Search Results (9,875)

This paper proposes a coordinated capacity configuration method for Virtual Power Plant (VPP) distributed resources that considers time-varying power coupling. The method addresses the inadequate economic efficiency and reliability of existing configuration schemes, which stems from insufficient attention to the time-varying power coupling characteristics of Distributed Energy Resources (DERs). Firstly, we define the concepts of direct and indirect power coupling among DERs, derive a Lagrange multiplier-based coupling coefficient model, and realize the quantification of time-varying coupling coefficients through sliding time window correlation analysis (STWCA). Next, a capacity correlation matrix integrating technical and economic synergies is constructed to map coupling characteristics to capacity configuration. Then, a coordinated configuration model with time-varying coupling constraints is established to minimize life-cycle cost and maximize power supply reliability, validated by case simulation. The results demonstrate that the proposed method effectively reduces VPP operation cost and improves resource utilization and reliability, providing theoretical support for the scientific configuration of DERs in VPPs. Full article

To address the limitations of parameter drift in physical models and poor generalization in data-driven methods, this paper proposes a self-evolving digital twin framework for PMSM thermal safety. The framework integrates a dynamic-batch Bayesian calibration (DBBC) algorithm and a hierarchical physics-aware network (HPA-Net). First, the DBBC eliminates plant–model mismatch by robustly identifying stochastic parameters from operational data. Subsequently, the HPA-Net adopts a “physics-augmented” strategy, utilizing the calibrated physical model as a dynamic prior to directly infer high-fidelity temperature via a hierarchical training scheme. Furthermore, a real-time demagnetization safety margin (DSM) monitoring strategy is integrated to eliminate “false safe” zones. Experimental validation on a PMSM test bench confirms the superior performance of the proposed framework, which achieves a Root Mean Square Error (RMSE) of 0.919 °C for the stator winding and 1.603 °C for the permanent magnets. The proposed digital twin ensures robust thermal safety even under unseen operating conditions, transforming the monitoring system into a proactive safety guardian. Full article

Geothermal energy is recognized as one of the most reliable and environmentally sustainable energy sources. This study presents a comprehensive energy, exergy, economic, and exergoenvironmental assessment of the Mis I binary geothermal power plant (GPP) operating with a low-temperature geothermal resource. This study fills a critical gap in the literature by providing a four-dimensional (4-E) assessment—energy, exergy, economic, and exergoenvironmental—of the Mis I binary geothermal power plant (GPP). Unlike conventional studies that focus on theoretical models, this research utilizes real-time operational data to identify potential improvements at the component level by evaluating exergy-based environmental sustainability and economic performance. The energy efficiency of the n-pentane Rankine cycle was calculated as 39.76%, indicating that a substantial portion of the geothermal heat is rejected as waste. The exergy input to the plant was determined to be 18,580.29 kW, while the net electrical power output was 8990 kW, resulting in an overall exergy efficiency of 48.38%. These results highlight the clear disparity between energy and exergy efficiencies and underline the importance of exergy-based performance evaluation for low-temperature geothermal power systems. Component-level exergy balance analyses were conducted using real operating data, revealing that the cooling towers are the dominant sources of exergy destruction, whereas the turbine units exhibit comparatively high thermodynamic effectiveness. Improvement potential analysis identified cooling towers I–II, evaporator II, and preheater I as key components requiring further optimization. Economic evaluation showed that approximately 64% of the total investment cost is associated with turbine units, with a total plant cost of about USD 6.7 million. The levelized cost of electricity was calculated as 0.0136 USD/kWh, and the payback period was approximately 1.5 years. Exergoenvironmental results indicate that the Mis I GPP achieves the highest sustainability index (1.94) among comparable plants, confirming its superior thermodynamic, economic, and environmental performance. Full article

