Search Results (10,780)

Forest fires significantly impact the global climate through carbon emissions, yet the multi-scale coupling mechanisms among meteorological factors, fire behavior, and emissions remain uncertain. Focusing on tropical Asia, this study integrated satellite-based fire behavior products, meteorological datasets, and emission factors, and employed machine learning together with structural equation modeling (SEM) to explore the mediating role of fire behavior in the meteorological regulation of carbon emissions. The results revealed significant differences among vegetation types in both carbon emission intensity and sensitivity to meteorological drivers. For example, average gas emissions (GEs) and particle emissions (PEs) in mixed forests (MF, 323.68 g/m²/year for GE and 0.73 g/m²/year for PE) were approximately 172% and 151% higher, respectively, than those in evergreen broadleaf forests (EBF, 118.92 g/m²/year for GE and 0.29 g/m²/year for PE), which exhibited the lowest emission intensity. Mixed forests and deciduous broadleaf forests exhibited stronger meteorological regulation effects, whereas evergreen broadleaf forests were comparatively stable. Temperature and vapor pressure deficit emerged as the core drivers of fire behavior and carbon emissions, exerting indirect control through fire behavior. Overall, the findings highlight fire behavior as a critical link between meteorological conditions and carbon emissions, with ecosystem-specific differences determining the responsiveness of carbon emissions to meteorological drivers. These insights provide theoretical support for improving the accuracy of wildfire emission simulations in climate models and for developing vegetation-specific fire management and climate adaptation strategies. Full article

This study presents a data-driven framework that integrates lean management and digital business process modelling to enhance sustainability in textile manufacturing. Conducted in a company producing industrial safety textiles from Peru, this research applies lean tools within a digital BPM structure supported by real-time data tracking. The integrated approach led to increased production efficiency (from 79% to 86%), reduced setup times, and improved operational agility. The digital infrastructure empowered operators and supported informed decision-making. This work contributes to Industrial Engineering, Business Administration, and MIS by offering a holistic model that bridges lean principles with Industry 4.0 technologies. The findings, though context-specific, provide actionable insights for manufacturers aiming for smart and sustainable operations. Future research should validate the proposed framework across diverse industrial contexts and assess its longitudinal impact on lean performance outcomes. Full article

Background: Pulmonary embolism (PE) is a major cause of cardiovascular morbidity and mortality. Guidelines favor direct oral anticoagulants (DOACs) over vitamin K antagonists (VKAs), but real-world Croatian data are scarce. Methods: A prospective dual-center registry included 773 patients discharged with acute PE between 2013 and 2024. Clinical, laboratory, and socioeconomic data were collected. The primary outcome was all-cause mortality; secondary outcomes were recurrent venous thromboembolism (VTE) and major bleeding. Results: DOAC users were younger, with higher education and income, than VKA or heparin patients. Median follow-up was 1106 days. Mortality reached 60.3% with VKA, 26.0% with DOAC, and 84.1% with heparin (p < 0.001). VTE recurrence did not differ significantly. Major bleeding occurred in 9.3% of VKA versus 2.9% of DOAC patients (p = 0.003). Adjusted analysis showed a lower mortality risk with DOAC versus VKA (HR 0.62, 95% CI 0.48–0.80, p < 0.001), while heparin predicted higher mortality (HR 3.63, 95% CI 2.54–5.21, p < 0.001). Higher PESI class independently increased mortality and recurrence. Conclusion: In the first Croatian PE cohort, DOACs were linked to reduced mortality and bleeding risk compared with VKAs, with similar recurrence. Clinical, socioeconomic, and policy factors strongly influenced prescribing patterns and outcomes. Full article

