Search Results (26,012)

Hydrogen chloride (HCl) is a hazardous acidic gas released from industrial processes and waste-treatment systems, posing risks to human health, process safety, and the surrounding environment. Accordingly, there is a need for practical adsorbent materials that can reduce HCl exposure without generating secondary liquid waste. In this study, pitch-based activated carbon pellets were surface-functionalized by oxygen plasma treatment to improve fixed-bed HCl removal performance. Plasma treatment was applied for 1, 2, and 4 min, and the resulting changes in surface chemistry, pore structure, and adsorption behavior were investigated using SEM, XPS, N₂ adsorption–desorption analysis, and breakthrough experiments. Oxygen plasma treatment increased the oxygen-containing surface functionalities of the pellets while largely preserving pellet morphology. Under moderate treatment conditions (1–2 min), the BET surface area and pore volume were mostly maintained, whereas prolonged treatment (4 min) reduced the accessible pore structure. In fixed-bed adsorption tests, the sample treated for 1 min showed the longest breakthrough behavior and the highest HCl uptake among the tested samples, while the sample treated for 2 min exhibited the shortest mass transfer zone and the highest bed utilization. These results indicate that controlled oxygen plasma treatment can improve the removal of hazardous HCl gas by balancing surface functionalization and pore preservation. The findings suggest that plasma-functionalized activated carbon pellets are a promising option for toxic acidic gas mitigation in air pollution control and waste-treatment applications. Full article

The expected rise in space operations challenges the European Air Traffic Management (ATM), as traditional static airspace segregation causes operational inefficiencies. To mitigate this, a new function within the European Network Manager Operations Centre (NMOC), supported by the novel Network Real-time Mission Monitoring (N-RMM) tool, and complemented by ad hoc Debris Response Areas (DRAs), are being developed. This paper introduces the safety assessment of this approach using the Expanded Safety Reference Material (E-SRM) methodology. By developing specialised Accident Incident Models (AIMs) for mid-air collisions with space debris, we quantify safety barrier efficiencies and define a Risk Classification Scheme (RCS). The results indicate that by developing dedicated AIMs for the proposed dynamic airspace-management concept, the derived safety criteria, under the stated assumptions, are compatible with the targeted safety thresholds. The potential reduction in segregated airspace volume and duration remains an expected operational benefit to be quantified in subsequent validation work. Full article

Atherosclerosis is a chronic inflammatory arterial disease and the primary underlying cause of cardiovascular morbidity and mortality worldwide. Its development and progression are driven by a mechanistically interconnected triad of endothelial dysfunction, oxidative stress, and vascular inflammation. Current pharmacotherapy, primarily focused on low-density lipoprotein cholesterol (LDL-C) reduction through statin-based and adjunctive therapies, does not fully address the residual inflammatory and calcific components of atherosclerotic risk. Menaquinone-7 (MK-7), a long-chain isoform of vitamin K2 with superior bioavailability and extrahepatic tissue distribution, has emerged as a multi-target modulator of atherogenic processes. Its classical function is to serve as a cofactor for the gamma-carboxylation of vitamin K-dependent proteins (VKDPs), principally matrix Gla protein (MGP), the primary endogenous inhibitor of vascular calcification. Beyond this established pathway, a growing body of experimental evidence indicates that MK-7 may modulate endothelial nitric oxide (NO) production through carboxylation-dependent activation of Growth Arrest-Specific Protein 6 (Gas6) and suppress lipid peroxidation and ferroptosis via Ferroptosis Suppressor Protein 1 (FSP1)-mediated reduction of vitamin K hydroquinone (VKH₂). In addition, it may attenuate nuclear factor kappa-B (NF-κB)-driven inflammatory gene transcription in vascular cells. Previous reviews mainly focused on how vitamin K2 influences vascular calcification and cardiovascular outcomes. However, emerging mechanistic evidence linking MK-7 to endothelial dysfunction, oxidative stress, ferroptosis, and vascular inflammation has not been comprehensively integrated. This review summarizes the current knowledge of in vitro, animal, observational, and randomized controlled trial evidence for MK-7 in the context of atherosclerosis. It particularly emphasises mechanistic pathways, the strength of evidence, and translational limitations, highlighting the lack of direct human vascular evidence in several areas. Full article

