Search Results (22,886)

Quasi-solid aqueous zinc batteries (QSAZBs) have wide applications in the energy storage field due to their advantages of high safety, cost-effectiveness, and eco-friendliness. Despite prolific research output in the field of QSAZBs, existing reviews predominantly focus on experimental advancements, with limited synthesis of global research trends, interdisciplinary connections, or knowledge gaps. Herein, we review the research on QSAZBs via bibliometric analysis using the VOSviewer software (version 1.6.20). First, the data from qualitatively evaluated publications on QSAZBs from 2016 and 2024 are integrated. In addition, the annual trends, leading countries/regions and their international collaborations, institutional research and patent distribution, and important keyword cluster analyses in QSAZB research are evaluated. The results reveal that China dominates in terms of publication output (71.16% of total papers), and Singapore exhibits the highest citation impact (103.2 citations/paper). International collaboration networks indicate the central role of China, with strong ties to Singapore, the USA, and Australia. Keyword clustering indicates core research priorities: cathode materials (MnO₂ and V₂O₅), quasi-solid electrolyte optimization (hydrogels and graphene composites), and interfacial stability mechanisms. By mapping global trends and interdisciplinary linkages, this work provides insights to accelerate QSAZBs’ transition from laboratory breakthroughs to grid-scale and wearable applications. Full article

Background: Delays in breast cancer treatment negatively affect prognosis and have increased over time. Data on waiting times in Switzerland are limited. Patients and Methods: This study analyzed cancer registry data from 2003 to 2005 (2628 patients) and 2015 to 2017 (421 patients) to evaluate waiting times for diagnosis, surgery, and radiotherapy; temporal trends; and survival in women with stage I–III invasive breast cancer treated with surgery without chemotherapy. Associations with demographic/clinical factors and overall survival (OS) were assessed using ANOVA, uni-/multivariable regression, Kaplan–Meier, and Cox regression. Results: From 2003 to 2005, mean intervals were biopsy-to-diagnosis 4.3 days, diagnosis-to-surgery 18.8 days, biopsy-to-surgery 26.8 days, and surgery-to-radiotherapy 56.7 days. Longer diagnosis-to-surgery times were associated with metropolitan areas, public hospitals, basic insurance, mastectomy, and older age (all p < 0.001). Radiotherapy delays were also longer in metropolitan areas and after mastectomy (p < 0.001). Between 2003–2005 and 2015–2017, diagnosis-to-surgery times rose in Eastern Switzerland (from 21.3 to 31.2 days), while radiotherapy timing remained stable. Five-year overall survival improved (from 76.7% to 88.4%), but was not significantly impacted by diagnosis-to-surgery intervals. Conclusions: Despite timely surgery in Switzerland (2003–2005), disparities existed, and time to surgery increased by 2015–2017. Reducing waiting times remains important despite no significant short-term OS impact. Full article

This narrative review explores the role of additive manufacturing (AM) technologies in the production of dental implants, focusing on materials and key AM methods. The study discusses several materials used in implant fabrication, including porous titanium, trabecular tantalum, zirconium dioxide, polymers, and composite materials. These materials are evaluated for their mechanical properties, biocompatibility, and suitability for AM processes. Additionally, the review examines the main AM technologies used in dental implant production, such as selective laser melting (SLM), electron beam melting (EBM), stereolithography (SLA), selective laser sintering (SLS), and direct metal laser sintering (DMLS). These technologies are compared based on their accuracy, material limitations, customization potential, and applicability in dental practice. The final section presents a data source analysis of the Web of Science and Scopus databases, based on keyword searches. The analysis evaluates the research trends using three criteria: publication category, document type, and year of publication. This provides an insight into the evolution and current trends in the field of additive manufacturing for dental implants. The findings highlight the growing importance of AM technologies in producing customized and efficient dental implants. Full article

