Search Results (2,968)

Lonicera japonica Flos (LJF) is widely used in pharmaceuticals and functional foods, with its bioactive constituents significantly influenced by processing methods. This study characterized the dynamic changes in chemical components in LJF under different maceration and decoction durations. Using UPLC-Q-TOF-MS and molecular networking, a total of 260 metabolites were unambiguously identified or tentatively characterized, including 66 iridoids, 42 flavonoids and 49 phenolic acids. Among these, 11 phenolic acids and 3 flavonoids were absent in the macerated samples. Twenty-two representative compounds were quantified using calibration curves. Most secondary metabolites, particularly phenolic acids, exhibited lower levels in the macerated samples than the decocted samples (e.g., 5-O-caffeoylquinic acid: 65.67–106.41 μg/g during maceration vs. 32,783.05–55,754.68 μg/g during decoction). The decoction process significantly enhances the extraction of active constituents. Notably, certain iridoids (e.g., 7-O-methyl morroniside: 92.91–354.59 μg/g during maceration vs. 50.43–171.40 μg/g during decoction) were better preserved under maceration, highlighting its advantage for retaining heat-sensitive bioactive components. During the decoction process, 5-hydroxycinnamoylquinic acids tended to transform into 3- and 4-hydroxycinnamoylquinic acid isomers. Most di-hydroxycinnamoylquinic acids and flavonoids significantly decreased after 30 min. Nitrogen-containing seco-iridoids declined rapidly after 15 min. To balance extraction efficiency with the preservation of heat-sensitive bioactive components, a decoction time of 15–30 min is recommended. The study systematically elucidates the dynamic changes in bioactive components under two preparation methods, offering critical insights and a scientific foundation for the precision utilization of LJF in pharmaceutical and functional food industries. Full article

As the integrated energy market evolves toward a multi-stakeholder coexistence model, balancing economic efficiency, user well-being, and system-level sustainability among interacting stakeholders has become a key challenge, particularly in the rapidly developing regional integrated energy markets in China. Thus, to satisfy user comfort and energy substitution requirements while achieving cost-effective electricity and heating supply, this study proposes a Stackelberg game-based market trading framework involving an integrated energy producer (IEP), an integrated energy operator (IEO), and a load aggregator (LA). First, the integrated energy market framework and transaction modes are established, and the profit models of IEP and IEO are formulated. Considering users’ energy substitution behavior, user comfort is quantified to explicitly reflect user welfare in market decision making, and a consumer surplus model is developed for LA participating in market transactions. Second, a Stackelberg game framework is constructed to coordinate the strategies of all participants by incorporating source–load energy flows, and the equilibrium solution is proven to be unique and solvable using quadratic programming. Finally, a case study based on historical data from Hebei Province, China, is conducted to validate the proposed strategy. The results demonstrate that the proposed method effectively coordinates the interests of all stakeholders, enhances demand response capability without reducing user comfort, and improves economic benefits for both supply and demand sides in regional integrated energy markets. Full article

High-strength stainless steels are essential materials for critical load-bearing aerospace components, and solution treatment serves as a core process governing their strength–toughness balance. However, in novel multi-element alloy systems, the complex dissolution behavior of precipitates and its underlying mechanisms affecting matrix phase transformations require further investigation. This study systematically explores the thermodynamic evolution and microstructural response of a novel Fe-Ni-Cr-Mo-Al-Ti ultra-high-strength stainless steel during solution treatment. The research highlights how solution temperature drives Laves phase dissolution, controls prior austenite grain growth, redistributes local chemical elements, and dictates retained austenite stability. By establishing the relationship between microstructural features and macroscopic properties, this study aims to provide crucial theoretical guidance for optimizing heat treatment protocols to achieve superior comprehensive mechanical properties in advanced high-strength stainless steels. Full article

