Search Results (9,271)

As core components of power grids, overhead transmission lines must traverse mountains and rivers, particularly in complex terrain where traditional wind speed prediction methods exhibit significant shortcomings in capturing sudden wind speed changes and spatial structural characteristics. The present study proposes a deep learning-based complex terrain wind speed prediction algorithm model utilizing meteorological data with the objective of enhancing the precision of wind speed variation prediction. The model utilizes historical meteorological data and terrain attributes derived from digital elevation models as inputs. The model’s design incorporates a terrain-aware temporal convolutional network and a terrain-modulated initialization strategy, resulting in high sensitivity to wind field variations. Subsequently, a terrain-relative position encoding bridging module is constructed to fuse local terrain features with spatial structural priors. A novel terrain-guided sparse attention mechanism is proposed to direct the model’s focus toward complex terrain regions, thereby enhancing the model’s capacity to predict wind speed with greater precision. The experimental results demonstrate that, for conventional wind speed prediction, this model reduces the mean absolute error and root mean square error by 6.6% and 30%, respectively, compared to current mainstream models. In tasks involving strong wind prediction, the model exhibits a reduction in the average false negative rate and false positive rate by 11.3% and 4.7%, respectively, when compared to conventional models. This finding suggests the model’s efficacy and robustness in complex terrain wind speed prediction tasks. Full article

Magnesite tailings are by-products of magnesite mining, yet their utilization rate remains extremely low. Although previous studies have explored their basic physical properties and potential use in cementitious or geotechnical materials, research on cement-stabilized magnesite tailings-particularly regarding their mechanical behavior, engineering applicability, and microstructural evolution-remains limited. Key scientific gaps include the lack of systematic evaluation of their compaction characteristics, strength development, stiffness evolution, and bearing capacity, as well as insufficient understanding of the stabilization mechanisms governing their performance. Addressing these gaps is essential for assessing their feasibility as road construction materials. In this study, magnesite tailings were selected as the primary raw material and mixed with ordinary Portland cement to prepare mixtures for evaluating their suitability as highway subgrade fillers. The compaction characteristics, unconfined compressive strength (UCS), ultrasonic pulse velocity (UPV), and California Bearing Ratio (CBR) of the mixtures were systematically examined. Furthermore, the evolution of composition and stabilization mechanisms of the mixtures was analyzed using X-ray diffraction, scanning electron microscopy, and thermogravimetric analysis. The results show that cement incorporation effectively improves the poor particle gradation of magnesite tailings, leading to a denser and more homogeneous structure. Adding 7% cement increases the maximum dry density and optimum moisture content by 3.7% and 5.1%, respectively. The unconfined compressive strength rises by 100.9–126.3% within 3–28 days, and the maximum uniaxial stress is 119.6% higher than that of the 1% cement mixture. These improvements demonstrate the potential of cement-stabilized magnesite tailings as a sustainable subgrade material and provide insight into their microstructural and mechanical behavior. Full article

This study focuses on the optimization of modern extraction techniques for selected by-product materials, including apple, lemon, and tangerine peels, and onion skins, using artificial neural network (ANN) models. The extraction methods included ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) with water as the extractant, as well as maceration (MAC) with natural deep eutectic solvents (NADES). Key parameters, such as total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activities, including reducing power (EC₅₀) and free radical scavenging capacity (IC₅₀), were evaluated to compare the efficiency of each method. Among the techniques, UAE outperformed both MAE and MAC in extracting bioactive compounds, especially from onion skins and tangerine peels, as reflected in the highest TPC, TFC, and antioxidant activity. UAE of onion skins showed the best performance, yielding the highest TPC (5.735 ± 0.558 mg CAE/g) and TFC (1.973 ± 0.112 mg RE/g), along with the strongest antioxidant activity (EC₅₀ = 0.549 ± 0.076 mg/mL; IC₅₀ = 0.108 ± 0.049 mg/mL). Tangerine peel extracts obtained by UAE also exhibited high phenolic content (TPC up to 5.399 ± 0.325 mg CAE/g) and strong radical scavenging activity (IC₅₀ 0.118 ± 0.099 mg/mL). ANN models using multilayer perceptron architectures with high coefficients of determination (r² > 0.96) were developed to predict and optimize the extraction results. Sensitivity and error analyses confirmed the robustness of the models and emphasized the influence of the extraction technique and by-product type on the antioxidant parameters. Principal component and cluster analyses showed clear grouping patterns by extraction method, with UAE and MAE showing similar performance profiles. Overall, these results underline the potential of UAE- and ANN-based modeling for the optimal utilization of agricultural by-products. Full article

