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Purpose: To compare the efficacy and safety of skip titanium plates combined with adjacent spinous process suture suspension versus continuous titanium plate fixation in cervical laminoplasty. Methods: A retrospective analysis of 125 patients (62 men, 63 women, average age 60.9 ± 10.4 years) with multilevel cervical spondylotic myelopathy who had cervical laminoplasty with Arch titanium plate fixation from January 2012 to March 2024 in our hospital was done. Patients were stratified into two cohorts based on the fixation technique: Group A (n = 64): Modified technique of skip-level titanium plate fixation (Arch titanium plates at C4 and C6 levels combined with adjacent spinous process suture suspension)Group B (n = 61): Continuous plating (Arch titanium plates applied sequentially from C3 to C7).The comparative analysis focused on perioperative parameters (operative duration, intraoperative blood loss, length of hospital stay), economic factors (hospital costs), and various clinical indicators. Results: The average follow up period was (73.0 ± 38.4) months. Both groups showed no significant differences in gender, age, and disease duration (P > 0.05). Group A had lower hospitalization costs, intraoperative blood loss, operation time, and postoperative hospital stay compared to Group B (P < 0.05). Postoperatively, both groups had significant improvements in JOA scores and NDI (P < 0.005), but there were no significant differences in postoperative scores and improvement rates between the two groups (P > 0.05). At 3 months postoperatively and at the last follow-up, the C2-7 Cobb angle and cervical curvature index decreased compared to preoperative values (P < 0.05), with a significant difference in the C2-7 Cobb angle at the last follow-up (P < 0.05). The sagittal diameter of the spinal canal from C3 to C7 significantly increased (P < 0.05), but there were no significant differences in the improvement of C3, C5, and C7 between the two groups (P > 0.05). At 3 months postoperatively, the opening angles of the C4 and C6 laminae in Group A were smaller than those in Group B (P < 0.05), but there were no significant differences at the last follow-up (P > 0.05). The healing of the C4 and C6 laminae in Group B was superior to that in Group A (P < 0.05), but there were no differences in healing at the last follow-up (P > 0.05). The incidence of axial symptoms was similar (10.9% in Group A and 14.8% in Group B, P = 0.523). Conclusions: During C3-7 laminoplasty, the clinical efficacy of the method combining mini titanium plate fixation (at C4 and C6) with suture fixation is comparable to that of continuous fixation. Moreover, it has an advantage in cost control. [ABSTRACT FROM AUTHOR]

This study aims to assess the feasibility of expanding the powder size distribution (PSD) of Ti-6Al-4V grade 5 powder for LPBF to achieve cost reduction. Parameter optimization to minimize the degradation of mechanical properties due to the expanded particle size distribution was conducted. Mechanical tests for specimens built using optimized parameters revealed minor reductions in strength: 3.9% in tensile yield strength, 1.1% in compressive strength, 5.5% in shear strength, and 4.5% in bearing yield strength—all of which complied with MMPDS standards. Statistical analysis, using the Anderson–Darling test, demonstrated stable mechanical performance and minimal variation between the original and expanded PSDs. These results highlight the potential of an expanded PSD to achieve cost reductions while maintaining compliance with industry standards, offering a practical solution for LPBF applications in cost-sensitive and high-performance industries. [ABSTRACT FROM AUTHOR]

