Search Results (2,111)

Climate-driven hydrological extremes and anthropogenic interventions are increasingly altering streamflow regimes worldwide. While prior studies have explored climate or regulation effects separately, few have integrated multiple teleconnection indices and reservoir chronologies within a cross-basin comparative framework. This study addresses this gap by assessing long-term streamflow nonstationarity and its drivers at two key stations—Khabarovsk on the Amur River and Datong on the Yangtze River—representing distinct hydroclimatic settings. We utilized monthly discharge records, meteorological data, and large-scale climate indices to apply trend analysis, wavelet transform, percentile-based extreme diagnostics, lagged random forest regression, and slope-based attribution. The results show that Khabarovsk experienced an increase in winter baseflow from 513 to 1335 m³/s and a notable reduction in seasonal discharge contrast, primarily driven by temperature and cold-region reservoir regulation. In contrast, Datong displayed increased discharge extremes, with flood discharges increasing by +71.9 m³/s/year, equivalent to approximately 0.12% of the mean flood discharge annually, and low discharges by +24.2 m³/s/year in recent decades, shaped by both climate variability and large-scale hydropower infrastructure. Random forest models identified temperature and precipitation as short-term drivers, with ENSO-related indices showing lagged impacts on streamflow variability. Attribution analysis indicated that Khabarovsk is primarily shaped by cold-region reservoir operations in conjunction with temperature-driven snowmelt dynamics, while Datong reflects a combined influence of both climate variability and regulation. These insights may provide guidance for climate-responsive reservoir scheduling and basin-specific regulation strategies, supporting the development of integrated frameworks for adaptive water management under climate change. Full article

Background/Objectives: This study examines how seasonality, pollution, and sample type (water and sediment) influence the presence and distribution of antibiotic resistance genes (ARGs), with a focus on antibiotic resistance genes (ARGs) located on plasmids (the complete set of plasmid-derived sequences, including ARGs) in a tropical urban river. Methods: Samples were collected from three sites along a pollution gradient in the Virilla River, Costa Rica, during three seasonal campaigns (wet 2021, dry 2022, and wet 2022). ARGs in water and sediment were quantified by qPCR, and metagenomic sequencing was applied to analyze chromosomal and plasmid-associated resistance profiles in sediments. Tobit and linear regression models, along with multivariate ordination, were used to assess spatial and seasonal trends. Results: During the wet season of 2021, the abundance of antibiotic resistance genes (ARGs) such as sul-1, intI-1, and tetA in water samples decreased significantly, likely due to dilution, while intI-1 and tetQ increased in sediments, suggesting particle-bound accumulation. In the wet season 2022, intI-1 remained low in water, qnrS increased, and sediments showed significant increases in tetQ, tetA, and qnrS, along with decreases in sul-1 and sul-2. Metagenomic analysis revealed spatial differences in plasmid-associated ARGs, with the highest abundance at the most polluted site (Site 3). Bacterial taxa also showed spatial differences, with greater plasmidome diversity and a higher representation of potential pathogens in the most contaminated site. Conclusions: Seasonality and pollution gradients jointly shape ARG dynamics in this tropical river. Plasmid-mediated resistance responds rapidly to environmental change and is enriched at polluted sites, while sediments serve as long-term reservoirs. These findings support the use of plasmid-based monitoring for antimicrobial resistance surveillance in aquatic systems. Full article

This study analyzes spatiotemporal aridity dynamics in Central Kazakhstan (1960–2022) using a monthly Aridity Index (AI = P/PET), where P is precipitation and PET is potential evapotranspiration, Mann–Kendall trend analysis, and climate zone classification. Results reveal a northeast–southwest aridity gradient, with Aridity Index ranging from 0.11 to 0.14 in southern deserts to 0.43 in the Kazakh Uplands. Between 1960–1990 and 1991–2022, southern regions experienced intensified aridity, with Aridity Index declining from 0.12–0.15 to 0.10–0.14, while northern mountainous areas became more humid, where Aridity Index increased from 0.40–0.44 to 0.41–0.46. Seasonal analysis reveals divergent patterns, with winter showing improved moisture conditions (52.4% reduction in arid lands), contrasting sharply with aridification in spring and summer. Summer emerges as the most extreme season, with hyper-arid zones (8%) along with expanding arid territories (69%), while autumn shows intermediate conditions with notable dry sub-humid areas (5%) in northwestern regions. Statistical analysis confirms these observations, with northern areas showing positive Aridity Index trends (+0.007/10 years) against southwestern declines (−0.003/10 years). Key drivers include rising temperatures (with recent degradation) and variable precipitation (long-term drying followed by winter and spring), and PET fluctuations linked to temperature. Since 1991, arid zones have expanded from 40% to 47% of the region, with semi-arid lands transitioning to arid, with a northward shift of the boundary. These changes are strongly seasonal, highlighting the vulnerability of Central Kazakhstan to climate-driven aridification. Full article