Willows (genus Salix) are versatile plants with applications in construction, medicine, and biomass fuel in North America. Advances in breeding have improved willow clones for higher yields and pest resistance, but the chemical content and distribution across different plant parts remain poorly understood. This study examined the variation in chemical elements (carbon, hydrogen, nitrogen, sulfur, chlorine, and ash) across six willow clones (India, Jorr, Olof, Otisco, Preble, and Tora) and three tissue types (wood, bark, twigs). We also compared freeze-drying and oven-drying methods to assess their impact on chemical content. Freeze-dried samples generally exhibited higher carbon and hydrogen concentrations than oven-dried samples, with statistically significant differences primarily observed for carbon, while nitrogen showed no overall significant difference between drying methods. Chemical composition varied among clones, although no single clone consistently dominated across all chemical parameters. In contrast, pronounced tissue-type differences were observed: bark had higher nitrogen, carbon, sulfur, chlorine, and ash contents, whereas wood exhibited relatively higher hydrogen concentrations, with twigs showing intermediate values. These findings suggest that accounting for tissue-specific chemical differences can improve the selection and utilization of willow biomass and increase the accuracy of ecological assessments, including carbon storage estimates. The findings of this study indicate that oven-drying should remain in use within the bioenergy sector, whereas freeze-drying ought to become the preferred standard for carbon-accounting protocols. Full article

Asparagine synthetase (AS) is a key enzyme in plant nitrogen metabolic network. Beyond its canonical role as a major nitrogen transport and storage molecule, asparagine also serves critical functions in plant immunity and tolerance to environmental stresses. This review systematically summarizes the characteristics of the core AS-mediated asparagine biosynthesis pathway and two other minor pathways in plants. It details the distribution of the AS gene family, protein structure, and evolutionary classification. The mechanisms governing AS expression are analyzed, revealing tissue-specific patterns and precise regulation by nitrogen availability, abiotic stresses, and exogenous hormones, mediated through an interactive network of cis-acting elements and transcription factors. Furthermore, the biological functions of AS are multifaceted: it influences plant biomass and nitrogen use efficiency by regulating nitrogen uptake, transport, and recycling during growth and development; it contributes to abiotic stress tolerance by synthesizing asparagine to maintain cellular osmotic balance and scavenge reactive oxygen species; and it indirectly enhances antibacterial and antiviral capacity by activating the SA signaling pathway and modulating programmed cell death. Current knowledge gaps remain regarding the crosstalk between AS-mediated signaling pathways, the upstream transcriptional regulatory network, and the balance between nitrogen utilization and disease resistance in crop breeding. Future research aimed at addressing these questions will provide a theoretical foundation and molecular targets for improving crop nitrogen use efficiency and breeding resistant cultivars. Full article

Background: Adopting novel feed ingredients and aligning feeding strategies with these formulations are key to improving aquaculture sustainability. This study assessed the combined effects of alternative protein and lipid sources and feeding regime on growth, nutrient utilization, and body composition of European sea bass (Dicentrarchus labrax) juveniles. Methods: Two isoenergetic and identical digestible protein diets (39%) were formulated: a control (conventional fishmeal/fish oil (FM/FO) and plant proteins, containing 20% FM and 6% FO) and an alternative diet replacing 50% of FM and 25% of vegetable proteins with a blend of poultry by-products, insect meal, and single-cell protein (Corynebacterium glutamicum) and totally replacing fish oil with alternative lipid sources (microalgae and by-product oils). Fish (28 g of initial body weight) were fed for 210 days either to apparent satiety (AS) or under moderate restriction (85% and 65% of AS). The number of fish used was 65 fish per 500 L tank (triplicate for each experimental group). Growth performance, feed conversion, nutrient efficiency ratios, protein retention, and proximate and fatty acid composition were measured. Results: The alternative diet significantly improved growth, feed and nutrient efficiency, and protein retention compared with the control. Whole-body fatty acid profiles of fish fed the alternative diet showed higher contents of nutritionally important fatty acids, including DHA. Restricted feeding at 65% of AS enhanced nutrient efficiency ratios and protein retention relative to 85% and AS, but reduced growth. Feeding to AS produced the highest feed intake and growth but poorer feed conversion and nutrient efficiency. No significant interaction between diet and feeding strategy was observed. Conclusions: Incorporating novel protein and lipid sources can improve sea bass performance and product nutritional value while supporting sustainability. Feeding at ~85% of AS may offer a practical compromise between growth and efficient nutrient utilization. Full article

