Strategies For Improving Efficiency Research Articles

Research on Learning Efficiency Improvement Strategies of Public English Perspective Based on Ant Colony Algorithm

Research on Learning Efficiency Improvement Strategies of Public English Perspective Based on Ant Colony Algorithm

Robust Covalent Organic Frameworks for Photosynthesis of H2O2: Advancements, Challenges and Strategies.

Since 2020, covalent organic frameworks (COFs) are emerging as robust catalysts for the photosynthesis of hydrogen peroxide (H2O2), benefiting from their distinct advantages. However, the current efficiency of H2O2 production and solar-to-chemical energy conversion efficiency (SCC) remain suboptimal due to various constraints in the reaction mechanism. Therefore, there is an imperative to propose efficiency improvement strategies to accelerate the development of this reaction system. This comprehensive review delineates recent advances, challenges, and strategies in utilizing COFs for photocatalytic H2O2 production. It explores the fundamentals and challenges (e.g., oxygen (O2) mass transfer rate, O2 adsorption capacity, response to sunlight, electron-hole separation efficiency, charge transfer efficiency, selectivity, and H2O2 desorption) associated with this process, as well as the advantages, applications, classification, and preparation strategies of COFs for this purpose. Various strategies to enhance the performance of COFs in H2O2 production are highlighted. The review aims to stimulate further advancements in utilizing COFs for photocatalytic H2O2 production and discusses potential prospects, challenges, and application areas in this field.

Straw Returning Proves Advantageous for Regulating Water and Salt Levels, Facilitating Nutrient Accumulation, and Promoting Crop Growth in Coastal Saline Soils

Saline soils limit plant growth due to high salinity. Straw returning has proven effective in enhancing soil adaptability and agricultural stability on saline lands. This study evaluates the effects of different straw-returning methods—straw mulching (SM), straw incorporation (SI), and straw biochar (BC)—on soil nutrients, water dynamics, and salinity in a barley–cotton rotation system using field box experiments. SM improved soil water retention during barley’s jointing and heading stages, while SI was more effective in its filling and maturation stages. BC showed lesser water storage capacity. During cotton’s growth, SI enhanced early-stage water retention, and SM benefited the flowering and boll opening stages. Grey relational analysis pinpointed significant water relationships at 10 cm and 20 cm soil depths, with SM regulating water across layers. SM and BC notably reduced soil conductivity, primarily within the top 20 cm, and their effectiveness decreased with depth. SI significantly lowered soil conductivity at barley’s jointing stage. SM effectively reduced salinity at 10 cm and 20 cm soil depths, whereas BC decreased soil conductivity throughout barley’s jointing, filling, and heading stages. For cotton, SI lowered soil conductivity at the seedling and boll opening stages. SM consistently reduced salinity across all stages, and BC decreased conductivity in the top 30 cm of soil during all growth stages. Both SM and BC significantly enhanced the total nutrient availability for barley and cotton, especially improving soil organic carbon and available potassium, with BC showing notable improvements. At barley’s heading stage, SI maximized dry matter accumulation, while SM boosted accumulation in leaves, stems, and spikes during the filling and maturation stages. Straw returning increased barley yield, particularly with SM and BC, and improved water use efficiency by 11.60% and 5.74%, respectively. For cotton, straw returning significantly boosted yield and water use efficiency, especially with SI and SM treatments, enhancing the total bolls and yield. In conclusion, straw returning effectively improves saline soils, enhances fertility, boosts crop yields, and supports sustainable agriculture. These results provide a robust scientific foundation for adopting efficient soil improvement strategies on saline lands, with significant theoretical and practical implications for increasing agricultural productivity and crop resilience to salt stress.

