Multichain Model Research Articles

Assessing Energy Consumption, Carbon Emissions, and Costs in Biomass-to-Gas Processes: A Life-Cycle Assessment Approach

China has a huge potential for biomass utilization. Converting low-grade biomass into high-quality hydrogen and natural gas is of great significance in promoting the utilization of biomass resources and the achievement of carbon reduction goals. Based on the data of biomass collection, transportation, power generation, hydrogen production and gas production stages in China, this paper constructs a multi-chain hybrid whole-life process evaluation model for “electricity to gas” and comprehensively compares the energy consumption, carbon emission and cost of the two chains of “hydrogen production from biomass power generation” and “methane production from biomass power generation”. We comprehensively compare the energy consumption, carbon emissions and costs of biomass-to-hydrogen and biomass-to-methane technologies. Biomass natural gas is found to have significant advantages in terms of energy consumption, carbon emissions and economics compared to biomass hydrogen production. In order to promote the development of the biomass “electricity to gas” industry in China, this paper proposes that PEM electrolysis tanks can be used for hydrogen production, and the distance from the biomass feedstock collection to the hydrogen production chemical park should be optimized to reduce the whole-life-cycle cost. Biomass natural gas can buy time for the development of China’s hydrogen industry and infrastructure construction.

The effect of outdoor activities on the medical expenditure of older people: multiple chain mediating effects of health benefits

BackgroundWith the global aging population, attention to the health and medical issues of older adults is increasing. By analyzing the relationship between older people's participation in outdoor activities and medical expenditure, this study aims to provide a scientific basis for improving their quality of life and reducing the medical burden.MethodsData on outdoor activity participation, medical expenditures, and relevant variables were collected through questionnaires and databases. A multi-chain mediation effect model was established to analyze the impact of outdoor activities on the medical expenditure of older people, considering mediation effects and heterogeneity.ResultsResults revealed that increased participation in outdoor activities among older adults correlated with lower medical expenditures. Outdoor activities positively influenced their health by improving mental health, cognition, eating habits, and activities of daily living, resulting in reduced medical expenditures. Robustness tests confirmed the consistent effect of outdoor activities on older people's medical expenditure.ConclusionThese findings contribute to understanding the relationship between outdoor activities, health, and medical expenditure in older people, guiding policy formulation and interventions. Encouraging and supporting older adults in outdoor activities can enhance their quality of life and alleviate medical resource strain. The study's conclusions can also inform health promotion measures for other populations and serve as a basis for future research in this area.

Design of Multi-Chain Traceability Model for Pepper Products Based on Traceability Code

In the specific application scenario of pepper product supply chain traceability, with the advancement of pepper product production, the expansion of links, and the increase of nodes, the quantity of data will become more and more enormous. The single-chain model is less efficient for querying if the data are all stored into the same blockchain. In order to improve the efficiency of blockchain data querying, this paper proposes a traceability model with one main chain and multiple side chain structures, which separate the uplinked data from each link and use multi-chain transactions to improve the efficiency of data queries. This model builds an indexing mechanism with a product traceability code, using one main chain and multiple side chains. The main and side chains form a one-to-many mapping relationship, storing the mapping relationship between the traceability code and the transaction address of the side chain traceability information in the main chain. This enables information to travel through the main chain traversal query based on the mapping relationship and then query the direct index out of the side chain, to achieve fast traceability query and improve the efficiency of querying.