Soil salinization remains a critical constraint on global land sustainability, severely limiting agricultural output and ecosystem resilience. To address this issue, a field trial was implemented to investigate the interactive benefits of vermicompost (VC) and a novel soil conditioner derived from coal gasification slag-based soil conditioner (CGSS) in mitigating saline–alkali stress. The perennial forage grass Leymus chinensis, valued for its ecological robustness and economic potential under adverse soil conditions, served as the test species. Five treatments were established: CK (unamended), T1 (CGSS alone), T2 (VC alone), T3 (CGSS:VC = 1:1), T4 (CGSS:VC = 1:2), and T5 (CGSS:VC = 2:1). Study results indicate that the combined application of CGSS and VC outperformed individual amendments, with the T4 treatment demonstrating the most effective results. Compared to CK, T4 reduced soil electrical conductivity (EC) by 12.00% and pH by 5.17% (p < 0.05), while markedly enhancing key fertility indicators—including soil organic matter and the availability of nitrogen, phosphorus, and potassium. Thus, these improvements translated into superior growth of L. chinensis, reflected in significantly greater dry biomass, expanded leaf area, and increased plant height. Additionally, the T4 treatment increased soil microbial richness (Chao1 index) by 21.5% and elevated the relative abundance of the Acidobacteria functional group by 16.9% (p < 0.05). Hence, T4 treatment (CGSS: 15,000 kg·ha⁻¹; VC: 30,000 kg·ha⁻¹) was identified as the optimal remediation strategy through a fuzzy comprehensive evaluation that integrated multiple soil and plant indicators. From an economic perspective, the T4 treatment (corresponding to a VC-CGSS application ratio of 2: 1) exhibits a lower cost compared to other similar soil conditioners and organic fertilizer combinations for saline–alkali soil remediation. This study not only offers a practical and economically viable approach for reclaiming degraded saline–alkali soils but also advances the circular utilization of coal-based solid waste. Furthermore, it deepens our understanding of how integrated soil amendments modulate the soil–microbe–plant nexus under abiotic stress. Full article

Globally, grasslands, savannas, and wetlands are degrading rapidly and increasingly being replaced by woody vegetation. Woody Plant Encroachment (WPE) disrupts natural landscapes and has significant consequences for biodiversity, ecosystem functioning, and key ecosystem services. This review synthesizes findings from 159 peer-reviewed studies identified through a PRISMA-guided systematic literature review to evaluate the drivers of WPE, its ecological impacts, and the remote sensing (RS) approaches used to monitor it. The drivers of WPE are multifaceted, involving interactions among climate variability, topographic and edaphic conditions, hydrological change, land use transitions, and altered fire and grazing regimes, while its impacts are similarly diverse, influencing land cover structure, water and nutrient cycles, carbon and nitrogen dynamics, and broader implications for ecosystem resilience. Over the past two decades, RS has become central to WPE monitoring, with studies employing classification techniques, spectral mixture analysis, object-based image analysis, change detection, thresholding, landscape pattern and fragmentation metrics, and increasingly, machine learning and deep learning methods. Looking forward, emerging advances such as multi-sensor fusion (optical– synthetic aperture radar (SAR), Light Detection and Ranging (LiDAR)–hyperspectral), cloud-based platforms including Google Earth Engine, Microsoft Planetary Computer, and Digital Earth, and geospatial foundation models offer new opportunities for scalable, automated, and long-term monitoring. Despite these innovations, challenges remain in detecting early-stage encroachment, subcanopy woody growth, and species-specific patterns across heterogeneous landscapes. Key knowledge gaps highlighted in this review include the need for long-term monitoring frameworks, improved socio-ecological integration, species- and ecosystem-specific RS approaches, better utilization of SAR, and broader adoption of analysis-ready data and open-source platforms. Addressing these gaps will enable more effective, context-specific strategies to monitor, manage, and mitigate WPE in rapidly changing environments. Full article

