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Background: Elderly individuals represent one of the populations most affected by COVID-19, exhibiting high vulnerability to malnutrition, sarcopenia, and poor clinical outcomes. The association between nutritional status and disease progression highlights the need for standardized assessment and targeted nutritional interventions. Methods: A systematic review was performed using PubMed, Cochrane Library, and Google Scholar, covering studies published between January 2020 and October 2025. The review followed PRISMA guidelines and included studies evaluating nutritional status, screening tools, and nutritional support strategies for the elderly population (≥65 years old) with COVID-19 across inpatient, outpatient, and institutional care settings. Results: A total of seven studies met the inclusion criteria. Reported malnutrition prevalence ranged from 25% to 65%, increasing with both age and COVID-19 severity. The most frequently applied tools were the Mini Nutritional Assessment–Short Form (MNA-SF), the Global Leadership Initiative on Malnutrition (GLIM) criteria, and the Geriatric Nutritional Risk Index (GNRI). New evidence supports early nutritional screening, high-protein supplementation, and individualized dietary strategies to reduce complications and improve recovery trajectories. Conclusions: Nutritional risk screening and timely intervention are essential in the management of elderly patients with COVID-19. Standardized assessment tools and multidisciplinary nutrition approaches enhance clinical outcomes, minimize disease burden, and should remain integral components of geriatric care in infectious and post-pandemic contexts. Full article

Microplastics are very small particles of plastics, usually smaller than 5 mm. Microplastic pollution has emerged as a rising and challenging issue worldwide, posing serious threats to aquatic and terrestrial ecosystems and human health. Because of global demand and frequent use in daily routines, including clothing, packaging, and household items, the production of plastic is increasing annually. This study provides a comprehensive overview of the source, classification (based on shape, color, polymer), transportation, and impact of microplastic pollution. Depending upon size, mass, and density, microplastics can be transported to the environment via air and water. However, microplastics can be inhaled and ingested by humans, causing various health issues; for example, aquatic organisms like small fish ingest microplastics, which accumulate through the food chain and end up in the human body. This can lead to physiological harm, including inflammation, digestion tract obstruction, biomagnification throughout the food chain, and reproductive failure. This study further highlighted initiatives taken by government agencies to address plastic and microplastic pollution across India; for example, The Ministry of Environment Forest and Climate Change (MoEFCC) has formulated and amended the Plastic Waste Management (PWM) rules, Mission LiFE (LiFEStyle for Environment) launched campaigns such as “Say No to Single Use Plastic” and “One Nation, One Mission: End Plastic Pollution” to create awareness at the grassroot level, and institutions like the Food Safety and Standards Authority of India (FSSAI) have initiated a project to detect microplastics in food products. In addition, the National Green Tribunal (NGT) has instructed the Central Pollution Control Board (CPCB) to actively take measures to address microplastic pollution across Indian cities, focusing on key parameters like air, water, food, and humans. This study presents several recommendations, including detection and removal techniques (conventional, advanced, and removal); strengthening legislative policies such as Extended Producer Responsibility (EPR); research collaboration and monitoring with institutions such as CSIR-IITR, ICAR-CIFT, and BITS-Pilani; integrating EPR and Material Recovery Facilities (MRF) to develop a circular economy model; and mass awareness through government initiatives like the Swachh Bharat and Smart City programs to foster long-term behavioral change. Full article

