Mathematical Modeling of Possibility Markov Chains by Possibility Theory

Statistical regression models are input-oriented estimation models that account for observation errors. On the other hand, an output-oriented possibility regression model that accounts for system fluctuations is proposed. Furthermore, the possibility Markov chain is proposed, which has a disidentifiable state (posterior) and a nondiscriminable state (prior). In this paper, we first take up the entity efficiency evaluation problem as a case study of the posterior non-discriminable production possibility region and mention Fuzzy DEA with fuzzy constraints. Next, the case study of the ex-ante non-discriminable event setting is discussed. Finally, we introduce the measure of the fuzzy number and the equality relation and attempt to model the possibility Markov chain mathematically. Furthermore, we show that under ergodic conditions, the direct sum state can be decomposed and reintegrated using fuzzy OR logic. We had already constructed the Possibility Markov process based on the indifferent state of this world. In this paper, we try to extend it to the indifferent event in another world. It should be noted that we can obtain the possibility transfer matrix by full use of possibility theory.

Durable poly(binaphthyl-co-p-terphenyl piperidinium)-based anion exchange membranes with dual side chains

Building well-developed ion-conductive highways is highly desirable for anion exchange membranes(AEMs).Grafting side chain is a highly effective approach for constructing a well-defined phaseseparated morphological structure and forming unblocked ion pathways in AEMs for fast ion transport.Fluorination of side chains can further enhance phase separation due to the superhydrophobic nature of fluorine groups.However,their electronic effect on the alkaline stability of side chains and membranes is rarely reported.Here,fluorine-containing and fluorine-free side chains are introduced into the polyaromatic backbone in proper configuration to investigate the impact of the fluorine terminal group on the stability of the side chains and membrane properties.The poly(binaphthyl-co-p-terphenyl piperidinium)AEM(QBNp TP)has the highest molecular weight and most dimensional stability due to its favorable backbone arrangement among ortho-and meta-terphenyl based AEMs.Importantly,by introducing both a fluorinated piperidinium side chain and a hexane chain into the p-terphenyl-based backbone,the prepared AEM(QBNp TP-QFC)presents an enhanced conductivity(150.6 m S cm^(-1))and a constrained swelling at 80℃.The electronic effect of fluorinated side chains is contemplated by experiments and simulations.The results demonstrate that the presence of strong electro-withdrawing fluorine groups weakens the electronic cloud of adjacent C atoms,increasing OH^(-)attack on the C atom and improving the stability of piperidinium cations.Hence QBNp TP-QFC possesses a robust alkaline stability at 80℃(95.3%conductivity retention after testing in 2 M Na OH for 2160 h).An excellent peak power density of 1.44 W cm^(-2)and a remarkable durability at 80℃(4.5%voltage loss after 100 h)can be observed.

A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Aligned Ion Conduction Pathway of Polyrotaxane‑Based Electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety problems.Our study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves conductivity.mPR-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain dispersion.Integrating this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 cycles.In situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen reactions.Ex situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability tests.The present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

Establishment of Regional Green Innovation Value Chains:A Case Study on Tackling the Impeded Diffusion of Green Products

The green innovation value chain is a key step in transforming green,innovative scientific,and technological achievements into productive forces.The establishment of green innovation value chains based on value distribution rather than technical conditions can effectively overcome the common bottleneck faced by different nations during their green innovation endeavors,namely,the substitution of conventional products with green alternatives.This study investigates the impeded diffusion of green products and their underlying causes,analyzes the internal structure and mechanism of the green innovation value chain,and explores the establishment of regional green innovation value chains and the models available for value chain upgrading.

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

Asia-Pacific Regional Economic Cooperation Under the Reshaping of Global Production and Supply Chains

As part of the important trends of the current development of the world economy,the reshaping of global industry and supply chains interacts with the intensified changes unprecedented in the past century in an increasingly close manner.“Benefit-sharing and risk-sharing”,the characteristics of global industry and supply chains,have a profound influence on the distribution of benefits among countries and the effectiveness of global economic governance.

Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

The evolution analysis of agricultural global value chains

With the Uruguay Round bringing agricultural trade into multilateral regulation,the major countries have actively participated in agricultural global value chains(AGVC)and occupied an important position according to their comparative advantages.Utilizing bilateral agricultural trade data of 66 countries based on the OECD Inter-Country-Input-Output Tables(OECD ICIO)from 2010 to 2018,this study applies social network analysis indicators to measure each country’s eigenvector centrality within AGVC and to examine the current global agricultural trade patterns,with particular attention to the changes in the status of world powers within AGVC.The main findings are as follows:first,with the multilateral and regional trade liberalization,growing numbers of developing nations,including China and India,are engaging in international agricultural trade,which contributes to its diversification;second,as AGVC develops,the structure of global agricultural trade networks has become more decentralized and balanced.This is evidenced by the emergence of additional central nodes,and large nations like the United States,which formerly held the most central position as indicated by a drop in its centrality,are becoming less dominant.

