Search Results (70,063)

L. ferrooxidans and their metabolic products have been explored as viable flotation reagents of pyrite and chalcopyrite for froth flotation. Scanning electron microscopy (SEM), near edge X-ray absorption fine structure (NEXAFS) spectroscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS) and captive bubble contact angle measurements have been used to examine the surface physicochemical properties of pyrite upon exposure to L. ferrooxidans grown in HH medium at pH 1.8. C K-edge NEXAFS spectra, collected using scanning transmission X-ray microscopy (STXM), indicate hydrophilic lipids, fatty acids, and biopolymers are formed at the mineral–bacterium interface within hours of exposure. The Fe L-edge NEXAFS show oxidation of the mineral surface from Fe (II) sulfide to Fe (III) oxyhydroxides. The leaching of the iron species at the pyrite surface is accelerated in the presence of L. ferrooxidans and extracellular polymeric substances (EPS) as compared to HH medium controls, as shown by ToF-SIMS. The surface chemical changes induced by the interaction with L. ferrooxidans show a significant decrease in surface hydrophobicity within the first 2 h of exposure. The implications of these findings are the potential use of EPS, produced during early attachment of L. ferrooxidans, as a depressant for bioflotation or to enhance bioleaching. Full article

State-of-charge (SoC) balancing across multiple battery energy storage systems (BESS) is a central challenge in renewable-rich mini-grids. Heterogeneous battery capacities, differing states of health, stochastic renewable generation, and variable loads create a high-dimensional uncertain control problem. Conventional droop-based SoC balancing strategies are decentralized and computationally light but fundamentally reactive and limited, whereas model predictive control (MPC) is insightful but computationally intensive and prone to modeling errors. This paper proposes a Hierarchical Predictive–Adaptive Control (HPAC) framework for SoC balancing in mini-grids using deep reinforcement learning. The framework consists of two synergistic layers operating on different time scales. A long-horizon Predictive Engine, implemented as a federated Transformer network, provides multi-horizon probabilistic forecasts of net load, enabling multiple mini-grids to collaboratively train a high-capacity model without sharing raw data. A fast-timescale Adaptive Controller, implemented as a Soft Actor-Critic (SAC) agent, uses these forecasts to make real-time charge/discharge decisions for each BESS unit. The forecasts are used both to augment the agent’s state representation and to dynamically shape a multi-objective reward function that balances SoC, economic performance, degradation-aware operation, and voltage stability. The paper formulates SoC balancing as a Markov decision process, details the SAC-based control architecture, and presents a comprehensive evaluation using a MATLAB-(R2025a)-based digital-twin simulation environment. A rigorous benchmarking study compares HPAC against fourteen representative controllers spanning rule-based, MPC, and various DRL paradigms. Sensitivity analysis on reward weight selection and ablation studies isolating the contributions of forecasting and dynamic reward shaping are conducted. Stress-test scenarios, including high-volatility net-load conditions and communication impairments, demonstrate the robustness of the approach. Results show that HPAC achieves near-minimal operating cost with essentially zero SoC variance and the lowest voltage variance among all compared controllers, while maintaining moderate energy throughput that implicitly preserves battery lifetime. Finally, the paper discusses a pathway from simulation to hardware-in-the-loop testing and a cloud-edge deployment architecture for practical, real-time deployment in real-world mini-grids. Full article

In this study, a comprehensive analysis of the fixed/preassigned-time synchronization of a class of quaternion-valued BAM (QBAM) neural networks with stochastic and impulsive effects is conducted. Unlike previous analysis methods, our method features a direct analysis approach. First, to clarify the combined impact of impulsive and stochastic phenomena on synchronization behavior, we establish a QBAM neural network system incorporating stochastic and impulsive effects. Notably, differing from prior relevant studies, we assume that the activation function is discontinuous, thereby enhancing the practical relevance of this research. Second, leveraging the quaternion-valued sign function and its properties, we implement impulsive control via the direct analysis method to achieve Fixed/Predefined-Time synchronization of the considered system. Finally, numerical simulations are performed to verify the ability of the theoretical analysis and the proposed control protocol to realize synchronization under impulsive and stochastic effects. Full article