(1) Background: Pulmonary embolism (PE) is a severe complication of coronavirus disease 2019 (COVID-19), particularly in hospitalized patients. Data from Eastern Europe, including Romania, are limited, despite potential regional differences in demographics, comorbidities, and thromboprophylaxis practices. (2) Methods: This retrospective cohort study included 395 adults hospitalized with RT-PCR-confirmed COVID-19 at the “Victor Babeș” Clinical Hospital of Infectious Diseases and Pneumophthisiology, Timișoara, Romania, from September 2022 to December 2024. Demographic, clinical, laboratory, and imaging data were extracted from medical records. PE was confirmed by computed tomography pulmonary angiography (CTPA). Group comparisons used chi-square and t-tests, with multivariable logistic regression to identify independent PE predictors. (3) Results: PE was diagnosed in 47 patients (11.9%). Compared to those without PE, patients with PE had higher D-dimer (5305.00 ± 1251.00 vs. 537.00 ± 203.00 ng/mL, p < 0.001), fibrinogen (6.33 ± 0.74 vs. 3.51 ± 0.60 g/L, p < 0.001), and PT/INR (1.68 ± 0.21 vs. 1.05 ± 0.09, p < 0.001). Prior venous thromboembolism (VTE; 19.1% vs. 8.3%, p = 0.03) and prolonged immobilization (61.7% vs. 23.0%, p < 0.001) were significant risk factors. Intensive care unit (ICU) transfer occurred in 59.6% of PE cases, with a 25.5% in-hospital mortality rate. All PE patients received anticoagulation; 10.6% underwent thrombolysis. (4) Conclusions: In this Romanian cohort, one of the first large-scale studies in Eastern Europe, PE was prevalent among hospitalized COVID-19 patients, associated with elevated coagulation markers, identifiable risk factors, and high mortality. Early recognition and optimized thromboprophylaxis are critical to improve outcomes. Full article

Research visibility has become a critical issue for universities, yet the institutional conditions that shape it remain underexplored. While Current Research Information Systems (CRISs) provide essential infrastructure for managing publications and researcher profiles, their impact depends on broader governance and cultural factors. This study compares four universities—two in Peru, one in Chile, and one in Spain—that have adopted the Pure CRIS platform. Data were manually extracted from institutional portals and analyzed descriptively, using normalized indicators such as publications per researcher, Sustainable Development Goal (SDG) alignment, and collaboration networks. Although based on a limited sample, the analysis highlights substantial contrasts: European institutions show consolidated integration of CRIS into national evaluation systems, while Latin American universities remain at earlier stages of adoption, with fragmented policies and limited international reach. The findings suggest that technological platforms alone are insufficient; institutional commitment, coherent policies, and academic cultures that value dissemination are decisive. These insights contribute a comparative framework to guide universities, particularly in Latin America, seeking to strengthen their global research visibility. Full article

Directive (EU) 2024/3019 on urban wastewater treatment requires municipal wastewater treatment plants (WWTPs) to achieve energy neutrality by 2045. This study assessed the energy efficiency of a WWTP in central Poland over eight years (2015–2022), considering influent variability, electricity use and cost, and biogas recovery. The facility served 41,951–44,506 inhabitants, with treated wastewater volumes of 3.08–3.93 million m³/year and a real population equivalent (PE) of 86,602–220,459. Over the study period, the specific energy demand remained stable at 0.92–1.20 kWh/m³ (average 1.04 ± 0.09 kWh/m³), equivalent to 17.4–36.3 kWh/PE∙year. Energy efficiency indicators (EEIs) per pollutant load removed averaged 1.12 ± 0.28 kWh/kgBODrem, 0.53 ± 0.12 kWh/kgCODrem, 1.18 ± 0.36 kWh/kgTSSrem, 12.1 ± 1.5 kWh/kgTNrem, and 62.3 ± 11.7 kWh/kgTPrem. EEI per cubic meter of treated wastewater proved to be the most reliable metric for predicting energy demand under variable influent conditions. Electricity costs represented 4.48–13.92% of the total treatment costs, whereas co-generation from sludge-derived biogas covered 18.1–68.4% (average 40.8 ± 13.8%) of the total electricity demand. Recommended pathways to energy neutrality include co-digestion with external substrates, improving anaerobic digestion efficiency, integrating photovoltaics, and optimizing electricity use. Despite fluctuations in influent quality and load, the ultimate effluent quality consistently complied with legal requirements, except for isolated cases of exceeded phosphorus levels. Full article

