Search Results (194)

A novel cellulose-degrading bacterial strain, D3-1, capable of degrading cellulose under medium- to high-temperature conditions, was isolated from soil samples and identified as Staphylococcus caprae through 16SrRNA gene sequencing. The strain’s cellulase production was optimized by controlling different factors, such as pH, temperature, incubation period, substrate concentration, nitrogen and carbon sources, and response surface methods. The results indicated that the optimal conditions for maximum cellulase activity were an incubation time of 91.7 h, a temperature of 41.8 °C, and a pH of 4.9, which resulted in a maximum cellulase activity of 16.67 U/mL, representing a 165% increase compared to pre-optimization levels. The above experiment showed that, when maize straw flour was utilized as a natural carbon source, strain D3-1 exhibited relatively high cellulase production. Furthermore, gas chromatography–mass spectrometry (GC-MS) analysis of products in the degradation liquid revealed the presence of primary sugars. The results indicated that, in the denitrification of simulated sewage, supplying maize straw flour degradation liquid (MSFDL) as the carbon source resulted in a carbon/nitrogen (C/N) ratio of 6:1 after a 24 h reaction with the denitrifying strain WH-01. The total nitrogen (TN) reduction was approximately 70 mg/L, which is equivalent to the removal efficiency observed in the glucose-fed denitrification process. Meanwhile, during a 4 h denitrification reaction in urban sewage without any denitrifying bacteria, but with MSFDL supplied as the carbon source, the TN removal efficiency reached 11 mg/L, which is approximately 70% of the efficiency of the glucose-fed denitrification process. Furthermore, experimental results revealed that strain D3-1 exhibits some capacity for nitrogen removal; when the cellulose-degrading strain D3-1 is combined with the denitrifying strain WH-01, the resulting TN removal rate surpasses that of a single denitrifying bacterium. In conclusion, as a carbon source in municipal sewage treatment, the degraded maize straw flour produced by strain D3-1 holds potential as a substitute for the glucose carbon source, and strain D3-1 has a synergistic effect with the denitrifying strain WH-01 on TN elimination. Thus, this research offers new insights and directions for advancement in environmental sewage treatment. Full article

Energy storage plays an essential role in stabilizing fluctuations in renewable energy sources such as wind and solar, enabling surplus electricity retention, and delivering dynamic frequency regulation. However, relying solely on a single form of storage often proves insufficient due to constraints in performance, capacity, and cost-effectiveness. To tackle frequency regulation challenges in remote desert-based renewable energy hubs—where traditional power infrastructure is unavailable—this study introduces a planning framework for an electro-hydrogen energy storage system with grid-forming capabilities, designed to supply both inertia and frequency response. At the system design stage, a direct current (DC) transmission network is modeled, integrating battery and hydrogen storage technologies. Using this configuration, the capacity settings for both grid-forming batteries and hydrogen units are optimized. This study then explores how hydrogen systems—comprising electrolyzers, storage tanks, and fuel cells—and grid-forming batteries contribute to inertial support. Virtual inertia models are established for each technology, enabling precise estimation of the total synthetic inertia provided. At the operational level, this study addresses stability concerns stemming from renewable generation variability by introducing three security indices. A joint optimization is performed for virtual inertia constants, which define the virtual inertia provided by energy storage systems to assist in frequency regulation, and primary frequency response parameters within the proposed storage scheme are optimized in this model. This enhances the frequency modulation potential of both systems and confirms the robustness of the proposed approach. Lastly, a real-world case study involving a 13 GW renewable energy base in Northwest China, connected via a ±10 GW HVDC export corridor, demonstrates the practical effectiveness of the optimization strategy and system configuration. Full article

