Identification Of Origin Research Articles

Light hydrocarbons composition and carbon isotopes unravel the origin of natural gas in Triassic marine strata of Moxi gas field, central Sichuan Basin

The Triassic marine gas reservoir in the Moxi Gas Field is one of the large gas fields initially discovered in the Sichuan Basin. However, the origin of its natural gas has long been debated. To study the genetic types and origin of natural gas, the light hydrocarbons (LHs) composition, carbon isotopes, chemical compositions, and stable carbon and hydrogen isotopic compositions were analyzed in the Triassic strata of Moxi gas field in the Sichuan Basin. The natural gases from the second member of the Jialingjiang Formation (T2j2) and the first member of the Leikoupo Formation (T2l1) have dryness coefficients higher than 0.997 and contain low content non−alkane gases such as CO2 and N2. The δ13C1 values of natural gas in the Moxi (MX) gas field range from −35.3‰ to −32.9‰, the δ13C2 values range from −34.0‰ to −30.3‰, and the δD1 values range from −144‰ to −120‰. As for light hydrocarbons composition, the C7 LHs are dominated by the methylcyclohexane (MCH), and the C6−C7 LHs have low normal alkane contents. The individual carbon isotopes of light hydrocarbons have the characteristics of δ13C > −28‰. The origin identification indicates that the natural gas in this area is oil−type gas that results from the secondary cracking of crude oil. Our results show that the natural gas in T2j2 of the MX gas field is sourced from the shale gas of the Є1q, the T2l1 gas is a mixed−source gas from different thermal evolution stages of the Є1q source rocks, shale gas and oil−cracking gas. The mixing effect is the main reason for the reversed phenomenon (δ13C1 > δ13C2).

Fluorescence Spectroscopy and a Convolutional Neural Network for High-Accuracy Japanese Green Tea Origin Identification

This study aims to develop a system combining fluorescence spectroscopy and machine learning through a convolutional neural network (CNN) to identify the origins of various Japanese green teas (Sayama tea, Kakegawa tea, Yame tea, and Chiran tea). Although food origin labeling is important for ensuring consumer quality and safety, ac-curate identification remains a priority for the food industry due to the emergence of problems with false origin labeling. In this study, image data of the fluorescent fingerprints of green teas were collected using fluorescence spectroscopy and analyzed using a CNN model implemented in Python (ver. 3.13.2), TensorFlow (ver. 2.18.0), and Keras (ver. 3.9). The fluorescence of each sample was measured in the range of 250 to 550 nm, highlighting the differences in chemical composition that reflect each region. Using these data, a CNN suitable for image recognition successfully identified the origins of the teas with an average accuracy of 92.83% in 10 trials. For Chiran tea and Yame tea, precision and recall rates of over 95% were achieved, showing clear differences from other regions. In contrast, the classification of Kakegawa and Sayama teas proved challenging due to their similar fluorescence patterns in the 300–350 nm spectral range, corresponding to catechins and polyphenolic compounds. These similarities are presumed to reflect the comparable growing conditions and processing methods characteristic of the two regions. This study shows the potential of this system in food origin identification, suggesting applications in preventing origin fraud and quality control. Future research will aim to extend the system to other regions and foods, enhance data preprocessing to improve accuracy, and develop a versatile identification system.

Nuclear forensic study for identification of origin of yellow cakes using chemometrics coupled laser-induced-breakdown-spectroscopy (LIBS)

Nuclear forensic study for identification of origin of yellow cakes using chemometrics coupled laser-induced-breakdown-spectroscopy (LIBS)

Origin identification of Angelica dahurica using a bidirectional mixing network combined with an electronic nose system

Origin identification of Angelica dahurica using a bidirectional mixing network combined with an electronic nose system

Linking the United Nations on the convention on the rights of the child (1989) to the needs of children affected by parental imprisonment

ABSTRACT Parental imprisonment is an adverse childhood experience. A recent research review has emphasised the need to explicitly consider children affected by parental imprisonment (CAPI) when promoting the children’s rights (UNCRC, 1989). This systematic mapping review provides an original identification and analysis of relationships between CAPI’s needs and children’s rights instrumentation. Drawing from the recent research review 2022), the identified needs of, and associated provisions for, CAPI in education are linked to a range of provisions of the United Nations Convention on the Rights of the Child (UNCRC). Of the 12 identified needs of CAPI, nine were referenced within at least one of the UNCRC sources, with many being referenced multiple times within and/or across sources. The significance of this linking of children’s needs and children’s rights to educational theory, to professional practice, and for future research, is highlighted.