Background: Childhood obesity continues to pose a major global health challenge, and schools offer a structured and scalable setting for implementing physical activity programs. However, the effectiveness of these interventions remains inconsistent. This systematic review synthesizes evidence from school-based physical activity interventions and evaluates their impact on obesity-related parameters, physical activity levels, physical fitness, and cardiorespiratory fitness among children. Methods: A comprehensive search of PubMed, Scopus, and the Cochrane Library identified randomized controlled trials published between January 2015 and March 2025. Eligible studies included children aged 5–18 years and assessed school-based physical activity interventions. Outcomes included BMI, body fat percentage, physical activity levels (including MVPA), physical fitness, and cardiorespiratory fitness. Due to methodological heterogeneity, a narrative synthesis was conducted. Results: A total of 28 studies met inclusion criteria. Among the 16 studies reporting obesity-related outcomes, 7 demonstrated statistically significant improvements in BMI or BMI z-scores, while 6 of 16 (37.5%) showed no measurable effect. Reductions in body fat percentage were more consistently observed (5 of 6 studies). Both short-term (<6 months) and long-term (>12 months) interventions showed comparable proportions of studies with statistically significant BMI improvements (~50%). For physical activity outcomes, 5 of 11 studies reported increased MVPA, whereas others showed no significant change. Sedentary behavior outcomes were mixed, with only 2 of 6 studies demonstrating significant reductions. Improvements in physical fitness were reported in two-thirds of studies, while cardiorespiratory fitness improvements were inconsistent, with significant gains observed primarily in higher-intensity or well-structured programs. Across outcomes, several findings were statistically significant but modest in clinical magnitude. Conclusions: School-based physical activity interventions have the potential to improve select obesity-related parameters, particularly body fat percentage and BMI in a subset of studies. However, effects on MVPA, sedentary time, overall activity levels, and cardiorespiratory fitness remain variable. The effectiveness of these programs appears influenced by intervention structure, intensity, and adherence rather than duration alone. Future interventions should incorporate tailored, multi-component approaches to enhance both clinical relevance and long-term sustainability. While several effects were statistically significant, most were modest in magnitude. However, even modest improvements in BMI z-score, body fat percentage, and fitness can be meaningful at a population level, particularly when delivered through universal, scalable school platforms that reach large numbers of children. Full article

Globally, lakes are increasingly recognized as sensitive indicators of climate change and ecosystem stress. Qaraoun Lake, Lebanon’s largest artificial reservoir, is a critical resource for irrigation, hydropower generation, and domestic water supply. Over the past 25 years, satellite remote sensing has enabled consistent monitoring of its hydrological and environmental dynamics. This study leverages the advanced cloud-based processing capabilities of Google Earth Engine (GEE) to analyze over 180 cloud-free scenes from Landsat 7 (Enhanced Thematic Mapper Plus) (ETM+) from 2000 to present, Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) from 2013 to present, and Landsat 9 OLI-2/TIRS-2 from 2021 to present, quantifying changes in lake surface area, water volume, and pollution levels. Water extent was delineated using the Modified Normalized Difference Water Index (MNDWI), enhanced through pansharpening to improve spatial resolution from 30 m to 15 m. Water quality was evaluated using a composite pollution index that integrates three spectral indicators—the Normalized Difference Chlorophyll Index (NDCI), the Floating Algae Index (FAI), and a normalized Shortwave Infrared (SWIR) band—which serves as a proxy for turbidity and organic matter. This index was further standardized against a conservative Normalized Difference Vegetation Index (NDVI) threshold to reduce vegetation interference. The resulting index ranges from near-zero (minimal pollution) to values exceeding 1.0 (severe pollution), with higher values indicating elevated chlorophyll concentrations, surface reflectance anomalies, and suspended particulate matter. Results indicate a significant decline in mean annual water volume, from a peak of 174.07 million m³ in 2003 to a low of 106.62 million m³ in 2025 (until mid-November). Concurrently, pollution levels increased markedly, with the average index rising from 0.0028 in 2000 to a peak of 0.2465 in 2024. Episodic spikes exceeding 1.0 were detected in 2005, 2016, and 2024, corresponding to documented contamination events. These findings were validated against multiple institutional and international reports, confirming the reliability and efficiency of the GEE-based methodology. Time-series visualizations generated through GEE underscore a dual deterioration, both hydrological and qualitative, highlighting the lake’s growing vulnerability to anthropogenic pressures and climate variability. The study emphasizes the urgent need for integrated watershed management, pollution control measures, and long-term environmental monitoring to safeguard Lebanon’s water security and ecological resilience. Full article