The critical success factors of smart port digitalization development in the post-COVID-19 era

The international outbreak of the new coronavirus (COVID-19) at the end of 2019 has caused an indelible impact on the global economy. However, it has grown against the trend in unmanned distribution and online consumption. In recent years, the maritime industry has gradually introduced artificial intelligence, blockchain, the Internet of Things, and big data. Through literature review and expert interviews, this research figures out the development status of smart ports at home and abroad and the digital development barriers of ports and then uses the Fuzzy Delphi and the Fuzzy Analytic Hierarchy Process method to identify three dimensions and thirteen key factors target companies. The survey targets shipping companies, shipping agencies, and port management companies. The paper conducted the questionnaires to identify the critical success factors of port digitization. It was found that the “digital solutions” dimension had the highest weight value among the three dimensions and the top five critical factors in the overall ranking were based on the order of “carbon emission management,” “enhancing port safety”, “technology standardization,” “digital asset management,” and “optimization of the supply chain.” The result of this study can help port operators and shipping companies identify critical success factors of smart ports and adopt port digital development strategies for operation efficiency improvement and climate change mitigation.

Techno-economic assessment of hydrogen as a fuel for internal combustion engines and proton exchange membrane fuel cells on long haul applications

Powertrain energy conversion and management are critical factors in providing affordable and robust solutions for transport decarbonization. Various powertrain technologies are being proposed to reduce the impacts of transportation-related carbon dioxide emissions, such as battery electric, fuel cell, and conventional vehicles running with lower carbon fuels. Specifically for the commercial sector, hydrogen internal combustion engines and fuel cells are being extensively discussed. In this sense, this investigation evaluates the benefits and areas of enhancement for hydrogen internal combustion engines and fuel cells from a techno-economic perspective. Power plant models were developed and validated in GT-Power, and detailed investigations on the energy loss pathways were performed. In addition, the powertrains are included in full longitudinal vehicle models and submitted to different driving cycles, representing homologation and real-world driving conditions, with the intent to understand the effect of the cycles from a global energy management perspective. Finally, the fuel consumption results are used as inputs for a total cost of ownership calculation to determine the economic viability of each powertrain. Overall, fuel cells offered efficient operation across the conditions assessed, with engine-powered powertrains showing reduced efficiencies ranging from 23 % to 63 % depending on the cycle and payload. The limited peak efficiency for the spark-ignited low-pressure hydrogen direct injection engine was a dominant factor for the reduced performance of this platform. Strategies for efficiency improvement are identified that could lead to improved internal combustion engine operation. Despite the limited efficiency benefits of hydrogen internal combustion engines, total cost of ownership calculations show hydrogen internal combustion engines being the most cost-effective solution in the near to medium-term scenario.

Mitigating trade-driven water scarcity via water-saving irrigation in China: Different role of surface water and groundwater

Examining virtual water flows in China, we identified a crucial gap in differentiating between groundwater (GW) and surface water (SW). Understanding the unique roles of virtual GW and SW is vital for local sustainable water use. We firstly track virtual GW and SW flows via inter-provincial trade, using a comprehensive inventory that included GW and SW uses in China. Our findings show nearly two-thirds of Chinese provinces face GW or SW scarcity in 2017, with about 34 % of GW and 31 % of SW use driven by interprovincial trade. Water rich regions acted as virtual SW exporters, while water scarce regions served as virtual GW exporters. Targeted irrigation efficiency improvement strategies, considering regional surface and groundwater pressures, could notably reduce interprovincial trade-driven GW and SW use by 12 % and 7 %. It's crucial to manage GW and SW as single resources, recognizing both their physical and virtual distinctions in local water use.

An Efficiency Improvement Strategy for Triple-Active-Bridge-Based DC Energy Routers in DC Microgrids

A triple-active bridge (TAB) can be used as a power conversion unit in a three-port DC energy router (DCER) such as a triple-active bridge-based DC energy router (TAB-DCER). The operational loss of a TAB can be seen as a key factor affecting the efficiency of a TAB-DCER. However, the RMS value of the inductor current of the TAB-DCER increases under single-phase shift (SPS) control, and this greatly increases the system operating losses. The use of phase-shifted plus PWM (PS-PWM) control can reduce the RMS value of the inductor current, but its mathematical model is complex, and involves difficult calculations. To address this problem, in the study reported here, we developed an optimal control strategy for the RMS value of the inductor current based on TAB-DCER. First, the working principle of a TAB-DCER under PS-PWM control was analyzed, and a circuit decomposition model was established. Second, the operating modes under PS-PWM control were analyzed, and corresponding expressions of port power and the RMS value of the inductor current were obtained. Third, an optimized mathematical model of the sum of squares of the RMS value of the inductor current of the TAB-DCER was constructed. Finally, a genetic algorithm was used to solve the mathematical model and derive the optimal phase shift angle; this resulted in a lower RMS value of the inductor current in the TAB-DCER and reduced the system operating losses. The simulation and experimental results show that the TAB-DCER used in the present study can reduce operating losses, improve system efficiency, and deliver coordinated power control.

