Optimization Strategies of Beijing Elderly Care Service Stations Based on Questionnaire Survey Method: A Case Study of Zhanlan Road Street of Xicheng District

4 elderly care service stations in Zhanlan Road Street,Xicheng District,Beijing are selected,and questionnaires are designed and distributed to the surrounding elderly population to understand their needs and satisfaction with the station environment.By observing elderly care service stations on site,the characteristics,obstacles,and shortcomings of the environment are recorded,and relevant data are collected and analyzed,such as the characteristics of the elderly population being interviewed,the planning and design data of the station environment,and the distribution of service facilities.The overall characteristics of the spatial environment of elderly care stations are summarized,and renovation measures and optimization suggestions are provided for the current shortcomings,thereby providing some basis for the spatial design of community elderly care service stations in the future.

Research Status,Practical Dilemmas,and Optimization Strategies of Blended Teaching in Universities

Blended teaching has emerged as a prominent subject in the recent reform and innovation of higher education.It has become imperative and guiding for colleges and universities to embrace a mixed teaching approach that aligns with the evolving needs of education and teaching in the new era.This paper aims to provide a comprehensive overview of the research status surrounding blended teaching,encompassing fundamental issues,teaching design,practical guidance,teaching effectiveness,and evaluation.By critically examining the current challenges associated with blended teaching,this study proposes optimization strategies including enhancing student participation and interaction,promoting deep learning,improving teachers’preparedness,teaching technologies,and curriculum design capabilities,strengthening top-level design,and perfecting evaluation and incentive mechanisms.These strategies provide new directions for the reform of blended teaching.

Recent Advances on Challenges and Strategies of Manganese Dioxide Cathodes for Aqueous Zinc-Ion Batteries

Aqueous zinc-ion batteries(AZIBs)are regarded as promising electrochemical energy storage devices owing to its low cost,intrinsic safety,abundant zinc reserves,and ideal specific capacity.Compared with other cathode materials,manganese dioxide with high voltage,environmental protection,and high theoretical specific capacity receives considerable attention.However,the problems of structural instability,manganese dissolution,and poor electrical conductivity make the exploration of high-performance manganese dioxide still a great challenge and impede its practical applications.Besides,zinc storage mechanisms involved are complex and somewhat controversial.To address these issues,tremendous efforts,such as surface engineering,heteroatoms doping,defect engineering,electrolyte modification,and some advanced characterization technologies,have been devoted to improving its electrochemical performance and illustrating zinc storage mechanism.In this review,we particularly focus on the classification of manganese dioxide based on crystal structures,zinc ions storage mechanisms,the existing challenges,and corresponding optimization strategies as well as structure-performance relationship.In the final section,the application perspectives of manganese oxide cathode materials in AZIBs are prospected.

Fundamental Understanding and Optimization Strategies for Dual‑Ion Batteries:A Review

There has been increasing demand for high-energy density and longcycle life rechargeable batteries to satisfy the ever-growing requirements for nextgeneration energy storage systems.Among all available candidates,dual-ion batteries(DIBs)have drawn tremendous attention in the past few years from both academic and industrial battery communities because of their fascinating advantages of high working voltage,excellent safety,and environmental friendliness.However,the dynamic imbalance between the electrodes and the mismatch of traditional electrolyte systems remain elusive.To fully employ the advantages of DIBs,the overall optimization of anode materials,cathode materials,and compatible electrolyte systems is urgently needed.Here,we review the development history and the reaction mechanisms involved in DIBs.Afterward,the optimization strategies toward DIB materials and electrolytes are highlighted.In addition,their energy-related applications are also provided.Lastly,the research challenges and possible development directions of DIBs are outlined.

