bluuebunny/crossref_metadata_2025 huggingface dataset:
Ocean Modeling Analysis and Modeling Based on Deep Learning
Authors: Niu Ming Hui , Cho Joung Hyung
Published: July 2022

The ocean comprises an uninterrupted body of salt water confined within a vast basin on the earth’s surface. The ocean is the largest ecosystem on earth with rich and diverse biological resources. Organisms that reside in salty water are referred to as “marine life.” Plants, animals, and microorganisms including archaea and bacteria are examples of these. The existence of marine life is not only a biological resource but also an economic source. Toys and other industries that imitate marine life have emerged in the market. A different modeling design of marine life has improved with the passage of time and the concept of modeling aesthetics has been incorporated. The identification of marine life images is challenging due to the complexity of the maritime environment, and there are several flaws in marine life models. The rise of deep learning has brought some new ideas for the weaknesses in marine life modeling, and the advantages of convolutional neural networks have contributed to some of the concepts based on deep learning. This research analyses marine modeling by using the benefits of convolutional neural networks, so that people can better understand marine life modeling. The experimental results indicate that the proposed approach has achieved good results in marine life detection, and the modeling effect of ocean modeling analysis based on deep learning is good.
Academic Procrastination Behavior among Public University Students
Authors: Fentaw Yared , Moges Bekalu Tadesse , Ismail Sayed M.
Published: July 2022

Academic procrastination among university students is a common problem. The authors examined the prevalence, reasons, areas, and effects of academic procrastination in selected higher education institutions in the Amhara Region, Ethiopia. We also examined whether academic procrastination varied with respect to the institutional category and gender of the student. 323 students sampled from three universities, using a stratified sampling technique, completed the questionnaire. In a concurrent mixed-methods study, both qualitative and quantitative data are integrated starting from data collection through conclusion. The results indicate that nearly 80 percent of the students are procrastinators to varying degrees, of which half always procrastinate due to poor time management skills, lack of planning for academic activities, laziness, and stress. The results also showed that procrastination happens irrespective of gender and institutional realities and results in not only academic failure but also affects student affective and emotional behavior. Finally, it is suggested that students are expected to improve their time management practices to minimize negative effects of the delay. It is also suggested that universities shall include such activities in their student support systems as counseling and training on specific areas that students procrastinate most.
The Effect of Interval Training on the Displacement Speed of Male Good Boxers
Authors: Hou Yun , Bu Xiangui
Published: July 2022

The change of boxing competition rules has put forward higher requirements on the speed quality of male boxers. To investigate the effect of interval training on the displacement speed of male outstanding boxers and to provide a theoretical basis for targeted improvement of speed quality of male boxers. A 4‐week interval training intervention was conducted on 20 male boxing athletes through literature method, interview method, and experimental method. The subjects in the experimental group had higher test results than the control group test data after the experiment, and the test results of the experimental group reached a highly significant difference before and after the experiment, and the test results of the control group before and after the experiment were improved but not significantly different. The effect of interval training was more effective than traditional physical training in improving the displacement speed of male good boxers, which significantly improved the displacement speed of the subjects.
[Retracted] Prevention of Venous Thrombosis of Lower Limbs after Cesarean Section Based on Smart Medical Air Pressure Therapy Instrument
Authors: Yin Yuanyuan , Xiao Xiang , Peng Lingyun
Published: July 2022

Affected by the environment, the incidence of lower extremity venous thrombosis after cesarean section is gradually increasing, and postoperative nursing is becoming more and more important. The intelligent medical air pressure therapy instrument is a common and effective postpartum nursing method. This paper studies the role of pneumatic therapeutic apparatus in the prevention of lower extremity venous thrombosis after cesarean section in smart medicine, describes its importance in nursing, and analyzes the role of pneumatic therapeutic apparatus and smart medicine combined with the postoperative nursing situation of patients with cesarean section in our hospital. In this paper, we aggregate the description text of six levels of hospital intelligent service grading evaluation. In order to show the characteristics of each level and the requirements of each level of hospital intelligent service, we can roughly see the differences between different levels. Research shows that with the construction of medical information platform, more and more medical processes rely on hospital information system, which promotes the integration of medical platform and the interconnection of medical equipment, provides convenient services for patients, and provides patients with easier access to services. At the same time, the massive data generated by appointment, nursing, treatment, and other activities will be recorded, and the pneumatic therapeutic instrument can avoid the occurrence of 60% lower extremity venous thrombosis. The data of air pressure therapeutic instrument is dynamic, and its performance is mainly reflected in the recording of dynamic index data.
COVID-19 and Pulmonary Tuberculosis Coinfection in a Moroccan Patient with Pulmonary Embolism: A Case Report and Literature Review
Authors: Zouaki Imane , Chahbi Zakaria , Raiteb Mohamed , Zyani Mohamed
Published: July 2022