Palladium, a non-toxic platinum-group metal, is widely used in catalysis, electronics, hydrogen storage, and chemical industries because of its excellent physical and chemical properties. However, given that the number of palladium-producing countries is limited, recycling is considered essential for ensuring a stable and sustainable global supply. Here, I describe a simple and efficient method for palladium recovery from electronic waste (e-waste) using Enterobacter oligotrophicus CCA6^T. To clarify biomineralization capacity, the role of electron donors in modulating biomineralization capacity was examined. Findings showed that formic acid was the most effective donor, enhancing the relative recovery rate to 44% compared to 23% without electron donors. Transmission electron microscopy analysis revealed palladium particles (1–10 nm) distributed across the cell wall, periplasmic space and cytoplasm, confirming active biomineralization rather than passive biosorption. Moreover, based on a comparison with the biomineralization mechanism of Escherichia coli, the biomineralization mechanism of E. oligotrophicus CCA6^T was estimated . Reaction parameters were then optimized by testing the effects of formic acid concentration, reaction temperature, and reaction pH. Under optimized conditions, the relative recovery rate exceeded 99% within 6 h using 40 mg/L palladium. When this method was applied to a metal dissolution solution prepared from e-waste , a recovery rate of 94% was achieved from trace concentrations (36 µg/L), and palladium loss from bacteria after the palladium recovery test was negligible (<0.01%). Taken together, these results demonstrate that biomineralization using E. oligotrophicus CCA6^T could potentially be applied to the recovery of palladium from e-waste, particularly for trace-level concentrations where conventional methods are ineffective. Full article

With the acceleration of global climate change and urbanization, urban flooding disasters have become increasingly frequent, posing significant threats to urban safety and sustainable development. Enhancing Urban Flood Resilience (UFR) has become a central issue in urban risk management and spatial planning. This study aims to scientifically assess UFR by employing the core concepts of resistance, recovery, and adaptation from urban resilience theory. A set of 20 indicators for assessing UFR is selected from four aspects: infrastructure, social economy, technological monitoring, and the ecological environment. Addressing the limitations of traditional evaluation methods, which struggle to effectively handle data gaps and ambiguous boundaries, and fail to balance subjective and objective weights, this study introduces the unascertained measure theory and adopts a combined weighting method to construct a UFR evaluation model. Using 2023 statistical data from Jiangxi Province, a comprehensive evaluation of flood resilience was conducted across 11 prefecture-level cities within the province. The analysis indicates that, among level-2 indicators, infrastructure holds the highest weight at 43.7%. Regarding resilience dimensions, resistance dominates with a weight of 54.6%. Furthermore, significant spatial disparities exist in flood resilience levels across Jiangxi Province: high resilience cities are distributed in central and northern Jiangxi, moderately high resilience cities account for the largest proportion. Only one city, Pingxiang, exhibits moderate resilience. Full article

Following the World Health Organization’s 2023 declaration, which ended the global health emergency, energy policy shifted from a short-term crisis response to a structural recovery focused on renewable energy. However, the current literature remains fragmented, often overlooking the realities of implementation in the Global South and failing to integrate diverse policy instruments. This study examines post-pandemic renewable recovery strategies to categorize instruments, evaluate effectiveness, and identify critical implementation gaps. An integrative review was conducted, combining bibliometric mapping of 113 documents (n = 113) and systematic thematic synthesis of 42 studies (n = 42), utilizing the SPIDER and PRISMA protocols. Policy instruments were classified into five groups: Recovery (REC), Fiscal/Financial (FISC), Regulatory (REG), Energy Efficiency (EE), and Social and Information (SOC), revealing a “Global North-South Asymmetry”, where advanced economies leverage fiscal–regulatory coupling while emerging markets face administrative bottlenecks. Findings identify coordination failures, such as missequencing, and propose a “Cascading Policy Logic” that prioritizes de-risking before mandatory standardization. This research bridges the evidence gap by validating the need for informal sector mechanisms and equity safeguards in developing nations. Ultimately, this review provides a strategic framework for policymakers to transition from a reactive stimulus to durable, socially legitimate decarbonization pathways beyond 2025. Full article