Optimization Strategies Toward Functional Sodium-Ion Batteries

Exploration of alternative energy storage systems has been more than necessary in view of the supply risks haunting lithium-ion batteries.Among various alternative electrochemical energy storage devices,sodium-ion battery outstands with advantages of cost-effectiveness and comparable energy density with lithium-ion batteries.Thanks to the similar electrochemical mechanism,the research and development of lithium-ion batteries have forged a solid foundation for sodium-ion battery explorations.Advancements in sodium-ion batteries have been witnessed in terms of superior electrochemical performance and broader application scenarios.Here,the strategies adopted to optimize the battery components(cathode,anode,electrolyte,separator,binder,current collector,etc.)and the cost,safety,and commercialization issues in sodium-ion batteries are summarized and discussed.Based on these optimization strategies,assembly of functional(flexible,stretchable,self-healable,and self-chargeable)and integrated sodium-ion batteries(−actuators,−sensors,electrochromic,etc.)have been realized.Despite these achievements,challenges including energy density,scalability,trade-off between energy density and functionality,cost,etc.are to be addressed for sodium-ion battery commercialization.This review aims at providing an overview of the up-to-date achievements in sodium-ion batteries and serves to inspire more efforts in designing upgraded sodium-ion batteries.

Understanding of the charge storage mechanism of MnO_(2)-based aqueous zinc-ion batteries:Reaction processes and regulation strategies

Though secondary aqueous Zn ion batteries(AZIBs)have been received broad concern in recent years,the development of suitable cathode materials of AZIBs is still a big challenge.The MnO_(2) has been deemed as one of most hopeful cathode materials of AZIBs on account of some extraordinary merits,such as richly natural resources,low toxicity,high discharge potential,and large theoretical capacity.However,the crystal structure diversity of MnO_(2) results in an obvious various of charge storage mechanisms,which can cause great differences in electrochemical performance.Furthermore,several challenges,including intrinsic poor conductivity,dissolution of manganese and sluggish ion transport dynamics should be conquered before real practice.This work focuses on the reaction mechanisms and recent progress of MnO_(2)-based materials of AZIBs.In this review,a detailed review of the reaction mechanisms and optimal ways for enhancing electrochemical performance for MnO_(2)-based materials is proposed.At last,a number of viewpoints on challenges,future development direction,and foreground of MnO_(2)-based materials of aqueous zinc ions batteries are put forward.This review clarifies reaction mechanism of MnO_(2)-based materials of AZIBs,and offers a new perspective for the future invention in MnO_(2)-based cathode materials,thus accelerate the extensive development and commercialization practice of aqueous zinc ions batteries.

TOWARD SUSTAINABLE MAIZE PRODUCTION FOR SMALLHOLDERS THROUGH OPTIMIZED STRATEGIES IN NORTH CHINA

Agricultural production by smallholders is crucial for ensuring food provision in China.However,smallholders face a series of challenges on their farms including high-to-excess resource inputs,low use efficiency,as well as negative environmental impacts,which may be unfavorable for sustainable agriculture production.This study developed a county-level sustainability assessment of maize production in Hebei,China,by applying multiple data sources in combination with emergy,carbon footprint,nitrogen footprint and costbenefit analyses.Scenario analysis was applied to explore the localized implementation strategies to achieve the sustainable farming system.The results show that the average emergy sustainability index(ESI)of maize at 2.31 is relatively low.The average greenhouse gas(GHG)emissions and reactive nitrogen(Nr)losses are 0.15 g·kcal^(−1) CO_(2)-eq and 3.75 mg·kcal^(−1) N,respectively.The average cost and net income are 12,700 and 4340 CNY·ha^(−1),respectively.These results indicate a great potential to improve the environmental-economic sustainability of the maize production system of smallholders.In addition,the environmental and economic indicators calculated from the maize production show a substantial spatial heterogeneity among counties,indicating a requirement for different optimization strategies to improve the environment-economy sustainability at a finer scale.Based on the multiple scenario analysis,optimal strategies targeting each county are proposed.By adopting the optimal strategies,the average ESI and net income could increase by 32%and 83%,respectively,and the average GHG emissions and Nr losses reduce by 33%and 35%,respectively.These findings provide an important reference for adopting different strategies to achieve environmenteconomy sustainability for smallholders production systems with diverse landscapes in North China and propose a transition pathway toward achieving agriculture sustainability for smallholders worldwide.