Efficiency improvement strategy of fuel cell system based on oxygen excess ratio and cathode pressure two-dimensional optimization

Improving the commercial fuel cell system efficiency is critical to reducing hydrogen consumption and improving the operational economy. This paper studies the power consumption pattern of the air supply subsystem, the most power-consuming auxiliary components, aiming to improve the system’s efficiency. A method was proposed to get the extremum of the system net power by optimizing the oxygen excess ratio and cathode pressure. Mathematical models describing the fuel cell stack and air supply subsystem power characteristics were developed based on the mechanism analysis and estimation of unknown parameters. Then, a system net power model for energy efficiency optimization was developed. The operating conditions for optimal efficiency at a specific current density can be obtained by numerical calculation. To verify the method’s effectiveness, a series of experiments were conducted, and the results show that the proposed method can maximize system net power output at various current density conditions. Compared with the conventional oxygen excess rate based one-dimensional optimization, the two-dimensional method can improve system efficiency by 2.06%, offering a good application prospect.

Research on Supply Chain Optimization Model Construction and Efficiency Improvement Strategy in Automobile Industry

Abstract This thesis combines the ABC classification method and hierarchical analysis method to propose the evaluation method of logistics spatial layout and applies it to actual automobile manufacturing enterprises. The spatial layout scheme of logistics nodes in the park has been adjusted and optimized to achieve dynamic inventory classification and improve inventory management. When the demand of the decision-making body decreases, the optimal production and transportation scheduling plan for the automobile industry supply chain is formulated using the dynamic scheduling decision-making model. The results show that the spatial layout optimization scheme of supply chain logistics nodes in the automobile industrial park is RDC-B3, VDC-B5, and PDC-B1. The total cost of supply chain logistics after optimization is reduced by 3.8 × 108 yuan. The inventory items in the storage center are divided into 3 categories: A category for inventory items numbered 1-6, B category for 7-9, and C category for 10-11, to improve the turnover rate of the whole inventory and reduce the impact of inventory risk. When the demand side of the supply chain is reduced, the total cost of scheduling the optimal solution is 138.01 million. The research results of this paper have some reference significance.

Study on energy efficiency improvement strategy of photovoltaic-hybrid energy storage DC microgrid considering green energy saving concepts

Abstract In this paper, the development of microgrid technology is discussed in close connection with the growing energy demand and the real needs of energy structure adjustment in the context of the times. Guided by green energy saving, the research focuses on constructing a hybrid energy storage DC microgrid model, especially the integrated photovoltaic power generation model and the related control strategy and power characteristics. The article further adopts a fuzzy PID control strategy to optimize the energy efficiency configuration of hybrid energy storage devices in DC microgrids. By carefully analyzing and optimizing the energy storage system in the DC microgrid, remarkable results are obtained: the optimized capacitive charge states range from 0.1 to 0.9, indicating a significant fluctuation of capacitive charge states, but at the same time avoiding the phenomenon of light abandonment and ensuring the reliability of power supply. More notably, during the increase of SOC (state of the energy storage system) from 0.40 to 0.70, the system can perform mode transitions under continuous load changes. This point shows the effectiveness of the optimization method in improving the energy storage efficiency and enhancing the system performance of the DC microgrid. Overall, the optimization method proposed in this paper provides a practical energy storage optimization scheme for developing microgrids, which is of great practical significance in promoting the research and application of microgrid technology. This not only helps to improve the efficiency of energy use, but also is a crucial step to realize sustainable energy development.

