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With the increased use of collaborative robots, a new production model of the human-robot collaborative hybrid assembly cell (HRCHAC) is becoming a new trend in customised production. Collaborative assembly between workers and robots in assembly cells can significantly increase productivity and improve the well-being of workers once the distribution of tasks and resources is optimised. This paper proposes a new integrated task allocation model to better utilise human-robot collaboration to increase productivity and improve worker well-being. The developed model enables the skills of both workers and robots to be fully utilised while ensuring economic efficiency and the effective protection of workers' physiological and psychological health. First, the product assembly process is decomposed into several assembly tasks, and the characteristics of each task are analysed. Second, a bi-objective mixed-integer planning model is developed with the objectives of minimising unit product assembly time and maximising total task matching. The ergonomics-related objectives are considered in terms of both the physiological and psychological fatigue of the worker, and relevant constraints are established. An improved NSGA-II algorithm is developed to determine the final task allocation scheme. Finally, the proposed method is applied to a real industrial case to verify the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

Under current conditions, ecological component is becoming increasingly important. Restoration of potential soil fertility by their saturation with organic matter of intermediate crop side-rates is the basis for growing environmentally friendly and high-quality products. Development and adaptation of effective agricultural technologies for growing potatoes in order to obtain organic products is an important scientific area today. One of the tasks of our research was to identify the payback of organic farming elements at current prices, in particular material resources directed on obtaining maximum and quality of potato harvest in the process of its growing. The results of farming and economic efficiency of using intermediate cultivation crops on green manure while growing potato are given. As a result of the conducted research was revealed positive influence of intermediate crops of sideral crops on economic efficiency of potato growing. Application of post-harvest Raphanus sativum siderate provided the highest yield of potato tubers - 30.9 t·ha-1 and starch yield - 4.08 t·ha-1. In the case of post-harvest Raphanus sativum siderate when growing potato, the highest net profit was obtained - 1369 €·ha-1 and an additional profit of 460 €·ha-1. Application of post-harvest Raphanus sativum siderate provided the lowest cost of potato growing - 36.35 €·t-1, and the highest profitability level of its cultivation - 121.7%, with a payback of additional costs - 0.43 €·t-1. [ABSTRACT FROM AUTHOR]

The development of technological processes for manufacturing machine tool parts with wear-resistant coatings deposited during their manufacturing is discussed. The performance features of tool parts during mechanical treatment of workpieces made of hard-to-cut materials is analyzed, and the use of gas-thermal coatings is substantiated to ensure the operational and technical characteristics of the products under consideration. [ABSTRACT FROM AUTHOR]

Under the new normal, the digital economy, as an essential engine of the new round of digital revolution, plays a significant role in driving the development of a green economy. This article constructs a logical framework from the perspective of economic agglomeration, using panel data from 2005 to 2019 in China's prefecture-level cities to empower green economic efficiency through the development of the digital economy. It then examines the enabling effect of the digital economy on green economic efficiency. The findings demonstrate that: (i) The digital economy has the potential to enhance the efficiency of the green economy, and this conclusion remains valid even after accounting for endogeneity and conducting a series of robustness tests. (ii) The results of the multi-mediation effect model demonstrate that enhancing economic agglomeration, facilitating industrial structure upgrade, and fostering technological innovation in energy saving and emission reduction serve as driving mechanisms for digital economic development to enhance urban green economic efficiency. (iii) In identifying heterogeneous characteristics, it was found that the enhancing effect of digital economic development on green economic efficiency is more pronounced in 'megacities', 'large', and 'medium' cities in eastern China, with better spillover effects. [ABSTRACT FROM AUTHOR]

The work is dedicated to the analysis of the efficiency of utilization of low-potential heat of the hydrogen complex at the NPP power unit. A new scheme for the integration of hydrogen technologies into an existing energy facility has been developed with an assessment of the economic efficiency of the event. It is shown that due to the utilization of low-potential heat obtained during the production of hydrogen by electrolysis, it is possible to increase the available capacity of nuclear power plants, which will ensure an increase in hydrogen production while reducing the cost. The object of integration, the Kola NPP, was selected and justified. Simulation modeling of the thermal circuit of a nuclear power plant power unit with a K-220-44 turbine unit in the United Cycle CAD, modeling of the hydrogen electrolysis process in the Aspen HYSYS program, with determination of the potential of waste heat in a hydrogen generating plant, as well as mathematical modeling using probabilistic estimation techniques to determine the main parameters of the economic efficiency of implementation, were chosen as research methods events. The paper estulates the theoretical possible volume of hydrogen generation at the Kola NPP, which amounted to 6.46 × 108 m3/year. An increase in power by 6.24 MW at the terminals of electric generators is shown due to the utilization of thermal energy of low potential electrolysis plants for two power units of the station. An assessment of the economic efficiency of the introduction of a heat recovery unit into the production cycle of a nuclear power plant has been carried out. An increase in the theoretical possible volume of hydrogen generation by 3 × 104 m3/day was obtained, which gives the expected annual economic effect from the introduction of the technology of 1.95 × 104 $/year. [ABSTRACT FROM AUTHOR]

Amid population growth and a shift from extensive to intensive shrimp farming, there may be a future reduction in extensive shrimp farming and mangrove forest areas. Understanding the correlation between land accumulation, economic efficiency, and potential losses is crucial. This study interviewed 311 black tiger shrimp farmers in the Mekong Delta, using one-step stochastic frontier analysis to estimate efficiency and investigate these correlations. Findings indicate an average economic efficiency of 82%, suggesting an 18% reduction in observed total costs. Economic losses, estimated at 82–465 USD/ha, were primarily seen in households with land areas below 2 ha. A positive correlation between land accumulation and economic efficiency suggests that maintaining a minimum pond area of 2 ha enhances income and mitigates losses. The study highlights the need for policies supporting land consolidation among shrimp farmers to achieve optimal pond sizes, reducing losses, and improving profitability, while promoting sustainable practices to balance shrimp farming with mangrove conservation. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. The objectives of this study were to evaluate associations of genetic change, cow management and nutrition, inbreeding, and crop yields from 1970 to 2020 with measures of production and economic efficiency according to a whole-farm model, and to evaluate effects of genetic change in individual traits on economic efficiency in comparison to expectations from economic selection indexes. Genetic and phenotypic performance metrics for Holsteins from 1970 and 2020 were retrieved and input into the Integrated Farm System Model (IFSM) for a 7,000-cow Texas herd and a 50-cow Pennsylvania grazing herd. Crop yields estimates from 1970 and 2020 were retrieved, and farm hectarage was altered so that forage and energy concentrate requirements were met through farm production; likewise, scenarios evaluating effects of atmospheric CO 2 fertilization (CO 2 F) on crop yield were evaluated by altering farm hectarage. For single traits that could be dynamically modeled by IFSM, performance shifts and resulting change in product prices or management expenses were added to 1970 base models. Economic efficiency was evaluated as the per-cow return to management and unpaid factors as compared with 1970 base models. As averaged across state scenarios, gains in economic efficiency were +$945 and −$76 for additive genetic and inbreeding effects, respectively, for a total gain from genetic change of +$869. Genetic gain in fat yield (+$549) and protein yield (+$524) were responsible for most of the genetic gain, whereas milk yield (−$128) and increased cow BW (−$129) depressed economic efficiency. Genetic change in productive life had a smaller effect (+$44) than predicted unless heifers were purchased and at double the default value. Gains due to cow management and nutrition increased efficiency by +$666 and crop yield increased efficiency by +$711, of which +$371 was attributed to CO 2 F across scenarios. Whole-farm DM efficiencies derived as the ratio of fat- and protein-corrected milk yield to DMI increased from 0.82 (PA) and 0.97 (TX) in 1970 to 1.20 in 2020 and could be higher if farms reduce the size of their replacement herd by producing beef calves. The landmass required in 2020 was 63% and 78% of the 1970 requirement for Texas and Pennsylvania, respectively. Changes in cow genetic merit, management and nutrition, and crop yields have all increased the economic and environmental sustainability of milk production, and systems such as IFSM could be a useful tool to help inform economic selection indices. [Display omitted] [ABSTRACT FROM AUTHOR]

