Search Results (417,018)

Amphibian populations have experienced a severe decline over the past 40 years, driven primarily by environmental pollution, habitat destruction, climate change, and disease. This work reports, for the first time, saprolegniosis in Pelophylax perezi egg masses and saprolegniosis in amphibians in Portugal. After isolation and phylogenetic analysis, the pathogen was identified as Saprolegnia australis. Following this, the present work intended to screen a collection of P. perezi skin bacteria for the existence of bacterial strains with inhibitory action against the newly identified S. australis SC1 and two other species, Saprolegnia diclina SAP 1010 UE and Saprolegnia australis SAP 1581 UE. The results showed that various bacterial species could inhibit the growth of these three species of oomycetes. Bacteria with the most significant antagonistic action against Saprolegnia spp. predominantly belonged to the genus Bacillus, followed by Serratia, Pseudomonas, and Aeromonas. Despite variations in bacterial diversity among frog populations, the present study also demonstrated the presence of bacteria on frogs’ skin that were capable of inhibiting Saprolegnia spp., as evidenced by in vitro challenge assays. These findings highlight the protective function of bacteria present in amphibian skin. The observed bacterial diversity may contribute to the metabolic redundancy of the frog skin microbiome, helping to maintain its functional capacity despite shifts in the community composition. Additionally, the study found that, when providing a more advantageous environment for pathogen growth—in this case a peptone–glucose (PG) medium instead of R2A—the percentage of bacteria with moderate-to-strong antagonistic activity dropped by 13% to 4%. In conclusion, the presence of bacteria capable of inhibiting Saprolegnia spp. in adult individuals and across different environmental conditions may contribute to lowering the susceptibility of frog adults towards Saprolegnia spp., compared with that in the early stages of development, like the tadpole or egg stages. Full article

Regenerative agricultural practices emphasize the use of diverse pasture species within sustainable agriculture production systems. The inclusion of a range of legume species in diverse pasture swards is likely to increase biological N fixation (BNF) across seasons, reducing the system’s reliance on synthetic N inputs. The present field study aims to quantify BNF in selected legume species within diverse pasture (combining 9 species) and standard pastures (ryegrass and clover combination) and assess their performance to identify the potential for improving N supply while maintaining year-round pasture quality. A year-round seasonal BNF was assessed by evaluating soil N status, nodulation patterns, plant composition, and conducting ¹⁵N natural abundance studies. The results revealed that the diverse pasture sward produced 5.4% more dry matter compared to the standard pasture, while soil mineral N (NO₃⁻, NH₄⁺) remained statistically similar between the two treatments. Nitrogen yield was 9.3% higher in the diverse pasture than in the standard pasture. ¹⁵N natural abundance analysis assessment revealed no substantial variation in BNF rates across treatments throughout the study. However, in contrast to standard pasture, the BNF rate in diverse pasture experienced a 3-fold increase from winter to summer, while the standard pasture exhibited a 1.5-fold increase. In both pasture systems, BNF increased with clover proportion up to 30%, indicating optimal fixation at moderate clover levels. The findings underscore the potential of diverse pastures when strategically managed to enhance seasonal BNF while sustaining pasture productivity. Full article

Prolonged exposure to landfill leachate can weaken the impermeability of liner systems, leading to leachate leakage and the contamination of surrounding soil and water. To improve loess impermeability to enable its use as a liner material, this study uses synthetic landfill leachate to investigate its effects on loess permeability via a series of laboratory tests. This study focused on the influence of varying dosages of calcium lignosulfonate (CLS) on loess permeability, along with its capacity to adsorb and immobilize heavy metal ions. Microscale characterization techniques, including Zeta potential analysis, X-ray fluorescence spectroscopy (XRF), and scanning electron microscopy (SEM), were employed to investigate the impermeability mechanisms of CLS-modified loess and its adsorption behavior toward heavy metals. The results indicate that the permeability coefficient of loess decreases significantly with increasing compaction, while higher leachate concentrations lead to a notable increase in permeability. At a compaction degree of 0.90, the permeability coefficient was reduced to 8 × 10⁻⁸ cm/s. In contrast, under conditions of maximum leachate concentration, the permeability coefficient rose markedly to 1.5 × 10⁻⁴ cm/s. Additionally, increasing the dosage of the compacted loess stabilizer (CLS) effectively reduced the permeability coefficient of the modified loess to 7.1 × 10⁻⁵ cm/s, indicating improved impermeability and enhanced resistance to contaminant migration. With the prolonged infiltration time of landfill leachate, the removal efficiency of Pb²⁺ gradually decreases and stabilizes, while the Pb²⁺ removal efficiency of the modified loess increased by approximately 40%. CLS-modified loess, through multiple mechanisms, reduces the fluid flow pathways and enhances its adsorption capacity for Pb²⁺, thereby improving the soil’s protection against heavy metal contamination. While these results demonstrate the potential of CLS-modified loess as a sustainable landfill liner material, the findings are based on controlled laboratory conditions with Pb²⁺ as the sole target contaminant. Future work should evaluate long-term performance under field conditions, including seasonal wetting–drying and freeze–thaw cycles, and investigate multi-metal systems to validate the broader applicability of this modification technique. Full article

