Identification Of Components Research Articles

Fractional Strong Metric Dimension of Convex Polytopes and its applications

The fractional versions of various metric related parameters have recently gained importance due to their applications in the fields of sensor networking, robot navigation and linear optimization problems. Convex polytopes are collection of those polytopes of Euclidean space which are their convex subsets. They have key importance in the field of network designing due to their stable and resilient structure which aids optimal data transfer. The identification and removal of components (nodes) of a communication network causing abruption in its flow is of key importance for optimal data transmission. These components are referred as strong resolving neighbourhood (SRNs) in graph theory and assigning least weight to these components aids the computation of fractional strong metric dimension (FSMD). In this paper, we compute FSMD for certain convex polytopes which include $\mathbb{P}_{n}$, $\mathbb{P}_{n}^{1}$ and $\mathbb{P}_{n}^{2}$. In this regard, it is shown that for $n \geq 3$, FSMD of $\mathbb{P}_{n}$ and $\mathbb{P}_{n}^{2}$ is $n$ and $\frac{3n}{2}$, respectively. Also, FSMD of $\mathbb{P}_{n}^{1}$ is $n$ when $n$ is odd and $\frac{3n}{2}$ when $n$ is even. Finally, an application of FSMD in the context of internet connection networks is furnished.

Active components and mechanisms of action of psychological interventions in bipolar disorder: A systematic literature review.

The efficacy of psychological interventions for bipolar disorder (BD) is well established, but much remains unknown about how change occurs. The primary objective of this exploratory study was to audit what is known about active components and mechanisms of action of psychological interventions for BD. We conducted a systematic review (PROSPERO CRD42022323276). Two independent reviewers screened references from four databases and extracted data from eligible studies. We included four component studies, six studies with mediation analyses and 26 studies presenting subjective experiences of how psychological interventions bring change. Ten mediators were examined across six studies, with only one putative mediator, medication adherence, tested in more than one study. Some initial support for mediation of varied outcomes by control over thoughts, positive non-verbal behaviour, self-esteem, post-trauma growth and medication adherence. Some preliminary support was found in two components, human support and IPT. Studies exploring participant experiences of therapeutic change enumerated a range of potential active components, mechanisms of action and contextual factors potentially warranting investigation in future research. However, the evidence base for active components and mechanisms of action in psychological interventions for BD is unsatisfactory. Findings were inconsistent, studies homogenous with significant methodological limitations and statistical approaches failed to meet quality criteria. Preliminary identification of potential components and mechanisms via qualitative analyses and the insights emerging from this review will inform future research aimed at investigating how psychological interventions work in BD.

Sustainable purchasing supply management assessment in construction supply chains: a design science research approach

Purpose In response to multiple disruptions, the purchasing supply management (PSM) function in construction supply chain management (CSCM) has gained prominence due to stakeholder pressures, dynamic market conditions and the need to adhere to complex sustainability, safety and health regulations and standards. However, there is a noticeable absence of empirical research on measuring and mitigating PSM vulnerabilities, especially considering the distinct challenges faced by large engineer-to-order project-oriented manufacturers. To address these issues, the purpose of this study is to develop and test a novel method to assist companies in construction supply chains in assessing and managing risks associated with sustainable procuring and sourcing materials. Design/methodology/approach Grounded in the literature gaps on construction PSM and a real case supply chain, the research uses the design science research (DSR) approach to develop an integrated method for assessing PSM strategies in this sector. The method integrates three essential purchasing dimensions: supply risks, profit impact and sustainability risks of materials, supported by nine subdimensions. Empirical validation took place within a multinational European construction company based in Denmark. Findings Findings from the supplier–buyer relationships confirmed that the developed method allows for the identification of the key components that significantly impact supplier–buyer relationships, profitability and sustainability. The research further suggests that construction supply chain managers and purchasing practitioners can use the proposed method to evaluate PSM, thus enabling them to make more informed decisions. Practical implications Through the utilization of the proposed artifact, construction companies can take a more proactive approach to address PSM uncertainties, thereby enhancing their competitiveness in dynamic construction supply chains. Originality/value The research contributes to bridging the theory and practice, providing valuable assistance for construction companies assessing and managing the PSM and supply risks within global construction value chains. This paper provides original insights for the CSCM, aiding in adopting competitive PSM strategies to improve overall supply chain performance.

