Cross-Domain Bilateral Access Control on Blockchain-Cloud Based Data Trading System

Data trading enables data owners and data requesters to sell and purchase data.With the emergence of blockchain technology,research on blockchain-based data trading systems is receiving a lot of attention.Particularly,to reduce the on-chain storage cost,a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading platform.Moreover,the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data marketplace.In the data marketplace,it is a challenge how to trade the data securely outsourced to the external cloud in a way that restricts access to the data only to authorized users across multiple domains.In this paper,we propose a cross-domain bilateral access control protocol for blockchain-cloud based data trading systems.We consider a system model that consists of domain authorities,data senders,data receivers,a blockchain layer,and a cloud provider.The proposed protocol enables access control and source identification of the outsourced data by leveraging identity-based cryptographic techniques.In the proposed protocol,the outsourced data of the sender is encrypted under the target receiver’s identity,and the cloud provider performs policy-match verification on the authorization tags of the sender and receiver generated by the identity-based signature scheme.Therefore,data trading can be achieved only if the identities of the data sender and receiver simultaneously meet the policies specified by each other.To demonstrate efficiency,we evaluate the performance of the proposed protocol and compare it with existing studies.

Understanding the correlation between energy-state mismatching and open-circuit voltage loss in bulk heterojunction solar cells

Photoinduced intermolecular charge transfer(PICT)determines the voltage loss in bulk heterojunction(BHJ)organic photovoltaics(OPVs),and this voltage loss can be minimized by inducing efficient PICT,which requires energy-state matching between the donor and acceptor at the BHJ interfaces.Thus,both geometrically and energetically accessible delocalized state matching at the hot energy level is crucial for achieving efficient PICT.In this study,an effective method for quantifying the hot state matching of OPVs was developed.The degree of energy-state matching between the electron donor and acceptor at BHJ interfaces was quantified using a mismatching factor(MF)calculated from the modified optical density of the BHJ.Furthermore,the correlation between the open-circuit voltage(Voc)of the OPV device and energy-state matching at the BHJ interface was investigated using the calculated MF.The OPVs with small absolute MF values exhibited high Voc values.This result clearly indicates that the energy-state matching between the donor and acceptor is crucial for achieving a high Voc in OPVs.Because the MF indicates the degree of energy-state matching,which is a critical factor for suppressing energy loss,it can be used to estimate the Voc loss in OPVs.

Transparent and Accountable Training Data Sharing in Decentralized Machine Learning Systems

In Decentralized Machine Learning(DML)systems,system participants contribute their resources to assist others in developing machine learning solutions.Identifying malicious contributions in DML systems is challenging,which has led to the exploration of blockchain technology.Blockchain leverages its transparency and immutability to record the provenance and reliability of training data.However,storing massive datasets or implementing model evaluation processes on smart contracts incurs high computational costs.Additionally,current research on preventing malicious contributions in DML systems primarily focuses on protecting models from being exploited by workers who contribute incorrect or misleading data.However,less attention has been paid to the scenario where malicious requesters intentionally manipulate test data during evaluation to gain an unfair advantage.This paper proposes a transparent and accountable training data sharing method that securely shares data among potentially malicious system participants.First,we introduce a blockchain-based DML system architecture that supports secure training data sharing through the IPFS network.Second,we design a blockchain smart contract to transparently split training datasets into training and test datasets,respectively,without involving system participants.Under the system,transparent and accountable training data sharing can be achieved with attribute-based proxy re-encryption.We demonstrate the security analysis for the system,and conduct experiments on the Ethereum and IPFS platforms to show the feasibility and practicality of the system.

Geomorphological evidence inconvenient for the antecedent rivers of the Arun and Tista across the Himalayan range

The Arun and Tista Rivers,which flow across the Himalayas,are commonly known as antecedent valleys that overcame the rapid uplift of the Higher Himalayan ranges.To clarify whether the idea of antecedent rivers is acceptable,we investigated the geomorphology of the Himalayas between eastern Nepal and Bhutan Himalayas.The southern part of Tibetan Plateau,extending across the Himalayas as tectonically un-deformed glaciated terrain named as'Tibetan Corridor,'does not suggest the regional uplift of the Higher Himalayas.The 8,000-m class mountains of Everest,Makalu,and Kanchenjunga are isolated residual peaks on the glaciated terrain composed of mountain peaks of 4,000–6,000 m high.The Tibetan glaciers commonly beheaded by Himalayan glaciers along the great watershed of the Himalayas suggest the expansion of Himalayan river drainage by glaciation.For the narrow upstream regions of the Arun and Tista Rivers with less precipitation behind the range,it is hard to collect enough water for the power of down-cutting their channels against the uplifting Himalayas.The fission track ages of the Higher Himalayan Crystalline Nappe suggest that the Himalayas attained their present altitude by 11–10 Ma,and the Arun and Tista Rivers formed deep gorges across the Himalayas by headward erosion.

