Browse Articles

Critical exponents and magnetocaloric response in Zintl phase EuIn2 X2 (X = As, P)

Stay or go? Exploring physician turnover in European Hospitals–Evidence from the METEOR survey

According to the World Health Organization (WHO), in 2022 there was a shortfall of approximately 1.2 million doctors, impacting healthcare system and patient care. Understanding turnover intentions is crucial for managing the healthcare workforce and ensuring continuous, and high-quality patient care. This study investigates the prevalence of physicians planning to leave their hospital or the profession, and risk factors such as job demand, resources, satisfaction, and burnout across four European countries. A cross-sectional multicenter study was conducted in eight hospitals across Belgium, the Netherlands, Poland and Italy, including both academic and non-academic institutions. Data from Poland were excluded due to a low response rate, to preserve respondent anonymity. Multivariable logistic regression analyses were performed, adjusted for country, demographics, and work context, using significant variables from the univariable analysis. The overall intention to leave the hospital was 16.5%, with the highest rates in Belgium (19.6%) and Italy (19%), and the lowest in the Netherlands (9.8%). The intention to leave the profession was 9.1%, with the highest rate in the Netherlands (16.1%), followed by Belgium (6.3%) and Italy (5.7%). Physicians at higher risk of leaving the hospital were younger (adjOR = 0.90, 95%CI = 0.86–0.93), lacked colleague support (adjOR = 3.18, 95%CI = 1.06–9.36), and were dissatisfied with job prospects (adjOR = 2.38, 95%CI = 1.02–5.54) and overall work (adjOR = 2.71, 95%CI = 1.09–6.69). Those more likely to leave the profession were from the Netherlands (adjOR = 4.14, 95%CI = 1.62–11.4), surgeons (adjOR = 2.90, 95%CI = 1.22–6.78), working in non-academic hospitals (adjOR = 2.43, 95%CI = 1.01–5.97), lacked development opportunities (adjOR = 5.97, 95%CI = 1.01–36.2), or were dissatisfied with career prospects (adjOR = 2.77, 95%CI = 1.04–7.27). Health system managers and relevant stakeholders involved in the planning, implementation, or evaluation of health policies and reforms aimed at improving healthcare job retention should take into account the key determinants of the intention to leave identified in this study.

Model testing and response surface investigation of eccentric loading on closely spaced strip footings

Influence of the modification with polymer microspheres on the structural, mechanical and post-processing properties of extruded thin-walled LDPE films

Geographically weighted regression analysis of incomplete basic childhood vaccination in Sub-Saharan Africa: Evidence from DHS, 2019–2024

Background Immunization is the safest way to protect against disease. Currently, vaccination saves more than 4 million lives annually. By 2030, 90% of people worldwide are expected to have received the basic immunizations, according to the Immunization Agenda 2030 (IA2030). However, in sub-Saharan Africa (SSA), only 54.1% of children receive the complete set of basic childhood vaccinations. Therefore, this study aims to assess the spatial variation of incomplete basic childhood vaccination and its determinants in SSA by using DHS data from 2019–2024. Method For our study, we utilized a total of 28,045 weighted children from 16 selected SSA countries. The vaccination status was determined through both maternal recall and the use of vaccination cards. Spatial autocorrelations, hotspot analysis, spatial interpolation, and SaTScan analysis were conducted to explore the spatial distribution. Ordinary Least Squares (OLS) and Geographical Weighted Regression (GWR) were performed to identify the associated factors of partial immunization. Results The pooled prevalence of partial immunization in SSA was 35.5% [95% CI: 28.49%, 42.51%]. Mauritania, Gabon, Côte d’Ivoire, central Tanzania, Liberia, and northeast Mozambique are among the hotspot regions that have been identified. Higher maternal education, female-headed households, maternal age between 15 and 24 years, absence of antenatal care, and urban residency were all found to be significant predictors with GWR analysis. Conclusion In SSA, partial immunization shows a clustered spatial pattern with different hotspot areas. The use of maternal health services and socio-demographic factors has an impact on incomplete immunization. Improving vaccination coverage requires focused programs that address awareness creation and service utilization.