Marine Bacteroidota are recognized bacterial producers of bioactive metabolites, yet their biosynthetic potential remains cryptic under standard laboratory conditions. Here, we developed chemically defined media for Fulvivirga kasyanovii 48LL (Cytophagia) and Tenacibaculum mesophilum fLL (Flavobacteriia) to evaluate the effect of environmentally relevant carbon sources on growth and secondary metabolism. F. kasyanovii utilized 31 of 34 tested carbon sources whereas T. mesophilum grew on only five substrates, underscoring a distinct nutritional preferences. Substrate significantly influenced the antibacterial activity of F. kasyanovii extracts. Growth on β-1,3-glucan, glycerol, poly(β-hydroxybutyrate) (PHB), fish gelatin, or pectin resulted in extracts generating the largest inhibition zones (10–13 mm) against Bacillus subtilis or Rossellomorea marisflavi. Genome analysis revealed F. kasyanovii to be enriched in biosynthetic gene clusters (BGCs), notably harboring a ~570 kb genomic island comprising five large NRPS/PKS-type clusters. Quantitative PCR confirmed carbon-source-dependent regulation of these operons: glucose induced BGC1, BGC3, and BGC4, while κ-carrageenan and PHB upregulated BGC2. Conversely, yeast–peptone medium (analogous to standard marine broth) repressed transcription across all active clusters. These findings demonstrate that naturally occurring carbon sources can selectively activate cryptic BGCs and modulate antibacterial activity in F. kasyanovii, suggesting that similar strategy can be used for natural-product discovery in marine Bacteroidota. Full article

Due to its efficiency, advanced oxidation processes (AOP), such as photo-Fenton, have become an alternative for removing emerging contaminants like paracetamol. The objective of this work was to perform a life cycle assessment (LCA) according to ISO 14040/44 for a heterogeneous photo-Fenton process catalyzed by Cu/Fe-pillared clays (PILC) for the removal of paracetamol from water. The study covered catalyst synthesis and four treatment scenarios, with inventories built from experimental data and ecoinvent datasets; treatment time was 120 min per functional unit. Environmental impacts for catalyst synthesis were quantified with ReCiPe 2016 (midpoint), while toxicity-related impacts of the degradation stage were assessed with USEtox™ (human carcinogenic toxicity, human non-carcinogenic toxicity, and freshwater ecotoxicity). Catalyst synthesis dominated most midpoint categories, the global warming potential for 1 g of Cu/Fe-PILC was 10.98 kg CO₂ eq. Toxicity results for S4 (photo-Fenton Cu/Fe PILC) showed very low values: 9.73 × 10⁻¹² CTUh for human carcinogenic and 1.29 × 10⁻¹³ CTUh for human non-carcinogenic. Freshwater ecotoxicity ranged from 5.70 × 10⁻⁴ PAF·m³·day at pH 2.7 (≥60 min) to 1.67 × 10⁻⁴ PAF·m³·day at pH 5.8 (120 min). Overall, optimizing pH and reaction time, are key levers to improve the environmental profile of AOP employing Cu/Fe-PILC catalysts. Full article

Biodegradable mulch films (BDMs) have emerged as a promising alternative to conventional polyethylene (PE) films in modern horticulture, yet the effect of film thickness on crop performance remains inadequately understood. In this study, a two-year field experiment (2023–2024) under protected cultivation was conducted to evaluate BDMs with thicknesses (0.006, 0.008, and 0.010 mm) for watermelon production in Beijing, China. The results showed that all BDMs enhanced soil temperature and moisture compared to bare soil (main effect of mulching, p < 0.05) and significantly influenced soil available nitrogen (p < 0.05), while other soil properties were less affected. Year effects were generally not significant, reflecting the stable microclimatic conditions under hoop-house cultivation. Mechanical property assessments indicated substantial declines in tensile load, tensile strength, and elongation at break after field use, especially for thinner films. Notably, Bio-0.006 and Bio-0.008 significantly improved fruit weight and soluble sugar content relative to PE (p < 0.05), leading to higher yields and better commercial quality. These results suggested that appropriately thin BDMs can satisfy agronomic requirements for watermelon under protected cultivation while minimizing plastic residues, offering a practical basis for optimizing biodegradable film thickness to balance mulching performance, productivity, and environmental sustainability. Full article

