Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle performance.This study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power sources.Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces.They often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing conditions.Moreover,these algorithms suffer from low sample efficiency.Collectively,these factors contribute to convergence difficulties,low learning efficiency,and instability.To address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience samples.Additionally,the correspondingMarkovDecision Process(MDP)is established.Finally,an EMSbased on the improvedDRLmodel is presented.Comparative simulation experiments are conducted against rule-based,optimization-based,andDRL-based EMSs.The proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global information.In the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 g.Compared to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%,15.1%,and 8.37%over the Deep QNetwork(DQN),Double DRL(DDRL),and original DDPG methods,respectively.The observational outcomes demonstrate that the proposed EMS based on improved DRL framework possesses good real-time performance,stability,and reliability,effectively optimizing vehicle economy and fuel consumption.

Optimizing pain management in elderly patients post-knee surgery:A novel collaborative strategy

Total knee replacement,a common surgery among the elderly primarily necessitated by osteoarthritis,replaces the damaged knee joint with an artificial one.Given the aging population and the increasing prevalence of such surgeries,the article highlights the critical need for effective postoperative care strategies.This editorial provides an overview of rehabilitation care for pain in elderly knee replacement patients,emphasizing the importance of a multimodal approach to postoperative recovery.Furthermore,the article advocates for a patient-centered,comprehensive rehabilitation regimen that enhances recovery and quality of life in elderly patients undergoing knee replacement surgery.

Research on Innovation Strategy of Supply Chain Management of Agricultural Enterprises Under the Background of Big Data

With the rapid development and widespread application of Big Data technology, the supply chain management of agricultural products enterprises is facing unprecedented reform and challenges. This study takes the perspective of Big Data technology and collects relevant information on the application of supply chain management in 100 agricultural product enterprises through a survey questionnaire. The study found that the use of Big Data can effectively improve the accuracy of demand forecasting, inventory management efficiency, optimize logistics costs, improve supplier management efficiency, enhance the overall level of supply chain management of enterprises, and propose innovative strategies for supply chain management of agricultural products enterprises based on this. Big Data technology brings a new solution for agricultural products enterprises to enhance their supply chain management level, making the supply chain smarter and more efficient.

Automobile Transportation Logistics Supply Chain Management Strategy

To enhance the management level and quality of the automobile transportation logistics supply chain and promote innovation and development in automobile transportation logistics enterprises,it is essential to strengthen the construction of the automobile transportation logistics supply chain management model.This can be achieved through the gradual improvement of the automobile transportation logistics management process,ensuring that the management of the automobile transportation logistics supply chain proceeds in an orderly manner.The aim is to improve automobile transportation and logistics service levels while meeting the changing market supply needs.This will enable automobile transportation and logistics enterprises to maintain steady economic benefits and enhance their core competitiveness in the market.Therefore,this paper has conducted a comprehensive exploration and research on managing the automobile transportation logistics supply chain.Corresponding management strategies are proposed as a starting point to achieve the aforementioned goals.

Analysis of Innovative Paths for Enterprise Marketing Management Development Strategy under the Background of New Media

From the perspective of enterprise marketing strategy planning,innovative research should be conducted based on the current trends in new media.The findings should be applied to practical activities within enterprises to achieve innovation in marketing strategy decision-making in the new media environment.Enterprises should adopt advanced communication transmission technologies and big data processing capabilities to effectively leverage the hidden value and promotional planning advantages of network media platforms.This approach can enhance customer loyalty and increase demand for new products.Enterprises should integrate into the continuously evolving new media landscape,explore their potential business characteristics,and innovate promotional methods.By effectively combining product information with digital media content,companies can ultimately achieve significant increases in corporate interests.

Interpretation of Chinese Expert Consensus on the Diagnosis and Management Strategy of Patients with Statin Intolerance: A guiding file for helping to lipid management for Chinese population

It is well-known that elevated low-density lipoprotein cholesterol(LDL-C)is a causal risk factor for atheroscler-otic cardiovascular disease(ASCVD),statins are cornerstone drugs for the cause-based treatment of ASCVD,which has created a new era for ASCVD therapy.However,statin intolerance is not clinically uncommon,which there are several issues with confu-sion and misunderstandings.Hence,a file named Chinese Expert Consensus on the Diagnosis and Management Strategy of Pa-tients With Statin Intolerance,like a navigator,has recently been published written by a team of experts from the Cardiovascular Metabolic Medicine Professional Committee,Expert Committee of the National Center for Cardiovascular Diseases aiming to en-hance the standardized clinical application of statins and improve the prevention and clinical outcome.In this article,author briefly summarized the key points of above consensus in order to helping to comprehending the content of the consensus sugges-tions.

Research on Enterprise Legal Service Strategy Based on Compliance Management Optimization

With the background of enterprise compliance management,this paper discusses how to improve the level of enterprise legal service and reduce enterprise legal risks by optimizing the compliance management system.It aims to analyze the current situation and existing problems of enterprise legal services through the analysis of the importance of compliance management.Furthermore,it delves into the case of enterprise legal service strategy based on compliance management optimization to verify the effectiveness and feasibility of enterprise legal service strategy.

