Agent Technology Application in Automating the Coordination and Decision-Making in Supply Chain

Coordinating all the activities among all the parties involved in supply chain can be a daunting task. This paper put forth the viewpoint of applying agent technology to automate the coordination and decision-making tasks in a typical home PC industry supply chain. The main features of the proposed approach, which differentiate it from other approaches, are the following:① In the prototype, the coordination agents have both cooperation and competition patterns; ② It uses JADE (Java Agent DEvelopment Framework) as the agent development environment to realize efficient and reusable agent software;③ It produces some innovative models for the business processes and issues faced by parties in the supply chain. A prototype and the overall process flow were also described.

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.

A mixed-coordination electron trapping-enabled high-precision touch-sensitive screen for wearable devices

Touch-sensitive screens are crucial components of wearable devices.Materials such as reduced graphene oxide(rGO),carbon nanotubes(CNTs),and graphene offer promising solutions for flexible touch-sensitive screens.However,when stacked with flexible substrates to form multilayered capacitive touching sensors,these materials often suffer from substrate delamination in response to deformation;this is due to the materials having different Young’s modulus values.Delamination results in failure to offer accurate touch screen recognition.In this work,we demonstrate an induced charge-based mutual capacitive touching sensor capable of high-precision touch sensing.This is enabled by electron trapping and polarization effects related to mixed-coordinated bonding between copper nanoparticles and vertically grown graphene nanosheets.Here,we used an electron cyclotron resonance system to directly fabricate graphene-metal nanofilms(GMNFs)using carbon and copper,which are firmly adhered to flexible substrates.After being subjected to 3000 bending actions,we observed almost no change in touch sensitivity.The screen interaction system,which has a signal-to-noise ratio of 41.16 dB and resolution of 650 dpi,was tested using a handwritten Chinese character recognition trial and achieved an accuracy of 94.82%.Taken together,these results show the promise of touch-sensitive screens that use directly fabricated GMNFs for wearable devices.

Optimizing high-coordination shell of Co-based single-atom catalysts for efficient ORR and zinc-air batteries

Atom-level modulation of the coordination environment for single-atom catalysts(SACs)is considered as an effective strategy for elevating the catalytic performance.For the MNxsite,breaking the symmetrical geometry and charge distribution by introducing relatively weak electronegative atoms into the first/second shell is an efficient way,but it remains challenging for elucidating the underlying mechanism of interaction.Herein,a practical strategy was reported to rationally design single cobalt atoms coordinated with both phosphorus and nitrogen atoms in a hierarchically porous carbon derived from metal-organic frameworks.X-ray absorption spectrum reveals that atomically dispersed Co sites are coordinated with four N atoms in the first shell and varying numbers of P atoms in the second shell(denoted as Co-N/P-C).The prepared catalyst exhibits excellent oxygen reduction reaction(ORR)activity as well as zinc-air battery performance.The introduction of P atoms in the Co-SACs weakens the interaction between Co and N,significantly promoting the adsorption process of ^(*)OOH,resulting in the acceleration of reaction kinetics and reduction of thermodynamic barrier,responsible for the increased intrinsic activity.Our discovery provides insights into an ultimate design of single-atom catalysts with adjustable electrocatalytic activities for efficient electrochemical energy conversion.

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Determination of the best materials for development and designing product using a multi-criteria decision-making

Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

Syntheses and catalytic performances of three coordination polymers with tetracarboxylate ligands

Three zincand cobaltcoordination polymers,namely{[Zn_(2)(μ_(6)-adip)(phen)_(2)]·4H_(2)O}_(n)(1),{[Co_(2)(μ_(6)-adip)(bipy)_(2)]·4H_(2)O}_(n)(2),and[Co_(2)(μ4-adip)(μ-bpa)_(2)]_(n)(3)have been constructed hydrothermally using H4adip(H4adip=5,5′-azanediyldiisophthalic acid),phen(phen=1,10-phenanthroline),bipy(bipy=2,2′-bipyridine),bpa(bpa=bis(4-pyridyl)amine),and zinc and cobalt chlorides at 160℃.The products were isolated as stable crystalline solids and were characterized by IR spectra,elemental analyses,thermogravimetric analyses,and single-crystal X-ray diffrac-tion analyses.Single-crystal X-ray diffraction analyses revealed that three compounds crystallize in the orthorhom-bic system Pnna(1 and 2)or P21212(3)space groups.All compounds exhibit 3D frameworks.The catalytic perfor-mances in the Henry reaction of these compounds were investigated.Compound 3 exhibited an effective catalytic activity in the Henry reaction at 70℃.CCDC:2339391,1;2339392,2;2339393,3.

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done.

