Preliminary Classification Research Articles

Overlap of International League of Associations for Rheumatology and Preliminary Pediatric Rheumatology International Trials Organization Classification Criteria for Nonsystemic Juvenile Idiopathic Arthritis in an Established UK Multicentre Inception Cohort.

The goal was to assess the degree of overlap between existing International League of Associations for Rheumatology (ILAR) and preliminary Paediatric Rheumatology International Trials Organisation (PRINTO) classification criteria for juvenile idiopathic arthritis (JIA). Participants from the Childhood Arthritis Prospective Study, a multicenter UK JIA inception cohort, were classified using the PRINTO and ILAR classification criteria into distinct categories. Systemic JIA was excluded because several classification items were not collected in this cohort. Adaptations to PRINTO criteria were required to apply to a UK health care setting, including limiting the number of blood biomarker tests required. The overlap between categories under the two systems was determined, and any differences in characteristics between groups were described. A total of 1,223 children and young people with a physician's diagnosis of JIA were included. Using PRINTO criteria, the majority of the patients had "other JIA" (69.5%). There was a high degree of overlap (91%) between the PRINTO enthesitis/spondylitis- and ILAR enthesitis-related JIA categories. The PRINTO rheumatoid factor (RF)-positive category was composed of 48% ILAR RF-positive polyarthritis and 52% undifferentiated JIA. The early-onset antinuclear antibodies-positive PRINTO category was largely composed of ILAR oligoarthritis (50%), RF-negative polyarthritis (24%), and undifferentiated JIA (23%). A few patients were unclassified under PRINTO (n=3) and would previously have been classified as enthesitis-related JIA (n=1) and undifferentiated JIA (n=2) under ILAR. Under the preliminary PRINTO classification criteria for childhood arthritis, most children are not yet classified into a named category. These data can help support further delineation of the PRINTO criteria to ensure homogenous groups of children can be identified.

Resident space objects classification by machine learning techniques

In recent years the number of resident space objects in near-Earth space has been increasing drastically, which can lead to a “cascade collisions” effect and other catastrophic consequences. Therefore, it is crucial to monitor resident space objects, maintain and update catalogues on time, including the identification of unknown space objects to estimate their location and potential orbit. It is necessary to perform resident space object identification quickly and accurately to avoid possible satellite collisions resulting in large clouds of uncontrollable space debris fragments. That is why the task of resident space object preliminary classification by TLEs is stated and solved by applying machine learning approaches to achieve a higher classification quality and speed. This issue is a highly imbalanced classification problem, which narrows and specifies the used models. Applying the proposed resident space object classification model to space surveillance systems can decrease the time required for the object identification significantly.

SU-VPDN: A scene understanding method for vehicle part detection

High-accuracy positioning and identification of vehicle parts are crucial for status detection, fault diagnosis, and the development of intelligent damage detection systems. However, detecting left–right and front-rear categories in vehicle parts remains challenging due to numerous categories and feature similarity. To address this, we propose the scene understanding vehicle part detection network (SU-VPDN). It comprises three subnetworks: vehicle orientation scene classification (VOSC), vehicle part instance segmentation (VPIS), and scene understanding (SU). VOSC performs preliminary classification of vehicle orientation scenes, while VPIS detects vehicle parts. SU fine-tunes VOSC results using the part logic correction module, fuses VOSC and VPIS results using the part replacement module, and obtains accurate VPIS results through confidence regulation and hierarchical filtering. SU-VPDN integrates results from multiple subnetworks, transforming the challenge of detecting similar objects into orientation scene detection for precise recognition. We evaluate the proposed method on a dataset containing 59 types of vehicle parts and compare it with advanced segmentation detection models. Experimental results demonstrate that SU-VPDN outperforms other models, achieving a 12.2% and 12.3% improvement in mean average precision (mAP) for box and mask, respectively, compared to the baseline model. Moreover, qualitative and quantitative experiments show that SU-VPDN significantly enhances the detection performance of objects with similar features. Overall, our proposed SU-VPDN offers a promising solution for detecting left–right and front-rear categories in vehicle parts. It surpasses existing models and can enable insurance companies to replace damaged parts and improve claims efficiency efficiently.