Construction Project Management and Construction Quality Control Strategy

With the gradual acceleration of the urbanization process,the construction industry has been developing rapidly.As the key link to ensure the quality and safety of the project,construction management and construction quality control are of great significance to enhance the competitiveness of construction enterprises and realize sustainable development.In this paper,the effective strategy of construction management and the effective strategy of construction quality control will be discussed in depth,aiming at providing useful management and quality control strategies for construction enterprises.

Research on Enterprise Human Resource Management Reform Strategy in the Era of Big Data

In the 21st century,with the development of the Internet,mobile devices,and information technology,society has entered a new era:the era of big data.With the help of big data technology,enterprises can obtain massive market and consumer data,realize in-depth analysis of business and market,and enable enterprises to have a deeper understanding of consumer needs,preferences,and behaviors.At the same time,big data technology can also help enterprises carry out human resource management innovation and improve the performance and competitiveness of enterprises.Of course,from another perspective,enterprises in this era are also facing severe challenges.In the face of massive data processing and analysis,it requires superb data processing and analysis capabilities.Secondly,enterprises need to reconstruct their management system to adapt to the changes in the era of big data.Enterprises must treat data as assets and establish a perfect data management system.In addition,enterprises also need to pay attention to protecting customer privacy and data security to avoid data leakage and abuse.In this context,this paper will explore the thinking of enterprise human resource management innovation in the era of big data,and put forward some suggestions on enterprise human resource management innovation.

The Integration Strategy of Class Teacher Management and Mathematics Teaching

The professional and moral education of high school mathematics teachers will make classroom management work better,but their work pressure will also lead to classroom management problems.To do a good job in high school class teacher management and organically integrate it with mathematics teaching,we need to start from two aspects:mathematics teaching class teachers and class teacher work teaching,and penetrate mathematical thinking into daily classroom management,moral education,and classroom culture construction.Based on the attributes of the subject,we guide high school students to reflect after class to stimulate their self-management initiative through the cultivation of qualified class representatives.In addition,it is necessary to skillfully resolve classroom generative problems,change the roles of teachers and students,and integrate classroom management with mathematics teaching.

Analysis of Information Leadership and Digital Campus Management Strategy

In the information age,the development of schools needs to be integrated with information education,and the principal,as the leader of the school,has a positive significance for the development of the school.Therefore,in the process of school informatization development,principals should continuously improve their informatization leadership,and take digitalization as the guide to build schools,accelerate the construction and improvement of campus management,and then promote the school to continuously optimize the overall management and business processes under the immersion of digital culture.Based on this,this paper is based on information leadership and digital campus,and explores the way to improve the information leadership of principals based on the construction of digital campus.

Site Management Strategy in Highway Project Management

Highway project management involves overseeing the on-site construction of a highway project,taking into account the specific circumstances and conditions of the site.This type of management requires a high level of expertise and is characterized by its dynamic and systematic approach.Effective on-site management can ensure the quality,cost-saving,smooth progress,and safety of highway construction.However,there are still some problems in the implementation of site management in some highway projects,which seriously affect the improvement of site management.This paper analyzes the characteristics and existing problems of highway engineering management,and puts forward the effective strategies of site management,hoping that this study will help to improve highway engineering site management.

Research on the Reform Strategy of University Education Management from the Perspective of Innovative Education

With the advent of the knowledge economy era and the acceleration of globalization,the demand for talent in society has gradually become innovative.The traditional mode of university education management has become difficult to adapt to the requirements of the new era.Therefore,it is urgent to reform university education management from the perspective of innovative education.This article aims to explore the inherent relationship between innovative education and education management,analyze the current situation and existing problems of university education management,and propose strategies for reforming university education management,providing references for universities to cultivate innovative talents.

Application Strategy of Digital Comprehensive Management and Maintenance System for Bridges

Effective application of digital integrated management and maintenance systems is essential for successful operation and maintenance management of bridge projects.This article analyzes the application strategy of such systems.It provides an overview of comprehensive digital management and maintenance of bridges,an analysis of the basic components of the integrated management and maintenance system,and its application strategies.This study aims to offer guidance for the application of the system and to improve the quality of modern bridge engineering management and maintenance work.

Smart City Rail Transit Operation and Management Information Construction Strategy

Rail transit is considered one of the safest and most efficient modes of transportation.Ticketing,vehicle dispatching,and passenger flow control during rail transit operations in China have been improving over the years.Smart city construction and intelligent management models has also been increasingly emphasized with the rapid development of information and internet technology.Therefore,it is essential to conduct relevant research and discussions to improve the overall efficiency and quality of urban rail transit operation and management.This article provides an overview of smart city rail transit operation and management informatization,the principles of construction,and the functions of smart city rail transit operation and management informatization.Additionally,it discusses the strategies for the construction of smart city rail transit operation and management information and its development prospects.