Hydroponic cultivation is expanding rapidly as a resource-efficient alternative to soil-based farming, but challenges related to nutrient management, abiotic or biotic stresses, and organic production still limit the system’s performance and efficiency. Biostimulants are increasingly being explored as a promising strategy to support productivity and sustainability in soilless systems. This review summarizes the current evidence on the use of plant biostimulants to support crop performance in hydroponic systems. Microbial biostimulants, such as plant growth promoting rhizobacteria, Arbuscular Mycorrhizal Fungi, and Trichoderma spp., have been reported to promote root growth by synthesizing phytohormones, enhance nutrient uptake, and reduce the impacts of salt and heat stress, with reported improvements in biomass and nutrient use efficiency. Seaweed extracts and protein hydrolysates modulate plant hormonal balance, improve antioxidant defense, and have been associated with improvements in yield and quality. Humic and fulvic acids increase micronutrient bioavailability through chelation and stimulate root activity through auxin-like effects. In organic hydroponics, biostimulants may help address the nutrient gap by accelerating organic matter mineralization. Existing key challenges include the lack of hydroponic-specific dosage guidelines and high commercialization costs. Future efforts should further evaluate system-specific strategies, including emerging tools such as artificial intelligence-optimized strategies and the use of clustered regularly interspaced short palindromic repeats-edited microbes to support the long-term sustainability of controlled environment agriculture. Full article

Coking coal flotation is a typical nonlinear, multi-variable, and multi-objective process in which concentrate quality and combustible matter recovery must be balanced under fluctuating feed and operating conditions. To improve both predictive reliability and decision support, this study proposes an integrated data-driven framework that combines particle swarm optimization-back propagation (PSO-BP) prediction, SHapley Additive exPlanations (SHAP) based interpretation, Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization, and entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (Entropy-TOPSIS) decision-making. After three-sigma outlier screening, 2000 valid distributed control system (DCS) samples were retained for model development and temporal holdout evaluation, and an additional 200 later-period industrial samples were used for independent validation. The data were partitioned chronologically, with months 1–4, month 5, and month 6 used for training, validation, and temporal holdout testing, respectively, while the months 7–8 dataset was reserved for later-period validation. The results show that PSO-BP consistently outperformed conventional BP under both temporal holdout and later-period validation. SHAP analysis identified raw coal ash and collector dosage as the dominant factors for product-quality prediction, while collector dosage and frother dosage contributed most strongly to tailing heat of combustion. NSGA-II further revealed the trade-off among clean coal ash, clean coal sulfur, and tailing heat of combustion, and Entropy-TOPSIS converted the Pareto-optimal candidate set into a practically balanced operating recommendation. Sensitivity and robustness analyses indicated acceptable stability of both the optimization process and the final decision result. Overall, the proposed framework provides an interpretable prediction–optimization–decision workflow for coking coal flotation and offers a practical basis for future DCS-assisted intelligent regulation. Full article

This study presents a structured methodology for mid-term electricity demand forecasting in the Greek interconnected power system, incorporating climate-sensitive and socio-economic variables. A set of linear regression models was developed to produce forecasts at both monthly and daily resolutions, aiming to balance accuracy with transparency and computational efficiency. Monthly demand was modeled using macro-trend variables such as GDP, population, and energy prices, while daily demand was approached through a disaggregated modeling structure, assigning a distinct regression model to each day of the week. Temperature effects were introduced at both levels using cooling and heating degree days, estimated based on seasonal weather forecasts provided by 51 meteorological models. The modeling approach developed shows a high predictive value. The monthly electricity demand forecast over a six-month horizon exhibits a mean absolute percentage error and a maximum error of approximately 1.4% and 3.9%, respectively, when actual meteorological data are employed, and 3.7% and 8.5%, respectively, when seasonal meteorological forecasts are used for the entire year 2022, in which it has been tested. Adjusting the model for projecting, the monthly peak load in the same time horizon, presents less accurate yet satisfactory results, with a mean and maximum error of 2.9% and 9.6%, respectively, when actual meteorological data are used, and 5.3% and 12.9%, respectively, when seasonal meteorological forecasts are employed. Full article

