Search Results (16,304)

Background/Objectives: Appropriate imaging surveillance, established by the Society of Vascular Surgery (SVS), following endovascular aorta repair (EVAR) is critical for patient monitoring. We hypothesized that adherence to follow-up decreases over time, and therefore, the ability to detect endoleaks after EVAR also decreases. Methods: A retrospective cohort study of patients who underwent EVAR from 2014 to 2022 at our institution was completed. Patients were stratified by adherence to SVS guidelines for up to five years postoperatively. Demographics, detection of an endoleak > 30 days postoperatively, distance from our facility, and Area Deprivation Index (ADI) were collected. Comparisons of baseline comorbidities between groups and multivariate logistic regressions were performed using R studio. Results: 395 patients underwent an index EVAR at our institution from 2014–2022. 174 (44%) of patients adhered to all imaging recommendations, with an average loss to follow-up of 9.7% per year. 61 (15.4%) patients had a detected type II endoleak during the study period. Multivariable analysis identified residence > 50 miles from our institution as an independent risk factor for nonadherence (OR 1.76, p = 0.018) when controlling for age, sex, race, and ADI quartile. Conclusions: Adherence to surveillance guidelines gradually decreases after EVAR, but type II endoleak detection continues to occur years following the operation. While residence greater than 50 miles away was associated with nonadherence, patients’ ADI was not. Our results identify an opportunity for providers who may see patients more frequently to assist in reminding and arranging imaging follow-up for patients following their procedure. Full article

Background: Personalized and accurate assessment of functional performance in chronic obstructive pulmonary disease (COPD) requires patient-centered tools that capture individualized activity limitations. The Patient-Specific Functional Scale (PSFS) is brief and clinically accessible, but its psychometric properties in COPD have not been fully established. This study aimed to evaluate the reliability and construct validity of the PSFS in individuals with COPD. Methods: A longitudinal psychometric evaluation was conducted with 70 adults diagnosed with COPD confirmed by spirometry. The PSFS was administered twice, 4–7 days apart, to examine test–retest reliability, standard error measurement (SEM), and minimal detectable change at 95% confidence interval (MDC_95%). Construct validity was assessed through correlations between the PSFS, the Duke Activity Status Index (DASI), and the St. George’s Respiratory Questionnaire (SGRQ). Floor and ceiling effects were also evaluated. Results: Seventy participants (mean age 63 ± 11 years) completed the study. The PSFS demonstrated excellent test–retest reliability (ICC = 0.94; 95% CI: 0.90–0.96), and low SEM (0.16 points), and the MDC_95% was 0.44 points, with no floor or ceiling effects. Construct validity was supported by moderate positive correlations with DASI (r = 0.51, p < 0.001) and moderate negative correlations with SGRQ total scores (r = –0.41, p < 0.001). PSFS scores were not associated with demographic variables or COPD severity. Conclusions: The PSFS demonstrates strong psychometric properties in COPD, including excellent reliability and moderate construct validity. Its individualized approach, ease of administration, and ability to capture functional limitations beyond traditional clinical measures support its utility in both clinical practice and research for personalized functional assessment. Full article