The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable socio-economic development. The research focused on the Yangtze River Economic Belt (YREB) and employed the miniumum distance to strong efficient frontier DEA (MinDs) model to measure the green economic efficiency of the municipalities in the region between 2008 and 2020. Then, the spatial autocorrelation model was used to analyze the evolution characteristics of its spatial pattern. Finally, Geodetector was applied to reveal the drivers and their interactions on green economic efficiency. It is found that: 1) the overall green economic efficiency of the YREB from 2008 to 2020 shows a W-shaped fluctuating upward trend, green economic efficiency is greater in the downstream and smallest in the upstream; 2) the spatial distribution of green economic efficiency shows clustering characteristics, with multi-core clustering based on 'city clusters-central cities' becoming more obvious over time; the High-High agglomeration type is mainly clustered in Jiangsu and Zhejiang, while the Low-Low agglomeration type is clustered in the western Sichuan Plateau area and southwestern Yunnan; 3) from input-output factors, whether it is the YREB as a whole or the upper, middle and lower reaches regions, the economic development level, labor input, and capital investment are the leading factors in the spatial-temporal evolution of green economic efficiency, with the comprehensive influence of economic development level and pollution index being the most important interactive driving factor; 4) from socio-economic factors, information technology drivers such as government intervention, transportation accessibility, information infrastructure, and Internet penetration are always high impact influencers and dominant interaction factors for green economic efficiency in the YREB and the three major regions in the upper, middle and lower reaches. Accordingly, the article puts forward relevant policy recommendations in terms of formulating differentiated green transformation strategies, strengthening network leadership and information technology construction and coordinating multi-factor integrated development, which could provide useful reference for promoting synergistic green economic efficiency in the YREB. [ABSTRACT FROM AUTHOR]

Cloud computing has emerged as an efficient distribution platform in modern distributed computing offering scalability and flexibility. Task scheduling is considered as one of the main crucial aspects of cloud computing. The primary purpose of the task scheduling mechanism is to reduce the cost and makespan and determine which virtual machine (VM) needs to be selected to execute the task. It is widely acknowledged as a nondeterministic polynomial-time complete problem, necessitating the development of an efficient solution. This paper presents an innovative approach to task scheduling and allocation within cloud computing systems. Our focus lies on improving both the efficiency and cost-effectiveness of task execution, with a specific emphasis on optimizing makespan and resource utilization. This is achieved through the introduction of an Advanced Max–Min Algorithm, which builds upon traditional methodologies to significantly enhance performance metrics such as makespan, waiting time, and resource utilization. The selection of the Max–Min algorithm is rooted in its ability to strike a balance between task execution time and resource utilization, making it a suitable candidate for addressing the challenges of cloud task scheduling. Furthermore, a key contribution of this work is the integration of a cost-aware algorithm into the scheduling framework. This algorithm enables the effective management of task execution costs, ensuring alignment with user requirements while operating within the constraints of cloud service providers. The proposed method adjusts task allocation based on cost considerations dynamically. Additionally, the presented approach enhances the overall economic efficiency of cloud computing deployments. The findings demonstrate that the proposed Advanced Max–Min Algorithm outperforms the traditional Max–Min, Min–Min, and SJF algorithms with respect to makespan, waiting time, and resource utilization. [ABSTRACT FROM AUTHOR]

The aim of this work was to determine quantitatively the temperature uniformity of steel slab in high-temperature heating process under non-contact measuring conditions. Specifically, the temperature distribution of steel slab in heating process was obtained by infrared thermal imager, steel slab analog, and industrial image acquisition. The image isoline method was utilized to extract the non-uniform temperature region and temperature gradient of the steel slab. The local discrepancy function was used to measure the temperature uniformity of steel slab surface. Results showed that the problem of internal thermal conductivity of the steel slabs was reflected on the surface. The temperature of the cross section raised more slowly than that of the surface, but the temperature distribution was more uniform. More attention should be paid to the temperature distribution of the smaller surface and cross section rather than larger ones. The temperature uniformity degree of the surface of the steel slab samples from open literature was quantified respectively by 0.95, 0.92, 0.91, and 0.98. The steel slab with better quality would be obtained since the non-uniform heating could be adjusted according to the understanding of the distribution characteristics of the temperature field of the steel slab. This work was probably of great significance to increase the qualified steel slab, reduce scrap rate, and improve economic efficiency. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate efficient, cost‐effective, and high‐quality drying technologies for Rosa roxburghii Tratt. Five drying methods—hot air drying (HAD), microwave drying (MD), vacuum drying (VD), microwave vacuum drying (MVD), and freeze vacuum drying (FVD), were employed to dry Rosa roxburghii Tratt. The study focused on evaluating drying characteristics, colors, texture and structure, and microstructure, as well as the content of active ingredients and antioxidant activity of Rosa roxburghii Tratt. The results of drying kinetics indicated that the Wang and Singh model was the most suitable for FVD, while the Page model was optimal for the other four drying methods. Rosa roxburghii Tratt subjected to HAD exhibited the highest energy consumption per unit but the lowest ΔE and the highest TFC. The microstructure of Rosa roxburghii Tratt under different drying methods was analyzed. Rosa roxburghii Tratt dried using MD experienced serious cell rupture, resulting in a large loss of active ingredients and the worst antioxidant ability, but it had the fastest drying rate. On the other hand, Rosa roxburghii Tratt dried under VD had the microstructure with the least pore space, leading to slower drying speed and the highest total polyphenol content. Rosa roxburghii Tratt dried using MVD had the least hardness and chewiness, with slightly better ΔE and active ingredient content compared to MD. FVD Rosa roxburghii Tratt took the longest time to dry, with the greatest ΔE difference, hardness, and chewiness, but it had the highest Vitamin C content and the most powerful antioxidant ability. Principal component analysis (PCA)–entropy weighting method was used to provide comprehensive scores for the different drying methods, with FVD, HAD, VD, MVD, and MD were 0.8107, 0.7037, 0.4499, 0.2746, and 0.0586 respectively. Through comprehensive analysis, we demonstrated that the quality of Rosa roxburghii Tratt obtained via FVD and HAD is satisfactory. Additionally, HAD is characterized by its economic efficiency and convenience, providing valuable insights for the industrial production of Rosa roxburghii Tratt drying. [ABSTRACT FROM AUTHOR]