Cyanobacterial blooms in lakes and reservoirs pose significant environmental and public health risks. This paper presents an effective exploration strategy to detect them from Autonomous Surface Vehicles (ASVs) equipped with probes, whose sensing trajectories are optimized by an AI-based planner that considers the 3D spatial-temporal evolution of the cyanobacteria concentration obtained by a multiphysics model. The planner, simultaneously working on the AI decision-making and robotic domains, optimizes the surface displacement of the ASV and the depth of its probe by solving a constrained multi-objective optimization problem that minimizes the mission duration and trajectory length, maximizes the possibilities of the probe to overpass areas with high concentration of cyanobacteria, and satisfies operational constraints (such as ASV velocity or acceleration limits, and obstacle avoidance). The optimization is supported by two well-known versions of the Non-Sorted Generic Algorithm (NSGA-II and NSGA-III) and by encoding the trajectories with spline curves whose number of control points can be fixed, progressively increased, or freely manipulated by the algorithm. The performance of different configurations of the planner is tested against six scenarios obtained from different simulations of the multiphysics model (which couples water dynamics and temperature, light transmission, daily vertical migration of the cyanobacteria and their growth). The statistical analysis of the planner results determines that NSGA-III working with variable-length chromosomes and NSGA-II with the progressive increment of spline points as the best configurations for maximizing cyanobacteria detection, and minimizing mission duration and trajectory length. Full article

In the context of revitalizing rural development, farmer entrepreneurship has emerged as a significant driver of rural economic growth. However, existing research has not sufficiently examined the specific mechanisms or heterogeneous effects through which digital skills influence farm household entrepreneurial behavior. This gap is the focus of the present study. Utilizing micro-level survey data collected from 936 farm households across Shandong, Shaanxi, and Henan provinces in 2021, we construct a digital skills index using factor analysis. We then employ a Probit model and an Interaction term model to examine the impact of digital skills on entrepreneurial behavior among Chinese rural households and its underlying mechanisms. Additionally, we explore heterogeneity across different household types. The results show that digital skills are positively associated with entrepreneurial decision-making. Further analysis provides suggestive evidence that this relationship may operate through three channels: shaping risk preferences, expanding relational networks, and improving access to credit. Heterogeneity tests reveal that the promoting effect of digital skills is stronger among disadvantaged households, households with a head younger than 45, and those engaged in opportunity-driven or online entrepreneurship. Theoretically, this study contributes by empirically validating a multi-pathway mechanism framework and identifying relevant boundary conditions. Practically, it offers targeted insights for policymakers to design skill-based interventions and foster inclusive entrepreneurial ecosystems in rural areas. Full article

Strongyloides stercoralis (S. stercoralis) is an important soil-transmitted helminth that infests over 600 million people worldwide. However, data on its seroprevalence in remote regions, such as Thailand’s island areas, remain limited. This study examined the seroprevalence and associated risk factors of anti-Strongyloides spp. IgG seropositivity among primary school children in Koh Yao, an island in southern Thailand. A total of 351 primary school children (156 males and 195 females) were included. The seroprevalence of anti-Strongyloides spp. IgG was determined using the Strongyloides-specific IgG antibodies ELISA, and risk factor data were collected through a questionnaire. Hematological parameters were also analyzed. Univariate and multivariate logistic regression analyses were used to assess associations between risk factors and anti-Strongyloides spp. IgG seropositivity. The seroprevalence of anti-Strongyloides spp. IgG was 3.7% (13/351 participants). Analysis of the risk factors revealed that participants who drank filtered water exhibited lower odds of anti-Strongyloides spp. IgG seropositivity compared to those who drank tap or rainwater (AOR = 0.21, 95% CI 0.05–0.95, p = 0.043). However, due to the small number of seropositive cases, this association is hypothesis-generating and likely serves as a proxy for better household hygiene rather than a direct protective factor. This study is the first report on anti-Strongyloides spp. IgG seropositivity among primary school children in Koh Yao, southern Thailand, demonstrating a low seropositivity rate in this population. These findings provide location-specific information on modifiable risk behaviors, aiding in developing more effective control and prevention strategies for anti-Strongyloides spp. IgG seropositivity in Thailand’s island area. Full article