Achieving optimal energy planning in Microgrids (MGs) is pivotal for addressing complex challenges associated with cost-effective and reliable energy supplies. This paper proposes a novel hybrid metaheuristic algorithm for optimal energy planning in microgrids using an Improved Salp Swarm Algorithm with Harris Hawk Foraging (ISSAHF). This technique is based on an improved multi-leader Salp Swarm Algorithm with an elite leader following strategy combined with Harris Hawks foraging. A simulation study is conducted on a low-voltage microgrid in off-grid and grid-connected modes. The optimization algorithm resulted in a daily average cost of 28.3370€ in off-grid mode compared to 19.2676€ in grid-connected one. Furthermore, the statistical study shows that the proposed algorithm outperforms well-established metaheuristic techniques regarding search capability and robustness. It yields mean optimal cost of 623.5248€ in off-grid and 404.7475€ for the grid-connected one, compared to other optimization techniques that vary from 667.2141€ to 959.5747€ in off-grid mode, and from 424.5841€ to 813.932€ in grid-connected mode. For robustness, the proposed technique performs well with a standard deviation of 20.765€ compared to the best (17.024€) and the worst (47.2423€) cases in off-grid mode, while in grid-connected mode, it is 28.8771€ compared to the best (21.6316€) and the worst (45.3774€) values. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the energy storage lifetime effects of the power allocation, there is a large space to improve the economy of the electric‐hydrogen hybrid DC microgrid. This paper provides an optimal control method based on the mutual learn salp swarm algorithm (MLSSA) in real‐time, which aims to enhance the economy and extend the system's service life. In order to realize the economic operation, operation cost and degradation cost of battery and hydrogen system are considered as the objective function first. Then, salp swarm algorithm based on mutual learn strategy is introduced to obtain optimal economy power allocation results in real‐time with higher convergence speed and increased accuracy. In addition, the proposed method also maintains the battery state of charge (SOC) and state of hydrogen charge (SOHC) within a proper range to guarantee the stable operation of the system. Finally, the results including power results, cost analysis and degradation rate analysis of the MATLAB/Simulink show that the proposed method is more economically beneficial than the non‐considering degradation cost strategy. [ABSTRACT FROM AUTHOR]

Effective inventory management can reduce costs, minimize waste, and ensure product availability, directly impacting a supermarket's revenue and operational efficiency. This study aims to investigate and improve inventory management policies for perishable items at H Supermarket, located in Riau. The research addresses fluctuating revenue and the gap between target and actual profit by optimizing inventory management through different policies. It specifically addresses the challenges of managing inventory for bread and fruits, which contribute significantly to the supermarket's revenue but are prone to high levels of waste and stockouts due to their short shelf lives. The research employs both qualitative and quantitative methods, including interviews with key stakeholders and analysis of three years of sales data, to identify root causes of inventory inefficiencies. Two distinct inventory policies were analyzed: a continuous review system for bread and a periodic review system for fruits. The continuous review system allows for real-time inventory monitoring, enabling more responsive restocking processes. In contrast, the periodic review system schedules inventory checks at regular intervals, optimizing the balance between freshness and stock levels. The results indicate that the continuous review system significantly reduces total annual costs for bread by approximately 61.4%, while the periodic review system, with a five-day review period, effectively manages fruit inventory, reducing annual costs by 19.1%. The research underscores the importance of tailored inventory management strategies for different types of perishable items. It highlights the need for accurate inventory tracking systems and comprehensive staff training to ensure precise inventory records. The findings suggest that implementing these optimized inventory policies can substantially enhance operational efficiency and reduce waste. [ABSTRACT FROM AUTHOR]

Radar systems are evolving towards distributed receiver networks. As individual stations might be separated too far to install a cable link, novel methods are required to synchronise individual data records in the time domain. State‐of‐the‐art GNSS receivers disciplining a highly stable oscillator are able to output a timing signal with several nanosecond accuracy solely using non‐proprietary signals. However, they typically require a stable environment and become a major cost factor for receiver networks with a high number of nodes. A method is presented to passively synchronise data records via GNSS raw signals in a single record requiring only a GNSS antenna, an analogue‐to‐digital converter and computation hardware. The clock bias is estimated via the common view method with either full raw signal correlation or software‐based code correlation of individual signals from the GPS, Galileo and BeiDou constellation with sub‐nanosecond precision. [ABSTRACT FROM AUTHOR]