A multi-scale CNN-GRU fusion model with stationary wavelet transform for 14-day ahead dam water level prediction

Acipimox as a potential antioxidant and neuromodulator mitigates high fat diet induced cognitive dysfunction

Understanding merger control remedies in China

We identified 8 merger cases with remedies in China for a period from the time when the Anti-monopoly Law was enacted in 2008–2018, and about 150 other merger cases corresponding to these 8 cases in their respective industries but approved without remedies. We then use the latter data to construct a counterfactual for the former to compare the factually observed level of competition after the merger decision with that derived from the counterfactual, based on a method called the synthetic control method (SCM). The exercise allows us to assess the remedies’ effectiveness. We find that overall the remedies are effective, but the structural remedies’ effect tends to be more abrupt and pronounced than behavioral remedies.

AMOchar: an amorphous MnOx functionalized biochar to stabilize metal(loid)s in soil and optimize phytostabilization

Abstract Biochar (BC) is widely used to immobilize metal(loid)s but its efficiency is not ubiquitous and can be improved via various surface modifications, such as impregnating amorphous Mn oxides (called AMOchars), which showed benefits for metal(loid) immobilization, but also induced considerable Mn leaching. To reduce those drawbacks, we tested two AMOchars, synthesized using molasses (BCM) or sucrose (BCS) as reducing agents, to evaluate the effectiveness of Mn oxide fixation on biochar to reduce metal(loid) transfer to plants and select the most appropriate reducing agent. Soil solution monitoring showed that all materials increased pH and immobilized Cd, Pb, and Zn. The AMOchars further improved Cd and Zn immobilization efficiency while releasing dissolved organic carbon, As, Cu, and Mn. In plants, metal(loid) shoot transfer was reduced by BC (As, Cd, Cu, Mn, and Zn) and BCS (Cd, Pb, and As). To conclude, we demonstrated the effectiveness of Mn oxide fixation on biochar using sucrose to improve phytostabilization. Sucrose as a reducing agent led to a more stable (less organic carbon leaching) material and thus less toxic to the plant. We believe that our study will help raise up the knowledge on biochar modification and make aided phytostabilization process more practiced on the field.

Robust modeling and evidence-based evaluation method for a active distribution network with EVs and CHPs

Abstract Promoting the increase of the proportion of new energy into the power grid and improving the utilization rate of energy has become the urgent needs of the world. To reduce the impact of renewable energy output prediction errors on the distribution network, this paper considers the charging and discharging behaviors of electric vehicles (EVs) and demand responses, and proposes a robust optimization model for the distribution network with a three-stage framework. In the day-ahead stage, a day-ahead optimization operation model is constructed by promoting load shifting through price-based demand response, minimizing daily operation costs while accounting for new energy uncertainty via penalty costs for supply-demand imbalances. In the intraday stage, an intraday rolling optimization model is developed by integrating EV charging/discharging responses, refining the day-ahead plan with higher-resolution forecasts to enhance renewable energy absorption and load balancing. In the real-time stage, a real-time adjustment model utilizes incentive-based demand response to smooth short-term fluctuations in renewable output, ensuring voltage stability and operational flexibility. Experimental simulations on the IEEE 33-bus test system demonstrate that the proposed three-stage cooperative operation strategy significantly promotes renewable energy consumption, reduces operational costs, and improves the reliability of active distribution network (ADN) operation.

Structured matching models in multimodal information fusion: An optimized Kuhn-Munkres algorithm

In modern multimodal interaction design, integrating information from diverse modalities—such as speech, vision, and text—presents a significant challenge. These modalities differ in structure, timing, and data volume, often leading to mismatches, low computational efficiency, and suboptimal user experiences during the integration process. This study aims to enhance both the efficiency and accuracy of multimodal information fusion. To achieve this, publicly available datasets—Carnegie Mellon University Multimodal Opinion Sentiment Intensity (CMU-MOSI) and Interactive Emotional Dyadic Motion Capture (IEMOCAP)—are employed to collect speech, visual, and textual data relevant to multimodal interaction scenarios. The data undergo preprocessing steps including noise reduction, feature extraction (e.g., Mel Frequency Cepstral Coefficients and keypoint detection), and temporal alignment. An improved Kuhn-Munkres algorithm is then proposed, extending the traditional bipartite graph matching model to support weighted multimodal matching. The algorithm dynamically adjusts weight coefficients based on the importance scores of each modality, while also incorporating a cross-modal correlation matrix as a constraint to improve the robustness of the matching process. The enhanced algorithm’s performance is validated through information matching efficiency tests and user interaction satisfaction surveys. Experimental results show that it improves multimodal information matching accuracy by 28.2% over the baseline method. Integration efficiency increases by 18.7%, and computational complexity is significantly reduced, with average computation time decreased by 15.4%. User satisfaction also improves, with a 19.5% increase in experience ratings. Ablation studies further confirm the critical contribution of both the dynamic weighting mechanism and the correlation matrix constraint to the overall performance. This study introduces a novel optimization strategy for multimodal information integration, offering substantial theoretical value and broad applicability in intelligent interaction design and human-computer collaboration. These advancements contribute meaningfully to the development of next-generation multimodal interaction systems.

