Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent integration.The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and processing.However,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion terminals.Simultaneously,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart grid.In response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these issues.The scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT terminals.It then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy states.This comprehensive approach reduces the impact of subjective factors on trust measurements.Additionally,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious terminals.This,in turn,enhances the security and reliability of the smart grid environment.The effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation experiments.Notably,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Energy Efficiency Maximization in Mobile Edge Computing Networks via IRS assisted UAV Communications

In this paper,we investigate the energy efficiency maximization for mobile edge computing(MEC)in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communications.In particular,UAVcan collect the computing tasks of the terrestrial users and transmit the results back to them after computing.We jointly optimize the users’transmitted beamforming and uploading ratios,the phase shift matrix of IRS,and the UAV trajectory to improve the energy efficiency.The formulated optimization problem is highly non-convex and difficult to be solved directly.Therefore,we decompose the original problem into three sub-problems.We first propose the successive convex approximation(SCA)based method to design the beamforming of the users and the phase shift matrix of IRS,and apply the Lagrange dual method to obtain a closed-form expression of the uploading ratios.For the trajectory optimization,we propose a block coordinate descent(BCD)based method to obtain a local optimal solution.Finally,we propose the alternating optimization(AO)based overall algorithmand analyzed its complexity to be equivalent or lower than existing algorithms.Simulation results show the superiority of the proposedmethod compared with existing schemes in energy efficiency.

Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work,the Slacks-Based Measure(SBM)model within Data Envelopment Analysis was employed to establish a set of indicators for evaluating the energy efficiency of manufacturing workshops.The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed.The findings indicated that aside from a few workshops operating at the production frontier,the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency.Subsequently,a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops.Regression analysis revealed that technological investments,employee quality,workshop production scale,investment in clean energy,and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops.By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors,this research aids company managers in understanding the energy efficiency of the manufacturing process.It optimizes the combination of various production elements,thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops,which can contribute to enhancing the corporation’s overall energy efficiency.

A credibility-aware swarm-federated deep learning framework in internet of vehicles

Although Federated Deep Learning(FDL)enables distributed machine learning in the Internet of Vehicles(IoV),it requires multiple clients to upload model parameters,thus still existing unavoidable communication overhead and data privacy risks.The recently proposed Swarm Learning(SL)provides a decentralized machine learning approach for unit edge computing and blockchain-based coordination.A Swarm-Federated Deep Learning framework in the IoV system(IoV-SFDL)that integrates SL into the FDL framework is proposed in this paper.The IoV-SFDL organizes vehicles to generate local SL models with adjacent vehicles based on the blockchain empowered SL,then aggregates the global FDL model among different SL groups with a credibility weights prediction algorithm.Extensive experimental results show that compared with the baseline frameworks,the proposed IoV-SFDL framework reduces the overhead of client-to-server communication by 16.72%,while the model performance improves by about 5.02%for the same training iterations.

UAV-assisted data collection for wireless sensor networks with dynamic working modes

Wireless Sensor Network(WSN)is a cornerstone of Internet of Things(IoT)and has rich application scenarios.In this work,we consider a heterogeneous WSN whose sensor nodes have a diversity in their Residual Energy(RE).In this work,to protect the sensor nodes with low RE,we investigate dynamic working modes for sensor nodes which are determined by their RE and an introduced energy threshold.Besides,we employ an Unmanned Aerial Vehicle(UAV)to collect the stored data from the heterogeneous WSN.We aim to jointly optimize the cluster head selection,energy threshold and sensor nodes’working mode to minimize the weighted sum of energy con-sumption from the WSN and UAV,subject to the data collection rate constraint.To this end,we propose an efficient search method to search for an optimal energy threshold,and develop a penalty-based successive convex approximation algorithm to select the cluster heads.Then we present a low-complexity iterative approach to solve the joint optimization problem and discuss the implementation procedure.Numerical results justify that our proposed approach is able to reduce the energy consumption of the sensor nodes with low RE significantly and also saves energy for the whole WSN.