Precise identification of early peanut leaf spot is strategically significant for safeguarding oilseed supplies and reducing pesticide reliance. However, general-purpose detectors face severe domain adaptation bottlenecks in unstructured field environments due to small feature dissipation, physical occlusion, and class imbalance. To address this, this study constructs a dataset spanning two phenological cycles and proposes POD-YOLO, a physics-aware and dynamics-optimized lightweight framework. Anchored on the YOLOv10n architecture and adhering to a “data-centric” philosophy, the framework optimizes the parameter convergence path via a synergistic “Augmentation-Loss-Optimization” mechanism: (1) Input Stage: A Physical Domain Reconstruction (PDR) module is introduced to simulate physical occlusion, blocking shortcut learning and constructing a robust feature space; (2) Loss Stage: A Loss Manifold Reshaping (LMR) mechanism is established utilizing dual-branch constraints to suppress background gradients and enhance small target localization; and (3) Optimization Stage: A Decoupled Dynamic Scheduling (DDS) strategy is implemented, integrating AdamW with cosine annealing to ensure smooth convergence on small-sample data. Experimental results demonstrate that POD-YOLO achieves a 9.7% precision gain over the baseline and 83.08% recall, all while maintaining a low computational cost of 8.4 GFLOPs. This study validates the feasibility of exploiting the potential of lightweight architectures through optimization dynamics, offering an efficient paradigm for edge-based intelligent plant protection. Full article

The time-scale mismatch between rapid influent fluctuations and slow biochemical responses hinders the stability of wastewater treatment plants (WWTPs). Existing models often fail to capture shock signals due to noise interference (“signal pollution”). To address this, we propose the HD-MAED-LSTM model, which employs a “decompose-and-conquer” strategy. Targeting the dynamic characteristics of different components, this study innovatively designs heterogeneous attention mechanisms: utilizing Long-term Dependency Attention to capture the global evolution of the trend component, employing Multi-scale Periodic Attention to reinforce the cyclic patterns of the seasonal component, and using Gated Anomaly Attention to keenly capture sudden shocks in the residual component. In a case study, the effectiveness of the proposed model was validated based on one year of operational data from a large-scale industrial WWTP. HD-MAED-LSTM outperformed baseline models such as Transformer and LSTM in the medium-to-long-term (10-h) prediction of COD, TN, and TP, clearly demonstrating the positive role of differentiated modeling. Notably, in the core task of shock load early warning, the model achieved an F1-Score of 0.83 (superior to Transformer’s 0.77 and LSTM’s 0.67), and a Mean Directional Accuracy (MDA) as high as 0.93. Ablation studies confirm that the specialized attention mechanism is the key performance driver, reducing the Mean Absolute Error (MAE) by 56.7%. This framework provides precise support for shifting WWTPs from passive response to proactive control. Full article

Campus community gardens are expected to leverage disciplinary resources and spatial conditions to deliver ecological, educational, and social benefits beyond those of general community gardens. In China, these gardens are primarily established under the guidance of educational authorities, leading to issues such as significant homogenization and a lack of diversity, which hinders the full realization of their potential. This study investigates the potential factors influencing the development of campus gardens. Focusing on university campuses in Beijing, it employs stratified sampling and a questionnaire survey (n = 1008), utilizing methods including exploratory factor analysis (EFA), multiple linear regression, and analysis of variance (ANOVA) to systematically identify the factors affecting their differentiated development. The results indicate that: (1) the willingness to participate is collectively driven by four dimensions: “planting expectation,” “funding and site selection,” “personal motivation,” and “organizational support,” with “planting expectation” being the most significant factor. (2) Students’ academic disciplines influence their perceptions of the need for organizational support and spatial resources for gardens. (3) Campus location and size moderate the demand for gardens, with students in the urban expansion belt (between the 4th and 5th Ring Roads) and those from smaller campuses showing a stronger “pro-nature compensation” tendency. Based on campus spatial scale, urban location, and the academic backgrounds of participants, the study proposes integrated “space-organization” development strategies. This research provides targeted planning strategies for campus community gardens in China, aiming to leverage institutional disciplinary strengths, respond to participant needs, and maximize the gardens’ benefits. Full article