Introduction: Farm mechanization has multi-dimensional impacts on agricultural production systems like economic efficiency and productivity, thereby improving the quality of life in the farming community by reducing work drudgeries. However, these impacts were not studied empirically in Ethiopia. Hence, this research was initiated to estimate the level of economic efficiency, and productivity of wheat and barley, and the impact of farm mechanization on economic efficiency and productivity of wheat and barley. Methods: The analysis was done for 232 and 257 wheat and barley producer farmers respectively who are selected from the Arsi and West Arsi zones. The stochastic frontier model was used to estimate economic efficiency while augmented inverse probability weighted (AIPW) was used to estimate the impact. Results and discussion: Based on the result, it is apparent that farm mechanization has a significant positive impact on wheat productivity while the percentage change in average treatment effect for the barley was not statistically significant. Farm mechanization also affects wheat and barley economic efficiency positively. Hence, we recommended the wider use of farm mechanization to improve economic efficiency and productivity. Therefore, policy design should focus on ways to avail farm machinery easily like establishing farm mechanization service centers and facilitating credit services for mechanization service renders. [ABSTRACT FROM AUTHOR]

Introductions: The cultural industry is pivotal in promoting sustainable economic development. This study aims to evaluate the economic efficiency of the cultural industry in Jiangsu Province by establishing a Data Envelopment Analysis (DEA) model and analyzing influencing factors using the Tobit model, all within the broader context of China's cultural industry. Methods: A DEA model was developed to assess the economic efficiency of the cultural industry across Chinese provinces, allowing for a comparative analysis of performance. The Tobit regression model was utilized to investigate factors influencing these efficiency outcomes, with a particular emphasis on inter-provincial comparisons to understand the position and challenges faced by Jiangsu's cultural industry. Results: Despite Jiangsu's cultural industry ranking among the largest in scale nationally, its economic efficiency is only moderate, consistently experiencing diminishing returns to scale. The study identifies low scale efficiency, small enterprise size, and suboptimal urbanization processes within the province as the main issues. Discussion: The inefficiencies highlighted by the DEA model suggest a misalignment between the scale of operations and the economic outputs in Jiangsu's cultural industry. Urbanization emerges as a crucial factor, with current practices not sufficiently supporting the growth potential of the cultural sector. Conclusion: Based on these findings, the study proposes targeted policy recommendations for Jiangsu, including avoiding blind scale expansion, adjusting industrial structures, encouraging enterprise consolidation and optimization, and identifying new growth areas to better support the cultural industry's development and contribute to sustainable economic progress. [ABSTRACT FROM AUTHOR]

The uncoordinated integration of numerous distributed resources poses significant challenges to the safe and stable operation of distribution networks. To address the uncertainties associated with the intermittent output of distributed power sources, we propose a multi-objective planning strategy for distribution networks based on distributionally robust model predictive control (MPC). Initially, an error fuzzy set is established on a Wasserstein sphere using historical data to enhance out-of-sample performance. Next, a multi-objective optimization framework is constructed, balancing returns and risks, and is subsequently converted into a single-objective solution using value-at-risk conditions. This is followed by the implementation of multi-step rolling optimization within the model predictive control framework. We have linearized the proposed model using the linearized power flow method and conducted a thorough validation on an enhanced IEEE 37-node test system. Distributionally robust optimization (DRO) has been shown to reduce costs by a significant 29.16% when compared to an RO method. Moreover, the energy storage capacity required has been notably reduced by 33.33% on the 29-node system and by 20% on the 35-node system. These quantified results not only demonstrate the substantial economic efficiency gains but also the enhanced robustness of our proposed planning under the uncertainties associated with renewable energy integration. [ABSTRACT FROM AUTHOR]

To address the issue of accommodating large-scale wind power integration into the grid, a unit commitment model for power systems based on an improved binary particle swarm optimization algorithm is proposed, considering frequency constraints and demand response (DR). First, incentive-based DR and price-based DR are introduced to enhance the flexibility of the demand side. To ensure the system can provide frequency support, the unit commitment model incorporates constraints such as the rate of change of frequency, frequency nadir, steady-state frequency deviation, and fast frequency response. Next, for the unit commitment planning problem, the binary particle swarm optimization algorithm is employed to solve the mixed nonlinear programming model of unit commitment, thus obtaining the minimum operating cost. The results show that after considering DR, the load becomes smoother compared to the scenario without DR participation, the overall level of load power is lower, and the frequency meets the safety constraint requirements. The results indicate that a comparative analysis of unit commitment in power systems under different scenarios verifies that DR can promote rational allocation of electricity load by users, thereby improving the operational flexibility and economic efficiency of the power system. In addition, the frequency variation considering frequency safety constraints has also been significantly improved. The improved binary particle swarm optimization algorithm has promising application prospects in solving the accommodation problem brought by large-scale wind power integration. [ABSTRACT FROM AUTHOR]

As the penetration of distributed renewable energy continues to increase in distribution networks, the traditional scheduling model that the inertia and primary frequency support of distribution networks are completely dependent on the transmission grid will place enormous regulatory pressure on the transmission grid and hinder the active regulation capabilities of distribution networks. To address this issue, this paper proposes a coordinated optimization method for distribution networks and microgrid clusters considering frequency constraints. First, the confidence interval of disturbances was determined based on historical forecast deviation data. On this basis, a second-order cone programming model for distribution networks with embedded frequency security constraints was established. Then, microgrids performed economic dispatch considering the reserves requirement to provide inertia and primary frequency support, and a stochastic optimization model with conditional value-at-risk was built to address uncertainties. Finally, a cooperative game between the distribution network and microgrid clusters was established, determining the reserve capacity provided by each microgrid and the corresponding prices through Nash bargaining. The model was further transformed into two sub-problems, which were solved in a distributed manner using the ADMM algorithm. The effectiveness of the proposed method in enhancing the operational security and economic efficiency of the distribution networks is validated through simulation analysis. [ABSTRACT FROM AUTHOR]