Connected Advantage Interlinked supply chains are good for both China and the rest of the world

As both a beneficiary of global supply chain integration and a contributor to the creation of a new supply chain ecosystem,China is of immense importance to the growth of international supply chains.For example,it’s manufacturing industry is indispensable across every stage of the global supply chain from raw material to intermediate goods production and the assembly of finished products.And with a large consumer base,China has been the place where global goods and services are consumed.

Return to Reality:Speculative Design of Interaction Ritual Chains and Exploration of Alone Together

“Alone together”is an ever-changing“wicked problem.”In this research and practice,the author tries to combine experience design,referring to the theory of“interaction ritual chain theory,”and creatively add interactive experience to discursive works,so that the audience can think between the real and the virtual.

An Evaluation of the Critical Success Factors in Sustainable Food Supply Chains in Developing Countries

Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.

Ultralong nitrogen/sulfur Co-doped carbon nano-hollowsphere chains with encapsulated cobalt nanoparticles for highly efficient oxygen electrocatalysis

The development of simple and effective strategies to prepare electrocatalysts,which possess unique and stable structures comprised of metal/nonmetallic atoms for oxygen reduction reaction(ORR)and oxygen evolution reaction(OER),is currently an urgent issue.Herein,an efficient bifunctional electrocatalyst featured by ultralong N,S-doped carbon nano-hollow-sphere chains about 1300 nm with encapsulated Co nanoparticles(Co-CNHSCs)is developed.The multifunctional catalytic properties of Co together with the heteroatom-induced charge redistribution(i.e.,modulating the electronic structure of the active site)result in superior catalytic activities toward OER and ORR in alkaline media.The optimized catalyst Co-CNHSC-3 displays an outstanding electrocatalytic ability for ORR and OER,a high specific capacity of 1023.6 mAh gZn^(-1),and excellent reversibility after 80 h at 10mA cm^(-2)in a Zn-air battery system.This work presents a new strategy for the design and synthesis of efficient multifunctional carbon-based catalysts for energy storage and conversion devices.

Dynamics of lump chains for the BKP equation describing propagation of nonlinear waves

A large member of lump chain solutions of the(2+1)-dimensional Bogoyavlenskii-Kadomtsev-Petviashvili(BKP)equation are constructed by means of theτ-function in the form of Grammian.The lump chains are formed by periodic arrangement of individual lumps and travel with distinct group and velocities.An analytical method related dominant regions of polygon is developed to analyze the interaction dynamics of the multiple lump chains.The degenerate structures of parallel,superimposed,and molecular lump chains are presented.The interaction solutions between lump chains and kink-solitons are investigated,where the kink-solitons lie on the boundaries of dominant region determined by the constant term in theτ-function.Furthermore,the hybrid solutions consisting of lump chains and individual lumps controlled by the parameter with high rank and depth are investigated.The analytical method presented in this paper can be further extended to other integrable systems to explore complex wave structures.

An Algorithm for the Inverse Problem of Matrix Processing: DNA Chains, Their Distance Matrices and Reconstructing

We continue to consider one of the cybernetic methods in biology related to the study of DNA chains. Exactly, we are considering the problem of reconstructing the distance matrix for DNA chains. Such a matrix is formed on the basis of any of the possible algorithms for determining the distances between DNA chains, as well as any specific object of study. At the same time, for example, the practical programming results show that on an average modern computer, it takes about a day to build such a 30 × 30 matrix for mnDNAs using the Needleman-Wunsch algorithm;therefore, for such a 300 × 300 matrix, about 3 months of continuous computer operation is expected. Thus, even for a relatively small number of species, calculating the distance matrix on conventional computers is hardly feasible and the supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains, then we publish algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. Previously, we used the method of branches and boundaries, but in this paper we propose to use another new algorithm for restoring the distance matrix for DNA chains. Our recent work has shown that even greater improvement in the quality of the algorithm can often be achieved without improving the auxiliary heuristics of the branches and boundaries method. Thus, we are improving the algorithms that formulate the greedy function of this method only. .

