Traceability Information Research Articles

Multilevel and Flexible Physical Unclonable Functions for High-End Leather Products or Packaging.

Counterfeit and substandard high-end leather products have inflicted substantial economic damage worldwide and have tarnished the reputation of the leather industry as a whole. Due to the limited security level, current anti-counterfeiting measures are often vulnerable to attacks. Physically unclonable function (PUF) is regarded as the pinnacle of protection against counterfeiting. Leather, with a distinctive micro-nano porous structure and random creasing patterns, serves as an ideal substrate for optical PUF. Here, a flexible and durable leather-based optical PUF device is introduced that incorporates leather and fluorescent perovskite quantum dots. The fluorescence intensity distributed along the texture of leather offers parametric support for challenge-response pairs. Combined with a self-defined fluorescence pattern, the hierarchical authentication of optical PUF is realized. In conclusion, this innovation offers a desired opportunity for achieving high-security anti-counterfeiting and information traceability.

Investment Decision and Coordination of Fresh Supply Chain Blockchain Technology Considering Consumer Preference

In this paper, we study the decision-making and coordination problem of a two-tier fresh food supply chain consisting of a supplier and a retailer. Considering the influencing factors of consumers’ information preference, freshness, and misrepresentation, we construct a centralized decision-making model and a decentralized decision-making Stackelberg game model. We also analyze the changes in the equilibrium solution of the supply chain before and after the input of blockchain technology, identify the conditions for the investment in blockchain technology, and design a “cost-sharing + benefit-sharing” combination contract for the coordination of the blockchain. The results are as follows: Firstly, under decentralized decision-making, if the fresh supplier misreports the freshness of the product, it will mislead the retailer to increase the order quantity, and its own profit will rise. Therefore, the fresh supplier has the motivation to misreport freshness. However, the backlog of fresh products will eventually damage the retailer‘s profit, and the overall profit of the supply chain will also be damaged. Therefore, the increase in the profit of the fresh supplier is at the expense of the overall interests and stability of the supply chain. Second, when the investment cost of blockchain technology is within a certain threshold, it is feasible to invest in blockchain technology. Consumers’ preference for traceable fresh products will encourage the fresh supply chain to improve the level of information traceability and increase investment in blockchain technology. Finally, there are double marginal effects in the fresh supply chain under decentralized decision-making. The combined contract of “cost-sharing + revenue-sharing” can coordinate the overall revenue of the supply chain to the level of centralized decision-making. When the contract parameters meet certain conditions, Pareto improvement in revenue can be achieved for all parties involved in the fresh supply chain. The willingness of retailers to invest in blockchain technology will change with the change in contract parameters. When the proportion of retailers’ costs and the proportion of shared income are higher, the level of retailers’ investment in blockchain technology will decrease. Therefore, the interests of supply chain members need to be balanced in the process of contract coordination.

Blockchain’s role in operation strategy of power battery closed-loop supply chain

With the rapid development of the electric vehicle industry, the issue of recycling retired power batteries is becoming increasingly prominent. Considering the adoption of blockchain technology to enhance information traceability for retired power batteries, we construct three closed-loop supply chain decision-making models: a supply chain that does not adopt blockchain technology, a manufacturing enterprise that independently bears the input cost of blockchain technology, and a scenario which both manufacturing and selling enterprises jointly bear the blockchain technology input costs. Through the comparative analysis of the equilibrium solutions of these models, including the profits of each supply chain member, consumer surplus, environmental impact, and social welfare, it is concluded that the level of information traceability increases with the increase of the blockchain technology input cost-sharing ratio λ by the selling enterprise. However, there is a threshold for λ and λ cannot be infinitely increased. The profits of both manufacturing and selling enterprises increase with the adoption of blockchain technology, yet the ladder-utilizing enterprise achieves the highest profits when not adopting blockchain technology. Furthermore, the adoption of blockchain technology can increase consumer surplus and social welfare while reducing the impact on the environment. These studies provide theoretical guidance on both economic and social environment for the operation decision of each member in the closed-loop supply chain of power batteries.