With the continuous penetration of flexible resources, the distribution network is gradually forming a two-way interactive supply and demand relationship with the transmission network and users. The deployment of soft open point (SOP) and energy storage represents a crucial strategy for voltage regulation and power flow control in distribution networks. This article puts forth a methodology for optimizing the configuration of SOP and energy storage based on the characteristics of the snowflake-shaped grid and sensitivity analysis. Firstly, the location of the SOP is determined based on the characteristics of the interconnection nodes between snowflake websites. Secondly, the voltage sensitivity analysis is employed to identify nodes that have a significant impact on the system voltage distribution, thereby enabling the selection of an optimal energy storage site. Subsequently, a multi-objective optimization configuration model for SOP and energy storage is established, taking into account the economic efficiency and load balancing of the power grid. Finally, the method is verified using a snowflake-shaped grid in Tianjin. In comparison with the plan that solely considers the economic aspects of the power grid, the method proposed in this article can reduce the degree of load balancing by 50.93% while simultaneously increasing the annual comprehensive cost by only 24.35%. [ABSTRACT FROM AUTHOR]

Considering the effect of surrounding rock on lining in the design of tunnel lining within fractured rock masses is challenging, particularly in accurately predicting the reserved deformation of the tunnel. This study bases a rock mass classification method and the established Hoek–Brown (H-B) strength criterion to assess the deformation characteristics of the surrounding rock. It establishes a more scientifically rigorous theoretical calculation method for the reserved deformation of tunnel linings that accounts for the rock–lining interaction. An optimization design approach for the lining structure, based on the synergistic effect and considering the stress safety of the concrete lining and the rock's displacement release rate, is proposed. Case analysis is utilized to validate the safety of the lining design in the study section through computational verification. The recommended optimized lining parameters are identified: the support time is initiated when the tunnel wall's surrounding rock deforms by 9 mm, and the lining thickness is optimized to 47 cm, which is approximately 36.5% less than the pre-optimization thickness. This precise optimization of support timing and lining thickness enhances both the safety and economic efficiency of the Wufengshan Tunnel. The method allows for the calculation of the optimal combination of support time and lining thickness tailored to different surrounding rock conditions, offering significant reference value for tunnel lining optimization. [ABSTRACT FROM AUTHOR]

As traditional power grids are unable to meet growing demand, extensive research on multi-microgrid scheduling has begun to address the issues present in conventional power grids. However, existing studies on the scheduling of grid-connected multi-microgrids still lack sufficient focus on system demand-side and interaction-side aspects. At the same time, the uncertainties of renewable energy and demand-side responses further complicate this research. To address this, this paper proposes an operational scheduling strategy based on an improved differential evolution algorithm, aiming to incorporate power interactions between microgrids, demand-side responses, and the uncertainties of renewable energy, thus enhancing the operational reliability and economic efficiency of multi-microgrid systems. The research in this paper is divided into the following steps: (1) constructing a multi-microgrid model primarily based on renewable energy; (2) formulating an optimization model with the objective of minimizing economic costs while ensuring stable system operation and solving it; (3) proposing an improved differential evolution algorithm for optimizing system scheduling; (4) testing and validating the improved differential algorithm; and (5) designing an operational strategy that accounts for the uncertainties of renewable energy and load demand. Through the application of real-world cases, the feasibility and effectiveness of the operational scheduling strategy based on the improved differential evolution algorithm are verified. [ABSTRACT FROM AUTHOR]

To enhance the transmission capabilities in power system scheduling, this paper develops a unit commitment model that incorporates dynamic transmission line capacities and proposes an efficient solving algorithm. A multi-scenario unit commitment model that integrates dynamic transmission line capacities is introduced, using quantile regression to construct a data-driven capacity increase model based on historical environmental data. The model is solved using Lagrangian relaxation and the Alternating Direction Method of Multipliers (ADMM) to decouple dynamic constraints, allowing the dual problem to be decomposed into sub-problems and solved iteratively. The proposed model and algorithm are validated using the IEEE-118 and IEEE-300 test cases, demonstrating their effectiveness in handling dynamic transmission line capacities and improving scheduling performance.The approach provides a robust and flexible solution for power system scheduling, enhancing reliability and economic efficiency. [ABSTRACT FROM AUTHOR]

The energy industry has a significant impact on the scarce fossil hydrocarbon resources and on the environment. The burning of natural energy carriers by traditional energy facilities is one of the factors increasing the content of greenhouse gases in the atmosphere that entails serious climate changes. Evaluating the efficiency of energy enterprises and the implementation of energy projects requires an integrated approach that considers not only technical and economic aspects, but also the environmental impact. Such approach is especially important in the context of the energy transition and the implementation of circular economy principles. Despite the attention of scientists to the tasks of scientific, methodological, and practical determination of the economic efficiency and environmental consequences of energy projects, the issue of environmental and economic assessment remains relevant, in particular considering resource and environmental efficiency. The purpose of this study is to improve the methodological tools of environmental and economic assessment of energy projects. The authors propose an approach to the assessment of energy projects using an integral indicator. This indicator is calculated based on a system of specific indicators of the natural resource capacity and the environmental compatibility of energy production at the energy facility, considering the regional environmental conditions. The formed approach can be used for environmental and economic assessment and comparison of energy projects, fast-acting measures, and projects for the development of energy enterprises. [ABSTRACT FROM AUTHOR]

This study evaluated the effect of four different feeding regimes on the growth, health, economic effiency and perception of aquaculturists regarding Oreochromis sp. in the Guayas Province, Ecuador. Four treatments based on different feeding regimes were established: T1, once a day with a daily interval; T2, once a day with an interval every two days; T3, twice a day with a daily interval; and T4, twice a day with an interval every two days. Growth parameters such as total fish weight gain, average daily weight gain, daily feed intake, expected weight gain for each daily feed intake, feed conversion ratio, protein efficiency, and protein productive value were measured. Health parameters included serum total protein content, albumin, serum globulins, cholesterol, triglycerides, and glucose levels. Economic efficiency parameters such as feed cost and feed cost per kilogram of weight gain were also assessed. Additionally, surveys were conducted with aquaculturists to assess the perception of aquaculture farmers regarding the importance of growth factors, fish health, and economic efficiency in the selection of feeding regimes for Oreochromis sp. The results indicated that treatment T3 was the most effective in maximizing growth; treatment T1 excelled in fish health; and treatment T2 was the most economically efficient. In conclusion, the choice of feeding regime will depend on the farmers' priorities, with a general trend, according to the survey, toward economic efficiency and growth, while fish health, although relevant, is a secondary priority. [ABSTRACT FROM AUTHOR]

