Verification Of Origins Research Articles

Exploring the influence of different processing conditions on DNA quality of collagen peptides and the feasibility of its raw material traceability

In this work, we have presented a new method for species origin verification of collagen peptides based on DNA techniques. First, we investigate the changes in DNA during the preparation of collagen peptides including the total amount of collagen peptide DNA and the DNA degradation under different processing conditions. Secondly, we discussed the possibility of using polymerase chain reaction (PCR) for follow-up detection of collagen peptides. The results showed that the total amount of DNA decreased as the treatment intensity increased. The size of the cleaved fragments of DNA are mainly concentrated between 200 and 500 bp. On this basis, the combined PCR results finally determined that trace collagen peptide DNA can be effectively amplified with amplicons of about 300 bp to complete the verification of the species origin of collagen peptide. This study provides a new strategy for determining the authenticity of food labels for bovine collagen peptides.

DIS-Guard: Enhancing SDN resilience to topology and RCO attacks

SDN controllers employ discovery protocols with LLDP packets to discover the network topology; however, this approach is susceptible to topology attacks due to the static reuse of LLDP packets without proper origin verification or integrity checks. This paper proposes a novel form of topology attack called the Round-trip time Confusion Onslaught (RCO) attack. Our findings showcase the capability of the RCO attack to mislead the discovery service of SDN controllers and bypass the Real-time Link Verification (RLV) defence mechanism, which depends on timing features in Machine Learning (ML) models. The RCO attack significantly reduces the effectiveness of the RLV mechanism in terms of True Positive Rate (TPR), Precision, F1-score, and Cohen’s Kappa and increases the False Positive Rate (FPR). These results underscore the difficulties in achieving dependable ML accuracy in topology attack detection. Accordingly, we propose the DIS-Guard framework, designed to protect and improve the efficiency of discovery protocols within SDN controllers. This framework utilizes the mutual Transport Layer Security (mTLS) protocol to discover hosts proactively. Moreover, it employs a novel combination of a chaos-tent map and the proposed statistical method for link discovery. Through extensive evaluation, we illustrate DIS-Guard’s superior performance and security over the established Ryu (switches.py) controller and the RLV defence mechanism. Notably, DIS-Guard reduces host-to-host access delays, decreases LLDP packet transmission and reception significantly, and improves control channel efficiency. Collectively, these quantifiable benefits manifest the efficacy of DIS-Guard as a significantly optimized solution for SDN security and performance.

A statistical interpretation of the EN 1993-1-10 brittle fracture criteria

EN 1993-1-10 contains tables for selection of steel quality class with respect to avoidance of brittle fracture. The conservatism of the method has not previously been examined statistically. The original verification of the method has been established basically on a deterministic assessment of 19 double edge cracked specimen tests. This verification has not accounted for e.g. constraint effects and the treatment of nominal data versus measured data is not fully satisfactory. Therefore, here the confidence of the procedure is examined statistically using more up to date information regarding the Charpy-V vs fracture toughness correlation and a quantitative assessment of the constraint effect. The study has two main purposes. First, to present a method by which consistent statistically defined criteria for a standard like EN 1993-1-10 can be developed and second, to obtain an approximate estimate of the conservatism contained in the present methodology. The statistical treatment is applied to the same 19 specimens originally used for the verification of the method.

Predicting the geospatial distribution of Chinese rice nutrient element in regional scale for the geographical origin—A case study on the traceability of Japonica rice