Future Air Quality Prediction Using Long Short-Term Memory Based on Hyper Heuristic Multi-Chain Model

Future Air Quality Prediction Using Long Short-Term Memory Based on Hyper Heuristic Multi-Chain Model

Research on Flexible Traceability System of Agaricus bisporus Supply Chain

The supply chain of Agaricus bisporus constitutes a complex, multi-layered production and distribution network, encompassing various stages. Challenges in information transmission and process integration between these stages often lead to reduced query efficiency, subsequently compromising the credibility of traceability results and the flexibility of the system. In traditional traceability systems, data for multiple service recipients may be stored on a single blockchain, resulting in complex data structures and making it challenging for users to conduct effective queries and analyses. To address this issue, this paper proposes a solution: a multi-chain tracing model tailored for stakeholders in the traceability process of Agaricus bisporus. This model establishes public chains, enterprise chains, and supervision chains for consumers, enterprises, and regulatory authorities, respectively, to enhance system storage and query efficiency. Additionally, leveraging the modular design of Hyperledger Fabric, the paper optimizes and upgrades the supply chain of Agaricus bisporus. The proposed multi-chain tracing model, designed for traceability for stakeholders, undergoes rigorous validation. Analysis and application results demonstrate that this approach significantly improves the query efficiency and credibility of traceability information while markedly enhancing system flexibility.

A Quality Traceability System for Fruit and Vegetable Supply Chain Based on Multi-Chain Blockchain

To enhance the efficiency and security of traceability in the fruit and vegetable industry, this paper proposes an optimized model based on multi-chain blockchain technology. Firstly, an analysis is conducted on the supply chain information of the fruit and vegetable industry, where traceability codes and product information from various stages of the supply chain are organized and extracted. Next, a trusted traceability optimization model is established based on blockchain technology. Finally, an information traceability system for the VFSC is implemented using Hyperledger fabric, and an improved Kafka load balancing algorithm is proposed to enhance message transmission efficiency. Simulation results demonstrate that the multi-chain traceability model proposed outperforms traditional single-chain blockchain models in terms of query efficiency when the number of data records exceeds 1000. After 10000 data records are deployed on the blockchain, the efficiency of the multi-chain model is improved by over 90% compared to the traditional single-chain model.

Study on magnetostriction of ferromagnetic particles–superconducting matrix based on multi-chain model

Based on the magnetic dipole theory and the elastic mechanical plane strain method, this paper establishes a multi-chain model of ferromagnetic particle inclusions–superconducting matrix and investigates the effects of the distribution form of ferromagnetic particle inclusions and elastic parameters on the effective magnetostriction of superconductors. A dimensionless parameter is introduced to describe the spatial distribution form of ferromagnetic particles in the matrix, and the calculation is carried out using the elastic mechanical plane strain method. The change of the effective magnetostriction following the elastic parameter is given for three kinds of distribution forms: single-chain, planar–laminar, and spatial three-dimensional multi-chain, respectively. The results show that the distribution of ferromagnetic particle inclusions and the change of elastic parameters have a notable influence on the displacement and magnetostrictive distribution of superconductors.

Research on the Construction of Grain Food Multi-Chain Blockchain Based on Zero-Knowledge Proof.

As the main food source of the world's population, grain quality safety is of great significance to the healthy development of human beings. The grain food supply chain is characterized by its long life cycle, numerous and complex business data, difficulty defining private information, and difficult managing and sharing. In order to strengthen the ability of information application processing and coordination of the grain food supply chain under many risk factors, an information management model suitable for the grain food supply chain is studied based on the blockchain multi-chain technology. First, the information on key links in the grain food supply chain is analyzed to obtain privacy data classifications. Second, a multi-chain network model of the grain food supply chain is constructed, and based on this model, the hierarchical encryption and storage mode of private data as well as the relay cross-chain communication mode, are designed. In addition, a complete consensus process, including CPBFT, ZKP, and KZKP algorithms, is designed for the global information collaborative consensus under the multi-chain architecture. Finally, the model is verified through performance simulation, theory analysis, and prototype system verification in terms of its correctness, security, scalability, and consensus efficiency. The results show that this research model effectively reduces the storage redundancy and deals with problems of data differential sharing in traditional single-chain research, as well as provides a secure data protection mechanism, a credible data interaction mechanism, and an efficient multi-chain collaborative consensus mechanism. By attempting to apply blockchain multi-chain technology to the grain food supply chain, this study provides new research ideas for the trusted protection of data and information collaborative consensus in this field.