OP4.7 Gluteal Complex is important in External Snapping Hip: intraoperative identification of syndrome origin and endoscopic stepwise release – a case series

Abstract Purpose: External snapping hip syndrome (ESHS) was historically attributed to isolated iliotibial band (ITB) contracture. However, the gluteus maximus complex (GMC) may also be involved. This study aimed to intraoperatively identify the ESHS origin and assess the outcomes of endoscopic treatment based on the identified aetiological type. Methods: From 2008-2014, 30 consecutive patients (34 hips) with symptomatic ESHS cases refractory to conservative treatment underwent endoscopic stepwise “fan-like” release, gradually addressing all known reasons of ESHS: from the isolated ITB, through the fascial part of the GMC until a partial release of gluteus maximus femoral attachment occurred. Snapping was assessed intra-operatively after each surgical step and prospectively recorded. Functional outcomes were assessed via the MAHORN Hip Outcome Tool (MHOT-14). Results: Twenty seven patients (31 hips) were available to follow-up at 24-56 months. In all cases, complete snapping resolution was achieved intra-operatively: in seven cases (22.6%) after isolated ITB release, in 22 cases (70.9%), after release of ITB + fascial part of the GMC, and in two cases (6.5%) after ITB + fascial GMC release + partial release of GM femoral insertion. At follow-up, there were no snapping recurrences and MHOT-14 score significantly increased from a pre-operative average of 46 to 93(p<0.001). Conclusion: Intraoperative identification and gradual addressing of all known causes of ESHS allows for maximum preservation of surrounding tissue during surgery while precisely targeting the directly involved structures. Endoscopic stepwise “fan-like” release of the ITB and GMC is an effective, tailor-made treatment option for ESHS regardless of the snapping origin in the patients with possibility to manually reproduce the snapping. Level of evidence: III Keywords: external snapping hip; iliotibial band; gluteus maximus complex; endoscopy; release; stepwise

Multivariate fusion for identification of geographic origins and varieties of coix seed

To ensure the authenticity of geographic origins and varieties of coix seeds and their preliminary processed products, this study focused on their viscosity characteristics and stable isotopes before and after gelatinization. The feasibility of identifying coix seed origins from Guizhou and Liaoning, China, and distinguishing between big coix seed (BCS) and small coix seed (SCS) based on viscosity parameters, protein and lipid content, stable isotope ratios and near-infrared spectra was investigated. Significant differences were observed in peak viscosity, trough viscosity, final viscosity, δ2H, and δ18O values between Guizhou and Liaoning coix seeds, as well as between BCS and SCS. Stable isotopic changes before and after gelatinization were consistent, with higher δ18O values in gelatinized coix seeds. PLS-DA models achieved prediction accuracies of 92.00% for Guizhou samples, 88.00% for Liaoning samples, and 84.00% for BCS and SCS, providing effective methods for the large-scale traceability of coix seeds’ geographic origins and varieties.

Rapid and accurate identification of Panax ginseng origins based on data fusion of near-infrared and laser-induced breakdown spectroscopy.

Rapid and accurate identification of Panax ginseng origins based on data fusion of near-infrared and laser-induced breakdown spectroscopy.

Rapid non-destructive identification of blueberry origin based on near infrared spectroscopy combined with wavelength selection

Rapid non-destructive identification of blueberry origin based on near infrared spectroscopy combined with wavelength selection

New methods collection to identify the building and decoration stones provenance

When investigating historical building stones, we often encounter an issue concerning the original material provenance identification. Addressing this issue is usually rather complicated due to the unavailability of samples to conduct a petrographic analysis that itself often cannot fully identify the site of acquisition. It is therefore imperative to focus on non-destructive research methods applicable in the field. Great emphasis is placed on interdisciplinarity with experts from a variety of fields contributing to the achievement of relevant results. The reflectance spectroscopy method in the near- and mid-infrared spectral range (1000–2500 nm), a simple and effective method to be applied in situ, is used for non-destructive identification of stone provenance. A unique spectral reflectance curve representing the reflectance in percentages versus the wavelength can be defined for each material. Consequently, the curve can be compared with spectra in the pre-prepared library in order to find the one best corresponding to the investigated curve to identify the material. The applied traceology methods are used to determine the approximate age of the stone elements to specify the achieved results, and not least, they are compared with the results of archival and art history research. Within our research, these methods were applied during the investigation of historical stone artefacts and masonry in St. Vitus Cathedral, located in Prague, Czech Republic. The achieved results corroborate a high potential of the selected methods and approaches.