Traffic flow forecasting plays a significant role in intelligent transportation systems (ITSs) and is instructive for traffic planning, management and control.Increasingly complex traffic conditions pose further challenges to the traffic flow forecasting. While improving the accuracy of model forecasting, the parameter effectiveness of the model is also an issue that cannot be ignored. In addition, existing traffic prediction models have failed to organically integrate data with well-designed model architectures. Therefore, to address the above two issues, we propose the STAE-BiSSSM model as a solution. STAE-BiSSSM consists of Spatio-Temporal Adaptive Embedding (STAE) and Bidirectional Selective State Space Model (BiSSSM), where STAE aims to process features to obtain richer spatio-temporal feature representations. BiSSSM is a novel structural design serving as an alternative to Transformer, capable of extracting patterns of traffic flow changes from both the forward and backward directions of time series with much fewer parameters. Comparative tests between baseline models and STAE-BiSSSM on five real-world datasets illustrates the advance performance of STAE-BiSSSM. This is especially so on METRLA and PeMSBAY datasets, compared with the SOTA model STAEformer. In the short-term forecasting task (horizon: 15min), MAE, RMSE and MAPE of STAE-BiSSSM decrease by 1.89%/13.74%, 3.72%/16.19% and 1.46%/17.39%, respectively. In the long-term forecasting task (horizon: 60min), MAE, RMSE and MAPE of STAE-BiSSSM decrease by 3.59%/13.83%, 7.26%/16.36% and 2.16%/15.65%, respectively. Full article

Background: Greenhouses are pivotal to sustainable agriculture as they provide suitable conditions to support the growth of crops in unusable land such as arid areas. However, conventional greenhouse cover materials such as glass, polycarbonate (PC), and polyethylene (PE) sheets are limited in regulating internal conditions in the greenhouses based on environmental changes. Quantum and nonlinear metamaterials are emerging materials with the potential to optimize the covers and ensure appropriate regulation. Objective: This comprehensive review investigated the performance optimization of greenhouse covers through the potential application of nonlinear and quantum metamaterials as nano-additives, examining their effects on electromagnetic radiation management, crop growth enhancement, and temperature regulation within greenhouse systems. Method: The scoping review method was used, where 39 published articles were examined. Results: The review revealed that integrating nano-additives ensured that the greenhouse covers would block harmful near-infrared (NIR) radiation that generated heat while also optimizing for photosynthetically active radiation (PAR) to promote crop yields. Conclusions: The insights also indicated that the high sensitivity of the metamaterials would facilitate the regulation of the internal conditions within the greenhouses. However, challenges such as complex production processes that were not commercially scalable and the recyclability of the metamaterials were identified. Future work should further investigate pathways to produce hybrid greenhouse covers that integrate metamaterials with conventional materials to enhance scalability. Full article

This research explores the phenomenon of plate-end (PE) debonding in reinforced concrete (RC) beams strengthened with fiber-reinforced polymer (FRP) composites. This type of failure represents a key mechanism that undermines the structural performance and efficiency of FRP reinforcement systems. Despite the widespread use of FRP in structural repair due to its high strength and corrosion resistance, PE debonding—often triggered by shear or inclined cracks—remains a major challenge. Traditional computational models for predicting PE debonding suffer from low accuracy due to the nonlinear relationship between influencing parameters. To address this, the research employs machine learning techniques and SHapley Additive exPlanations (SHAP), to develop more accurate and explainable predictive models. A comprehensive database is constructed using key parameters affecting PE debonding. Machine learning algorithms are trained and evaluated, and their performance is compared with existing normative models. The study also includes parameter importance and sensitivity analyses to enhance model interpretability and guide future design practices in FRP-based structural reinforcement. Full article