Exploring the action mechanisms and enhancement pathways of the resilience of agricultural product green supply chains is conducive to strengthening the system’s risk resistance capacity and providing decision support for achieving the “dual carbon” goals. Based on theories such as dynamic capability theory and complex adaptive systems, this paper constructs a resilience framework covering the three stages of “steady-state maintenance–dynamic adjustment–continuous evolution” from both single and multiple perspectives. Combined with 768 units of multi-agent questionnaire data, it adopts Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the influencing factors of resilience and reveal the nonlinear mechanisms of resilience formation. Secondly, by integrating configurational analysis with machine learning, it innovatively constructs a resilience level prediction model based on fsQCA-XGBoost. The research findings are as follows: (1) fsQCA identifies a total of four high-resilience pathways, verifying the core proposition of “multiple conjunctural causality” in complex adaptive system theory; (2) compared with single algorithms such as Random Forest, Decision Tree, AdaBoost, ExtraTrees, and XGBoost, the fsQCA-XGBoost prediction method proposed in this paper achieves an optimization of 66% and over 150% in recall rate and positive sample identification, respectively. It reduces false negative risk omission by 50% and improves the ability to capture high-risk samples by three times, which verifies the feasibility and applicability of the fsQCA-XGBoost prediction method in the field of resilience prediction for agricultural product green supply chains. This research provides a risk prevention and control paradigm with both theoretical explanatory power and practical operability for agricultural product green supply chains, and promotes collaborative realization of the “carbon reduction–supply stability–efficiency improvement” goals, transforming them from policy vision to operational reality. Full article

(1) Background: The provision of monofunctional or inadequately distributed services in urban park green spaces often constrains residents’ opportunities and diversity for outdoor activities, particularly limiting access and participation for specific age groups or activity preferences. However, functional nodes with temporal and spatial flexibility demonstrate high-quality characteristics of resilient and shared services through integrated development. Accurately identifying user demand provides a solid basis for optimizing the functional configuration of urban parks. (2) Methods: This study took the old city area of Zhengzhou, Henan Province, China, as a case study. By collecting and integrating various types of data, such as geographic spatial data, field investigation data, and behavioral observations, we developed a population demand quantification method and a modular analysis approach for park service functions. This framework enabled correlation analysis between diverse user needs and park services. The study further classified and combined park functions into modular units, quantifying their elastic and shared service capabilities—namely, the adaptive flexibility and shared utilization capacity of park services. Additionally, we established a demand-responsive evaluation system for identifying and diagnosing problem areas in park services based on multi-source data. (3) Results: The demand response index and diagnostic results indicate that the supply of fitness facilities—particularly equipment-based installations—is insufficient within the old urban district of Zhengzhou. Among the three user groups—children, young and middle-aged adults, and the elderly—the elderly population exhibited the lowest demand response index, revealing a significant gap in meeting their specific needs. (4) Conclusions: Based on the research findings, a three-tier optimization strategy is proposed: A. improve green space connectivity to expand the service coverage of parks; B. implement multifunctional overlay and coordinated integration in spatial design based on site characteristics and demand diagnostics; and C. increase the total supply of facilities to enhance spatial efficiency in parks. By integrating the demand assessment data and diagnostic results, this approach enabled a data-driven reorganization of service types and targeted allocation of resources within existing park infrastructure, offering a practical tool and reference for the planning of urban outdoor activity spaces. Full article

Enhancing the load-adjustment flexibility of combined heat and power units facilitates the integration of renewable energy and enhances their profitability in dynamic electricity markets. However, the optimal coordination of various retrofitted combined heat and power units to maximize profitability has not been thoroughly investigated. To address this gap, this study conducts thermodynamic analysis and operation optimization for a combined heat and power plant integrated with flexibility retrofits, by developing models for the extraction-condensing unit, high back-pressure retrofitted unit, and low-pressure turbine zero output retrofitted unit. Results show that the low-pressure turbine zero output retrofitted unit achieves the largest energy efficiency (90.7%), while the extraction-condensing unit attains the highest exergy efficiency (38.0%). A plant-level optimization model is proposed to maximize profitability, demonstrating that the retrofitted combined heat and power plant increases total profit by 8.1% (CNY 86.4 million) compared to the original plant (CNY 79.9 million). The profit improvement stems from reduced coal consumption and enhanced heating capacity, enabling better power generation optimization. Furthermore, the study evaluates the profitability under different retrofit combinations. The findings reveal that an optimal profit can be achieved by reasonably coordinating the energy-saving characteristics of high back-pressure units, the heat supply capacity of low-pressure turbine zero output units, and the flexible adjustment capability of extraction-condensing units. Full article