Research on carbon flow traceability system for distribution network based on blockchain and power flow calculation

With the proposal of the two-carbon goal, energy conservation and emission reduction will become the focus of China’s energy system in the future for a long time to come. The establishment of a complete and efficient carbon traceability system will play an important role in promoting carbon emission reduction in the power system. Based on blockchain, this paper uses the consensus mechanism, time stamp, decentralization features, smart contract and other functions of blockchain, combined with the power flow calculation and the characteristics related to carbon emission and active power of the generator set, to obtain the corresponding carbon emission intensity of the generator set and carbon flow rate. It realizes the calculation and tracing of carbon emission flow in power distribution network and ensures the reliability of carbon traceability results, high efficiency of information transmission and transparency of traceability process. Firstly, based on the characteristics of the master-slave multi-chain structure in the consortium chain, In this paper, high-voltage substation nodes are the main chain nodes, and carbon flow tracing and calculation are carried out for the associated low-voltage substations, and the information of high-voltage or low-voltage substation nodes is guaranteed to be tamper-free through the hash anchoring method. The master-slave multi-chain model adopted in this paper is that the main chain adopts EA-DPoS (Evaluation and Agent-DPoS) algorithm, the slave chain adopts improved PBFT algorithm, and the comprehensive evaluation and reward and punishment mechanism are introduced to complete the consensus. Secondly, considering the security requirements of the power system data and the fact that some nodes of the distribution network do not have powerful computing resources comparable to those of the power grid company or major nodes, this paper encrypts and decrypts relevant data in the main chain node by combining the smart contract of blockchain. Meanwhile, cloud service providers with computing resources are responsible for generator power distribution combined with power flow calculation and carbon emission intensity calculation of the generator set. The power grid company adopts the cloud computing framework based on the double check mechanism to calculate the carbon flow rate while verifying the correct calculation results of the cloud service provider, and finally realizes the safe and accurate tracing of the carbon flow of the distribution network.

How do information and communication technology and urbanization affect carbon emissions? Evidence from 42 selected "Belt and Road Initiative" countries.

Reducing carbon emissions is key to achieving the 13th UN sustainable development goals. With the acceleration of informatization and urbanization in the "Belt and Road Initiative" (BRI) countries, it is necessary to explore the impact of ICT and urbanization on carbon emissions in the BRI countries. This paper uses the Driscoll-Kraay panel regression method, multi-chain mediation effect model, and panel moment quantile regression method to study the influence channel and heterogeneous impact of ICT, urbanization, and their interaction on carbon emissions in 42 selected BRI countries. The main empirical results reveal the inhibition of ICT and the promotion of urbanization on carbon emissions. Moreover, the integrated development of ICT and urbanization contributes to reducing carbon emissions. Industrial structure upgrading and energy intensity are found to be the channels through which ICT, urbanization, and their interactions affect carbon emissions. In addition, the impact of ICT, urbanization, and their interaction on carbon emissions varies with different measurement indicators and quantiles. Therefore, it is suggested that BRI countries should formulate appropriate ICT development policies according to their conditions, strengthen ICT application, and especially promote the integrated development of ICT and urbanization, to achieve sustainable urban development.

Optimal portfolio diversification with a multi-chain regime-switching spillover GARCH model

A multi-chain regime-switching spillover GARCH (MCRSSG) model is proposed for optimal portfolio diversification. MCRSSG specifies the within-regime time-varying correlation via a multi-chain state-dependent spillover factor and quantifies the magnitude of volatility spillovers under different regime combinations. MCRSSG is applied to investigate the diversification benefit of precious metals, crude oil, and financial securities for the Korean stock market at a sector level. The empirical results reveal that the Dow Jones Islamic market US total return index provides the best diversification benefit and MCRSSG exhibits superior effectiveness for risk-adjusted return and reward-to-semivariance ratio.