Preliminary group classification and exact solutions of Smoluchowski equation with a source

Population balance equations are essential to scientists and engineers of widely varying discipline, applications have covered a wide range of processes involving bioreactors, catalytic reaction, and cell populations, but the lack of exact solutions necessitates the use of numerical methods. Group classification of Smoluchowski equation with a source is provided by use of the method of preliminary group classification. The determining equation is successfully solved by the method of developed Lie group analysis. All source functions, reduced equations, invariant solutions, explicit exact solutions and dynamic behavior analysis of solutions are presented in this paper.

Morphological Study of Active Galaxies based on SDSS Images. Preliminary Results

Activity in galaxies has mainly two major forms: Active Galactic Nuclei (AGN) and Starburst (SB). Moreover, different types of AGN have different morphology. However, this question has not yet been properly investigated and due to old low-quality images, the morphology of many galaxies is not well described. SDSS images give a good possibility to homogeneously classify galaxies and investigate differences by the activity types. The concentration of the central part and the ratio between the central bulge and the total flux is a subject for detailed study. We use SDSS images to classify different types of active galaxies (both AGN and Starburst) and understand differences between QSOs, Seyferts 1 and 2, LINERS and Composites, as well as Starburst galaxies. The best expectation from our study will be the preliminary classification of active galaxies into activity types based on the images and before having their spectral types.

Evaluating ClinGen variant curation expert panels' application of PVS1 code

BackgroundThe 2015 American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) guidelines articulates that the effects of certain types of variants on gene function can often be seen as a complete absence of the gene product by leading to a lack of transcription or nonsense-mediated decay(NMD). However, detailed information considering different types of loss of function(LOF) variants, refined steps assimilating details concerning location of variant, changes in strength levels, NMD boundary, or any additional information pointing to a true null effect, were all left to expert judgement. As part of its Clinical Genome Resource (ClinGen) initiative, Variant Curation Expert Panels (VCEPs) are designated to make gene/disease-centric specifications in accordance with the ACMG/AMP guidelines, including a more detailed definition of what constitutes an appropriate LOF evidence. Our goal was to evaluate the current LOF guidelines developed by the VCEPs and analyse the prior curated variants concerning the PVS1 criteria, bringing people occupied in genetic data analysis a comprehensive understanding of this code. MethodsOur study evaluated 7 VCEPs for their LOF criteria (PVS1). Subsequently, we assessed the predictive criteria by considering the underlying disease mechanism, protein transcript, and variant types delineated. Then, we meticulously curated the LOF evidence referenced by each VCEP in their preliminary variant classification, thereby scrutinizing the recommendations put forth by VCEPs and their application in the interpretation of the aforementioned predictive criteria. Based on these, an extensive curation of evidence summary considering PVS1 applied by VCEPs according to their classification of pilot variants for the purpose of analyzing VCEP criteria specifications and their use in the understanding of LOF was conducted. ResultsWe observed in this article that the VCEPs discussed followed the majority of Sequence Variant Interpretation (SVI) recommendations concerning the application of this LOF criteria, except for some disease/gene specific considerations. We highlighted the wide range of PVS1 strength levels approved by VCEP, reflecting the diversity of evidence for each variants type. In addition, we observed substantial differences in the approach used to determine relative strengths for different types of null variants and in the attitude towards these principles concerning variant location, NMD and influence to protein function between VCEPs. ConclusionsIt is difficult to understand the intricacies of the predictive data(PVS1), which often requires expert-level knowledge of disease/gene. The VCEP criteria specifications for the predictive evidence play an important role in making it more accessible for the curators to apply the predictive data by providing details concerning this complex criteria. Despite this, we believe there is a need for more guidance on standardizing this process and ensuring consistency in the application of this predictive evidence.

Safety assessment of pedestrian-vehicle interaction at signalized intersections: An observational study

Road safety is a crucial aspect of global policies and management. Surrogate Safety Measures (SSMs) have gained attention in the study of pedestrian safety. This study aims to establish an effective SSM methodology to analyze driver-pedestrian interactions. The analysis relies on SSM indicators, without the need for an initial classification of driver-pedestrian interactions into specific interaction patterns. The proposed methodology offers several advantages, including the accurate identification of conflicts through an affordable approach making it easily accessible for public administrations and authorities to assess pedestrian safety at road intersections. A dataset comprising 270 driver-pedestrian interactions, observed at three road intersections in Rome, Italy, was examined. The severity level of each event was assessed through a preliminary classification of each interaction into three patterns: high, low, and none. Subsequently, the severity levels were evaluated using three methods, employing Time-to-Collision (TTC), Post-Encroachment Time (PET), and a combination of TTC and PET. A comparison between the severity levels identified by the two approaches was conducted. The findings reveal that Method 2, utilizing PET, consistently identifies conflicts. Additionally, a binomial logistic regression analysis was performed to identify the variables that influence the likelihood of an interaction escalating into a conflict. The results demonstrate that the probability of conflict increases with the duration of a red signal, particularly for younger pedestrians.

