360 patients were screened between January 2015 and May 2023, with 148 excluded. After selection, 212 patients were included in the final analysis, with 79 receiving TTM and 133 not receiving TTM. Findings Patients in the TTM group had a higher rate of successful weaning from extracorporeal membrane oxygenation (64.6% vs. 42.1%, p = 0.002), survival to discharge (58.2% vs. 38.3%, p = 0.005) and lower cerebral performance category (CPC) scores at discharge (3.6 vs. 4.2, p = 0.001). A higher proportion of patients in the TTM group had a CPC score of 1–2 points at discharge, indicative of a favorable neurologic outcome (29.1% vs. 10.5%, p < 0.001). After adjusting for potential confounders, TTM was significantly associated with reduced odds of in-hospital death (adjusted odds ratio [OR] 0.34, 95% confidence interval [CI] 0.15–0.72, p = 0.006) and poor neurological outcomes (CPC 3–5; adjusted OR 0.30, 95% CI 0.12–0.72, p = 0.008). Conclusions Among patients receiving ECPR, the use of TTM is associated with improved neurological outcomes and increased survival to hospital discharge. Future randomized controlled trials are needed to elucidate the pathophysiology and clinical impact of combining TTM with ECPR.
Prevalence and factors associated with underweight among children under five born to adolescent mothers: Evidence from the 2022 Kenya Demographic and Health Survey
Background Undernutrition remains a major public health concern in low- and middle-income countries, with children born to adolescent mothers being particularly at risk of underweight. In Kenya, despite high adolescent birth rates, there is limited nationally representative evidence on the prevalence of underweight and its determinants among children under five years born to adolescent mothers. This study examined the prevalence and factors associated with underweight among Kenyan children under five years of age born to adolescent mothers, using nationally representative data from the 2022 Kenya Demographic and Health Survey (KDHS). Methods This study was a cross-sectional analysis of data from the child recode file (KR) of the 2022 KDHS, comprising a weighted sample of 819 children under five years born to adolescent mothers aged 15–19 years. Underweight was defined as a weight-for-age Z-score of less than −2 SD. Modified Poisson regression analyses were performed to identify factors associated with underweight. All analyses accounted for the complex survey design and sampling weights. Results from the bivariate model are presented as crude prevalence ratios (CPR), while results from the multivariable model were presented as adjusted prevalence ratios (APR). Statistical significance was set at P < 0.05. Results The prevalence of underweight among Kenyan children born to adolescent mothers was 11.03% (n = 77/702; 95% CI: 8.65–13.97). In the multivariable model, children of married adolescent mothers were more likely to be underweight (APR = 2.22; 95% CI: 1.15–4.28; P = 0.018) than those of unmarried mothers. Additionally, the prevalence of underweight increased with an increase in the child’s age. Children aged 6–23 months (APR = 2.73; 95% CI: 1.22–6.12; P = 0.015) and those aged ≥24 months (APR = 4.35; 95% CI: 1.84–10.30; P = 0.001) were more likely to be underweight than those aged six months and below. Conclusion Approximately 1 in 9 children under five years born to adolescent mothers in Kenya were underweight. Being in a marital union and an increase in the child’s age emerged as key factors associated with underweight among children born to adolescent mothers. These findings highlight the need for targeted interventions to prevent early marriage among adolescent girls and to improvee complementary feeding practices among adolescent mothers to reduce the risk of underweight among their children..
Integrative bioinformatics and experiments identify RIBC2 as a key regulator in the esophageal cancer
Early detection of esophageal cancer (EC) remains a major challenge due to the limited understanding of its initial molecular alterations. Therefore, this study aimed to identify the key molecular drivers involved in EC carcinogenesis. Human normal esophageal epithelial cells were subjected to chronic malignant transformation, followed by assessment of their morphological changes, proliferative capacity, clonogenic potential, migration, and invasion abilities. To elucidate the molecular mechanisms underlying tumorigenesis, transcriptome sequencing was performed and integrated with clinical datasets from two independent EC cohorts. Machine learning algorithms were then applied to pinpoint diagnostic and prognostic gene signatures, which were further validated through comprehensive in vitro and in vivo experiments. Differential expression analysis and machine learning identified RIB43A domain with coiled-coils 2 (RIBC2) as a strong diagnostic and prognostic biomarker for EC. RIBC2 expression was markedly upregulated in chronically transformed epithelial cells, established EC cell lines, and clinical tumor specimens, and its elevation was associated with unfavorable clinicopathological characteristics. Functional studies revealed that silencing RIBC2 significantly inhibited cell proliferation, migration, and invasion in both transformed and EC cells. Moreover, immune profiling indicated that high RIBC2 expression was linked to an immune-excluded tumor microenvironment, implying a potential role in modulating responsiveness to immunotherapy. These findings reveal RIBC2 as a novel driver of EC initiation and progression, highlighting its potential as a biomarker for early diagnosis and as a promising target for therapeutic intervention.