Comparison and identification of aroma components in 21 kinds of frankincense with variety and region based on the odor intensity characteristic spectrum constructed by HS–SPME–GC–MS combined with E-nose

Frankincense is an important seasoning and spice known for its distinctive and intricate flavor profile. Considering the considerable variation in the aromatic quality of frankincense due to geographical origin, species diversity and cultivation conditions, frankincense from major global origins was characterized holistically for the first time. The electronic nose (E-nose) with headspace solid-phase microextraction gas chromatography–mass spectrometry (HS–SPME–GC–MS) and sensory evaluation were implemented to characterize the aroma components of 21 commercial varieties of frankincense from around the world. The results showed that a total of 149 volatile organic compounds (VOCs) of 10 categories were identified in frankincense, among which the numbers of alcohols, terpenes and esters compounds accounted for 22.15 %, 18.79 % and 15.44 % of the total VOCs of frankincense, respectively. The PLS-DA model effectively distinguished frankincense from Oman/Somalia and other origins. Furthermore, the study identified two differential VOCs with VIP > 1 in three Asian countries and five in six African countries. The total VOCs content and sensory characteristic score of “Lemon/Citrus” in Oman frankincense is significantly higher than other regions. The OAV results showed that 61 substances (e.g., Diacety, alpha-Pinene, Camphene, Myrcene) as key aroma compounds and OICS model indicated that p-Cymenol was found to contribute significantly to the citrus aroma in frankincense. This study identified the fundamental components of frankincense flavor and revealed different flavor descriptors of frankincense, which are crucial for reconstructing frankincense flavor and improving flavor quality.

An investigation of deep learning approaches for efficient assembly component identification

BackgroundWithin the manufacturing sector, assembly processes relying on mechanical fasteners such as nuts, washers, and bolts hold critical importance. Presently, these fasteners undergo manual inspection or are identified by human operators, a practice susceptible to errors that can adversely affect product efficiency and safety. Given considerations such as time constraints, escalating facility and labor expenses, and the imperative of seamless integration, the integration of machine vision into assembly operations has become imperative.ResultsThis study endeavors to construct a robust system grounded in deep learning algorithms to autonomously identify commonly used fasteners and delineate their attributes (e.g., thread type, head type) with acceptable precision. A dataset comprising 6084 images featuring 150 distinct fasteners across various classes was assembled. The dataset was partitioned into training, validation, and testing sets at a ratio of 7.5:2:0.5, respectively. Two prominent object detection algorithms, Mask-RCNN (regional-based convolutional neural network) and You Look Only Once-v5 (YOLO v5), were evaluated for efficiency and accuracy in fastener identification. The findings revealed that YOLO v5 surpassed Mask-RCNN in processing speed and attained an mean average precision (MAP) of 99%. Additionally, YOLO v5 showcased superior performance conducive to real-time deployment.ConclusionsThe development of a resilient system employing deep learning algorithms for fastener identification within assembly processes signifies a significant stride in manufacturing technology. This study underscores the efficacy of YOLO v5 in achieving exceptional accuracy and efficiency, thereby augmenting the automation and dependability of assembly operations in manufacturing environments. Such advancements hold promise for streamlining production processes, mitigating errors, and enhancing overall productivity in the manufacturing sector.