Capsosiphon fulvescens suppresses LPS-stimulated inflammatory responses by suppressing TLR4/NF-κB activation in RAW264.7 murine macrophages

Objective:To evaluate the effects of Capsosiphon fulvescens(C.fulvescens)ethanolic extract on inflammation in lipopolysaccharide(LPS)-induced RAW296.7 macrophages.Methods:The protective effects of C.fulvescens ethanolic extract on LPS-induced inflammation in RAW264.7 macrophages were assessed using biochemical analysis,including enzyme-linked immunosorbent assay,quantitative reverse transcription-polymerase chain reaction,and Western blot analysis.To examine reactive oxygen species(ROS)production,flow cytometry analysis,and immunofluorescence staining were used.Furthermore,the modulatory effect of C.fulvescens ethanolic extract on NF-κB activation was investigated.Results:C.fulvescens ethanolic extract significantly attenuated LPS-induced levels of pro-inflammatory cytokines and notably reduced the secretion and mRNA levels of LPS-mediated matrix metalloproteinases.In addition,C.fulvescens ethanolic extract decreased ROS production and suppressed the TLR4/NF-κB signaling pathway.Conclusions:C.fulvescens ethanolic extract alleviates inflammation as well as oxidative stress by modulating the TLR4/NF-κB signaling in LPS-induced RAW264.7 macrophages.C.fulvescens can be used as a potential therapeutic agent to suppress inflammation and oxidative stress-associated diseases.

Magnesium alloys as alternative anode materials for rechargeable magnesium-ion batteries:Review on the alloying phase and reaction mechanisms

Magnesium-ion batteries(MIBs)are promising candidates for lithium-ion batteries because of their abundance,non-toxicity,and favorable electrochemical properties.This review explores the reaction mechanisms and electrochemical characteristics of Mg-alloy anode materials.While Mg metal anodes provide high volumetric capacity and dendrite-free electrodeposition,their practical application is hindered by challenges such as sluggish Mg^(2+)ion diffusion and electrolyte compatibility.Alloy-type anodes that incorporate groups XIII,XIV,and XV elements have the potential to overcome these limitations.We review various Mg alloys,emphasizing their alloying/dealloying reaction mechanisms,their theoretical capacities,and the practical aspects of MIBs.Furthermore,we discuss the influence of the electrolyte composition on the reversibility and efficiency of these alloy anodes.Emphasis is placed on overcoming current limitations through innovative materials and structural engineering.This review concludes with perspectives on future research directions aimed at enhancing the performance and commercial viability of Mg alloy anodes and contributing to the development of high-capacity,safe,and cost-effective energy storage systems.

Light-Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications

This review provides a comprehensive overview of the progress in light-material interactions(LMIs),focusing on lasers and flash lights for energy conversion and storage applications.We discuss intricate LMI parameters such as light sources,interaction time,and fluence to elucidate their importance in material processing.In addition,this study covers various light-induced photothermal and photochemical processes ranging from melting,crystallization,and ablation to doping and synthesis,which are essential for developing energy materials and devices.Finally,we present extensive energy conversion and storage applications demonstrated by LMI technologies,including energy harvesters,sensors,capacitors,and batteries.Despite the several challenges associated with LMIs,such as complex mechanisms,and high-degrees of freedom,we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations.

