Theoretical Foundation For Research Research Articles

Identification and validation of ferroptosis-related biomarkers and the related pathogenesis in precancerous lesions of gastric cancer

Using advanced bioinformatics techniques, we conducted an analysis of ferroptosis-related genes (FRGs) in precancerous lesions of gastric cancer (PLGC). We also investigated their connection to immune cell infiltration and diagnostic value, ultimately identifying new molecular targets that could be used for PLGC patient treatment. The Gene Expression Omnibus (GEO) and FerrDb V2 databases were used to identify FRGs. These genes were analysed via ClueGO pathways and Gene Ontology (GO) enrichment analysis, as well as single-cell dataset GSE134520 analysis. A machine learning model was applied to identify hub genes associated with ferroptosis in PLGC patients. Receiver Operating Characteristics (ROC) curve analysis was conducted to verify the diagnostic efficacy of these genes, and a PLGC diagnosis model nomogram was established based on hub genes. R software was utilized to conduct functional, pathway, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) on the identified diagnostic genes. Hub gene expression levels and survival times in gastric cancer were analysed using online databases to determine the prognostic value of these genes. MCPcounter and single-sample gene set enrichment analysis (ssGSEA) algorithms were used to investigate the correlation between hub genes and immune cells. Finally, noncoding RNA regulatory mechanisms and transcription factor regulatory networks for hub genes were mapped using multiple databases. Eventually, we identified 23 ferroptosis-related genes in PLGC. Enrichment analyses showed that ferroptosis-related genes were closely associated with iron uptake and transport and ferroptosis in the development of PLGC. After differential analysis using machine learning algorithms, we identified four hub genes in PLGC patients, including MYB, CYB5R1, LIFR and DPP4. Consequently, we established a ferroptosis diagnosis model nomogram. GSVA and GSEA mutual verification analysis helped uncover potential regulatory mechanisms of hub genes. MCPcounter and ssGSEA analysed immune infiltration in the disease and indicated that B cells and parainflammation played an important role in disease progression. Finally, we constructed noncoding RNA regulatory networks and transcription factor regulatory networks. Our study identified ferroptosis-related diagnostic genes and therapeutic targets for PLGC, providing novel insights and a theoretical foundation for research into the molecular mechanisms, clinical diagnosis, and treatment of this disease.

Study on the Glider Soaring Strategy in Random Location Thermal Updraft via Reinforcement Learning

Soaring birds can use thermal updrafts in natural environments to fly for long periods or distances. The flight strategy of soaring birds can be implemented to gliders to increase their flight time. Currently, studies on soaring flight strategies focus on the turbulent nature of updrafts while neglecting the random characteristics of its generation and disappearance. In addition, most flight strategies only focus on utilizing updrafts while neglecting how to explore it. Therefore, in this paper, a complete flight strategy that seeks and uses random location thermal updrafts is mainly emphasized and developed. Moreover, through the derivation of flight dynamics and related formulas, the principle of gliders acquiring energy from thermal updrafts is explained through energy concepts. This concept lays a theoretical foundation for research on soaring flight strategies. Furthermore, the method of reinforcement learning is adopted, and a perception strategy suitable for gliders that considers the vertical ground speed, vertical ground speed change rate, heading angle, and heading angle change as the main perception factors is developed. Meanwhile, an area exploring strategy was trained by reinforcement learning, and the two strategies were combined into a complete flight strategy that seeks and uses updrafts. Finally, based on the guidance of the soaring strategy, the flight of the glider in the simulation environment is tested. The soaring strategy is verified to significantly improve the flight time lengths of gliders.

Research on dissipative structure of China's green building industry system based on Brusselator model

With the introduction of the “Double Carbon” initiative, the urgency to develop green buildings in China has become paramount. The green building industry aims to reduce energy consumption and carbon emissions while fostering its rapid growth. However, several challenges still hinder the industry's progress. Therefore, this study employs dissipative structure theory to examine whether the green building industry can transform from a disordered state to an ordered state by continuously exchanging material, energy, and information with the external environment. By establishing the industry structure, 13 internal indicators and 10 external indicators are identified through a comprehensive literature review. The Brusselator model and entropy method are applied to calculate the system entropy using questionnaire data. The results indicate a positive entropy value (A) of 0.67823, while the negentropy value (B) is −1.438553. Clearly, the relationship between positive entropy and negentropy does not meet the critical condition B>A2+1, which validates that the current green building industry in China is not a dissipative structure. This finding signifies that the industry faces challenges in achieving sustainable and stable development. Consequently, based on these calculations, five effective strategies are proposed to facilitate the transformation of the green building industry into a dissipative structure and promote its sustainable and healthy development. The research findings serve as a valuable reference for the Chinese government in formulating laws and regulations pertaining to the green building industry, thereby facilitating its comprehensive and effective management and aiding the achievement of energy conservation and emission reduction goals in the construction sector. This study contributes to expanding the application of dissipative structure theory in the green building industry and enriches the theoretical foundations of research on the industry from the perspective of complex systems.