Geological Conditions of Shale Gas Accumulation in Coal Measures

The shale of different potential layers is studied by using rock pyrolysis analysis, total organic carbon determination (TOC), kerogen microscopic component identification, mineral X-ray diffraction, scanning electron microscopy, and low-temperature nitrogen adsorption experiments. The results are as follows: (1) Shishui Formation of the Lower Carboniferous and Longtan Formation of the Upper Permian are the two most important shale gas reservoirs in the Chenlei Depression. The sedimentary environment of the target shale is a marine land interaction facies coastal bay lagoon swamp sedimentary system. Two sedimentary facies of tidal flat facies, subtidal zone, and lagoon swamp facies are developed. (2) The organic matter types of shale are Type III and II2, with TOC content greater than 1%. The maturity of shale samples is relatively higher (Ro,max is above 2%), which means they have entered the stage of large-scale gas generation. The overall brittle mineral content of the target shale sample is relatively higher (above 40%), which is conducive to artificial fracturing and fracture formation in the later stage, while an appropriate amount of clay minerals (generally stable at 40%) is conducive to gas adsorption. (3) The overall pore structure of the water measurement group and Longtan group is good, with a higher specific surface area and total pore volume (average specific surface area is 12.21 and 8.36 m2/g, respectively), which is conducive to the occurrence of shale gas and has good adsorption and storage potential. The gas content of the water measurement group and the Longtan Formation varies from 0.42 to 5 cm3/g, with an average of 2.1 cm3/g. It indicates that the water measurement group and the Longtan Formation shale gas in the study area have good resource potential.

Chemical Profile and Potential Application of Agri-food Waste Products for Counteracting Diabetes Induced Neuropathy in Rats.

This study aimed to prepare defatted ethanol extract of Abelmoschus esculentus leaves, Morus nigra leaves and Punica granatum peel, to identify the chemical composition of these extracts and to explore their efficacy in counteracting diabetic neuropathy. LC-ESI-MS spectrometry was the hyphenated tool for component identification of these extracts. Behavioral, biochemical, and histopathological investigations were carried out after treatments of diabetic rats. The phenolic contents in the extracts are 16.38, 34.75 and 40.57 mg GAE/g extract regarding A. esculentus leaves, M. nigra leaves and P. granatum peel respectively. Chemodiversity of the phenolic contents was observed from the LC/Mass, where A. esculentus extract contained isoflavonoids and flavanones, M. nigra extract consisted of benzofurans, prenylated flavonoids, stilbenes, and xanthones, and P. granatum extract was rich in ellagitanins, condensed tannins, and anthocyanins. The extracts normalize of blood glucose levels, enhance the explorative behavior of the rats and their response time to thermal pain, restore the oxidant/antioxidant balance, attenuate inflammation, augment brain monoamines levels and modulate MAO-A and Ache enzyme activity. Furthermore, they recovered brain histopathological alterations. Conclusively, this study offers experimental evidence for the neuroprotective impact of studied defatted ethanol extracts against diabetic neuropathy via their hypoglycemic effect, antioxidant activity, and anti-inflammatory potential.

Online identification of potential antioxidant components and evaluation of DNA oxidative damage protection ability in Prunus persica flowers

A high performance liquid chromatography-ultraviolet-visible detector-electrospray ionization-ion trap-time-of-flight-mass spectrometry-total antioxidant capacity determination (HPLC-UVD-ESI-IT-TOF-MS-TACD) new online technique was developed for efficient screening of potential antioxidant active components in Prunus persica flowers (PPF) from 4 origins. Through this online system, 46 compounds were initially identified, while 20 compounds with DPPH binding activity and 21 compounds with FRAP binding activity were detected. The antioxidant activities of 9 compounds obtained from the screening were then validated in DNA oxidative damage protection study. The results showed that this online system can cope well with the complexity of the samples. This also provides technical basis for rapid screening of antioxidant resources of PPF. In short, this study made the chemical composition of PPF more abundant and its potential antioxidant active compounds more explicit, which provided new ideas for the detection and development of natural antioxidants and provided scientific basis for PPF as functional food.