Flow characteristics and hot workability of a typical low-alloy high-strength steel during multi-pass deformation

Heavy components of low-alloy high-strength(LAHS) steels are generally formed by multi-pass forging. It is necessary to explore the flow characteristics and hot workability of LAHS steels during the multi-pass forging process, which is beneficial to the formulation of actual processing parameters. In the study, the multi-pass hot compression experiments of a typical LAHS steel are carried out at a wide range of deformation temperatures and strain rates. It is found that the work hardening rate of the experimental material depends on deformation parameters and deformation passes, which is ascribed to the impacts of static and dynamic softening behaviors. A new model is established to describe the flow characteristics at various deformation passes. Compared to the classical Arrhenius model and modified Zerilli and Armstrong model, the newly proposed model shows higher prediction accuracy with a confidence level of 0.98565. Furthermore, the connection between power dissipation efficiency(PDE) and deformation parameters is revealed by analyzing the microstructures. The PDE cannot be utilized to reflect the efficiency of energy dissipation for microstructure evolution during the entire deformation process, but only to assess the efficiency of energy dissipation for microstructure evolution in a specific deformation parameter state.As a result, an integrated processing map is proposed to better study the hot workability of the LAHS steel, which considers the effects of instability factor(IF), PDE, and distribution and size of grains. The optimized processing parameters for the multi-pass deformation process are the deformation parameters of 1223–1318 K and 0.01–0.08 s^(-1). Complete dynamic recrystallization occurs within the optimized processing parameters with an average grain size of 18.36–42.3 μm. This study will guide the optimization of the forging process of heavy components.

Propagation and sealing efficiency of chemical grouting in a two-dimensional fracture network with flowing water

In this study, an orthogonal array experiment is conducted by using a transparent fracture network replica. Image processing and theoretical analysis are performed to investigate the model sealing efficiency(SE), factors influencing SE, and the effect of flowing water on propagation. The results show that grout propagation can be classified into three patterns in the fracture network: sealing off, partial sealing,and major erosion. The factors controlling the SE in a descending order of the amount of influence are the initial water flow speed, fracture aperture, grout take, and gel time. An optimal value for the combination of the gel time and grout take(artificial factors) can result in a good SE. The grouting and seepage pressures are measured, and the results reveal that their variations can indicate the SE to some extent. The SE is good when the seepage pressure at each point increases overall;the frequent fluctuations in the seepage pressure indicate a moderately poor SE, and an overall decline in the seepage pressure indicates a major erosion type. The deflection effect of grouting shows an approximately elliptical propagation with the long axis expanding along the wider fracture opening, demonstrating further application in grouting design.

Fairness-Aware Harvested Energy Efficiency Algorithm for IRS-Aided Intelligent Sensor Networks with SWIPT

In this paper,a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer(SWIPT)aided sensor networks is developed for active beamforming of multiantenna transmitter and passive beamforming at intelligent reflecting surfaces(IRS).By optimizing the active beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS,we aimtomaximize the minimumharvested energy efficiency among all the energy receivers(ER)where information receivers(IR)are bound to the signal-interference-noise-ratio(SINR)and the maximum transmitted power of the transmitter.To handle the non-convex problem,both semi-definite relaxation(SDR)and block coordinate descent technologies are exploited.Then,the original problem is transformed into two convex sub-problems which can be solved via semidefinite programming.Numerical simulation results demonstrate that the IRS and energy beamformer settings in this paper provide greater system gain than the traditional experimental setting,thereby improving the fairness-aware harvested energy efficiency of the ER.