This paper presents the formulation and simulation-based validation of a novel hierarchical fuzzy-adaptive Proportional–Integral–Derivative (PID) control framework for a rectilinear active mass damper, designed to enhance vibration suppression in structural applications. The proposed scheme utilizes a Linear–Quadratic Regulator (LQR)-optimized PID controller as the baseline regulator. To address the limitations of this baseline PID controller under varying seismic excitations, an auxiliary fuzzy adaptation layer is integrated to adjust the state-weighting matrices of the LQR performance index dynamically. The online modification of the state weightages alters the Riccati equation’s solution, thereby updating the PID gains at each sampling instant. The fuzzy adaptive mechanism modulates the said weighting parameters as nonlinear functions of the classical displacement error and normalized acceleration. Normalized acceleration provides fast, scalable, and effective feedback for vibration mitigation in structural control using AMDs. By incorporating the system’s normalized acceleration into the adaptation scheme, the controller achieves improved self-tuning, allowing it to respond efficiently and effectively to changing conditions. The hierarchical design enables robust real-time PID gain adaptation while maintaining the controller’s asymptotic stability. The effectiveness of the proposed controller is validated through customized MATLAB/SIMULINK-based simulations. Results demonstrate that the proposed adaptive PID controller significantly outperforms the baseline PID controller in mitigating structural vibrations during seismic events, confirming its suitability for intelligent structural control applications. Full article

Unmanned Aerial Vehicles (UAVs) integrated with lightweight deep learning models represent an effective solution for image-based rapid post-earthquake damage assessment. UAVs, equipped with cameras, capture high-resolution aerial imagery of disaster-stricken areas, providing essential data for evaluating structural damage. When paired with light eight Convolutional Neural Network (CNN) models, these UAVs can process the captured images onboard, enabling real-time, accurate damage level predictions that might with potential interest to orient efficiently the efforts of the Search and Rescue (SAR) teams. This study investigates the use of the MobileNetV3-Small lightweight CNN model for real-time post-earthquake damage level prediction using UAV-captured imagery. The model is trained to classify three levels of post-earthquake damage, ranging from no damage to severe damage. Experimental results show that the adapted MobileNetV3-Small model achieves the lowest FLOPs, with a significant reduction of 58.8% compared to the ShuffleNetv2 model. Fine-tuning the last five layers resulted in a slight increase of approximately 0.2% in FLOPs, but significantly improved accuracy and robustness, yielding a 4.5% performance boost over the baseline. The model achieved a weighted average F-score of 0.93 on a merged dataset composed of three post-earthquake damage level datasets. It was successfully deployed and tested on a Raspberry Pi 5, demonstrating its feasibility for edge-device applications. This deployment highlighted the model’s efficiency and real-time performance in resource-constrained environments. Full article

