Research on Public Engineering Emergency Decision-Making Based on Multi-Granularity Language Information

To effectively deal with fuzzy and uncertain information in public engineering emergencies,an emergency decision-making method based on multi-granularity language information is proposed.Firstly,decision makers select the appropriate language phrase set according to their own situation,give the preference information of the weight of each key indicator,and then transform the multi-granularity language information through consistency.On this basis,the sequential optimization technology of the approximately ideal scheme is introduced to obtain the weight coefficient of each key indicator.Subsequently,the weighted average operator is used to aggregate the preference information of each alternative scheme with the relative importance of decision-makers and the weight of key indicators in sequence,and the comprehensive evaluation value of each scheme is obtained to determine the optimal scheme.Lastly,the effectiveness and practicability of the method are verified by taking the earthwork collapse accident in the construction of a reservoir as an example.

A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets,Aggregation Operators and Basic Uncertainty Information Granule

Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.

Optimizing electronic structure through point defect engineering for enhanced electrocatalytic energy conversion

Point defect engineering endows catalysts with novel physical and chemical properties,elevating their electrocatalytic efficiency.The introduction of defects emerges as a promising strategy,effectively modifying the electronic structure of active sites.This optimization influences the adsorption energy of intermediates,thereby mitigating reaction energy barriers,altering paths,enhancing selectivity,and ultimately improving the catalytic efficiency of electrocatalysts.To elucidate the impact of defects on the electrocatalytic process,we comprehensively outline the roles of various point defects,their synthetic methodologies,and characterization techniques.Importantly,we consolidate insights into the relationship between point defects and catalytic activity for hydrogen/oxygen evolution and CO_(2)/O_(2)/N_(2) reduction reactions by integrating mechanisms from diverse reactions.This underscores the pivotal role of point defects in enhancing catalytic performance.At last,the principal challenges and prospects associated with point defects in current electrocatalysts are proposed,emphasizing their role in advancing the efficiency of electrochemical energy storage and conversion materials.

Morphology engineering of ZnO micro/nanostructures under mild conditions for optoelectronic application

Zinc oxide(ZnO)serves as a crucial functional semiconductor with a wide direct bandgap of approximately 3.37 eV.Solvothermal reaction is commonly used in the synthesis of ZnO micro/nanostructures,given its low cost,simplicity,and easy implementation.Moreover,ZnO morphology engineering has become desirable through the alteration of minor conditions in the reaction process,particularly at room temperature.In this work,ZnO micro/nanostructures were synthesized in a solution by varying the amounts of the ammonia added at low temperatures(including room temperature).The formation of Zn^(2+)complexes by ammonia in the precursor regulated the reaction rate of the morphology engineering of ZnO,which resulted in various structures,such as nanoparticles,nanosheets,microflowers,and single crystals.Finally,the obtained ZnO was used in the optoelectronic application of ultraviolet detectors.

Defect Engineering with Rational Dopants Modulation for High‑Temperature Energy Harvesting in Lead‑Free Piezoceramics

High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless sensors.However,simultaneously excellent performances,including high figure of merit(FOM),insulation resistivity(ρ)and depolarization temperature(Td)are indispensable but hard to achieve in lead-free piezoceramics,especially operating at 250°C has not been reported before.Herein,well-balanced performances are achieved in BiFeO3–BaTiO3 ceramics via innovative defect engineering with respect to delicate manganese doping.Due to the synergistic effect of enhancing electrostrictive coefficient by polarization configuration optimization,regulating iron ion oxidation state by high valence manganese ion and stabilizing domain orientation by defect dipole,comprehensive excellent electrical performances(Td=340°C,ρ250°C>10^(7)Ωcm and FOM_(250°C)=4905×10^(–15)m^(2)N^(−1))are realized at the solid solubility limit of manganese ions.The HT-PEHs assembled using the rationally designed piezoceramic can allow for fast charging of commercial electrolytic capacitor at 250°C with high energy conversion efficiency(η=11.43%).These characteristics demonstrate that defect engineering tailored BF-BT can satisfy high-end HT-PEHs requirements,paving a new way in developing selfpowered wireless sensors working in HT environments.