Facial emotion recognition abilities of individuals with schizophrenia and the influence of parental bonding—An exploratory study in a forensic sample
Individuals diagnosed with schizophrenia experience cognitive impairments, including a decline in social cognition, which encompasses facial emotion recognition. Facial emotion recognition is an important aspect of social interaction, guiding people’s actions and influencing their social functioning. Early childhood experiences, such as parental attachment, are one of the most influential factors in the development of many psychiatric symptoms including impairment of social cognition. Our aim was to explore this poorly researched area. We investigate the hypothesis that dysfunctional parenting styles negatively affect facial emotion recognition abilities in general and further worsen these deficits in individuals diagnosed with schizophrenia. A total of 32 participants were included in an exploratory study, comprising 16 patients with paranoid schizophrenia recruited from forensic clinics in Switzerland, and 16 age and education matched healthy controls without history of psychiatric or neurological illnesses. Parental attachment was assessed using the Parental Bonding Inventory and subjects were assigned to subgroups of optimal vs. neglectful parenting style from both parental sides. Facial emotion recognition was operationalized as the error rate in an emotion-naming task using standardized images of the five basic emotions. Overall, schizophrenia patients made significantly more errors in the facial emotion recognition task than healthy controls. Interestingly, in the subgroup with optimal parental attachment experiences, patients did not significantly differ from controls, whereas in cases of neglectful parenting, the patients showed a much higher error rate in facial emotion recognition compared to healthy controls ( p < .001), as well as compared to patients with optimal parenting experience ( p < .01). Neglectful parenting appears to exacerbate the adverse effects of schizophrenia on facial emotion recognition; i.e., optimal parenting might mitigate deficits caused by schizophrenia spectrum disorder patients and help compensate for FER impairments.
Clonal hematopoiesis associates with prevalent and incident cardiometabolic disease in a cardiac catheterization cohort
Background Clonal hematopoiesis of indeterminate potential (CHIP) is the age-related presence of expanded somatic clones secondary to leukemogenic driver mutations and is associated with cardiovascular (CV) disease and mortality. We sought to evaluate relationships between CHIP with cardiometabolic diseases and incident outcomes in high-risk individuals. Methods CHIP genotyping was performed in 8469 individuals referred for cardiac catheterization at Duke University (CATHGEN study) to identify variants present at a variant allele fraction (VAF) ≥2%. Associations were tested among any CHIP variant, large CHIP clones (VAF > 10%) and individual CHIP genes with prevalent cardiometabolic traits. Cox proportional hazard models tested CHIP associations with time-to-overall mortality and Fine-Gray analyses tested CHIP associations with incident cardiovascular outcomes. Results We identified 463 CHIP variants in 427 individuals (5.0%) of which 268 (3.2%) harbored large CHIP clones. CHIP and large CHIP were associated with lower odds of obesity (OR 0.79 [95% CI 0.65–0.98], p = 0.03; OR 0.76 [95% CI 0.57–0.99], p = 0.04, respectively). CHIP was associated with prevalent heart failure (HF, OR 1.25 [95% CI 1.01–1.55], p = 0.04; especially for non- DNMT3A CHIP (OR 1.38 [95% CI 1.04–1.82], p = 0.02). CHIP was also associated with incident events: Non- DNMT3A CHIP was associated with increased risk of time-to-HF hospitalization (HR 1.29 [95% CI 1.02–1.63], p = 0.03). Conclusions In high-risk individuals referred for cardiac catheterization, large CHIP and non- DNTM3A CHIP were associated with obesity, prevalent HF, incident CV events. These findings strengthen the importance of CHIP as a biomarker for CV disease and highlight the contributing risk of large CHIP clones and non- DNMT3A CHIP variants.