Active Targets and Potential Mechanisms of Erhuang Quzhi Formula in Treating NAFLD: Network Analysis and Experimental Assessment.

The purpose of this research was to investigate the main active components, potential targets of action, and pharmacological mechanisms of Erhuang Quzhi Formula (EHQZF) against NAFLD using network pharmacology, molecular docking, and experimental validation. The main active chemical components of EHQZF and the potential targets for treating NAFLD were extracted and analyzed. The PPI network diagram of "Traditional Chinese Medicine-Active Ingredients-Core Targets" was constructed and the GO, KEGG, and molecular docking analysis were carried out. Identification of components in traditional Chinese medicine compounds was conducted by LC-MS. NAFLD models were established and relevant pathologic indicators and Western blot were analyzed in vivo and ex vivo. Totally 8 herbs attributed to the liver meridian and 20 corresponding targets of NAFLD were obtained from EHQZF. Flavonoids and phenolic acids as the main components of EHQZF treated NAFLD through the MAPK/AKT signaling pathway. Pathway enrichment analysis focused on the MAPK/AKT signaling pathway and apoptosis signaling pathway. Molecular docking showed that Quercetin and Luteolin had stable binding structures with AKT1, STAT3, and other targets. Experiments showed that EHQZF reduced lipid accumulation, regulated changes in adipose tissue, inhibited the MAPK/AKT signaling pathway and exert multiple components, several targets, and multiple pathway interactions to treat NAFLD.

Component diagnosis of food allergy: precise identification of allergenic components in egg and milk

Food allergy are triggered by an abnormal immune response to specific food components, with milk and eggs being the most common food allergens, especially in children. Food allergy can cause various symptoms such as rashes, difficulty breathing, and digestive issues. Allergen component diagnostics is a technique used to identify specific allergenic proteins, aiding doctors in providing more precise treatment and management recommendations for patients. This article analyzes the latest research developments and clinical significance of milk and egg allergen components based on the " Molecular Allergology User's Guide 2.0 (MAUG 2.0)" issued by the European Academy of Allergy and Clinical Immunology (EAACI), including their applications in clinical diagnosis, treatment, and management. This article aims to enhance healthcare professionals' understanding of milk and egg allergies, offering new perspectives and practical guidelines for research and clinical practice to promote accurate diagnosis and personalized treatment strategies.

Intelligent Classification and Segmentation of Sandstone Thin Section Image Using a Semi-Supervised Framework and GL-SLIC

This study presents the development and validation of a robust semi-supervised learning framework specifically designed for the automated segmentation and classification of sandstone thin section images from the Yanchang Formation in the Ordos Basin. Traditional geological image analysis methods encounter significant challenges due to the labor-intensive and error-prone nature of manual labeling, compounded by the diversity and complexity of rock thin sections. Our approach addresses these challenges by integrating the GL-SLIC algorithm, which combines Gabor filters and Local Binary Patterns for effective superpixel segmentation, laying the groundwork for advanced component identification. The primary innovation of this research is the semi-supervised learning model that utilizes a limited set of manually labeled samples to generate high-confidence pseudo labels, thereby significantly expanding the training dataset. This methodology effectively tackles the critical challenge of insufficient labeled data in geological image analysis, enhancing the model’s generalization capability from minimal initial input. Our framework improves segmentation accuracy by closely aligning superpixels with the intricate boundaries of mineral grains and pores. Additionally, it achieves substantial improvements in classification accuracy across various rock types, reaching up to 96.3% in testing scenarios. This semi-supervised approach represents a significant advancement in computational geology, providing a scalable and efficient solution for detailed petrographic analysis. It not only enhances the accuracy and efficiency of geological interpretations but also supports broader hydrocarbon exploration efforts.