Healthcare providers’perspectives on factors influencing their critical care decision-making during the COVID-19 pandemic:An international pilot survey

BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpful in uncertain situations is clinical judgment.Clinicians must deal with contradictory information,lack of time to make decisions,and long-term factors when emergencies occur.AIM To examine the ethical issues healthcare professionals faced during the coronavirus disease 2019(COVID-19)pandemic and the factors affecting clinical decision-making.METHODS This pilot study,which means it was a preliminary investigation to gather information and test the feasibility of a larger investigation was conducted over 6 months and we invited responses from clinicians worldwide who managed patients with COVID-19.The survey focused on topics related to their professional roles and personal relationships.We examined five core areas influencing critical care decision-making:Patients'personal factors,family-related factors,informed consent,communication and media,and hospital administrative policies on clinical decision-making.The collected data were analyzed using the χ^(2) test for categorical variables.RESULTS A total of 102 clinicians from 23 specialties and 17 countries responded to the survey.Age was a significant factor in treatment planning(n=88)and ventilator access(n=78).Sex had no bearing on how decisions were made.Most doctors reported maintaining patient confidentiality regarding privacy and informed consent.Approximately 50%of clinicians reported a moderate influence of clinical work,with many citing it as one of the most important factors affecting their health and relationships.Clinicians from developing countries had a significantly higher score for considering a patient's financial status when creating a treatment plan than their counterparts from developed countries.Regarding personal experiences,some respondents noted that treatment plans and preferences changed from wave to wave,and that there was a rapid turnover of studies and evidence.Hospital and government policies also played a role in critical decision-making.Rather than assessing the appropriateness of treatment,some doctors observed that hospital policies regarding medications were driven by patient demand.CONCLUSION Factors other than medical considerations frequently affect management choices.The disparity in treatment choices,became more apparent during the pandemic.We highlight the difficulties and contradictions between moral standards and the realities physicians encountered during this medical emergency.False information,large patient populations,and limited resources caused problems for clinicians.These factors impacted decision-making,which,in turn,affected patient care and healthcare staff well-being.

Defect Engineering:Can it Mitigate Strong Coulomb Effect of Mg^(2+)in Cathode Materials for Rechargeable Magnesium Batteries?

Rechargeable magnesium batteries(RMBs)have been considered a promising“post lithium-ion battery”system to meet the rapidly increasing demand of the emerging electric vehicle and grid energy storage market.However,the sluggish diffusion kinetics of bivalent Mg^(2+)in the host material,related to the strong Coulomb effect between Mg^(2+)and host anion lattices,hinders their further development toward practical applications.Defect engineering,regarded as an effective strategy to break through the slow migration puzzle,has been validated in various cathode materials for RMBs.In this review,we first thoroughly understand the intrinsic mechanism of Mg^(2+)diffusion in cathode materials,from which the key factors affecting ion diffusion are further presented.Then,the positive effects of purposely introduced defects,including vacancy and doping,and the corresponding strategies for introducing various defects are discussed.The applications of defect engineering in cathode materials for RMBs with advanced electrochemical properties are also summarized.Finally,the existing challenges and future perspectives of defect engineering in cathode materials for the overall high-performance RMBs are described.

Voices that matter:The impact of patient-reported outcome measures on clinical decision-making

The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.

Geographical Engineering and Its Role in Promoting Integrated Geography Research

Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orientation,rendering it inseparable from being merely a derivative of geographical science or technology.This paper defines geographical engineering and introduces its development history through the lens of Chinese geographical engineering praxises.Furthermore,it is highlighted the logical and functional consistency between the theory of human-earth system and the praxis of geographical engineering.Six modern cases of geographical engineering projects are presented in detail to demonstrate the points and characteristics of different types of modern geographical engineering.Geographical engineering serves as an engine for promoting integrated geography research,and in response to the challenge posed by fragmented geographies,this paper advocates for an urgent revitalization of geographical engineering.The feasibility of revitalizing geographical engineering is guaranteed because it aligns with China’s national strategies.