Enhancing urban air quality and thermal comfort involves addressing multifaceted environmental and design challenges. Investigating the effects of urban morphological and building geometrical parameters on enhancing air quality and thermal comfort is a multifaceted problem, influenced by different parameters. This study aims to develop optimized design solutions for university buildings and courtyards to enhance outdoor thermal comfort and reduce CO₂ concentration levels as an indicator of air quality. Consequently, the methodology involved a combination of field monitoring at two university faculties in Egypt and a computational parametric methodology using Rhino 3D+Grasshopper(V8) for enhancing thermal comfort, reducing CO₂ concentration levels, and improving wind velocity. The in situ measurements revealed significantly high CO₂ levels (780 ppm) and wind speed (3.8 m/s). The parametric methodology’s findings revealed a substantial reduction in the Universal Thermal Climate Index (UTCI) by 2.04 to 10.3 °C, a decrease in CO₂ concentration by 57 to 197 ppm, and an increase in wind speed by 0.4 to 4.07 m/s. The most suitable vegetation ratio for trees within narrow courtyard designs was found to be 30%. This ratio effectively enhances thermal comfort (UTCI) and reduces CO₂ concentrations, while also maintaining adequate airflow and avoiding excessive obstruction of natural ventilation within the courtyard. These findings provide valuable guidance for optimizing courtyard designs in hot arid climates. Full article

To enhance the utilization efficiency of coal gangue aggregate, coarse aggregates are chemically modified with 5% sodium silicate solution. The effects of this modification on the compressive strength and microstructural characteristics of concrete are systematically investigated through integrated macro-testing and micro-characterization. By evaluating the compressive performance of modified coal gangue concrete blocks, the optimal mix ratio of each strength grade of blocks is determined. Experimental results indicate that the apparent density, water absorption, and crushing index of the modified coal gangue coarse aggregate exhibit better mechanical properties than the control group. The modified coal gangue coarse aggregate demonstrates improved mechanical performance, with the compressive strength of 28-day concrete showing a 15.3% increase relative to the control group. Furthermore, using a sodium silicate solution effectively enhances the interface transition zone’s performance between coal gangue coarse aggregate and cement mortar, improving the compactness of this interface. The modified coal gangue concrete blocks exhibit higher compressive strength than the original material. When the substitution rate remains constant, the compressive strength of modified coal gangue concrete decreases with increasing water–cement ratio. Similarly, at a constant water–binder ratio, compressive strength decreases with higher modified gangue aggregate replacement. Finally, compressive tests are conducted on masonry constructed with hollow blocks of strength grades MU7.5, MU10, and MU15. Then, a calculation model for the average compressive strength of modified coal gangue concrete hollow block masonry is proposed, providing theoretical support for its engineering application. Full article

Market gardening plays a crucial role in ensuring food security and reducing poverty in Africa’s rapidly urbanizing regions. However, urban agricultural systems are increasingly threatened by climatic shocks such as floods, droughts, and heat waves. This study uses an integrated approach to analyze the multidimensional factors of climatic vulnerability among urban market gardeners in the Grand Nokoué region of Benin. Based on socio–economic, technico–agronomic, and perceptual data collected from 369 growers, multiple correspondence analysis (MCA) coupled with ascending hierarchical analysis (AHA) was performed to identify vulnerability profiles. K–means partitioning was used to confirm the optimal number of groups, thereby guaranteeing the robustness and internal consistency of the typology. Three distinct vulnerability groups were identified, each characterized by specific socioeconomic, technical, and territorial characteristics, as well as varying exposure to the risks of flooding, drought, and dry spells. The results show that the most vulnerable farmers tend to be young women with low incomes, limited access to land, and a reliance on manual irrigation in flood–prone areas. These findings emphasize the uneven distribution of adaptive capacities and the pressing requirement for tailored public policies to enhance resilience, especially among small–scale, low–income, and land–insecure urban farmers, who are vulnerable to various climate–related risks. Full article

Reducing environmental impacts and energy consumption in construction is increasingly important, prompting the use of renewable, ecological, and cost-effective materials. This research investigates an ecological building material combining clay and ground reed fibers, offering a promising alternative to conventional resources. A composite made of 50% clay and 50% ground reed was developed to study the influence of fiber size after grinding, as reed is typically used in its unprocessed form. Initial analyses included a physico-chemical characterization of both clay and reed. Thermal performance was then evaluated under steady-state and transient conditions to assess heat storage, heat transfer, and the material’s thermal inertia. The results showed a thermal conductivity of 0.38 W/m·K and an estimated 50% energy savings compared to clay alone, demonstrating the composite’s enhanced insulation capacity. Mechanical tests revealed compressive strengths of 2.48 MPa and flexural strengths of 0.79 MPa, with no significant effect from fiber size. The composite is lighter and more insulating than traditional clay blocks, indicating potential for reduced heating demand and improved indoor comfort. This study confirms the feasibility of incorporating ground reed fibers into clay-based composites to produce more sustainable building materials, supporting the transition toward energy-efficient and environmentally responsible construction practices. Full article