Reasonable nitrogen fertilizer management and cultivation methods can enhance the nitrogen supply and carbon sequestration capabilities of soil, which is beneficial for meeting the growth requirements of crops and alleviating environmental issues. However, the existing research on optimizing nitrogen use efficiency and soil carbon sequestration in organic systems remains limited. Therefore, a field trial was conducted to elucidate the impacts of different cultivation patterns and nitrogen application rates on soil carbon and nitrogen pools, especially on how these factors affect the components of soil organic carbon. The treatments included conventional cultivation with low nitrogen treatment (CFN12), conventional cultivation with high nitrogen treatment (CFN18), organic cultivation with low nitrogen treatment (OFN12), and organic cultivation with high nitrogen treatment (OFN18). The results demonstrated that, relative to CFN18, OFN12 significantly increased the accumulation amounts of organic carbon and nitrogen in paddy soil. This was evident under multiple classifications of organic carbon, while it showed no advantage in the accumulation of mineral nitrogen. Notably, the organic cultivation mode increased the activities of enzymes involved in the carbon–nitrogen cycle in the cultivated layer and optimized the structure of humus, which gave the proportion of aggregates with a particle size greater than 0.5 mm more advantages. Correlation analysis demonstrated that the pertinent indices associated with soil carbon and nitrogen pools exhibited a highly significant positive correlation in the topsoil layer, accompanied by pronounced synergistic interactions among them. The PCA comprehensive scoring results indicate that OFN12 has the highest total score, indicating that it is beneficial for the improvement of soil fertility. This study offers practical insights for improving soil health, boosting plant growth, and enhancing climate mitigation through soil carbon storage, contributing to more sustainable agricultural practices. Full article

With the development of modern power systems, AC distribution networks face increasing demands for supply flexibility and reliability. Energy storage-based soft open points (E-SOPs), which integrate energy storage systems into the DC side of traditional SOP connecting AC distribution networks, not only maintain power flow control capabilities but also enhance system supply performance, providing a novel approach to AC distribution network fault recovery. To fully leverage the advantages of E-SOPs in handling faults in flexible interconnected AC distribution networks (FIDNs), this paper proposes an E-SOP-based FIDN islanding recovery method. First, the basic structure and control modes of SOPs for AC distribution networks are elaborated, and the E-SOP-based AC distribution network structure is analyzed. Second, with maximizing total load recovery as the objective function, the constraints of E-SOPs are comprehensively considered, and recovery priorities are established based on load importance classification. Then, a multi-dimensional improvement of the dung beetle optimizer (DBO) algorithm is implemented through Logistic chaotic mapping, adaptive parameter adjustment, elite learning mechanisms, and local search strategies, resulting in an efficient solution for AC distribution network power supply restoration. Finally, the proposed FIDN islanding partitioning and fault recovery methods are validated on a double-ended AC distribution network structure. Simulation results demonstrate that the improved DBO (IDBO) algorithm exhibits a superior optimization performance and the proposed method effectively enhances the load recovery capability of AC distribution networks, significantly improving the self-healing ability and operational reliability of AC distribution systems. Full article

As the primary force driving the sustainable development of the rural economy, the improvement of the total factor productivity (TFP) of agricultural enterprises (AEs) is of great strategic significance. This study innovatively zeroes in on AEs, leveraging micro-level data from agricultural listed companies in China’s A-share market spanning from 2007 to 2023. It aims to investigate the impact of supply chain finance (SCF) on the TFP of these enterprises and elucidate the underlying mechanisms. Uniquely, this study incorporates enterprise digital transformation and innovation capability as moderating variables into the mechanism analysis framework. Furthermore, it examines the heterogeneous effects across different characteristics of AEs. The findings reveal that SCF significantly boosts the TFP of AEs. Specifically, a one-standard-deviation increase in the level of SCF is associated with a 0.2658% increase in TFP relative to the mean. This conclusion holds robustly across various tests. Moreover, the interaction terms of SCF with both enterprise digital transformation and innovation capability are significantly positive. This indicates that greater digital transformation and stronger innovation capability amplify the positive effect of SCF on TFP. The heterogeneous analysis further indicates that for AEs with highly optimized human capital, higher financing constraints, and more efficient credit resource allocation, the positive impact of SCF on TFP is particularly pronounced. Full article