AbstractEffective geographical origin discrimination of Chinese rice requires a large database of samples to ensure sufficient data for origin verification at a regional scale. In this study, environmental similarity was used to establish a spatial database of rice nutrient element, and then the validity of the database was verified using the back propagation artificial neural networks modeling (BPNN). The spatial distribution model of 14 rice nutrient element (Al, Ba, Ca, Cu, Cr, Fe, K, Mg, Mn, Mo, Na, Ni, Rb, and Zn) on regional scale was built using an environmental similarity method for the first time. Elemental concentrations of 692 samples were used to build a simulated geographical origin prediction model for northeastern (N‐E), middle to lower Yangtze River plain (Y‐R), southwestern (S‐W), and southeastern (S‐E) in China. The results indicated that the performance of the environmental similarity model for these four growing regions was S‐W > N‐E > S‐E > Y‐R based on the lowest ranking root mean square error (RMSE) for each region. For example, the RMSEs of Zn in S‐W, N‐E, S‐E, and Y‐R regions were 2.0, 2.4, 2.7, and 3.7 mg/kg, respectively. A case study on the traceability of Japonica rice was shown that Japonica rice could be discriminated with higher origin accuracy using a simulated database (91.8%) than by the actual database (87.0%) using the BPNN model. This indicates that a simulated rice element database could improve the accuracy of geographical origin discrimination for Chinese rice and potentially be applied to other large national‐scale crop datasets.

수입국의 규제와 정부의 요인이 무역원활화에 미치는 영향

Purpose: This study aimed to empirically analyze how the institutional quality of importing countries affects the trade facilitation of domestic exporting companies. Research design, data, and methodology: This study first distributed questionnaires and collected responses from domestic exporting companies listed by KOTRA, KITA, and those participating in relevant training programs. Subsequently, the indices from the WGI of the World Bank were used to assess the regulatory strictness and government trustworthiness of the export destination countries. Poisson regression analysis was conducted using STATA 17 SE based on the collected data. Results: The analysis indicated that regulatory strictness increases the frequency of origin verification, while government trustworthiness decreases the frequency of origin verification. The moderating effect of export experience mitigates the impact of regulatory strictness but does not affect government trustworthiness. Conclusions: Companies should understand the regulations and characteristics of the importing country's government to reduce the factors that hinder trade facilitation and promote trade. In addition, gaining diverse export experience can help mitigate the impact of regulatory strictness.

Construction of oral squamous cell carcinoma organoids invitro 3D-culture for drug screening.

Patient-derived organoids are potent pre-chemotherapy models. Due to limited research on diverse types of oral squamous cell carcinoma (OSCC) and construction efficiency, our goal was to optimize OSCC organoid models from various sites and assess drug responsiveness. We screened and optimized culture media, employing three-dimensional techniques to construct human-derived oral squamous cell carcinoma (OSCC) organoid models invitro. Morphological validation, immunofluorescence analysis, tissue origin verification, and Short Tandem Repeat (STR) sequencing confirmed the consistency between organoids and source tissues. These organoid models were then subjected to varying concentrations of anticancer drugs, with subsequent assessment of cell viability to calculate IC50 values. Twenty-nine surgical specimens yielded an 86.2% success rate in culturing 25 organoids invitro. Morphological consistency confirmed nuclear atypia and positive expression of K5, P40, and E-cadherin, indicating squamous epithelial origin. Cultured complex organoids included α-SMA+ tumour-associated fibroblasts and tumour stem cells expressing CD44 and Ki67. STR sequencing affirmed genomic homogeneity between cultured organoids and source tissues. Drug sensitivity testing revealed diverse responses among organoids, highlighting their value for assessing drug sensitivity. An efficient OSCC organoid culture system for personalized invitro drug sensitivity screening was established, laying the foundation for precise treatment development.

How the Digital Product Passport Can Lead the Plastics Industry towards a Circular Economy-A Case Study from Bottle Caps to Frisbees.

The Digital Product Passport (DPP) as a product-specific data set is a powerful tool that provides information on the origin or composition of products and increases transparency and traceability. This recycling case study accompanies the production of 2192 frisbees, which originated from collected beverage bottle caps. In total, 486.7 kg of feedstock was collected and transformed into 363.2 kg of final product with verified traceability through all process steps via a DPP, provided by the R-Cycle initiative and based on the GS1 standard. This demanded a generally agreed dataset, the availability of technical infrastructure, and additional effort in the processing steps to collect and process the data. R-Cycle offers a one-layer DPP where the data structure is lean and information is visible to everyone. This is beneficial to a variety of stakeholders in terms of transparency. However, it does not allow the sharing of sensitive information. On the one hand, the DPP has a high potential to be an enabler for customer engagement, origin verification, or as a starting point for more efficient and advanced recycling of plastics. On the other hand, the DPP involves a certain effort in data generation and handling, which must be justified by the benefits. For small, simple packaging items, the DPP may not be the perfect solution for all problems. However, with a broader societal mindset and legislative push, the DPP can become a widely used and trusted declaration tool. This can support the plastics industry in its journey towards a circular economy.