The study was conducted to analyse the possibilities of integrating the principles of sustainable development and circular economy into the accounting system of agricultural enterprises. The study employed various methods to analyse the implementation of the circular economy in agricultural enterprises. The study found that the integration of the principles of sustainable development and circular economy into the accounting of agricultural enterprises allows increasing the efficiency of resource management. It was also found that the introduction of environmental and social indicators into the accounting system contributes to better control over the use of natural resources, reduction of production costs, and minimisation of waste. The analysis revealed that the application of the circular model in agriculture contributes to the economic sustainability of enterprises through the reuse of materials and reduced dependence on external resources. It was also confirmed that such innovations positively affect the ecological state of land and other natural resources used in agricultural production. The study found that the use of circular approaches in accounting can increase the transparency and accuracy of financial reports, considering the environmental impact. The analysis of enterprises from different countries, such as Nibulon, The Green Shop, and the Farmers for Climate Action cooperative, revealed concrete benefits of implementing circular approaches in reducing costs, improving resource management, increasing environmental efficiency, and increasing profitability, which confirmed their significance in modern agribusiness. It was established that the assessment of environmental and social factors enables a more objective determination of the economic efficiency of agricultural enterprises. Furthermore, it was proved that the implementation of sustainable approaches reduces the risks associated with environmental regulations and increases the confidence of investors and partners. It was concluded that the integration of these approaches contributes to the long-term sustainability of agricultural enterprises. The study made a valuable contribution to science by revealing innovative approaches to the integration of environmental and social indicators into the accounting of agricultural enterprises, which contributed to their sustainable development and responsibility towards the environment. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants are crucial for water management, enabling water reuse, recycling, and regulating pollutant levels. Their operation varies based on factors such as season, wastewater type, and treatment volume, impacting electricity and material consumption. Despite their longstanding use, chemical agents are often applied at constant ratios, resulting in excessive use and environmental impact. A model was employed to analyse plant operation, focusing on optimising polymer concentration and electricity demand. Polymer reduction was monitored through sedimentation kinetics at different concentrations, incorporating zeta potential measurement and particle size distribution. Sedimentation data were interpreted using a TurbiScan Lab®, examining the effect of sample collection and analysis time on sedimentation kinetics. The optimal cationic polyacrylamide concentration for treating wastewater with approximately 5 mg/L suspended particles and 5.525 mg/mL phosphorus ranged from 0.1 mg/mL to 1.3 mg/mL. In-line sensing of suspended particles can optimise polymer use. Additionally, a novel electricity operation mode was tested in a Finnish plant, presenting a model that can be extrapolated to enhance global wastewater treatment operations. [ABSTRACT FROM AUTHOR]

The cascaded H‐bridge multi‐level converter is the main topology of high‐voltage and high‐capacity converter in renewable energy power generation, energy storage system and reactive power compensation equipment. The parameter design of cascaded H‐bridge multi‐level converters directly determines the material cost and performance. Taking the output current distortion rate and the ripple voltage of the capacitor of the cascaded H‐bridge multi‐level converter as the constraint conditions, this paper proposes an overall parameter optimal design method of the cascaded H‐bridge multi‐level converter based on the optimization of the total material cost. Finally, the effectiveness of the proposed parameter design method is verified by the simulation result. [ABSTRACT FROM AUTHOR]

In order to maximize the electricity supply from clean energy sources, the goal of the smart power system is to unite all renewable energy sources. The goal of the present study is to use three optimization techniques, artificial rabbits optimization algorithm (ARO), grey wolf optimizer (GWO), and whale optimization algorithm (WOA), to reduce the cost of electricity (COE) while improving the reliability of the power supply for rural areas. While using the same control variables for the optimization methods and load profile, various hybrid system configurations are explored. Photovoltaic, wind turbine, fuel cell, and electrolyser systems are all involved in the proposed hybrid renewable system. The ARO methodology is more effective than the GWO, WOA, and PSO procedures in terms of net present cost (NPC) and cost of energy (COE) generation, according to data comparing the three optimization techniques with the traditional Particle Swarm Optimization (PSO) method. The proposed ARO reached a value of COE of 0.4412$/kWh compared to 0.4438$/kWh for GWO, 0.4443$/kWh for WOA, and 0.44378$/kWh for PSO. [ABSTRACT FROM AUTHOR]

The complex compositional space of high entropy alloys (HEAs) has shown a great potential to reduce the cost and further increase the catalytic activity for hydrogen evolution reaction (HER) by compositional optimization. Without uncovering the specifics of the HER mechanism on a given HEA surface, it is unfeasible to apply compositional modifications to enhance the performance and save costs. In this work, a combination of density functional theory and Bayesian machine learning is used to demonstrate the unique catalytic mechanism of IrPdPtRhRu HEA catalysts for HER. At high coverage of underpotential‐deposited hydrogen, a d‐band investigation of the active sites of the HEA surface is conducted to elucidate the superior catalytic performance through electronic interactions between elements. At low coverage, a novel Bayesian learning with oversampling approach is then outlined to optimize the HEA composition for performance improvement and cost reduction. This approach proves more efficacious and efficient and yields higher‐quality structures with less training set bias compared with neural‐network optimization. The proposed HEA optimization theoretically outperforms benchmark Pt catalysts’ overpotential by ≈40% at a 15% reduced synthesis cost comparing to the equiatomic ratio HEA. [ABSTRACT FROM AUTHOR]