Carbon sequestration by vegetation and soil conservation are vital components in balancing greenhouse gas emissions and enhancing terrestrial ecosystem carbon sinks. They also represent an efficient pathway towards achieving carbon neutrality objectives and addressing numerous environmental challenges arising from global warming. Soil and water conservation, as crucial elements of ecological civilisation development, constitute a key link in realising carbon neutrality. This study systematically quantifies and forecasts the spatiotemporal characteristics of carbon sink capacity in soil and water conservation within the study area of Puding County, a typical karst region in Guizhou Province, China. Following a research approach of “mechanism elucidation–model construction–categorised estimation”, we established a carbon sink calculation system based on the dual mechanisms of vertical biomass carbon fixation via vegetative measures and horizontal soil organic carbon (SOC) retention using engineering measures. This system combines forestry, grassland, and engineering, with the aim of quantifying regional carbon sinks. Machine learning regression algorithms such as Random Forest, ExtraTrees, CatBoost, and XGBoost are used for backtracking estimation and optimisation modelling of soil and water conservation as carbon sinks from 2010 to 2022. The results show that the total carbon sink capacity of soil and water conservation in Puding County in 2017 was 34.53 × 10⁴ t, while the contribution of engineering measures was 22.37 × 10⁴ t. The spatial distribution shows a pattern of “higher in the north and lower in the south”. There are concentration hotspots in the central and western regions. Model comparison demonstrates that the Random Forest and extreme gradient boosting regression models are the best models for plantations/grasslands and engineering measures, respectively. The LSTM model was applied to predict carbon sink variables over the next ten years (2025–2034), showing that the overall situation is relatively stable, with only slight local fluctuations. This study solves the problem of the lack of quantitative data on soil and water conservation as carbon sinks in karst areas and provides a scientific basis for regional ecological governance and carbon sink management. Our findings demonstrate the practical significance of promoting the realisation of the “double carbon” goal. Full article

This study examines how the education sector in one Canadian province has navigated post-pandemic recovery between 2023 and 2025, drawing on cross-sectional survey data from a convenience sample of sector employees in the 2023–2024 (n = 1411) and 2024–2025 (n = 742) school years. The findings revealed selective improvement over time, including increased organizational commitment among teachers and other education workforce members, alongside reduced perceptions of students’ academic, social, and behavioural needs. Teachers indicated no corresponding increases in their perceived frequency of meeting students’ needs, whereas other educator sector employees indicated improvement in this area. In contrast, no year-over-year differences were found in the education workforce members’ and teachers’ stress, coping, well-being or connectedness, and job search behaviours remained high, ranging from 14 to 43%. Guided by the Job Demands–Resources (JD-R) model, these findings suggest that post-pandemic recovery reflects the establishment of a new and complex baseline. The coexistence of improved commitment with persistent job strain signals a paradox of stability amid depletion. Qualitative responses reinforced this interpretation, revealing how educators adapt to ongoing organizational resource constraints and shifting student needs. Together, the findings extend JD-R-informed understandings of post-crisis workforce adaptation and identify implications for leadership and policy aimed at supporting organizational health and workforce sustainability. Full article

To promote a sustainable coffee industry, Davao Oriental has branded its coffee in association with Mt. Hamiguitan. This study profiles the production capacities and agricultural practices of smallholder coffee farmers along the Mt. Hamiguitan buffer zone, focusing on women’s roles and farmers’ climate change awareness and adaptation strategies. Fifty-seven purposively selected farmers (28 females, 29 males) were interviewed using a validated semi-structured questionnaire. Data were analyzed using thematic analysis and descriptive statistics. Most farmers (70%) were old (≥51) with over 40 years of experience (51%). Non-participation in farmers’ associations (73.7%) surpassed active membership (26.3%), with only 14% attending training. Most farmers (65%) intercropped 500–600 Robusta coffee trees/ha, with many farms established in the 1980s (36%). The farmers performed clearing (82%) and pruning (94%) of their coffee. Women played a vital role, especially during drying and harvesting. All respondents acknowledged climate change and employed practices such as intercropping, pruning, using ipil-ipil for shade, and utilizing nets, which, though originally aimed at improving crop resilience, can also serve as adaptations to mitigate the impacts of climate change. Recommendations for fostering sustainable practices while improving livelihoods include joining cooperatives, providing training for enhanced climate change adaptation strategies, and increasing women’s participation in coffee production. Full article