The mass rearing of natural enemy insects is a cornerstone of effective green pest control, making the development of optimized artificial diets critical for sustaining large populations. However, existing artificial diets often have limitations, including inhibitory effects on the reproductive development of natural enemies. In this study, we innovatively incorporated 20% catalpol into the artificial diets for Harmonia axyridis, aiming to comprehensively assess the effects of such dietary regimens on larval development, reproductive performance, and the regulation of energy metabolism in H. axyridis. Our results demonstrated that catalpol supplementation significantly shortened the duration of the 4th instar larval and pupal stages and increased pupal weight. Furthermore, catalpol treatment enhanced reproductive capacity, as evidenced by increased fecundity, improved hatching rate stability, and enhanced ovarian development. This effect was directly correlated with the significant upregulation of the vitellogenin genes Vg1 and Vg2 and their receptor gene VgR at 3 days post-emergence. Regarding energy metabolism, catalpol supplementation led to increased glycogen reserves and glucose content. The expression of the membrane-bound trehalase enzyme gene TRE2 was significantly higher than that in the control group, and the expression level of the soluble trehalase enzyme gene TRE1 also showed a significant increase. These findings indicate that catalpol effectively optimized energy metabolism, thereby accelerating developmental processes and enhancing reproductive capacity. In this study, we elucidated the mechanism by which catalpol regulates physiological metabolism in predatory natural enemy insects. For the first time, catalpol was incorporated into the artificial diet of H. axyridis as a synergistic component, significantly enhancing its growth, reproductive capacity, and energy metabolism. These findings provide a scientific basis for developing efficient artificial feeding systems and improving the field adaptability of natural enemy insects. Full article

Managing complex and large-scale building facilities requires reliable, easily interpretable, and computationally efficient models. Considering the electrical-circuit analogy, lumped-parameter resistance–capacitance (RC) thermal models have emerged as both simulation surrogates and advanced tools for energy management. This review synthesizes recent uses of RC models for building energy management in large facilities and aggregates. A systematic review of the most recent international literature, based on the analysis of 70 peer-reviewed articles, led to the classification of three main areas: (i) the physics and modeling potential of RC models; (ii) the methods for automation, calibration, and scalability; and (iii) applications in model predictive control (MPC), energy flexibility, and digital twins (DTs). The results show that these models achieve an efficient balance between accuracy and simplicity, allowing for real-time deployment in embedded control systems and building-automation platforms. In complex and large-scale situations, a growing integration with machine learning (ML) techniques, semantic frameworks, and stochastic methods within virtual environments is evident. Nonetheless, challenges persist regarding the standardization of performance metrics, input data quality, and real-scale validation. This review provides essential and up-to-date guidance for developing interoperable solutions for complex building energy systems, supporting integrated management across district, urban, and community levels for the future. Full article