Efficiency Improvement Mechanism of Smart Logistics Technology in Rural E-commerce Logistics and Distribution

Abstract This paper addresses the problems existing in the current two-way logistics and distribution model of rural e-commerce and proposes the study of rural e-commerce distribution efficiency with the technical support of intelligent logistics. Based on the knowledge of multi-objective optimization theory, the maximization of distribution efficiency of logistics enterprises and the maximization of demand coverage as the objective function, while the constraints are vehicle load, service time, path constraints, and finally, complete the construction of the multi-objective optimization model of rural e-commerce logistics and distribution efficiency. According to the NSGA-II algorithm with low computational complexity, fast operation speed, and good convergence, the NSGA-II algorithm is used to solve the constructed model, and then the optimal solution of rural e-commerce logistics distribution efficiency is derived. With regional logistics as the research subject, a multi-objective optimization model for rural e-commerce logistics distribution efficiency supported by intelligent logistics technology is simulated and analyzed. The data show that compared with other algorithms, the NSGAII algorithm has a smoother learning curve oscillation, while the final result of convergence (-1.473), the objective function is smaller (20.42), and the optimal total transportation time is smaller (609.22s). Finally, in order to solve the current rural e-commerce logistics and distribution problems in part, from the improvement of rural e-commerce logistics and distribution system, strengthen the rural logistics infrastructure construction of the two aspects of rural e-commerce logistics and distribution efficiency improvement strategy.

The Present Situation and Efficiency Improvement Strategy of Dance Art Education in the Digital Age

The Present Situation and Efficiency Improvement Strategy of Dance Art Education in the Digital Age

A review of the 1-2 apartment residential building stock in Lithuania based on an analysis of Energy Performance Certificates

One of priorities of the EU’s climate change policy is the energy performance of buildings. This is reflected primarily through the series of Directives the EU has enacted along the years, but is most precisely conveyed in the Energy Performance of Buildings Directive (EPBD). As part of the European Union, Lithuania has enacted its own long-term strategy aimed at transforming the current building stock in one which is more energy efficient. Building energy certification, legalized in accordance with the requirements of the directive is the primary tool used to evaluate the energy-efficiency of a building, which includes determination of the energy consumption of a building and subsequently assigning it with an energy performance class. Energy performance certificates (EPC) are obligatory for new and existing buildings in all European Union (EU) member states and provide not only a description of the energy performance characteristics of individual buildings, but are also useful source of legal information for determination of the achievements of building energy efficiency improvement strategy. Despite the current wide spread presence of EPC analyses in other European countries, similar information on the national EPC register of Lithuania is still hardly present in research studies. To this effect this paper presents a detailed overview of the stock of Lithuanian residential 1-2 apartments buildings using data from the national EPC register. The results obtained present the impact of the implementation of EPBD on Lithuanian residential 1-2 apartments buildings, including changes in thermal insulation of building elements, heating system typology, energy consumption and CO2 emissions.

Study on Energy Efficiency Improvement Strategies of Photovoltaic-Hybrid Energy Storage DC Microgrids under the Concept of Green Energy Conservation

Abstract To improve the energy efficiency of a PV-hybrid energy storage DC microgrid, a series of management strategies are proposed in this paper. According to the working principle of photovoltaic cells, the variable step conductance increment method is used to track and control the output power of photovoltaic cells, and the time constant of the low-pass filter is dynamically adjusted according to the output characteristics of supercapacitors in different SOC intervals, so as to put forward a limit management strategy based on the supercapacitor’s SOC partitioning. An energy management strategy for PV DC microgrid based on hybrid energy storage is proposed to address the impact of internal power fluctuation on DC microgrid operation stability. Based on the voltage deviation range, the system is divided into five operation modes to achieve efficient distribution of system power. Through simulation verification, the charging state difference of the battery bank is reduced by 0.00537 after a charging process of 20 s under the withdrawal and addition of PV power, and the charging power ratio is 5.00:8.14:6.82 at steady state under the withdrawal and addition of the hybrid energy storage unit, U dc = 405.4V. This paper’s strategy makes the DC microgrid effective in improving energy efficiency and smoothing out power fluctuations in all operating modes.