Emerging cases of coinfection of coronavirus disease 2019 (COVID-19) and tuberculosis (TB), although rare, have attracted the attention of health systems around the world and have arisen many concerns about the diagnosis, treatment, and prognosis of this coinfection especially in high TB burden countries. Here, we report a rare case and, to the best of our knowledge, the first reported case in Morocco of simultaneous diagnosis of an active pulmonary TB infection and a COVID-19 pneumonia. We present a case of a sixty-seven-year-old male patient who was admitted to our COVID-19 emergency department with a diagnosis of COVID-19 pneumonia, confirmed by nasopharyngeal swab’s polymerase chain reaction (PCR) for detection of SARS-CoV-2. The atypical radiological findings suggested a TB coinfection which was later confirmed by sputum cultures and Xpert MTB/Rif assay. The patient also presented some complications including thrombosis of the left leg, pulmonary embolism and inaugural ketosis. Treatment was administered as per local protocols: broad spectrum antibiotics, corticosteroids, fixed dose-combination of antituberculosis treatment along with hydration and insulin therapy for ketosis treatment and anticoagulation. The patient was discharged after twenty-three days of hospitalization. Due to the currently limited data, further studies are necessary to establish any possible correlation between COVID-19 infection and the progression of a latent and/or the severity of an active TB infection.
Survival Improvement in Patients with Renal Cell Carcinoma and Disparities between Different Sexes, Races, and Socioeconomic Status: 1977–2016
Authors: Ouyang Dijun , Sun Huanhuan , Chen Nan , Yan Yan , Ma Haiqing , Xia Jianchuan
Published: July 2022

Objective. Rare research of renal cell carcinoma (RCC) has been made in a comprehensive and full description based on a long period of time as yet. This study was aimed at investigating the incidence and relative survival rates (RSRs) of RCC in the past forty years and to disclose the impact of sex, race, and socioeconomic status (SES) on RCC. Methods. The data as variables, including age, gender, race, and SES, were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. SES was divided into three levels: low poverty, medium poverty, and high poverty. The medium- and high-poverty groups were integrated into one group in all analyses. The RSRs were calculated using period analysis methodology. Summary statistics including incidence and RSRs were analyzed by Kaplan–Meier and Cox proportional hazards models with GraphPad Prism 8.0.1 software and Stata 12.0 software. Results. A total of 77,513 patients diagnosed with RCC were enrolled in this study, showing an increased incidence and 10-year RSRs from 1977 to 2016. Patients older than 60 years had the highest incidence and the lowest RSRs. This research also showed significant disparities between different groups: incidence in males, blacks, and medium-high poverty groups was higher than that in females, whites, and low poverty groups, while RSRs were lower. For sex groups, the disparity of RSRs was obvious among patients who were 30–59 years old, but not among those younger than 29 years or older than 60 years. Based on SES, the survival gaps between different SES groups were getting wider over the past forty years. Conclusion. This study showed how age, sex, race, and SES affected the incidence and RSRs of RCC, which may be beneficial for both better designed clinical trials and efficient prevention methods.
Analysis of Human Capital Social Network Model Based on Industry Distribution
Authors: Li Yifan , Tang Xiao , Du Mingyu
Published: July 2022