Background/Objectives: Differential scanning calorimetry (DSC) analysis of blood plasma, also known as thermal liquid biopsy (TLB), is a promising approach for disease detection and monitoring; however, its wider adoption in clinical settings has been hindered by labor-intensive data processing workflows, particularly baseline correction. Methods: We developed and tested two automated algorithms to address critical bottlenecks in TLB analysis: (1) a baseline-correction algorithm utilizing rolling-variance analysis for endpoint detection, and (2) a signal-detection algorithm that applies auto-regressive integrated moving average (ARIMA)-based stationarity testing to determine whether a profile contains interpretable thermal features. Both algorithms are implemented in ThermogramForge, an open-source R Shiny web application providing an end-to-end workflow for data upload, processing, and report generation. Results: The baseline-correction algorithm demonstrated excellent performance on plasma TLB data (characterized by high heat capacity), matching the quality of rigorous manual processing. However, its performance was less robust for low signal biofluids, such as urine, where weak thermal transitions reduce the reliability of baseline estimation. To address this, a complementary signal-detection algorithm was developed to screen for TLB profiles with discernable thermal transitions prior to baseline correction, enabling users to exclude non-informative data. The signal-detection algorithm achieved near-perfect classification accuracy for TLB profiles with well-defined thermal transitions and maintained a low false-positive rate of 3.1% for true noise profiles, with expected lower performance for borderline cases. The interactive review interface in ThermogramForge further supports quality control and expert refinement. Conclusions: The automated baseline-correction and signal-detection algorithms, together with their web-based implementation, substantially reduce analysis time while maintaining quality, supporting more efficient and reproducible TLB research. Full article

To promote the resource utilization of high-titanium blast furnace slag (HTBFS) and advance the development of lightweight prefabricated structures, this study developed a lightweight HTBFS concrete composite beam (HTC composite beam) by replacing natural gravel and sand in concrete with HTBFS coarse and fine aggregates, and incorporating fly ash ceramsite to reduce self-weight. Symmetrically two-point bending tests were conducted on five HTC composite beams with different reinforcement ratios and precast heights, one Integrally cast HTC beam, and one ordinary concrete composite beam. The failure modes, load-carrying capacities, and deformation characteristics were evaluated. The loading process was also simulated using Abaqus, and the numerical results were compared with experimental data for validation. The results indicate that HTC composite beams satisfy the plane-section assumption; increasing the reinforcement ratio improves the load-carrying capacity, and the precast height has positive effect of HTC composite beams’ load-carrying. Compared with the ordinary concrete composite beam, the HTC composite beam exhibited a 12.30% higher load-carrying capacity, smaller deflection, and better deformation capacity. Multiple energy-based indices demonstrated that HTC composite beams possess favorable post-cracking plastic deformation capacity and stiffness retention. The difference between the finite element simulations and experimental results was less than 5%, confirming both the reliability of the numerical model and the accuracy of the experimental data. An economic analysis revealed that this structural system has significant potential for carbon reduction and cost savings, with an overall saving of approximately 141,000–500,000 CNY. These findings provide theoretical and engineering support for the application of HTC composite beams in prefabricated construction and have positive implications for reducing project costs and promoting the industrialization and low-carbon development of prefabricated buildings. Full article

In this study, we aimed to investigate the potential of utilizing red grape pomace as a source of polyphenolic compounds in the growing, fragmented winemaking sector in Poland. For polyphenol extraction, we compared two methods: conventional extraction using water and alcohol solutions, and the supercritical CO₂ technique with ethanol as a cosolvent. The conventional method yielded at least 30% more polyphenols compared to the advanced SC-CO₂ technique. Experimentally chosen conditions, including a solvent composition of ethanol–water (1:1; v/v) containing 3% HCl, a liquid-to-solid ratio of 25:1 mL/g, and 2 min of ultrasound pretreatment and conventional extraction at a temperature of 30 °C over 4.5 h, enabled an extraction efficiency of 101 mg of total polyphenols per 1 g of raw material used, with an antioxidant capacity equivalent to 600 µmol of Trolox. According to HPLC analyses, the main components of the investigated biomass were epicatechin, anthocyanins and p-coumaric acid. The extract was encapsulated in liposomes, revealing no negative effect on their stability or aggregation under the conditions tested (21 days). The study suggests that conventional water–ethanol extraction can be a relatively safe and effective method for managing winemaking residuals, increasing the competitiveness of small producers through the production of high-value antioxidant additives. Full article

