Search Results (955)

Fertilizer coating is an emerging strategy in fertilizer management in the quest to decrease their loss and environmental impact. Nitrous oxide (N₂O) is a significant greenhouse gas, and agricultural soils happen to be an important anthropogenic source of N₂O gases, mainly because of the use of nitrogen (N) fertilizers such as urea. This study examined the effects of double urea coating with nano-sulfur (NS) and organic materials; lignite, biochar and compost on N₂O fluxes from silt loam and sandy loam soils. N₂O fluxes were measured using an N₂O analyzer in a controlled environment for a period of 26 days. Cumulative N₂O fluxes were calculated for different treatments (nano-sulfur; NS, NS + lignite, NS + biochar, and NS + compost) as coatings on urea fertilizer with propagated uncertainties. Sandy loam soil had higher maximum N₂O emission (155.64 µg N m⁻² h⁻¹) compared to silt loam soil (24.47 µg N m⁻² h⁻¹). Uncoated urea and urea + NS coating resulted in higher N₂O emissions in both soils. Meanwhile, NS + organic second layer coatings decreased the N₂O fluxes, especially in sandy loam soil. The second organic layer coatings lowered the N₂O emissions with relatively lower effects in silt loam soil (3.8–7.0%) and a higher reduction in sandy loam soil (35.2–41.5%). Among the second organic coating materials, NS + lignite performed best, followed by NS + biochar and NS + compost. The results indicate that the urea coating as fertilizer management strategy as well as soil texture have considerable effects on fertilizer-induced N₂O emissions. The present study does not address the individual effects of organic coatings on N₂O emissions; furthermore, the characterization of the size distribution and morphology of the synthesized nano-sulfur, as well as the physicochemical properties (e.g., particle size, pH, C/N ratio, elemental composition) of the lignite, biochar, and compost coating materials, are omitted. The results of these analyses, together with the physical and chemical characterization of the produced organo-mineral fertilizers, will be presented in a forthcoming paper. Full article

Chronic obstructive pulmonary disease (COPD), which includes chronic bronchitis and emphysema, is highly prevalent worldwide and is the third leading cause of death. While some aspects of the disease were known since the Enlightenment, Laennec’s work in the 19th century began the process of our current understanding of this disease. In this narrative review, 13 clinicians and scientists with over three centuries of cumulative experience treating and studying COPD give their perspectives on the science underpinning our modern concept of this disease and its management. These include (1) the challenges of coming up with a name for what is a complex syndrome; (2) the evolution of our thinking on the natural history of the disease; (3) the importance of particulate matter inhalation in its pathogenesis; (4) the often-overlooked but important—and often treatable—systemic effects of the disease that contribute to its morbidity and mortality; (5) the changes in our perspective of not just addressing pathologic or physiologic abnormalities but also measuring outcomes, such as breathlessness or health-related quality of life, that are of considerable importance to the patient; (6) the role of pharmacologic therapy in not only providing symptomatic relief by increasing airway caliber but also in disease modification, especially by reducing exacerbation frequency; (7) lung hyperinflation as an essential feature of COPD pathophysiology, driving symptom burden, exercise limitation, and mortality risk; (8) long-term oxygen therapy, despite being demonstrated to prolong survival in a defined set of hypoxemic patients with COPD, still having unanswered questions regarding its application and delivery; and (9) pulmonary rehabilitation, a major component of the non-pharmacologic treatment of COPD patients and prominently situated in clinical guidelines for this disease. While this, by necessity, must be a brief review of a very complex disease, the perspectives of these esteemed clinicians and scientists should be of use to other clinicians in understanding and managing this disease. Full article

South Africa is highly susceptible to climate variability and long-term climatic shifts, necessitating a comprehensive understanding of changing extreme precipitation patterns to guide effective mitigation and adaptation responses. This study examined variations in extreme precipitation indices from 1981 to 2023 across the eastern Free State Province using daily rainfall records derived from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Ten extreme precipitation indices were evaluated, with trend detection conducted through the Innovative Trend Analysis (ITA) technique. Findings indicate that the majority of municipalities exhibited statistically significant declining trends (p < 0.05) in total wet-day precipitation (PRCPTOT), R99P, R95P, the Simple Daily Intensity Index (SDII), CDD, RX5day, R20mm, and R10mm, suggesting an overall reduction in both heavy and moderate rainfall occurrences. In contrast, significant upward trends (p < 0.05) were identified in CWD, and RX1day, reflecting a shift toward prolonged wet periods and more intense short-duration rainfall events. Taken together, these divergent patterns point to the simultaneous emergence of heightened drought vulnerability driven by reduced cumulative rainfall and increased flood risk linked to intensified precipitation extremes. These results underscore the importance of forward-looking, climate-resilient water resource management and context-specific adaptation strategies suited to the eastern Free State’s complex mountainous terrain. Full article