Blockchain and IoT Integration for Secure Supply Chain Operations: Unlocking Real-Time Transparency and Business Continuity

This paper presents an analysis of the ways in which Blockchain and Internet of Things (IoT) systems can be combined for the betterment of supply chain management as well as a discussion of the increased security, transparency and/or continuity of business that may result from such an integration. In the current world where the global supply chains are continuing to expand and integrate, it has been noted that there is need to protect real time information flows and enhance the integrity and traceability of information. Using Blockchain’s decentralized and immutable structure together with IoT’s data-collection aspect, this research explores ways in which supply chain processes could benefit from these technologies while minimizing the risks posed by data theft, forgery, and disruptions. The research employs published data analysis and a case study, encompassing cross-industry benchmarks, research, and empirical evaluation of Blockchain-IoT applications in industries. Survey data was obtained from recent implementations in industries including pharmaceutical, F&B and logistics. Quantitative tools and techniques were applied to evaluate the integrity and the reliability of Blockchain-IoT systems operations. Some insights discovered reveals that the integration between Blockchain and IoT fosters better real-time monitoring, minimizes counterfeiting and promotes better traceability of an average of 40% based on observed instances. Literature is advanced in this paper by presenting grounded data on Blockchain and IoT’s ability to maintain enduring and reliable supply chain security. The research implies that when the technologies are well deployed, they act as a key driver in facilitating secure and efficient supply chain. The presented research provides guidance on the adaptation of Blockchain and IoT to enhance the stability of the supply chain; it maps a tactical plan that industry participants can follow to achieve sustainable, secure supply chain operations.

Metabolomic analysis of rice cultivars from diverse production areas.

Rice grown in Yunnan Province is known for its excellent taste and consumer preference. However, the metabolite composition of this unique rice remains unclear. In this study, the metabolic profile of different rice planted in various producing regions was evaluated. A total of 1,005 metabolites were identified, including nucleotides and their derivatives, amino acids and their derivatives, alkaloids, organic acids, phenolic acids, lignans and coumarins, lipids, terpenoids, quinones, flavones, tannins, and others. Procucing region and varieties can be clearly distinguished on the PCA diagram. Differential metabolites accumulated in the MSD502 vs. MSR88 (138)/LHHG (234)/LHR88 (188) comparison groups. The results in this study provide scientific information for the origin tracing and variety differentiation of raw rice materials.

Digital Footprints and Evidence: The Need for a Theoretical and Normative Definition in the Context of Digitalization

Introduction: the paper analyzes the scientific positions of understanding footprints and evidence processed exclusively in digital form, their nature, and their relationship with generally accepted categories. The current discussion allows for developing a unified approach to understanding the nature of digital footprints and their interpretation in the science of criminalistics, criminal procedure, and other branches of legal science. The study aims to examine the most influential scientific perspectives on comprehending the fundamental nature of digital footprints and evidence, with the goal of subsequently incorporating these understandings into the criminal law sciences and legislation. The author analyzes the controversial issues of the nature of digital footprints and evidence, clarifies some judgments, and identifies potential solutions. Methods: the dialectical, systemic, and logical methods (general scientific) were used in the course of the study. Among the specific scientific research methods, the formal legal and generalization methods prevailed. Results: based on the results of the conducted research, the most general theoretical positions on understanding the essence of trace and evidentiary information in the digital (electronic) environment are highlighted. The information on the main approaches to understanding this category is summarized, and some additions to the domestic legislation are proposed in order to eliminate existing contradictions. Conclusions: the use of data created and processed in electronic form as orienting and evidentiary information is an objective necessity. The available scientific views on the problem under consideration have studied its essence quite comprehensively, operate in various terms, and, in the author’s opinion, require the development of a conceptual construct, including those enshrined in the legislation to optimize criminal proceedings.

Combing chemical composition profiling with machine learning for geographical origins identification of Nardostachys jatamansi DC.

Nardostachys jatamansi DC., a herb endemic to the Himalayas, has a long history of use in ayurvedic and other traditional medicine systems. The quality of N. jatamansi materials is closely related to their geographical origins. This study aims to develop a method for quickly and accurately identifying the geographical origin of N. jatamansi samples. A total of 118 samples of N. jatamansi samples were collected from five production areas in China. High performance liquid chromatography (HPLC), inductively coupled plasma mass spectrometry (ICP-MS) and gas chromatography-mass spectrometry (GC–MS) were used to characterize the active compounds, mineral elements, and volatile components in N. jatamansi, and four algorithms were introduced to explore the potential of various machine learning modeling techniques for geographical origin authentication. Three active compounds, 8 mineral elements and 24 volatile metabolites in N. jatamansi were identified to be the key information for origin traceability and authentication. The fused data based on the 3 active compounds and the other feature variables led to the highest accuracies for origin classification, with the accuracies of linear discriminant analysis (LDA), K-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF) are 94.44 %, 100 %, 100 %, and 100 %, respectively. This study demonstrates the effectiveness of a multi-source data fusion strategy for geographical origin traceability of N. jatamansi.