Tuberculosis is still one of the leading infectious causes of morbidity and mortality worldwide. Rapid diagnosis is essential for effective treatment and control of tuberculosis transmission. In recent years, nucleic acid amplification tests (NAATs), such as GeneXpert MTB/RIF, BD MAX™, Xpert MTB/RIF-Ultra, have significantly improved tuberculosis diagnostics. However, they mainly require expensive and advanced equipment. The aim of our study was to assess the usefulness of the novel RITA MTBC assay in this diagnostic context. A total of 61 clinical specimens were tested using the RITA MTBC assay in comparison with established molecular diagnostic platforms (GeneXpert and BD MAX™), used as molecular reference assays. Culture and microscopy were performed as part of initial clinical assessment, but the comparative analysis focused on molecular assays to provide a relevant evaluation of diagnostic performance. Among 31 samples previously identified as positive for M. tuberculosis DNA, the assay correctly detected 30 (LOT HPA01/20230601) and 29 (LOT HPA01/20230602). Of 30 negative samples, 28 and 30 were confirmed negative for the respective lots. These results correspond to an average sensitivity of 95% and an average specificity of 97%. The kit demonstrated diagnostic performance that meets requirements for molecular testing in tuberculosis, with sensitivity and specificity comparable to established platforms, although further validation on larger sample sets is necessary. Nevertheless, its excellent specificity, rapid turnaround time, and operational simplicity, make it especially well-suited for decentralized or resource-limited settings. These findings underscore the potential of RITA MTBC as a valuable diagnostic tool in both routine clinical settings and in populations with limited access to healthcare. Full article

Deep Reactive Ion Etching (DRIE), as a key process in silicon micromachining, remains constrained in high-precision applications by sidewall angle deviation and aspect ratio limitations. This study systematically investigates the mapping relationship between process parameters and etching morphology, focusing on the following aspects: the influence mechanism of C₄F₈ passivation time and bottom RF power on sidewall perpendicularity; and the effect patterns of etch cycle count, single-step time, and bottom RF power on aspect ratio and top–bottom line width (CD) difference. The findings reveal that dynamic adjustment of bottom RF power significantly influences sidewall angle: incremental adjustment tends to cause sharp angles (decreased angular precision), while decremental adjustment tends to form obtuse angles. Simply increasing the cycle count leads to a bottleneck in etch depth growth. Combining incremental bottom RF power adjustment can overcome depth limitations but induces axial variation in aperture dimensions. Optimizing the passivation-to-etch time ratio effectively controls etch morphology characteristics. This study achieved an etch depth of 112.2 μm for a 5 μm wide trench with an overall aperture size difference of 0.279 μm, providing a theoretical basis and practical guidance for parameter optimization in DRIE processes for high-precision silicon structure fabrication. Full article

Direct agricultural use of digestate from food waste is hindered by its high phytotoxicity, and the addition of common auxiliary materials during composting increases the project cost. In this study, mature compost (MC) was used to replace part of mushroom residue as auxiliary materials for controlled experiments at a pilot-scale horizontal double-layer mechanical composting device. The results showed that the MC addition heated up more rapidly than the control group (NC), peaking at 72 °C on day 5. The moisture content was reduced from 47.17% to 25.36%, which was lower than the final value of 28.48% in the NC. The final humic acid (HA) content in the MC group (60.88 g/kg) was higher than that in the NC (44.82 g/kg). The seed germination index (GI) for both groups exceeded 70%, meeting the national standard. The MC group achieved a final GI of 119.37%, which was significantly higher than that of the NC (81.29%). The phylum Firmicutes became the dominant group in the MC group during the thermophilic phase, demonstrating strong thermotolerance and a high capacity for degrading recalcitrant organic compounds such as cellulose. At the genus level, Bacillus demonstrated a relatively high abundance during the thermophilic phase. These findings imply that the MC addition improves the composting property, enhances the degree of humification, and shortens the composting time, providing technical support for the improvement of aerobic composting of food waste digestate, thus contributing to more sustainable waste management by promoting a circular economy and reducing reliance on external inputs. Full article