The Oncotype DX^® 21-gene recurrence score (RS) guides adjuvant chemotherapy decisions in estrogen receptor-positive, human epidermal growth factor receptor 2-negative (ER+/HER2−) breast cancer, yet requires invasive tissue sampling and involves substantial costs. This study evaluated intratumoral tumor ecological diversity (iTED), a habitat imaging approach, as a non-invasive complement for predicting Oncotype DX^® high-risk classification (RS > 25). This retrospective multi-center study included 312 patients with ER+/HER2− invasive breast cancer who underwent Oncotype DX^® testing (development: n = 168; external validation: n = 144). The iTED framework employed superpixel-based habitat determination using Gaussian mixture models on pretreatment dynamic contrast-enhanced MRI. Four predictive models were compared: clinical, conventional whole-tumor radiomics (C-radiomics), iTED, and combined (Clinical + iTED). The iTED model achieved higher discriminative performance compared with C-radiomics in both development (area under the curve [AUC]: 0.868 ± 0.068 vs. 0.730 ± 0.112) and external validation (AUC: 0.811 vs. 0.587) sets. The combined model further improved performance (development AUC: 0.908 ± 0.043; external AUC: 0.889). Habitat imaging-based iTED features achieved numerically higher performance than conventional radiomics in predicting Oncotype DX^® high-risk classification. These findings suggest the potential of iTED as a non-invasive imaging biomarker to support molecular testing in clinical decision-making. Full article

Background: Artificial intelligence (AI) is becoming increasingly integrated into orthopaedic surgery for tasks such as implant positioning, dislocation risk prediction, and surgical decision-making. However, the current evidence varies widely across anatomical regions and applications. Methods: A structured narrative review was conducted using PubMed and Web of Science Core Collection to identify studies applying machine learning or deep learning in orthopaedic procedures, focusing on parameters such as the anatomical region addressed, data types used, primary AI tasks, evaluation designs, and validation strategies. Reviews and meta-analyses were excluded. Study selection was summarized using a PRISMA-style flow diagram, and included studies were narratively synthesized according to anatomical region, AI task, imaging modality, validation strategy, and clinical relevance. Results: We identified three main application areas: (1) AI in imaging-driven planning and implant positioning, often linked with navigation or robotic systems; (2) postoperative evaluation related to implants; and (3) prediction of clinically relevant outcomes such as dislocation risk. The strongest evidence is found in hip arthroplasty, where AI improves measurement accuracy and workflow efficiency, whereas applications in knee, shoulder, and spine surgery are less developed and often supported by smaller studies. Although existing risk prediction models demonstrate good performance, their generalizability is hindered by limited external validation and inconsistent reporting. Conclusions: Overall, while AI shows significant promise in enhancing various aspects of orthopaedic surgery, stronger links between technical advancements and patient outcomes are needed. Future research should prioritize extensive validations, workflow-aware evaluations, failure analysis, and adherence to AI-specific reporting guidelines to facilitate safe and effective clinical implementation. Full article

Cancer-associated thrombosis (CAT) is a major cause of morbidity and mortality in patients with cancer. The management of special situations—including recurrent venous thromboembolism (VTE), thrombosis at unusual sites, and central venous catheter-associated thrombosis (CVC-AT)—remains particularly challenging because of the limited availability of high-quality evidence. This narrative review synthesizes recommendations from major international and Spanish clinical practice guidelines and expert consensus documents, including those from SEOM, ESMO, ASCO, NCCN, ITAC and SEMI, to provide a structured framework for the management of these complex scenarios. Our analysis identified substantial heterogeneity across guidelines, particularly regarding anticoagulant selection, dosing strategies, and treatment duration. Although some convergence exists in the management of CVC-AT, important discrepancies and evidence gaps persist in areas such as splanchnic vein thrombosis, hepatic impairment, central nervous system involvement, and recurrent VTE despite treatment. In many cases, recommendations are based primarily on expert opinion rather than robust trial data, and several clinical scenarios are addressed by only a limited number of guidelines. These findings underscore the need for more standardized management strategies and prospective clinical studies to better inform decision-making in daily practice. Overall, this review highlights the growing importance of individualized anticoagulant management aimed at balancing thrombotic and bleeding risks in high-risk oncology patients, thereby helping to bridge the gap between expert consensus and evidence-based precision anticoagulation. Full article