Mechanical densification synthesis of single-crystalline Ni-rich cathode for high-energy lithium-ion batteries

The intergranular microcracking in polycrystalline Ni-rich cathode particle is led by anisotropic volume change and stress corrosion along grain boundary,accelerating battery performance decay.Herein,we have suggested a simple but advanced solid-state method that ensures both uniform transition metal distribution and single-crystalline morphology for Ni-rich cathode synthesis without sophisticated coprecipitation.Pelletization-assisted mechanical densification(PAMD)process on solid-state precursor mixture enables the dynamic mass transfer through the increased solid-solid contact area which facilitates the grain growth during sintering process,readily forming micro-sized single-crystalline particle.Furthermore,the improved chemical reactivity by a combination of capillary effect and vacancyassisted diffusion provides homogeneous element distribution within each primary particle.As a result,single-crystalline Ni-rich cathode with PAMD process has eliminated a potential evolution of intergranular cracking,thus achieving superior energy retention capability of 85%over 150 cycles compared to polycrystalline Ni-rich particle even after high-pressure calendering process(corresponding to electrode density of~3.6 g cm^(-3))and high cut-off voltage cycling.This work provides a concrete perspective on developing facile synthetic route of micron-sized single-crystalline Ni-rich cathode materials for high energy density lithium-ion batteries(LIBs).

Blockchain-Based Secure and Fair IoT Data Trading System with Bilateral Authorization

These days,data is regarded as a valuable asset in the era of the data economy,which demands a trading platform for buying and selling data.However,online data trading poses challenges in terms of security and fairness because the seller and the buyer may not fully trust each other.Therefore,in this paper,a blockchain-based secure and fair data trading system is proposed by taking advantage of the smart contract and matchmaking encryption.The proposed system enables bilateral authorization,where data trading between a seller and a buyer is accomplished only if their policies,required by each other,are satisfied simultaneously.This can be achieved by exploiting the security features of the matchmaking encryption.To guarantee non-repudiation and fairness between trading parties,the proposed system leverages a smart contract to ensure that the parties honestly carry out the data trading protocol.However,the smart contract in the proposed system does not include complex cryptographic operations for the efficiency of onchain processes.Instead,these operations are carried out by off-chain parties and their results are used as input for the on-chain procedure.The system also uses an arbitration protocol to resolve disputes based on the trading proof recorded on the blockchain.The performance of the protocol is evaluated in terms of off-chain computation overhead and on-chain gas consumption.The results of the experiments demonstrate that the proposed protocols can enable the implementation of a cost-effective data trading system.

A Blockchain-Assisted Distributed Edge Intelligence for Privacy-Preserving Vehicular Networks

The enormous volume of heterogeneous data fromvarious smart device-based applications has growingly increased a deeply interlaced cyber-physical system.In order to deliver smart cloud services that require low latency with strong computational processing capabilities,the Edge Intelligence System(EIS)idea is now being employed,which takes advantage of Artificial Intelligence(AI)and Edge Computing Technology(ECT).Thus,EIS presents a potential approach to enforcing future Intelligent Transportation Systems(ITS),particularly within a context of a Vehicular Network(VNets).However,the current EIS framework meets some issues and is conceivably vulnerable tomultiple adversarial attacks because the central aggregator server handles the entire systemorchestration.Hence,this paper introduces the concept of distributed edge intelligence,combining the advantages of Federated Learning(FL),Differential Privacy(DP),and blockchain to address the issues raised earlier.By performing decentralized data management and storing transactions in immutable distributed ledger networks,the blockchain-assisted FL method improves user privacy and boosts traffic prediction accuracy.Additionally,DP is utilized in defending the user’s private data from various threats and is given the authority to bolster the confidentiality of data-sharing transactions.Our model has been deployed in two strategies:First,DP-based FL to strengthen user privacy by masking the intermediate data during model uploading.Second,blockchain-based FL to effectively construct secure and decentralized traffic management in vehicular networks.The simulation results demonstrated that our framework yields several benefits for VNets privacy protection by forming a distributed EIS with privacy budget(ε)of 4.03,1.18,and 0.522,achieving model accuracy of 95.8%,93.78%,and 89.31%,respectively.