Bottom-up holistic carrier management strategy induced synergistically by multiple chemical bonds to minimize energy losses for efficient and stable perovskite solar cells

The defects from electron transport layer,perovskite layer and their interface would result in carrier nonradiative recombination losses.Poor buried interfacial contact is detrimental to charge extraction and device stability.Here,we report a bottom-up holistic carrier management strategy induced synergistically by multiple chemical bonds to minimize bulk and interfacial energy losses for high-performance perovskite photovoltaics.4-trifluoromethyl-benzamidine hydrochloride(TBHCl)containing–CF_(3),amidine cation and Cl^(-)is in advance incorporated into SnO_(2)colloid solution to realize bottom-up modification.The synergistic effect of multiple functional groups and multiple-bond-induced chemical interaction are revealed theoretically and experimentally.F and Cl^(-)can passivate oxygen vacancy and/or undercoordinated Sn^(4+)defects by coordinating with Sn^(4+).The F can suppress cation migration and modulate crystallization via hydrogen bond with FA^(+),and can passivate lead defects by coordinating with Pb^(2+).The–NH_(2)–C=NH^(+)_(2)and Cl^(-)can passivate cation and anion vacancy defects through ionic bonds with perovskites,respectively.Through TBHCl modification,the suppression of agglomeration of SnO_(2)nanoparticles,bulk and interfacial defect passivation,and release of tensile strains of perovskite films are demonstrated,which resulted in a PCE enhancement from 21.28%to 23.40%and improved stability.With post-treatment,the efficiency is further improved to 23.63%.

Overview of the immunological mechanisms in hepatitis B virus reactivation:Implications for disease progression and management strategies

Hepatitis B virus(HBV)reactivation is a clinically significant challenge in disease management.This review explores the immunological mechanisms underlying HBV reactivation,emphasizing disease progression and management.It delves into host immune responses and reactivation’s delicate balance,spanning innate and adaptive immunity.Viral factors’disruption of this balance,as are interac-tions between viral antigens,immune cells,cytokine networks,and immune checkpoint pathways,are examined.Notably,the roles of T cells,natural killer cells,and antigen-presenting cells are discussed,highlighting their influence on disease progression.HBV reactivation’s impact on disease severity,hepatic flares,liver fibrosis progression,and hepatocellular carcinoma is detailed.Management strategies,including anti-viral and immunomodulatory approaches,are critically analyzed.The role of prophylactic anti-viral therapy during immunosuppressive treatments is explored alongside novel immunotherapeutic interventions to restore immune control and prevent reactivation.In conclusion,this compre-hensive review furnishes a holistic view of the immunological mechanisms that propel HBV reactivation.With a dedicated focus on understanding its implic-ations for disease progression and the prospects of efficient management stra-tegies,this article contributes significantly to the knowledge base.The more profound insights into the intricate interactions between viral elements and the immune system will inform evidence-based approaches,ultimately enhancing disease management and elevating patient outcomes.The dynamic landscape of management strategies is critically scrutinized,spanning anti-viral and immunomodulatory approaches.The role of prophylactic anti-viral therapy in preventing reactivation during immunosuppressive treatments and the potential of innovative immunotherapeutic interventions to restore immune control and proactively deter reactivation.

Reinforcement Learning-Based Electric Vehicles Energy Management Strategy with Battery Thermal Model

The promotion of electric vehicles(EVs)is restricted due to their short cruising range.It is desirable to design an effective energy management strategy to improve their energy efficiency.Most existing work concerning energy management strategies focused on hybrids rather than the EVs.The work focusing on the energy management strategy for EVs mainly uses the traditional optimization strategies,thereby limiting the advantages of energy economy.To this end,a novel energy management strategy that considered the impact of battery thermal effects was proposed with the help of reinforcement learning.The main idea was to first analyze the energy flow path of EVs,further formulize the energy management as an optimization problem,and finally propose an online strategy based on reinforcement learning to obtain the optimal strategy.Additionally,extensive simulation results have demonstrated that our strategy reduces energy consumption by at least 27.4%compared to the existing methods.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Factors affecting farmers'choice to adopt risk management strategies:The application of multivariate and multinomial probit models

This study investigates the factors that impact farmers'adoption of risk management strategies(RMS)in Pakistan during times of uncertainty.The study examines farmers'adoption of RMS using both multinomial probit(MNP)and multivariate probit(MVP).Data were collected from 382 farmers sampled from four districts in KhyberPakhtunkhwa(KP)province of Pakistan via a multistage sampling technique.This study utilizes the MNP model,considering the assumption of Independence of Irrelevant Alternatives(IIA)and incorporating correlated error terms.The objective is to understand farmers'behavior in risky situations and determine if there is heterogeneity.Results are compared with the MVP model to assess robustness and gain deeper understanding of farmers'decisionmaking processes.The research findings reveal that our results are robust,and farmers behave homogeneously in various RMS scenarios.Farmers adopt RMS individually or in combination to mitigate the adverse effects of natural calamities on their livelihood.The risk-averse farmers,who perceive weather-related risks as a threat,access credits and information,and have farms close to a river are more likely to adopt RMS,irrespective of the format of the strategies available.Moreover,the predicted probabilities and correlation of the RMS and RM categories have strengthened our model estimation.These findings provide insights into the behavior of farmers in adopting RMS which are helpful for policymakers and stakeholders in developing strategies to mitigate the impacts of natural calamities on farmers.