Speed breeding represents a pivotal technology for enhancing crop breeding efficiency. This study systematically examined the regulation of LED light environments, planting density, and gibberellic acid (GA₃) on rice growth cycle progression in plant factories, establishing an integrated speed breeding protocol. The experimental design comprised three components: (1) coupling seedling age (9–25 days, variety-dependent) with LED environments and planting densities (25–100 plants/tray); (2) combining light intensity gradients (450 and 900 μmol·m⁻²·s⁻¹) with photoperiod control; (3) applying GA₃ gradients (0–120 ppm) to enhance immature seed germination. Results indicated that high planting densities (>50 plants/tray) prolonged the growth cycle and decreased yield, whereas 25 plants/tray optimally balanced growth cycle shortening and yield maximization. Under short-day induction, Nipponbare (Nip) and Wufeng B (WFB) reached heading at 39 and 58 days after sowing (DAS), respectively. Stage-specific light responses were observed: 450 μmol·m⁻²·s⁻¹ during the basic vegetative phase (BVP) promoted morphological development, whereas 900 μmol·m⁻²·s⁻¹ during the photoperiod-sensitive phase (PSP) accelerated tillering and panicle differentiation. GA₃ treatment (60 ppm) enhanced the germination rate of immature seeds by 31%. The optimized lightregimes comprised natural light + 900 μmol·m⁻²·s⁻¹ (NL–900) and 450 μmol·m⁻²·s⁻¹ + 900 μmol·m⁻²·s⁻¹ (450–900), combined with density control (25 plants/tray) and GA₃-mediated immature seed utilization, shortened the generation time to 54 days and 70 days for Nip and WFB, respectively. This integrated protocol establishes an efficient strategy for rice speed breeding in plant factories. Full article

Understanding seasonal water acquisition strategies of desert plants is critical for predicting vegetation resilience under increasing hydrological stress in arid inland river basins. In hyper-arid oases, strong evaporative demand and declining groundwater levels impose tightly coupled constraints on plant water uptake across soil–plant–atmosphere continua. In this study, we combined hydrogen and oxygen stable isotopes, Bayesian mixing models, soil moisture measurements and groundwater monitoring, and leaf δ¹³C analysis to quantify monthly water-source contributions and long-term water-use efficiency of three dominant species (Reaumuria soongarica, Tamarix ramosissima, and Populus euphratica) in the Ejina Oasis. Clear ecohydrological niche differentiation was evident among the three species. R. soongarica exhibited moderate temporal flexibility by integrating shallow and deep soil water with episodic groundwater use, whereas T. ramosissima adopted a vertically integrated and hydraulically plastic strategy combining precipitation, multi-depth soil water, and groundwater. In contrast, P. euphratica followed a conservative strategy, relying predominantly on deep soil water with only minor and transient inputs from precipitation and groundwater. Across species and seasons, deep vadose-zone soil water (120–200 cm) consistently acted as the most stable and influential reservoir, buffering seasonal drought and sustaining transpiration. T. ramosissima maintained the highest intrinsic water-use efficiency, and P. euphratica exhibited consistently lower efficiency associated with sustained access to stable deep soil water. These contrasting strategies reveal multiple pathways of hydraulic stability and plasticity that underpin vegetation persistence under progressive groundwater depletion. By linking water-source partitioning with physiological regulation, this study provides a mechanistic basis for understanding plant water-use strategies and informs ecological water management and species-specific restoration in hyper-arid inland oases. Full article