Size matters:analyzing bank profitability and efficiency under the Basel III framework

The latest regulatory framework,which has been introduced globally in the form of Basel III,and its implementation in the legislation of the member states of the Euro-pean Union has generated much interest in the impact of regulation on the efficiency and profitability of banks.This study aims to examine the impact of the introduction of two major regulatory changes(Basel II and Basel III)on bank performance,in terms of bank size and bank-specific and macroeconomic variables.A two-stage empirical anal-ysis was conducted on a sample of 433 European commercial banks over the 2006–2015 period.In the first stage,relative efficiency was calculated using non-parametric data envelopment analysis.In the second stage,the generalized method of moments was used to examine the impact of bank-specific and macroeconomic variables as well as regulation on bank performance,that is,profitability and efficiency.Consider-ing bank size,the results show a diverse impact of regulation on bank performance.Regarding large-and medium-sized banks,regulation positively affects both efficiency and profitability,whereas,for small banks,it negatively affects performance.The results suggest that larger banks have skillfully adapted to the new regulatory environment.In contrast,small banks have problems with profitability and efficiency because the new regulatory framework has imposed additional administrative and regulatory burdens.This could result in future failure or mergers with larger banks,resulting in a higher concentration in the banking sector and increased systemic risk.Our results strongly suggest that regulation should not be implemented equally for all banks;that is,on a one size fits all terms.A distinction between small and large banks when introducing new regulatory frameworks should be made if a reasonable level of competition is to be preserved.

Future Vision on Artificial Intelligence Assisted Green Energy Efficiency Network

To meet the key performance requirement of the 5G network and the demand of the growing number of mobile subscribers,millions of base stations are being constructed.5G New Radio is designed to enable denser network deployments,which raises significant concerns about network energy consumption.Machine learning(ML),as a kind of artificial intelligence(AI)technologies,can enhance network optimization performance and energy efficiency.In this paper,we propose AI/ML-assisted energy-saving strategies to achieve optimal performance in terms of cell shutdown duration and energy efficiency.To realize network intelligence,we put forward the concept of intrinsic AI,which integrates AI into every aspect of wireless communication networks.

Maximizing the Efficiency of Automation Solutions with Automation 360: Approaches for Developing Subtasks and Retry Framework

I present a solution that explores the use of A360 subtasks as a comparable concept to functions in programming. By leveraging subtasks as reusable and maintainable functions, users can efficiently develop customized high-quality automation solutions. Additionally, the paper introduces the retry framework, which allows for the automatic retrying of subtasks in the event of system or unknown exceptions. This framework enhances efficiency and reduces the manual effort required to retrigger bots. The A360 Subtask and Retry Framework templates provide valuable assistance to both professional and citizen developers, improving code quality, maintainability, and the overall efficiency and resiliency of automation solutions.

Formulation of Work-Study Combined and Result-Oriented Integrated Curriculum Standards

According to the Annex Technical Regulations for Integrated Curriculum Development(Trial)in Document No.30 of the General Office of the Ministry of Human Resources and Social Security(2012),this paper studies the formulation of the curriculum standards for the integration of Chinese medicinal materials production.We focus on the formulation ideas of the curriculum standards for the integration of Chinese medicinal materials production,the formulation process of the curriculum standards for the integration of Chinese medicinal materials production,including the description of typical work tasks,the determination of curriculum objectives,the analysis of study content,the description of referential study tasks,teaching implementation suggestions,assessment and evaluation suggestions,which can provide a reference for the development and research of other related integrated courses.

Effect of antioxidants on the efficiency of jet milling and the powder characteristics of Sm2Co17 permanent magnets

This study investigated the effect of antioxidants on the grinding efficiency,magnetic powder characteristics,microstructure,and magnetic properties of 2:17 type SmCo permanent magnet materials.The results show that adding antioxidants helps improve the dispersion among magnetic powders,leading to a 33.3%decrease in jet milling time and a 15.8%increase in magnet powder production yield.Additionally,adding antioxidants enhances the oxidation resistance of the magnetic powders.After being stored in a constant temperature air environment at 25C for 48 h,the O content in the powder decreased by 33%compared to samples without antioxidants.While in the magnet body,the O content decreased from 0.21 wt.%to 0.14 wt.%,which helps increase the effective Sm content and domain wall pinning uniformity in the magnet.Excellent magnetic properties were obtained in the magnet with added antioxidants:B_(r)=11.6 kGs,SF=79.6%,H_(cj)=16.8 kOe,and(BH)_(max)=32.5 MGOe.