The impact of digital intelligence technologies on innovation performance: Evidence from specialized, refined, differential and innovative enterprises
The integration of digital and intelligent technologies has created new opportunities for the innovative growth of Specialized, Refined, Differential, and Innovative (SRDI) enterprises in China. This study examines SRDI enterprises listed on the Shanghai/Shenzhen A-share from 2014 to 2022. A three-stage Data Envelopment Analysis, incorporating a knowledge breadth framework, is employed to evaluate their innovation performance. Furthermore, an empirical analysis is conducted to assess the influence of digital intelligence on innovation outcomes. The results indicate that: (1) Digital intelligence, measured by datafication, digitization, and the adoption of intelligent technologies, significantly improves the innovation performance of SRDI enterprises, with intelligent technologies exerting the greatest effect; (2) Digital intelligence effectively mitigates financing constraints, allowing firms to allocate more resources to innovation; and (3) Heterogeneity analysis shows that the positive impact of digital intelligence is more pronounced among non-state-owned enterprises, manufacturing firms, and those located in Eastern China. These findings provides valuable guidance for policymakers seeking to develop targeted and differentiated strategies to enhance the innovation capacity of SRDI enterprises. In particular, the results underscore the role of digital intelligence in easing financing constraints. By accounting for firm-level heterogeneity, this study offers a robust theoretical and empirical foundation for policy design and delivers actionable recommendations for enterprises aiming to optimize resource allocation and strengthen innovation capabilities through digital transformation.
The predictive value of a multivariable model based on vaginal Lactobacillus relative abundance and microecological features at 24 weeks gestation and before delivery in spontaneous preterm birth: A Prospective cohort study
Background Vaginal microecological imbalance, particularly reduced Lactobacillus dominance, is a significant risk factor for spontaneous preterm birth (sPTB).However, the predictive value of microbial composition, pathogen colonization, and vaginal inflammation biomarkers at different pregnancy stages remains unclear. This study aims to evaluate the predictive potential of vaginal microecology at 24 weeks of gestation and before delivery for spontaneous preterm birth. Methods This was a prospective multicenter cohort study. Vaginal swabs were collected at 24 weeks of gestation and before delivery to assess Lactobacillus relative abundance(LRA), pathogen colonization, and biochemical markers (pH, hydrogen peroxide, leukocyte esterase, and sialidase). Multivariable logistic regression models, ROC curves, and Kaplan-Meier survival analysis were used to identify predictors of spontaneous preterm birth. Results At 24 weeks of gestation, the preterm group showed significantly lower Lactobacillus relative abundance, higher AV and Nugent scores, and higher vaginal pH. Logistic regression revealed that an increase in Lactobacillus relative abundance(LRA) was negatively associated with sPTB (OR = 0.97, 95% CI = 0.96–0.98, P < 0.001), while higher parity (OR = 2.28, 95% CI = 1.56–3.32, P < 0.001) and a history of late miscarriage/preterm birth (OR = 6.96, 95% CI = 2.77–17.47, P < 0.001) increased the risk. Lactobacillus relative abundance(LRA) below 57.5% was linked to increased preterm birth risk in univariate analysis, but this was no longer significant after multivariable adjustment. Parity, late miscarriage/preterm birth history, vaginal pH > 4.5, and GBS positivity remained independent risk factors (AUC = 0.775). Kaplan-Meier survival analysis showed that women with LRA > 72.5% at 24 weeks and LRA > 57.5% before delivery had significantly higher term delivery probabilities (log-rank P < 0.001). Conclusion At 24 weeks, reduced vaginal LRA is an independent predictor of spontaneous preterm birth. Early vaginal microbiome assessment, combined with clinical features, can help identify high-risk pregnant women and improve outcomes.
The influence of city size versus urban form on land surface temperature variation and the surface urban heat island effect: A cross-city analysis of German cities
This paper seeks to: 1) determine the extent of the intra-urban surface urban heat island (SUHI) effect within German cities using novel urbanization-level data with high spatial resolution, and 2) to assess the influence of city size and urban form using this data together with landscape metrics. The study uses aggregated Landsat LST data to measure the intra-urban SUHI effect across German cities of various population sizes. The first stage of the research utilizes urbanization-level data based on differing thresholds of population and building density, providing a novel method of measuring the correlation between the intra-urban SUHI phenomenon and density. The second stage assesses the impact of urban form by calculating specific landscape metrics using high-resolution land cover data, which is then clustered to identify homogeneous patterns among cities. We show that the SUHI effect can be found within all cities included in the study; however, a positive correlation between increase in city size and increase in heat stress could not be confirmed. The study shows that German urban areas are characterized by specific patterns of urban form that correspond with size, and specific urban forms particularly related to density and shape correspond with higher overall LST.