Background/Objectives: Lung cancer remains a leading cause of cancer-related mortality and is characterized by complex tumor–host interactions, including systemic inflammation, metabolic dysregulation, and immune imbalance. This study aimed to evaluate whether a diagnosis of anemia reflects underlying inflammatory burden and to explore phenotype-based interactions between anemia, inflammation, and muscle depletion in lung cancer patients. Methods: A retrospective cohort study was conducted, including 70 patients diagnosed with lung cancer between 2019 and 2023. Anemia was defined using standard hemoglobin thresholds (<12 g/dL in women, <13 g/dL in men). Systemic inflammation was assessed using complete blood count-derived indices (NLR, PLR, SII, SIRI, and AISI), both individually and combined into a cumulative inflammatory score. Sarcopenia was evaluated through CT-based quantification of skeletal muscle area at the L3 level. Patients were stratified into four phenotypes based on anemia status, inflammatory burden, and sarcopenia. Statistical analyses like Mann–Whitney U, Kruskal–Wallis with Dunn post hoc testing, and univariate logistic regression were used. Results: Anemia was present in 44.3% of patients and was associated with a significantly higher inflammatory score compared to non-anemic patients (median 5 [IQR 4–5] vs. 4 [3–5], p = 0.024). Among inflammatory markers, PLR was significantly associated with anemia (OR = 4.94, 95% CI: 1.57–15.52, p = 0.004). The cumulative inflammatory score showed a non-significant association with anemia (OR = 1.28, 95% CI: 0.93–1.75, p = 0.124). Phenotype-based analysis revealed significant differences in skeletal muscle area (p = 0.004), with the sarcopenic-inflammatory phenotype exhibiting significantly lower muscle mass compared to other groups. No associations were observed between phenotypes and tumor stage or histological subtype. Conclusions: Anemia in lung cancer patients is closely associated with systemic inflammation and may reflect underlying biological vulnerability rather than tumor-specific characteristics. A phenotype-based approach integrating anemia, inflammatory markers, and sarcopenia provides a more comprehensive understanding of disease heterogeneity and may improve risk stratification. Further studies are needed to validate these findings and assess their prognostic implications. Full article

Accurate short-term prediction of urban waterlogging depth is essential for real-time flood risk management in rapidly urbanizing areas under climate variability. Departures from quasi-stationary operating conditions, caused by changes in drainage efficiency, inflow patterns, or measurement quality, weaken historical rainfall–water depth relationships, making purely data-driven models prone to error accumulation. In this study, a GeoAI-based, physics-enhanced machine learning framework is proposed, which translates the water balance principle into Physical Violation Scores (PVSs) and incorporates them as additional input features. PVSs remain zero under expected rainfall–water depth behavior and become positive only under departure scenarios, providing sparse and lightweight diagnostic signals without modifying model structures or loss functions. The framework is implemented on five algorithms (Support Vector Machine, Multilayer Perceptron, Random Forest, Extremely Randomized Trees, and XGBoost) to construct physics-enhanced models (PEMs). These are evaluated against original feature models (OFMs) across 1 h and 2 h forecasting horizons. Results show that most PEMs improve prediction performance compared with their corresponding OFMs, with more pronounced gains at the 2 h horizon. Bootstrap analysis and RMSE-based error amplification factor further indicate comparable or lower R² variability and reduced recursive error amplification for most PEMs. Interpretability analyses show that rainfall forcing and water-depth persistence remain dominant predictors, whereas PVSs act as auxiliary diagnostic signals. Overall, the proposed framework provides a lightweight, reliable, interpretable, and scalable GeoAI approach for incorporating water balance knowledge into short-term urban waterlogging prediction, supporting climate resilience and smart urban water management. Full article

Vanadium tailings-based ceramsite (VT-Ceramsite), a type of porous ceramsite synthesized from vanadium tailings, was employed for the adsorption of fluoride ions from high-fluoride wastewater. This approach not only mitigates environmental pollution caused by industrial solid waste but also effectively removes fluoride contaminants from wastewater. The effects of vanadium tailings content, sintering temperature, and sintering time on the adsorption performance of the VT-Ceramsite were systematically investigated. Comprehensive characterizations via XRD, SEM, BET, and adsorption modeling reveal that fluoride sequestration by VT-Ceramsite is governed by the synergy between physical diffusion and chemical interactions. While the porous architecture provides essential transport pathways, the chemically active sites facilitate stable bonding. Future research will prioritize surface functionalization and tailoring strategies to augment the density of these active sites, thereby maximizing the adsorption potential for treating complex industrial effluents. The optimal preparation conditions were determined to be a ratio of 6.5:2.5:1 for vanadium tailings, fly ash, and kaolin, with a preheating temperature of 300 °C for 20 min and a sintering temperature of 900 °C for 20 min. In these conditions, the adsorption capacity for fluorine ions can reach 43.59 mg/g. VT-Ceramsite exhibited a specific surface area of 3.61 m²/g, hydrochloric acid solubility of 1.2%, and a void fraction of 48.68%, all parameters met national industrial standards. In addition, the leaching concentrations of heavy metals were found to be well below the limits specified in CJ/T 299-2008, indicating that the material poses no risk of secondary pollution. The study provides an economical, safe, and environmentally friendly route for the utilization of solid waste, and it offers a promising adsorbent for treating high-fluoride wastewater. Full article