Geographical Origin Identification of Chinese Red Jujube Using Near-Infrared Spectroscopy and Adaboost-CLDA

Geographical Origin Identification of Chinese Red Jujube Using Near-Infrared Spectroscopy and Adaboost-CLDA

Comprehensive Quality Evaluation and Botanical Differentiation of Typhae Pollen Using UHPLC-DAD/Q-TOF-MS and Multivariate Chemometric Analysis.

In China, Typhae Pollen (TP) has been extensively utilized as a medicinal product, which is the dried pollen from the male inflorescences of Typha angustifolia L. (TA), Typha orientalis Presl (TO), or species within the same genus. However, existing methods for differentiating the botanical origin and controlling the quality of TP are confusing, unreliable, and unsystematic. This study aims to elucidate the microstructural similarities and differences between pollen grains of the two species and to develop a comprehensive method for the qualitative and quantitative analysis of multiple flavonoids and phenolic acids in TP. Scanning electron microscopy (SEM) was employed to examine the dried pollen grains. A comprehensive analytical approach was developed using ultra-high performance liquid chromatography with diode array detection and quadrupole-time-of-flight mass spectrometry to quantitatively and qualitatively analyze 17 flavonoids and phenolic acids. Discrepancies in constituents were further explored using partial least squares discrimination analysis and hierarchical clustering analysis. Microscopic examination revealed distinct differences between the pollen grains of the two species, which could be distinguished using SEM. The analytical methods established for these 17 constituents-comprising 13 flavonoids and 4 phenolic acids-proved reliable and accurate. The flavonoid glycosides in TP could be categorized into three distinct groups. In TA, the average contents of constituents 1, 2, 3, 4, 8, and 12 were higher than in TO, whereas the reverse was true for constituents 7, 14, 16, and 17. Constituents 9, 10, and 13 were unique to TO. And constituent 14 should be chosen as a more appropriate quality indicator for TO. Chemometric techniques effectively differentiated between TA and TO. This study contributes to enhancing quality control and facilitating botanical origin identification of TP and provides an experimental foundation for improving its standards.

FT-NIR Spectra of Different Dimensions Combined with Machine Learning and Image Recognition for Origin Identification: An Example of Panax notoginseng.

Panax notoginseng (P. notoginseng) is a traditional medicinal plant with high medicinal and economic values. The authenticity of P. notoginseng often determines its quality, and the quality of geographical indication (GI)-producing areas is usually superior to that of other producing areas, which are exploited by unscrupulous traders and affect the market order. The aim of this study was to characterize and identify the geographic origin of P. notoginseng using Fourier transform near-infrared (FT-NIR) spectroscopy, with rapid detection combined with multivariate analysis. The use of principal component analysis and correlation spectral analysis enabled the initial differential characterization and identification of P. notoginseng from different production areas. Then, random forest (RF) and support vector machine (SVM) models were established, and the results show that the results showed that the second-order derivative preprocessing and successive projection algorithm feature extraction achieved 100% classification correctness and the model training time is the shortest. Further constructing the image recognition model, synchronous two-dimensional correlation spectroscopy (2DCOS) image combined with residual convolutional neural network achieved accurate classification (accuracy of 100%) and did not require complex preprocessing and artificial feature extraction process, to maximize the avoidance of errors caused by human factors. The recognition results of the externally validated set showed that the image recognition method has a strong generalization ability and has a high potential for application in the identification of P. notoginseng production areas.

The application of fetal nucleated red blood cells in the noninvasive prenatal testing for monogenic diseases

Fetal nucleated red blood cells (fNRBCs) in the peripheral blood of pregnant women which contain the complete genetic information of the fetus, emerge as the ideal cells for fetal genetic diseases screening and prediction. These cells have been proven useful for fetal sex identification and the detection of chromosomal aneuploidy. Given the strong heterogeneity and diverse mutation sites and types of monogenic diseases, several bottleneck issues, such as rare cell enrichment and sorting, cell origin identification, sequencing of minute amounts of DNA, and bioinformatics analysis, merits further investigation prior to utilizing fNRBCs for testing. Addressing these challenges can contribute to obtaining highly purified fetal cells, high-coverage, high-fidelity, and unbiased whole-genome amplification products, as well as accurate genetic mutation detection and analysis results. In light of the aforementioned issues, this article primarily focuses on the advancements and challenges in the non-invasive prenatal testing of monogenic diseases using fNRBCs.

The systematic techno-stylistic and chemical study of glass beads from post-15th century West African sites.