The dual imperative of mitigating carbon emissions and maximizing hydrocarbon recovery has amplified global interest in carbon capture, utilization, and storage (CCUS) technologies. These integrated processes hold significant promise for achieving net-zero targets while extending the productive life of mature oil reservoirs. However, their effectiveness hinges on a nuanced understanding of the complex interactions between geological formations, reservoir characteristics, and injection strategies. In this study, a comprehensive machine learning-based framework is presented for estimating CO₂ storage capacity and enhanced oil recovery (EOR) performance simultaneously in subsurface reservoirs. The methodology combines simulation-driven uncertainty quantification with supervised machine learning to develop predictive surrogate models. Simulation results were used to generate a diverse dataset of reservoir and operational parameters, which served as inputs for training and testing three machine learning models: Random Forest, Extreme Gradient Boosting (XGBoost), and Artificial Neural Networks (ANN). The models were trained to predict three key performance indicators (KPIs): cumulative oil production (bbl), oil recovery factor (%), and CO₂ sequestration volume (SCF). All three models exhibited exceptional predictive accuracy, achieving coefficients of determination (R²) greater than 0.999 across both training and testing datasets for all KPIs. Specifically, the Random Forest and XGBoost models consistently outperformed the ANN model in terms of generalization, particularly for CO₂ sequestration volume predictions. These results underscore the robustness and reliability of machine learning models for evaluating and forecasting the performance of CO₂-EOR and sequestration strategies. To enhance model interpretability and support decision-making, SHapley Additive exPlanations (SHAP) analysis was applied. SHAP, grounded in cooperative game theory, offers a model-agnostic approach to feature attribution by assigning an importance value to each input parameter for a given prediction. The SHAP results provided transparent and quantifiable insights into how geological and operational features such as porosity, injection rate, water production rate, pressure, etc., affect key output metrics. Overall, this study demonstrates that integrating machine learning with domain-specific simulation data offers a scalable approach for optimizing CCUS operations. The insights derived from the predictive models and SHAP analysis can inform strategic planning, reduce operational uncertainty, and support more sustainable oilfield development practices. Full article

To address the challenges of decarbonization in the global transportation sector and disposal of waste tires, warm asphalt rubber (WAR) with low viscosity and high performance was prepared. In particular, the preparation and rheological behavior of WAR incorporating composite warm mix systems at relatively high crumb rubber contents have not been thoroughly documented. In this study, WAR prepared under such conditions was systematically examined. A five-factor, three-level segmented orthogonal experimental design (OED) was employed to investigate the effects of preparation parameters on hot mix asphalt rubber (AR) properties. Based on the optimized AR formulation, a composite warm mix system combining Ultra-Warm Mix additive (UWM) and Sasobit was developed, and control groups containing 5% UWM only and 1.5% Sasobit only were prepared for comparison. Conventional physical tests together with rheological characterization, including Dynamic Shear Rheometer (DSR), Multiple Stress Creep Recovery (MSCR), and Bending Beam Rheometer (BBR) tests, were conducted to evaluate the high- and low-temperature performance of WAR. Results show that the optimal preparation process consisted of aromatic oil content 5%, crumb rubber content 30%, shear temperature 220 °C, shear time 120 min, and reaction time 90 min. The composite warm mix system notably enhanced WAR performance, with the WAR-5U1.5S group exhibiting the most balanced properties. A marked reduction in rotational viscosity was achieved while maintaining a stable softening point, and satisfactory ductility and elastic recovery were also retained. DSR and MSCR tests confirmed improved high-temperature deformation resistance, an increase in percent recovery R, and a decrease in non-recoverable creep compliance J_nr. BBR test further verified that the composite system maintained good low-temperature cracking resistance, meeting all specification requirements. Overall, these results indicate that, compared with the optimized AR, WAR can reduce mixing viscosity without sacrificing rutting or cracking performance, while alleviating the limitations observed for single warm mix additives. This study provides essential technical support for promoting WAR that integrates low-carbon construction with superior pavement performance. Full article