Fashion marketing in the metaverse

ABSTRACT The metaverse is a shared virtual environment with significant implications for several aspects of businesses. This conceptual paper focuses on how fashion brands can benefit from the metaverse’s vast opportunities. Reviewing the key publications in this field, it identifies the key stakeholders who shape fashion marketing in the metaverse: fashion brands, tech developers, and consumers. Furthermore, the paper outlines the opportunities and challenges of fashion marketing in the metaverse. The study presents a conceptual framework that shows the collaborative relationships between critical stakeholders involved in fashion marketing to take such opportunities and overcome potential challenges. The framework provides a theoretical foundation for research and practice in fashion marketing within the metaverse. The study contributes to the expanding body of research on the intersection of the metaverse and fashion marketing, offering valuable managerial insights for fashion brands and tech developers and a rich agenda for future research.

Changes in sulfur in soybean rhizosphere soil and the response of microbial flora in a continuous cropping system mediated by Funneliformis mosseae.

Soybean is an S-loving crop, and continuous cropping might cause soil sulfur shortage. The primary objectives of this study are to determine whether Funneliformis mosseae (F. mosseae) can enhance the content of available S in S-deficient soil and thereby improve the sulfur utilization rate in soybean. The experiment used Heinong 48 (HN48), a soybean variety with a vast planting area in Heilongjiang Province, and F. mosseae was inoculated in the soil of soybean that had been continuously cropped for 0 and 3 years. The results of the barium sulfur turbidimetric assay show that the sulfur content in the soil and soybean was reduced by continuous cropping and increased by inoculation with F. mosseae; the results of the macro-genome sequencing technology, show that the diversity and abundance of bacteria in the soil was decreased by continuous cropping and increased by inoculation with F. mosseae. The sulfur-oxidizing bacteria (SOB) activity and sulfur-related gene expression levels were lower in the continuous crop group compared to the control group and higher in the F.mosseae-inoculated group compared to the control group. Continuous cropping reduced the sulfur content and ratio of soybean rhizosphere soil, affecting soil flora activity and thus soybean growth; F. mosseae inoculation increased the sulfur content of soybean root-perimeter soil and plants, increased the diversity and abundance of rhizosphere soil microorganisms, increased the expression of genes for sulfur transport systems, sulfur metabolism, and other metabolic functions related to elemental sulfur, and increased the species abundance and metabolic vigor of most SOB. In summary, continuous cropping inhibits soil sulfur uptake and utilization in soybean while the inoculation with F. mosseae can significantly improve this situation. This study offers a theoretical research foundation for using AMF as a bio-fungal agent to enhance soil sulfur use. It also supports the decrease of chemical fertilizers, their substitution, and the protection of native soil.

Ultrafast fabrication of deep eutectic solvent flexible ionic gel with high-transmittance, freeze-resistant and conductivity by frontal polymerization

As a common flexible sensing device, gels are widely used in electronic skin, personalized health monitoring, and smart manufacturing. However, gel suffers from temperature sensitivity, long polymerization times or thickness limitations. Deep eutectic solvents (DESs) have abundant hydrogen bond networks and low saturated vapor pressure, which can accelerate the frontal polymerization of ionic gels, and overcome the temperature sensitivity problem. Here, we showed how choline chloride (ChCl)-glycerol (Gly) DES can be used to create ionic gels with different properties and functions by combining them with different monomers (acrylamide (AM), acrylic acid (AA) and itaconic acid (IA)). Subsequently, we revealed the rapid gelation mechanism of PAM-ChCl-Gly ionic gel from multiple perspectives by density functional theory and molecular dynamics simulation, which was then applied to flexible sensing. The experimental results showed that the PAM-ChCl-Gly ionic gel had excellent tensile properties, high transparency, self-adhesion and stability. In addition, its gelation time was only 90 s without heating. ChCl-Gly DES offered a plentiful and stable hydrogen bonding network. PAM-ChCl-Gly ionic gels can detect tiny pressure and strain changes, making them suitable for flexible sensing. This greatly enriched the theoretical research foundation of DES-based ionic gels and broadened their application areas.