Development of an integrated strategy for comprehensive characterization of Sinomenii Caulis extract and metabolites in rats based on UPLC/Q-TOF-MS

Sinomenii Caulis (SC), a commonly used traditional Chinese medicine for its therapeutic effects on rheumatoid arthritis, contains rich chemical components. At present, most studies mainly focus on sinomenine, with little research on other alkaloids. In this study, a comprehensive profile of compounds in SC extract, and biological samples of rats (including bile, urine, feces, and plasma) after oral administration of SC extract was conducted via ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS). The fragmentation patterns and potential biotransformation pathways of six main types of alkaloids in SC were summarized, and the corresponding characteristic product ions, relative ion intensity, and neutral losses were obtained to achieve rapid classification and identification of complex components of SC from in vitro to in vivo. As a result, a total of 114 alkaloid compounds were identified, including 12 benzyl alkaloids, 4 isoquinolone alkaloids, 32 aporphine alkaloids, 28 protoberberine alkaloids, 34 morphinan alkaloids and 4 organic amine alkaloids. After administration of SC extract to rats, a total of 324 prototypes and metabolites were identified from rat plasma, urine, feces and bile, including 81 aporphines, 95 protoberberines, 117 morphinans and 31 benzylisoquinolines. The main types of metabolites were demethylation, hydrogenation, dehydrogenation, aldehydation, oxidation, methylation, sulfate esterification, glucuronidation, glucose conjugation, glycine conjugation, acetylation, and dihydroxylation. In summary, this integrated strategy provides an additional approach for the incomplete identification caused by compound diversity and low abundance, laying the foundation for the discovery of new bioactive compounds of SC against rheumatoid arthritis.

RANCANG BANGUN SISTEM PENDINGIN UNTUK MESIN BUBUT BV 20

The purpose of this study is to design and create a cooling system on the BV 20 lathe. The method used in this study is the design method by conducting direct design manufacturing based on the condition of the BV 20 lathe and designs by calculating the total head pump and pumping heading. The manufacturing process is carried out starting from the identification of working drawings and identification of components using existing tools or machines, ordering and procuring the market for other components. Then it can be produced a cooling system for a BV 20 lathe with a 3 watt pump. Keyword designs, cooling system, lathe BV 20

Identification of landscape components for heat mitigation in Bahrain’s arid climate urban waterfront parks

Abstract Heat mitigation became a significant issue in urban spaces because of increased urban temperature due to urban heat phenomena in cities worldwide, particularly in regions with arid climates. This paper discusses the potential of landscape component configurations that mitigate heat in urban parks in arid climate regions. This paper explores the possibility of landscape components in arid climates to mitigate heat in the microthermal areas of urban parks. A case study area and systematic literature review methodology were applied to analyze combining landscape components to generate outdoor heat mitigation in arid climate regions. The study found that combinations of ground asphalt and solid building provide the lowest temperature compared to other configurations in Bahrain’s arid urban waterfront park, which might provide a solid shadow and supported by wind speeds.

In vivo identification of bioactive components of Poria cocos for adjusting mitochondria against metabolic dysfunction-associated fatty liver disease

Currently, no specific treatment exists to alleviate metabolic dysfunction-associated fatty liver (MAFLD). Previously, Poria cocos (PC) effectively relieved MAFLD, but its bioactive components are still unknown. The bioactive substances in PC that regulate mitochondria function to alleviate MAFLD were thus determined. The L02 hepatocyte model induced by fat emulsion and the MAFLD rat model induced by a high-fat diet (HFD) were developed to explore the efficacy of PC against MAFLD. The activity of PC-derived components in the liver mitochondria of HFD-fed rats was evaluated using the L02 hepatocyte model. Additionally, the PC-derived components from the liver mitochondria were identified by ultra-high performance liquid chromatography/mass spectrometry. Finally, the anti-steatosis ability of PC-derived monomers and monomers groups was evaluated using the adipocyte model. PC maintained the mitochondrial ultrastructure, alleviated mitochondrial oxidative stress, and regulated the energy metabolism and the fatty acid β oxidation to relieve lipid emulsion-induced cellular steatosis and HFD-induced MAFLD. PC-derived components entering the liver mitochondria inhibited oxidative stress injury and improved the energy metabolism to fight cellular steatosis. Additionally, 15 chemicals were identified in the PC-treated rat liver mitochondria. These identified chemical molecules and molecule groups in the mitochondria prevented cellular steatosis by regulating mitochondrial oxidative stress and energy metabolism. PC restores mitochondrial structure and function, alleviating MAFLD, which is related to oxidative stress, energy metabolism, and fatty acid β oxidation. The identified 15 components may be the main effective PC components regulating mitochondria function to alleviate MAFLD. Thus, PC may be a promising mitochondrial regulator to prevent MAFLD.