As vehicular technology advances, intelligent vehicles generate numerous computation‐intensive tasks, challenging the computational resources of both the vehicles and the Internet of Vehicles (IoV). Traditional IoV struggles with fixed network structures and limited scalability, unable to meet the growing computational demands and next‐generation mobile communication technologies. In congested areas, near‐end Mobile Edge Computing (MEC) resources are often overtaxed, while far‐end MEC servers are underused, resulting in poor service quality. A novel network framework utilizing sixth‐generation mobile communication (6G) and digital twin technologies, combined with task migration, promises to alleviate these inefficiencies. To address these challenges, a task migration and re‐offloading model based on task attribute classification is introduced, employing a hybrid deep reinforcement learning (DRL) algorithm—Dueling Double Q Network DDPG (QDPG). This algorithm merges the strengths of the Deep Deterministic Policy Gradient (DDPG) and the Dueling Double Deep Q‐Network (D3QN), effectively handling continuous and discrete action domains to optimize task migration and re‐offloading in IoV. The inclusion of the Mini Batch K‐Means algorithm enhances learning efficiency and optimization in the DRL algorithm. Experimental results show that QDPG significantly boosts task efficiency and computational performance, providing a robust solution for resource allocation in IoV. [ABSTRACT FROM AUTHOR]

How bridge refurbishment projects are performed requires a trade-off between the speed and cost of the project and the amount of traffic disturbances during the project. A possible way to help reach a better balance between these two extremes is the ASTRA Bridge developed in Switzerland. The ASTRA Bridge is a 236-meter long steel ramp system on wheels, which is placed on top of the bridge deck undergoing refurbishment to enable vehicles to continue to pass over the bridge while construction work progresses underneath. This study illustrates new refurbishment processes by using the ASTRA Bridge and presents the first quantitative analysis of the effects of using the ASTRA Bridge on the time, costs and traffic disturbances associated with bridge refurbishment. The bridge investigated is a short-span (50 m long) highway bridge requiring refurbishment of its superstructure. The analysis indicates that the use of the ASTRA Bridge resulted in reductions in duration and costs (14% and 3% for the example), and a substantial reduction in user costs (51% for the example). Although more analysis is required for different types of refurbishment projects, the initial results indicate that the ASTRA Bridge may become an integral part of future highway bridge refurbishment projects. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is currently under active development as a method for remote sensing, environmental monitoring and biomedical diagnostics. The development of hyperspectral sensors is aimed at their miniaturization and reducing the cost of components for the purpose of the widespread use of such devices on unmanned aerial vehicles and satellites. In this review, we present a broad overview of recent work on the development of hyperspectral devices' configurations, studies aimed at modifying sensors and the possibility of reducing the cost of components of such devices. In addition, we will present the main trends in the development of hyperspectral device configurations for ubiquitous applications. [ABSTRACT FROM AUTHOR]

Abstract The connection queue has seen unparalleled growth over the last 24 months. With the record number of connection agreement applications representing a pivotal time for system development as we drive investment that will enable us to transition into an electrified future. The authors look to address challenges posed to the connection queue through congestion management‐based techniques. Conducting a top down approach, the authors first visualise the state of the queue. Observing highest growth in pure storage based applications distributed close to traditional load centres, followed by wind projects along the East Coast and Northern Scotland. Supporting close analysis is performed on the representative B6 boundary. The authors compare methodologies, validate a process for the attribution of congestion cost and quantify the value of investment given by unit power changes. Finding that most significant value of investment in storage lies in the Southeast of England and the North of Scotland. This reflects the identified current state of constraint and most efficient current utilisation of available capacity. These approaches have been aligned with current system thinking and progress towards a new industry data sharing standard, forming strategy by which we look to transition the energy system and country into a decarbonised future.

Abstract Due to the energy storage lifetime effects of the power allocation, there is a large space to improve the economy of the electric‐hydrogen hybrid DC microgrid. This paper provides an optimal control method based on the mutual learn salp swarm algorithm (MLSSA) in real‐time, which aims to enhance the economy and extend the system's service life. In order to realize the economic operation, operation cost and degradation cost of battery and hydrogen system are considered as the objective function first. Then, salp swarm algorithm based on mutual learn strategy is introduced to obtain optimal economy power allocation results in real‐time with higher convergence speed and increased accuracy. In addition, the proposed method also maintains the battery state of charge (SOC) and state of hydrogen charge (SOHC) within a proper range to guarantee the stable operation of the system. Finally, the results including power results, cost analysis and degradation rate analysis of the MATLAB/Simulink show that the proposed method is more economically beneficial than the non‐considering degradation cost strategy.