Motion simulation of moorings using optimized LSTM neural network

Mooring arrays have been widely deployed in sustained ocean observation in high resolution to measure finer dynamic features of marine phenomena.However,the irregular posture changes and nonlinear response of moorings under the effect of ocean currents face huge challenges for the deployment of mooring arrays,which may cause the deviations of measurements and yield a vacuum of observation in the upper ocean.We developed a data-driven mooring simulation model based on LSTM(long short-term memory)neural network,coupling the ocean current with position data from moorings to predict the motion of moorings,including single-step output prediction and multi-step prediction.Based on the predictive information,the formation of the mooring array can be adjusted to improve the accuracy and integrity of measurements.Moreover,we proposed the cuckoo search(CS)optimization algorithm to tune the parameters of LSTM,which improves the robustness and generalization of the model.We utilize the datasets observed from moorings anchored in the Kuroshio Extension region to train and validate the simulation model.The experimental results demonstrate that the model can remarkably improve prediction accuracy and yield stable performance.Moreover,compared with other optimization algorithms,CS is more efficient and performs better in simulating the motion of moorings.

Optimal Strategies Trajectory with Multi-Local-Worlds Graph

This paper constructs a non-cooperative/cooperative stochasticdifferential game model to prove that the optimal strategies trajectory ofagents in a system with a topological configuration of a Multi-Local-Worldgraph would converge into a certain attractor if the system’s configuration isfixed. Due to the economics and management property, almost all systems aredivided into several independent Local-Worlds, and the interaction betweenagents in the system is more complex. The interaction between agents inthe same Local-World is defined as a stochastic differential cooperativegame;conversely, the interaction between agents in different Local-Worldsis defined as a stochastic differential non-cooperative game. We construct anon-cooperative/cooperative stochastic differential game model to describethe interaction between agents. The solutions of the cooperative and noncooperativegames are obtained by invoking corresponding theories, and thena nonlinear operator is constructed to couple these two solutions together.At last, the optimal strategies trajectory of agents in the system is proven toconverge into a certain attractor, which means that strategies trajectory arecertainty as time tends to infinity or a large positive integer. It is concluded thatthe optimal strategy trajectory with a nonlinear operator of cooperative/noncooperativestochastic differential game between agents can make agentsin a certain Local-World coordinate and make the Local-World paymentmaximize, and can make the all Local-Worlds equilibrated;furthermore, theoptimal strategy of the coupled game can converge into a particular attractorthat decides the optimal property.

Modeling and Analysis of COVID-19 Optimizated Vaccination Strategies with Age Structure

The rational and effective implementation of epidemic prevention and control measures is crucial to controlling the spread of COVID-19, and vaccination is a key part to be considered in the development of epidemic prevention and control strategies. In order to give full play to the greater role of vaccination strategies in epidemic prevention and control, more accurate and efficient vaccination strategies should be explored. Based on the classical SEIR dynamic model, this paper established a COVID-19 dynamic model of population age structure in the form of population grouping and combined with the transmission characteristics of the COVID-19 epidemic. An optimization model with the goal of minimizing daily infection was established to analyze the optimization studies on infection-related specificity of vaccination for different age groups under the condition of limited daily vaccine supply at the early stage of the epidemic, and to obtain the priority of vaccination strategies for Chinese age groups. And the effect of the heterogeneity of infection rate and hospitalization rate on the priority of vaccine allocation.

Cognitive interference decision method for air defense missile fuze based on reinforcement learning

To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.

A Review of Anode Materials for Dual‑Ion Batteries

Distinct from"rockingchair"lithium-ion batteries(LIBs),the unique anionic intercalation chemistry on the cathode side of dual-ion batteries(DIBs)endows them with intrinsic advantages of low cost,high voltage,and ecofriendly,which is attracting widespread attention,and is expected to achieve the next generation of large-scale energy storage applications.Although the electrochemical reactions on the anode side of DIBs are similar to that of LIBs,in fact,to match the rapid insertion kinetics of anions on the cathode side and consider the compatibility with electrolyte system which also serves as an active material,the anode materials play a very important role,and there is an urgent demand for rational structural design and performance optimization.A review and summarization of previous studies will facilitate the exploration and optimization of DIBs in the future.Here,we summarize the development process and working mechanism of DIBs and exhaustively categorize the latest research of DIBs anode materials and their applications in different battery systems.Moreover,the structural design,reaction mechanism and electrochemical performance of anode materials are briefly discussed.Finally,the fundamental challenges,potential strategies and perspectives are also put forward.It is hoped that this review could shed some light for researchers to explore more superior anode materials and advanced systems to further promote the development of DIBs.