Two-Stage Hyperspectral Image Classification Using Few Labeled Samples

Hyperspectral image classification (HIC) has attracted considerable attention in the last two decades, and significant progress has been made. However, the small sample size problem of HIC is still challenging. This letter presents a two-stage HIC approach that achieves high classification accuracies with few labeled samples. For a given hyperspectral image, the spatial features are first extracted by local binary patterns (LBP). Spatial features and spectral features for each pixel are then stacked into feature vectors. These vectors are fed into SVM to finish the first classification stage. Based on the preliminary classification results, a superpixel segmentation method is introduced for selecting some superpixels which include training samples and all test pixels assigned to some class. These selected superpixels with their labels obtained by SVM are then added to training samples. According to the enlarged training sample set, Random Multi-Graph (RMG) is finally utilized to classify the remaining samples. Experimental results on three benchmark HSI datasets demonstrate that the proposed LBP and RMG-based two-stage method (LBP-RMG2) significantly outperforms several state-of-the-art algorithms with a few labeled samples.

Implicit temporality from the perspective of relevance theory

The article presents an attempt to apply the basic principles of Dan Sperber and Deidre Wilson’s Relevance theory to the study of implicit means of time reference. The theory combines both cognitive and pragmatic features, which makes it suitable for online analysis of the natural communicative process including the possible mistakes in the cognitive mechanism of inference. The article contains an overview of the main aspects of Relevance theory exemplified by contexts with implicit temporality. The preliminary classification of implicit means of temporal location of an action, which includes lexical, grammatical and contextual implicit means, is also provided. The article also provides analysis of the addressee’s perception of implicit time information in accordance with its relevance. The article also dwells on the problem of how a person decides that an utterance is of informative and cognitive value (that is relevant) and hence must be processed. Besides, the author looks into the factors that affect the relevance of an utterance (for instance its broad communicative context, by which we understand both communicants’ background knowledge about the language, the situation of communication and the world) and cites situations in which informative relevance decreases resulting in mistakes in information processing and the addressor’s informative and communicative failures. The author also attempts to demonstrate the prospects of further integration of the conceptual framework of Relevance theory and other cognitive and pragmatic linguistic theories, the theory of presuppositions and mental spaces in particular. Besides, the author looks into the terminological inexactitude of such notions as ‘implicature’ (implication) and ‘explicature’ and also suggests considering the application of weak implicatures to the analysis of inferential mistakes.

Geographic Information Systems as a Tool of Modern Age Archeology in Western Siberia

Geographic Information Systems (GIS) can be applied to archeological sites that belong to the epoch of Russian exploration of Western Siberia. GIS make it possible to collect, accumulate, and visualize archeological data. Although the method has gained a lot of popularity in the recent decades, Russian GIS-archeology has poor theoretical foundations. This article summarizes experience, problems, and prospects of using GIS at Modern Age archeological sites in Western Siberia. It starts with a comprehensive historiographic analysis of the domestic experience in various regions of Russia. The author introduces a preliminary classification of GIS-technologies. The analysis proved that GIS are acknowledged practical tools that make it possible to accumulate available theoretical data about archeological sites. Some regions have more prospects for GIS-archeology than others. A number of issues will have to be solved to develop the domestic GIS-archeology. For instance, attributive markers, conventional designations, and map bases should be unified. Moreover, archeologists often experience problems with access to data and experience obtained by their colleagues. Finally, there are very few specialized archeological GIS on Modern Age sites. In addition, Russian archeology will definitely benefit from AI-technologies.

