Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

Operation optimization strategy of existing residential building energy-saving renovation market:From the perspective of subject behavior

The energy-saving renovation of existing residential buildings is a crucial measure to achieve the strategic goal of energy conservation and emission reduction in China and build ecologically livable cities.This article focuses on the perspective of subject behavior,starting from analyzing the current situation and difficulties of the operation of the energy-saving renovation market for existing residential buildings in China,drawing on the practical experience of the operation of the existing residential building energy-saving renovation market abroad.Based on principles such as systematicity,humanization,feasibility,and sustainability,the article constructs an operation optimization system of the existing residential building energy-saving renovation market from the perspective of subject behavior.In order to provide a reference for the healthy and orderly operation of the existing residential building energy-saving renovation market,this paper proposes implementation strategies for optimizing the operation of the existing residential building energy-saving renovation market.Suggestions are proposed from four aspects:optimizing the market environment,innovating the financing model,building the information sharing platform,and utilizing the synergies of the main subjects.

Energy-Saving Construction Technologies for Buildings

The development of the construction industry is shifting towards low-carbon construction,so it is necessary to improve and optimize related construction concepts,methods,and processes.By improving resource and energy control efficiency in building projects,minimizing construction waste,and reducing environmental impact,a foundation for the sustainable development of the industry can be established.This paper mainly analyzes the significance of low-carbon energy-saving construction technology and the control factors of construction,summarizes the status quo of the development of building energy-saving construction,and puts forward strategies for applying building energy-saving construction technology.These strategies serve to achieve low-carbon and energy-saving goals to promote the healthy development of energy-saving construction.

Application of Energy-Saving Materials in Architectural Design

The conventional process of building construction is associated with issues such as the waste of construction materials and environmental pollution.Sustainable development highlights the importance of energy conservation and eco-friendly practices.It is essential to use energy-efficient and green materials in building designs to ensure the healthy growth of construction companies.This article discusses the advantages and principles of incorporating energy-saving materials in architectural design.It examines the strategies and critical control points for using energy-saving materials in architectural design,offering guidance for the sustainable development of the construction industry.

Exploration of Energy-Saving Technologies in Building Electrical System Design

Green energy conservation is the mainstream trend in the current development of the construction industry.The application of energy-saving technology in building electrical system design can effectively reduce energy consumption,avoid unnecessary energy consumption,and truly achieve energy conservation and environmental protection.Based on this,the article elaborates on the principles of energy-saving design in building electrical systems,and actively explores the application of energy-saving technologies from different perspectives such as optimizing power supply and distribution system design,adopting high-efficiency energy-saving lighting equipment,applying renewable energy,promoting smart home technology,and improving the efficiency of building electrical equipment.

Multi-subject and multi-objective integrated optimization system and implementation strategy for energy-saving renovation of the existing residential buildings

The core of the healthy and orderly operation of the existing residential building energy-saving renovation market lies in the exploration of the implementation mechanism of multi-subject and multi-objective integrated optimization.The multi-agent and multi-objective integrated optimization system framework is a powerful tool to guide the scientific decision-making of the market core structural entities in the future market practice. This paper analyzes the practical dilemma of energy-saving renovation of theexisting residential buildings in China, summarizes the practical experience of multi-subject and multi-objective integrated optimization of energy-saving renovation of the existing residential buildings in foreign countries, and puts forward beneficial practical enlightenment on the basis of comparison at home and abroad;The design principles of the target integrated optimization system have established a multi-subject and multi-objective integrated optimization system framework for the energy-saving renovation of the existing residential buildings, from six aspects: government guidance, trust consensus, value co-creation, risk sharing, revenue sharing, and social responsibility sharing. This paper proposes a multi-subject and multi-objective integrated practice strategy, in order to promote the efficient and orderly development of China's existing residential building energy-saving renovation market.

Application Strategy of PLC Technology in Energy-Saving Control of Tunnel Lighting

In this study,we investigated on the application of planar lightwave circuit(PLC)technology in energy-saving control of tunnel lighting.The application status of PLC in the field of energy saving followed by the necessity of energy saving in tunnel lighting was analyzed.Finally,the application of PLC in tunnel lighting energy-saving control around the three dimensions of system overall architecture design,control scheme,and program control process was investigated.The results showed that the system meets the requirements of control effect,robustness,and visual effect after trial operation,and is suitable for practical applications.

Green,Sustainable Architectural Bamboo with High Light Transmission and Excellent Electromagnetic Shielding as a Candidate for Energy-Saving Buildings

Currently,light-transmitting,energy-saving,and electromagnetic shielding materials are essential for reducing indoor energy consumption and improving the electromagnetic environment.Here,we developed a cellulose composite with excellent optical transmittance that retained the natural shape and fiber structure of bamboo.The modified whole bamboo possessed an impressive optical transmittance of approximately 60%at 6.23 mm,illuminance of 1000 luminance(lux),water absorption stability(mass change rate less than 4%),longitudinal tensile strength(46.40 MPa),and surface properties(80.2 HD).These were attributed to not only the retention of the natural circular hollow structure of the bamboo rod on the macro,but also the complete bamboo fiber skeleton template impregnated with UV resin on the micro.Moreover,a multilayered device consisting of translucent whole bamboo,transparent bamboo sheets,and electromagnetic shielding film exhibited remarkable heat insulation and heat preservation performance as well as an electromagnetic shielding performance of 46.3 dB.The impressive optical transmittance,mechanical properties,thermal performance,and electromagnetic shielding abilities combined with the renewable and sustainable nature,as well as the fast and efficient manufacturing process,make this bamboo composite material suitable for effective application in transparent,energy-saving,and electromagnetic shielding buildings.