Objective • This study aims to assess the impact of details management on the handling of instruments in the operating room, comprehensively evaluating its impact on device intactness, economic efficiency, overall care quality, and physician satisfaction. Methods • We analyzed 1050 procedural packs used in our hospital from March to December 2019. The control group included 525 procedural packs with conventional management (March-August 2019), while the experimental group had 525 instrument packs with details management. Outcome measures included operating room device use, surgical care quality, and device tracking outcome. Results • Details management showed significantly higher device intactness (97.73%), a marked decrease in device preparation errors (0.00%), and more efficient device checking time (1.13±0.41) compared to conventional management (84.09%, 11.36%, 2.85±1.03) (P < .05). The experimental group had higher scores in intraoperative nursing ability, nursing operating specification, nursing staff professionalism, and device care quality (9.08±0.31, 9.23±0.32, 9.17±0.55, 97.81±0.96) compared to the control group (8.11±0.67, 7.98±0.98, 8.35±0.69, 75.25±1.87) (P < .05). Details management was associated with higher economic efficiency and lower incidences of device loss and mix-up compared to conventional management (P < .05). Conclusions • Implementing details management in instrument handling positively affects device intactness, economic efficiency, overall care quality, and physician satisfaction. It enhances device intactness, reduces device checking time, improves economic efficiency and overall care quality, and increases physician satisfaction. The findings provide insights into the benefits of a detailed instrument management approach in a hospital setting. [ABSTRACT FROM AUTHOR]

The use of wireless technology in common marine engineering applications as a medium for data transaction in measurement and control systems, is not as popular as it should be. This article aims to demonstrate the advantages of using wireless technology in maritime engineering applications through a proposed Wi-Fi based wireless system dedicated to performance and safety monitoring in marine cargo cranes. The system is based on some concepts that were suggested in the earlier literature to perform authenticated data transmission from multiple sensors through using both the ESP-NOW protocol and the WebSerial remote serial monitor. The introduced system will be integrated with an already installed system in order to render the means for implementing effective principles in automation and control engineering, such as functional safety and predictive maintenance. Additionally, this article will highlight the economic efficiency of adopting wireless technology instead of cabling as a medium for data transaction in measurement and control systems in marine engineering applications such as cargo cranes. [ABSTRACT FROM AUTHOR]

The increase in new energy grid connections has reduced the supply-side regulation capability of the power system. Traditional economic dispatch methods are insufficient for addressing the flexibility limitations in the system's balancing capabilities. Consequently, this study presents a day-ahead scheduling method for renewable energy systems that balances flexibility and economy. This approach establishes a dual-layer optimized scheduling model. The upper-layer model focuses on the economic efficiency of unit start-up and shut-down, utilizing a particle swarm algorithm to identify unit combinations that comply with minimum start-up and shut-down time constraints. In contrast, the lower-layer model addresses the dual uncertainties of generation and load. It employs the Generalized Polynomial Chaos approximation to create an opportunity-constrained model aimed at minimizing unit generation and curtailment costs while maximizing flexibility supply capability. Additionally, it calculates the probability of flexibility supply-demand insufficiency due to uncertainties in demand response resource supply and system operating costs, providing feedback to the upper-layer model. Ultimately, through iterative solutions of the upper and lower models, a day-ahead scheduling plan that effectively balances flexibility and economy is derived. The proposed method is validated using a simulation of the IEEE 30-bus system case study, demonstrating its capability to balance system flexibility and economy while effectively reducing the risk of insufficient supply-demand balance. [ABSTRACT FROM AUTHOR]

The academic publishing market is characterized by its oligopolistic market structure. Two aspects are particularly striking: Few large commercial publishers have high market shares in almost all research disciplines. This is reflected in high subscription and publication costs. At the same time, the majority of work for the journals is provided free of charge by researchers. The paradox can be explained by the tremendous importance of leading journals for researchers. Publishers turn this into market power. While key stakeholders in the market are primarily focusing on open access and open science, I argue in this article that competition plays a key role in increasing not only economic efficiency but also diversity and the participation of researchers. One exceptional option would be to shift the now-established "pay per article" system back to subscription models. [ABSTRACT FROM AUTHOR]

After Tunisia's independence from France in 1956, the country was engaged in what has been termed the "supply management policy", that is, a maximum mobilization of water resources through large‐scale modern hydraulic infrastructure. Towards the beginning of the 1980s, the country entered a crisis and had to adopt in 1986, under pressure from the International Monetary Fund and the World Bank, a "Structural Adjustment Program" (SAP) that prioritized measures to improve economic efficiency and liberalize the economy. Since then, Tunisian water policy has progressively shifted towards "Integrated Water Resources Management" (IWRM). This review critically analyzes the water governance discourses that have framed these policy interventions. I will draw on academic research and official and civil society reports to suggest that these discourses have been "rendered technical", stripping issues of any political (and therefore conflicting) character. When rendered technical discourses raise development projects and policies above the terrain of political contestation, the possibilities of action available to those opposed to them become limited. This depoliticization of development interventions through technical discourses narrows the public space of democratic debate. I will also argue that the "technification" (rendering technical) process is reversible. Opposition groups can challenge technical discourses with a critical approach that can reconfigure and alter the trajectory of governmental programs. However, critical discourses can, in turn, be rendered technical. This article is categorized under:Human Water > Water GovernanceHuman Water > Rights to Water [ABSTRACT FROM AUTHOR]

The global energy era is accelerating ahead of schedule. At the urban level, can large-scale utilization of renewable energy in cities promote energy consumption reduction and economic cost saving, improving energy economic efficiency (EEE)? Based on balanced panel data for 260 prefecture-level cities in China from 2010 to 2020, we used data envelope analysis (DEA) window analysis and difference-in-differences and propensity score matching to evaluate the effect of the New Energy Demonstration City Program on urban EEE. We found that the policy promoted the improvement of urban EEE. However, there is specific regional heterogeneity in the policy effects, with this policy having a more significant effect on EEE improvements in the Northeast, cities with high pollution levels, and cities with high-tech innovation levels. These findings have significant policy implications for supporting the country in promoting the development and utilization of new energy sources to improve EEE. [ABSTRACT FROM AUTHOR]

Investigating the relationship between green finance (GF), government environmental governance (GEG), and green economic efficiency (GEE) is essential for developing sustainable development policies. This study uses panel data from 30 provincial administrative regions in China, covering the period from 2011 to 2021, to assess the effects of GF and GEG on GEE through the Spatial Durbin Model. The findings reveal several key points. First, most provinces are in low-low spatial clusters in terms of GEE, though there is a gradual improvement over time. Second, GF significantly enhances GEE, while GEG has a notable inhibitory effect. Third, GF exhibits a positive spatial spillover effect on the GEE of neighboring regions, whereas GEG shows a negative spatial spillover effect. Fourth, these spillover effects are mainly observed in the eastern regions, with little significance in the central and western areas. Moreover, one of the GEG indicators, environmental regulation, demonstrates a positive spatial spillover effect in the eastern region, contrary to the overall negative national trend. In general, this paper examines the interplay among the three variables within a unified analytical framework, filling the gaps in existing research. Furthermore, the paper delineates GEG into environmental regulation and environmental investment, which is a dimension frequently neglected in current research. [ABSTRACT FROM AUTHOR]