A comparative study of Chinese women 3 × 3 basketball players exercise load in Tokyo Olympic preparation cycle.

Objective: The aim of this study was to compare the variances in-game loads exhibited by Chinese women's 3 × 3 basketball team across different stages of the preparation cycle for the Tokyo Olympic Games, and to summarize the fundamental regulations governing Chinese women's 3 × 3 basketball training and games, in order to establish a theoretical research foundation for the team's new preparation cycle. Methods: This study measured load-related data during the preparation and main competition periods of the 2019-2021 Tokyo Olympics, from April to August 2019 and from April to June 2021. The aim was to compare the changes and differences in a load of competition during different stages and to explore patterns of load changes during the preparation period. This study used wearable devices authorized by FIFA and NBA, along with the Catapult GPS performance monitoring system from Australia (Catapult&Polar Team) as instruments for collecting sports load data. The OptimEye S5 device was worn around the athlete's neck to collect data prior to the game, while the Open Field™ system was utilized for data editing and report generation post-game. Results: Compared to the primary competition load during the 2019 preparation period, the 2021 preparation period exhibited significant increases and decreases (p < 0.05) in competition load, high-intensity load, the number of explosive moves, the number of high-intensity acceleration, several changes to the left and right, and the number of explosive jumps. During the 2021 preparation period, the mean heart rate, mean heart rate percentage, and mean speed of the race demonstrated significant decreases in comparison to the race during the 2019 preparation period (p < 0.05). Throughout the training period spanning from 2019 to 2021, no significant differences were observed in running distance and maximum speed (p > 0.05). Conclusion: The findings of this study reveal that the national training team has fostered positive adaptive changes in athletes, resulting in a significant enhancement in both load and sports performance science data during competition from 2019 to 2021.

Porcine reproductive and respiratory syndrome virus regulates lipid droplet accumulation in lipid metabolic pathways to promote viral replication

Porcine reproductive and respiratory syndrome (PRRS) is a severe respiratory disease caused by porcine reproductive and respiratory syndrome virus (PRRSV) that can lead to the abortion of pregnant sows and decreased boar semen quality. However, the mechanisms of PRRSV replication in the host have not yet been fully elucidated. As lipid metabolism and lipid droplets (LDs) have been reported to play important roles in the replication of various viruses, we aimed to explore the mechanisms through which LDs affect PRRSV replication. Laser confocal and transmission electron microscopy revealed that PRRSV infection promoted intracellular LD accumulation, which was significantly reduced by treatment with the NF-κB signaling pathway inhibitors BAY11–7082 and metformin hydrochloride (MH). In addition, treatment with a DGAT1 inhibitor significantly reduced the protein expression of Phosphorylated NF-ΚB P65and PIκB and the transcription of IL-1β and IL-8 in the NF-κB signaling pathway. Furthermore, we showed that the reduction of the NF-κB signaling pathway and LDs significantly reduced PRRSV replication. Together, the findings of this study suggest a novel mechanism through which PRRSV regulates the NF-κB signaling pathway to increase LD accumulation and promote viral replication. Moreover, we demonstrated that both BAY11–7082 and MH can reduce PRRSV replication by reducing the NF-κB signaling pathway and LD accumulation. This study lays a theoretical foundation for research on the mechanism of PRRS prevention and control, as well as the research and development of antiviral drugs.

Conceptual and Theoretical Foundations of Research on Social and Cultural Processes in the Environment of the Titular Nation of the Ukrainian SSR during the 1960s and 1970s

The article considers the сonceptual and theoretical foundations of research on social and cultural processes in the environment of the titular nation of the Ukrainian SSR during the 1960s and 1970s. It is characterized by the semantic content of concepts of “titular nation” and “indigenous people” in the Ukrainian SSR, identified primarily with Ukrainians, who were united by a single language, faith, spirituality, national traditions, customs, culture, ethnic origin and ancient residence on the territory of Ukraine, the official name of which was determined by their nationality. The conceptual components of the research are interpretation of the following concepts of: “Ukrainian ethnos”, “Ukrainian ethnic territory” or “Ukrainian ethnic land”, “national majority”, “national minority”, “nation-state”, “nonconformism”, “counterculture”, “sixties”, “dissidence”, “Ukrainian diaspora”, etc.&#x0D; Research of the conceptual and theoretical foundations of the outlined topic makes it possible to resolve controversial issues which have not been adequately covered in historical science, also makes it possible to specify the process of national self-expression of Ukrainians through cultural space, and allows to get new assessments, judgments and conclusions.