Teaching Reform of Environmental Engineering Microbiology Based on OBE Concept in the Context of New Engineering Disciplines

In response to meeting the needs of cultivating applied talents in the construction of new engineering disciplines,based on the concept of Outcome-Based Education(OBE),this study analyzes the problems existing in the teaching of the course Environmental Engineering Microbiology,and put forward some corresponding curriculum reform schemes.According to the target points of professional graduation requirements,the scheme proposes revising the syllabus of Environmental Engineering Microbiology,clarifying the curriculum objectives,updating the teaching content,and reforming the teaching methods.Through these measures,it is intended to achieve the unity of teachers way of"teaching"and students way of"learning",construct a new teaching mode,fully stimulate students subjective initiative,and enhance students innovative consciousness and practical ability.Besides,in this study,a"whole process-diversification"evaluation system is established to comprehensively evaluate students performance in theoretical knowledge learning and practical application,comprehensively evaluate students learning situation,and analyze the teaching effect in real time,so as to achieve continuous improvement,and ultimately achieve the goal of improving classroom quality.

Characterization and correlation of engineering properties with microstructure in peanuts:A microscopic to macroscopic analysis

Peanut varieties are diverse globally,with their characters and nutrition determining the product quality.However,the comparative analysis and statistical analysis of key quality indicators for peanut kernels across the world remains relatively limited,impeding the comprehensive evaluation of peanut quality and hindering the industry development on a global scale.This study aimed to compare and analyze the apparent morphology,microstructure,single-cell structure,engineering and mechanical properties,as well as major nutrient contents of peanut kernels from 10 different cultivars representing major peanut-producing countries.The surface and cross-section microstructure of the peanut kernels exhibited a dense“blocky”appearance with a distinct cellular structure.The lipid droplets were predominantly spherical with a regular distribution within the cells.The single-cell structure of the kernels from these 10 peanut cultivars demonstrated varying morphologies and dimensions,which exhibited correlations with their mechanical and engineering properties.Furthermore,the mass loss versus temperature profiles of the peanut kernels revealed five distinct stages,corresponding to moisture loss,volatile loss,protein denaturation,and the degradation of various biomacromolecules.Variations were also observed in the lipid,protein,and sucrose contents,texture,bulk density,true density,porosity,geometric mean diameter,and sphericity among the diferent peanut varieties.This study establishes relationships and correlations among microstructure,engineering properties,and nutritional composition of commonly grown peanut varieties in major peanut-processing countries.The findings provide valuable insights into peanut quality evaluation,empowering the peanut industry to enhance their processing and product development efforts.

Kinked Rebar and Engineering Structures Applying Kinked Materials:State-ofthe-Art Review

Kinked rebar is a special type of steel material,which is installed in beam column nodes and frame beams.It effectively enhances the blast resilience,seismic collapse resistance,and progressive collapse resistance of reinforced concrete(RC)structures without imposing substantial cost burdens,thereby emerging as a focal point of recent research endeavors.On the basis of explaining the working principle of kinked rebars,this paper reviews the research status of kinked rebars at home and abroad from three core domains:the tensile mechanical properties of kinked rebars,beam column nodes with kinked rebars,and concrete frame structures with kinked rebars.The analysis underscores that the straightening process of kinked rebars does not compromise their ultimate strength but significantly bolsters structural ductility and enhances energy dissipation capabilities.In beam-column joints,the incorporation of kinked rebars facilitates the seamless transfer of plastic hinges,adhering to the design principle of“strong columns and weak beams.”In addition,kinked rebars can greatly improve the resistance of the beam;The seismic resistance,internal explosion resistance,and progressive collapse resistance of reinforced concrete frame structures with kinked rebar have significantly improved.Beyond its primary application,the principle of kinked rebar was extended to other applications of kinked materials such as corrugated steel plates and origami structures,and the stress characteristics of related components and structures were studied.Intriguingly,this paper also proposes the application of kinked rebars in bridge engineering,aiming to address the challenges of localized damage concentration and excessive residual displacement in RC bridge piers.The introduction of kinked rebars in piers is envisioned to mitigate these issues,with the paper outlining its advantages and feasibility,thereby offering valuable insights for future research on kinked reinforcement and seismic design strategies for bridges.

Intervention decision-making in MAV/UAV cooperative engagement based on human factors engineering

Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle（MAV/UAV） cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human factors engineering（HFE）.Firstly, based on the brief review of research status of HFE, it gives structural description to emergency in the process of cooperative engagement and analyzes intervention of commanders. After that,constraint conditions of intervention decision-making of commanders based on HFE（IDMCBHFE） are given, and the mathematical model, which takes the overall efficiency value of handling emergencies as the objective function, is established. Then, through combining K-best and variable neighborhood search（VNS） algorithm, a K-best optimization variable neighborhood search mixed algorithm（KBOVNSMA） is designed to solve the model. Finally,through three groups of simulation experiments, effectiveness and superiority of the proposed algorithm are verified.