Ambient heat exposure reduces male fertility in mammals with scrotal testes. Our previous work has demonstrated that some stallions are more susceptible to ambient heat-related subfertility than others, yet the mechanism for heat-induced subfertility remains uncertain, limiting both diagnosis and preventative measures. This study sought to define how the phenotype of stallions susceptible to heat-induced subfertility differs from that of more resilient animals, by measuring the systemic (blood plasma) and localized (reproductive tract) inflammatory and oxidative stress markers of sperm concentration, sperm motility assessments, total antioxidant capacity (TAC; in blood and seminal plasma), malondialdehyde (MDA; in blood and seminal plasma), oxidized guanine species (8-OH-2dG; in blood plasma and spermatozoa DNA), sperm DNA damage (assessed via Halo, SCSA (Sperm Chromatin Structure Assay) and CMA3 (Chromomycin A3)), and c-reactive protein (CRP; in blood plasma). Post-breeding dismount semen samples (n = 357) and blood plasma samples (n = 97) were collected from 31 stallions at commercial thoroughbred studs throughout one breeding season (NSW, Australia). A subset of stallions (16%) was deemed heat-induced subfertility-susceptible (HISS) stallions. These animals showed reduced seminal plasma antioxidant capacity, increased systemic and localized lipid peroxidation, and distinct systemic inflammatory response. Seminal antioxidant capacity was found to be strongly associated with impaired sperm motility (r = 0.739 * vs. r = −0.059). The plasma c-reactive protein of heat-susceptible stallions correlated to heat exposure (r = 0.597 *) and affected sperm motilities (r = −0.527 **, r = −0.434 *). Systemic oxidative DNA damage (8-OH-2dG) also increased following heat events (r = 0.862 ***) and correlated with fertility losses (FCP: r = −0.740 **, PCP: r = −0.603 *). Non-HISS stallions displayed greater variability in systemic antioxidant status and robust response following heat exposure (r = 0.307 *) and localized antioxidant capacity was more strongly correlated to systemic antioxidant capacity than in the heat-susceptible group (r = 0.897 *** vs. r = 0.482 **). We demonstrate that impaired antioxidant responses, altered redox balance and suppressed acute-phase inflammatory signalling are key features associated with heat-induced subfertility in stallions and highlight biomarkers that could be used to identify animals with heat-susceptible fertility. Full article

Since their discovery in 2009, perovskite solar cells (PSCs) have demonstrated rapid progress. Ambient-processed, carbon-based PSCs utilizing a pre-heating step offer a cost-effective fabrication route. Nevertheless, the role of the compact titanium dioxide (TiO₂-c) layer in ambient conditions has remained under-explored and inconsistently reported in the literature. This study then investigated the impact of TiO₂-c layer thickness, ranging from 70 nm to 155 nm, on the performance of PSCs fabricated entirely in ambient air with high relative humidity (RH > 70%). The layers were deposited via the sol-gel spin-coating method. Experimental results then revealed that the thinnest layer (70 nm) yielded the lowest average power conversion efficiency (PCE) of 2.05% due to diminished J_sc and V_oc values. The optimized TiO₂-c thickness was also identified at 95 nm, achieving an average PCE of 2.95% and a peak efficiency of 4.5%. Structural analysis via XRD confirmed the presence of both anatase and brookite phases. Notably, increasing the thickness from 70 nm to 155 nm resulted in a slight reduction in the anatase peak and a corresponding increase in the brookite peak. The superior performance at 95 nm could be attributed to a balanced crystal intensity between these two phases. Furthermore, TiO₂-c thickness was found to correlate with larger aggregate formation, better uniform shape grains, and reduced surface roughness, significantly influencing the morphology of the subsequent mesoporous TiO₂-m layer. These findings then provided critical insights into how thickness variation in the TiO₂-c layer could influence the performance of ambient-processed carbon-based PSCs. Full article

Heating, ventilation, and air conditioning (HVAC) systems are essential for indoor air quality and thermal comfort but can simultaneously act as vectors for microbial contamination, particularly bacteria and fungi. While the COVID-19 pandemic intensified focus on airborne viral transmission, bacterial and fungal contamination in indoor environments remains a persistent and significant health risk. This study presents a detailed case study of a restaurant HVAC system, analysing the impact of different ventilation strategies on bacterial contamination, infection transmission risk, energy consumption, and thermal comfort. By focusing on a real-world application, the research evaluates practical challenges and trade-offs associated with HVAC operation modifications aimed at mitigating microbial risks while maintaining acceptable energy and comfort levels. The research compares three operational scenarios: normal operation with air recirculation, 24 h operation with 100% outdoor air, and extended operation periods. Results demonstrate that while strategies emphasizing outdoor air intake and extended operation reduce infection probability by up to 60–65%, they simultaneously increase energy consumption by over 1700% and compromise thermal comfort parameters. In the h24 case, the pre-heat coil rises from 2421.7 to 43,923.7 kWh and the post-heat coil from 24,812.8 to 152,970.4 kWh, while the Plus 2 h strategy reduces the energy penalty by roughly 42–51% with respect to the h24 case. The findings are contextualized within current research on bacterial and fungal risks in HVAC systems, highlighting the critical need for balanced ventilation strategies that integrate health protection, energy efficiency, and comfort considerations. Full article