The systematic chemical analysis of large collections of archaeological glass beads is essential to better understand trade patterns at different times around the world. Glass beads' trade towards and within sub-Saharan West Africa grew exponentially over time to culminate with the establishment of the Atlantic Trade. Although these artefacts are very commonly found in archaeological contexts dating after the 15th century CE, the assemblages are generally poorly studied from a chemical point of view. We present here the study of 916 glass beads found in five archaeological sites in Ghana, Mali, and Senegal, in contexts dated between the 15th and the mid-20th century CE. Besides the techno-stylistic classification of the whole assemblage, the compositional study of a sub-group of 578 monochrome and polychrome glass beads was performed. The 798 glass samples composing the selected beads were therefore classified based on their main chemical composition. Moreover, major, minor, and trace elements analysis by Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) and the statistical analysis of the results by Principal Component Analysis (PCA) led to the identification of the probable origin of the glass. Different suppliers were distinguished for the Ghanaian earlier beads and the Senegalese and Malian later ones, in relation to the different European trade partners at different times.

Origin and Variety Identification of Dried Kelp Based on Fluorescence Fingerprinting and Machine Learning Approaches

Accurate labeling of the origin of food ingredients is essential to ensure quality and safety; however, establishing a reliable identification method remains an urgent task. The origin and variety of dried kelp are generally identified based on their morphological characteristics; however, they are difficult to distinguish unless experts are involved. In addition, genetically close varieties have almost no differences in their base sequences; therefore, the accuracy of conventional identification methods using genetic analysis is limited. This study aimed to develop a system for identifying the origin and variety of dried kelp using fluorescence fingerprint data obtained by fluorescence spectroscopy and a convolutional neural network (CNN). The fluorescence characteristics of dried kelp were measured in the range between 250 and 550 nm. The obtained fluorescence fingerprint data were converted into image data and analyzed using a CNN model implemented in Python, TensorFlow, and Keras. Unlike conventional methods that rely on morphological characteristics and genetic analyses, by combining fluorescence spectroscopy and CNN, a high identification accuracy of 98.86% was achieved even for genetically close varieties. These results highlight the excellent potential of fluorescent fingerprints in identifying the origin and variety of food and are believed to contribute to preventing food fraud and quality control.

Using near-infrared hyperspectral imaging combined with machine learning to predict the components and the origin of Radix Paeoniae Rubra.

The efficacy and safety of drugs are closely related to the geographical origin and quality of the raw materials. This study focuses on using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms to construct content prediction models and origin identification models to predict the components and origin of Radix Paeoniae Rubra (RPR). These models are quick, non-destructive, and accurate for assessing both component content and origin. Spectral data were preprocessed using multiple scattering correction (MSC), Savitzky-Golay smoothing (S-G), and standard normal variate (SNV). Content prediction models for paeoniflorin were developed using principal component regression (PCR), partial least squares regression (PLSR), and ridge regression (RR). Classification models for origin identification utilized support vector machine (SVM), K-nearest neighbor (KNN), and random forest (RF). The SNV-RR model achieved a determination coefficient of 0.8943, while the SNV-SVM model achieved an accuracy of 0.9790. Meanwhile, two feature selection methods were used to further simplify the prediction model while ensuring accuracy, in order to improve the detection efficiency in practical applications. This research demonstrates the feasibility of combining NIR-HSI with machine learning for quality analysis of RPR, providing a theoretical basis for promoting hyperspectral imaging technology in the food and pharmaceutical sectors.

Tracing the geographical origin of Chinese green tea based on fluorescent sensor array combined with multi-way chemometrics analyses.

Tracing the geographical origin of Chinese green tea based on fluorescent sensor array combined with multi-way chemometrics analyses.

Radial intralesional linear calcifications and focal hyperostosis: key points for diagnosis, extension and point of origin identification of sinonasal inverted papilloma.

Sinonasal inverted papilloma (IP) often appears as a unilateral sinonasal soft-tissue mass with varying enhancement, often accompanied by bone remodelling, intralesional calcifications, focal hyperostosis, and cone-shaped bone thickening (observed in 60 to 80% of cases) (1,2). A non-contrast sinonasal CT scan may reveal a soft tissue polypoid mass that closely resembles inflammatory polyps (Figure 1 A-D). While hyperostosis is recognized as a marker of the tumor's point of origin (1), intralesional calcifications are less frequently described but may offer valuable insights. Early studies, such as those by Lund and Lloyd (1984), highlighted the presence of intralesional calcifications as a distinct feature of inverted papilloma, a finding later supported by studies emphasizing the role of bone morphogenic proteins in calcification development (4-7).

Data fusion of Fourier transform infrared spectroscopy and high-performance liquid chromatography for the origin identification of different medicinal rhizomes of genus Atractylodes

Data fusion of Fourier transform infrared spectroscopy and high-performance liquid chromatography for the origin identification of different medicinal rhizomes of genus Atractylodes