National parks are widely recognized as a key spatial conservation strategy for simultaneously safeguarding biodiversity and sustaining ecosystem services, yet comprehensive and causally robust evaluation frameworks are still needed to accurately assess their effectiveness and support evidence-based management. This study evaluates the conservation effectiveness of Qianjiangyuan National Park (QJYNP) from 2015 to 2024 using a multidimensional index, a PSM-DID quasi-experimental framework, and interpretable machine learning. The results show that the direct policy effect was significantly positive during 2015–2020, but shifted to a negative cumulative effect by 2024. The spillover effect in the buffer zone also turned significantly negative, potentially associated with tourism-related development shifting outward. In addition, slope, temperature, and population density were identified as key drivers of EEI heterogeneity with nonlinear threshold effects, while road-related impacts intensified over time. These findings indicate that quasi-experimental approaches better capture phased policy effects than conventional descriptive comparisons, and suggest that simple boundary controls are insufficient; instead, buffer zones should be incorporated into integrated management frameworks to mitigate external development pressures. Full article

Unmanned aerial vehicles (UAVs) serve as both communication relays and aerial couriers in modern urban logistics networks. Conventional trajectory optimization methods assume perfect localization and isotropic free-space tracking signal propagation, which limits their effectiveness in urban canyons. To address the positional uncertainty and signal blockage from buildings, we propose a digital twin-driven framework for continuous trajectory and resource optimization in UAV swarms. We model an urban environment containing random high-rise structures, applying a non-line-of-sight (NLoS) uncertainty to reflect realistic communication degradation. The digital twin (DT) architecture utilizes a dual-layer spatial representation that captures a dynamically decaying positional uncertainty radius of the recipient. We define a strict visual localization boundary that initiates deterministic target tracking with a state transition mechanism. To manage the complexity of swarm routing, we apply Density-Based Spatial Clustering of Applications with Noise (DBSCAN), assigning one UAV courier and one logistics transfer station to each cluster. The system executes a continuous re-optimization loop using an adaptive multi-objective Genetic Algorithm. This framework jointly minimizes cumulative outage probability and total flight time while enforcing a signal-to-noise ratio threshold and throughput constraints. This continuous adaptation mechanism mitigates NLoS blockage risks, supporting reliable communication and efficient delivery in Global Navigation Satellite System (GNSS)-degraded and obstacle-dense urban environments. Full article

High-density urban plazas hosting multi-session public events often experience pulsed inflows, prolonged crowd retention, and localized bottleneck congestion, creating crowd-safety risks that cannot be fully captured by static capacity or total evacuation time alone. This study develops an agent-based simulation framework to evaluate ultra-high-density exposure and evacuation dynamics in Guangzhou Huacheng Plaza during the International Light Festival. The model was constructed in AnyLogic using site-layout data, event organization records, official attendance information, historical event timelines, and publicly available video observations. Two scenarios were examined: normal dynamic entry–exit operation under different inter-performance intervals, and overload-triggered evacuation under alternative spatial management strategies. Model calibration and event-process validation were conducted by comparing simulated congestion hotspots, key event timing, delayed dispersal patterns, and evacuation-duration ranges with historical observations and documented event records. The results show that extending the inter-performance interval from 90 min to 120 min reduced the overload duration from 75 min to 5 min and decreased cumulative ultra-high-density exposure from 25.62 to 13.93. Under overload evacuation, zonal guidance mainly improved early-stage crowd redistribution, whereas increased exit capacity produced a stronger reduction in total evacuation time and sustained congestion. Total evacuation time decreased from 185 min in the baseline condition to 160 min under the combined strategy, while effective discharge capacity increased from 231.12 to 338.28 pedestrians/min. These findings indicate that crowd safety in open urban plazas depends not only on total attendance, but also on event pacing, bottleneck recovery time, and effective discharge capacity. The proposed exposure-oriented framework provides a quantitative basis for evaluating crowd accumulation and evacuation strategies in high-density open public spaces. Full article