Background/Objectives: Remnant cholesterol (remnant-C), derived from triglyceride-rich lipoproteins, is an important risk factor for cardiometabolic diseases. Given the metabolic link between dyslipidemia and skeletal muscle dysfunction, we aimed to evaluate the association between remnant-C and two key components of sarcopenia—low muscle mass and myosteatosis (ectopic fat deposition in skeletal muscle). Methods: This cross-sectional study included 11,570 patients who underwent abdominal computed tomography (CT) for health check-ups. Remnant-C was calculated as total cholesterol minus low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. We conducted multivariable logistic and linear analyses to assess the association between remnant-C and low muscle mass, defined as appendicular skeletal muscle mass divided by body mass index. Additional analysis examined the relationship between remnant-C and myosteatosis, defined using the NAMA (normal attenuation muscle area) divided by TAMA (total abdominal muscle area) index, a novel index derived from muscle quality mapping of abdominal CT scans. Results: Low muscle mass was observed in 244 males (3.9%) and 74 females (1.4%). Myosteatosis affected 950 males (15.0%) and 800 females (15.3%). There was an increasing prevalence of both low muscle mass and myosteatosis across remnant-C quartiles. The multivariate-adjusted odds ratios (ORs) for low muscle mass in the highest remnant-C quartile compared with the lowest quartile were 2.17 (95% confidence interval [CI] 1.45–3.26) for males and 1.37 (95% CI 0.68–2.76) for females. The corresponding ORs for myosteatosis were 1.37 (95% CI 1.11–1.69) for males and 1.24 (95% CI 0.96–1.59) for females. Conclusions: Elevated remnant-C level is associated with low muscle mass and myosteatosis, especially in male patients. Individuals with higher remnant-C levels may warrant comprehensive evaluation for skeletal muscle health. Full article

Colpodella spp. are phylogenetically related to apicomplexans such as Plasmodium spp., Babesia spp., and Cryptosporidium spp. Colpodella spp. are free-living protists that prey on bodonids, ciliates, and algae using myzocytosis. Colpodella spp. cause human and animal infections known as colpodellosis, with transmission via ticks across different geographic areas on different continents. Colpodella spp. DNA has been detected in ticks, the biting fly Stomoxys indicus and vertebrate samples using polymerase chain reaction (PCR). Ticks transmit zoonotic pathogens, and the identification of Colpodella spp. in animals poses a major public health risk due to human and animal encounters exposing humans to tick bites. However, it is unclear if ticks are confirmed vectors for Colpodella spp., since tick vector competence and capacity for Colpodella spp. transmission has not been experimentally demonstrated. Human cases of colpodellosis have involved three cases of blood infection, a fourth case of tickborne infection, and a fifth case of urinary tract infection. In this narrative review, the occurrence of Colpodella spp. in ticks that transmit zoonotic pathogens will be reviewed. Differences in the disease presentations and symptoms of colpodellosis in tickborne infections will be discussed. The pattern of Colpodella spp. coinfections with piroplasms and Cryptosporidium spp. will be evaluated. The pressing need for morphological identification of Colpodella spp. to assist proper characterization of the different species identified in arthropods and vertebrate hosts will be highlighted. Full article

Achieving efficient and high-quality surface processing of single-crystal diamond (SCD) remains challenging due to its extreme hardness and chemical inertness. Traditional Fenton-based slurries using H₂O₂ suffer from poor stability, safety risks, and strict acidic pH requirements. In this study, peroxymonosulfate (PMS) is introduced as an alternative oxidant to develop a novel chemical mechanical polishing (CMP) slurry for SCD. Compared with H₂O₂, PMS exhibits higher stability and generates sulfate radicals (SO₄⁻·) with stronger oxidation capability when activated by Fe²⁺. The proposed slurry achieves efficient material removal over a wider pH range (2–6). Under optimal conditions (pH = 3), a maximum material removal rate (MRR) of 676 nm/h is obtained, along with an ultra-smooth surface (Sa = 0.177 nm in the measuring area of 868 × 868 μm²). Notably, the slurry maintains high MRR (>400 nm/h) even under weakly acidic conditions (pH 5–6). XPS and radical quenching experiments confirm that continuous generation of reactive radicals promotes surface oxidation and stable material removal. This work provides a stable and efficient CMP slurry for SCD with enhanced pH adaptability. Full article