Taxonomic Analysis of Asteroids with Artificial Neural Networks

We study the surface composition of asteroids with visible and/or infrared spectroscopy. For example, asteroid taxonomy is based on the spectral features or multiple color indices in visible and near-infrared wavelengths. The composition of asteroids gives key information to understand their origin and evolution. However, we lack compositional information for faint asteroids due to the limits of ground-based observational instruments. In the near future, the Chinese Space Survey Telescope (CSST) will provide multiple colors and spectroscopic data for asteroids of apparent magnitude brighter than 25 and 23 mag, respectively. With the aim of analyzing the CSST spectroscopic data, we applied an algorithm using artificial neural networks (ANNs) to establish a preliminary classification model for asteroid taxonomy according to the design of the survey module of CSST. Using the SMASS II spectra and the Bus–Binzel taxonomic system, our ANN classification tool composed of five individual ANNs is constructed, and the accuracy of this classification system is higher than 92%. As the first application of our ANN tool, 64 spectra of 42 asteroids obtained by us in 2006 and 2007 with the 2.16 m telescope in the Xinglong station (Observatory Code 327) of National Astronomical Observatory of China are analyzed. The predicted labels of these spectra using our ANN tool are found to be reasonable when compared to their known taxonomic labels. Considering its accuracy and stability, our ANN tool can be applied to analyze CSST asteroid spectra in the future.

A Preliminary Study on the Effectiveness of K-Nearest Neighbor Algorithm Based on Local Mean for Classification of Bioinformatics Data.

The preliminary classification of biological class data is of great importance for bioinformatics. One can quickly classify object data by comparing their existing features with known traits. k-nearest neighbor algorithm is easy to apply in this field, but its drawbacks make it less meaningful to improve the efficiency of the algorithm by simply changing the distance model, so this study uses a local mean-based k-nearest neighbor classifier and compares the accuracy of the predicted classification of six different distance models used. The prediction accuracies in the experimental results were all greater than 70%, and the highest accuracy was achieved in different data sets for all distance models with K=2; the prediction accuracy of Minkowski distance with different parameters had the highest volatility in the test.and the experimental results can be used as a reference for related practitioners.

Wing morphometry of worker bees of Kharkiv, Sumy and Poltava regions of Ukraine

The affiliation of local bee populations spread across the territory of Ukraine to the subspecies A. m. carnica, A. m. macedonica, A. m. mellifera, and A. m. caucasica has been studied previously in most cases using various phenotypic characteristics, and in some cases, through the study of mitochondrial DNA. According to previous morphometric studies, it was not possible to identify bee families that could be qualified as "purebred". The aim of this study was to investigate three apiaries from different regions of Ukraine where selection measures are systematically carried out to reproduce and preserve the local population of Ukrainian steppe bees, subspecies A. m. macedonica. The goal was to confirm this breeding positioning and find bee families suitable for further breeding work. The study focused on the wing phenotypes of worker bees. In this work, 10 traits were considered as wing phenotypes: seven indices Ci, Dbi, Disc.sh, Ri, Ci.2, Ci.3, Ci.2.1, and three angles A4, E9, J10. Statistical data processing methods and the STATISTICA software package were used as research tools. A total of 5200 wings of worker bees from 53 apiaries in the Kharkiv, Sumy, and Poltava regions were studied. The classification of wings in the Sumy and Poltava regions was carried out into four clusters, while in Kharkiv, it was into three clusters. Preliminary classification based on Euclidean distances using the mean values of traits for individual wing clusters and taking into account the Mahalanobis distances between cluster centroids formed three data arrays labeled as "UkrStep" and "UkrStep.2," which were attributed to the subspecies A. m. macedonica, and "Carnica," attributed to the subspecies A. m. carnica. These can be used as regional standards for studying bee families in this part of Ukraine with the aim of establishing their probable breed. It was found that the population of Ukrainian steppe bees (62.2%) predominates by phenotype on the studied apiaries. For four bee families from the Kuzemin apiary, 92%-100% of worker bees belong to Ukrainian steppe bees. АOn the apiary in Kharkiv, only one bee family had 86% of worker bees belonging to the population of Ukrainian steppe bees. It is recommended to use queens from four bee families for breeding purposes: one queen from the Kharkiv apiary and three queens from the Kuzemin apiary. Key words: Classical morphometry of worker bee wings, discriminant analysis.

Classification of long-distance trails into nature-based tourism niches:

Hiking tourism has intensified in Brazil in recent years. Among the evidence of this process is the creation, in 2018, of the Brazilian Network of Long-Distance Trails (RBT), which brings together trails that require at least one overnight stay to complete their route. Considering the country's potential in this field and the rapid growth of this tourist offer, the research sought to develop and test a methodology to classify these trails according to niches in the nature tourism segment. To this end, it collected data from RBT websites and social media and from the Long-Distance Trails (LDT) of Rio Grande do Sul, as well as applied online questionnaires with managers to identify evidence that would make it possible to associate these trails with certain niches of nature tourism. As a result, it obtained a preliminary classification of the Long-Distance Trails of Rio Grande do Sul in relation to the niches of the nature tourism segment, as well as identified important aspects to be considered for the construction of methodologies with the same purpose.