Spatial patterns and environmental influences of COVID-19 outbreaks, post-Omicron
The seasonality of many respiratory pathogen outbreaks, such as influenza and respiratory syncytial virus, is driven by climate factors, such as specific humidity or temperature. However, it remains unclear whether climate plays a role in determining the seasonality of COVID-19, given that the evolution of novel strains likely plays a key role in shaping outbreak dynamics. Here we use Emergency Department data to explore spatial differences in COVID-19 outbreak dynamics over three years, from April 2022 through March 2025. We observe that outbreak patterns varied across latitude, with southern states experiencing larger summer peaks and northern states facing more evenly distributed summer to winter outbreaks or larger winter peaks. We find that specific humidity and temperature at the state level are significantly associated with observed differences in ED visits with a COVID-19 diagnosis, even after controlling for state-level variation in vaccination status. Our results imply a role for climate in influencing COVID-19 outbreak dynamics. We anticipate these findings will provide a foundational understanding of factors shaping SARS-CoV-2 transmission as COVID-19 becomes endemic in the United States.
Bayesian spatio-temporal modeling for policy evaluation: Sensitivity of policy effect estimates in the context of COVID-19 stay-at-home orders
This study applies a Bayesian spatio-temporal model to demonstrate the sensitivity of policy effect estimates to spatial and temporal structure, using COVID-19 stay-at-home orders as a case study. Unlike conventional approaches, this framework accounts for geographic spillovers, temporal dependence, and space–time interaction, all of which are central to policy effect evaluation in heterogeneous settings. Implemented via Integrated Nested Laplace Approximation (INLA), the model also accommodates missing data and supports inference in high-dimensional contexts. Using Google mobility data and policy information from the Oxford COVID-19 Tracker, we estimate four models of increasing complexity: OLS, spatial, temporal, and spatio-temporal. While simpler models suggest substantial reductions in workplace and residential mobility, these effects become statistically insignificant once spatio-temporal interactions are incorporated. This pattern indicates that earlier studies may have overstated policy effects by overlooking spatio-temporal heterogeneity. Our findings demonstrate the importance of spatio-temporal modeling for policy evaluation, particularly when working with large-scale, incomplete, and unevenly distributed data.
Measuring and analyzing the emotional engagement exhibited by chinese university students in ideological and political theory courses via the IPTCSSE
This study investigates the emotional responses and engagement levels of Chinese university students enrolled in Ideological and Political Theory Courses (IPTCs), with particular attention to how curriculum design influences students’ attitudes and feelings. Using the IPTCSSE scale, a quantitative analysis was conducted to measure multiple dimensions of emotional engagement. A total of 3,992 valid questionnaires were collected. Based on the emotional engagement subscale, exploratory and confirmatory factor analyses identified seven underlying factors: interest and belonging, classmates and peers, family and curriculum, emotions and feelings, sense of identification, teacher support and influence, and sense of achievement in courses. Descriptive statistics indicated that students generally evaluated all seven factors positively, and all factors were significantly and positively correlated. Among them, sense of achievement in courses received the highest score, while classmates and peers scored the lowest. Correlation and linear regression analyses further showed that each factor positively predicted emotional engagement in IPTCs. Interest and belonging emerged as the strongest predictor, whereas sense of achievement exerted the smallest predictive effect. Drawing on these findings, the study discusses how emotional engagement can be strategically emphasized to improve the pedagogical effectiveness of IPTCs. The results highlight the importance of fostering interest, belonging, supportive teacher-student relationships, and positive emotional experiences to enhance students’ overall engagement with ideological and political education in China’ s higher education context.