Animal models of the placenta accreta spectrum: current status and further perspectives.

Placenta accreta spectrum disorder (PAS) is a kind of disease of placentation defined as abnormal trophoblast invasion of part or all of the placenta into the myometrium, even penetrating the uterus. Decidual deficiency, abnormal vascular remodeling in the maternal-fetal interface, and excessive invasion by extravillous trophoblast (EVT) cells contribute to its onset. However, the mechanisms and signaling pathways underlying such phenotypes are not fully understood, partly due to the lack of suitable experimental animal models. Appropriate animal models will facilitate the comprehensive and systematic elucidation of the pathogenesis of PAS. Due to the remarkably similar functional placental villous units and hemochorial placentation to humans, the current animal models of PAS are based on mice. There are various mouse models induced by uterine surgery to simulate different phenotypes of PAS, such as excessive invasion of EVT or immune disturbance at the maternal-fetal interface, which could define the pathological mechanism of PAS from the perspective of the "soil." Additionally, genetically modified mouse models could be used to study PAS, which is helpful to exploring the pathogenesis of PAS from the perspectives of both "soil" and "seed," respectively. This review details early placental development in mice, with a focus on the approaches of PAS modeling. Additionally, the strengths, limitations and the applicability of each strategy and further perspectives are summarized to provide the theoretical foundation for researchers to select appropriate animal models for various research purposes. This will help better determine the pathogenesis of PAS and even promote possible therapy.

Exploring the influence mechanism of water grinding on the gel properties of corn starch based on changes in its structure and properties.

At present, most studies have focused on the preparation of modified starches by dry grinding. As an excellent starch plasticizer, water might enhance the action of grinding on the structure of starch granules, and water grinding might improve the gel properties of starch. Therefore, this article explored the influence mechanism of water grinding on the gel properties of corn starch based on the changes in its structure and properties. The results showed that water grinding could make water enter the starch granules and hydrate the starch molecules, and the starch gelatinized after water grinding for 20 min. Thus, water enhanced the action of grinding on the structure of the starch granules. Under the plasticization and grinding action of water grinding, the mechanochemical effect of the starch granules occurred. When the starch was in the aggregation stage (7.5-10 min), the crystallinity of the starch increased, and the starch molecules rearranged into a more stable structure, which increased apparent viscosity (η), elastic modulus (G') and viscous modulus (G″) of the starch gels. Therefore, appropriate water grinding (10 min) contributed to increasing the viscoelasticity of starch gels. This study provided a theoretical foundation for research on improving the properties of starch by mechanical modification in future. © 2023 Society of Chemical Industry.

Problems of Artificial Personality (Artificial Intelligence) Control

Today, a number of researchers representing both technical knowledge and the humanities believe that it is necessary to endow Artificial Intelligence with subjective “human” qualities, which include the ability to self-aware, as well as to make a free choice. In this regard, the problem of the AI autonomy becomes extremely relevant, and further – AI creator’s rights and capabilities (or ineligibility) to hold control over AI. Within this framework the Artificial Personality project has been developing over the past 20 years. Given its active scientific and social activities with the involvement of the remarkable interdisciplinary community, the project is far from complete. The presented article summarizes the executed research for Artificial Personality conceptualization and demonstrates that today the fundamental possibility of the creation of Artificial Personality has not yet been convincingly proven. Also, conceptually, there has not been formulated the single generally accepted approach to promising methods and technology for the implementation and the embodiment of the Artificial Personality. So, at the current stage, the study of the Artificial Personality is rather abstract theoretical research. As a result of the study, the authors come to the conclusion that today it is reasonable to use the results of the Natural Personality and Natural Intelligence studies and transfer the methods that have shown their relative effectiveness in various existing manifestations of real social life to the field of creating the concept of Artificial Personality. The proposed approach for the conceptualization of Artificial Personality will help to create a theoretical and methodological foundation for theoretical research and further implementation of Artificial Personality projects.