Applying Job Shop Scheduling to SMEs Manufacturing Platform to Revitalize B2B Relationship

A small and medium enterprises(SMEs)manufacturing platform aims to perform as a significant revenue to SMEs and vendors by providing scheduling and monitoring capabilities.The optimal job shop scheduling is generated by utilizing the scheduling system of the platform,and a minimum production time,i.e.,makespan decides whether the scheduling is optimal or not.This scheduling result allows manufacturers to achieve high productivity,energy savings,and customer satisfaction.Manufacturing in Industry 4.0 requires dynamic,uncertain,complex production environments,and customer-centered services.This paper proposes a novel method for solving the difficulties of the SMEs manufacturing by applying and implementing the job shop scheduling system on a SMEs manufacturing platform.The primary purpose of the SMEs manufacturing platform is to improve the B2B relationship between manufacturing companies and vendors.The platform also serves qualified and satisfactory production opportunities for buyers and producers by meeting two key factors:early delivery date and fulfillment of processing as many orders as possible.The genetic algorithm(GA)-based scheduling method results indicated that the proposed platform enables SME manufacturers to obtain optimized schedules by solving the job shop scheduling problem(JSSP)by comparing with the real-world data from a textile weaving factory in South Korea.The proposed platform will provide producers with an optimal production schedule,introduce new producers to buyers,and eventually foster relationships and mutual economic interests.

Reinforcement Learning-Based Handover Scheme with Neighbor Beacon Frame Transmission

Mobility support to change the connection from one access point(AP)to the next(i.e.,handover)becomes one of the important issues in IEEE 802.11 wireless local area networks(WLANs).During handover,the channel scanning procedure,which aims to collect neighbor AP(NAP)information on all available channels,accounts for most of the delay time.To reduce the channel scanning procedure,a neighbor beacon frame transmission scheme(N-BTS)was proposed for a seamless handover.N-BTS can provide a seamless handover by removing the channel scanning procedure.However,N-BTS always requires operating overhead even if there are few mobile stations(MSs)for the handover.Therefore,this paper proposes a reinforcement learning-based handover scheme with neighbor beacon frame transmission(MAN-BTS)to properly consider the use of N-BTS.The optimization equation is defined to maximize the expected reward tofind the optimal policy and is solved using Q-learning.Simulation results show that the proposed scheme outperforms the comparison schemes in terms of the expected reward.

Enhanced charge separation by interchain hole delocalization in nonfullerene acceptor-based bulk heterojunction materials

Bulk heterojunction(BHJ)composites show improved power conversion efficiencies when optimized in terms of morphology using various film processing methods.A reduced carrier recombination loss in an optimized BHJ was characterized previously.However,the driving force that leads to this reduction was not clearly understood.In this study,we focus on the decreased carrier recombination loss and its driving force in optimized nonfullerene acceptor-based PTB7-Th:IEICO-4F BHJ composites.We demonstrate that the optimized BHJ shows deactivation in the sub-nanosecond nongeminate carrier recombination process.The driving force for this deactivation was determined to be the improved interchain hole delocalization between the polymers.An enhanced interchain hole delocalization was observed using steady-state photoinduced absorption(PIA)spectroscopy.In particular,increased splitting between the polaron PIA bands was noted.Moreover,improved interchain hole delocalization was observed for other state-of-the-art BHJ materials,including D18:Y6 with optimized morphologies.

Genetic algorithm tuned PI controller on PMSM simplified vector control

A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.

Geochemistry,Nd Isotopic Characteristics of Metamorphic Complexes in Northern Hebei:Implications for Crustal Accretion