Cost overruns are a significant issue in infrastructure projects, adversely affecting not only economic performance but also sustainability goals by straining resources and extending project timelines. There is consensus among researchers about the persistence of cost overruns and the importance of accurate estimates. However, there are significant differences in the explanation of the reasons for the overruns. While we recognize the importance of understanding the reasons for cost overruns at all stages of project development, we have focused on the reasons for cost overruns after contract award due to the rarely available real and valid data collected at the source of the information. We analyze the deviations between actual and contracted costs, as well as the dependence of cost deviations of individual project types on the size of the contract. For example, the size of the tunnel significantly affects relative cost deviations, while for standard viaducts or road sections this effect is minimal. The results confirmed that cost overruns are less frequent in standard facilities than in those where the experience factor has little influence on the final cost estimate. For example, deviations in the average value of the contracted costs for highway sections range between −12.1% and 27.9% of the contracted value, and for standardized viaduct projects they range between −16.73% and 6.27% of the contracted value. The type of distribution function of deviations between actual and contractually agreed costs was investigated, and a predictive model for estimating future cost deviations of project programs was presented. The goal is to improve economic sustainability and the related optimization of resources in the development of infrastructure, which contributes to the broader agenda of sustainable development. The results encourage the adoption of improved project documentation and forecasting tools, which are essential for sustainable project management. [ABSTRACT FROM AUTHOR]

When is state coercion for the provision of public goods justified? And how should the social surplus of public goods be distributed? Philosophers approach these questions by distinguishing between essential and discretionary public goods. This article explains the intractability of this distinction, and presents two upshots. First, if governments provide configurations of public goods that simultaneously serve essential and discretionary purposes, the scope for justifiable complaints by honest holdouts is narrower than commonly assumed. Second, however, claims to distributive fairness in the provision of public goods also turn out to be more complex to assess. [ABSTRACT FROM AUTHOR]

The digital economy enhances economic efficiency and improves economic structure, driving economic growth through transformations in efficiency, momentum, and quality. It has become a new driving force for advancing common prosperity. This study uses SDM, SDID, and SPSTR models to explore the impact of digital economy on common prosperity, which constructs the index system to evaluate the common prosperity from process index and outcome index. According to the panel data of 76 cities in the Yellow River Basin from 2011 to 2021, and the findings are as follows: (1) The digital economy exhibits a development pattern characterized by high activity downstream and lower activity upstream, and the development trend is stable. The development pattern of common prosperity has changed from sporadic distribution to regional agglomeration, and the level of common prosperity in most cities has improved. (2) The digital economy has a significant positive spatial effect on common prosperity. And the findings are robust after introducing the "Big Data" exogenous policy impact, dynamic SDM model, and other methods. Moreover, spatial heterogeneity exists. The promotion effect in the upper and lower reaches is stronger, while the middle reaches are weakly affected by the digital economy. (3) The spatial spillover effect of the digital economy on common prosperity has a boundary, and the positive spillover reaches a maximum value at 600–650 km. (4) Nonlinear analysis confirms that the digital economy provides momentum for common prosperity industrial structure optimization that can effectively stimulate the "endogenous" growth mechanism, strengthen the marginal increasing effect of the digital economy driving common prosperity and enhance the effect of "making a bigger pie". The digital economy makes effective use of digital resources and technologies, promotes the equalization of public services, exerts a positive impact on the realization of common prosperity, and consolidates the effect of "dividing a better cake". [ABSTRACT FROM AUTHOR]

This paper presents a day‐ahead scheduling for multi‐energy entities. The deep load regulation involving pumped storages, which refers to deep peak regulation, is adopted to address the impact of wind power and photovoltaic (PV) uncertainties, thereby improving the economic efficiencies of day‐ahead dispatching. And the impact of different peak valley electricity price differences on the peak shaving effectiveness of pumped storage energy was studied. Firstly, the multi‐scenario random programming method is applied to solve the prediction uncertainties of wind power and PV output in the day‐ahead. Subsequently, the multi‐scenario set of day‐ahead wind power and PV output and the load forecasting curve are considered. A pumped storage scheduling model is then established integrating the hydropower, thermal power and pumped storage. The optimal generation scheduling of pumped storage and thermal units is determined by minimizing load fluctuations and peak shaving costs. Finally, a local power grid in the Hunan province of China is selected for verification. It is shown that the proposed model can effectively accommodate the fluctuation of renewable energy output, reduce the peak regulating pressure of thermal units, and improve the operational economy of the power system. [ABSTRACT FROM AUTHOR]

Within a country, there are major differences between regions in terms of economic activity and socio-economic, cultural and environmental conditions. These interact to a considerable extent with people's preferences as to where they want to settle and the resulting (dis)agglomeration effects. Although people's decisions and migration movements may result in a spatial balance of individual benefits, political interference and regional transfers from economically stronger to economically weaker regions may be necessary in order to increase overall economic efficiency and ensure political distribution targets. However, as regional transfers are associated with economic costs, these must be carefully weighed against the potential welfare gains. [ABSTRACT FROM AUTHOR]

International climate finance institutions increasingly articulate their goals as catalyzing transformation, but can these institutions bring about deep structural change when they reflect the same liberal logics that arguably created the challenges they are designed to address? In this analysis, we use a virtual ethnography of Green Climate Fund (GCF) board meetings. We ask: how does the GCF navigate the tensions between different conceptualizations of transformation? Our sample included deliberations on 181 projects, and over 42 h of board meetings. Discussions were thematically coded to reveal concerns raised by board members and observers, followed by a structured content analysis. We found that while the transformational potential of proposals featured prominently in deliberations, there was no unified vision or clear definition of transformation. However, approaches that emphasized economic efficiency, technology and infrastructure, and market mechanisms and the private sector aligned with the liberal logic of the fund, while proposals that framed transformation in other ways faced more scrutiny. Board members and observers also raised concerns that proposals had the potential to increase vulnerability or cause harm. Despite this, almost all projects in our sample were approved, suggesting that more work is needed to expand beyond liberal understandings of transformation. [ABSTRACT FROM AUTHOR]