A Review of Research on Information Traceability Based on Blockchain Technology

Blockchain technology, as an emerging distributed ledger technology, has gradually shown great potential in the field of information traceability due to its characteristics of decentralization, non-tamperability, and transparency. Through blockchain technology, the production, circulation, and consumption of products can be recorded and verified to ensure the authenticity and credibility of the data. This article reviews the application of blockchain in information traceability, focusing on analyzing its practice and effects in food safety, drug traceability, supply chain management, and energy industry traceability. Through a systematic review of existing literature, this article summarizes the research status, main results, and technical challenges of blockchain information traceability, points out its significant advantages in improving transparency and trust, and also discusses the implementation complexity, limitations in terms of cost, and performance. Finally, this article proposes future development trends, including multi-chain integration and the combination of blockchain with other technologies. The research in this article provides important reference and guidance for the further development of blockchain technology in information traceability.

Customer perceptions about traceable meat: research from Northern China

Food traceability and food safety, including quality assurance processes, are essential for ensuring the health of members of society and can prevent food-supply-related problems. Meat-related food safety issues are significant, especially in developing countries like China. The main aim of this paper was to explore customer perceptions and purchase behavior, including willingness to pay, related to traceable meat. A qualitative exploratory approach was applied. Five focus groups were implemented with interviewees from Northern China, and grounded theory methodology was used in their analysis. The results showed that participants were influenced by product characteristics, sales-related factors, and subjective norms when purchasing meat. Their level of trust in traceability information was variable; respondents preferred independent quality assurance associations and information obtainable by scanning QR codes. The findings of this study may contribute to the introduction and development of food traceability systems in the meat industry, reinvigorating consumer trust.

Factors influencing young adults’ organic food purchase intention on fresh food e-commerce platforms

PurposeUnderstanding young adults’ organic food purchasing behavior in the fresh food e-commerce platforms (FFEP) is crucial for expanding the global environmental product market. The study aims to investigate how specific characteristics of platforms and organic food information impact young adults’ perceived value, leading to their subsequent purchase intention.Design/methodology/approachAround 535 valid responses were collected through an online survey and then analyzed applying a two-stage structural equation model (SEM) and artificial neural network (ANN) approach.FindingsResults of this research show that platform characteristics (including system quality and evaluation system) and product information characteristics (including organic label, ingredient information and traceability information) significantly affect young adults’ perceived utilitarian and hedonic value. The platform’s service quality has a strong effect on their perceptions of hedonic value, while the delivery system strongly influences their utilitarian value. Moreover, the perceived value, as a crucial mediator, plays a significant role in moderating the influence of platform and product information characteristics on the purchase intentions of young consumers regarding organic food.Originality/valuePrevious research has overlooked the credence attributes of organic food and particularities of online purchasing, focusing instead on general platform and product characteristics. This study addresses this gap by proposing a more appropriate model that integrates the characteristics of both the platform and product information. This offers theoretical and managerial implications for effectively stimulating organic food consumption among young adults in online environments.

Research on the Impact of Multi-Agent Information Traceability on Quality and Safety of Agricultural Product Supply Chain Under Blockchain

Research on the Impact of Multi-Agent Information Traceability on Quality and Safety of Agricultural Product Supply Chain Under Blockchain

Маркировка вещественных доказательств как элемент обеспечения их технической достоверности

Introduction. The article is devoted to the issue of introducing into criminal justice system the procedure of labelling physical evidence with dynamic QR codes generated in the conditions of seizure of trace information after filling in a digital individual map for each object. Working with the encoded information is suggested to be carried out with appliance of the programme ‘Verification of technical authenticity of physical evidence’ providing access of the user authorised on a permanent or temporary basis to the primary and supplemented information on the labelled physical evidence, formed in handling the object equipped with a QR code. These data include factographic data on territorial-temporal parameters and conditions of seizure of objects, their localisation, information on the persons involved in processing physical evidence, technical and forensic means and methods applied in the process of detection, fixation, seizure, preliminary and expert investigation, accounting and registration activities. The authors emphasise the necessity of creation of systems of automatic identification of physical evidence with appliance of QR codes making it possible to trace the whole life cycle of objects. It is noted that the development and introduction of advanced software into practice can contribute to the creation of a modern system of traceability of handling a labelled object, aimed at preventing illegal activities related to intellectual or material forgery of physical evidence. Methods. The universal dialectical method of scientific research, as well as a set of various methods of general scientific and cognitive orientation, including logical, comparative-legal and other private methods of research are used as a methodological basis of the study. Results. The authors have substantiated the reasonability of introducing into the activity of law enforcement bodies the procedure of labelling each physical evidence, attached to the materials of a criminal case by using dynamic QR codes. This means provides technical reliability of each object, attached to the materials of a criminal case due to full traceability of all manipulations, carried out in processing it when investigating crimes.