This article presents the development of a compact, high-precision, and energy-efficient temperature monitoring system designed for tracking applications where continuous and accurate thermal monitoring is essential. Built around the HY0020 System-on-Chip (SoC), the system integrates two bandgap-based temperature sensors—one internal to the SoC and one external (Si7020-A20)—mounted on a custom PCB and powered by a coin cell battery. A distinctive feature of the system is its support for real-time parameterization of the internal sensor, which enables advanced capabilities such as thermal profiling, cross-validation, and onboard diagnostics. The system was evaluated under both room temperature and refrigeration conditions, demonstrating high accuracy with the internal sensor showing an average error of 0.041 °C and −0.36 °C, respectively, and absolute errors below ±0.5 °C. With an average current draw of just 0.01727 mA, the system achieves an estimated autonomy of 6.6 years on a 1000 mAh battery. Data are transmitted via Bluetooth Low Energy (BLE) to a Raspberry Pi 4 gateway and forwarded to an IoT cloud platform for remote access and analysis. With a total cost of approximately EUR 20 and built entirely from commercially available components, this system offers a scalable and cost-effective solution for a wide range of temperature-sensitive applications. Its combination of precision, long-term autonomy, and advanced diagnostic capabilities make it suitable for deployment in diverse fields such as supply chain monitoring, environmental sensing, biomedical storage, and smart infrastructure—where reliable, low-maintenance thermal tracking is essential. Full article

Due to the unbalanced temporal and spatial distribution of the passenger flow on metro lines during peak hours, the implementation of passenger flow control strategies effectively ensures operational safety and travel efficiency for passengers. In this study, we analyze the coupling relationship between trains and passengers, introduce train-stopping state variables, and synergistically optimize both train operation schedules and station passenger flow control. Aiming to minimize the total passenger delay time and maximize the number of boarding passengers, we consider four constraints: the train operation process, the passenger entry process, the passenger–train interaction process, and system constraints. This framework enables us to construct a cooperative passenger flow control optimization model for oversaturated metro lines. Subsequently, we propose an improved artificial bee colony algorithm to solve this model. We utilize evolutionary operators and an enhanced tabu search to create new food sources for employed bees and enhance their local search capabilities during the employed phase. Finally, Shanghai Metro Line 9 is used as a case study for the model validation. The computational results indicate that the proposed Collaborative passenger flow control strategy significantly reduces the number of stranded passengers on platforms and decreases the total passenger delay time by 36.26% compared to the existing passenger flow control strategy. The findings demonstrate that the cooperative control strategy proposed in this paper can effectively alleviate the pressure from passenger flow on oversaturated lines, balance the asymmetry between supply and demand, and markedly improve both safety and efficiency in the metro system during peak hours. Full article

Governments often plan multiple fire stations simultaneously to improve firefighting capabilities, but constructing them within limited resources and time remains a challenge. A spatial decision support model is proposed in this study to determine the prioritized construction sequence of urban fire stations. Two simulation environments were established: one with only existing fire stations and another with both existing and proposed stations as fire service supply points (FSSPs). Response times were simulated using real-time traffic data. The construction urgency of the proposed fire stations was assessed using the construction sequence scoring equation. To validate the model, a case study of Shaoyang City, China, was conducted. A total of 30,968 fire service demand points were gathered, with 20 existing fire stations and 13 proposed fire stations designated as FSSPs. Twenty-five evaluation scenarios were established, resulting in 1,297,025 valid simulation results. The scoring results revealed a maximum score of 119,320, a minimum of 23,420, and an average of 61,412. Based on these results, recommendations for the construction sequence of proposed fire stations in Shaoyang City were made, and the improvements in fire protection levels were calculated. By prioritizing the construction of higher-performance fire stations, this model maximizes resource efficiency and enhances public safety. Full article

To further quantify the role of coal-fired power units in a wind–solar–thermal storage system and improve the construction of clean energy bases, this study examined the temporal production characteristics of wind and solar power and established an operational model for coal-fired power units within a wind–solar–thermal storage system. This approach ensured a stable electricity supply on the basis of power balance. The findings indicate that the correlation between the installed capacity of coal-fired power and the daily power supply capability of energy storage that meets various scheduled power demands can be obtained via the model. As the proportion of wind and solar power in the output power decreases, the influence of the minimum operational load of the coal-fired power units on the curtailment rate intensifies. Notably, the operational cost savings from reducing this minimum operational load surpass those obtained by either downsizing the installed capacity of coal-fired power units or energy storage devices. Among the parameters of this study, the lowest operational cost for the system was observed when wind and solar power generation constituted 76% of the total. This scenario, which ensured stable power output for 95% of the days in a year, had a wind and solar power curtailment rate of 11.3%. Additionally, the energy supplied by storage devices amounted to 1000 MWh, with the ratio of the installed capacity of coal-fired power to the total installed capacities of wind and solar power remaining at 25%. When the ratio of wind and solar power generation to output power was 91%, 76%, and 58%, a 1% reduction in coal consumption by coal-fired units during low-load operation resulted in a decrease in total system operating costs of 0.012%, 0.093%, and 0.089%, respectively. These findings provide valuable data support for the development of clean energy infrastructures. Full article