Preventive geohazard assessment in heritage landscapes presents a methodological challenge, as environmental processes rarely operate within clearly bounded states. Instead, they evolve gradually across space and time and are often only partially observable. Conventional cumulative indices based on linear aggregation and fixed classification thresholds provide operational clarity but may suppress gradual activation, interaction effects, and uncertainty that are critical for preventive heritage management. This study develops a fuzzy geohazard assessment approach that extends cumulative hazard modeling through graded representation and uncertainty-aware aggregation. Environmental variables are represented as spatial fuzzy sets, allowing hazard conditions to be expressed as degrees of activation rather than discrete classes. Hazard-specific activation is derived through rule-based fuzzy inference, while cumulative geohazard conditions are synthesized using a weighted fuzzy γ aggregation operator that balances conjunctive behavior with precautionary disjunctive amplification. The approach is implemented within a Geographic Information System (GIS) environment and demonstrated in Parrhasian Heritage Park, a mountainous heritage landscape in Southern Greece. Results show that cumulative geohazard patterns respond systematically to variations in the precautionary parameter γ, enhancing transitional zones where multiple hazards coexist at moderate activation levels while preserving spatial continuity. Sensitivity analysis indicates that cumulative activation patterns remain structurally stable under moderate variations in membership calibration, supporting preventive GIS-based decision making. Full article

Life Cycle Assessment (LCA) is extensively employed to support sustainability evaluation in waste management and manufacturing systems; however, outcomes are highly sensitive to methodological decisions, particularly end-of-life (EoL) allocation approaches. This study examines how cut-off and substitution approaches affect the energy performance and decarbonisation potential of high-density polyethylene (HDPE) injection moulding systems. A dual framework is adopted: first, a literature review examines methodological sensitivities in EoL modelling; second, a quantitative case study assesses industrial-scale primary data for the production of durable HDPE bottles (300 mL). The LCA model integrates specific technical parameters, including a 220 °C melt temperature and a 36 s cycle time, ensuring a realistic representation of manufacturing conditions. The results indicate that allocation choices significantly influence calculated impacts, sometimes reversing the relative ranking of configurations. Substitution-based approaches report higher benefits by crediting avoided primary production, while cut-off logic provides more conservative estimates. Quantitative analysis shows that transitioning from open-loop to fully closed-loop configurations reduces cumulative energy demand by 3.2% and freshwater emissions per functional unit by 2.8%. Furthermore, the study identifies a ‘landfill paradox’ specific to HDPE waste within transitional energy systems: due to the carbon sequestration effect of landfilled polymers and current grid emission factors, landfilling exhibits a lower net carbon footprint (0.03 kg CO₂-eq./kg) than high-efficiency incineration (1.54 kg CO₂-eq./kg). These findings highlight that circular economy evaluations are strongly shaped by methodological assumptions, with direct implications for energy policy. Bridging the gap between specific industrial processing parameters and end-of-life allocation logic underscores the need to incorporate primary industrial data and transparent allocation frameworks to support reliable decision-making in the transition toward low-carbon and energy-efficient manufacturing systems. Full article

To mitigate the impact of global climate change, countries worldwide must take necessary measures to address this environmental issue. China’s goals of carbon peaking and carbon neutrality and the “1 + N” policy framework have provided guidance for various industries and enterprises in advancing carbon accounting, carbon reduction, and green transformation. This study focuses on the sludge dewatering facility of a typical water treatment plant, which uses water from the South-to-North Water Diversion Project as its water source. Based on its construction and operational data, the carbon emissions at different phases were calculated with the emission factor method in the study, and the composition of these emissions was analyzed. The results show that during the three-year construction period, the sludge dewatering facility emitted a total of 1385.57 tons of CO₂-eq, with materials being the main source of carbon emissions. While in the one-year operation period, the facility generated 19.38 tons of CO₂-eq only, with electricity consumption being the primary contributor, followed by chemicals consumption. In conclusion, both the short-term intensive emissions during the construction phase and the long-term cumulative emissions during the operation phase should be considered, so that an integrated mitigation effect can be achieved across the construction and operation stages. This highlights the necessity of adopting a life-cycle perspective in carbon reduction strategies within the defined system boundary, while also supporting the sustainable planning and management of water treatment infrastructure. Full article