Background/Objectives: Pulmonary typical carcinoid (TC) is a rare type of primary neuroendocrine neoplasm of the lung with indolent behavior and a good prognosis. The main treatment strategy is surgery, the extent of which is controversial given the nature of the disease. The aim of this study is to assess whether the extent of resection influences survival and recurrence in patients undergoing lung resection and lymphadenectomy for TC and to investigate negative prognostic factors for OS. Methods: A single-centre retrospective study of 15 years’ experience was conducted. Data from all patients who underwent lung resection and lymphadenectomy for TC were collected. Patients were divided into two groups: anatomical and non-anatomical resections. Perioperative and long-term oncological results were analyzed. Results: In total, 115 patients were surgically treated for TC, of whom 83 (72%) underwent anatomical resection and 32 (28%) non-anatomical resection. Univariate analyses showed that age, left lower lobe, and many comorbidities had a detrimental effect on OS, whereas on multivariate analysis, only left lower lobe location and a high Charlson–Deyo comorbidity index (CCI) were confirmed as negative prognostic factors for OS. At a median follow-up of 93 months (IQR 57-129), the OS survival curves show a slightly lower trend for non-anatomical resections (p 0.152), while no differences were found for DFS. Conclusions: The results of this study confirm that in selected patients at risk for major resections, non-anatomical resection can be used to treat TC when R0 is achievable. These data, together with evidence from the literature, highlight the importance of patient-centred care in this rare disease. Full article

Willow stands (Salix spp.) are an essential part of riparian ecosystems, as they sustain biodiversity and provide bioenergy solutions. The present review synthesizes the global scientific literature about the management of willow stands. In order to achieve this goal, we used a dual approach combining bibliometric analysis with traditional literature review. As such, we consulted 416 publications published between 1978 and 2024. This allowed us to identify key species, ecosystem services, conservation strategies, and management issues. The results we have obtained show a diversity of approaches, with an increase in short-rotation coppice (SRC) systems and the multiple roles covered by willow stands (carbon sequestration, biomass production, riparian restoration, and habitat provision). The key trends we have identified show a shift toward topics such as climate resilience, ecological restoration, and precision forestry. This trend has become especially pronounced over the past decade (2014–2024), as reflected in the increasing use of these keywords in the literature. However, as willow systems expand in scale and function—from biomass production to ecological restoration—they also raise complex challenges, including invasive tendencies in non-native regions and uncertainties surrounding biodiversity impacts and soil carbon dynamics over the long term. The present review is a guide for forest policies and, more specifically, for future research, linking the need to integrate and use adaptive strategies in order to maintain the willow stands. Full article

Post-traumatic stress disorder (PTSD) is a chronic mental health condition resulting from exposure to traumatic events. It is associated with long-term neurobiological changes and disturbances in emotional regulation. Understanding the sociodemographic profiles, biomarkers, and emotional control in patients with PTSD helps to better comprehend the impact of the disorder on the body and its clinical course. An analysis of biomarkers such as Interleukin-18 (IL-18), Inositol-Requiring Enzyme 1 (IRE1), Phosphorylated Extracellular Signal-Regulated Kinase (pERK), and Activating Transcription Factor–6 (ATF-6) in PTSD patients with varying durations of illness (≤5 years and >5 years) and a control group without PTSD revealed significant differences. Patients with recently diagnosed PTSD (≤5 years) showed markedly elevated levels of inflammatory and cellular stress markers, indicating an intense neuroinflammatory response during the acute phase of the disorder. In the chronic PTSD group (>5 years), the levels of these biomarkers were lower than in the recently diagnosed group, but still significantly higher than in the control group. An opposite trend was observed regarding the suppression of negative emotions, as measured by the Courtauld Emotional Control Scale (CECS): individuals with chronic PTSD exhibited a significantly greater suppression of anger, depression, and anxiety than those with recent PTSD or healthy controls. Correlations between biomarkers were strongest in individuals with chronic PTSD, suggesting a persistent neuroinflammatory dysfunction. However, the relationships between biomarkers and emotional suppression varied depending on the stage of PTSD. These findings highlight the critical role of PTSD duration in shaping the neurobiological and emotional mechanisms of the disorder, which may have important implications for therapeutic strategies and patient monitoring. 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