A Cross-Chain Trusted Reputation Scheme for a Shared Charging Platform Based on Blockchain

With the development of electric vehicles, the shortage of charging piles (CPs) has gradually been exposed. In response to this situation, CP operators have taken private CPs into the shared charging system. Due to the lack of maintenance personnel for private CPs that join shared charging, users often face the problems of damaged CPs and poor service attitudes of CP owners. Reputation solutions based on third-party platforms face a problem of single-point failures and reputation solutions based on blockchain face problems of storage and query efficiency. To improve storage and query efficiency, this article proposes a multichain charging model that stores different types of information on different blockchains. However, it faces the problem of unreliable information called across chains, when calculating reputation across chains. Therefore, this article proposes a cross-chain trusted smart contract ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$C_{2}T$ </tex-math></inline-formula> smart contract) to ensure the authenticity, real-time, and interchain write mutual exclusion of cross-chain information, making reputation calculation in the multichain charging model more convenient and more accurate. Especially, we propose a data mutual trust mechanism based on Merkle proof to ensure the authenticity of cross-chain information and prevent forged information from participating in calculating reputation. Furthermore, we present a data structure composed of multiple counting Bloom filters (MCBFs) to verify the real time of information and filter out non-real-time information, thereby ensuring the real time of the calculated reputation. In addition, we put forward an algorithm to guarantee the interchain write mutual exclusion by hash mutexes, making the reputation calculation process more accurate and complete. The security analysis and experimental results demonstrate that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$C_{2}T$ </tex-math></inline-formula> smart contract is feasible in practice.

Slip-Spring Hybrid Particle-Field Molecular Dynamics for Coarse-Graining Branched Polymer Melts: Polystyrene Melts as an Example.

The topology of chains significantly modifies the dynamical properties of polymer melts. Here, we extend a recently developed efficient simulation method, namely the slip-spring hybrid particle-field (SS-hPF) model, to study the structural and dynamical properties of branched polymer melts over large spatial-temporal scales. In the coarse-grained SS-hPF simulation of polymers, the bonded potentials are derived by iterative Boltzmann inversion from the underlying fine-grained model. The nonbonded potentials are computed from a density functional field instead of pairwise interactions used in standard molecular dynamics simulations, which increases the computational efficiency by a factor of 10-20. The entangled dynamics is lost due to the soft-core nature of density functional field interactions. It is recovered by a multichain slip-spring model that is rigorously parametrized from existing experimental or simulation data. To quantitatively predict the relaxation and diffusion of branched polymers, which are dominated by arm retraction rather than chain reptation, the slip-spring algorithm is augmented to improve the polymer dynamics near the branch point. Multiple dynamical observables, e.g., diffusion coefficients, arm relaxations, and tube survival probabilities, are characterized in an example coarse-grained model of symmetric and asymmetric star-shaped polystyrene melts. Consistent dynamical behaviors are identified and compared with theoretical predictions. With a single rescaling factor, the prediction of diffusion coefficients agrees well with the available experimental measurements. In this work, an efficient approach is provided to build chemistry-specific coarse-grained models for predicting the dynamics of branched polymers.

Beauty of Block Chain Technology in Supply Chain Management

Block chain is an innovative device which plays an important part in Supply chain management (SCM). Most importantly, it solves the discernibility issue in the supply chain management. We in the first place introduce a general block chain-based item detectability structure. This system depends on a cross-fringe web based business flexible chain setting. It is a model which combines multi-chain framework model, information board model and square artefact model. A few other techniques and calculations such as data tying down strategy, key dissemination technique, data encryption calculation and hostile to forging technique are additionally used. The structure, models and techniques assessed by applying to a few regular issues. The adequacy, security, execution and administration problems of applying these arrangements are also important and hence addressed in this article.&#x0D; HIGHLIGHTS&#x0D; &#x0D; It resolves the discernibility issue in the supply chain management&#x0D; This system depends on a cross-fringe web based business flexible chain setting&#x0D; It is a combination of multi-chain framework model, information board model and square artefact model&#x0D;