Confirmation that Monochamol is a Male Produced Aggregation-Sex Pheromone for Monochamus maculosus Haldeman (Coleoptera: Cerambycidae).

The recognition of cerambycids as frequent and damaging invaders led to an increase in the interest in the chemical ecology of the group with the identification of pheromones and pheromone-like attractants for well over 100 species. Pheromone components of the Cerambycidae are often phylogenetically conserved, with a single compound serving as a pheromone component for several related species. In the subfamily Lamiinae, the compound 2-(undecyloxy)ethanol (monochamol) has been identified as an aggregation-sex pheromone for several species of the genus Monochamus. In other species, including Monochamus maculosus Haldeman, field trials have demonstrated that monochamol is a pheromone attractant, but at that point it was still unknown as to whether it was a pheromone for this species. Here we report the identification, and laboratory and field trials of a pheromone component produced by adult male M. maculosus. Chemical analyses of headspace volatile collections sampled from field collected beetles of both sexes revealed the presence of one male-specific compound that was identified as 2-(undecyloxy)ethanol. Electroantennography analyses showed that monochamol elicited responses from the antennae of female beetles. Traps baited with monochamol in the field captured M. maculosus adults of both sexes corroborating the identification of monochamol as the sex-aggregation pheromone of this species. The attractivity of monochamol to adult M. maculosus in our field trapping experiment was synergized by the addition of the host volatile α-pinene.

Growth inhibition of P. aeruginosa by methanol extract of Bridelia stipularis and identification of active components using in silico studies

BackgroundAntimicrobial resistance among pathogens is an emerging problem, gaining significant importance recently. Pharmaceutical scientists are constantly exploring innovative and effective antibacterial agents. Pseudomonas aeruginosa (P. aeruginosa) is a bacterium primarily responsible for pneumonia and infections in the liver, kidneys, and other body parts. It is a Gram-negative bacterium that can be controlled by antibiotics such as ciprofloxacin and levofloxacin. However, this pathogen sometimes exhibits resistance to these antibacterial agents.MethodsRecognizing the well-known potential of plants as sources of medicinal compounds, our study focused on the ethyl acetate, acetone and methanol extract of the leaves of Bridelia stipularis and its impact on the growth of P. aeruginosa using well diffusion method. To gain insight into the composition of the extract, we conducted GC–MS analysis. After identifying the components present in the extract, we assessed the drug-likeness, absorption, distribution, metabolism, and excretion (ADME) and conducted docking studies of the molecules with the selected structural receptors of P. aeruginosa to find out the active component present in the extract.ResultsRemarkably, only methanol extract of Bridelia stipularis demonstrated significant antibacterial activity against this pathogen. In silico investigations revealed that two compounds, namely ethyl iso-allocholate and toluene sulfonylhydrazone derivative, exhibited high inhibition potencies. All structural receptors of the pathogen taken for this study were well inhibited by ethyl iso-allocholate while the receptors such as laconizing lipase and penicillin-binding protein of the bacterium were bound well with the 4-phenyl-3-penten-2-one p-toluene sulfonylhydrazone.ConclusionsObservations of this study clearly establish that the two phytochemicals present in the methanolic extract, i.e., ethyl iso-allocholate and toluene sulfonylhydrazone derivative of Bridelia stipularis leaves are highly active against the growth of the opportunistic pathogen P. aeruginosa.Graphical abstract