Introduction: Haglund’s deformity, characterized by bony enlargement at the back of the heel, often coincides with Achilles tendon pathology due to impingement on the retrocalcaneal bursa and tendon insertion. Surgical management of Haglund’s deformity with a preexisting Achilles tendon rupture is complex, and understanding the outcomes of this subset of patients is essential for optimizing treatment strategies. Methods: This retrospective study reviewed patients undergoing open surgical management for Haglund’s syndrome between January 2015 and December 2023. Patients with chronic degenerative changes secondary to Haglund’s deformity and a preoperative Achilles tendon rupture were compared to those without. Data on demographics, surgical techniques, weightbearing protocols, and complications were collected. Univariate analysis was performed using χ² or Fisher’s exact test for categorical variables, and the T-test or Wilcoxon rank-sum test for continuous and ordinal variables, with normality assessed via the Shapiro–Wilk test. Results: Four hundred and three patients were included, with 13 having a preoperative Achilles tendon rupture. There was a higher incidence of preoperative ruptures among males. Surgical repair techniques and postoperative weightbearing protocols varied, though were not randomized. Complications included persistent pain, wound breakdown, infection, plantar flexion weakness, and revision surgery. While patients with Haglund’s deformity and a preoperative Achilles tendon rupture demonstrated a trend toward higher complication rates, including postoperative rupture and wound breakdown, these differences were not statistically significant in our analysis. Conclusions: A cautious approach is warranted in managing these patients, with careful consideration of surgical planning and postoperative rehabilitation. While our findings provide valuable insights into managing patients with Haglund’s deformity and preoperative Achilles tendon rupture, the retrospective design, limited sample size of the rupture group, and short duration of follow-up restrict generalizability and the strength of the conclusions by limiting the power of the analysis and underestimating the incidence of long-term complications. Therefore, the results of this study should be interpreted with caution. Further studies with larger patient cohorts, validated functional outcome measures, and comparable follow-up durations between groups are needed to confirm these results and optimize treatment approaches. Full article

Promoting sustainable development requires a clear understanding of how short-term fluctuations in anthropogenic emissions affect urban environmental quality. This is especially relevant for cities experiencing rapid industrial changes or emergency policy interventions. Among key environmental concerns, variations in ambient pollutants like ozone (O₃) are closely tied to both public health and long-term sustainability goals. However, traditional chemical transport models often face challenges in accurately estimating emission changes and providing timely assessments. In contrast, statistical approaches such as the difference-in-differences (DID) model utilize observational data to improve evaluation accuracy and efficiency. This study leverages the synthetic difference-in-differences (SDID) approach, which integrates the strengths of both DID and the synthetic control method (SCM), to provide a more reliable and accurate analysis of the impacts of interventions on city-level air quality. Using Shanghai’s 2022 lockdown as a case study, we compare the deweathered ozone (O₃) concentration in Shanghai to a counterfactual constructed from a weighted average of cities in the Yangtze River Delta (YRD) that did not undergo lockdown. The quasi-natural experiment reveals an average increase of 4.4 μg/m³ (95% CI: 0.24–8.56) in Shanghai’s maximum daily 8 h O₃ concentration attributable to the lockdown. The SDID method reduces reliance on the parallel trends assumption and improves the estimate stability through unit- and time-specific weights. Multiple robustness checks confirm the reliability of these findings, underscoring the efficacy of the SDID approach in quantitatively evaluating the causal impact of emission perturbations on air quality. This study provides credible causal evidence of the environmental impact of short-term policy interventions, highlighting the utility of SDID in informing adaptive air quality management. The findings support the development of timely, evidence-based strategies for sustainable urban governance and environmental policy design. Full article