Wastewater treatment plants play a crucial role in water management by facilitating water reuse, recycling and maintaining a safe level of pollutants released into the environment. The operation of these plants varies according to a several factors, including the season, type of wastewater, and volumes to be treated. These factors commonly influence the consumption of electricity and other input materials, such as coagulants and flocculants. Despite the process being well-established and in use for decades, the use of chemical agents often remains at constant ratios, which may depend on inflow volumes. Consequently, the use of those chemical agents often surpasses the actual process needs, leading to unnecessary costs and environmental impacts. In this context, modelling was employed to analyze the typical operation of a wastewater treatment plant, with the polymer concentration and the electricity demand as the variables to be optimized. The reduction of the amount of polymer was determined by tracking the sedimentation kinetics at different polymer concentrations, combining zeta potential measurement and particle size distribution. Sedimentation data were obtained by interpreting the transmission and backscattering profile using a TurbiScan Lab®. The impact of the sample collection and analysis time on sedimentation kinetics was also investigated. It was found that the optimal concentration of cationic polyacrylamide to treat wastewater containing approximately 5 mg/L of suspended particles and initial concentration of phosphorous of 5.525 mg/mL can vary from 0.1 mg/mL to 1.3 mg/mL depending on the analysis time. Therefore, by implementing in-line sensing, the concentration of suspended particles can be used to optimize polymer consumption. Additionally, a new electricity operation mode is proposed for the wastewater treatment plant in Finland, a concept that could yield benefits beyond economic profit. These findings could be utilized to enhance the operation of wastewater treatment plants worldwide.

Abstract In order to maximize the electricity supply from clean energy sources, the goal of the smart power system is to unite all renewable energy sources. The goal of the present study is to use three optimization techniques, artificial rabbits optimization algorithm (ARO), grey wolf optimizer (GWO), and whale optimization algorithm (WOA), to reduce the cost of electricity (COE) while improving the reliability of the power supply for rural areas. While using the same control variables for the optimization methods and load profile, various hybrid system configurations are explored. Photovoltaic, wind turbine, fuel cell, and electrolyser systems are all involved in the proposed hybrid renewable system. The ARO methodology is more effective than the GWO, WOA, and PSO procedures in terms of net present cost (NPC) and cost of energy (COE) generation, according to data comparing the three optimization techniques with the traditional Particle Swarm Optimization (PSO) method. The proposed ARO reached a value of COE of 0.4412$/kWh compared to 0.4438$/kWh for GWO, 0.4443$/kWh for WOA, and 0.44378$/kWh for PSO.

Abstract The cascaded H‐bridge multi‐level converter is the main topology of high‐voltage and high‐capacity converter in renewable energy power generation, energy storage system and reactive power compensation equipment. The parameter design of cascaded H‐bridge multi‐level converters directly determines the material cost and performance. Taking the output current distortion rate and the ripple voltage of the capacitor of the cascaded H‐bridge multi‐level converter as the constraint conditions, this paper proposes an overall parameter optimal design method of the cascaded H‐bridge multi‐level converter based on the optimization of the total material cost. Finally, the effectiveness of the proposed parameter design method is verified by the simulation result.

Recently, firms like Toyota and social planners like the Government of India have invested in various initiatives leading to the firm's cost reduction. Further, such cost reduction collaborations also benefit the social planner because of higher industry output, and therefore, higher employment opportunities. In this paper, we investigate different scenarios in which the firm, or the social planner, or both exert efforts to reduce the firm's manufacturing cost. Interestingly, we find that under certain conditions, the firm may exert lower effort than the social planner. Our analysis reveals that when both players' cost reduction effectiveness is low, then collaboration results in higher payoffs for both the players. However, when the effectiveness of any player is high, then both players are better off if only one of them exerts effort. Our study further reveals that collaboration between the social planner and the firm always leads to a win–win situation. [ABSTRACT FROM AUTHOR]