Geographical origin verification of Crocus sativus L. grown using “two-segment” cultivation

Two-segment cultivation has recently been adopted to increase vegetative propagation and flower production of Crocus sativus in some Asian countries. Crocus sativus flowers (petals and stigmas) from Hangzhou (Jiande saffron with a geographical indication or GI status) and relocated daughter Crocus sativus corms from Shanghai (an origin without GI status) were investigated using stable isotopes (δ13C, δ15N, δ2H, δ18O) and elemental concentrations (%C and %N). Results showed that δ13C, δ15N, and δ18O of stigma and petal samples from daughter corms originating from Hangzhou and Shanghai had significant differences between the two regions (p < 0.001), even though the Shanghai origin daughter corms were harvested in Hangzhou. Furthermore, the δ15N values of stigmas and petals had a significant correlation (p<0.05, r = 0.566), but corresponding δ13C and δ2H values did not show a correlation (p>0.05). Finally, supervised PLS-DA pattern recognition models effectively discriminated stigmas and petals from crocus corms originating from the two locations. This research provides a globally-applicable mechanism to identify imposter GI Crocus sativus transferred from a non-GI origin before flowering and will enhance trust within the saffron industry.

Analysis of the Influence of Investor Sentiment on IPO Underpricing under Full Registration System: Empirical Analysis Based on PSM-DID

In February 2023, China promulgated the full implementation of the registration system in the entire stock market, replacing the original verification system. Taking the main board and GEM companies listed from January 2019 to January 2023 as research samples, this paper uses PSM-DID Model to investigate the impact of the registration system on the IPO underpricing rate. Meanwhile, OLS model is used to analyze the impact of investor sentiment and the interaction of the registration system on the IPO underpricing rate. The implementation of the registration system significantly improves the IPO underpricing rate on the basis of 1%. Parallel trend test and placebo test further verify the robustness of the conclusion. the interaction between investors' speculation and the registration system also improves the IPO underpricing rate.

Impact of Noodle Formulation, Boiling Methodology and Their Interactions on Stable Hydrogen and Oxygen Isotope Ratios.

Stable isotopes are commonly utilized for the geographical origin verification of foods, including wheat. However, assessing processed products poses a greater challenge due to the alterations that take place during processing and which have not been fully elucidated yet. In the current study, the effects of the formulation (the mass ratios of gluten to starch), boiling process and their interaction on the stable hydrogen (δ2H) and oxygen (δ18O) isotopic ratios of wheat noodles were evaluated. The δ2H and δ18O of noodles with different formulations (the mass ratios of gluten to starch) as raw materials, in uncooked and cooked (boiled in water) noodles, were examined. The results indicated that the δ2H of the boiled noodles ranged from -80.1‱ to -46.8‱ and were significantly lower than those of the raw materials, which ranged from -73.0‱ to -39.2‱, and the uncooked noodles, which ranged from -73.3‱ to -39.6‱. Oppositely, 18O was enriched in the boiled noodles, ranging from 27.7‱ to 31.3‱, compared with the uncooked noodles, ranging from 28.4‱ to 29.6‱. In addition, a significant interaction effect between the formulation and the boiling process was recorded for δ18O. This study shows that the hydrogen and oxygen stable isotopic compositions of noodles were significantly changed during the boiling process, and the isotopic fractionation varies with the different formulations.

Eigenvalue-based quantum state verification of three-qubit W class states

In quantum many-body systems, W class states are typical examples of states with genuine multipartite entanglement. They have been found to be valuable resources in many quantum information processing tasks. However, the characterization and verification of W class states still remains an intractable problem. Here we first propose an eigenvalue-based verification protocol consisting of four practical adaptive local projective measurement tests, and obtain the optimal test probabilities with particle swarm optimization algorithm. The efficiency achieved by this protocol is far from satisfactory when compared with the theoretical upper bound. Then by utilizing the symmetry of the target states and a class of specific unitaries, we optimize the original verification strategy based on group theory. In this case, our new protocol can realize the efficient verification of three-qubit W class states.