This paper presents a critical and comprehensive review of the application of mining waste, specifically waste rock and tailings, in asphalt pavements, with the aim of synthesizing performance outcomes and identifying key research gaps. A systematic literature search yielded a final dataset of 41 peer-reviewed articles for detailed analysis. Bibliometric analysis indicates a notable upward trend in annual publications, reflecting growing academic and practical interest in this field. Performance-based evaluations demonstrate that mining wastes, particularly iron and copper tailings, have the potential to enhance the high-temperature performance (i.e., rutting resistance) of asphalt binders and mixtures when utilized as fillers or aggregates. However, their effects on fatigue life, low-temperature cracking, and moisture susceptibility are inconsistent, largely influenced by the physicochemical properties and dosage of the specific waste material. Despite promising results, critical knowledge gaps remain, particularly in relation to long-term durability, comprehensive environmental and economic Life-Cycle Assessments (LCA), and the inherent variability of waste materials. This review underscores the substantial potential of mining wastes as sustainable alternatives to conventional pavement materials, while emphasizing the need for further multidisciplinary research to support their broader implementation. Full article

Background: Immune checkpoint inhibitors (ICIs) have limited efficacy in proficient mismatch repair (pMMR) and microsatellite stability (MSS) metastatic colorectal cancer (mCRC). Inhibition of vascular endothelial growth factor (VEGF) or cytotoxic chemotherapy can boost immunogenicity and has the potential to upregulate ICI efficacy. Methods: A comprehensive electronic literature search was conducted up to April 2025 to identify randomized controlled trials comparing cytotoxic chemotherapy plus bevacizumab with or without ICI. The primary outcome was progression-free survival (PFS), and secondary outcomes were overall survival (OS), objective response rate (ORR), and severe adverse events (AEs: grade 3 or more). A meta-analysis was performed using random-effects models to calculate hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs). Results: Four studies involving 986 patients (With-ICI group, n = 651; Without-ICI group, n = 335) were included. The meta-analysis demonstrated a significant improvement in PFS in the With-ICI group compared with the Without-ICI group, with an HR of 0.82 (95% CI: 0.70–0.96, p = 0.01) without statistical heterogeneity. No significant improvements were observed between the With- and Without-ICI groups in OS and ORR meta-analyses, but the With-ICI group had a favorable trend in OS. A significant increase in serious AEs was not observed in the With-ICI group. Conclusions: This meta-analysis suggests a potential benefit of adding ICIs to chemotherapy plus bevacizumab in pMMR mCRC; however, the evidence remains preliminary and hypothesis-generating, warranting further investigation in biomarker-driven trials and clarification of long-term outcomes. Full article

This study presents a comprehensive analysis of CO₂ trapping mechanisms in subsurface reservoirs by integrating numerical reservoir simulations, geochemical modeling, and machine learning techniques to enhance the design and evaluation of carbon capture and storage (CCS) strategies. A two-dimensional reservoir model was developed to simulate CO₂ injection dynamics under realistic geomechanical and geochemical conditions, incorporating four primary trapping mechanisms: residual, solubility, mineralization, and structural trapping. To improve computational efficiency without compromising accuracy, advanced machine learning models, including random forest, gradient boosting, and decision trees, were deployed as smart proxy models for rapid prediction of trapping behavior across multiple scenarios. Simulation outcomes highlight the critical role of hysteresis, aquifer dynamics, and producer well placement in enhancing CO₂ trapping efficiency and maintaining long-term storage stability. To support the credibility of the model, a qualitative validation framework was implemented by comparing simulation results with benchmarked field studies and peer-reviewed numerical models. These comparisons confirm that the modeled mechanisms and trends align with established CCS behavior in real-world systems. Overall, the study demonstrates the value of combining traditional reservoir engineering with data-driven approaches to optimize CCS performance, offering scalable, reliable, and secure solutions for long-term carbon sequestration. Full article