As the most critical resource to promote the continuous growth of economic volume, human resources are indispensable to the development of the industry. With the development of market economy and the improvement of people’s pursuit of quality of life, the time of talent flow is increasing, which forms the social network of human capital. As a new stock, human capital social network can have an impact on individual thoughts or behaviors. This paper with a recruitment website workers repeatedly changes employment resume as the research object and uses literature research and empirical analysis based on human capital social network model analysis for the industry distribution of employment analysis and discussion. The results show that the IT internet industry in labor cross-industry network has high resource control and information advantage and has large correlation with other industries; traditional industry is limited; construction, leasing, and business services, electricity, heat, coal, and water flow frequency are the lowest; and the network structure is more stable.
Robust Detection Model of Vascular Landmarks for Retinal Image Registration: A Two‐Stage Convolutional Neural Network
Authors: Kim Ga Young , Kim Jae Yong , Lee Sang Hyeok , Kim Sung Min
Published: July 2022

Registration is useful for image processing in computer vision. It can be applied to retinal images and provide support for ophthalmologists in tracking disease progression and monitoring therapeutic responses. This study proposed a robust detection model of vascular landmarks to improve the performance of retinal image registration. The proposed model consists of a two‐stage convolutional neural network, in which one segments the retinal vessels on a pair of images, and the other detects junction points from the vessel segmentation image. Information obtained from the model was utilized for the registration. The keypoints were extracted based on the acquired vascular landmark points, and the orientation features were calculated as descriptors. Then, the reference and sensed images were registered by matching keypoints using a homography matrix and random sample consensus algorithm. The proposed method was evaluated on five databases and seven evaluation metrics to verify both clinical effectiveness and robustness. The results established that the proposed method showed outstanding performance for registration compared with other state‐of‐the‐art methods. In particular, the high and significantly improved registration results were identified on FIRE database with area under the curve (AUC) of 0.988, 0.511, and 0.803 in S, P, and A classes. Furthermore, the proposed method worked well on poor quality and multimodal datasets demonstrating an ability to achieve high AUC above 0.8.
Analysis of Public Big Data Management under Text Analysis
Authors: Zhu Yue , Kan Ho Yin
Published: July 2022

Based on text analysis, public big data management is studied. The public data management of Mount Wutai tourism network travel notes is discussed. The positive, neutral, and negative effects of the naive Bayesian classification model and decision tree classification model on the tourism sentiment attitude of Mount Wutai are compared. The relationship between tourism resources, tourism facilities, tourism services, tourism environment, and tourism sentiment and attitude of Wutai Mountain is analyzed. The results show that the true positive rate, true negative rate, and F-measure of the Bayesian decision tree classifier to classify positive text are 86.64%, 81.27%, and 84.62%, respectively. The true positive rate for neutral text is 82.05%, the true negative rate is 78.89%, and the F-measure is 77.11%. The true positive rate for negative text is 83.67%, the true negative rate is 98.29%, and the F-measure is 82.83%. The Bayesian decision tree classifier can evaluate positive and negative texts better than neutral texts. The true positive rate of the C4.5 decision tree classifier for positive text is 91.44%, the true negative rate is 86.57%, and the F-measure is 89.45%. The true positive rate for neutral text is 90.17%, the true negative rate is 83.28%, and the F-measure is 84.06%. The true positive rate for negative text is 91.84%, the true negative rate is 99.05%, and the F-measure is 90.91%. The decision tree classifier has a better evaluation effect on positive and negative texts than on neutral texts. The ROC curve of the evaluation effect of the two classifiers shows that the evaluation effect of the two classifiers has a better evaluation effect on positive text than that of the neutral and negative texts, and the evaluation effect of the C4.5 decision tree classifier is better than that of the Bayesian classifier. The promotion degree of tourism resources and facilities in forwarding online travel notes is obviously higher, and there is a high correlation between tourism resources and facilities and forward online travel notes. In negative online travel notes, the promotion degree of tourism service and tourism environment is high, and the correlation between tourism service and tourism environment and negative online travel notes is high. In summary, improving the quality of tourism services and the tourism environment of Mount Wutai scenic spots can better enhance the recognition and satisfaction of tourists with Mount Wutai tourism.
Comprehensive Analysis of Genomic and Expression Data Identified Potential Markers for Predicting Prognosis and Immune Response in CRC
Authors: He Yongshan , Dai Xuan , Chen Yuanyuan , Huang Shiyong
Published: July 2022