China’s nuclear power plants traditionally operate to meet baseload needs, with minimal involvement in peak load regulation. However, as the share of renewable energy generation rapidly increases, the volatility of the power system and the demand for peak load regulation have significantly risen, necessitating greater nuclear power flexibility to meet the new power system’s requirements. Our study forecasts the energy structure and load demand for the Province of Liaoning in Northeastern China in 2035. Under this vision, it analyzes the flexibility challenges faced by nuclear generation units. A joint clearing model for spot electricity and ancillary services, along with an energy storage revenue model, was established. Based on this, this study analyzed the clearing results for various typical scenarios in the Province of Liaoning in 2035. The simulation results demonstrate that nuclear units will participate in peak shaving by the target year. This study demonstrates the feasibility of solid-state thermal storage in improving both flexibility and economic efficiency of nuclear generation. Based on these findings, policy recommendations are proposed, including improving regulation compensation mechanisms and promoting multi-energy coupling, providing crucial theoretical and practical support for the role transformation of nuclear generation entities in the new power system. This study establishes a full lifecycle economic assessment model for combined heat and power revenue versus thermal storage investment costs, considering integrated nuclear power–solid thermal energy storage heating systems as the primary technical pathway. Taking a configuration plan with a 715 MW heating capacity and a 6000 MWh thermal storage capacity as an example under Liaoning Province’s 2035 long-term scenario, the simulation results indicate that introducing solid thermal energy storage can significantly improve the revenue structure of nuclear units while meeting deep peak shaving demands, reducing the project’s static payback period to under 11 years. Full article

Water and nitrogen are the key factors restricting the productivity improvement of onion in the Hexi Oasis. Unreasonable water and fertilizer management not only increases input costs, but also causes environmental pollution of farmland soil, thereby affecting the sustainable development of agriculture. To explore the effects of the water–nitrogen interaction and optimized combination schemes on onion yield, water–nitrogen use efficiency, and economic benefits under mulched drip irrigation in the Hexi Oasis, a four-year (2020–2023) water–nitrogen coupling regulation experiment was conducted at the Yimin Irrigation Experimental Station in Minle County, Hexi Corridor. The onion was used as the test crop and three irrigation levels were established, based on reference crop evapotranspiration (ET_c): low water (W1, 70% ET_c), medium water (W2, 85% ET_c), and sufficient water (W3, 100% ET_c), as well as high nitrogen N3 (330 kg·ha⁻¹), medium nitrogen N2 (264 kg·ha⁻¹), and low nitrogen N1 (198 kg·ha⁻¹). Meanwhile, no nitrogen application N0 (0 kg·ha⁻¹) was set as the control at three irrigation levels. This study analyzed the effects of different water and nitrogen supply conditions on onion quality, yield, water–nitrogen use efficiency, and economic benefits. A water–nitrogen economic benefit coupling model was established to optimize water–nitrogen combination schemes targeting different economic objectives. The results revealed that medium-to-high water–nitrogen combinations were beneficial for improving onion quality, while excessive irrigation and nitrogen application inhibited bulb quality accumulation. Both yield and economic benefits increased with the increasing amount of irrigation, whereas excessive nitrogen application showed a diminishing yield-increasing effect, simultaneously increasing farm input costs and ultimately reducing the economic benefits. In the four-year experiment, the N3W3 treatment in 2020 achieved the highest yield, economic benefits, and net profit, reaching 136.93 t·ha⁻¹, 20,376.3 USD·ha⁻¹, and 14,320.8 USD·ha⁻¹, respectively, with no significant difference from the N2W3 treatment. From 2021 to 2023, the N2W3 treatment achieved the highest yield, economic benefits, and net profit, averaging 130.87 t·ha⁻¹, 28,449.5 USD·ha⁻¹, and 21,881.5 USD·ha⁻¹, respectively. Lower irrigation and nitrogen application rates mutually restricted the water and nitrogen utilization, resulting in low water use efficiency, irrigation water use efficiency, nitrogen partial factor productivity, and nitrogen agronomic use efficiency. The relationship between the irrigation amount, nitrogen application rate, and the economic benefits of onion fits a bivariate quadratic regression model. This model predicts that onion’s economic benefits are highly correlated with the actual economic benefits, with analysis revealing a parabolic trend in economic benefits as water and nitrogen inputs increase. By optimizing the model, it was determined that when the irrigation amount reached 100%, the ET_c and nitrogen application rate was 264 kg·ha⁻¹, and the economic benefits were close to the target range of 27,000–29,000 USD·ha⁻¹; this can be used as the optimal water and nitrogen management model and technical reference for onion in the Hexi Oasis irrigation area, which can not only ensure high yield and quality but also improve the use efficiency of water and nitrogen. Full article