In recent years, extreme climate events such as high temperatures and droughts have become increasingly frequent and intense, posing significant threats to the carbon sink stability of C₃, C₄, and CAM plants. As a result, identifying photosynthetic strategies that balance adaptability with resilience has emerged as a critical focus in carbon sink research. C₂ photosynthesis offers a promising solution by recycling photorespiratory CO₂ through the glycine shuttle between mesophyll cells (MCs) and bundle sheath cells (BSCs), thereby optimizing carbon concentration and recovery without additional ATP expenditure, thus minimizing carbon loss. This review provides a comprehensive analysis of the diversity, distribution, evolutionary status, and regulatory mechanisms of C₂ photosynthesis, emphasizing its physiological and ecological resilience in carbon sequestration. In comparison to C₃ and C₄ pathways, C₂ photosynthesis demonstrates distinct carbon sink resilience, positioning it as a vital strategy for addressing both current and future global climate challenges. The review also highlights existing gaps in C₂ research, particularly in species identification, molecular mechanisms, and ecological studies, and recommends prioritizing these areas to fully harness its potential for enhancing climate resilience. Full article

The depletion of natural resources remains a major global challenge, emphasizing the need to develop sustainable processes that enable both metal recovery and waste recycling. This study investigates the leaching of valuable metals from lead smelting slag using methanesulfonic acid (MSA), a biodegradable and environmentally benign reagent. Batch experiments were performed under different MSA concentrations (0.35–1.4 M) and temperatures (22–80 °C). Metal dissolution increased nearly linearly with acid concentration up to 1 M, with maximum recoveries after 60 min of 85% Zn, 64% Pb, 75% Cu, and 68% Fe. Copper dissolution was governed by the oxidation of Cu₂S, while Fe leaching was affected by pH variations that promoted re-precipitation. Kinetic modeling indicated mixed chemical–diffusion control mechanisms, with activation energies of 22.6 kJ mol⁻¹ for Zn and 31–33 kJ mol⁻¹ for Pb, Cu, and Fe. Beyond efficient metal extraction, the process generated a leach residue with reduced concentrations of base metals and a mineralogical composition dominated by stable calcium-silicate phases, improving its potential suitability for reuse in construction or mining backfill applications. Overall, methanesulfonic acid proved to be an effective and sustainable lixiviant, combining high metal recovery with the generation of recyclable slag, thereby contributing to circular metallurgical practices. Full article

Phosphate is a crucial non-renewable mineral resource, mainly utilized in producing fertilizers that support global agriculture. As phosphorus is an indispensable nutrient for plant growth, phosphate holds a key position in ensuring food security. While deposits are distributed worldwide, the largest reserves are concentrated in Morocco. The Benguerir phosphate mining in Morocco generates heterogeneous waste (i.e., including overburden, tailings, and phosphogypsum) that complicates management and valorization, which is the beneficial reuse or value recovery from waste materials (e.g., use in cover systems, buffering, or other engineered applications). Therefore, it is essential to characterize their mineralogical properties to evaluate their environmental impact and possibilities for reuse or site revegetation. To do so, we integrate VNIR–SWIR reflectance spectroscopy with HandHeld X-ray fluorescence (HHXRF) to characterize phosphate waste rock and assess its reuse potential. For this purpose, field samples (n = 104) were collected, and their spectral reflectance was measured using an ASD FieldSpec 4 spectroradiometer (350–2500 nm) under standardized laboratory conditions. Spectra were processed (Savitzky–Golay smoothing, convex-hull continuum removal) and matched to ECOSTRESS library references; across the dataset, library matching achieved mean RMSE = 0.15 ± 0.053 (median 0.145; 0.085–0.350), median SAM = 0.134 rad, median SID = 0.029, and mean R² = 0.748 ± 0.170, with 84% of spectra yielding R² > 0.70. In parallel, HHXRF major and trace elements were measured on all samples to corroborate spectral interpretations. Together, these analyses resolve carbonate–clay–phosphate assemblages (dolomite commonly dominant, with illite/smectite–kaolinite, quartz, and residual carbonate-fluorapatite varying across samples). Elemental ratios (e.g., Mg/Ca distinguishing dolomite from calcite; K/Al indicating illite) reinforce spectral trends, and phosphate indicators delineate localized enrichment (P₂O₅ up to 23.86 wt % in apatite-rich samples). Overall, the combined workflow is rapid, low-impact, and reproducible, yielding coherent mineralogical patterns that align across spectroscopic and geochemical lines of evidence and providing actionable inputs for selective screening, targeted material reuse, and more sustainable mine reclamation planning. Full article