Brewer’s spent grain (BSG), a by-product originating from the brewing industry, contains substantial amounts of fibers, proteins, and bioactive compounds; however, its utility is restricted by anti-nutritional factors. Solid-state fermentation (SSF) presents a viable method for improving the nutritional and functional properties of BSG. Microorganisms such as Rhizopus oligosporus have been demonstrated to enhance nutrient bioavailability, facilitate the degradation of complex carbohydrates, and improve protein digestibility while simultaneously reducing anti-nutritional components. Furthermore, this fermentation process yields bioactive compounds that exhibit antioxidant, anti-inflammatory, and prebiotic properties, thereby contributing to improved gut health, the prevention of metabolic disorders, and enhanced nutritional outcomes. Additionally, SSF seeks sustainability by repurposing agro-industrial by-products, reducing waste, and promoting the principles of a circular economy. Collectively, these advantages underscore the transformative potential of SSF in converting BSG into a functional food ingredient, effectively addressing contemporary health and environmental challenges and offering innovative solutions for food security and sustainable development. Full article

Wireless sensor networks (WSNs) are fundamental to applications in the Internet of Things, smart cities, and environmental monitoring, where coverage optimization is critical for maximizing monitoring efficacy under constrained resources. Conventional approaches often suffer from low global coverage efficiency, high computational overhead, and a tendency to converge to local optima. To address these challenges, this study proposes the fusion multi-strategy gray wolf optimizer (FMGWO), an advanced variant of the Gray Wolf Optimizer (GWO). FMGWO integrates various strategies: electrostatic field initialization for uniform population distribution, dynamic parameter adjustment with nonlinear convergence and differential evolution scaling, an elder council mechanism to preserve historical elite solutions, alpha wolf tenure inspection and rotation to maintain population vitality, and a hybrid mutation strategy combining differential evolution and Cauchy perturbations to enhance diversity and global search capability. Ablation studies validate the efficacy of each strategy, while simulation experiments demonstrate FMGWO’s superior performance in WSN coverage optimization. Compared to established algorithms such as PSO, GWO, CSA, DE, GA, FA, OGWO, DGWO1, and DGWO2, FMGWO achieves higher coverage rates with fewer nodes—up to 98.63% with 30 nodes—alongside improved convergence speed and stability. These results underscore FMGWO’s potential as an effective solution for efficient WSN deployment, offering significant implications for resource-constrained optimization in IoT and edge computing systems. Full article

The purpose of this research is to investigate the misconceptions related to geological concepts among Secondary Education students in the region of Achaia, Greece. The study focuses on both Lower Secondary Education (Gymnasium, grades 7–9) and Upper Secondary Education, including General and Vocational Education (grades 10–12). Previous research has shown that students entering Lower Secondary Education or High School often possess several misconceptions about geological concepts. These misconceptions result in a fragmented or incorrect understanding, which may arise from intuitive perceptions of how the natural world evolves that are incorrect, or from stereotypes and assumptions acquired from the family environment or inadequacies in the school curriculum. Despite teachers’ efforts to clarify these concepts, a significant percentage of students continue to hold misconceptions, mainly related to minerals and rocks. A total of 1065 secondary students completed an online closed-ended questionnaire that was designed and validated based on previous research findings to highlight their misconceptions. This study results showed a clear differentiation between students from urban and rural areas, while demographic characteristics (such as gender, age, parents’ occupation, and parents’ marital status) did not appear to play a significant role. In addition, the responses to specific sets of questions varied depending on the student’s grade level. Identifying students’ misconceptions can support the development of appropriate educational tools and/or inform targeted interventions that aim to clarify these concepts and correct any incorrect assumptions. Full article