Background: Glioblastomas (GBMs) are the most aggressive and common neoplasms that affect glial cells, presenting rapid growth, invasion, and resistance to treatments. Studies have demonstrated the potentially inhibitory effect of flavonoids on glioblastoma cells’ stemness and viability. However, further research is needed to explore sensitivity and the mechanism of action in chemoresistant cells. Methods: In this study, we characterized the impact of apigenin treatment on the viability and differentiation of human GBM cells in vitro and its effects on tumorigenesis and regulation of the inflammatory response in vivo. Results: The flavonoid apigenin reduced the viability of U-251 cells, patient-derived cells TG-1 and OB-1 stem cells in a dose-dependent manner, associated with the induction of acidic vesicle organelles formation and apoptosis. Treatment with apigenin also inhibited migration and induced neural differentiation in the remaining viable cells, characterized by a decrease in the expression of the precursor marker nestin and an increase in the expression of astrocyte and neuron markers, GFAP and β-III tubulin, respectively. The xenotransplantation of apigenin-pretreated U251 cells into rat brains did not lead to tumor formation, unlike untreated cells. The surrounding area of transplanted untreated U251 cells exhibited reactive microglia and astrocytes, along with increased VEGF expression, which was absent in implant sites of apigenin-pretreated GBM cells. Moreover, in this implant area, we observed a significant decrease in the expression of mRNA for inflammatory factors IL-1β, TNF, and NOS2, and the downregulation of IL-10 and IL-4. Conclusions: These results demonstrate that apigenin inhibits the growth of tumoral cells, affecting the viability of tumor stem cells and impairing tumorigenicity, while altering the regulatory profile of immunomodulatory proteins. Therefore, this flavonoid can be considered for further studies to determine its use as an adjuvant to the treatment of human GBMs. Full article

Polyethylene microplastics (PE-MPs) and glyphosate (GLY) are widespread aquatic contaminants, but their combined effects on microalgae remain poorly understood. This study assessed the individual and joint toxicity of GLY and PE-MPs to the model microalga Chlorella vulgaris. Acute (3-day) and chronic (7-day) exposures were performed using GLY at 1–40 mg/L, alone or combined with PE-MPs (10 mg/L). A four-parameter log-logistic (4PL) model was applied to estimate median effect concentrations (EC₅₀). After 72 h, the EC₅₀ values were 9.77 mg/L for the GLY single system and 2.31 mg/L for the GLY-PE combined system, confirming enhanced toxicity in combined exposures. Co-exposure reduced pigment levels (chlorophyll a, chlorophyll b, and carotenoids) by up to 65% and significantly increased oxidative stress markers, including reactive oxygen species production and malondialdehyde accumulation, compared with single treatments. Antioxidant enzymes (superoxide dismutase and catalase) showed concentration- and time-dependent responses, indicating activation of cellular defense mechanisms. Scanning Electron Microscopy revealed PE-induced aggregation and structural damage to algal cells, particularly at higher GLY concentrations. These findings demonstrate that PE-MPs can amplify the toxic effects of GLY on microalgae and highlight the need for further studies at environmentally relevant concentrations and with different polymer types. Full article

This paper provides a comprehensive overview of the application of fractional calculus in modern optimization methods, with a focus on its impact in artificial intelligence (AI) and computational science. We examine how fractional-order derivatives have been integrated into traditional methodologies, including gradient descent, least mean squares algorithms, particle swarm optimization, and evolutionary methods. These modifications leverage the intrinsic memory and nonlocal features of fractional operators to enhance convergence, increase resilience in high-dimensional and non-linear environments, and achieve a better trade-off between exploration and exploitation. A systematic and chronological analysis of algorithmic developments from 2017 to 2025 is presented, together with representative pseudocode formulations and application cases spanning neural networks, adaptive filtering, control, and computer vision. Special attention is given to advances in variable- and adaptive-order formulations, hybrid models, and distributed optimization frameworks, which highlight the versatility of fractional-order methods in addressing complex optimization challenges in AI-driven and computational settings. Despite these benefits, persistent issues remain regarding computational overhead, parameter selection, and rigorous convergence analysis. This review aims to establish both a conceptual foundation and a practical reference for researchers seeking to apply fractional calculus in the development of next-generation optimization algorithms. Full article