Knowledge, attitudes and practices regarding bovine tuberculosis in cattle and humans in Malawi
Background Bovine tuberculosis (BTB) has a significant impact on both the cattle industry and human health. Understanding its transmission, clinical signs, risk factors, and control measures is essential for prevention. This study aimed to evaluate the knowledge, attitudes, and practices regarding BTB in high-burden areas of Malawi. Methods A stratified sampling design was employed to collect data from 463 butchers, dairy farmers and cattle farmers in different locations and settings in Malawi. Aggregate scores on knowledge, attitudes, and practices were taken as multivariate measurements and fitted with multivariate linear regression models. Results Participants displayed satisfactory knowledge (88.68%), negative attitudes towards risky behaviours (92.27%), and appropriate practices (86.83%) concerning BTB. Most were aware of its presence in cattle (85.71%) and potential transmission to humans (74.09%), yet exhibited gaps in understanding clinical signs and held misconceptions about hereditary transmission. Many participants demonstrated risky behaviours, such as consuming raw animal products and selling products from infected animals. Individuals with secondary (β: −2.148; 95% CI: −4.168, −0.127) and tertiary education (β: −3.488; 95% CI: −6.626, −0.349) exhibited more negative attitudes towards risky behaviours compared to those with informal education. Adults aged 18−30 (β: −2.777; 95% CI: −5.469, −0.085) and those aged 31−45 (β: −3.035; 95% CI: −5.752, −0.319) demonstrated better protective practices than youths under 18. Conclusion There is an urgent need for targeted health education on BTB, focusing on clinical signs and the myth of hereditary transmission, particularly aimed at young people, individuals with limited formal education, and farmers, to enhance prevention efforts.
A novel approach towards a histone replacement system in Tetrapods
Histone replacement systems are valuable tools for studying histone modifications, but in vertebrates this is so far only possible by labor-intensive CRISPR base editing of each single histone gene. To facilitate such studies, we developed an alternative method and conducted proof-of-principle experiments using histone 2B (H2B) as an example. This method relies on shRNA targeted degradation of endogenous histone mRNA and simultaneous re-expression of a replacement histone. Due to their limited histone gene number, chicken cells proved suitable as a tetrapod model system for this approach. In the first-generation system we developed an shRNA design tool that identified shRNAs leading to efficient downregulation of each of the canonical histones using a single doxycycline (Dox)-inducible shRNA. As H2B knockdown cells are not viable, they were rescued by simultaneous Dox-inducible re-expression of H2B. Since the comparability between wild-type and mutated histone variants is limited due to random chromosomal integration, we developed a second-generation “inducible knockdown-re-expression” system. This new version employs genomic landing pads to facilitate Bxb1 recombinase-mediated cassette exchange with mutated histones. The system successfully rescued reconstituted cells from histone depletion-induced cell death, but requires optimization to align histone expression levels with endogenous levels. Overall, this system offers a promising new method for studying specific histone modifications in chicken cells.
ROS-induced ATP synthase mRNA degradation and metabolism dysfunction reveals the mechanism of artificial deteriorated cotton seeds
Seed aging is a complex biological process, the deterioration of oil crop seeds, in particular, has caused yield decline and economic loss to a large extent. However, research on the aging mechanism of oilseeds, such as cotton seeds, is still unclear. In this study, the physiological and biochemical changes in artificially aged cotton seeds were examined to further reveal the mechanism of seed aging and deterioration. Cotton seeds of “Xinluzao 74” were treated by artificial aging treatment method with high temperature (45°C) and high relative humidity (100%) for 1, 2, 3, 4, or 5 days, respectively, and untreated cotton seeds were used as control (CK). Our results showed that the germination rate, seed embryo viability, dehydrogenase activity, the activities of dehydrogenase antioxidant enzymes (SOD and POD), seed respiration rate, ATP content, ATP synthase activity and ATP synthase subunit mRNA integrity all showed a significant downward trend with the aging treatment time ( P < 0.05 ), whereas the ROS generation (H 2 O 2 content and ‧O 2 - production rate), relative conductivity, MDA content of seeds increased significantly, and the ultrastructure of cell membrane, mitochondria and chromatin of seed embryo was seriously damaged. Correlation analysis showed that there was a strong negative correlation between germination rate, SOD and POD activities, and respiration rate with H 2 O 2 content ( P < 0.05 ). This study reveals that excessive ROS, particularly H₂O₂, causes oxidative damage to ATP synthase subunit mRNAs, leading to impaired mitochondrial respiration and reduced seed vigor. These findings provide new molecular evidence linking oxidative RNA damage with seed aging, which could inform seed quality evaluation and storage strategies.