Purpose Method Results Conclusions Student‐led clinics generate a range of benefits to multiple stakeholder groups. Students receive important educational opportunities to advance in their training. Patients with limited access to care may access effective care or a higher amount of effective care and so reduce burden on the health care system. The financial viability of student‐led clinics run by universities is uncertain, and establishing this is complicated by the range of stakeholder costs and benefits that may be involved. This systematic review aimed to synthesise evidence related to the costs and benefits of student‐led clinics and report the methods that have been used to measure these costs and benefits.We conducted a systematic search of MEDLINE All, PsychInfo, CINAHL, A+ Education (Informit), ERIC (ProQuest) and ProQuest Education databases for studies that reported the costs and/or economic benefits of student‐led clinics from inception through August 2023. Studies were screened for eligibility, and data were extracted including study characteristics, student‐led clinic description and economic outcomes. A narrative synthesis was undertaken due to the heterogeneity of studies.Of 349 potentially eligible studies, 24 were included. Nine studies (38%) used an outcome description‐monetised approach; four used partial economic evaluation (17%); four employed cost description (17%); two used cost approximation (8%); two used cost analyses (8%); and one was a full economic analysis (4%). Studies examined costs or benefits, from the perspective of a range of stakeholders, but few examined both. Only six studies (25%) had established the clinical effectiveness of their service. Student clinics generate costs for universities in supplying supervision, capital and consumables. Benefits are shared by patients, students, universities and the broader health system, however, economic evaluations to date have largely ignored or not monetised/valued these benefits.Student‐led clinics involve many different stakeholders, each of whom may incur costs and reap benefits. This complicates how we can go about trying to establish the economic efficiency and viability of student‐led clinics. Measurement of both costs and benefits is needed to understand the efficiency of student‐led clinics in comparison to alternatives. Without the full picture, decision‐makers may make decisions that are ill‐informed and lead to a loss of benefit for society. [ABSTRACT FROM AUTHOR]

With the implementation of China's carbon reduction policies, the role of thermal power units will transition to a regulating power source. Hence, the electricity market fails to accurately reflect the capacity value of thermal power units, resulting in potential future losses for these units. Therefore, it is imperative to establish a rational capacity compensation mechanism that guarantees the revenue of thermal power units and offers effective investment and construction signals. Therefore, this paper proposes a capacity compensation mechanism for thermal power units based on effective capacity. To achieve this, a two‐layer power source planning model is established. At the upper level of the model, the installed capacity and capacity price of various types of power sources are optimized, while minimizing the operating costs of the planning horizon year under constraints such as annual net profit of units. The lower level focuses on the operation of typical days, optimizing the output of various types of units. Through case analysis, it can be concluded that the proposed model can achieve coordinated planning of capacity and capacity prices for various types of units, effectively ensuring the economic efficiency of the system while safeguarding the revenue of each unit. [ABSTRACT FROM AUTHOR]

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Aqueous zinc ion batteries (AZIBs) are considered one of the most prospective new‐generation electrochemical energy storage devices with the advantages of high specific capacity, good safety, and high economic efficiency. Nevertheless, the enduring problems of low Coulombic efficiency (CE) and inadequate cycling stability of zinc anodes, originating from dendrites, hydrogen precipitation and passivation, are closely tied to their thermodynamic instability in aqueous electrolytes, which significantly shortens the cycle life of the battery. Electrolyte additives can solve the above difficulties and are important for the advancement of affordable and reliable AZIBs. Organic electrolyte additives have attracted widespread attention due to their unique properties, however, there is a lack of systematic discussion on the performance and mechanism of action of organic electrolyte additives. In this review, a comprehensive overview of the application of organic electrolyte additives in AZIBs is presented. The role of organic electrolyte additives in stabilizing zinc anodes is described and evaluated. Finally, further potential directions and prospects for improving and directing organic electrolyte additives for AZIBs are presented. [ABSTRACT FROM AUTHOR]

Oil is one of the main resources used by all countries in the world. The ever-growing demand for oil and oil products forces oil companies to increase production and refining. In order to increase net profit, oil producing companies are constantly upgrading equipment, improving oil production technologies, and preparing oil for further processing. When considering the elements of primary oil refining in difficult conditions, such as hard-to-reach or in remote locations, developers face strict limitations in energy resources and dimensions. Therefore, the use of traditional systems causes a number of difficulties, significantly reducing production efficiency. In this study, the authors solve the problem of improving the characteristics of the oil separation process. In their work, the authors analyzed the separation columns of primary oil distillation, identified the shortcomings of the technological process, and searched for technological solutions. Having identified the lack of technical solutions for monitoring the state of the temperature field of the separation column, the authors developed their own hardware–software complex for monitoring the separation column (RF patents No. 2020665473, No. 2021662752 were received). The complex was tested and successfully implemented into production. The study provides an assessment of the economic efficiency of implementation for a year and a forecast of the economic effect for 10 years. [ABSTRACT FROM AUTHOR]

This paper presents a simulation model for determining the most suitable type of microbiogas plant for small local communities on Slovenian farms, focusing on the efficient processing of organic waste. This model uses various input parameters, including different types and quantities of slurry and corn silage. Four different scenarios were developed to represent potential plant sizes, each evaluated using key economic indicators: net present value, breakthrough price, and internal rate of return. A scenario sensitivity analysis was conducted to assess the effects of changes in investment costs, fluctuations in energy prices, and the addition of corn silage to the anaerobic digestion process. The results highlight significant differences in economic viability across the scenarios, with some demonstrating positive financial outcomes and shorter payback periods and others indicating potential financial risks and longer recovery times under certain conditions. The analysis suggests that smaller micro biogas plants may struggle to achieve profitability without optimizing input ratios or reducing costs, whereas larger plants show more favorable economic indicators, provided certain conditions are met. Furthermore, the economic efficiency improves when adding maize silage to the fermentor mixture. [ABSTRACT FROM AUTHOR]

This research is motivated by the need for higher education institutions to enhance economic efficiency in the learning process through innovative technology. ChatGPT, as an artificial intelligence (AI) model, is expected to support more effective and efficient learning processes significantly. This study aims to evaluate ChatGPT integration's impact on economic efficiency at Budi Utomo National Institute. The research uses a quantitative method with a survey approach involving 150 respondents consisting of lecturers and students. Data collection was conducted through questionnaires, and the results were analyzed using simple linear regression techniques. The findings show that the integration of ChatGPT significantly improves operational cost efficiency in education, reduces administrative burdens, and accelerates access to learning resources. The discussion focuses on AI's long-term potential in enhancing teaching quality and the challenges of implementing such technology in higher education institutions. This study concludes that ChatGPT can be an effective tool for achieving economic efficiency in higher education, though proper strategies are needed to optimize its use sustainably. [ABSTRACT FROM AUTHOR]

Mariculture has not fundamentally reduced its dependence on resources and the environment; ecological and economic efficiency has become an important target of concern for the sustainable and healthy development of China's mariculture industry. Environmental regulation (ER) is a core tool to realize the synergistic development of economic development and environmental resource protection in mariculture. In this paper, the provincial panel data of China's coastal areas from 2007 to 2020 was selected, and the level of ecological and economic efficiency of mariculture in different provinces of China was measured by using the super slacks‐based measurement–data envelopment analysis model considering the undesirable output of mariculture, and the impact of different ERs on ecological and economic efficiency was explored. It was found that the impacts of different ER methods on the eco‐economic efficiency (EEF) of mariculture may be non‐linearized, and there is also regional heterogeneity in the optimal choice and combination of ER methods to improve the EEF of mariculture. [ABSTRACT FROM AUTHOR]