This paper proposes a novel fusion paradigm integrating information entropy with deep learning architectures to address the challenges of uncertainty, robustness, and subjectivity in intelligent open-pit mining management. Methodologically, we develop three integrated models: an IE-LSTM model for dynamic ore blending that quantifies system uncertainty to balance efficiency with robustness, an IE-CNN model that utilizes local image entropy to filter false alarms for robust visual detection, and an IE-DNN model employing entropy-weighted objective evaluation for equipment performance. These models form the computational core of an intelligent control system deployed at the Qidashan Iron Mine. Industrial validation conducted over a two-year period demonstrated that the framework led to a blending accuracy of 93.6%, a 73.7% reduction in visual detection false alarms, and objective equipment performance scoring. System-wide outcomes included a resource utilization rate of 98.64%, improvements in overall equipment effectiveness between 4.07% and 22.70%, and cumulative direct economic benefits exceeding 43 million RMB. This research establishes a systematic framework that transitions mine operations from experience-based to data-driven intelligent control, distinguishing itself by explicitly quantifying and managing uncertainty through entropy–deep learning fusion. This provides a replicable blueprint for the mining industry’s digital transformation. It effectively addresses the high-dimensional complexity and dynamic uncertainties inherent in open-pit mining environments. Full article

Concrete structures in western saline soil regions are subjected to extreme environments with coupled dry-wet cycles and high concentrations of erosive ions such as Cl⁻, SO₄²⁻, and Mg²⁺, leading to severe degradation of mechanical properties. This study employed a simulated accelerated, high-concentration solution (Solution A, ~8× seawater salinity) similar to the composition of actual saline soil to perform accelerated dry-wet cycling corrosion tests on ordinary C40 concrete specimens for six corrosion ages (0, 5, 8, 10, 15, and 20 months). For each age, three replicate cube specimens were tested per property. The changes in cube compressive strength, splitting tensile strength, prism stress–strain full curves, and microstructure were systematically investigated. Results show that in the initial corrosion stage (0–5 months), strength exhibits a brief increase (compressive strength by 11.87%, splitting tensile strength by 9.23%) due to pore filling by corrosion products such as ettringite, gypsum, and Friedel’s salt. It then enters a slow deterioration stage (5–15 months), with significant strength decline by 20 months, where splitting tensile strength is most sensitive to corrosion. Long-term prediction models for key parameters such as compressive strength, splitting tensile strength, elastic modulus, peak stress, and peak strain were established based on grey GM(1,1) theory using the measured data from 0 to 20 months, achieving “excellent” accuracy (C ≤ 0.1221, p = 1). A segmented compressive constitutive model that considers the effect of corrosion time was proposed by combining continuous damage mechanics and the Weibull distribution. The ascending branch showed high consistency with the experimental curves. Life prediction indicates that under natural dry-wet cycling conditions, the service life of ordinary concrete in this region is only about 7.5 years when splitting tensile strength drops to 50% of initial value as the failure criterion, far below the 50-year design benchmark period. This study provides reliable theoretical models and a quantitative basis for durability design and life assessment of concrete structures in western saline soil regions. Full article