Subcutaneous coding via laser directed energy deposition (DED-LB) for unalterable component identification

Part identification has become a priority in manufacturing, especially when it comes to the additive manufacturing (AM) industry, where the counterfeit printing of almost any digitalized component is possible. As a means of avoiding forgery, the development of non-detectable labels, or digital passports is necessary. In the present work, a novel methodology for printing subcutaneous coding on aeronautical parts is proposed thanks to the multimaterial capabilities of the laser based directed energy deposition (DED-LB). The coding is based on embedding a dot pattern of a high-density alloy on a small area of a lower density component, which once covered and finished generates a pattern only visible by X-ray imagining. The viability of the proposed methodology is proven by embedding WC particles on a Ti6Al4V substrate. Firstly, the most relevant process parameters are optimized to ensure a sharp and a readable code, and their geometry is analysed by means of industrial Computed Tomography (CT). Also, the metallurgical quality and chemical composition of the generated dots is evaluated by Scanning Electron Microscope (SEM). Finally, a demonstrator part is fabricated with a hidden code. The code readability and the mechanical properties are tested to ensure the feasibility of the developed methodology.

Advances and Prospects in Liquid Biopsy Techniques for Malignant Tumor Diagnosis and Surveillance.

Liquid biopsy technology provides invaluable support for the early diagnosis of tumors and surveillance of disease course by detecting tumor-related biomarkers in bodily fluids. Currently, liquid biopsy techniques are mainly divided into two categories: biomarker and label-free. Biomarker liquid biopsy techniques utilize specific antibodies or probes to identify and isolate target cells, exosomes, or molecules, and these techniques are widely used in clinical practice. However, they have certain limitations including dependence on tumor markers, alterations in cell biological properties, and high cost. In contrast, label-free liquid biopsy techniques directly utilize physical or chemical properties of cells, exosomes, or molecules for detection and isolation. These techniques have the advantage of not needing labeling, not impacting downstream analysis, and low detection cost. However, most are still in the research stage and not yet mature. This review first discusses recent advances in liquid biopsy techniques for early tumor diagnosis and disease surveillance. Several current techniques are described in detail. These techniques exploit differences in biomarkers, size, density, deformability, electrical properties, and chemical composition in tumor components to achieve highly sensitive tumor component identification and separation. Finally, the current research progress is summarized and the future research directions of the field are discussed.

Analysis and Application of Fluid Components in High-Clay Matrix Shale Oil: A Case Study of Gulong Shale Oil

Fluid components in cores are crucial parameters in evaluating the quality of a shale reservoir in both laboratory analyses and log interpretation. In the Gulong area, shale reservoirs are characterized by a high clay content, with clay spaces hosting both oil and water phases, complicating the occurrence mechanism of fluid components, as a result, traditional research methods are no longer applicable. As an advanced technique, nuclear magnetic resonance (NMR) has been applied in oilfields to determine the specific petrophysical properties of rocks. To more accurately identify the types of fluid components, this study carried out a new, well-designed 2D NMR experiment, rock pyrolysis experiment, and quantitative oil and water detection experiment (QOWDE) to study the Gulong shale. This study measured the 2D NMR map of the original state, saturation state, centrifugal state, and pyrolysis at different temperatures, and conducted mutual verification between the QOWDE and 2D NMR pyrolysis experiments to obtain the distribution of different components of Gulong shale on the 2D NMR map. Based on the experimental results, this study developed a component identification template suitable for the Gulong area and calculated the 2D NMR porosity and saturation from it. This lays a foundation for the analysis and application of fluid components in the Gulong region and provides a new experimental basis and methodological support for porosity and saturation calculations.