Secure and Trusted Interoperability Scheme of Heterogeneous Blockchains Platform in IoT Networks

With the rapid development of the Internet of Things(IoT),there is an increasing need for interac-tion between different networks.In order to improve the level of interconnection,especially the interoper-ability of users/devices between different nodes is very important.In the IoT heterogeneous blockchain sce-nario,how to ensure the legitimacy of the chain and how to confirm the identity of cross-chain informa-tion users/devices become the key issues to be solved for blockchain interoperability.In this paper,we pro-pose a secure and trusted interoperability mechanism for IoT based on heterogeneous chains to improve the security of blockchain interoperability.In this mecha-nism,a primary sidechain architecture supporting au-thentication at both ends of the heterogeneous chain is designed.In addition,a distributed gateway archi-tecture is proposed for cross-chain authentication and protocol conversion.The security and performance analysis shows that our scheme is feasible and effec-tive in improving the security of cross-chain opera-tions in IoT.

Highly efficient organic solar cells with improved stability enabled by ternary copolymers with antioxidant side chains

The stability of organic solar cells(OSCs)remains a major concern for their ultimate industrialization due to the photo,oxygen,and water susceptibility of organic photoactive materials.Usually,antioxidant additives are blended as radical scavengers into the active layer.However,it will induce the intrinsic morphology instability and adversely affect the efficiency and long-term stability.Herein,the antioxidant dibutylhydroxytoluene(BHT)group has been covalently linked onto the side chain of benzothiadiazole(BT)unit,and a series of ternary copolymers D18-Cl-BTBHTx(x=0,0.05,0.1,0.2)with varied ratio of BHT-containing side chains have been synthesized.It was found that the introduction of BHT side chains would have a negligible effect on the photophysical properties and electronic levels,and the D18-Cl-BTBHT0.05:Y6-based OSC achieved the highest power conversion efficiency(PCE)of 17.6%,which is higher than those based active layer blended with BHT additives.More importantly,the unencapsulated device based on D18-Cl-BTBHTx(x=0.05,0.1,0.2)retained approximately 50%of the initial PCE over 30 hours operation under ambient conditions,significantly outperforming the control device based on D18-Cl(90%degradation in PCE after 30 h).This work provides a new structural design strategy of copolymers for OSCs with simultaneously improved efficiency and stability.

Floquet dynamical quantum phase transitions in transverse XY spin chains under periodic kickings

Floquet dynamical quantum phase transitions(DQPTs),which are nonanalytic phenomena recuring periodically in time-periodic driven quantum many-body systems,have been widely studied in recent years.In this article,the Floquet DQPTs in transverse XY spin chains under the modulation ofδ-function periodic kickings are investigated.We analytically solve the system,and by considering the eigenstate as well as the ground state as the initial state of the Floquet dynamics,we study the corresponding multiple Floquet DQPTs emerged in the micromotion with different kicking moments.The rate function of return amplitude,the Pancharatnam geometric phase and the dynamical topological order parameter are calculated,which consistently verify the emergence of Floquet DQPTs in the system.

Detecting and Classifying Darknet Traffic Using Deep Network Chains

The anonymity of the darknet makes it attractive to secure communication lines from censorship.The analysis,monitoring,and categorization of Internet network traffic are essential for detecting darknet traffic that can generate a comprehensive characterization of dangerous users and assist in tracing malicious activities and reducing cybercrime.Furthermore,classifying darknet traffic is essential for real-time applications such as the timely monitoring of malware before attacks occur.This paper presents a two-stage deep network chain for detecting and classifying darknet traffic.In the first stage,anonymized darknet traffic,including VPN and Tor traffic related to hidden services provided by darknets,is detected.In the second stage,traffic related to VPNs and Tor services is classified based on their respective applications.The methodology of this paper was verified on a benchmark dataset containing VPN and Tor traffic.It achieved an accuracy of 96.8%and 94.4%in the detection and classification stages,respectively.Optimization and parameter tuning were performed in both stages to achieve more accurate results,enabling practitioners to combat alleged malicious activities and further detect such activities after outbreaks.In the classification stage,it was observed that the misclassifications were due to the audio and video streaming commonly used in shared real-time protocols.However,in cases where it is desired to distinguish between such activities accurately,the presented deep chain classifier can accommodate additional classifiers.Furthermore,additional classifiers could be added to the chain to categorize specific activities of interest further.

Effect of temperature on heavy ion-induced single event transient on 16-nm FinFET inverter chains

The variations of single event transient(SET)pulse width of high-LET heavy ion irradiation in 16-nm-thick bulk silicon fin field-effect transistor(Fin FET)inverter chains with different driven strengths are measured at different temperatures.Three-dimensional(3D)technology computer-aided design simulations are carried out to study the SET pulse width and saturation current varying with temperature.Experimental and simulation results indicate that the increase in temperature will enhance the parasitic bipolar effect of bulk Fin FET technology,resulting in the increase of SET pulse width.On the other hand,the increase of inverter driven strength will change the layout topology,which has a complex influence on the SET temperature effects of Fin FET inverter chains.The experimental and simulation results show that the device with the strongest driven strength has the least dependence on temperature.