Colorectal cancer (CRC) is the most prevalent type of malignant tumor of the gastrointestinal tract. In the current study, we characterized the landscape of genomic alterations in CRC patients. Based on the results of whole-exome sequencing (WES), we identified 31 significantly mutated genes. Among them, several genes including TP53, KRAS, APC, PI3KCA, and BRAF were reported as significantly mutated genes in previous studies. In the current study, the most frequently mutated gene was TP53, which encodes tumor suppressor p53, affecting approximately 60% of CRC patients. In addition, we performed the expression profiles of significantly mutated genes between the normal group and tumor groups and identified 20 differentially expressed genes (DEGs); among them, CSMD3, DCHS2, LRP2, RYR2, and ZFHX4 were significantly negatively correlated with PFS. Moreover, consensus clustering analysis for CRC based on the expression of significantly somatic mutated genes was performed. In total, three subtypes of CRC were identified in CRC, including cluster1 (n = 453), cluster2 (n = 158), and cluster 3 (n = 9), based on expression level of significantly somatic mutated genes. Clinicopathological features analysis showed subtype C1 had the longest progression-free survival (PFS) with median time of 8.2 years, while subtypes C2 and C3 had 4.1 and 2.7 years of PFS, respectively. Moreover, we found three subtypes related to tumor infiltration depth, lymph node metastasis, and distant metastasis. Immune infiltration analysis showed the tumor infiltration levels of B cell native, T cell CD8+, T cell CD4+ memory activated, T cell gamma delta, NK cell resting, macrophage M0, macrophage M2, myeloid dendritic cell activated, mast cell activated, and mast cell resting significantly changed among the three groups, demonstrating the three subgroups classified by 22 somatically significantly mutated genes had a high capacity to differentiate patients with different immune statuses, which is helpful for the prediction of immunotherapy response of CRC patients. Our findings could provide novel potential predictive indicators for CRC prognosis and therapy targets for CRC immunotherapy.
An Effective Approach of Vehicle Detection Using Deep Learning
Authors: Chen Yidan , Li Zhenjin
Published: July 2022

With the rise of unmanned driving and intelligent transportation research, great progress has been made in vehicle detection technology. The purpose of this paper is employing the method of deep learning to study the vehicle detection algorithm, in which primary-stage target detection algorithms, namely, YOLOv3 algorithm and SSD algorithm, are adopted. Therefore, the method first processes the image data in the open-source road vehicle dataset for training. Then, the vehicle detection model is trained by using YOLOv3 and SSD algorithms to show the detection effect, respectively. The result is by comparing the detection effects of the two models on vehicles. The researchers accomplished the result analysis and summarized the characteristics of various models obtained by training, to apply to target tracking, semantic segmentation, and unmanned driving.
Engineering Disaster Investigation and Recurrence of the Covering Effect in a Petroleum and Gas Station in Seasonally Frozen Soil Region
Authors: Liu Xiaohui , Zhang Ruiling , Zhang Huyuan , Wu Kai , Zhou Weibin , Liang Bo , Li Guang
Published: July 2022

The impermeable engineering surface layer in the cold regions blocks the water and heat exchange between the foundation soil and the atmospheric environment. Especially in cold areas with significant temperature differences, the moisture in the foundation soil accumulates at the bottom of the structure layer to form a covering effect. This will exacerbate the occurrence of engineering freeze-thaw diseases. This paper conducts a disease survey of the Guanshan oil and gas station site, which is located in a seasonally frozen soil zone. The ponding and freeze-thaw diseases under the concrete cover are analyzed. The formation process of the pot covering effect in the lower part of the concrete surface layer was reproduced through indoor tests. In addition, a water-vapor-heat coupling model of unsaturated soil was established, which quantitatively produced the formation process of silty clay covering under the concrete slab. The results show that (1) in-situ monitoring demonstrated that the water content of the roadbed soil from 0 to 50 cm below the concrete slab gathered significantly, with the water content increasing by 5 to 30%. (2) Under the action of the indoor time-varying covering effect, the moisture content of silty clay will increase with the number of freezing-thawing cycles, with a maximum migration amount of 6%. (3) Seasonal temperature changes lead to the accumulation of water in the subgrade surface, and the maximum accumulation amount is 32%. (4) During the freezing period, the liquid water and vapor water in the subgrade migrate to the surface layer of the subgrade. As a result, the moisture content of the subgrade surface layer increases, while the melting period is the opposite. The above research results can provide theoretical support and scientific countermeasures for engineering design and disease control in cold regions.
Health Effects of Probiotics on Nonalcoholic Fatty Liver in the Life Cycle Based on Data Analysis
Authors: Wang Jia , Hao Yanfei , Jin Xiao , Li Xiaoyue , Liu Yi , Zhang Li , Wang Jing , Hu Mingxin
Published: July 2022