The rapid development of renewable energy has highlighted the issue of its accommodation, which has become a critical challenge for power grids with high renewable energy penetration. Accurately assessing a grid’s renewable energy accommodation capability is essential for ensuring power grid operational security, as well as for the rational planning and efficient operation of renewable energy sources and adjustable power resources. This paper adopts a long-term chronological power balance simulation approach, integrating the dynamic balance among multiple types of power sources, loads, and outbound transmission. Dispatch schemes suitable for different types of power sources, including hydropower, thermal power, wind power, solar power, and nuclear power, were designed based on their operational characteristics. Key operational constraints, such as output limits, staged water levels, pumping/generation modes of pumped storage, and nuclear power regulation duration, were considered. A refined analysis model for renewable energy accommodation in regional power grids was constructed, aiming to maximize the total accommodated renewable energy electricity. Using actual data from the Northeast China Power Grid in 2024, the model was validated, showing results largely consistent with actual accommodation conditions. Analysis based on next-year forecast data indicated that the renewable energy utilization rate is expected to decline to 90.6%, with the proportion of curtailment due to insufficient peaking capacity and grid constraints expanding to 8:2. Sensitivity analysis revealed a clear correlation between the renewable energy utilization rate and the scale of newly installed renewable capacity and energy storage. It is recommended to control the expansion of new renewable energy installations while increasing the construction of flexible power sources such as pumped storage and other energy storage technologies. Full article

The increasing volume of digital medical data offers substantial research opportunities, though its complete utilization is hindered by ongoing privacy and security obstacles. This proof-of-concept study explores and confirms the viability of using Secure Multi-Party Computation (SMPC) to ensure protection and integrity of sensitive patient data, allowing the construction of clinical trial cohorts. Our findings reveal that SMPC facilitates collaborative data analysis on distributed, private datasets with negligible computational costs and optimized data partition sizes. The established architecture incorporates patient information via a blockchain-based decentralized healthcare platform and employs the MPyC library in Python for secure computations on Fast Healthcare Interoperability Resources (FHIR)-format data. The outcomes affirm SMPC’s capacity to maintain patient privacy during cohort formation, with minimal overhead. It illustrates the potential of SMPC-based methodologies to expand access to medical research data. A key contribution of this work is eliminating the need for complex cryptographic key management while maintaining patient privacy, illustrating the potential of SMPC-based methodologies to expand access to medical research data by reducing implementation barriers. Full article

Diet and living environments exert a profound influence on gut microbiota composition. This study presents the first comprehensive characterization of fecal bacteria, fungi, and protozoa in wild (WA) (n = 10) and captive (DA) (n = 11) wapiti (Cervus canadensis) in China. Results reveal distinct microbial profiles between the two groups. In wild wapiti, Escherichia-Shigella and UCG-005 were the dominant bacterial genera, while Succinivibrio and Treponema predominated in captive individuals. Among fungi, Agaricus and Preussia were most abundant in wild wapiti, whereas Xeromyces was identified in captive ones. For protozoa, Heteromita was the primary genus in wild wapiti, while Heteromita, Entamoeba, and Eimeria were the main genera in captive wapiti. Functional predictions further underscored these differences. In wild wapiti, bacterial and fungal functions were primarily associated with carbon metabolism and the pyruvate cycle, with mutualistic interactions prevailing among bacteria, fungi, and protozoa. Conversely, captive wapiti exhibited functional profiles centered on lipopolysaccharide and amino acid metabolism, also characterized by mutualistic coexistence among microbial communities. These findings highlight the significant impact of dietary composition on the gut microbiome. In summary, wild wapiti appear to possess a superior capacity for plant fiber utilization. These findings provide valuable data for the health management of farmed wapiti and their adaptability in natural habitats. Full article