Objectives: The aim of this study was to evaluate the impact of four working heights on lumbar biomechanics during wall construction tasks, focusing on work-related musculoskeletal disorders (WMSDs). Methods: Fifteen young male participants performed simulated mortar-spreading and bricklaying tasks while actual body movements were recorded using Inertial Measurement Unit (IMU) sensors. Muscle activities of the lumbar erector spinae (ES), quadratus lumborum (QL), multifidus (MF), gluteus maximus (GM), and iliopsoas (IL) were estimated using a 3D musculoskeletal (MSK) model and measured via surface electromyography (sEMG). The analysis of variance (ANOVA) test was conducted to identify the significant differences in muscle activities across four working heights (i.e., foot, knee, waist, and shoulder). Results: Findings showed that working at foot-level height resulted in the highest muscle activity (7.6% to 40.6% increase), particularly in the ES and QL muscles, indicating an increased risk of WMSDs. The activities of the ES, MF, and GM muscles were statistically significant across both tasks and all working heights (p < 0.01). Conclusions: Both MSK and sEMG analyses indicated significantly lower muscle activities at knee and waist heights, suggesting these as the best working positions (47 cm to 107 cm) for minimizing the risk of WMSDs. Conversely, working at foot and shoulder heights was identified as a significant risk factor for WMSDs. Additionally, the similar trends observed between MSK simulations and sEMG data suggest that MSK modeling can effectively substitute for sEMG in future studies. These findings provide valuable insights into ergonomic work positioning to reduce WMSD risks among wall construction workers. Full article

Potassium bromide (KBr) thin films were deposited by resistive thermal evaporation at substrate temperatures ranging from 50 °C to 250 °C to systematically elucidate the temperature-dependent evolution of their physical properties. Structural, morphological, and optical characteristics were examined by X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), and Fourier transform infrared spectroscopy (FTIR). The results reveal a complex, non-monotonic response to temperature rather than a simple linear trend. As the substrate temperature increases, growth evolves from a mixed polycrystalline texture to a pronounced (200) preferred orientation. Morphological analysis shows that the film surface is smoothest at 150 °C, while the microstructure becomes densest at 200 °C. These structural variations directly modulate the optical constants: the refractive index attains its highest values in the 150–200 °C window, approaching that of bulk KBr. Cryogenic temperature (6 K) FTIR measurements further demonstrate that suppression of multi-phonon absorption markedly enhances the infrared transmittance of the films. Taken together, the data indicate that 150–200 °C constitutes an optimal process window for fabricating KBr films that combine superior crystallinity, low defect density, and high packing density. This study elucidates the temperature-driven structure–property coupling and offers valuable guidance for optimizing high-performance infrared and cryogenic optical components. Full article

Forest fires are commonly regarded as negative for ecosystems; however, they also represent a major ecological force shaping the biodiversity of invertebrates and many other organisms. The aim of this study was to better understand how multiple groups of invertebrates respond to wildfire across different forest types in Central Europe. The research was conducted following a large forest fire (ca. 1200 ha) that occurred in 2022. Data were collected over two years (2023 and 2024), from April to September. The research was conducted in coniferous forests and included six pairwise study types: burnt and unburnt dead spruce (bark beetle affected), burnt and unburnt clear-cuts, and burnt and unburnt healthy stands. In total, 96 traps were deployed each year. Across both years, 220,348 invertebrates were recorded (1.Y: 128,323; 2.Y: 92,025), representing 24 taxonomic groups. A general negative trend in abundance following forest fire was observed in the groups Acari, Auchenorhyncha, Blattodea, Dermaptera, Formicidae, Chilopoda, Isopoda, Opiliones, and Pseudoscorionida. Groups showing a neutral response included Araneae, Coleoptera, Collembola, Diplopoda, Heteroptera, Psocoptera, Raphidioptera, Thysanoptera, and Trichoptera. Positive responses, indicated by an increase in abundance, were recorded in Hymenoptera, Orthoptera, Lepidoptera, and Diptera. However, considerable differences among management types (clear-cut, dead spruce, and healthy) were evident, as their distinct characteristics largely influenced invertebrate abundance in both unburnt and burnt variants of the types across all groups studied. Forest fire primarily creates favorable conditions for heliophilous, open-landscape, and floricolous invertebrate groups, while less mobile epigeic groups are strongly negatively affected. In the second year post-fire, the total invertebrate abundance in burnt sites decreased to 59% of the first year’s levels. Conclusion: Forest fire generates a highly heterogeneous landscape from a regional perspective, creating unique ecological niches that persist more than two years after fire. For many invertebrates, successional return toward pre-fire conditions is delayed or incomplete. Full article