Multi-factors decision-making entropy method and its application in engineering management

In order to meet the strict requirements for information in engineering management, the positive interval （0, 1 ] in Shannon information entropy is extended to the real number interval [ - 1, 1 ]. The information theory and the decision theory are combined effectively, and the deficiencies that the traditional Bayes decision-making methods only consider a single factor are made up for. The multi-factors engineering decision-making methods are proposed, and some critical problems are solved in the practical engineering management decision-making process.

Forecasting and Decision-Making of Systematic Theories for Engineering Geology in Environmental Geoscience

The paper discusses the problems of engineering geology in environmental geoscience from several aspects. For natural sciences and social sciences, it deduces essential theory from logistic cycle model, logic mapping and Verhulst model. It had been discovered that these aspects are equal. However, these were the studies of normal effects. We must establish mathematical model to check from contrary course for gray forecasting and decision-making and answer several questions satisfactorily.

Multi-criteria decision-making selection model with application to chemical engineering management decisions

Chemical industry project management involves complex decision making situations that require discerning abilities and methods to make sound decisions. Chemical engineers as project managers are faced with decision environments and problems in chemical industry projects that are complex. Multiple-criteria decision making （MCDM） approaches are major parts of decision theory and analysis. This paper presents all of MCDM approaches for use in chemical engineering management decisions. In this work, case study is Research and Development （R＆D） project selection in chemical industry. The ability to make sound decisions is very important to success of R＆D projects. It is hoped that this work will provide a ready reference on MCDM and this will encourage the application of the MCDM in chemical engineering management.

Compositional and Hollow Engineering of Silicon Carbide/Carbon Microspheres as High-Performance Microwave Absorbing Materials with Good Environmental Tolerance

Microwave absorbing materials(MAMs)characterized by high absorption efficiency and good environmental tolerance are highly desirable in practical applications.Both silicon carbide and carbon are considered as stable MAMs under some rigorous conditions,while their composites still fail to produce satisfactory microwave absorption performance regardless of the improvements as compared with the individuals.Herein,we have successfully implemented compositional and structural engineering to fabricate hollow Si C/C microspheres with controllable composition.The simultaneous modulation on dielectric properties and impedance matching can be easily achieved as the change in the composition of these composites.The formation of hollow structure not only favors lightweight feature,but also generates considerable contribution to microwave attenuation capacity.With the synergistic effect of composition and structure,the optimized SiC/C composite exhibits excellent performance,whose the strongest reflection loss intensity and broadest effective absorption reach-60.8 dB and 5.1 GHz,respectively,and its microwave absorption properties are actually superior to those of most SiC/C composites in previous studies.In addition,the stability tests of microwave absorption capacity after exposure to harsh conditions and Radar Cross Section simulation data demonstrate that hollow SiC/C microspheres from compositional and structural optimization have a bright prospect in practical applications.

Biomimetic natural biomaterials for tissue engineering and regenerative medicine:new biosynthesis methods,recent advances,and emerging applications

Biomimetic materials have emerged as attractive and competitive alternatives for tissue engineering(TE)and regenerative medicine.In contrast to conventional biomaterials or synthetic materials,biomimetic scaffolds based on natural biomaterial can offer cells a broad spectrum of biochemical and biophysical cues that mimic the in vivo extracellular matrix(ECM).Additionally,such materials have mechanical adaptability,micro-structure interconnectivity,and inherent bioactivity,making them ideal for the design of living implants for specific applications in TE and regenerative medicine.This paper provides an overview for recent progress of biomimetic natural biomaterials(BNBMs),including advances in their preparation,functionality,potential applications and future challenges.We highlight recent advances in the fabrication of BNBMs and outline general strategies for functionalizing and tailoring the BNBMs with various biological and physicochemical characteristics of native ECM.Moreover,we offer an overview of recent key advances in the functionalization and applications of versatile BNBMs for TE applications.Finally,we conclude by offering our perspective on open challenges and future developments in this rapidly-evolving field.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.