In the mission scenario of On-Orbit Assembly (OOA), servicing spacecraft are frequently tasked with towing large-scale, flexible truss structures to designated assembly sites. This process involves complex coupled dynamics between the spacecraft and the flexible payload, which are often unmodeled or unknown, posing significant challenges to control precision. Furthermore, the proximity of other assembled structures in the construction area necessitates strict collision avoidance. To address these challenges, this paper proposes a novel adaptive robust controller for spacecraft thruster-based orbital control that integrates Prescribed Performance Control (PPC) with a Radial Basis Function Neural Network (RBFNN). The PPC framework ensures that the position tracking errors remain within user-predefined, time-varying boundaries, providing an intrinsic mechanism for collision avoidance during the towing of large flexible structures. Concurrently, the RBFNN is employed to approximate the entire unknown nonlinear dynamics of the combined spacecraft-truss system online, effectively compensating for uncertainties arising from the flexibility of the truss and external disturbances. The performance of the proposed controller is validated through both numerical simulations and hardware experiments on a ground-based air-bearing satellite simulator. Simulation results demonstrate the controller’s superior tracking accuracy compared to a conventional PID controller, while strictly adhering to the prescribed error constraints. Experimental results further confirm its effectiveness, showing that the simulator can track a desired trajectory with high precision, with tracking errors converging to approximately 5 mm while consistently remaining within the predefined safety boundaries. The proposed approach provides a robust and safe control solution for complex proximity operations in on-orbit construction, eliminating the need for precise dynamic modeling of flexible payloads. Full article

Hydroxyl-terminated polybutadiene (HTPB) is widely used in polyurethane binders, adhesives, and elastomers, but its low polarity and unsaturated backbone limit adhesion and long-term stability. Epoxidation presents a promising approach to addressing these limitations. However, most prior studies have focused on high-cis polybutadiene (PB), and systematic tuning of epoxidation in industrial low-cis HTPB has not been thoroughly examined. In this work, the epoxidation conversion of low-cis HTPB was systematically controlled by varying the equivalent amount of 3-chloroperbenzoic acid (m-CPBA). Conversion was governed solely by oxidant stoichiometry, while reaction time, concentration, and temperature had minimal effect, consistent with rapid, mixing-controlled epoxidation. Selective modification of 1,4-cis and 1,4-trans units enabled direct evaluation of how epoxidation degree influences polyurethane network formation and performance. Polyurethanes derived from epoxidized HTPB (EHTPB-PU) exhibited a clear correlation between epoxidation degree and network formation. Mechanical, adhesion, and chemical-resistance measurements revealed optimal performance at 10% epoxidation, where polarity and network compactness are effectively balanced. At this level, polyurethanes showed enhanced tensile strength, broad substrate adhesion, and increased resistance to acidic, basic, polar, and nonpolar environments, along with reduced water uptake. These results identify moderate epoxidation as a practical and efficient strategy for improving HTPB-based polyurethane materials. Full article