Background: Clear cell renal cell carcinoma (RCC) is the most common primary tumor that metastasizes to the pancreas, and surgery is the established treatment option. The aim of this study was to compare surgical treatment options for RCC metastases to the pancreas and to assess long-term outcomes, identifying risk factors for recurrence and death. Methods: We retrospectively analyzed data from 62 patients with RCC metastases to the pancreas who underwent pancreatic surgery at the Department of Gastrointestinal Surgery, Medical University of Silesia, Katowice. Patients were divided into two groups: those who underwent local tumor removal (group A, N = 10) and those who underwent classical pancreatic resection (group B, N = 52). Demographic data, postoperative course, histological findings, and clinical outcomes—recurrence-free survival (PFS) and overall survival (OS)—were analyzed. Results: In group A, tumors were smaller (p < 0.001) and exclusively single (p = 0.100), and Clavien–Dindo complications were milder, with a predominance of grade 0 (90% vs. 28.8%; p = 0.042). In group B, blood loss was greater (p < 0.001), and hospitalization was longer (median 12.5 days vs. 10.5 days; p = 0.022) compared with group A. Group A had a longer PFS (144 months vs. 61 months; p = 0.007) and longer OS (144 months vs. 70 months; p = 0.006) compared with group B. In the entire cohort, independent factors associated with worse OS in multivariate analysis were larger tumor size (p = 0.003), lymphatic invasion (p < 0.001), vascular invasion (p < 0.001), perineural invasion (p < 0.001), R1 resection (p < 0.001), and symptoms of the metastases (p < 0.001). Conclusions: The prognosis following surgical resection of pancreatic RCC metastases is excellent: median OS is 77 months, and 5-year survival reaches 71.4%. In multivariate analysis, the type of surgical treatment is not significantly associated with OS or PFS. The choice of surgical procedure should depend on the preoperative CT results and the intraoperative assessment of the surrounding tissues. Full article

In recent years, the production of tight reservoirs with waterflooding in China has entered a progressively declining phase with unstable oil rate and higher water cut, rising challenges to any further enhancement of oil recovery. Targeting the high water cut and complex pore structure characteristics typical of these reservoirs, this work evaluates the reservoir compatibility of a microspheres-alternating-nanoemulsion flooding process and optimizes its injection strategy. Representative reservoir scenarios were first established; laser-particle-size analyzers and other laboratory instruments were then employed to quantify formulation-reservoir compatibility. A multiscale numerical study has been performed with CMG-STARS v.2022. The core-scale simulations systematically examined the influence of key factors on displacement efficiency improvement and water cut reduction, matched with the experimental results of core flooding tests. The combined experimental/numerical workflow furnishes a theoretical framework for optimizing the injection scheme. Beyond assessing formulation compatibility, the study delivers optimized injection parameters and strategies for microspheres-alternating-nanoemulsion flooding, providing both theoretical analysis and practical technology reference for improving oil recovery in tight reservoirs with higher water cut. Specifically, when the microsphere concentration increased from 0.1% to 0.3%, the minimum water cut was reduced by approximately 5%, while further concentration increases showed no significant additional impact on water content. Compared with water flooding, the relative permeability curve of the microspheres-alternating-nanoemulsion flooding system shifted entirely to the right. Numerical simulation of representative well groups revealed that a slug design with a microsphere-to-nanoemulsion ratio of 1:3 yielded the optimal enhanced oil recovery effect, and after ten years of production, the recovery factor increased by 0.46%. Full article

Brain rot refers to the cognitive decline and mental exhaustion resulting from excessive consumption of low-quality, short-form digital content, particularly affecting Generation Alpha and Generation Z. This study developed and validated the Brain Rot Scale (BRS) to assess digital content overconsumption among digital natives aged 8–24 years. A two-phase design employed separate Egyptian samples for exploratory factor analysis (EFA; n = 403) and confirmatory factor analysis (CFA; n = 897). The initial 21-item Arabic scale underwent principal axis factoring with promax rotation, guided by parallel analysis. Following iterative item deletion, a 14-item scale (BRS-14) emerged with three factors: Attention Dysregulation (6 items), Digital Compulsivity (5 items), and Cognitive Dependency (3 items), accounting for 35.114% of common variance. Confirmatory factor analysis demonstrated excellent fit (CFI = 0.988; TLI = 0.985; RMSEA = 0.031 [0.023, 0.039]; SRMR = 0.040), with standardized loadings ranging from 0.667 to 0.758 (p < 0.001). The scale showed excellent reliability (ω = 0.900, α = 0.899), with subscale reliabilities from 0.759 to 0.857. Convergent validity was established (CR > 0.70, AVE > 0.50). Factor intercorrelations (0.636–0.671) supported a hierarchical model where a general Brain Rot factor explained 62.9–69.9% of first-order variance. The BRS-14 provides a psychometrically sound instrument for assessing problematic digital consumption patterns among contemporary youth populations. Full article