This paper presents a non-contact depth detection method for corrugated heat exchanger plates, aiming to improve measurement efficiency and accuracy. The system integrates a line laser sensor with a precision linear guide rail, enabling continuous acquisition of high-resolution 2D surface profiles as the sensor moves along the plate. To reduce data redundancy while preserving geometric features, a multi-stage data reduction strategy is proposed. This strategy combines the angle–chord height criterion with spline-based filtering to identify key regions of curvature and eliminate unnecessary point cloud data. For depth extraction, a two-stage feature recognition algorithm is designed. First, a coarse analysis locates candidate peaks and valleys by identifying local extrema in the reduced 2D data. Then, a fine detection process is applied: local B-spline fitting is performed near each candidate point, and a binary search algorithm is used to accurately determine the spline extrema. By computing the vertical distance between precisely located peaks and valleys, the system rapidly extracts the corrugation depth parameters. This method achieves a high balance between speed and precision, offering a practical and reliable solution for automated surface morphology inspection in heat exchanger manufacturing. Full article

This study presents the design, thermodynamic modelling, and numerical optimisation of a medium-scale (100 kW) transcritical CO₂ air-source heat pump water heater (ASHP-WH) intended to deliver 90 °C domestic hot water under sub-zero ambient conditions. A detailed component-sizing methodology was established and implemented in AMESim 2404 using REFPROP-based property calculations, with model convergence confirmed by the mass and energy balance closure. Parametric investigations covering the discharge pressure, refrigerant charge, ambient air temperature, and water outlet temperature were conducted through 140 steady-state simulations. The results show that the system achieved a heating capacity of 100–121 kW with a coefficient of performance (COP) of 2.7–3.3 across −15 °C to +10 °C ambient conditions. The optimal discharge pressure (≈11.2 MPa) and charge inventory (10 ± 2 kg) define a broad operating window that ensures COP stability (±2%) and avoids liquid carry-over. The exergetic efficiency remained above 0.75 throughout the tested climate range. Compared with published laboratory prototypes, the proposed 100 kW module demonstrates a superior performance at harsher sub-zero boundaries, highlighting its potential for commercial hot water and industrial applications. The findings provide actionable guidelines for component sizing, charge management, and adaptive pressure control, and establish a pathway from a numerical prototype to scalable field deployment of medium-scale transcritical CO₂ systems. Full article

Hydrocarbon-contaminated sites are among the most common challenges for environmental professionals worldwide. Although bioremediation strategies have emerged, their efficiency in cleaning hydrocarbon-contaminated soil depends considerably on local conditions. This study presents a science-based framework to assess the potential for soil bioremediation based on site-specific conditions. At multiple depths, soil samples were collected from four locations (S1, S7, S13, and S16) within a historically contaminated heating plant site. Using a three-step framework based on the content of total petroleum hydrocarbons (TPH), hydrocarbon pollutant fractions, ecotoxicity, and microbial population density, the study quantitatively (using a scoring matrix) revealed considerable variability across locations regarding the potential for bioremediation. Thus, due to balanced parameter contributions, S16 has the most promising bioremediation potential. Location S1 may require additional effort to enhance microbial populations. Locations S7 and S13 have low scores, with S13 being the least suitable, requiring extensive efforts to improve site-specific conditions for bioremediation. By integrating chemical, biological, and ecological factors, this science-based framework emphasizes the importance of site pre-characterization, thus providing an evaluation tool for bioremediation applications at hydrocarbon-contaminated sites with similar data availability. Moreover, the pre-remediation matrix scoring evaluation results align with the in situ bioremediation efficiency observed at the site. Full article