Polychlorinated biphenyls (PCBs) remain a major concern in marine ecosystems, where bioaccumulation in fish occurs as complex congener mixtures whose dynamics challenge conventional indicator approaches. This study develops and evaluates a data-driven framework for refining mixture-based indicators of PCB contamination by integrating ensemble machine learning with explainable artificial intelligence. Focusing on PCB-138 as a target indicator of cumulative PCB burden, we analyse concentrations of 24 organochlorines together with biological covariates in four Mediterranean edible pelagic fish species (sardine, anchovy, horse mackerel, and chub mackerel). Comparative evaluation of indicator performance shows that alternative congener combinations, including i4 PCBs (-138, -153, -170, -180), i6 PCBs (-138, -153, -170, -180, -118, -123), and mixtures incorporating DDD and DDE, more effectively represent total PCB burden than traditional indicator groups. Clustering identifies two distinct bioaccumulation settings, characterized by high-concentration coherent congener effects and low-concentration heterogeneous responses, demonstrating that indicator performance depends on concentration range and mixture context. The study illustrates how interpretable machine learning approaches can serve as formal tools for indicator evaluation and optimisation, strengthening long-term monitoring and management of legacy contaminants in marine ecosystems, particularly under conditions of persistent exposure and renewed inputs from sediment remobilization and riverine transport. Full article

Groundwater level (GWL) variations in the arid regions of Northwest China are driven by both natural processes and human activities. Identifying causal links between hydrological variables is fundamental to understanding groundwater evolution and conducting dynamic simulations. This study integrates the Mann–Kendall test, Seasonal-Trend decomposition using Loess, and the Peter and Clark Momentum-threshold and Momentary Conditional Independence (PCMCI) causal inference to analyze GWL variation characteristics and causal response processes across seven sub-basins in the Tarim Basin using multi-source remote sensing data. Results show an overall decline in GWL, primarily in the north-central part of the basin, with the Kaidu–Konqi River Basin reaching a maximum rate of 0.51 m/year. The trend components reveal localized depletion alongside broad stability, while seasonal components exhibit three types of temporal shifts in fluctuations. A mismatch exists between the prevalence of environmental influences and their causal strength. Daytime land surface temperature (LST_D), surface runoff (RO), and evapotranspiration (ET) show the highest detection frequencies, yet volumetric soil water in layers 2 (SWVL₂) and RO exhibit the largest ranges in strength and drive variations at specific sites. Response times are asymmetric. Negative effects from ET on GWL transmit quickly, while positive recovery is slow. Conversely, positive recharge from volumetric soil water in layer 1 (SWVL₁) is faster than its negative lag. At the basin scale, surface processes recharge GWL while mediating indirect influences from other variables. Climate and agricultural irrigation act as direct sinks. Depending on local conditions, three regional patterns emerge: direct climate-driven depletion, obstructed shallow water retention, and indirect compensation from agricultural water use. Causal networks indicate that RO and SWVL₁ have the highest centrality and dominate water output, whereas SWVL₂ acts as a passive receiver. Pathways from the surface to GWL are also asymmetric. The most frequent path involves step-by-step infiltration along RO → ET → SWVL₁ → SWVL₂ → GWL. In contrast, the paths with the highest cumulative strength are shorter and faster, specifically RO → ET → GWL and RO → SWVL₁ → GWL. The identified pathways and lag parameters provide a direct basis for groundwater dynamic modeling and water resource management in the basin. Full article

Lepidolite deposits are rare-metal deposits in which lepidolite is the principal industrial mineral. Owing to thin overburden and widespread open-pit mining, their exploitation supports raw material supply for the new energy industry but also continuously disturbs mining ecosystems, thereby threatening regional ecological security. Under the combined effects of fragile natural conditions and human-induced mining disturbance, traditional fixed-weight evaluation methods have difficulty identifying stage-wise changes and localized high-risk characteristics of ecological security in lithium mining areas. Taking the lithium mining area of Huaqiao Township, Yichun, as a case study, this study constructed an ecological-security evaluation system based on the Driver–Pressure–State–Impact–Response–Management (DPSIRM) framework and introduced variable weight (VW) theory to develop a penalty-dominated state variable weight model. This model enabled the dynamic adjustment of indicator weights across years and evaluation units, while the geographic detector was used to identify the main driving factors. Results showed that (1) from 2010 to 2024, ecological security exhibited a stage-wise pattern of initial improvement followed by degradation, and low-security areas first contracted and then expanded outward; (2) vegetation coverage was a key driving factor, while interactions between any two factors were stronger than the effect of a single factor, indicating that cumulative multi-stressor effects strongly shaped spatial differentiation; and (3) compared with the constant weight (CW) method, the VW method produced finer stratification within the severely degraded tail at the Shixiawo mining site across the four assessment years, demonstrating applicability at a representative mining site in this Huaqiao case study. These findings provide a scientific basis for ecological assessment, restoration, and coordinated resource management in lithium mining areas. Full article