Objective. To observe the effect of intestinal probiotics in the treatment of nonalcoholic fatty liver disease (NAFLD) and the effect on liver function and inflammatory factors. Methods. 34 healthy rats were selected for the study and divided into 10 rats in the control group, 12 rats in the model group, and 12 rats in the treatment group according to the random number table method. The control group was given behavioral and lifestyle interventions, and the treatment group was given Bifidobacterium minus Black enteric capsules 5 g/(kg-d) by strong feeding method on the basis of the control group. The fatty liver index (FLI), liver ultrasound examination results, liver function, and inflammatory factor levels were compared among the three groups. After 8 weeks of treatment, there were statistically significant differences between the FLI values and liver ultrasound results of the three groups, and the serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), triacylglycerol (TG), and total cholesterol (TC) levels of the observation group were lower than those of the control group and the model group. The levels of serum high molecular weight lipocalin (HMW-APN) and interleukin 22 (IL-22) in the observation group were higher than those in the control group, and the levels of tumor necrosis factor-α (TNF-α) were lower than those in the control and model groups, and the differences were statistically significant (

P
<
0.05

). Conclusion. Intestinal probiotics can improve the clinical efficacy of patients with NAFLD, improve liver function, and alleviate the inflammatory response, in order to provide a theoretical basis for the clinical treatment of patients with NAFLD.
Confirming Multiplex RT-qPCR Use in COVID-19 with Next-Generation Sequencing: Strategies for Epidemiological Advantage
Authors: Carpenter Rob E. , Tamrakar Vaibhav , Chahar Harendra , Vine Tyler , Sharma Rahul
Published: July 2022

Rapid identification and tracking of emerging SARS-CoV-2 variants are critical for understanding the transmission dynamics and developing strategies for interrupting the transmission chain. Next-Generation Sequencing (NGS) is an exceptional tool for whole-genome analysis and deciphering new mutations. The technique has been instrumental in identifying the variants of concern (VOC) and tracking this pandemic. However, NGS is complex and expensive for large-scale adoption, and epidemiological monitoring with NGS alone could be unattainable in limited-resource settings. In this study, we explored the application of RT-qPCR-based detection of the variant identified by NGS. We analyzed a total of 78 deidentified samples that screened positive for SARS-CoV-2 from two timeframes, August 2020 and July 2021. All 78 samples were classified into WHO lineages by whole-genome sequencing and then compared with two commercially available RT-qPCR assays for spike protein mutation(s). The data showed good concordance between RT-qPCR and NGS analysis for specific SARS-CoV-2 lineages and characteristic mutations. RT-qPCR assays are quick and cost-effective and thus can be implemented in synergy with NGS for screening NGS-identified mutations of SARS-CoV-2 for clinical and epidemiological interest. Strategic use of NGS and RT-qPCR can offer several COVID-19 epidemiological advantages.
[Retracted] Sport Resource Classification Algorithm for Health Promotion Based on Cloud Computing: Rhythmic Gymnastics’ Example
Authors: Zhang Tairan , Han Qing , Zhang Zhenji
Published: July 2022

In the processing of rhythmic gymnastics resources, there are inefficiency problems such as confusion of teaching resources and lack of individuation. To improve the health access to teaching resource data, such as videos and documents, this study proposes a cloud computing‐based personalized rhythmic gymnastics teaching resource classification algorithm for health promotion. First, personalized rhythmic gymnastics teaching resource database is designed based on cloud computing technology, and the teaching resources in the database are preprocessed to obtain a meta‐sample set. Then, the characteristics of teaching resources are selected by the information acquisition method, and a vector space model is established to calculate the similarity of teaching resources. Finally, the distance‐weighted k‐NN method is used to classify the teaching resources for health promotion. The experimental results show that the classification accuracy of the proposed algorithm is high, the recall rate is high, and the F‐measure value is high, which verifies the effectiveness of the algorithm.
A Review on Recent Advances of Cerebral Palsy
Authors: Paul Sudip , Nahar Anjuman , Bhagawati Mrinalini , Kunwar Ajaya Jang
Published: July 2022