Invasive species are a recurring global problem, and the water hyacinth (Pontederia crassipes) is a well-known example. Various strategies have been explored to manage its spread, including its use as an agricultural amendment. However, when P. crassipes biomass is incorporated into soil and undergoes degradation, it may increase soil conductivity and promote metal leaching, potentially affecting soil biota, particularly microbiota. Saprophytic fungi play a key role in the decomposition and renewal of organic matter, and their resilience to stressors is crucial for maintaining soil function. Thus, the aim of this study was to evaluate the effects of P. crassipes biomass extracts on the saprophytic fungus Trametes versicolor by evaluating fungal growth and metabolic changes [including sugar content, phosphatase enzymatic activity, and reactive oxygen species (ROS) production]. The fungus was exposed for 8 days to a dilution series of extracts (100%—undiluted, to 3.13%) prepared from P. crassipes biomass collected at five locations in Portuguese wetlands. Two sites were in the south, within a Mediterranean climate (Sorraia and Estação Experimental António Teixeira), and three were in the north, within an Atlantic climate (São João de Loure, Pateira de Fermentelos, and Vila Valente), representing both agricultural-runoff–impacted areas and recreational zones. Extracts were used to simulate a worst-case scenario. All extracts have shown high conductivity (≥15.4 mS/cm), and several elements have shown a high soluble fraction (e.g., K, P, As, or Ba), indicating substantial leaching from the biomass to the extracts. Despite this, T. versicolor growth rates were generally not inhibited, except for exposure to the São João de Loure extract, where an EC₅₀ of 45.3% (extract dilution) was determined and a significant sugar content decrease was observed at extract concentrations ≥25%. Possibly due to the high phosphorous leachability, both acid and alkaline phosphatase activities increased significantly at the highest percentages tested (50% and 100%). Furthermore, ROS levels increased with increasing extract concentrations, yet marginal changes were observed in growth rates, suggesting that T. versicolor may efficiently regulate its intracellular redox balance under stress conditions. Overall, these findings indicate that the degradation of P. crassipes biomass in soils, while altering chemical properties and releasing soluble elements, may not impair and could even boost microbiota, namely saprophytic fungi. This resilience highlights the potential ecological benefit of saprophytic fungi in accelerating the decomposition of invasive plant residues and contribution to soil nutrient cycling and ecosystem recovery. Full article

End-of-life wind turbine blade accumulation is a growing global materials management problem and current industrial recycling routes for glass fiber-reinforced polymer composites remain limited in material recovery value. There is limited understanding on how to recover clean glass fibers while keeping thermal exposure and energy input low, and existing studies have not quantified whether very short isothermal thermal residence can still result in complete matrix removal. The hypothesis of this study is that a mild two-step thermochemical sequence can recover clean glass fibers at lower temperature and near zero isothermal dwell if pyrolysis and oxidation are separated. We used wind-blade epoxy-based GFRP in a step-batch reactor and combined TGA-based thermodynamic mapping, short pyrolysis at 425 °C, and mild oxidation at 475 °C with controlled dwell from zero to thirty minutes. We applied model-free kinetics and machine learning methods to quantify activation energy trends as a function of conversion. The thermal treatment of 425 °C for zero minutes in nitrogen, followed by 475 °C for fifteen minutes in air, resulted in mechanically sound, visually clean white fibers. These fibers retained 76% of the original tensile strength and 88% of the Young’s modulus, which indicates the potential for energy-efficient GFRP recycling. The activation energy was found to be approximately 120 to 180 kJ mol⁻¹. These findings demonstrate energy lean recycling potential for GFRP and can inform future industrial scale thermochemical designs. Full article