Research on Convergence Media Ecological Model Based on Blockchain

Currently, the media industry is in the rapid development stage of media integration, which has brought about great changes in content production mode, presentation form, communication mechanism, operation and maintenance management, etc. At the same time, it is also faced with problems such as difficult information traceability, declining industry credibility, low data circulation quality and efficiency, difficult data security and user privacy protection, etc. Utilizing blockchain’s characteristics can solve these problems that the media industry is currently facing. This paper designs a convergence media ecology model based on blockchain (CMEM-BC), focusing on the basic elements of the model, node operation and maintenance system, node management mechanism, value circulation mechanism, and storage mechanism, trying to establish a decentralized, traceable, and immutable convergence media ecosystem. On this basis, this paper summarizes the ecological framework and ecological model of CMEM-BC. Finally, the paper describes the verification of the effectiveness of CMEM-BC in key links through simulation experiments, verifying that CMEM-BC has high originality and is more suitable for the application of convergence media ecology through model analysis and comparison.

Harmonic voltage phasor reconstruction and harmonic state estimation based on the measurement data of a capacitive voltage transformer

AbstractHarmonic state estimation, which highly depends on accurate synchronised phasors, is a crucial basis for the location, traceability, and governance of harmonics in power systems. However, most existing synchronous phasor measurement units (PMUs) provide power frequency phasors rather than harmonic phasors. In addition, as the dominant voltage signal provider for PMUs in power systems, capacitive voltage transformers (CVTs) have complex frequency responses and cannot be directly used for harmonic measurement. Therefore, accurate harmonic state estimation is difficult to achieve in applications. A method for harmonic voltage phasor reconstruction and harmonic state estimation based on the measurement data of a CVT is proposed. First, the reasons for harmonic voltage measurement errors were analysed. Second, the scattering parameter method was used to measure the wideband voltage transfer characteristics of CVT. Third, a voltage reconstruction method was proposed to improve the measurement accuracy and expand the frequency range of synchronous phasor measurement. Fourth, this method was applied to harmonic state estimation, and the performance of harmonic state estimation before and after voltage reconstruction was quantitatively compared. Results showed that the proposed method can remarkably improve the accuracy of harmonic state estimation. Finally, some factors, such as state observability, complex error disturbances, CVT structure, and harmonic order, influencing the performance of the proposed method were investigated. Results further demonstrated that the method has high accuracy, strong anti‐interference, and adaptability, and can provide basic information for harmonic localisation and traceability.

Determining the legality of newly described CITES-listed species in the horticulture trade of tropical pitcher plants (Nepenthes).

Due diligence is a fundamental component of ensuring a sustainable and legal wildlife trade that is also supportive of the livelihoods and businesses that depend on the trade. This is particularly true with species listed on the Convention on International Trade in Endangered Species (CITES) that are considered threatened or may become threatened by trade. Undertaking due diligence exercises requires access to information on which to base such decisions; however, the extent to which information is available is unclear. We used the trade in tropical pitcher plants (Nepenthes) for horticultural purposes as a case study to determine the extent to which information is available. A systematic survey of online trade was conducted for species described from 1996 to 2016. For the species found in trade, these were cross-referenced with the CITES trade database, and inquiries were made to the relevant CITES Management Authorities and National Focal Points Access and Benefit Sharing (ABS). Of 83 newly described species, 61% were offered for sale online in 2018. Despite all Nepenthes species being listed on CITES, only 23% (n=19) of the species being sold online were reported in trade on the CITES Trade Database, and only 3 were from the countries of origin. Thirty-two of these species had no international trade recorded according to the database. Management authorities of CITES for the countries of origin confirmed trade had been permitted for 5 of 32 species. Lack of CITES records may be explained by trade under "Nepenthes spp." or as exempt parts and derivatives. However, permits to collect and commercialize are likely to be required as part of the Nagoya Protocol on ABS from the Convention on Biological Diversity. The ABS National Focal Points were contacted to determine whether collection or commercialization permits had been issued for the remaining species. Only 2 of 7 focal points replied, and both stated no permits had been issued. Lack of traceability information or response related to the issuance of collection and commercialization permits is concerning and hinders the due diligence of businesses and consumers wanting to ensure their trade is legal, sustainable, and ethical.