The year 2025 likely marks a turning point in both the perception and the reality of mosquito-borne arboviral diseases in Europe. While chikungunya and dengue viruses have long been regarded as tropical illnesses confined to intertropical regions, West Nile virus has circulated for decades in temperate areas, including southern Europe. Nevertheless, all three mosquito-borne viruses are now increasingly established across the European continent. This evolution reflects a profound transformation of the European epidemiological landscape, where arboviral diseases are increasingly emerging as endemic and seasonal threats. This shift concerns not only the scale but also the dynamics of transmission, with the appearance of newly affected regions, an earlier onset of the transmission season, and a broader diversity of arboviruses involved. Europe is thus entering a new phase in which longer, wider, and more intense transmission of vector-borne diseases is likely to become the new norm requiring strengthened preparedness. Full article

Online adaptive radiotherapy (ART) is rapidly transforming clinical radiation oncology by enabling adaptation of treatment plans based on patient-specific anatomical and biological changes. However, most medical physics training programs lack structured education in ART. To address this critical gap, the Medical Physics Adaptive Radiotherapy (MPART) Fellowship was established at our center to train post-residency or practicing physicists in advanced adaptive technologies and workflows. The MPART Fellowship is a two-year program that provides immersive, platform-specific training in CBCT-guided (Varian Ethos), MR-guided (Elekta Unity), and PET-guided (RefleXion X1) radiotherapy. Fellows undergo modular clinical rotations, hands-on training, and dedicated research projects. The curriculum incorporates competencies in imaging, contouring, online planning, quality assurance, and team-based decision-making. Evaluation is based on the Accreditation Council for Graduate Medical Education competency domains and includes milestone tracking, mentor reviews, and structured presentations. The fellowship attracted applicants from both domestic and international institutions, reflecting strong demand for formal ART training. Out of 22 applications, two fellows have been successfully recruited into the program since 2024. Fellows actively participate in all phases of adaptive workflows and are expected to function at near-attending levels by the second year of their training. Each fellow also leads at least one translational or operational research project aimed at improving ART delivery. Fellows contribute to clinical coverage and lead developmental projects, resulting in presentations and publications at the national and international levels. The MPART Fellowship addresses a vital educational need by equipping medical physicists with the advanced competencies necessary for implementing and leading ART. This program offers a replicable framework for other institutions seeking to advance precision radiation therapy through structured post-residency training in adaptive radiotherapy. As this fellowship program is still in its early phase of establishment, the primary goal of this paper is to introduce the structure, framework, and implementation model of the program. Comprehensive outcome analyses—such as quantitative assessments, fellow feedback, and longitudinal competency evaluations—will be incorporated in future work as additional cohorts complete training. Full article

Each maritime country produces annual reports on its maritime safety policy. The annual report details the implementation of established policies, plans, and regulations concerning the supervision and protection of rights and interests at sea. By analyzing the Annual Reports for the Republic of Croatia from 2017 to 2024, maritime traffic and activities at sea were examined. The data include the number of available inspection vessels, the nautical miles traveled, fuel consumption, and similar metrics. All this information is related to the total number of inspected vessels, which is a key performance indicator for maritime traffic control. The aim of the analysis is to determine the correlation between fuel consumption, distance traveled, number of voyages, and number of inspected vessels over eight consecutive years. Data Envelopment Analysis (DEA) is used to assess the relationship between inputs and outputs to identify which years were efficient. Additionally, the multi-criteria decision-making method PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) is used to interpret and validate the DEA results, particularly the efficiency ranking. The proposed DEA–PROMETHEE hybrid model enables decision-makers to better understand DEA results, especially when efficiency scores are very similar. In terms of practical applications, the results based on the DEA input and output analysis, extended with the PROMETHEE method, show that the optimized use of available resources contributes to increased overall maritime safety. Full article