Increase in mechanical load and pro-fibrotic stimulation leads to fibrotic and hypertrophic remodeling in porcine living myocardial slices

Abstract Heart failure (HF) is a growing global health concern, driven by factors such as increased mechanical load of the heart muscle tissue. This pathogenic condition is the result of remodeling processes, partially mediated by the cytokine transforming growth factor β (TGF- β1), with progressive deposition of extracellular matrix within the myocardium that ultimately increases tissue stiffness. To elucidate early cellular and molecular processes underlying cardiac remodeling, translational experimental models are required. Living myocardial slices (LMS) represent a promising ex vivo model with preserved multicellularity, and physiology. In this study, we developed a disease model with hypertrophic and fibrotic features in porcine LMS. For this, LMS were prepared from porcine left ventricular tissue and cultured under mechanical overload with or without TGF-β1 stimulation. LMS cultured under overload showed reduced contractile performance, while adding TGF- β1 resulted in higher collagen deposition in the tissue, increase in secretion levels of pro-fibrotic miR-21 into the culture supernatant and increased expression of pro-fibrotic and hypertrophic marker genes. Our findings demonstrate early fibrotic changes in pig LMS induced by both mechanical and chemical stimulations. This ex vivo model could provide valuable insights into the early changes in heart failure pathogenesis and could be utilized as a screening platform to validate treatment strategies targeting cardiac remodeling.

Impact of curing temperature on accuracy and physical properties of additively manufactured FDPs and bar specimens

Abstract Additive manufacturing based on photopolymer resins requires additional light curing during postprocessing to achieve the final mechanical properties. The present in-vitro study aimed to evaluate the impact of the curing temperature during postprocessing on the fracture resistance and accuracy of both additively manufactured four-unit fixed dental prostheses (FDPs) and bar-shaped, ISO-conform specimens. All samples were fabricated by either additive manufacturing using two different light-curing resins or subtractive manufacturing using polymethyl methacrylate. Three different curing temperatures were evaluated (40 °C, 60 °C, 80 °C). All bars ( n  = 136) were subjected to a three-point bending test after 68 of them had been stored in water for 24 h. All bridges ( n  = 90) were analyzed for dimensional accuracy and afterwards subjected to static loading until fracture. Additively manufactured bar-shaped specimens exhibited significantly higher flexural strength compared to the subtractively manufactured counterparts. In contrast, all but one group ( p  = 0.082) of the additively manufactured four-unit FDPs demonstrated significantly lower fracture strength than the subtractively manufactured bridges ( p  < 0.024). Post-curing temperature had no significant effect on accuracy for the temporary resin ( p  > 0.469), whereas the permanent resin showed significant differences for some regions of interest and temperature combinations. For the recommended curing duration of 40 min, the lowest tested curing temperature of 40 °C already resulted in a sufficient degree of cure and mechanical properties with no general benefit to higher curing temperatures, indicating their use to be unnecessary.