Reinforcement Learning Based Quantization Strategy Optimal Assignment Algorithm for Mixed Precision

The quantization algorithm compresses the original network by reducing the numerical bit width of the model,which improves the computation speed. Because different layers have different redundancy and sensitivity to databit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determinethe optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantizationcan effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In thispaper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to low bitwidth is proposed, and reinforcement learning is used to automatically predict the mixed precision that meets theconstraints of hardware resources. In the state-space design, the standard deviation of weights is used to measurethe distribution difference of data, the execution speed feedback of simulated neural network accelerator inferenceis used as the environment to limit the action space of the agent, and the accuracy of the quantization model afterretraining is used as the reward function to guide the agent to carry out deep reinforcement learning training. Theexperimental results show that the proposed method obtains a suitable model layer-by-layer quantization strategyunder the condition that the computational resources are satisfied, and themodel accuracy is effectively improved.The proposed method has strong intelligence and certain universality and has strong application potential in thefield of mixed precision quantization and embedded neural network model deployment.

Optimized Strategy for Layout of Crop Production Areas in Hunan Province

The optimized strategy made a comprehensive consideration of resources, technology, market orientation, production scale, industry basis and layout based on the principle of crop security and farmers’ income increasing, and determined the general planning on layout and structure optimization of future crop production ar-eas, with present crop production, market outlook, future industry development, con-cluding crop production characteristics of the 4 crop regions, and proposing function orientation and highlights.

Teaching Mode Reform of the Electrical Automation Control Course

Under the background of the new era,higher requirements are put forward for colleges and universities to carry out teaching reform.Teachers of electrical automation control courses should update their teaching ideas regularly,innovate teaching methods,and take novel and effective measures to carry out related work.Because electrical automation control courses tend to be technology-oriented,teachers can help students consolidate basic knowledge.They should also focus on developing practical skills so students can easily adapt to future job positions.However,there are many problems in the actual teaching process,which hampers the improvement of the teaching quality to a certain extent.In view of this,this paper presents an in-depth exploration based on theories and practical experiences.It starts with an analysis of the current teaching status of electrical automation control courses in colleges and universities,followed by suggestions to improve them based on their characteristics and students’needs.

Recent progress and strategies toward high performance zinc-organic batteries

Energy sustainable development has stimulated the pursuit of an eco-friendly energy storage system.Carbon peak and neutrality targets oriented energy storage development will guide the way of further studies on batteries system.However,conventional batteries system(lead-acid batteries,lithium-ion batteries)based on ungreen transition metal oxide,flammable electrolytes or hazardous metals cannot keep pace with the development of society sooner or later.Thus,vast explorations on the advanced rechargeable battery systems were conducted.Compared with other battery systems,zinc ion battery systems with inherent safety,low cost were widely investigated.Especially,the zinc organic batteries based on the eco-efficiency organic cathodes were promising alternative advanced batteries for future energy storage systems.Therefore,various organics and different electrochemistry mechanisms were explored in the zinc batteries system.Herein,a timely review on elaborate analysis about functional groups,fundamentals,progress accompanied by the discussion on the four core issues:voltage,capacity,rate performance,cycle life was presented.Specifically,aiming at these issues,three levels of solution strategies:materials design concepts,morphology structure optimization and electrolyte environment were summarized and proposed for the development and innovation of zinc organic batteries.

Integration strategies of hydrogen network in a refinery based on operational optimization of hydrotreating units

Inferior crude oil and fuel oil upgrading lead to escalating increase of hydrogen consumption in refineries.It is imperative to reduce the hydrogen consumption for energy-saving operations of refineries.An integration strategy of hydrogen network and an operational optimization model of hydrotreating(HDT)units are proposed based on the characteristics of reaction kinetics of HDT units.By solving the proposed model,the operating conditions of HDT units are optimized,and the parameters of hydrogen sinks are determined by coupling hydrodesulfurization(HDS),hydrodenitrification(HDN)and aromatic hydrogenation(HDA)kinetics.An example case of a refinery with annual processing capacity of eight million tons is adopted to demonstrate the feasibility of the proposed optimization strategies and the model.Results show that HDS,HDN and HDA reactions are the major source of hydrogen consumption in the refinery.The total hydrogen consumption can be reduced by 18.9%by applying conventional hydrogen network optimization model.When the hydrogen network is optimized after the operational optimization of HDT units is performed,the hydrogen consumption is reduced by28.2%.When the benefit of the fuel gas recovery is further considered,the total annual cost of hydrogen network can be reduced by 3.21×10~7CNY·a^(-1),decreased by 11.9%.Therefore,the operational optimization of the HDT units in refineries should be imposed to determine the parameters of hydrogen sinks base on the characteristics of reaction kinetics of the hydrogenation processes before the optimization of the hydrogen network is performed through the source-sink matching methods.