Comparison of the osteogenic potential of fibroblasts from different sources

ObjectiveWith the growing interest in the role of fibroblasts in osteogenesis, this study presents a comparative evaluation of the osteogenic potential of fibroblasts derived from three distinct sources: human gingival fibroblasts (HGFs), mouse embryonic fibroblasts (NIH3T3 cells), and mouse subcutaneous fibroblasts (L929 cells). MC3T3-E1 pre-osteoblast cells were employed as a positive control for osteogenic behavior. DesignOur assessment involved multiple approaches, including vimentin staining for cell origin verification, as well as ALP and ARS staining in conjunction with RT-PCR for osteogenic characterization. ResultsOur findings revealed the superior osteogenic differentiation capacity of HGFs compared to MC3T3-E1 and NIH3T3 cells. Analysis of ALP staining confirmed that early osteogenic differentiation was most prominent in MC3T3-E1 cells at 7 days, followed by NIH3T3 and HGFs. However, ARS staining at 21 days demonstrated that HGFs produced the highest number of calcified nodules, indicating their robust potential for late-stage mineralization. This late-stage osteogenic potential of HGFs was further validated through RT-PCR analysis. In contrast, L929 cells displayed no significant osteogenic differentiation potential. ConclusionsIn light of these findings, HGFs emerge as the preferred choice for seed cells in bone tissue engineering applications. This study provides valuable insights into the potential utility of HGFs in the fields of bone tissue engineering and regenerative medicine.

Geographical discrimination of Paw San rice cultivated in different regions of Myanmar using near-infrared spectroscopy, headspace-gas chromatography-ion mobility spectrometry and chemometrics

Paw San rice, also known as “Myanmar pearl rice”, is considered the highest quality rice in Myanmar. There are considerable differences in terms of the premium commercial value of Paw San rice, which is an incentive for fraud, e.g. adulteration with cheaper rice varieties or mislabelling its geographical origin. Shwe Bo District is one of the most popular rice growing areas in the Sagaing region of Myanmar which produces the most valued and highly priced Paw San rice (Shwe Bo Paw San). The verification of the geographical origin of Paw San rice is not readily undertaken in the rice supply chain because the existing analytical approaches are time-consuming and expensive. Therefore, there is a need for rapid, robust and cost-effective analytical techniques for monitoring the authenticity and geographical origin of Paw San rice.In this 4-year study, two rapid screening techniques, Fourier-transform near-infrared (FT-NIR) spectroscopy and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), coupled with chemometric modelling, were applied and compared for the regional differentiation of Paw San rice. In addition, low-level fusion of the FT-NIR and HS-GC-IMS data was performed and its effect on the discriminative power of the chemometric models was assessed. Extensive model validation, including the validation using independent samples from a different production year, was performed. Furthermore, the effect of the sample preparation technique (grinding versus no sample preparation) on the performance of the discriminative model, obtained with FT-NIR spectral data, was assessed. The study discusses the suitability of FT-NIR spectroscopy, HS-GC-IMS and the combination of both approaches for rapid determination of the geographical origin of Paw San rice.The results demonstrated the excellent potential of the FT-NIR spectroscopy as well as HS-GC-IMS for the differentiation of Paw San rice cultivated in two distinct geographical regions. The OPLS-DA model, built using FT-NIR data of rice from 3 production years, achieved 96.67% total correct classification rate of an independent dataset from the 4th production year. The DD-SIMCA model, built using FT-NIR data of ground rice, also demonstrated the highest performance: 94% sensitivity and 97% specificity. This study has demonstrated that FT-NIR spectroscopy can be used as an accessible, rapid and cost-effective screening tool to discriminate between Paw San rice cultivated in the Shwe Bo and Ayeyarwady regions of Myanmar.