Investment Value Analysis and Regulatory Trends in China's Medical Cosmetology Industry

With the rapid rise of the Internet celebrity economy and the live broadcasting industry, medical beauty has become a hot spot sought after by consumers and operators with its advantages of low risk and fast start-up. However, considering that China's medical beauty industry started late compared with other developed countries, both the social foundation and the theoretical research foundation are relatively weak to cultivate the medical cosmetology industry to become a truly valuable investment track, we must analyze and study. Given the recent rise of the medical beauty industry in the capital market, many investors and consumers lack understanding and analysis of the medical beauty industry. This paper first analyzes the development status and trend of the medical cosmetology industry from the perspective of investment. Analyze the investment value of several listed companies in the medical beauty industry from a macro and micro perspective. Second, analyze the current problems in the beauty industry and regulatory measures.

Characterization and Functional Analysis of OcomOBP7 in Ophraella communa Lesage

The olfactory system plays a key role in various insect behaviors, and odorant-binding proteins participate in the first step of the olfactory process. Ophraella communa Lesage is an oligophagous phytophagous insect that is a specific biological control agent for Ambrosia artemisiifolia L. The leaf beetle must identify and locate A. artemisiifolia through olfaction; however, its odorant-binding protein (OBP) function has not yet been reported. In this study, OcomOBP7 was cloned, and its tissue expression profile and binding ability were analyzed using RT-qPCR and fluorescence binding assays, respectively. Sequence analysis demonstrated that OcomOBP7 belongs to the classical OBP family. The RT-qPCR results showed that OcomOBP7 was specifically expressed in the antennae, indicating that OcomOBP7 may be involved in chemical communication. The fluorescence binding assay showed that OcomOBP7 has an extensive binding ability to alkenes. The electroantennography experiments showed that O. communa antennal response to α-pinene and ocimene decreased significantly after interference because the two odors specifically bound to OcomOBP7. In summary, α-pinene and ocimene are odorant ligands corresponding to OcomOBP7, indicating that OcomOBP7 is involved in the chemical recognition of A. artemisiifolia. Our study lays a theoretical foundation for research into O. communa attractants, which is helpful for the better biological control of A. artemisiifolia by O. communa.

SLAF marker based QTL mapping of fruit-related traits reveals a major-effect candidate locus ff2.1 for flesh firmness in melon

Flesh firmness (FF) is an important and complex trait for melon breeders and consumers. However, the genetic mechanism underlying FF is unclear. Here, a soft fruit melon (P5) and a hard fruit melon (P10) were crossed to generate F2, and the FF and fruit-related traits were recorded for two years. By performing quantitative trait locus (QTL) specific-locus amplified fragment (SLAF) (QTL-SLAF) sequencing and molecular marker-linkage analysis, 112 844 SLAF markers were identified, and 5 919 SNPs were used to construct a genetic linkage map with a total genetic distance of 1 356.49 cM. Ten FF- and fruit-related QTLs were identified. Consistent QTLs were detected for fruit length (FL) and fruit diameter (FD) in both years, and QTLs for single fruit weight (SFW) were detected on two separate chromosomes in both years. For FF, the consistent major locus (ff2.1) was located in a 0.17-Mb candidate region on chromosome 2. Using 429 F2 individuals derived from a cross between P5 and P10, we refined the ff2.1 locus to a 28.3-kb region harboring three functional genes. These results provide not only a new candidate QTL for melon FF breeding but also a theoretical foundation for research on the mechanism underlying melon gene function.

Research on resource analysis method based on attribute similarity and position weight for conceptual design

Resource analysis is one of the important methods and tools to solve inventive problems in TRIZ. Effective use of resources is the key to form product functional principle innovations and generate technical solutions. In view of the problems that the conceptual design process requires too much experience of designers and is not systematic, the conceptual design is combined with resource analysis method in this paper. Considering the influence of attribute similarity and position weight between components in technical system, an innovative resource analysis method is proposed to accurately exploit available resources in system and super-system to assist the process of conceptual design. The abstract process of resource exploiting in conventional resource analysis methods can be transformed into a specific process of calculating resource similarity by this method. It has the advantages of high computability, strong standardisation and systematisation. The method can not only effectively improve the efficiency and quality of conceptual design, but also lay a theoretical research foundation for the development of computer aided innovation (CAI) software in the future.

Investigation of suddenly expanded flows at subsonic Mach numbers using an artificial neural networks approach.