A fluvial record of late Quaternary climate changes and tectonic uplift along the Marche Piedmont Zone of the Apennines: New insights from the Tesino River (Italy)

Fluvial terraces are a pre-eminent continental record of climate changes and tectonics. Although the use of fill terraces for incision rate derivation is complicated due to their cyclical nature relative to strath terraces, they remain a relatively complete record of incision and deposition, thus allowing one to derive interpretations about both tectonics and climate. The Adriatic piedmont of the Apennines (central Italy) offers a well-preserved staircase of such terraces, caused by the cyclical alternation of fluvial aggradation and incision over the Middle and Late Pleistocene in response to a combination of low-rate tectonic uplift and climate changes. Although the staircase has been already widely described with examples from several valleys of the Adriatic Piedmont, its geochronological constraints are limited and must be enhanced to extract reliable climatic and tectonic signals from terrace deposits—especially for the older terrace levels.This research provides new Optically Stimulated Luminescence (OSL) data on the terrace chronology in combination with new semi-automatically extracted data on the altimetric and along-valley terrace distributions, as well as the sedimentological characteristics of fill terraces within the Tesino River basin in the Marche piedmont zone of the Apennines. The semi-automatic extraction of the terrace tread allowed a preliminary level classification as a function of the terrace height above the modern channel thalweg. The results demonstrate that, within the slowly uplifting Adriatic piedmont of the Apennines, the main phases of fluvial aggradation occurred during cold and full-glacial conditions followed by river incision and floodplain-channel abandonment during warmer periods. This finding confirms previous results from the last fluvial aggradation-incision cycle (Late Pleistocene). The results also show that the same formation mechanism is valid for the older (Middle Pleistocene) terraces. Indeed, this study provides new geochronological constraints for the regional-scale paradigm of cyclical formation and development of Quaternary fill terrace staircases along this sector of the Apennines. The use of a dated fill terrace staircase allowed estimation of a Middle Pleistocene long-term bedrock incision rate ranging from 0.3 to 0.5 mm yr−1 in agreement with previous studies in the central-northern sector of the Adriatic Apennines. The resulting uplift rate supports the presence of differently uplifted blocks due to the fragmentation of the peri-Adriatic region caused by the activity of left-lateral faults.

Teori-Teori Simbolisme Seni Bina Darihal Masjid Tradisional: Satu Pengelasan Awal

The productive scholarship on the architectural symbolism of the traditional mosque expounded by the Traditionalist School at the end of the second millennium, which continued well into the third millennium by scholars exhibiting a strong Traditionalist influence or otherwise, is a testament to the subject’s importance to the development of Islāmic architecture. Despite its prolificity and agency, most studies on the subject remain theoretically arbitrary, if not deficient, rudimentary at best, and disjointed. To fill this theoretical gap, this article, for the first time, identifies, outlines and synthesises the many disparate theories of the architectural symbolism of the traditional mosque to establish a preliminary classification. It employs a hermeneutic reading of 32 significant theoretical and empirical studies on the architectural symbolism of the traditional mosque sourced from books, journals, conference proceedings, and periodicals available to the authors. By capitalising on the textual and comparative analyses, it is found that as many as 28 distinct theories of the architectural symbolism of the traditional mosque with their attendant symbolic dimensions and parameters were posited in all 32 studies, all of which can be consolidated into three broad theoretical frameworks. These findings present an original systematisation of theories of the architectural symbolism of the traditional mosque, which is instrumental in two ways: it encourages scholars to develop existing theories or establish new ones, and it assists Muslims in recognising and acknowledging the spiritual agency of their built forms while offering foreign readers another expansive and inspiring lens to view them.