Multi-Chain Collaboration-Based Information Management and Control for the Rice Supply Chain

The issue of food quality and safety is a major concern. Rice is considered one of the three staple foods. Rice quality and safety problems have occurred frequently, which seriously affect human health. The rice supply chain is characterized by complex links, discrete data, and numerous types of hazardous substances. Strengthening the information management and control capabilities of the rice supply chain is an important means to ensure the quality and safety of rice. Based on multi-chain collaboration, we have conducted research on information management and control of the rice supply chain. First, a multi-chain collaborative model of “blockchain + sub-chain” is designed. Based on this model, the following four mechanisms are designed: a trusted chain mechanism, a multi-level sub-chain encryption mechanism, a trusted supervision mechanism, and a hierarchical consensus mechanism. These mechanisms jointly serve the multi-chain collaborative management and control of the rice supply chain information. Secondly, smart contracts and operating procedures are designed, and a comparative analysis of them is executed. Finally, the design and implementation of the prototype system is carried out, and an example is verified and analyzed in a grain enterprise. Results show that this model serves the information supervision of the rice supply chain by studying the multi-chain collaboration. The study solves the real-time data interaction problem between each link of the rice supply chain. The credible management of information and control of the rice supply chain is accomplished. This study applies new information technology to the coordination and resource sharing of the food supply chain and provides ideas for the digital transformation of the food industry.

Atomic-scale interactions between quorum sensing autoinducer molecules and the mucoid P. aeruginosa exopolysaccharide matrix

Mucoid Pseudomonas aeruginosa is a prevalent cystic fibrosis (CF) lung coloniser whose chronicity is associated with the formation of cation cross-linked exopolysaccharide (EPS) matrices, which form a biofilm that acts as a diffusion barrier, sequestering cationic and neutral antimicrobials, and making it extremely resistant to pharmacological challenge. Biofilm chronicity and virulence of the colony is regulated by quorum sensing autoinducers (QSAIs), small signalling metabolites that pass between bacteria, through the biofilm matrix, regulating genetic responses on a population-wide scale. The nature of how these molecules interact with the EPS is poorly understood, despite the fact that they must pass through EPS matrix to reach neighbouring bacteria. Interactions at the atomic-scale between two QSAI molecules, C4-HSL and PQS—both utilised by mucoid P. aeruginosa in the CF lung—and the EPS, have been studied for the first time using a combined molecular dynamics (MD) and density functional theory (DFT) approach. A large-scale, calcium cross-linked, multi-chain EPS molecular model was developed and MD used to sample modes of interaction between QSAI molecules and the EPS that occur at physiological equilibrium. The thermodynamic stability of the QSAI-EPS adducts were calculated using DFT. These simulations provide a thermodynamic rationale for the apparent free movement of C4-HSL, highlight key molecular functionality responsible for EPS binding and, based on its significantly reduced mobility, suggest PQS as a viable target for quorum quenching.

Application of multi layer perceptron neural network Markov Chain model for LULC change detection in the Sub-Himalayan North Bengal