Aggregate drying is a crucial step in asphalt mixture production. Enhancing the model accuracy and controller performance of aggregate dryer burners is essential for consistent flame characteristics, reducing NOx emissions, and minimizing fuel consumption. This paper introduces a second-order nonlinear parametric model for coal powder burners that includes delay and noise. Model parameters were determined through experimental data using the Salp Swarm Algorithm, showing higher accuracy than models based on the least square method. A dual-layer model predictive control (MPC) based on this mathematical model was developed to improve the economic efficiency of the aggregate drying process. Simulation results showed that the dual-layer MPC saves 1.08 tons of coal every 10 h compared to a standard MPC. A full-scale prototype demonstrated average flame length, flame temperature, and NOx emissions of 4242.6 mm, 1729.4 °C, and 460.2 mg/m³, respectively, validating the accuracy of the proposed mathematical model and controller. [ABSTRACT FROM AUTHOR]

Developing a green economy is key to achieving the 2030 Sustainable Development Goals. This paper uses the SBM-GML index, which includes non-desired outputs, to measure the trend of regional green economic efficiency changes and analyze the impact mechanism and realization path of industrial transformation on green economic efficiency. The research results show that advanced industrial structure has a positive influence on green economic efficiency nationwide, while energy utilization structure and energy utilization efficiency have positive partial intermediary effects in the influence path; industrial structure rationalization is also significantly positively related to green economic efficiency nationwide, and the mediating effect of energy utilization is positive. The impact of industrial transformation on green economic efficiency has regional heterogeneity, and the mediating effect of energy use also differs. Among them, the impact effect in the eastern region is basically consistent with the national sample, but is negative in the central and western regions. This paper proposes countermeasures in terms of adjusting the industrial structure, improving energy efficiency, and perfecting industrial and energy policies, which can provide theoretical and practical references for promoting the transformation and upgrading of regional industrial structure, optimizing energy utilization, and advancing the efficiency of the national and regional green economy. [ABSTRACT FROM AUTHOR]

In order to achieve maximum carbon reduction during the operation of pure electric buses, the author proposes a re estimation of carbon emissions in international trade based on evolutionary algorithm analysis of electric vehicle green energy regeneration systems. On the basis of analyzing single line scheduling, the author focuses on studying the regional scheduling mode of pure electric buses, and establishes a multi-objective optimization model for pure electric bus regional scheduling considering carbon benefits with the goals of minimizing the number of operating vehicles, minimizing the empty distance, and maximizing carbon benefits. Based on the actual operation data of pure electric buses 146 and 149 in a certain city, the author used an improved particle swarm optimization algorithm to solve the regional scheduling problem of pure electric buses according to the characteristics of the model. The results indicate that assuming other conditions remain unchanged, when the price of diesel rises to around 7.9 yuan, its operating costs will exceed those of pure electric buses, and the cost advantage of diesel vehicles will gradually decrease. Other conditions remain unchanged, and when the battery price per vehicle drops to around 300,000 yuan, the operating cost of pure electric buses will be lower than that of diesel vehicles. Conclusion: Under the premise of considering carbon benefits, adopting regional dispatch mode for pure electric buses has better economic efficiency and is more conducive to the promotion of pure electric buses. [ABSTRACT FROM AUTHOR]

The data management system of health cloud authentication plays an important role in the optimization of logistics vehicle routing. It can not only help logistics vehicles choose the best distribution path, but also save time and cost and improve economic efficiency. At present, logistics has not yet formed a complete service system. High distribution costs and low distribution efficiency limit the development of the entire logistics. The reduction of logistics costs and the improvement of distribution efficiency have become the top priorities of the society. The optimization of the distribution route is the key to cost saving and distribution logistics. It is particularly important to study and optimize the distribution route, because the distribution route affects the logistics transportation efficiency and the loss cost during transportation. Therefore, this paper adjusted the scheduling system of logistics vehicles through a distributed intelligent system, and optimized the path of logistics vehicles according to the improved genetic algorithm, thereby reducing the transportation cost of logistics and improving the efficiency of logistics distribution. This article first explains the definition, classification, and main components of the delivery vehicle routing problem. Then, using cloud authentication path optimization, a distributed intelligent system is constructed. Finally, an improved ant colony algorithm is used to analyze and study the distance constraints of vehicles. By improving the ant colony algorithm, it can be seen that the optimized path pheromone concentration and the optimized sub-function have gradually increased with time. The mean pheromone concentration was 40 %, and the seventh day was 15 % higher than the first. The mean value of the optimized subfunction was 0.34 %, and the seventh day was 20 % higher than the first. The distribution cost and distribution efficiency of the optimized logistics vehicle distribution path were much higher than those of the traditional logistics distribution path. Moreover, the distribution cost of the logistics distribution path was 9 % lower than the traditional one, and the distribution efficiency was 13 % higher. The average smoothness of the optimized logistics path is about 90 %, and the seventh day is 11 % higher than the first day. The average fitness of the optimized logistics path is 88 %, and the seventh day is 14 % higher than the first day. In a word, the data management system can uniformly schedule logistics vehicles and improve the efficiency of distribution. [ABSTRACT FROM AUTHOR]

HVDC is a promising interconnection solution for connecting asynchronous systems and ensuring power control. In Indonesia, a remote industrial system in Sumatra is experiencing load growth and has the option to draw power from the Sumatra system. However, due to frequency differences, the use of HVDC is crucial. The Generation Expansion Planning has proposed six converters but not their interconnection points. This study will determine the most reliable interconnection locations. The chosen converters are modular multilevel converters (MMCs) with high modularity. The converter reliability modeling considers voltage levels, the number of modules, and redundancy strategies. This modeling is then implemented at the power system level to obtain the best placement at the available high-voltage (HV) substation options. Determining the best placement is based on the optimal reliability index. The optimal placement also includes the option to convert from HV to medium-voltage (MV) interconnection. MV interconnection offers higher flexibility but tends to be more expensive. The availability for HV converters is 99.69%, while for MV converters, it is slightly higher, at 99.81%. Additionally, converting from HV to MV reduces the SAIFI (system average interruption frequency index) from 0.2668 to 0.2284 occurrences per year, lowering the interruption cost from 7.804 million USD to 5.737 million USD per year. The sensitivity of interruption, investment, and maintenance costs shows that converting at least one HV converter to MV remains economical. In this case study, the optimal converter placement includes Area VI–2, recommended for conversion from HV to a more distributed MV configuration, improving reliability and economic efficiency. [ABSTRACT FROM AUTHOR]