Effect of building energy efficiency standards on carbon emission efficiency in commercial buildings

The building sector plays a crucial role in the worldwide shift toward achieving net-zero emissions.Building energy efficiency standards(BEESs)are highly effective policies for reducing carbon emissions.Therefore,exploring the provincial variations in carbon emission efficiency(CEE)in the building sector and identifying the effect of BEESs on CEE is crucial.This study focuses on commercial buildings in China and applies a difference in differences model to evaluate the impact of BEESs on the CEE of commercial buildings.The slacks-based measure–data envelopment analysis model is employed to assess the CEE of commercial buildings in 30 Chinese provinces from 2000 to 2019.Furthermore,heterogeneous tests are used to explore how climate characteristics and economic conditions affect the efficiency of BEESs.The results indicate that BEESs positively influence the CEE of commercial buildings.Specifically,a 1%increase in the intensity of BEESs causes a 0.1484%increase in the CEE of commercial buildings.Moreover,the impact of BEESs is particularly pronounced in the southern and western provinces.This study provides valuable scientific evidence for governments to enhance BEESs implementation.

The Impact of Privatization on Terminal Efficiency: A Case Study of Tema Port

Port and terminal efficiency are of utmost importance to the container shipping industry due to their significance in enhancing the competitive advantage of ports within a region. Consequently, there have always been notable variations of studies around it. This paper analyzes the impact of privatization on terminal efficiency using the Port of Tema as a Case Study. The main objective of this paper is to analyze the efficiency trends of the public and private terminals in the port over the years. To achieve this objective, DEA-CCR methodology was employed to calculate the annual technical efficiency trends of the private and public terminals using four input variables and three output variables. The main results of the paper indicated that the public and private terminals were efficient for multiple years. However, the efficiency scores over the years demonstrated inconsistency, exhibiting notable fluctuations. The findings of this study will aid policymakers across the region on policies relating to the efficiency and ownership structure of ports and terminals.

OsNPF3.1,a nitrate,abscisic acid and gibberellin transporter gene,is essential for rice tillering and nitrogen utilization efficiency

Low-affinity nitrate transporter genes have been identified in subfamilies 4-8 of the rice nitrate transporter 1(NRT1)/peptide transporter family(NPF),but the OsNPF3 subfamily responsible for nitrate and phytohormone transport and rice growth and development remains unknown.In this study,we described OsNPF3.1 as an essential nitrate and phytohormone transporter gene for rice tillering and nitrogen utilization efficiency(NUtE).OsNPF3.1 possesses four major haplotypes of its promoter sequence in 517 cultivars,and its expression is positively associated with tiller number.Its expression was higher in the basal part,culm,and leaf blade than in other parts of the plant,and was strongly induced by nitrate,abscisic acid(ABA)and gibberellin 3(GA_3)in the root and shoot of rice.Electrophysiological experiments demonstrated that OsNPF3.1 is a pH-dependent low-affinity nitrate transporter,with rice protoplast uptake assays showing it to be an ABA and GA_3 transporter.OsNPF3.1 overexpression significantly promoted ABA accumulation in the roots and GA accumulation in the basal part of the plant which inhibited axillary bud outgrowth and rice tillering,especially at high nitrate concentrations.The NUtE of OsNPF3.1-overexpressing plants was enhanced under low and medium nitrate concentrations,whereas the NUtE of OsNPF3.1 clustered regularly interspaced short palindromic repeats(CRISPR)plants was increased under high nitrate concentrations.The results indicate that OsNPF3.1 transports nitrate and phytohormones in different rice tissues under different nitrate concentrations.The altered OsNPF3.1 expression improves NUtE in the OsNPF3.1-overexpressing and CRISPR lines at low and high nitrate concentrations,respectively.