Experimental Challenges and Modelling Approaches of Floating Wind Turbines

This paper reviews experimental methods for testing floating wind turbines. The techniques covered include early-stage and up-to-date approaches such as a porous disc method and hybrid model testing. First, the challenges induced by Froude and Reynolds similitudes and the importance of the various aerodynamic phenomena are discussed. The experimental methods are evaluated based on their cost, versatility, requirements, and limitations. The work primarily focuses on representing aerodynamic loads via hybrid and physical rotor testing, and a preliminary classification is proposed to facilitate the selection of the approaches. The work does not aim to identify an optimal method, but it provides insights into each method’s distinctive features, serving as a roadmap for selecting the most appropriate methodology based on the specific testing goals and level of accuracy. Overall, this study offers a comprehensive resource for testing the coupled hydrodynamic and aerodynamic performance of floating wind turbines. The conclusions offer guidance for selecting an appropriate methodology based on the desired testing outcome.

Революционный процесс в 2022 г.

The year 2022 turned out to be not only very rich in various important, and in some cases, fateful events, but also fully confirmed the idea of the authors of the article about the third revolutionary wave of the 21st century currently underway (since 2018), as well as its causes. This article provides a brief overview of various forms of revolutionary and quasi-revolutionary destabilization in fourteen countries of the world in 2022. Information is provided on the causes, motives, actors and outcomes of the identified episodes in chronological order, as well as a preliminary classification of the nature of the episodes in question.

Software System for Automatic Grading of Paper Tests

The advent of digital technology has revolutionized numerous aspects of modern life, including the field of assessment and testing. However, paper tests, despite their seemingly archaic nature, continue to hold a prominent position in various assessment domains. The accessibility, familiarity, security, cost-effectiveness, and versatility of paper tests collectively contribute to their continued prominence. Hence, numerous educational institutions responsible for conducting examinations involving a substantial number of candidates continue to rely on paper tests. Consequently, there arises a demand for the possibility of automated assessment of these tests, aiming to alleviate the burden on teaching staff, enhance objectivity in evaluation, and expedite the delivery of test results. Therefore, diverse software systems have been developed, showcasing the capability to automatically score specific question types. Thus, it becomes imperative to categorize related question types systematically, thereby facilitating a preliminary classification based on the content and format of the questions. This classification serves the purpose of enabling effective comparison among existing software solutions. In this research paper, we present the implementation of such a software system using artificial intelligence techniques, progressively expanding its capabilities to evaluate increasingly complex question types, with the ultimate objective of achieving a comprehensive evaluation of all question types encountered in paper-based tests. The system detailed above demonstrated a recognition success rate of 99.89% on a curated dataset consisting of 734,825 multiple-choice answers. For the matching type, it achieved a recognition success rate of 99.91% on 86,450 answers. In the case of short answer type, the system achieved a recognition success rate of 95.40% on 129,675 answers.

Single-Factor Comprehensive Reservoir Quality Classification Evaluation-Taking the Hala'alat Mountains at the Northwestern Margin of the Junggar Basin as an Example.

In the process of petroleum geology exploration and development, reservoir quality evaluation is an essential component. However, conventional reservoir quality evaluation methods are no longer able to provide accurate and comprehensive assessments for all types of reservoirs. Therefore, the comprehensive evaluation of reservoir quality using multiple single factors is of significant importance in improving the level of reservoir quality assessment and enhancing the effectiveness of oil and gas exploration techniques. Conventional reservoir quality evaluation methods can assess only the quality of individual reservoir properties, resulting in limited classification outcomes. Taking the Cretaceous formations in the southern margin of the Hala'alat Mountain in the Junggar Basin as the research object, preliminary classification criteria were established based on the principles of formation coefficient, storage coefficient, and flow unit index. Combining experimental data such as core observation, thin-section identification, pore permeability analysis, and scanning electron microscopy, a comprehensive set of reservoir quality classification and evaluation criteria were developed. Furthermore, the corresponding reservoir classification evaluation maps were generated to illustrate the spatial distribution of reservoir quality. The study reveals that the area can be classified into four types of reservoirs, namely, Class I, Class II, Class III, and Class IV, corresponding to the best reservoir, relatively good reservoir, relatively poor reservoir, and poor reservoir, respectively. Among them, the second (K1q2) and third (K1q3) members of the Cretaceous Qingshuihe Formation, as well as the first (K1h1) and third (K1h3) members of the Cretaceous Hutubi Formation, exhibit the best reservoir quality as Class II. On the other hand, the second member of the Cretaceous Hutubi Formation (K1h2) exhibits the best reservoir quality as Class III, with relatively poorer reservoir quality overall. The research findings of this study can provide an important theoretical basis for oil and gas exploration and development in the region.