β-alanine has been shown to significantly improve nitrogen utilization efficiency in beef cattle, but its impact on growth performance remains unclear. This study involved 36 healthy 18-month-old Simmental crossbred bulls with similar weights (627 ± 41 kg). The cattle were divided into two groups, with each group comprising six replicates of three animals. While the control group received the basal diet, the treatment group was administered an additional 96 g/d/cattle rumen-protected β-alanine (RP-β-Ala). The study was conducted over a 35-day period, which included an initial 7 days for adaptation. At the end of the trial, body weight was recorded, and samples were collected. Results show that RP-β-Ala enhanced average daily gain (p = 0.065) and crude protein (CP) digestibility (p = 0.065) and reduced gain-to-feed ratio (p = 0.078). Analysis of rumen microbiota revealed that RP-β-Ala positively modulated the rumen microbiota by enriching beneficial genera such as Prevotella, Treponema, and Selenomonas. This enrichment increased volatile fatty acid production and nitrogen utilization efficiency, as evidenced by elevated ruminal ammonia-N and microbial CP levels, along with decreased serum urea nitrogen. Metabolomics identified key alterations in arachidonic acid metabolism, specifically the upregulation of metabolites 14,15-DiHETrE and prostaglandin D2, and enhanced antioxidative capability indicated by increased serum total antioxidant capacity (T-AOC). Concurrently, RP-β-Ala reduced serum TNF-α levels. This reduction was achieved by suppressing harmful bacteria like Thermoactinomyces and Saccharopolyspora, along with inhibiting their polyamine synthesis, specifically spermine and spermidine. Collectively, these effects alleviated oxidative stress and inflammation. These findings demonstrate that RP-β-Ala enhances beef cattle growth through improved energy supply and antioxidant capacity. Full article

At present, the continuous growth of renewable energy integration and power grid load demand has placed higher requirements on the transmission capacity and power flow control capability of power systems. Owing to its flexible and controllable power flow characteristics, DC transmission technology has been introduced into AC grid structures, making AC/DC hybrid power grids an important development trend. However, the increasingly prominent power flow security issues caused by the complex coupling characteristics between AC and DC systems pose new challenges. First, this paper conducts an in-depth analysis of the operating mechanisms and power flow coupling characteristics of AC/DC hybrid transmission sections under various operating conditions. To address the dual challenges of insufficient utilization of transmission capacity and power flow security, a novel AC-like AC/DC power flow coordinated optimization strategy is proposed. Based on phase angle coordinated control, the autonomous response capability of the DC system is leveraged to perform real-time control and optimization of transmission power on lines, maximizing the capacity utilization of AC/DC hybrid transmission section while satisfying security and stability requirements. Finally, simulation studies based on a transmission network containing two four-machine AC systems verify that the proposed strategy fully meets the security and stability requirements of AC/DC hybrid power grids, providing reliable technical support for the coordinated development of future AC/DC grids. Full article

Pb (II) contamination in wastewater represents a grave threat to the environment and ecosystems. Consequently, there is an urgent need to prepare low-cost and highly efficient Pb (II) adsorbents. To address this need, abundant and low-cost natural silica-based desert sand (DS) was innovatively utilized as a carrier to develop efficient and selective Pb (II) adsorbents. Modified desert sand (MDS) was first prepared via 1 M HCl pretreatment for 2 h and subsequent KH550 silane modification. Pb (II)-imprinted composites (Pb (II)-IIP@MDS) were then fabricated via ion-imprinted polymerization, using Pb (II) as the template ion and N-hydroxymethacrylamide (NHMA)/hydroxyethyl methacrylate (HEMA) as dual functional monomers with a molar ratio of 1:1. The synthesized Pb (II)-IIP@MDS was comprehensively characterized by X-ray photoelectron spectrometer (XPS), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FT-IR). The adsorption capacity, selectivity, and reusability of this material for lead ions were evaluated through three experiments conducted within the optimized pH range of 6–7, with error bars indicated. In adsorption isotherm experiments, the initial Pb (II) concentration ranged from 50 to 500 mg·L⁻¹, conforming to the Langmuir model (R² = 0.992), with a theoretical maximum adsorption capacity reaching 107.44 mg·g⁻¹; this indicates that the adsorbate forms a monolayer adsorption on the homogeneous imprinted sites. Kinetics data indicate that the process best fits a quasi-first-order kinetic model (R² ≥ 0.988), while the favorable quasi-second-order kinetic fit (R² ≥ 0.982) reflects the synergistic effect of physical diffusion and ion-imprinting chemistry, reaching equilibrium within 120 min. Thermodynamic parameters (ΔH⁰ = 12.51 kJ·mol⁻¹, ΔS⁰ = 101.19 J·mol⁻¹·K⁻¹, ΔG⁰ < 0) confirmed endothermic, entropy-increasing, spontaneous adsorption. In multicomponent systems, Pb (II)-IIP@MDS showed distinct Pb (II) selectivity. It retained 80.3% adsorption efficiency after eight cycles. This work provides a promising strategy for fabricating low-cost, high-performance Pb (II) adsorbents, and Pb (II)-IIP@MDS stands as a practical candidate for the remediation of Pb (II)-contaminated wastewater. Full article