Oil spill simulation models are essential for predicting the oil spill behavior and movement in marine environments. In this study, we comprehensively reviewed a large and diverse body of peer-reviewed literature obtained from Scopus and Web of Science. Our initial analysis phase focused on examining trends in scientific publications, utilizing the complete dataset derived after systematic screening and database integration. In the second phase, we applied elements of a systematic review to identify and evaluate the most influential contributions in the scientific field of oil spill simulations. Our analysis revealed a steady and accelerating growth of research activity over the past five decades, with a particularly notable expansion in the last two. The field has also experienced a marked increase in collaborative practices, including a rise in international co-authorship and multi-authored contributions, reflecting a more global and interdisciplinary research landscape. We cataloged the key modeling frameworks that have shaped the field from established systems such as OSCAR, OIL-MAP/SIMAP, and GNOME to emerging hybrid and Lagrangian approaches. Hydrodynamic models were consistently central, often integrated with biogeochemical, wave, atmospheric, and oil-spill-specific modules. Environmental variables such as wind, ocean currents, and temperature were frequently used to drive model behavior. Geographically, research has concentrated on ecologically and economically sensitive coastal and marine regions. We conclude that future progress will rely on the real-time integration of high-resolution environmental data streams, the development of machine-learning-based surrogate models to accelerate computations, and the incorporation of advanced biodegradation and weathering mechanisms supported by experimental data. These advancements are expected to enhance the accuracy, responsiveness, and operational value of oil spill modeling tools, supporting environmental monitoring and emergency response. Full article

Background/Objectives: Targeting individuals with certain characteristics provides improved precision in many healthcare applications. An alert mechanism for COPD exacerbations has recently been validated. It has been argued that its efficacy improves considerably with stratification. This paper provides an in-depth analysis of the cough data of the stratified cohort to identify options for and the feasibility of improved precision in the alert mechanism for the intended patient group. Methods: The alert system was extended using a system complementary to the existing one to accommodate observed rapid changes in cough trends. The designed system was tested in a post hoc analysis of the data. The trend data were inspected to consider their meaningfulness for patients and caregivers. Results: While stratification was effective in reducing misses, the augmented alert system improved the sensitivity and number of early alerts for the acute exacerbation of COPD (AE-COPD). The combination of stratification and the augmented mechanism led to sensitivity of 86%, with a false alert rate in the order of 1.5 per year in the target group. The alert system is rule-based, operating on interpretable signals that may provide patients or their caregivers with better insights into the respiratory condition. Conclusions: The augmented alert system operating based on cough trends has the promise of increased precision in detecting AE-COPD in the target group. Since the design and testing of the augmented system were based on the same data, the system needs to be validated. Signals within the alert system are potentially useful for improved self-management in the target group. Full article

Accurate forecasting of tropical cyclone (TC) tracks is critical for disaster preparedness and risk mitigation. While traditional numerical weather prediction (NWP) systems have long served as the backbone of operational forecasting, they face limitations in computational cost and sensitivity to initial conditions. In recent years, deep learning (DL) has emerged as a promising alternative, offering data-driven modeling capabilities for capturing nonlinear spatiotemporal patterns. This paper presents a comprehensive review of DL-based approaches for TC track forecasting. We categorize all DL-based TC tracking models according to the architecture, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), Transformers, graph neural networks (GNNs), generative models, and Fourier-based operators. To enable rigorous performance comparison, we introduce a Unified Geodesic Distance Error (UGDE) metric that standardizes evaluation across diverse studies and lead times. Based on this metric, we conduct a critical comparison of state-of-the-art models and identify key insights into their relative strengths, limitations, and suitable application scenarios. Building on this framework, we conduct a critical cross-model analysis that reveals key trends, performance disparities, and architectural tradeoffs. Our analysis also highlights several persistent challenges, such as long-term forecast degradation, limited physical integration, and generalization to extreme events, pointing toward future directions for developing more robust and operationally viable DL models for TC track forecasting. To support reproducibility and facilitate standardized evaluation, we release an open-source UGDE conversion tool on GitHub. Full article