The middle segment of the northern margin of the North China Craton （NCC） consists mainly of metamorphosed Archean Dantazi Complex, Paleoproterozoic Hongqiyingzi Complex and unmetamorphosed gabbro-anorthosite-meta-alkaline granite, as well as metamorphosed Late Paleozoic mafic to granitoid rocks in the Damiao-Changshaoying area. The -2.49 Ga Dantazi Complex comprises dioritic-trondhjemitic-granodoritic-monzogranitic gneisses metamorphosed in amphibolite to granulite facies. Petrochemical characteristics reveal that most of the rocks belong to a medium- to high-potassium calc-alkaline series, and display Mg^# less than 40, right-declined REE patterns with no to obviously positive Eu anomalies, evidently negative Th, Nb, Ta and Ti anomalies in primitive mantlenormalized spider diagrams, εNd（t）=＋0.65 to -0.03, and depleted mantle model ages TDM=2.78-2.71 Ga. Study in petrogenesis indicates that the rocks were formed from magmatic mixing between mafic magma from the depleted mantle and granitoid magma from partial melting of recycled crustal mafic rocks in a continental margin setting. The 2.44-2.41 Ga Hongqiyingzi Complex is dominated by metamorphic mafic-granodioritic-monzogranitic gneisses, displaying similar petrochemical features to the Dantazi Complex, namely medium to high potassium calc-alkaline series, and the mafic rocks show evident change in LILEs, negative Th, Nb, Ta, Zr anomalies and positive P anomalies. And the other granitiod samples also exhibit negative Th, Nb, Ta, P and Ti anomalies. All rocks in the Hongqiyingzi Complex show right-declined REE patterns without Eu anomaly. The metamorphic mafic rocks with εNd（t） = -1.64 may not be an identical magmatic evolution series with granitoids that have εNd（t） values of ＋3.19 to ＋1.94 and TDM ages of 2.55-2.52 Ga. These granitic rocks originated from hybrid between mafic magma from the depleted mantle and magma from partial melting of juvenile crustal mafic rocks in an island arc setting. All the -311 Ma Late Paleozoic metamorphic mafic rocks and related granitic rocks show a medium-potassium calc-alkaline magmatic evolution series, characterized by high Mg^#, obviously negative Th, Nb, Ta anomalies and positive Sr anomalies, from no to strongly negative Ti anomalies and flat REE patterns with εNd（t） = ＋8.42, implying that the maflc magma was derived from the depleted mantle. However the other granitic rocks are characterized by right-declined REE patterns with no to evidently positive Eu anomalies, significantly low εNd（t） = -13.37 to -14.04, and TDM=1.97-1.96 Ga, revealing that the granitoid magma was derived from hybrid between maflc magma that came from -311 Ma depleted mantle and granitoid magma from Archean to Early Paleoproterozoic ancient crustal recycling. The geochemistry and Nd isotopic characteristics as well as the above geological and geochronological results indicate that the middle segment of the northern margin of the NCC mainly experienced four crustal growth episodes from Archean to Late Paleozoic, which were dominated by three continental marginal arc accretions （-2.49, -2.44 and 311 Ma）, except the 1.76-1.68 Ga episode related to post-collisional extension, revealing that the crustal accretion of this segment was chiefly generated from arc accretion and amalgamation to the NCC continental block.

Improved estimation of rotor position for sensorless control of a PMSM based on a sliding mode observer

This work proposes a new strategy to improve the rotor position estimation of a permanent magnet synchronous motor(PMSM) over wide speed range. Rotor position estimation of a PMSM is performed by using sliding mode observer(SMO). An adaptive observer gain was designed based on Lyapunov function and applied to solve the chattering problem caused by the discontinuous function of the SMO in the wide speed range. The cascade low-pass filter(LPF) with variable cut-off frequency was proposed to reduce the chattering problem and to attenuate the filtering capability of the SMO. In addition, the phase shift caused by the filter was counterbalanced by applying the variable phase delay compensation for the whole speed area. High accuracy estimation result of the rotor position was obtained in the experiment by applying the proposed estimation strategy.

Magnetic force improvement and parameter optimization for magnetic abrasive polishing of AZ31 magnesium alloy

The magnetic force acting on workpiece to be machined plays a significantly important role in magnetic abrasive polishing process.But in a case of polishing nonferrous materials,the strength of magnetic force is very low and it leads lower polishing efficiency.The magnesium alloy that has superior mechanical properties for industrial application such as a lightweight and high specific strength is one of the most famous nonferrous materials.An improving strategy of the magnetic force for the AZ31 magnesium alloy installed with a permanent magnet was proposed and experimental verification was carried out.For the proposed strategy,the effect of process parameters on the surface roughness of the AZ31 magnesium alloy was evaluated by a design of experimental method.

区域断裂对韩国东南部地区现今应力状态的影响

利用朝鲜半岛东南部地区浅层地应力数据,给出区域现今应力状态的分布特征及其与断层分布的关系。地应力数据表明,区域最大主压应力呈ENE-WSW到NE-SW向,这与地震震源机制解及欧亚板块东部构造应力方向的一阶模式一致。或许是受到断层的影响,现今应力张量在大小和方向上表现出不均匀性。区域水平主应力变化较为一致,而垂向则变化较大。应力场的大小受区域断层多少的影响,断层越多应力越小,这表明断层应力释放或许是造成低应力的主要原因之一。为了验证这种假设的正确性,我们对第四纪活动断层与现今应力场的关系进行分析。在现今应力状态下,断层剪应力与正应力比值较高,这与区域大部分断层以走滑为主是一致的,这意味着断层的活动可以维持当前的应力场。