Accurate yield estimation is vital for precision wheat management and breeding. Traditional methods based on single growth stages or single-source data cannot capture cumulative growth effects, limiting prediction accuracy. UAV remote sensing provides high-resolution, multi-source, and multi-temporal data, enabling improved non-destructive yield estimation. In this study, UAV-based multispectral and RGB imagery were collected at six key growth stages, and vegetation indices, texture, and color features were extracted to develop yield prediction models using RF, XGBoost, and KNN under single- and multi-temporal scenarios. The results showed that red-edge-based vegetation indices were highly sensitive to wheat yield and outperformed texture- and color-based features. Multi-feature fusion further improved prediction accuracy at key growth stages, particularly during booting and flowering (R² = 0.53–0.67). Compared with single-temporal models, multi-temporal data fusion significantly enhanced yield estimation accuracy, achieving a maximum R² of 0.72 by integrating data from the late-jointing, booting and flowering stages. Among the algorithms, XGBoost and KNN exhibited superior accuracy and stability across most growth stages. Overall, these results demonstrate that integrating UAV-based multi-source and multi-temporal remote sensing data effectively improves the accuracy and robustness of wheat yield estimation, providing valuable technical support for precision agriculture and phenotyping-assisted breeding. Full article

Background/Aim: Cardiovascular disease (CVD) represents a relevant global public health challenge with dyslipidemia as a major modifiable cardiovascular risk factor (CVRF). Recent advances have introduced injectable lipid-lowering therapies (LLT). Their clinical effectiveness in real-world practice seems to depend not only on pharmacological efficacy but also on patients’ acceptance, adherence, and persistence, influenced directly by perceived barriers and facilitators. The main objective of this scoping review is to map the barriers and facilitators related to the use of novel injectable LLTs among adult patients with dyslipidemia or CVD. Methods: This review was conducted in accordance with JBI methodology and reported according to Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for scoping reviews (PRISMA-ScR); pre-registration on Open Science Framework (OSF) was performed. A search was conducted in MEDLINE from PubMed, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL) from EBSCOhost, and Google Scholar up to June 2025. Eligible studies included qualitative, quantitative, mixed-methods, and review papers involving adult patients with dyslipidemia who reported experiences, perceptions or challenges related to the use of injectable LLT in any healthcare or community setting worldwide. Two reviewers independently screened studies, selected and extracted data. Results: Out of 665 records identified, 7 studies met the inclusion criteria. Patients’ adherence to injectable LLTs is shaped by psychological fears, prior negative experiences, and perceived efficacy. Satisfaction increases when patients feel supported and informed. Convenience, self-administration, and motivational meaning facilitate persistence. Organizational support and economic accessibility further influence uptake, highlighting that adherence depends on both patient experience and structural factors. Conclusions: Patient acceptance and persistence with injectable LLT depends on a complex interplay of emotional, clinical, organizational and economic factors, beyond pharmacological efficacy alone. Fear of injections, previous statin-related experiences, administrative complexity, and high costs remain major barriers, while shared decision-making, trust in healthcare providers, perceived efficacy, regimen convenience, and supportive structures act as strong facilitators. Addressing these challenges requires multidimensional and multidisciplinary strategies for policy makers and clinical managers. Full article

Objectives: Management of unstable pelvic fractures during pregnancy presents a major therapeutic challenge, requiring careful multidisciplinary evaluation to balance maternal benefits and fetal radiation risks. Methods: We report the case of a 32-year-old patient who presented with a pelvic fracture due to a road traffic accident at three months of pregnancy. A left sacroiliac osteosynthesis was performed to treat a left sacroiliac diastasis with pelvic osteosynthesis using a trans-iliosacral approach under cone-beam CT (CBCT) guidance using a very-low-dose protocol. Radiation parameters and fetal dose estimates were calculated in advance in collaboration with a medical physicist. Tight beam collimation, a reduced field of view, and minimization of fluoroscopic checks were applied to keep fetal exposure as low as reasonably achievable. This article aims to demonstrate the feasibility of managing a complex pelvic fracture using interventional radiology and to review the literature on management options and gestational age-dependent fetal risks. Results: The estimated cumulative fetal dose from initial imaging, open surgery, and CBCT-guided osteosynthesis remained below 70 mGy using a pregnant phantom (Duke Organ Dose–Dosewatch–General Electric system), which is below thresholds associated with deterministic effects. The procedure achieved optimal screw positioning with less than 40 s of fluoroscopy. Maternal postoperative recovery was favorable, and follow-up revealed normal fetal development. Conclusions: This case demonstrates that CBCT-guided percutaneous iliosacral screw fixation can be safely performed during pregnancy with meticulous planning, dose-reduction strategies, and multidisciplinary collaboration, maintaining fetal radiation exposure below accepted safety thresholds. Full article