Syntheses,crystal structures,and catalytic properties of three zinc(Ⅱ),cobalt(Ⅱ)and nickel(Ⅱ)coordination polymers constructed from 5⁃(4⁃carboxyphenoxy)nicotinic acid

Three zinc(Ⅱ),cobalt(Ⅱ),and nickel(Ⅱ)coordination polymers,namely[Zn(μ^(3-)cpna)(μ-dpea)_(0.5)]_(n)(1),[Co(μ^(3-)cpna)(μ-dpey)_(0.5)]_(n)(2),and[Ni(μ^(3-)cpna)(μ-dpey)_(0.5)(H_(2)O)]_(n)(3),have been constructed hydrothermally using H_(2)cpna(5-(4-carboxyphenoxy)nicotinic acid),dpea(1,2-di(4-pyridyl)ethane),dpey(1,2-di(4-pyridyl)ethylene),and zinc,cobalt,and nickel chlorides at 160℃.The products were isolated as stable crystalline solids and were characterized by IR spectra,elemental analyses,thermogravimetric analyses,and single-crystal X-ray diffraction analyses.Single-crystal X-ray diffraction analyses revealed that three compounds crystallize in the triclinic system,space group P1.Compounds 1-3 show 2D layer structures.The catalytic activities in the Knoevenagel condensation reaction of these compounds were investigated.Compounds 1 and 2 exhibit effective catalytic activities in the Knoevenagel condensa-tion reaction at room temperature.For this reaction,various parameters were optimized,followed by the investiga-tion of the substrate scope.CCDC:2335676,1;2335677,2;2335678,3.

A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

Combination of Nitrogen-Rich Skeleton and Coordination Group:Synthesis of a High-Energy Primary Explosive Based on 1H-Tetrazole-5-Carbohydrazide

The high energy coordination compounds Cu(TZCA)_(2)(ClO_(4))_(2)(ECCs-1) was prepared by 1H-tetrazole-5-carbohydrazide(TZCA) with a high energy skeleton and a strong coordination ability group.At the same time,the reaction activity of the ligand was explored,and the single crystal structure of it and intermediate were obtained.The structures of all substances were characterized by IR and EA.And the structure and composition of ECCs-1 are confirmed by ESP,AC,SEM and ICP-OES.Physical and chemical properties tests show that ECCs-1 has an acceptable thermal stability(T_(d)=177℃) and extremely sensitive mechanical stimulation(IS=1 J,FS=5 N).The comprehensive performance test results show that ECCs-1 has excellent initiation ability.In addition,the decomposition mechanism of ECCs-1 is explored from two aspects of experiment and theoretical calculation.

Transition metal coordination polymers with flexible dicarboxylate ligand:Synthesis,characterization,and photoluminescence property

Under solvothermal conditions,six new coordination polymers(CPs)[Mn(L)(phen)(H_(2)O)]_(n)(1),[Co(L)(phen)(H_(2)O)]_(n)(2),[Cu(L)(phen)(H_(2)O)]_(n)(3),[Zn_(2)(L)_(2)(phen)2(H_(2)O)]_(n)(4),[Zn(L)(phen)]_(n)(5),and[Cd(L)(phen)2]_(n)(6)were synthesized by reactions of dicarboxylate ligand 2,2'-(1,2-phenylenebis(methylene))bis(sulfanediyl)dinobutyric acid(H_(2)L)and 1,10-phenanthroline(phen)with the corresponding metal salts.Complexes 1-6 have been structurally characterized by single-crystal X-ray diffraction analyses,elemental analysis,IR,thermogravimetric analysis,and powder X-ray diffraction.The structures of 1-6 are 1D chains,which are further connected by hydrogen bonding interac-tions to form 3D supramolecular structures.Among them,1 and 2 are isomorphic with L2-of syn-conformation,while L2-shows anti-conformation in 3-6.In addition,the solid-state photoluminescence property of 4-6 was investigated.

Solution for Output Coordination Equations of Several Typical Parallel Six-Dimensional Acceleration Sensing Mechanisms

Aiming at the problem that it is difficult to generate the dynamic decoupling equation of the parallel six-dimensional acceleration sensing mechanism,two typical parallel six-dimensional acceleration sensing mechanisms are taken as examples.By analyzing the scale constraint relationship between the hinge points on the mass block and the hinge points on the base of the sensing mechanism,a new method for establishing the dynamic equation of the sensing mechanism is proposed.Firstly,based on the scale constraint relationship between the hinge points on the mass block and the hinge points on the base of the sensing mechanism,the expression of the branch rod length is obtained.The inherent constraint relationship between the branches is excavated and the branch coordination closed chain of the“12-6”configuration is constructed.The output coordination equation of the sensing mechanism is successfully derived.Secondly,the dynamic equations of“12-4”and“12-6”configurations are constructed by the Newton-Euler method,and the forward decoupling equations of the two configurations are solved by combining the dynamic equations and the output coordination equations.Finally,the virtual prototype experiment is carried out,and the maximum reference errors of the forward decoupling equations of the two configuration sensing mechanisms are 4.23%and 6.53%,respectively.The results show that the proposed method is effective and feasible,and meets the real-time requirements.

UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

Achieving an ion-homogenizing and corrosion-resisting interface through nitro-coordination chemistry for stable zinc metal anodes

Suppression of uncontrollable dendrite growth and water-induced side reactions of Zn metal anodes is crucial for achieving long-lasting cycling stability and facilitating the practical implementations of aqueous Zn-metal batteries.To address these challenges,we report in this study a functional nitro-cellulose interfacial layer(NCIL)on the surface of Zn anodes enlightened by a nitro-coordination chemistry strategy.The NCIL exhibits strong zincophilicity and superior coordination capability with Zn^(2+)due to the highly electronegative and highly nucleophilic nature of the nitro functional group.This characteristic facilitates a rapid Zn-ion desolvation process and homogeneous Zn plating,effectively preventing H_(2) evolution and dendrite formation.Additionally,the negatively charged surface of NCIL acts as a shield,repelling SO_(4)^(2-)anions and inhibiting corrosive reactions on the Zn surface.Remarkably,reversible and stable Zn plating/stripping is achieved for over 5100 h at a current density of 1 mA cm^(-2),which is nearly 30 times longer than that of bare Zn anodes.Furthermore,the Zn/V_(2)O_(5) full cells with the functional interface layer deliver a high-capacity retention of 80.3%for over 10,000 cycles at 5 A g^(-1).This research offers valuable insights for the rational development of advanced protective interface layers in order to achieve ultra-long-lifeZnmetal batteries.

Identification of the highly active Zn-N_(4) sites with pyrrole/pyridine-N synergistic coordination by dz^(2)+s-band center for electrocatalytic H_(2)O_(2) production

Single metal atoms anchored on nitrogen-doped carbon materials(M-N_(4))have been identified as effective active sites for catalyzing the two-electron oxygen reduction reaction(2e-ORR).However,the relationship between the local atomic/electronic environments of the M-N_(4) sites(metal atoms coordinated with different types of N species)and their catalytic activity for 2e-ORR has rarely been elaborated clearly,which imposes significant ambiguity for the rational design of catalysts.Herein,guided by the comprehensive density-functional theory calculations and predictions,a series of Zn-N_(4) single-atom catalysts(SACs)are designed with pyrrole/pyridine-N(N_(Po)/N_(Pd))synergistic coordination and prepared by controlling the pyrolysis temperature(600,700,and 800℃),Among them,the dominated Zn-N_(4) configurations with rationally combined N_(Po)/N_(Pd)coordination show~*OOH adsorption strength close to the optimal value,much superior to those with mono N species.Thus,the as-prepared catalyst exhibits a high H_(2)O_(2) selectivity of over 90%both in neutral and alkaline environments,with a superb H_(2)O_(2) yield of up to 33.63 mol g^(-1)h^(-1)in an alkaline with flow cell.More importantly,a new descriptor,dz^(2)+s band center,has been proposed,which is especially feasible for predicting the activity for metal types with fully occupied s and d orbitals.This work thus presents clear guidance for the rational design of highly active SACs toward ORR and provides a complement to the d-band theory for more accurately predicting the catalytic activity of the materials.

Coupling Coordination Analysis of Cropland Intensification and Agroecosystem Services:Evidence from Loess Plateau in Shaanxi Province,China

One of the greatest challenges in the agroecosystem is to improve cropland intensification while preserving agroecosystem services.While many studies have investigated the effect of cropland intensification on agroecosystem service,the interactive coupling and coordination among these factors remain largely unexplored.In view of this,this study performed a case study of the Loess Plateau in Shaanxi Province,China and constructed comprehensive evaluation models to quantify the cropland intensification and agroecosystem service in this area.Balance analysis and the coupling coordination degree model were used to evaluate the interactive relationship between cropland intensification and agroecosystem service,and statistical analysis and spatial autocorrelation were used to analyze the spatial characteristics and potential mechanism of the coupling coordination.Results show that both the cropland intensification and agroecosystem service in the study area were relatively low yet gradually increased from 2000 to 2020.Agroecosystem service lag was identified as the dominant unbalanced development type.Improving the supply capacity of agroecosystem services plays a key role in the balanced development of cropland in the Loess Plateau.The coupling coordination degree between cropland intensification and agroecosystem service ranges from basic coordination to serious incoordination.Therefore,cropland intensification practices in the area should be optimized to enhance this coordination degree.An upward trend was also observed in the coupling coordination degree from2000 to 2020.The withdrawal of marginal cropland in the Grain for Green program is one of the most important reasons for this trend,especially for the northern region.Around 83.6%of the high-high clusters are concentrated in the southern region of the Loess Plateau,whereas 70.5%of the low-low clusters are distributed in the northern region.These clustering characteristics are mainly attributed to the environmental suitability of these areas for agriculture and their degree of economic development.