Low-content Pt-triggered the optimized d-band center of Rh metallene for energy-saving hydrogen production coupled with hydrazine degradation

Utilizing the hydrazine-assisted water electrolysis for energy-efficient hydrogen production shows a promising application, which relies on the development and design of efficient bifunctional electrocatalysts. Herein, we reported a low-content Pt-doped Rh metallene(Pt-Rhene) for hydrazine-assisted water electrolysis towards energy-saving hydrogen(H_(2)) production, where the ultrathin metallene is constructed to provide enough favorable active sites for catalysis and improve atom utilization.Additionally, the synergistic effect between Rh and Pt can optimize the electronic structure of Rh for improving the intrinsic activity. Therefore, the required overpotential of Pt-Rhene is only 37 mV to reach a current density of-10 mA cm^(-2) in the hydrogen evolution reaction(HER), and the Pt-Rhene exhibits a required overpotential of only 11 mV to reach a current density of 10 mA cm^(-2) in the hydrazine oxidation reaction(HzOR). With the constructed HER-HzOR two-electrode system, the Pt-Rhene electrodes exhibit an extremely low voltage(0.06/0.19/0.28 V) to achieve current densities of 10/50/100 mA cm^(-2) for energy-saving H_(2) production, which greatly reduces the electrolysis energy consumption. Moreover,DFT calculations further demonstrate that the introduction of Pt modulates the electronic structure of Rh and optimizes the d-band center, thus enhancing the adsorption and desorption of reactant/intermediates in the electrocatalytic reaction.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Experimental study on the effect of unloading rate on gneiss rockburst

Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic,intricately governed by natural selection and historically garnering considerable attention.Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain,ushering in an unprecedented era of mutation rate research.This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates.It examines various types of mutations,explores the evolutionary dynamics and associated theories,and synthesizes both classical and contemporary hypotheses.Furthermore,this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies,mutational patterns,molecular mechanisms,and driving forces influencing variations in mutation rates across species and tissues.Finally,it proposes several potential research directions and pressing questions for future investigations.

Design of Diversified Intelligent Control System for Energy-saving Optimization of Solar Greenhouse in North China

Intelligent greenhouse can promote the development of modern agriculture, realize the high quality and high yield of crops, and also bring greater economic benefits. In accordance with the climate conditions in northwest China, a set of intelligent control system for diversified environment of solar greenhouse was designed. The system divides the annual greenhouse control into six stages according to the optimal energy saving. It uses modern detection technology to collect the greenhouse environmental temperature, environmental humidity, soil humidity, CO_(2) concentration and illumination parameters under different working modes. It uses programmable logic control technology to realize the data processing of various parameters and the action control of rolling film, wet curtain fan and other actuators. It uses KingView monitoring software to realize the monitoring and manual control of greenhouse environment parameters. The operation results indicate that the control system runs stably and basically meets the control requirements.

Behavior characteristics and market operation problems of existing building energy-saving renovation market

The long-term and effective implementation of the existing building energy efficiency renovation depends on the development of the existing building energy efficiency renovation market.The key to the development of the existing building energy efficiency renovation market is the joint role of the market players.Starting with the analysis of the externalities and information asymmetry of the existing building energy efficiency renovation market,this paper analyzes the behavioral characteristics and influencing factors of the existing building energy efficiency renovation market entities(central government,local government,owners,energy conservation service enterprises,third-party evaluation institutions,and other market entities),and reveals the problems of the existing building energy efficiency renovation market,such as the absence of government,the lack of main power,and the lack of financing channels,Thus,it lays a platform foundation for the research on the behavior strategy and security system of the existing building energy-s aving renovation market.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.

Application of Variable Strategies in the Low-cost and Energy-saving Rural Residences in Transitional Areas

Changeful and complex rural family structure and climatic features of transitional areas in China make the application of variable strategy in energy-saving rural residence designs possible.Aiming at the low cost,several effective and reasonable variable strategies were proposed for the design of interior spaces,main bedroom,sunshine room,staircase,west wall,door and window design to satisfy changing structure of a family during different periods and their different thermo-technical requirements in winter and summer.In this way,thermal comfort of rural indoor spaces will be improved,more energy saved,useful experience and thoughts provided for the energy-saving residence design in cold regions and regions hot in summer and cold in winter.

Fluorinated semi-interpenetrating polymer networks for enhancing the mechanical performance and storage stability of polymer-bonded explosives by controlling curing and phase separation rates

Herein, the effect of fluoropolymer binders on the properties of polymer-bonded explosives(PBXs) was comprehensively investigated. To this end, fluorinated semi-interpenetrating polymer networks(semiIPNs) were prepared using different catalyst amounts(denoted as F23-CLF-30-D). The involved curing and phase separation processes were monitored using Fourier-transform infrared spectroscopy, differential scanning calorimetry, a haze meter and a rheometer. Curing rate constant and activation energy were calculated using a theoretical model and numerical method, respectively. Results revealed that owing to its co-continuous micro-phase separation structure, the F23-CLF-30-D3 semi-IPN exhibited considerably higher tensile strength and elongation at break than pure fluororubber F2314 and the F23-CLF-30-D0 semi-IPN because the phase separation and curing rates matched in the initial stage of curing.An arc Brazilian test revealed that F23-CLF-30-D-based composites used as mock materials for PBXs exhibited excellent mechanical performance and storage stability. Thus, the matched curing and phase separation rates play a crucial role during the fabrication of high-performance semi-IPNs;these factors can be feasibly controlled using an appropriate catalyst amount.