Rising temperatures are among the most predictable outcomes of climate change, and cacti are particularly vulnerable at the germination stage. We tested seeds of ten Cuban Leptocereus species from coastal and inland habitats under five temperature regimes to evaluate germination responses, thermal buffering capacity for optimal germination, photoblastic behavior, recovery after heat stress, and seedling vigor. Germination declined sharply with increasing temperature, revealing minimal thermal buffering capacity for optimal germination. All species exhibited positively photoblastic seeds, while recovery and the degree of physiological dormancy varied among taxa. Except for one taxon, most displayed partial dormancy that could stagger germination over time. Seedling vigor was not affected by high temperatures in the same way in all species. Overall, our findings suggest that climate warming will further constrain the germination niche of Leptocereus, underscoring the importance of conservation measures such as ex situ propagation. Full article

Thermoelectric systems configured in multistring arrays of thermoelectric generators (TEGs) represent a promising solution for energy harvesting in environments with non-uniform thermal gradients. However, the presence of multiple maximum power points (MPPs) in such configurations poses significant challenges to energy extraction efficiency. This study presents a comprehensive performance evaluation of four maximum power point tracking (MPPT) algorithms, Perturb and Observe (P&O), Incremental Conductance (InC), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), applied to multistring thermoelectric generator (TEG) arrays under multiple and asymmetric thermal gradients. The simulated systems, modeled in MATLAB/Simulink, replicate real-world thermoelectric configurations by employing series-parallel topologies and eleven distinct thermal scenarios, including uniform, localized, and sinusoidal temperature distributions. The key contribution of this work lies in demonstrating the superior capability of metaheuristic algorithms (PSO and GA) to locate the global maximum power point (GMPP) in complex thermal environments, outperforming classical methods (P&O and InC), which consistently converged to local maxima under multi-peak conditions. Notably, PSO achieved the best average convergence time (0.23 s), while the GA recorded the fastest response (0.05 s) in the most challenging multi-peak scenarios. Both maintained high tracking accuracy (error ≈ 0.01%) and minimized power ripple, resulting in conversion efficiencies exceeding 97%. The study emphasizes the crucial role of algorithm selection in maximizing energy harvesting performance in practical TEG applications such as embedded systems, waste heat recovery, and autonomous sensor networks. Future directions include physical validation through prototypes, incorporation of dynamic thermal modeling, and development of hybrid or AI-enhanced MPPT strategies. Full article

Sandstone-hosted uranium deposits represent one of the most critical global uranium resources suitable for in situ recovery, with their formation closely associated with organic matter (OM). We conducted a systematic literature review to synthesize over 100 published studies sourced from authoritative databases (Elsevier, Google Scholar, Web of Science, Scopus, CNKI, etc.). This study systematically summarizes the types and geological characteristics of OM in sandstone reservoirs and thoroughly analyzes the geochemical mechanisms by which OM regulates the transport and precipitation of aqueous uranium. By integrating case studies of representative sandstone uranium deposits globally, three major OM-related metallogenic models are proposed with distinct core characteristics: the humic-dominated model is driven by the complexation and direct reduction of uranium by humic substances/coal-derived OM; the roll-front model relies on reactions between oxidized uranium-bearing fluids and scattered OM, as well as microbially generated sulfides at the migration front; and the seepage-related model is fueled by upward-migrating deep hydrocarbon fluids (petroleum, methane) that act as both uranium carriers and reductants. Furthermore, this review explores the spatial coupling relationships between OM distribution and uranium mineralization in typical geological settings, evaluates the guiding significance of OM for uranium exploration, and outlines key unresolved scientific issues. The findings refine the genetic theoretical framework of sandstone-hosted uranium deposits and provide important technical support and theoretical guidance for future uranium exploration deployment and resource potential evaluation. Full article