A framework for tracing timber following the Ukraine invasion

Scientific testing including stable isotope ratio analysis (SIRA) and trace element analysis (TEA) is critical for establishing plant origin, tackling deforestation and enforcing economic sanctions. Yet methods combining SIRA and TEA into robust models for origin verification and determination are lacking. Here we report a (1) large Eastern European timber reference database (Betula, Fagus, Pinus, Quercus) tailored to sanctioned products following the Ukraine invasion; (2) statistical test to verify samples against a claimed origin; (3) probabilistic model of SIRA, TEA and genus distribution data, using Gaussian processes, to determine timber harvest location. Our verification method rejects 40–60% of simulated false claims, depending on the spatial scale of the claim, and maintains a low probability of rejecting correct origin claims. Our determination method predicts harvest location within 180 to 230 km of true location. Our results showcase the power of combining data types with probabilistic modelling to identify and scrutinize timber harvest location claims.

Combination of fingerprint and chemometric analytical approaches to identify the geographical origin of Qinghai-Tibet plateau rapeseed oil

Verification of the geographical origin of rapeseed oil is essential to protect consumers from fraudulent products. A prospective study was conducted on 45 samples from three rapeseed oil-producing areas in Qinghai Province, which were analyzed by GC-FID and GC-MS. To assess the accuracy of the prediction of origin, classification models were developed using PCA, OPLS-DA, and LDA. It was found that multivariate analysis combined with PCA separate 96% of the samples, and the correct sample discrimination rate based on the OPLS-DA model was over 98%. The predictive index of the model was Q2 = 0.841, indicating that the model had good predictive ability. The LDA results showed highly accurate classification (100%) and cross-validation (100%) rates for the rapeseed oil samples, demonstrating that the model had strong predictive capacity. These findings will serve as a foundation for the implementation and advancement of origin traceability using the combination of fatty acid, phytosterol and tocopherol fingerprints.

Machine learning-driven hyperspectral imaging for non-destructive origin verification of green coffee beans across continents, countries, and regions

Machine learning-driven hyperspectral imaging for non-destructive origin verification of green coffee beans across continents, countries, and regions

Advancements in food authentication using soft independent modelling of class analogy (SIMCA): a review

Abstract Food authentication verifies the match between product characteristics and claims and it is crucial in a globalized and complex food sector. Currently, class-modelling approaches, such as soft independent modelling of class analogy (SIMCA), are powerful tools for assessing food authenticity. The aim of this review is to discuss the application of SIMCA for food authentication and to describe the conceptual differences between discriminant and class-modelling approaches. The discussion of research articles is organized around three elements: (i) the research objectives, (ii) the analytical methodologies, and (iii) the food products investigated. Moreover, the challenges and future perspectives considering the development of innovative food products are discussed. Adulteration is the most investigated food authentication issue, followed by verification of geographical origin. Food authenticity appeared to be predominantly evaluated using non-destructive spectroscopy. Overall, the articles collectively cover a broad spectrum of food categories, representing those most prone to adulteration. However, there is a notable lack of food authentication studies on innovative food products, underscoring the urgency for further research in this field.

한중간 비특혜원산지검증의 효과적 이행을 위한 대응방안

Purpose: This paper finds out why non-special origin verification between Korea and China is important, because post-verification of exported goods is not carried out. This raises issues such as false issuance of certificates of origin or laundering of origin.&#x0D; Research design, data, and methodology: Using comparative and empirical case analysis methods, this paper focuses on verification of non-preferential origin in Korea and China.&#x0D; Results: According to this study, there are differences in application standards under the legal system verifying non-Korean origin in both Korea and China&#x0D; Conclusions: Owing to differences between Korea and China in the criteria determining non-preferential origin, it is necessary to respond effectively to contribute to trade facilitation by solving customs and procedural problems in the import and export processes with China.

Blockchain-Powered Agricultural Traceability Systems: Ensuring Food Transparency And Sustainability In Agroecosystems 5.0

Blockchain-Powered Agricultural Traceability Systems: Ensuring Food Transparency And Sustainability In Agroecosystems 5.0

Analysis of δ13C and δ15N values in Croatian honey by EA–IRMS and possibility of their application in botanical origin verification

Analysis of δ13C and δ15N values in Croatian honey by EA–IRMS and possibility of their application in botanical origin verification