Background and Objectives: Diabetes affects quality of life (QoL) in physical, psychological, and social aspects. With high prevalence rates in Saudi Arabia, this study aimed to assess QoL in adults with diabetes across different regions and identify associated factors, addressing research gaps on complications and demographic influences. Materials and Methods: This cross-sectional study recruited adults diagnosed with diabetes from all regions of Saudi Arabia through phone interviews and the distribution of self-administered questionnaires via social media platforms. Data on demographics, health behaviors, diabetes-related complications, comorbidities, and diabetes management were collected. QoL was assessed using the Diabetic Quality of Life (DQoL) tool. Statistical analysis included descriptive statistics and multivariate regression, with significance set at p < 0.05. Results: Among the 527 individuals with diabetes, 57.7% were married, 56.1% were female, 93.7% lived in urban areas, and 37.2% had at least a bachelor’s degree. Common comorbidities included hypertension (29.2%) and hypercholesterolemia (22.8%). Physical activity and healthy weight were linked to improved DQoL. Diabetic complications, such as neuropathy (6.6%) and diabetic foot (4.9%), were significantly associated with lower DQoL scores. Depression was reported in 4.7% of participants and was the strongest predictor of poor QoL (β = −2.01, p < 0.001). Furthermore, individuals who exercised less than five times per week had significantly lower QoL scores (beta = −1.83; 95% CI = −2.56 to −1.10; p-value < 0.001). Conclusions: The study highlights the significant impact of education, health behaviors, diabetes complications, and comorbid depression on QoL. Comprehensive diabetes care that addresses both physical and psychological factors is essential for achieving improved outcomes. Full article

This study introduces a real-time, non-intrusive monitoring system designed to support elderly care through vision-based pose estimation and hand gesture recognition. The proposed framework integrates convolutional neural networks (CNNs), temporal modeling using LSTM networks, and symmetry-aware keypoint analysis to enhance the accuracy and reliability of behavior detection under varied real-world conditions. By leveraging the bilateral symmetry of human anatomy, the system improves the robustness of posture and gesture classification, even in the presence of partial occlusion or variable lighting. A total of 21 hand landmarks and 33 body pose points are used to recognize predefined actions and communication gestures, enabling seamless interaction without wearable devices. Experimental evaluations across four distinct lighting environments confirm a consistent accuracy above 90%, with real-time alerts triggered via IoT messaging platforms. The system’s modular architecture, interpretability, and adaptability make it a scalable solution for intelligent elderly individual monitoring, offering a novel application of spatial symmetry and optimized deep learning in healthcare technology. Full article

Dysregulation contributes to Alzheimer’s disease (AD) pathophysiology. Zinc therapy promotes enterocyte copper sequestration, potentially reducing systemic copper. Individual biological responses may vary. Methods: ZINCAiD was a 24-week, randomized, double-blind, placebo-controlled phase II trial assessing zinc therapy in individuals with mild cognitive impairment (MCI) due to AD (EudraCT No.: 2019-000604-15; registered on 26 March 2020). Participants were randomized 2:1 to receive elemental zinc (135 mg/day for 12 weeks, then 65 mg/day) or placebo. Ceruloplasmin was measured at predefined intervals for safety monitoring, blinded to the investigators. Post hoc, “Zinc Responders” were defined by ≥20% reduction in ceruloplasmin at week 12. The primary cognitive endpoint was the Cognitive Composite 2 scale (CC2); secondary endpoints included MMSE and CDR-Sob. Findings: Of the 48 participants randomized, 9 discontinued, primarily due to unrelated clinical deterioration; 39 had complete ceruloplasmin data. Two serious adverse events occurred in the Placebo group. Mild gastrointestinal symptoms occurred in eight participants, with only four leading to dropout. In the primary zinc vs. placebo analysis, no significant differences emerged in cognitive outcomes. A post hoc exploratory analysis stratified participants by pharmacodynamic response: 12 individuals with MCI due to AD (31%) met the criteria for “Zinc Responder,” defined by ≥20% reduction in serum ceruloplasmin at week 12. Only Zinc Responders maintained cognitive stability over 24 weeks, whereas the combined group of Zinc Non-Responders and placebo-treated participants showed a significant decline. For the composite cognitive score (CC2), the interaction between visit and response group was significant (p = 0.030), with deterioration observed only in the Non-Responder + Placebo group (Δ = –2.72, p < 0.0001 vs. –0.71, p = 0.35 in Responders). Similar patterns were observed for CDR-Sob (interaction p = 0.017) and MMSE (trend p = 0.09). Interpretation: Zinc therapy stabilized cognition in a pharmacodynamically defined MCI subgroup. These exploratory findings suggest serum ceruloplasmin as a feasible biomarker of target engagement. Larger trials are needed for confirmation. Full article