Distributed generation has emerged as a viable solution to supplement traditional grid problems and lessen their negative effects on the environment worldwide. Nevertheless, distributed generation issues are unpredictable and intermittent and impede the power system’s ability to operate effectively. Moreover, the problems associated with outliers and denial of service (DoS) attacks hinder energy management. Therefore, efficient energy management in grid-connected microgrids is critical to ensure sustainability, cost efficiency, and reliability in the presence of uncertainties, outliers, denial-of-service attacks, and false data injection attacks. This paper proposes a hybrid optimization approach that combines adaptive sheep flock optimization (ASFO) and gradient descent optimization (GDO) to address the challenges of energy dispatch and load balancing in MG. The ASFO algorithm offers robust global search capabilities to explore complex search spaces, while GDO safeguards precise local convergence to optimize the dispatch schedule and energy cost and maximize renewable energy utilization. The hybrid method ASFOGDO leverages the strengths of both algorithms to overcome the limitations of standalone approaches. Results demonstrate the efficiency of the proposed hybrid algorithm, achieving substantial improvements in energy efficiency and cost reduction compared to traditional methods like interior point optimization, gradient descent, branch and bound, and a population-based algorithm named Golden Jackal optimization. In case 1, the overall cost in scenario 1 and scenario 2 was reduced from 1620.4 rupees to 1422.84 rupees, whereas, in case 2, the total cost was reduced from 12,350 rupees to 12,017 rupees with the proposed hybrid ASFOGDO algorithm. Further, a detailed impact of attacks and outliers on scheduling, operational cost, and reliability of supply is presented in case 3. Full article

Currently, there is a need for dynamic space missions based on small satellites. These missions can be supported by propulsion systems with thrust-vectoring capabilities. This capability can be realized based on electrodeless plasma thrusters (EPTs). EPTs stand out for their versatility, offering adjustable thrust characteristics and fewer components, making them ideal for small satellites. However, their efficiency remains below optimal levels, largely due to complexities in plasma acceleration. This research aims to better understand dominant acceleration mechanisms in EPTs by studying ion energy distribution function changes based on exhaust orifice diameter and power variations. The total power supplied to the thruster varies in the range of 24 to 40 W, and the exhaust diameter varies in the range from 6.5 to 10.5 mm. It was found that the ion velocity does not change as a function of the diameter of the exit aperture. This indicates the insignificance of the mechanism of the gas-dynamic acceleration of plasma in EPTs with a small form factor and supports recent views that the main contribution to the acceleration of particles in EPT is made by electromagnetic effects. The findings could help refine EPT designs, enhancing their overall effectiveness and reliability for future space missions. Full article

Water and energy use, along with wastewater reuse, are critical for sustainable industrial production. This study develops a decision support framework (DSF) to assess wastewater treatment and reuse, incorporating Water and Carbon Footprint indicators. The framework is applied to a Greek brewery producing 1.4 × 10⁶ hL of beer annually, with a total water consumption of 5.6 hL per hL of beer and an in-house wastewater treatment plant (WWTP). The WWTP consumes over 40% more energy than expected, indicating a need for efficiency improvements. An advanced wastewater treatment method is proposed, capable of treating 43% of the total wastewater volume, with 3% covering the brewery’s utility water demand and the rest allocated to restricted irrigation. This reduces the operational Water Footprint by 12% and the supply chain Water Footprint by 1%, while increasing energy use by 3%. The optimal scenario, integrating water reuse and energy efficiency improvements, results in a 35% reduction in the Carbon Footprint, a 10% decrease in the operational Water Footprint, and a 1% reduction in the supply chain Water Footprint. The DSF provides a structured approach for industries to optimize sustainability by balancing water reuse with energy efficiency. Full article