Joint angle trajectories are Robust to segment length estimation methods in human reaching

Background Quantitative movement analysis is increasingly used to assess motor deficits, but joint angle calculations depend on assumptions about limb segment lengths. These lengths are often estimated from average anthropometric proportions rather than measured directly. The extent to which such assumptions influence joint angle accuracy and variability remains unclear. Methods In prior studies, we recorded reaching movements in nine healthy adults using active-marker motion capture system. In this study, we computed arm joint angles with a dynamic model scaled using either measured segment lengths (Individual method) or proportions based on body height (Average method). Each participant served as their own control across two modeling conditions. We compared segment proportions and the variability in joint angle trajectories arising from segment length assumptions (between-participant variability) with within-participant variability across repeated movements. Results Segment length proportions remained unchanged despite increases in population height. Joint angle trajectories derived from the two scaling methods were very similar. Segment length assumptions had only minor effects on joint angle amplitudes, primarily due to kinematic redundancy, and these effects were substantially smaller than the within-participant variability observed across repeated movements in most individuals. Importantly, while segment length estimates shifted absolute joint angle amplitudes, they did not alter the shape of angular trajectories. Conclusions/significance Morphological variability in segment lengths contributes less to joint angle variability than the variability expressed by individuals across repeated movements. This indicates that movement variability inherent in movement execution outweighs that introduced by morphological differences. These findings suggest that motion capture–based assessments of reaching quality remain accurate even when segment lengths are inferred from height, supporting their practical use in remote or telehealth clinical assessments where direct anthropometry is not feasible.

Effect of biochar reinforcement on the mechanical and corrosion behavior of closed-cell aluminum foams

Electrophysiological resting-state signatures link polygenic scores to general intelligence

Abstract Intelligence is associated with important life outcomes. Behavioral, genetic, structural, and functional brain correlates of intelligence have been studied for decades, but questions remain as to how genetics are related to trait expression and what intermediary role brain properties play. This study investigated these mediations in a representative sample of 434 individuals, comprising young and older adults. Polygenic scores (PGS) for intelligence were calculated. Resting-state EEG recordings were analyzed using graph theory quantifying functional connectivity across different frequencies. We tested whether global and local graph metrics like efficiency and clustering mediated the association between PGS and intelligence. PGS significantly predicted variance in intelligence and were related to frequency-specific graph metrics in areas predominantly located in parieto-frontal regions, which in turn were associated with intelligence. These findings, based on the first study linking PGS to intelligence using EEG-derived graph metrics, identify candidate pathways through which genetic variation may shape intelligence, providing a foundation for future hypothesis-driven investigations. Data for this study were collected as part of the Dortmund Vital Study ( https://www.researchprotocols.org/2022/3/e32352 ; ClinicalTrials.gov: NCT05155397).

Evaluation of a “one-stop shop” for integrated harm reduction and primary care for people who inject drugs

Background People who inject drugs (PWID) experience high risk for HIV and HCV infection, which can be mitigated by harm reduction strategies, including syringe service programs (SSP). Understanding individuals’ patterns of substance use and SSP utilization is important for optimizing harm reduction strategies and disease prevention for PWID. Methods We evaluated demographic characteristics and service utilization from the New Haven Syringe Services Program (NHSSP), a low-threshold service delivery site in New Haven, Connecticut that provides fully integrated harm reduction and primary healthcare services to PWID. Site-specific data were extracted from the e2ctprevention database, managed by the Connecticut Department of Public Health, and EvaluationWeb from January 2017 to October 2023. We conducted a descriptive analysis of basic demographic and social characteristics of SSP clients, transaction characteristics, and service utilization. Statistical analyses were conducted using STATA v 16.1 and IBM SPSS Statistics (v 29.0.2.0). Results Among 1,189 unique individuals utilizing SSP during the observation period, most (65.2%) identified as men and white (73.3%), consistent with SSP clients regionally and nationally. The mean age of clients was 41 years (SD = 9.8); approximately half of participants were unstably housed and 80% were unemployed at intake. From June 2020 to October 2023, there were 7,238 transactions, which increased throughout the COVID-19 pandemic period. During this period, the program dispensed 1,860,621 syringes, in addition to other materials, including overdose education and naloxone distribution (OEND), and provided patient education on safer injecting techniques and wound care. Conclusion In this first comprehensive analysis of a large SSP since its inception and through the COVID-19 pandemic, we described important client characteristics and utilization of an array of syringe services from an integrated SSP. Findings suggest the SSP attracts a high volume of clients, provides on-demand services, and reaches a wide range of clients. Future research is needed to evaluate the impact of the program’s home-delivery service and increased outreach efforts. Despite limitations, the program’s success demonstrates the SSP can serve as a model for other harm reduction programs nationally.