This narrative review summarizes the latest advances in cerebral palsy and identifies where more research is required. Several studies on cerebral palsy were analyzed to generate a general idea of the prevalence of, risk factors associated with, and classification of cerebral palsy (CP). Different classification systems used for the classification of CP on a functional basis were also analyzed. Diagnosis systems used along with the prevention techniques were discussed. State-of-the-art treatment strategies for CP were also analyzed. Statistical distribution was performed based on the selected studies. Prevalence was found to be 2-3/1000 lives; the factors that can be correlated are gestational age and birth weight. The risk factors identified were preconception, prenatal, perinatal, and postnatal categories. According to the evidence, CP is classified into spastic (80%), dyskinetic (15%), and ataxic (5%) forms. Diagnosis approaches were based on clinical investigation and neurological examinations that include magnetic resonance imaging (MRI), biomarkers, and cranial ultrasound. The treatment procedures found were medical and surgical interventions, physiotherapy, occupational therapy, umbilical milking, nanomedicine, and stem cell therapy. Technological advancements in CP were also discussed. CP is the most common neuromotor disability with a prevalence of 2-3/1000 lives. The highest contributing risk factor is prematurity and being underweight. Several preventions and diagnostic techniques like MRI and ultrasound were being used. Treatment like cord blood treatment nanomedicine and stem cell therapy needs to be investigated further in the future to apply in clinical practice. Future studies are indicated in the context of technological advancements among cerebral palsy children.
The Role Model of Inclusive Finance in Regional Economic Development Based on Carbon Neutrality Theory
Authors: Yu Zeyi
Published: July 2022

The most significant global challenge is global climate change; carbon emission reduction and carbon neutralization are the last way to solve global climate change. Achieving carbon neutrality will significantly impact the global economy and the national economy. The “dual carbon goals” proposed by China will also substantially impact the global economy and regional economic development. Focusing on regional economic development, achieving carbon neutrality is not only an opportunity for regional economic development but also a challenge. To achieve the goal of carbon neutrality, there must be institutional innovation and management innovation, which will provide new opportunities for balanced development among regions. With the development of inclusive finance, financial services for many disadvantaged groups and small and medium-sized enterprises have been further developed, thereby promoting economic development. With the development of Internet finance, big data, cloud computing, and other technologies, the development of inclusive finance, etc., the concept has also emerged. However, due to the short time of digital financial inclusion, the imperfect regulatory system, and the low degree of public participation, it is worth investigating whether the development of digital financial inclusion has a catalytic effect on the improvement of economic growth. Using the data of 31 provinces to build a panel regression model, this paper studies the market development, the development degree of digital financial inclusion, and the impact of digital financial inclusion on the relationship between factor markets and product markets and regions from the perspective of factor markets and product markets.
Research on the Evaluation of Moral Education Effectiveness and Student Behavior in Universities under the Environment of Big Data
Authors: Zhu Rui
Published: July 2022

Traditional moral evaluation relies on artificial and subjective evaluation by teachers, and there are subjective errors or prejudices. To achieve further objective evaluation, students’ classroom performance can be identified, and the effectiveness of moral education can be evaluated based on student behavior. Since student classroom behavior is random and uncertain, in order to accurately evaluate its indicators, a large amount of student classroom behavior data must be used as the basis for analysis, while certain techniques are used to filter out valuable information from it. In this paper, an improved graph convolutional network algorithm is proposed to study students’ behaviors in order to further improve the accuracy of moral education evaluation in universities. The technique of video recognition is used to achieve student behavior recognition, thus helping to improve the quality of moral education evaluation in colleges and universities. First, the multi-information flow data related to nodes and skeletons are fused to improve the computing speed by reducing the number of network parameters. Second, the spatiotemporal attention module based on nonlocal operations is constructed to focus on the most action discriminative nodes and improve the recognition accuracy by reducing redundant information. Then, the spatiotemporal feature extraction module is constructed to obtain the spatiotemporal association information of the nodes of interest. Finally, the action recognition is realized by the Softmax layer. The experimental results show that the algorithm of action recognition in this paper is more accurate and can better help moral evaluation.
Artificial Intelligence-Based Feature Analysis of Ultrasound Images of Liver Fibrosis
Authors: Xie Youcheng , Chen Shun , Jia Dong , Li Bin , Zheng Ying , Yu Xiaohui
Published: July 2022