The increasing demand for sustainable and clean-label foods has intensified the search for natural preservatives that are capable of replacing synthetic additives. In this study, an exploratory assessment of two distinct spruce needle aqueous extracts were conducted—an aqueous extract of Picea pungens (NWE-1) and an aqueous extract of Picea abies obtained after prior supercritical CO₂ treatment (NWE-2)—and both were investigated as potential bioactive ingredients for plant-based meat analogues. Using UPLC–MS, both extracts were comprehensively characterized, revealing a diverse array of phenolic acids, flavonoids, and glycosides. Even though NWE-2 contained a broader range of bioactive compounds, NWE-1 exhibited superior antibacterial performance (total microbial count (TMC)—4.94 log CFU/g), effectively limiting microbial contamination and ensuring product stability for up to 16 days of storage below the typical spoilage threshold (6.0–7.0 log CFU/g). Sensory analysis indicated that the model plant-based meat analogue matrix tolerated up to 3% (w/w) inclusion of NWE-1 and 5% (w/w) inclusion of NWE-2 before significant degradation of flavor and overall acceptability occurred. By utilizing conifer needles as an underexploited side-stream biomass, this work offers an approach for the valorization of conifer needle material through combined green extraction and food application, contributing to circular and resource-efficient processing concepts. The study provides an exploratory perspective on the potential role of forest-derived resources in the development of natural preservatives and their possible contribution to more sustainable food preservation strategies within a circular bioeconomy framework. Full article

Biochar is known to enhance soil potassium (K) availability and promote plant K uptake; however, its influence on the transformation pathways of fertilizer potassium and the mechanisms regulating crop potassium accumulation remains insufficiently understood. This study conducted a pot experiment using three soil types—Albic, Brown, and Sandy soils—with different biochar application rates (0, 10, and 20 g·kg⁻¹) in combination with potassium fertilizer, to systematically evaluate the regulation of soil K forms, K fertilizer transformation rates, K use efficiency, and K uptake and accumulation in soybeans. The results demonstrated that the combined application of biochar and K fertilizer significantly increased the contents of available, water-soluble, exchangeable, and non-exchangeable K across all three soils. At the highest biochar application rate (20 g·kg⁻¹), available K increased by 15.37%, 16.78%, and 11.77% in the Albic, Sandy, and Brown soils, respectively, compared to the control. Furthermore, biochar altered the transformation pathways of fertilizer K; it consistently reduced the conversion rate of fertilizer K into exchangeable K across all soils, redirecting it toward the water-soluble and non-exchangeable K pools, thus functioning as a potassium “scheduling center”. Adsorption–desorption experiments revealed that biochar exhibits a strong multilayer adsorption capacity for K ions, with most of the adsorbed K not easily desorbed, providing mechanistic support for the observed shift in transformation pathways. In terms of K use efficiency, biochar reduced the K of agronomic efficiency (KAE) due to a “dilution effect” from its inherent K content. Under the high application rate (20 g·kg⁻¹), the KAE decreased by 11.79% in Albic soil, 88.48% in Sandy soil, and 71.73% in Brown soil, while significantly increasing the partial factor productivity of K (PFPK) and apparent recovery efficiency of K (AREK). Ultimately, the co-application of biochar and K fertilizer significantly enhanced total K accumulation and seed yield in soybeans by increasing K concentrations in various plant parts and promoting dry matter accumulation. At the biochar application rate of 20 g·kg⁻¹, the potassium accumulation and soybean yield under biochar treatment reached maximum increases of 70.77% (in Brown soil) and 42.63% (in Albic soil), respectively. This study demonstrates that biochar can synergistically reduce potassium (K) leaching and improve fertilizer use efficiency by regulating K transformation pathways. This provides a practical guideline for utilizing biochar as a dual-function amendment, which acts as both a supplemental K source and a soil conditioner, thereby supporting the development of more sustainable potassium management practices in diverse cropping systems. Full article