Bioinformatics analysis to explore the potential prognostic utility of hsa-miR-103a-3p in head and neck squamous cell carcinoma

Abstract Head and neck squamous cell carcinoma (HNSCC), the seventh most common cancer globally, has not yet seen an exploration of the specific role of hsa-miR-103a-3p. This study employs integrated bioinformatics analysis to investigate the function, regulatory patterns, and prognostic significance of hsa-miR-103a-3p in HNSCC. The Kaplan-Meier database was used for pan-cancer prognostic analysis of hsa-miR-103a-3p. Expression significance was assessed using the dbDEMC and GSE124566 dataset from GEO. TargetScan, RNA22, miRDB, and miRWalk identified potential targets, while GEPIA 2.0 provided differentially expressed genes (DEGs). Functional and pathway enrichment analyses were conducted using ShinyGO and KOBAS. Elevated hsa-miR-103a-3p expression correlated with poor overall survival and was upregulated in HNSCC tissues. Integration of four target prediction tools yielded 297 candidate genes. Among them, HOXD10 , HMGA2 , and THY1 showed the highest expression, whereas UBL3 , AMOT , and PDK4 displayed low levels. UBE2Q1 , ZFPM2 , and ATXN1 demonstrated the strongest accessibility to hsa-miR-103a-3p binding. Network analysis revealed interactions with transcription factors and tumor-related genes, while enrichment highlighted involvement in upstream regulators and downstream cancer-associated pathways. This study identified 297 target genes and clarified the regulatory role of hsa-miR-103a-3p through interaction networks, transcription factor associations, and pathway enrichment. These findings suggest a potential oncogenic role for hsa-miR-103a-3p in modulating the cAMP signaling pathway, proteoglycans in cancer, and related mechanisms, thereby linking its molecular regulation to poor prognosis and potential therapeutic targeting in HNSCC.

Straintronic and spintronic properties of MnO₂/SiC Van der Waals heterostructure: a DFT study

Single-cell RNA sequencing reveals the role of immunoinflammatory cells in the progression of renal tubulointerstitial fibrosis

Renal tubulointerstitial fibrosis (TIF) is an independent risk factor for chronic kidney disease (CKD) progression and prognosis. It is known that immunoinflammatory cell infiltration plays a crucial role in TIF development and progression. However, what types of immunoinflammatory cells and by what means they promote TIF have not been fully clarified. In this study, mice models of unilateral ureteral obstruction (UUO) in which the left ureters were ligated for 3, 7, and 14 days, respectively, were used to simulate different levels of TIF severity. Single-cell RNA sequencing (scRNA-seq) was performed to characterize the immunoinflammatory cells in the kidneys of mice in each group. The results showed that the degree of renal pathological injury and expression level of fibrosis-related proteins increased over time in the UUO groups. Compared with the sham group, the proportion of T and NK cells, neutrophils, and mononuclear phagocyte cells was elevated in the kidney of UUO mice. Except for a decrease in the UUO7d group, the proportion of B cells did not differ notably between groups. The proportion of NaiveB_Ccl4 subset increased significantly in all UUO groups, and its up-regulated genes were mainly enriched in toll-like receptor signaling. The proportions of CD8Teff_Arhgap15, GDTCells_Trdc, HelperT_Tnf, and Treg_Foxp3 subsets were also significantly increased in all UUO groups, and their up-regulated genes were mainly enriched in NF-kappa B and TNF signaling. Neutrophils-4 subset was located at the terminal of neutrophil differentiation and mainly activated cytokine production and mitochondrial autophagy. Notably, the Macrophages_Arg1 subset had high scores in extracellular matrix remodeling, pro-angiogenesis, pro-inflammation, and immune regulation. Moreover, interactions between fibroblasts and immunoinflammatory cells increased with prolonged UUO time, with the strongest interactions with macrophages. When fibroblasts acted as ligand cells, the important interacting gene pairs with immunoinflammatory cells were CXCL6-CXCR1, APP-CD74, CX3CL1-CX3CR1, and THBS1-CD36, whereas when fibroblasts acted as receptor cells, the important interacting gene pairs with immunoinflammatory cells were TYROBP-CD44, TNF-TNFRSF1A, LGALS3-MERTK, PDGFA/B-PDGFRA, OSM-OSMR, and DKK2-LRP6. Overall, this study revealed the dynamic changes of immunoinflammatory cells and their interactions with fibroblasts in the kidneys during the UUO-induced TIF process.