Advancements in light detection and ranging (LiDAR) technology have significantly improved robotics and automated navigation. However, the high cost of traditional LiDAR sensors restricts their use in small-scale robotic projects. This paper details the development of a low-cost LiDAR prototype for small mobile robots, using time-of-flight (ToF) sensors as a cost-effective alternative. Integrated with an ESP32 microcontroller for real-time data processing and Wi-Fi connectivity, the prototype facilitates accurate distance measurement and environmental mapping, crucial for autonomous navigation. Our approach included hardware design and assembly, followed by programming the ToF sensors and ESP32 for data collection and actuation. Experiments validated the accuracy of the ToF sensors under static, dynamic, and varied lighting conditions. Results show that our low-cost system achieves accuracy and reliability comparable to more expensive options, with an average mapping error within acceptable limits for practical use. This work offers a blueprint for affordable LiDAR systems, expanding access to technology for research and education, and demonstrating the viability of ToF sensors in economical robotic navigation and mapping solutions. [ABSTRACT FROM AUTHOR]

Abstract In a modular multilevel converter (MMC) system, the sub‐module (SM) capacitors account for a large proportion of cost, volume and weight. Increasing modulation index (m) is an effective method to reducing the capacitance. Traditional MMC based on half‐bridge SM (HBSM) cannot boosting m while the hybrid MMC composed of HBSMs and full‐bridge sub‐modules (FBSM) can increase the m. The negative voltage is required when hybrid MMC works at the boosted m, which is only provided by the FBSMs because the HBSMs cannot output negative voltage. Therefore, appropriate control strategies are needed to achieve the normal operation of hybrid MMC under boosted m. This paper presents a control method suitable for hybrid MMC with high m based on multi‐harmonic voltage injection. The m is increased to 1.41 with the proposed multi‐harmonic voltage injection. Compared with the HBSM‐MMC, the proposed method reduces the total capacitance by more than 32%. Boosting m also reduces the RMS and peak value of the arm current by 18%. A comprehensive comparison was presented to demonstrate the cost and effect. Simulation and experiment verified the proposed method.

Abstract Aiming at the power supply scheme (PSS) of the on‐board supercapacitor‐powered tram, considering the cost and margin of the PSS, a two‐stage method is designed to optimize the layout of the charging stations and the configuration of the supercapacitor (SC). First, the SC‐powered tram model and stable cycle operation model are established, and a two‐stage optimization problem model with the lowest PSS cost and the largest SC margin is established. Then, an improved dual‐population differential evolution algorithm is designed, and the layout of charging stations and the configuration of SC are co‐optimized in the first stage, and then the layout of charging stations is optimized again in the second stage. The simulation results show that co‐optimization can obtain a lower cost of PSS, and furthermore, the layout of charging stations can be optimized again to effectively improve the margin of SC, thereby improving the matching degree between the layout of charging stations and the connection scheme of SC.

Abstract Recently, a novel low‐cost coding digital receiving array based on machine learning (ML‐CDRA) has been proposed to reduce the required radio frequency channels in modern wireless systems. The spatial sensitivity of ML‐CDRA is studied which describes the spatial accumulation gain in different directions. It is demonstrated that the spatial sensitivity is determined by the encoding network, decoding network, and beamforming criterion. To obtain the desired spatial sensitivity, a spatial sensitivity synthesis method is proposed based on the alternate projection by optimising the encoding network with the constraint of amplitude‐phase quantisation. Simulation results show that the proposed method can significantly improve the spatial sensitivity of ML‐CDRA. Furthermore, in the directions of interest, the spatial accumulation gain of ML‐CDRA can exceed the full‐channel digital receiving array.

In a modular multilevel converter (MMC) system, the sub‐module (SM) capacitors account for a large proportion of cost, volume and weight. Increasing modulation index (m) is an effective method to reducing the capacitance. Traditional MMC based on half‐bridge SM (HBSM) cannot boosting m while the hybrid MMC composed of HBSMs and full‐bridge sub‐modules (FBSM) can increase the m. The negative voltage is required when hybrid MMC works at the boosted m, which is only provided by the FBSMs because the HBSMs cannot output negative voltage. Therefore, appropriate control strategies are needed to achieve the normal operation of hybrid MMC under boosted m. This paper presents a control method suitable for hybrid MMC with high m based on multi‐harmonic voltage injection. The m is increased to 1.41 with the proposed multi‐harmonic voltage injection. Compared with the HBSM‐MMC, the proposed method reduces the total capacitance by more than 32%. Boosting m also reduces the RMS and peak value of the arm current by 18%. A comprehensive comparison was presented to demonstrate the cost and effect. Simulation and experiment verified the proposed method. [ABSTRACT FROM AUTHOR]