Conventional dental materials with organised crystal structures exhibit limitations in corrosion resistance, bioactivity, and drug delivery capability. In contrast, amorphous nanomaterials offer potential advantages in overcoming these limitations due to their unique structural properties. They are characterised by a non-crystalline, disordered atomic structure and are similar to a solidified liquid at the nanoscale. Among the amorphous nanomaterials used in dentistry, there are five major categories: calcium-, silicon-, magnesium-, zirconia-, and polymer-based systems. This study reviewed these amorphous nanomaterials by investigating their synthesis, properties, applications, limitations, and future directions in dentistry. These amorphous nanomaterials are synthesised primarily through low-temperature methods, including sol–gel processes, rapid precipitation, and electrochemical etching, which prevent atomic arrangements into crystalline structures. The resulting disordered atomic configuration confers exceptional properties, including enhanced solubility, superior drug-loading capacity, high surface reactivity, and controlled biodegradability. These characteristics enable diverse dental applications. Calcium-based amorphous nanomaterials, particularly amorphous calcium phosphate, demonstrate the ability to remineralise tooth enamel. Silicon-based amorphous nanomaterials function as carriers that can release antibacterial agents in response to stimuli. Magnesium-based amorphous nanomaterials are antibacterial and support natural bone regeneration. Zirconia-based amorphous nanomaterials strengthen the mechanical properties of restorative materials. Polymer-based amorphous nanomaterials enable controlled release of medications over extended periods. Despite the advances in these amorphous nanomaterials, there are limitations regarding material stability over time, precise control of degradation rates in the oral environment, and the development of reliable large-scale manufacturing processes. Researchers are creating smart materials that respond to specific oral conditions and developing hybrid systems that combine the strengths of different nanomaterials. In summary, amorphous nanomaterials hold great promise for advancing dental treatments through their unique properties and versatile applications. Clinically, these materials could improve the durability, bioactivity, and targeted drug delivery in dental restorations and therapies, leading to better patient outcomes. Full article

Background: This study aimed to assess the efficacy, optimal dosing, and timing of colchicine therapy in reducing major adverse cardiovascular events (MACE), its impact on inflammatory markers, and safety concerns in patients following acute coronary syndrome (ACS) through a systematic review and meta-analysis of randomized controlled trials (RCTs). Methods: A comprehensive search of PubMed, Embase, and the Cochrane Library was conducted in accordance with PRISMA guidelines to identify RCTs comparing colchicine versus placebo or standard treatment in ACS patients. The primary outcome was MACE and secondary outcomes included all-cause and cardiovascular mortality, non-fatal MI, stroke, revascularization, heart failure, CRP/hs-CRP changes, and adverse effects. Fifteen RCTs involving 19,131 patients were analyzed. Results: The benefit of colchicine in reducing MACE risk was marginally significant (RR = 0.79, 95% CI: 0.63–0.99, p = 0.04, I² = 59%). No significant reduction was observed for all-cause mortality, cardiovascular mortality, other cardiovascular outcomes, early initiation of colchicine (≤3 days), or choice of dosage (≤0.5 mg/day vs. >0.5 mg/day). The findings pertaining to the delayed time-to-initiation (>3 days) and changes in CRP or hs-CRP levels were inconclusive. Gastrointestinal side effects, especially diarrhea (RR = 1.76, 95% CI: 1.16–2.66, p = 0.001), were most common. No increase in hematologic events or infections was observed. Conclusions: Colchicine potentially reduces MACE in ACS patients, without evidence of benefit in improving all-cause mortality or other cardiovascular outcomes. Gastrointestinal intolerance is the most common side effect. This result is consistent with current clinical guidelines: a Class IIb recommendation for colchicine use in ACS. There is a need for further high-quality trials to refine patient selection and optimize treatment regimens. Full article

Traditional reliability indicators, such as SAIDI, SAIFI, DEC, and FEC, remain essential benchmarks, but they have proven insufficient to capture recovery capacity and vulnerability under extreme events. This bibliometric review clarifies these limitations while mapping how advanced control solutions—such as deep reinforcement learning (DRL), model predictive control (MPC), and graph neural networks (GNNs)—are being employed to enhance network restoration, voltage regulation, and outage management. By integrating discussions of conventional indices with the emerging role of artificial intelligence and storage technologies, this study provides a dual contribution: (i) identifying how resilience and reliability are being redefined in the literature, and (ii) highlighting research gaps in the standardization of event-based metrics, such as restoration time and customer minutes lost. The results aim to support regulators and operators in adopting intelligent, secure, and sustainable strategies for distribution networks, ensuring that technological advances are aligned with energy justice and real operational challenges. Full article