Soybean is a vital crop supporting global food, feed, and biofuel production. Soybean yields have surged, with record yields reaching 14,678 kg/ha⁻¹, though average farm yields remain stagnant at 2770–2790 kg ha⁻¹. The persistent yield gaps leave 44% of potential production unrealized due to climate change, threatening food security. To meet future caloric demands, which are projected to rise by 46.8% by 2050, soybean breeding must prioritize climate-resilient, high-yielding varieties with minimal ecological footprints. In this comprehensive and in-depth review, we synthesized existing literature and Google Patents and reviewed the multifaceted impacts of climate-change driven eCO₂ and stresses (heat, drought, flooding, salinity, and pathogens), revealing non-linear interactions where eCO₂ may not compensate yield losses under combined stresses. We then highlight key strategies for soybean breeding under climate-change scenario. To this regard, we provide a detailed trait-by-trait breeding roadmap covering seed number, seed size, seed weight, protein-oil balance and their metabolic trade-offs, above and below ground plant architecture, nitrogen fixation and nodulation dynamics, root system architecture, water use efficiency, canopy architecture, flowering time regulation, early maturity etc., in light of specific genes and validated strategies. We explicitly discuss the novel strategies including deeper understanding of traits, abiotic stress physiology, changing pathogen dynamics, phenomics, (multi-)omics, machine learning, and modern biotechnological techniques for developing future soybean varieties. We provide a future roadmap prioritizing specific actions, including engineering climate-resilient ideotypes through gene stacking, optimizing nitrogen fixation and nutrition under stresses leveraging omics data, pan-genome, wild soybean, speeding breeding hubs, and participatory farmer-network validation, while redefining the future soybean breeder would be a hybrid orchestrator of data and dirt. This review establishes a foundational framework for translating climate-adaptive morphological, biochemical, physiological, omics, agronomic, phenomics, and biotechnological insights into actionable breeding strategies, thereby guiding policy-driven investment in soybean improvement programs targeting 2050 and beyond. Full article

Urban districts are increasingly exposed to overlapping heat stress and stormwater loads driven by warming trends, more intense rainfall, and continued growth of impervious surfaces. Pavements occupy a large share of the public right-of-way, so their material and structural design offers a scalable pathway for urban climate adaptation. Yet the literature on porous asphalt remains fragmented, with hydrological performance often assessed using infiltration or permeability metrics in isolation, while thermal studies frequently report surface cooling without consistently tracking the governing water budget or its persistence. To reconcile these disconnected strands, this review synthesizes a conceptual hydro-thermal balance framework in which runoff mitigation and heat moderation are treated as a coupled problem controlled by storage, drainage pathways, and evaporative demand. Within this framing, cooling is primarily water-limited: permeability enables wetting and redistribution, but the magnitude and duration of temperature reduction depend on how much water is retained near the surface and how long it remains available for evaporation, rather than on permeability alone. The review integrates the current understanding of mixture structure and pore connectivity, permeability–storage behavior, moisture availability and evaporation, and the operational factors that govern performance persistence. Laboratory and field evaluation approaches are summarized alongside modeling methods used to interpret coupled hydro-thermal responses under different climates. Practical constraints—including clogging, maintenance requirements, and durability risks under repeated moisture–temperature cycling—are discussed as mechanisms that can progressively suppress both infiltration and water availability, undermining long-term function without performance-based specifications and life-cycle planning. Finally, design and policy implications are outlined for integrating porous asphalt into coordinated heat-and-stormwater strategies, and research priorities are identified to advance standardization, long-term monitoring, and coupled hydro-thermal–mechanical assessment. Full article

Converter steelmaking remains the dominant route for global steel production, and the double-slag process is an important refining method that merits further study. In this work, a MATLAB-based mathematical model was developed for the double-slag process under a fixed dephosphorization rate, focusing on slag control during the low-temperature dephosphorization stage (1360–1400 °C) and the subsequent decarburization stage. The model was used to guide industrial trials and analyze the effect of the deslagging ratio (Rds) on slag control and process behavior. The results show that: (1) under a given Rds, the double-slag process can theoretically approach stable slag control and slag volume with increasing decarburization slag recycling cycles; (2) at a fixed dephosphorization rate, changes in Rds affect both the total amount of slag-forming materials and their distribution between refining stages; (3) although the double-slag process reduces slag-forming material consumption compared with the single-slag process and conventional low-slag practice, it does not necessarily guarantee low-slag smelting; and (4) an optimal Rds exists under specific conditions, indicating that a higher deslagging ratio is not always beneficial and must be balanced with effective phosphorus removal. Industrial trials showed that the compliance rate of key slag parameters exceeded 60%, the dephosphorization rate during the dephosphorization stage was above 60%, and the overall dephosphorization rate exceeded 90% on average. The recycling of decarburization slag also showed complex effects on phosphorus removal in subsequent heats, indicating that its influence should be evaluated over multiple cycles rather than from isolated heats. Therefore, ideal stability predicted by the model cannot be fully achieved in industrial practice, and controlled recycling combined with timely slag renewal is required for process optimization. Full article