Discussion of Consumers’ Preference for Food Product Traceability Information: Beijing Traceable Tomato Case Study

The paper exemplifies a practical application of combining MNL, RPL and LCM econometric models to study consumer preference heterogeneity in the multi-attributive setting, by analyzing a case study of information traceability preferences of Beijing consumers who buy fresh tomatoes in the post-COVID period. Methodologically, such application of different models (MNL, RPL, LCM) has initially allowed to identify general patterns in Chinese consumers’ preference in the tomato traceability information, then to identify and categorize distinct groups of customers and finally to provide details to their ‘marketing’ profiles towards their willingness to pay. As a result, consumer groups in this study were classified around three key attributes of tomato traceability information which reflect their priorities: consumers from “Price sensitivity” group demonstrated a higher willingness to pay for information on how products were produced (production condition) and products’ certification; “Testing Information Preference” group was willing to pay for the information about tomato’s product quality detection, and “Official Authority Approval Preference” group has developed priority for information on production condition. Such methodological approach provides rather precise characteristics about three different consumer groups, and thus fills in the existing lacunae in the literature and can serve a guiding tool for designing a regional food safety policy. The suggested methodology is transferrable for analyzing consumers’ choices for traceability information about other food products and beyond China.

Providing Provenance in eHealth.

eHealth data can be generated by different health professionals. Documenting and storing the provenance of medical data will help in providing patients and medical institutions with trustable and traceable information regarding medical procedures and their results. The use of a modular architecture like HIPAMS allows covering different eHealth information representation formats as well as providing protection mechanisms and access control.

Transparency requirements after the pandemic: traceability information, information usefulness and trust

PurposeThe flagship traceability technology is increasing transparency, social benefit and economic value particularly after the pandemic. There has not been much research on how information quality in transparency affects information usefulness and trust. The research model is built on the framework of transparency requirements and incorporates the usefulness of traceability information and trust.Design/methodology/approachQuestionnaire survey was used for data collection. To evaluate the research model, structural equation modeling (SEM) was employed. Measurement invariance analysis was used to investigate variations in trust between groups.FindingsThe results show that transparency requirements including information relevancy, ease of manipulation and value-added information affect information usefulness. The usefulness of traceability information positively affects trust in producers. Information receivers who believe in the credibility of traceability information have a higher level of trust than those who do not.Originality/valueThe results have important theoretical and practical implications for academia and industry to devise strategies and policies on data-centric traceability systems.

The Block Copolymer Phase Behavior Database.

The Block Copolymer Database (BCDB) is a platform that allows users to search, submit, visualize, benchmark, and download experimental phase measurements and their associated characterization information for di- and multiblock copolymers. To the best of our knowledge, there is no widely accepted data model for publishing experimental and simulation data on block copolymer self-assembly. This proposed data schema with traceable information can accommodate any number of blocks and at the time of publication contains over 5400 block copolymer total melt phase measurements mined from the literature and manually curated and simulation data points of the phase diagram generated from self-consistent field theory that can rapidly be augmented. This database can be accessed via the Community Resource for Innovation in Polymer Technology (CRIPT) web application and the Materials Data Facility. The chemical structure of the polymer is encoded in BigSMILES, an extension of the Simplified Molecular-Input Line-Entry System (SMILES) into the macromolecular domain, and the user can search repeat units and functional groups using the SMARTS search syntax (SMILES Arbitrary Target Specification). The user can also query characterization and phase information using Structured Query Language (SQL) and download custom sets of block copolymer data to train machine learning models. Finally, a protocol is presented in which GPT-4, an AI-powered large language model, can be used to rapidly screen and identify block copolymer papers from the literature using only the abstract text and determine whether they have BCDB data, allowing the database to grow as the number of published papers on the World Wide Web increases. The F1 score for this model is 0.74. This platform is an important step in making polymer data more accessible to the broader community.

Does the selection of the fracture model affect the calculation of the permeability of a rock mass?

The permeability of a rock mass is an indispensable and significant parameter for the construction of rock engineering. Since most fractures are buried in the rock mass, accurately assessing the permeability of the rock mass has posed a challenge to scholars in the field. The discrete fracture network (DFN) is recognized as an effective method for calculating the permeability of rock masses. However, the impact of the fracture model on permeability calculations is neglected during the construction of DFNs. This study uses the FracMan software to conduct a series of numerical simulation experiments, demonstrating that the selection of the fracture model significantly influences permeability calculations. Furthermore, we investigate the effects of constructing different circular DFNs based on trace information from various sampling windows. The results indicate that relying solely on a circular DFN derived from a single sampling window to calculate permeability is unreliable, and we reveal the fundamental laws of how DFNs constructed based on different fracture models influence the permeability assessment of rock masses. Therefore, integrating multi-source information from rock mass outcrops and boreholes, in conjunction with selecting an appropriate fracture model for constructing DFNs, is crucial for accurate permeability calculations of rock masses.