Land use and land cover (LULC) changes may occur due to natural and anthropogenic activities. The present study area is situated in the Himalayan foothill region of north-eastern India and covers around 1507 km2. This area comprises Siliguri Municipal Corporation (SMC) and the surrounding five community development blocks. Geopolitical location of the study area makes it significant as it is exposed to the negative impacts of human and commercial activities across the region. The present study aims to identify the LULC classes in the study area from 1991 to 2021 with their change dynamics and predict the LULC changes in 2050. Apart from these, a perception study is also carried out to identify the major drivers of LULC changes in the study area. After delineating the study area, supervised classification of Landsat satellite images was done applying the maximum likelihood classification (MLC) tool for the year 1991, 2001, 2011 and 2021. Each image was classified into six LULC classes i.e., vegetation, plantation, agricultural land, built up, water bodies and fallow land and the overall accuracy (average) of the classified maps is 88.83%. The result shows that vegetation, agricultural land and fallow land are decreased from 23% to 20%, 35%–28% and 23%–19% respectively and plantation and built up areas are significantly increased from 14% to 24% and 2%–8% respectively. Then the land change modeler (LCM) under multi layer perceptron neural network Markov Chain (MLPNN-MC) model was applied to predict the spatio-temporal LULC changes from 2021 to 2050. The result reveals that in 2050 built up areas will be increased significantly and are expected to cover almost 12% of the total study area and only 24% of agricultural land will be left. The model was validated by Pearson's chi-squared test and found no significant distinguishes between simulated and actual classified maps. For identifying the main drivers of the LULC changes in the study area people's perceptions were taken from 25 focus group discussions (FGD) randomly over the area. The result reveals that physical and economic location, immigration, development of transport network, increasing multi-functional land use, expansion of small trade and enterprises, and cutting of trees for fuel wood and construction purposes are the key drivers of LULC change for this particular region. The change in the land surface in this Sub-Himalayan region is threatened by unplanned urbanization and unorganized land use practices so, crucial measures are needed indeed.

Model Penentuan Jumlah Produksi yang Optimal pada Rantai Pasok dengan Produsen Tunggal dan Multi-Retailer

Determining the optimal size of procurement or production is the key word in determining optimal inventory. An integrated procurement and production size optimization model becomes a model that provides optimal results for all parties involved in the supply chain. This study proposes the development of a single producer and multi retailer supply chain model with the aim of minimizing the total inventory cost (TIC). The company distributes products to each retailer for further sale to consumers by the retailer. The annual demand from retailers is assumed to be different. Model development is carried out to obtain optimal production quantities for producers, optimal delivery quantities and determine the optimal number of retailers. The determination is based on the manufacturer's production cycle time is the same as the inventory cycle time at each retailer is the same. A simple algorithm is used to determine the optimal cycle time which can be followed by determining the optimal production size, optimal number of shipments and optimal number of retailers. At the end of this study, a numerical example of the use of a model that has been built based on case study data of a fertilizer industry is presented as a producer and its partners as retailers. The results of the numerical examples that have been carried out show that the optimal number of retailers is 3 retailers with an optimal production of 742 units, the determination of the optimal number of retailers is obtained from experiments with the lowest TIC value.

A Master-slave Multi-chain Hierarchical Cross-chain Model Based on Credit Voting Consensus

This paper proposes a consensus algorithm based on the credit voting mechanism, which introduces the voting mechanism to decide the ownership of the accounting privilege, avoids the competition of the computation power among nodes, and makes all nodes in the system get the accounting privilege fairly. By assigning credit value to nodes, the influence of equity on the system can be reduced. Meanwhile, quantitative evaluation on the behavior of nodes can better prevent nodes conducting malicious behaviors. Based on PoVT, we propose a master-slave multi-chain layered cross-chain model, and conduct experiments to evaluate the performance. The results show that the efficiency of the system is improved, and the system has a certain defense capability against attack methods such as double spending attack, selfish mining, nothing-at-stake attack.

Why ultrafast charge separation occurs in bulk-heterojunction organic solar cells: a multichain tight binding model study.

Bulk-heterojunction (BHJ) organic solar cells (OSCs) exhibit ultrafast charge separation (UCS) which enables lower geminate charge recombination and high internal quantum efficiency. Unravelling why UCS occurs in BHJ-OSCs is important for the exploration of devices in future, however it is still far from clear. In this work, we build a multichain tight-binding model to study the conditions for realizing UCS. We propose that two conditions are important: (i) the BHJ-OSC has a morphology with donor and acceptor molecules being individually aggregated; (ii) the ratio of the donor/acceptor interfacial coupling to the internal donor/donor and acceptor/acceptor coupling should be smaller than a threshold. In addition, we suggest that increasing the donor/acceptor energetic offset will boost the UCS efficiency. As a fundamental theoretical analysis on the underlying mechanism of UCS, our work provides design rules for optimizing high-performance BHJ OSCs.