Red mud is a highly alkaline solid waste with an annual emission of over 200 million tons, which requires large-scale utilization methods. Soil Cd remediation is a global concern, due to its high toxicity and strong mobility. Given red mud’s potential for soil Cd remediation, this study reviews its basic characteristics, the mechanisms of soil Cd immobilization by red mud, and the use of red mud-based passivators for agricultural soil Cd remediation. In general, red mud regulates soil pH, thus increasing the soil’s Cd adsorption capacity; provides abundant surface active sites for adsorption and complexation with soil Cd; introduces cations to immobilize Cd via ion exchange; and enriches Cd-resistant microbe species to reduce soil Cd toxicity. Furthermore, the potential environmental risks and suggestions on red mud application are discussed. Further research should focus on improving the remediation effectiveness of red mud on cadmium-contaminated agricultural soil, demonstrating its long-term efficacy and economic costs, and proposing practical technical models and standards for application. Full article

In arid regions, rainfall is scarce, summer-concentrated, and prone to extreme events, while evaporation exceeds precipitation, creating fragile ecosystems that need scientific stormwater management for flood resilience. Sponge cities, through the implementation of green infrastructure, can alleviate urban flooding, improve rainwater utilization, and enhance the urban ecological environment. Under the “dual carbon” target, sponge city construction has gained new developmental significance. It must not only ensure core functions and minimize construction costs but also fully leverage its carbon reduction potential, thereby serving as a crucial pathway for promoting urban green and low-carbon development. Therefore, this study focused on Xining, a typical arid city in Northwest China, and couples the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) with the Storm Water Management Model (SWMM) to construct a multi-objective optimization model for Low Impact Development (LID) facilities. The layout optimization design of LID facilities is conducted from three dimensions: life cycle cost (LCC), rainwater utilization rate (K), and carbon emission intensity (CI). Hydrological simulations and scheme optimizations were performed under different design rainfall events. Subsequently, the entropy-weighted TOPSIS method was utilized to evaluate and compare these optimized schemes. It is shown by the results that: (1) The optimized LID schemes achieved a K of 76.2–80.43%, an LCC of 2.413–3.019 billion yuan, and a CI of −2.8 to 0.19 kg/m²; (2) Compared with the no-LID scenario, the optimized scheme significantly enhanced hydrological regulation, flood mitigation, and pollutant removal. Under different rainfall return periods, the annual runoff control rate increased from 64.97% to 80.66–82.23%, with total runoff reduction rates reaching 46.41–49.26% and peak flow reductions of 45–47.62%. Under the rainfall event with a 10-year return period, the total number of waterlogging nodes decreased from 108 to 82, and the number of nodes with a ponding duration exceeding 1 h was reduced by 62.5%. The removal efficiency of total suspended solids (TSS) under the optimized scheme remained stable above 60%. The optimized scheme is highly adaptable to the rainwater management needs of arid areas by prioritizing “infiltration and retention”. Vegetative swales emerge as the primary facility due to their low cost and high carbon sink capacity. This study provides a feasible pathway and decision-making support for the low-carbon layout of LID facilities in arid regions. Full article

High photovoltaic (PV) penetration in distribution networks (DNs) often causes network congestion, which in turn leads to renewable curtailment. Existing studies on battery swapping stations (BSSs) mainly focus on energy management of established stations, rather than system-level planning and coordination. To address these challenges, this study proposes a coordinated planning method for electric vehicle (EV) BSSs to improve PV utilization. The method integrates BSS siting, capacity sizing, and price-subsidy strategies into a unified mixed-integer linear programming (MILP) model. The model is developed to integrate road networks (RNs) and DNs, capturing the interaction between EV battery swapping behavior and DN operation. By guiding swapping behavior through price-subsidy strategies to align with local PV output, the method enables more flexible energy utilization and mitigates network congestion. Case studies are conducted on a combined IEEE 33-bus DN system and Sioux Falls RN. Results show that the proposed method can effectively improve local PV utilization and reduce curtailment without violating DN operational constraints. Overall, the proposed method provides an efficient and practical decision-support tool for the integrated planning of BSSs and renewable-rich DNs. Full article