To prolong the service life of asphalt pavement and reduce its maintenance cost, a fiber Bragg grating (FBG) sensor encapsulated in carboxylated carbon nanotube (CNT-COOH)-modified gel material suitable for strain monitoring of asphalt pavement was developed. Through tensile and bending tests, the effects of carboxylated carbon nanotubes on the mechanical properties of gel materials under different dosages were evaluated and the optimal dosage of carbon nanotubes was determined. Infrared spectrometer and scanning electron microscopy were used to compare and analyze the infrared spectra and microstructure of carbon nanotubes before and after carboxyl functionalization and modified gel materials. The results show that the incorporation of CNTs-COOH increased the tensile strength, elongation at break, and tensile modulus of the gel material by 36.2%, 47%, and 17.2%, respectively, and increased the flexural strength, flexural modulus, and flexural strain by 89.7%, 7.5%, and 63.8%, respectively. Through infrared spectrum analysis, it was determined that carboxyl (COOH) and hydroxyl (OH) were successfully introduced on the surface of carbon nanotubes. By analyzing the microstructure, it can be seen that the carboxyl functionalization of CNTs improved the agglomeration of carbon nanotubes. The tensile section of the modified gel material is rougher than that of the pure epoxy resin, showing obvious plastic deformation, and the toughness is improved. According to the data from the calibration experiment, the strain and temperature sensitivity coefficients of the packaged sensor are 1.9864 pm/μm and 0.0383 nm/°C, respectively, which are 1.63 times and 3.61 times higher than those of the bare fiber grating. The results of an applicability study show that the internal structure strain of asphalt rutting specimen changed linearly with the external static load, and the fitting sensitivity is 0.0286 με/N. Combined with ANSYS finite element analysis, it is verified that the simulation analysis results are close to the measured data, which verifies the effectiveness and monitoring accuracy of the sensor. The dynamic load test results reflect the internal strain change trend of asphalt mixture under external rutting load, confirming that the encapsulated FBG sensor is suitable for the long-term monitoring of asphalt pavement strain. Full article

Total knee arthroplasty is an extensive orthopedic surgery for patients with severe cases of osteoarthritis. This surgery restores the range of motion in the knee joint and allows for pain-free movement. Advancements in medical techniques used in the surgical zone and implant technology, as well as the management of operations and administration for around two decades prior, have hugely improved surgical outcomes for patients. In this study, advancements in TKA were examined through exploring aspects such as robotic surgery, new implants and materials, minimally invasive surgery, and post-surgery rehabilitation. This paper entails a review of the peer-reviewed literature published between 2005 and 2025 in the PubMed and Google Scholar databases. For predictors, we incorporated clinical relevance together with methodological soundness and relation to review questions to select relevant research articles. We used the PRISMA flowchart to illustrate the article selection system in its entirety. Since robotic surgical and navigation systems have been implemented, surgical accuracy has improved, there is an increased possibility of ensuring alignment, and the use of cementless and 3D-printed implants has increased, offering durable long-term fixation features. The trend in the current literature is that minimally invasive knee surgery (MIS) techniques reduce permanent pain after surgery and length of hospital stays for patients, though the long-term impact still needs to be established. There is various evidence outlining that the enhanced recovery after surgery (ERAS) protocols show positive results in terms of functional recovery and patient satisfaction. The integration of these new advancements enhances TKA surgeries and translates them into ‘need of patient’ procedures, ensuring improved results and increases in patient satisfaction. The aim of this study was to perform a comprehensive analysis of the existing literature regarding TKA advancement studies to identify current gaps and problems. Full article

Traffic conditions are a key factor in our society, contributing to quality of life and the economy, as well as access to professional, educational, and health resources. This emphasizes the need for a reliable road network to facilitate traffic fluidity across the nation and improve mobility. Reaching these characteristics demands good traffic volume prediction methods, not only in the short term but also in the long term, which helps design transportation strategies and road planning. However, most of the research has focused on short-term prediction, applied mostly to short-trip distances, while effective long-term forecasting, which has become a challenging issue in recent years, is lacking. The team proposes a traffic prediction method that leverages K-means clustering, long short-term memory (LSTM) neural network, and Fourier transform (FT) for long-term traffic prediction. The proposed method was evaluated on a real-world dataset from the U.S. Travel Monitoring Analysis System (TMAS) database, which enhances practical relevance and potential impact on transportation planning and management. The forecasting performance is evaluated with real-world traffic flow data in the state of California, in the western USA. Results show good forecasting accuracy on traffic trends and counts over a one-year period, capturing periodicity and variation. Full article