Over the past decade, the number and diversity of identified protein post-translational modifications (PTMs) have grown significantly. However, most PTMs occur at relatively low abundance, making selective enrichment of modified peptides essential. To address this, we developed a thermodynamic model describing the free beads enrichment in suspension enrichment process and derived a theoretical relationship between material dosage and analyte recovery. The model predicts a non-linear trend, with enrichment efficiency increasing up to an optimal dosage and declining thereafter—a pattern confirmed by experimental data. We validated the model using centrifugation-based enrichment for glycosylated peptides and magnetic-based enrichment for phosphorylated peptides. In both cases, the results aligned with theoretical predictions. Additionally, the optimal dosage varied among peptides with the same modification type, highlighting the importance of tailoring enrichment strategies. This study provides a solid theoretical and experimental basis for optimizing PTMs enrichment and advancing more sensitive, accurate, and efficient mass spectrometry-based proteomic workflows. Full article

Since late 2023, an increase in Bordetella pertussis infections has been noticed in Europe, particularly among children. Our data showed the upward trend of B. pertussis cases in the Lazio region, even among adults with severe influenza-like illnesses, highlighting the necessity for maintaining high vaccination rates across both children and adults. These findings underscore the urgent need for clinicians to maintain a high index of suspicion for B. pertussis in patients with respiratory symptoms, prioritize nasopharyngeal swabs for accurate diagnosis, assess for co-infections, verify booster vaccination status in adults, and support timely reporting to public health authorities. Full article

Food security is crucial for social stability and economic development. Ensuring food security in the arid region of Northwest China presents unique challenges due to limited water and soil resources. This study addresses these challenges by integrating a comprehensive water and soil resource matching assessment with grain production forecasting. Based on data from 2000 to 2020, this research projects the food security status to 2035 using the GM(1,1) model, incorporating a comprehensive index of soil and water resource matching and regression analysis to inform production forecasts. Key assumptions include continued historical trends in population growth, urbanization, and dietary shifts towards an increased animal protein consumption. The findings revealed a consistent upward trend in grain production from 2000 to 2020, with an average annual growth rate of 3.5%. Corn and wheat emerged as the dominant grain crops. Certain provinces demonstrated comparative advantages for specific crops like rice and wheat. The most significant finding is that despite the projected growth in the total grain output by 2035 compared to 2020, the regional grain self-sufficiency rate is projected to range from 79.6% to 84.1%, falling below critical food security benchmarks set by the FAO and China. This projected shortfall carries significant implications, underscoring a serious challenge to regional food security and highlighting the region’s increasing vulnerability to external food supply fluctuations. The findings strongly signal that current trends are insufficient and necessitate urgent and proactive policy interventions. To address this, practical policy recommendations include promoting water-saving technologies, enhancing regional cooperation, and strategically utilizing the international grain trade to ensure regional food security. Full article