The purpose of this study is to explore two concepts: first, the use of artificial neural networks (ANN) to forecast the base pressure (β) and wall pressure (ω) originating from a suddenly expanded flow field at subsonic Mach numbers. Second, the implementation of Garson approach to determine the critical operating parameters affecting the suddenly expanded subsonic flow process in the subsonic range. In a MATLAB environment, a network model was constructed based on a multilayer perceptron with an input, hidden, and output layer. The network input parameters were the Mach number (M), nozzle pressure ratio (η), area ratio (α), length to diameter ratio (γ), micro jet control (ϵ), and duct location to length ratio (δ). The network output included two variables; base pressure (β) and wall pressure (ω). The ANN was trained and tested using the experimental data. The experimental results found that micro-jet controls were successful in increasing the base pressure for low Mach numbers and high nozzle pressure ratios. It was also found that the wall pressure was same for with and without micro jet control. The ANN predicted values agreed well with the experimental values, with average relative errors of less than 5.02% for base pressure and 6.71% for wall pressure. Additionally, with a relative significance of 32% and 43%, the nozzle pressure ratio and duct location to length ratio had the highest influence on the base pressure and wall pressure, respectively. The results demonstrate that the ANN model is capable of accurately predicting the pressure results, enabling theoretical foundation for research into pressure distribution in aerodynamic systems.

Reducing embodied carbon in concrete materials: A state-of-the-art review

The construction sector is responsible for about 40% of energy-related emissions worldwide. Utilizing low-carbon concrete materials (LCCMs) has been recognized as an efficient way to reduce embodied carbon (EC). However, there is a lack of systematic understanding and a unified comparison of the LCCMs’ EC reduction potentials. This paper identifies publications related to LCCMs and conducts a content analysis in three dialectical dimensions. Identified LCCMs were categorized into four divisions. The results show that the most prospective LCCMs are low-carbon cementitious binders, achieving 52.6% EC reductions. The results also demonstrate the significance of comparing the EC reduction potentials of different LCCMs at a unified level, as up to 11% inconsistency was identified when switching between cement & concrete level and components & building level. It provides a theoretical foundation for researchers and practitioners to examine possible LCCMs. The findings reveal new directions for achieving a more reliable cross-case comparison among the EC reduction potentials of different LCCMs.

Comparative Transcriptome Analysis on the Regulatory Mechanism of Thoracic Ganglia in Eriocheir sinensis at Post-Molt and Inter-Molt Stages.

Eriocheir sinensis is an aquatic species found distributed worldwide. It is found in the Yangtze River of China, where the commercial fishing of this valuable catadromous aquatic species has been banned. As an important member of the phylum Arthropoda, E. sinensis grows by molting over its whole lifespan. The central nervous system of Eriocheir sinensis plays an important regulatory role in molting growth. Nevertheless, there are no reports on the regulatory mechanisms of the nervous system in E. sinensis during the molting cycle. In this study, a comparative transcriptome analysis of E. sinensis thoracic ganglia at post-molt and inter-molt stages was carried out for the first time to reveal the key regulatory pathways and functional genes operating at the post-molt stage. The results indicate that pathways and regulatory genes related to carapace development, tissue regeneration, glycolysis and lipolysis and immune and anti-stress responses were significantly differentially expressed at the post-molt stage. The results of this study lay a theoretical foundation for research on the regulatory network of the E. sinensis nervous system during the post-molt developmental period. Detailed knowledge of the regulatory network involved in E. sinensis molting can be used as a basis for breeding improved E. sinensis species, recovery of the wild E. sinensis population and prosperous development of the E. sinensis artificial breeding industry.

Artificial Intelligence Technology in Basketball Training Action Recognition.

The primary research purpose lies in studying the intelligent detection of movements in basketball training through artificial intelligence (AI) technology. Primarily, the theory of somatosensory gesture recognition is analyzed, which lays a theoretical foundation for research. Then, the collected signal is denoised and normalized to ensure that the obtained signal data will not be distorted. Finally, the four algorithms, decision tree (DT), naive Bayes (NB), support vector machine (SVM), and artificial neural network (ANN), are used to detect the data of athletes' different limb movements and recall. The accuracy of the data is compared and analyzed. Experiments show that the back propagation (BP) ANN algorithm has the best action recognition effect among the four algorithms. In basketball training athletes' upper limb movement detection, the average accuracy rate is close to 93.3%, and the average recall is also immediate to 93.3%. In basketball training athletes' lower limb movement detection, the average accuracy rate is close to 99.4%, and the average recall is immediate to 99.4%. In the detection of movements of upper and lower limbs: the recognition method can efficiently recognize the basketball actions of catching, passing, dribbling, and shooting, the recognition rate is over 95%, and the average accuracy of the four training actions of catching, passing, dribbling, and shooting is close to 98.95%. The intelligent basketball training system studied will help basketball coaches grasp the skilled movements of athletes better to make more efficient training programs and help athletes improve their skill level.