A multi-criteria decision model to support sustainable building energy management system with intelligent automation

With rising energy consumption in buildings, optimizing energy management is crucial for sustainability. This research pioneers the application of multi-criteria decision making (MCDM) techniques for real-time operational optimization of energy systems in buildings. A multicriteria decision analysis framework is used in this study to provide a model for decision making of generation and load balance. To assess the selection criteria, a thorough investigation is undertaken. The decision-based sustainable framework across conflicting criteria (encapsulating equal and objective weights) and aims towards the suitable trade-off solution. The framework is applied on workshop building across load-generation balance and is benchmarked with hardware. The research endeavor relies heavily on the deployment of sensor systems to prevent power wastage. By incorporating sensor systems, solar power usage control becomes smarter and more adaptable, enabling real-time modifications according to environmental conditions and energy requirements. This maximizes the overall efficiency and effectiveness of solar energy systems. Furthermore, the integration of sensor systems in solar power usage control improves reliability and maintenance through the identification and alerting of potential problems. TOPSIS and MCE are two methodologies that can be used in the field of multi-criteria decision model (MCDM). The originality of this study lies in the development of a MCDM framework to assist consumers in identifying resilient and optimal combinations of energy efficiency, cost-saving, and Indoor Environmental Quality (IEQ) improvement strategies for buildings in Pakistan.

Comparative genomic characterization of indigenous fat‐tailed Akkaraman sheep with local and transboundary sheep breeds

AbstractThe domestic sheep with over 1200 breeds descended from those early domesticated animals that are bred for a variety of resources such as meat, milk and wool. Akkaraman, a fat‐tailed indigenous sheep breed of Türkiye, is widespread throughout Central Anatolia, with the largest indigenous sheep population. Assessing the genetic diversity and genomic structure of animal breeds is among the key contributors to deciphering adaptation to environmental extremes and constructing efficient genetic improvement strategies. Therefore, this study aimed to characterize the genome of Akkaraman breed against various world‐renowned transboundary sheep and indigenous sheep with fat and thin tails. Genetic similarities and differences between those breeds have been displayed by estimating and comparing various genetic diversity indices, linkage disequilibrium (LD) estimates and fixation index (FST), runs of homozygosity (ROH) as well as PCA and neighbour‐joining tree analysis. Akkaraman sheep were observed to form a cluster alongside Moghani, Karakas, Tibetan and Cyprus Fat Tail sheep, which are primarily the sole representatives of fat‐tailed sheep in the study. This clustering was evident in both the PCA and neighbour‐joining tree analysis. The Akkaraman sheep was also observed to have the lowest genomic inbreeding and one of the lowest numbers of ROHs, which might also indicate that the breed has not been exposed to historical intensive selection pressure, inbred mating or a massive population bottleneck that might leave strong marks of genomic homozygosity. The results improve our understanding of the genetic diversity in Akkaraman sheep in comparison with certain mainstream sheep breeds as well as those indigenous breeds from around the world. Additionally, findings will also provide valuable insights to perform further GWAS effectively by considering population structure, diversity and LD patterns observed among the breeds while providing practical knowledge that will contribute to designing efficient and successful genome‐based selection programmes for worldwide sheep production systems.

WORKING CAPITAL EFFICIENCY AND ICT STRATEGY TOWARDS SME'S SUCCESS POST PANDEMIC

Resource efficiency is closely related to working capital management. Combined with professional experience, a small business must be able to develop daily activities that support the achievement of the goals and objectives set in the plan. For survival, the use of ICT becomes a priority. This study aims to identify working capital efficiency improvement strategies needed to respond to the impact of the ongoing pandemic on SMEs by leveraging ICT to improve the performance of SMEs in Batu City. This research using a quantitative research approach. The sample of respondents in this study was 100 SME’s in Batu City. This study produced several conclusions, including cash management which has a significant and positive effect on continuance intention. Receivable management, inventory management has a significant and positive effect on the success of MSMEs. ICT Implementation is proven to be able to strengthen the relationship between receivable management and the success of SME’s and ICT Implementation is proven to be able to strengthen the relationship between inventory management and the success of SME’s.