Dominating factors on well productivity and development strategies optimization in Weiyuan shale gas play, Sichuan Basin, SW China

Weiyuan shale gas play is characterized by thin high-quality reservoir thickness,big horizontal stress difference,and big productivity differences between wells.Based on integrated evaluation of shale gas reservoir geology and well logging interpretation of more than 20 appraisal wells,a correlation was built between the single well test production rate and the high-quality reservoir length drilled in the horizontal wells,high-quality reservoir thickness and the stimulation treatment parameters in over 100 horizontal wells,the dominating factors on horizontal well productivity were found out,and optimized development strategies were proposed.The results show that the deployed reserves of high-quality reservoir are the dominating factors on horizontal well productivity.In other words,the shale gas well productivity is controlled by the thickness of the high-quality reservoir,the high-quality reservoir drilling length and the effectiveness of stimulation.Based on the above understanding,the development strategies in Weiyuan shale gas play are optimized as follows:(1)The target of horizontal wells is located in the middle and lower parts of Longyi 11(Wei202 area)and Longyi 11(Wei204 area).(2)Producing wells are drilled in priority in the surrounding areas of Weiyuan county with thick high-quality reservoir.(3)A medium to high intensity stimulation is adopted.After the implementation of these strategies,both the production rate and the estimated ultimate recovery(EUR)of individual shale gas wells have increased substantially.

Implementation of Radial Basis Function Artificial Neural Network into an Adaptive Equivalent Consumption Minimization Strategy for Optimized Control of a Hybrid Electric Vehicle

Continued increases in the emission of greenhouse gases by passenger vehicles have accelerated the production of hybrid electric vehicles. With this increase in production, there has been a parallel demand for continuously improving strategies of hybrid electric vehicle control. The goal of an ideal control strategy is to maximize fuel economy while minimizing emissions. Methods exist by which the globally optimal control strategy may be found. However, these methods are not applicable in real-world driving applications since these methods require a priori knowledge of the upcoming drive cycle. Real-time control strategies use the global optimal as a benchmark against which performance can be evaluated. The goal of this work is to use a previously defined strategy that has been shown to closely approximate the global optimal and implement a radial basis function (RBF) artificial neural network (ANN) that dynamically adapts the strategy based on past driving conditions. The strategy used is the Equivalent Consumption Minimization Strategy (ECMS), which uses an equivalence factor to define the control strategy and the power train component torque split. An equivalence factor that is optimal for a single drive cycle can be found offline with a priori knowledge of the drive cycle. The RBF-ANN is used to dynamically update the equivalence factor by examining a past time window of driving characteristics. A total of 30 sets of training data (drive cycles) are used to train the RBF-ANN. For the majority of drive cycles examined, the RBF-ANN implementation is shown to produce fuel economy values that are within ±2.5% of the fuel economy obtained with the optimal equivalence factor. The advantage of the RBF-ANN is that it does not require a priori drive cycle knowledge and is able to be implemented in real-time while meeting or exceeding the performance of the optimal ECMS. Recommendations are made on how the RBF-ANN could be improved to produce better results across a greater array of driving conditions.

Bi-matrix Games with Fuzzy Strategies and Fuzzy Payoffs and Their Mathematical Programming Equivalents

A fuzzy bi-matrix game（FBG）,namely a two-person non-zero-sum game with fuzzy strategies and fuzzy payoffs is proposed.We have defined and analyzed the optimal strategies of this FBG,and shown that it can be transformed into a corresponding fuzzy mathematical programming issue,for which a ranking function approach can be applied.In addition,optimal strategies of FBG for both Player I and Player II can be gotten.