This article examines the impact of integration between Lean Accounting (LA) tools and Just-in-Time (JIT) techniques on Cost Reduction (CR) in a modern sustainable manufacturing environment in Saudi companies, Ethical Standards (ESs) mediate these two variables. A quantitative methodology was used for realizing the study goals and answering study questions. The main tool used for producing the primary data was a fully structured questionnaire with closed-ended questions which was designed and distributed online through a chosen sample of 109 managers and accountants in Saudi industrialization companies. Descriptive and deductive statistics were adopted to deduce the findings. The gathered responses analyzed by SPSS and AMOS and the results pointed out that there is a direct and indirect impact of LA tools and JIT techniques on CR in Saudi industrial companies especially when using ESs. Moreover, these findings could provide decision-makers in Saudi manufacturing companies with the importance of adopting both methods in an integrated way to maximize the profits of these firms. The practical implications of this study are that the implementation of these methods has a positive impact on the promotion of sustainable manufacturing and consequently the achievement of distinct sustainable performance. [ABSTRACT FROM AUTHOR]

Every day, health centers receive a significant number of patients seeking care and hospitalization, leading to long waiting times. Simulation modeling techniques are considered an effective solution to this issue. However, some research efforts had limited success mainly due to the neglect of systematic and straightforward approaches to identify and eliminate time waste in the healthcare system. To address this limitation, this study developed an LSS approach by collecting arriving patients and staff in a health center and using it as a case study. Then, a simulation model of the current system was created using the SIMPROCESS software. Finally, alternative solutions to shorten the queue time were proposed and supported by statistical graphs and tables. This is expected to improve overall health outcomes and enhance the delivery of healthcare services. A scenario is presented to evaluate the impact of the proposed improvements, which includes adding a general practitioner, a pediatrician, a dentist, and another pharmacy counter. This scenario improves system performance by up to 21%, reduces patient waiting times by approximately 50%, and ensures a fair distribution of workload among staff. [ABSTRACT FROM AUTHOR]

This article delves into the implementation and benefits of collaborative logistics, a strategic approach wherein logistics stakeholders engage in close cooperation to optimize resources and processes. The significance of a robust technological infrastructure is underscored, enabling real-time information sharing and integrated planning, which are pivotal for enhancing supply chain efficiency, reducing costs, and fostering sustainability. The discussion includes various collaborative logistics models, such as shared transportation routes and warehouses, which are instrumental in minimizing waste and mitigating environmental impact. The article further emphasizes the critical role of trust, transparency, and comprehensive legal frameworks in ensuring the success of such collaborations. By incorporating sustainability aspects into inventory management practices, companies can not only achieve substantial economic and environmental benefits but also secure a long-term competitive advantage. This integrated approach aligns with contemporary demands for sustainable operations, ultimately contributing to reduced global environmental footprint and compliance with stringent regulatory standards. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article describes elements of the know-how of using carbon electrodes produced using the technology of molding around a rod when smelting silicon metal. Application of our know-how will dramatically increase the competitiveness of silicon metal production. Experts' concerns regarding the use of such electrodes were that such electrodes have a through axial hole. This significantly reduces the mechanical strength of such electrodes, which can presumably lead to problems associated with the breakage of the working side of the electrode, which is immersed in the smelting space of the furnace under the charge layer. Industrial testing of such electrodes was carried out in a 30 MVA furnace of "Tau-Ken Temir" LLP. During testing, we used an approach previously developed by our team for working with a furnace in the process of smelting silicon metal. In particular, we used an interval between top treatments of about 30 min and adhered to the principles of balanced smelting, i.e., provided a balance between the intensity of the uniform supply of the charge into the furnace and the current active electrical power. Industrial testing carried out over four weeks confirmed the stability of the operation of cheaper carbon electrodes with a through axial hole. The recovery of silicon into finished products was also improved to 88–89% and the specific energy consumption was reduced to 11.2–12.1 MWh/t of silicon metal from the initial value 14,752 MWh/t. Thus, we received additional evidence for the effectiveness of our approach in furnace operating compared to an approach based on the ultimate provision of gas and permeability of the furnace top due to excessively intense processing of the top and an uncontrolled, uneven supply of charge to the furnace. [ABSTRACT FROM AUTHOR]