Enhancing I^(0)/I^(-)Conversion Efficiency by Starch Confinement in Zinc-lodine Battery

The redox couple of I^(0)/I^(-)in aqueous rechargeable iodine–zinc(I^(2)-Zn)batteries is a promising energy storage resource since it is safe and cost-effective,and provides steady output voltage.However,the cycle life and efficiency of these batteries remain unsatisfactory due to the uncontrolled shuttling of polyiodide(I_(3)^(-)and I_(5)^(-))and side reactions on the Zn anode.Starch is a very low-cost and widely sourced food used daily around the world.“Starch turns blue when it encounters iodine”is a classic chemical reaction,which results from the unique structure of the helix starch molecule–iodine complex.Inspired by this,we employ starch to confine the shuttling of polyiodide,and thus,the I^(0)/I^(-)conversion efficiency of an I^(2)-Zn battery is clearly enhanced.According to the detailed characterizations and theoretical DFT calculation results,the enhancement of I^(0)/I^(-)conversion efficiency is mainly originated from the strong bonding between the charged products of I_(3)^(-)and I_(5)^(-)and the rich hydroxyl groups in starch.This work provides inspiration for the rational design of high-performance and low-cost I^(2)-Zn in AZIBs.

Enhanced Cooling Efficiency of Urban Trees on Hotter Summer Days in 70 Cities of China

Increasing the urban tree cover percentage(TCP) is widely recognized as an efficient way to mitigate the urban heat island effect. The cooling efficiency of urban trees can be either enhanced or attenuated on hotter days, depending on the physiological response of urban trees to rising ambient temperature. However, the response of urban trees' cooling efficiency to rising urban temperature remains poorly quantified for China's cities. In this study, we quantify the response of urban trees' cooling efficiency to rising urban temperature at noontime [~1330 LT(local time), LT=UTC+8] in 17summers(June, July, and August) from 2003–19 in 70 economically developed cities of China based on satellite observations. The results show that urban trees have stronger cooling efficiency with increasing temperature, suggesting additional cooling benefits provided by urban trees on hotter days. The enhanced cooling efficiency values of urban trees range from 0.002 to 0.055℃ %-1 per 1℃ increase in temperature across the selected cities, with larger values for the lowTCP-level cities. The response is also regulated by background temperature and precipitation, as the additional cooling benefit tends to be larger in warmer and wetter cities at the same TCP level. The positive response of urban trees' cooling efficiency to rising urban temperature is explained mainly by the stronger evapotranspiration of urban trees on hotter days.These results have important implications for alleviating urban heat risk by utilizing urban trees, particularly considering that extreme hot days are becoming more frequent in cities under global warming.

Design and optimization of fluid lubricated bearings operated with extreme working performances——a comprehensive review

Fluid lubricated bearings have been widely adopted as support components for high-end equipment in metrology,semiconductor devices,aviation,strategic defense,ultraprecision manufacturing,medical treatment,and power generation.In all these applications,the equipment must deliver extreme working performances such as ultraprecise movement,ultrahigh rotation speed,ultraheavy bearing loads,ultrahigh environmental temperatures,strong radiation resistance,and high vacuum operation,which have challenged the design and optimization of reliable fluid lubricated bearings.Breakthrough of any related bottlenecks will promote the development course of high-end equipment.To promote the advancement of high-end equipment,this paper reviews the design and optimization of fluid lubricated bearings operated at typical extreme working performances,targeting the realization of extreme working performances,current challenges and solutions,underlying deficiencies,and promising developmental directions.This paper can guide the selection of suitable fluid lubricated bearings and optimize their structures to meet their required working performances.