Background: The implementation of intravenous thrombolysis (IVT) and mechanical thrombectomy (MT) in acute ischemic stroke (AIS) has proven effective, offering significant benefits for patient outcomes. We therefore investigated trends in the implementation of IVT and MT in Germany between 2015 and 2023. Methods: We conducted a retrospective analysis using German Diagnosis-Related Group (DRG) statistics from 2015 to 2023. Treatment numbers were analyzed annually based on OPS codes. We examined the age and sex distribution of patients undergoing these treatments. Additionally, we analyzed all hospital cases coded with ICD-10 for acute ischemic stroke (AIS). Results: Between 2015 and 2023, the number of AIS cases in Germany slightly declined from 250,802 to 248,107 (−1.1%), with the largest annual decrease (−4.3%) occurring during the COVID-19 pandemic (2019–2020). Despite this, the use of IVT increased from 40,766 cases (16.25%) in 2015 to 48,378 (19.50%) in 2023. MT usage rose even more sharply, from 7840 cases (3.13%) to 22,445 (9.05%). Among MT recipients, the proportion of patients aged ≥80 years rose significantly, from 27.2% to 42.1%. In this age group, women consistently comprised the majority of MT patients—65.4% in 2015 and 65.5% in 2023. Conclusions: Despite a stable stroke incidence, the use of IVT—and particularly MT—continued to increase in Germany from 2015 to 2023, even during the COVID-19 pandemic. MT usage nearly tripled, especially among patients aged ≥80 years. These trends highlight a resilient stroke care system and underscore the need for future planning to meet the rising demand for endovascular treatment in an aging population. Full article

To address the inefficiency of traditional concrete crack detection methods and the heavy reliance of supervised learning on extensive labeled data, in this study, an intelligent assessment method of concrete damage based on pseudo-label semi-supervised learning and fractal geometry theory is proposed to solve two core tasks: one is binary classification of pixel-level cracks, and the other is multi-category assessment of damage state based on crack morphology. Using three-channel RGB images as input, a dual-path collaborative training framework based on U-Net encoder–decoder architecture is constructed, and a binary segmentation mask of the same size is output to achieve the accurate segmentation of cracks at the pixel level. By constructing a dual-path collaborative training framework and employing a dynamic pseudo-label refinement mechanism, the model achieves an F1-score of 0.883 using only 50% labeled data—a mere 1.3% decrease compared to the fully supervised benchmark DeepCrack (F1 = 0.896)—while reducing manual annotation costs by over 60%. Furthermore, a quantitative correlation model between crack fractal characteristics and structural damage severity is established by combining a U-Net segmentation network with the differential box-counting algorithm. The experimental results demonstrate that under a cyclic loading of 147.6–221.4 kN, the fractal dimension monotonically increases from 1.073 (moderate damage) to 1.189 (failure), with 100% accuracy in damage state identification, closely aligning with the degradation trend of macroscopic mechanical properties. In complex crack scenarios, the model attains a recall rate (Re = 0.882), surpassing U-Net by 13.9%, with significantly enhanced edge reconstruction precision. Compared with the mainstream models, this method effectively alleviates the problem of data annotation dependence through a semi-supervised strategy while maintaining high accuracy. It provides an efficient structural health monitoring solution for engineering practice, which is of great value to promote the application of intelligent detection technology in infrastructure operation and maintenance. Full article

Tennis is a demanding sport that requires physical abilities and optimal body composition. The aim of this study was to investigate the anthropometric characteristics, body composition, and somatotype development of young Slovenian tennis players (754 boys and 514 girls aged 12 to 18 years) over the last two decades. Using standardised anthropometric measurements and the Heath-Carter method, somatotypes were calculated and analysed by age and gender. The results showed clear age- and gender-specific trends and differences in both somatotype profiles and detailed anthropometric characteristics. Significant differences were found in height, body mass, BMI, skinfolds, girths, and limb lengths, with gender differences becoming more pronounced in the older age groups. In boys, mesomorphy increased with age, reflecting an increase in musculature, while in girls, a shift from ectomorphic to endomorphic profiles was observed during adolescence, probably influenced by pubertal and hormonal changes. Significant sex-specific differences were observed in all three somatotype components in most age groups, especially in fat mass and muscle. The longitudinal design provides valuable data and insights into the evolving physical profiles of adolescent tennis players that support more effective talent identification and training. Despite the changes that have taken place in tennis over time, standardised measurement protocols ensured comparability, making the results relevant for practitioners working with adolescents in tennis development. Full article