Parametric Analysis and Optimization for Thermal Efficiency Improvement in a Turbocharged Diesel Engine with Peak Cylinder Pressure Constraints

While the original equipment manufacturers are developing engines that can withstand higher PCP, the methodology to maximize the thermal efficiency gain with different PCP limits is still not well-known or documented in the literature. This study aims to provide guidance on how to co-optimize air system parameters, compression ratio, and intake valve closing (IVC) timing of heavy-duty turbocharged diesel engines to enhance thermal efficiency with peak cylinder pressure (PCP) constraints. In this study, a one-dimensional turbocharged engine model is established and validated by experimental data. The effects of turbocharger efficiency, boost pressure, high-pressure exhaust gas recirculation (HP EGR) ratio, compression ratio (CR), and IVC timing on diesel engine efficiency are assessed under PCP constraints through parametric analysis. The results indicate that for enhancing engine thermal efficiency under limited PCP, an increment in boost pressure and CR, and late IVC timing compared to baseline is required. By multiple parameter optimization, the best parameter combination under different PCP constraints is proposed. At a PCP limit of 20 MPa, the combination of a compression ratio of 18.57, boost pressure of 298 kPa, and IVC timing of −95.2 °CA ATDC yields a 1.56% (absolute value) improvement in ITEn over the baseline condition. Raising the PCP limits from 20 MPa to 25 MPa requires increasing the compression ratio to 21.92, boost pressure to 308 kPa, and delaying the intake valve closing timing to −88.7 °CA ATDC, which results in an absolute improvement of 0.86% in ITEn. Baseline engine configuration is updated accordingly to validate the thermal efficiency improvement strategy at a 25 MPa PCP limitation. Experimental results demonstrate a 2.2% (absolute value) improvement in brake thermal efficiency and 1.98% (absolute value) improvement in overall energy efficiency.

Opportunities and challenges for decentralised clinical trials in sub-Saharan Africa: a qualitative study

IntroductionDigital health has gained traction in research and development, and clinical decision support systems. The COVID-19 pandemic accelerated the adoption of decentralised clinical trials (DCTs) as a mitigation and efficiency...

Green light optimized speed advisory achieves fuel savings and CO2 emission reduction by profoundly impacting driving behavior

Green Light Optimized Speed Advisory (GLOSA) is an emerging smart transportation technology that guides drivers through signalized intersections during green light phases, showing promise in mobile source pollution control. However, there is still a lack of comprehensive understanding regarding its impact on driving behavior, fuel consumption, and CO2 emissions. In this study, we used heavy-duty diesel truck (HDDT) as an example and conducted a comprehensive path study from the changes in driving behavior to fuel consumption and CO2 emission reduction after the application of GLOSA, using a portable emission measurement system for real-world driving tests at two research scales: signal-controlled road section and signalized intersections. The study was innovatively conducted in three scenarios: Without GLOSA, With GLOSA, and GW GLOSA, which considers the simultaneous application of Green Wave (GW) traffic control system. Results show that applying GLOSA, the passing rate of vehicles at signalized intersections significantly improves, the driving cycle curve tends to be smoother, the cruise time ratio increases to 67.60%, and the travel time is reduced by 5%–13%. HDDT's average speed on the road segments (Seg) decreases by 25.15%, and the aggressive acceleration and deceleration behavior near signalized intersections are significantly reduced. The trip fuel consumption and CO2 emissions of HDDT decrease by 16.63%–23.51% and 16.06%–24.12%, respectively. These fuel savings and CO2 emission reductions mainly occur in the Seg and Signalized intersection-after sections. After the simultaneous application of GLOSA and GW, the trip average speed increases by 60.90%, and traffic efficiency is greatly improved. Although the fuel consumption and CO2 emissions are slightly higher compared to GLOSA alone due to the higher driving speed, GW GLOSA still offers relatively considerable fuel and environmental benefits. This study deepens people's understanding of GLOSA and GW and provides support for the formulation of transportation efficiency improvement and environmental protection strategies.