Liver fibrosis is a common liver disease that seriously endangers human health. Liver biopsy is the gold standard for diagnosing liver fibrosis, but its clinical use is limited due to its invasive nature. Ultrasound image examination is a widely used liver fibrosis examination method. Clinicians can diagnose the severity of liver fibrosis according to their own experience by observing the roughness of the texture of the ultrasound image, and this method is highly subjective. Under the premise that artificial intelligence technology is widely used in medical image analysis, this paper uses convolutional neural network analysis to extract the characteristics of ultrasound images of liver fibrosis and then classify the degree of liver fibrosis. Using neural network for image classification can avoid the subjectivity of manual classification and improve the accuracy of judging the degree of liver fibrosis, so as to complete the prevention and treatment of liver fibrosis. Therefore, the following work is done in this paper: (1) the research background, research significance, research status at home and abroad, and the impact of the development of medical imaging on the diagnosis of liver fibrosis are introduced; (2) the related technologies of deep learning and deep convolutional network are introduced, and the indicators of liver fibrosis degree assessment are constructed by using ultrasonic image extraction features; (3) using the collected liver fibrosis dataset to conduct model evaluation experiments, four classic CNN models are selected to compare and analyze the recognition rate. The experiments show that the GoogLeNet model has the best classification and recognition effect.
On Sum Degree-Based Topological Indices of Some Connected Graphs
Authors: Hussain Muhammad Tanveer , Iqbal Navid , Babar Usman , Rashid Tabasam , Alam Md Nur
Published: July 2022

In mathematical chemistry, molecular structure of any chemical substance can be expressed by a numeric number or polynomial or sequence of number which represents the whole graph is called topological index. An important branch of graph theory is the chemical graph theory. As a consequence of their worldwide uses, chemical networks have inspired researchers since their development. Determination of the expressions for topological indices of different derived graphs of graphs is a new and interesting problem in graph theory. In this article, some graphs which are derived from honeycomb structure are studied and obtained their exact results for sum degree-based indices. Additionally, a comparison is shown graphically among all the indices.
Multifactors Affecting Residential Well-Being in Urban Communities of Shenzhen Incorporating Intelligent Technologies
Authors: Wei Xintong , Zou Guangtian , Siu Kin Wai Michael
Published: July 2022

Rapid urban development is inseparable from technological advances, and the application of artificial intelligence in community life is becoming widespread, affecting residents’ lifestyles and psychological well-being. This study investigated a variety of factors that affect the well-being of urban community residents. Environmental and emotional perceptions and overall well-being were assessed based on the responses of 179 respondents from six small communities in Shenzhen, China. Property management was strongly correlated with satisfaction with the physical environment and least correlated with neighborhood form. Pleasure, comfort, and the sense of belonging were correlated. In addition, interviews and questionnaires revealed a strong influence of AI facilities on people’s well-being. Factor analysis revealed two-component matrices that explained more than 60% of the factors, which were described as “external” and “internal” factors. Finally, the study analyzes the relationship between intelligent devices and impact factors and their effects on residential well-being.
Influence of Percutaneous Drainage Surgery and the Interval to Perform Laparoscopic Cholecystectomy on Acute Cholecystitis through Genetic Algorithm-Based Contrast-Enhanced Ultrasound Imaging
Authors: Li Qiaoying , Cheng Rong , Gao Xiao , Zhu Limin
Published: July 2022

To discuss the optimal interval time between genetic algorithm-based ultrasound imaging-guided percutaneous drainage surgery (PTGD) and laparoscopic cholecystectomy (LC), 64 cholecystitis patients were selected as the research objects and evenly divided into experimental group (intelligent algorithm was adopted to recognize patients’ ultrasonic images) and control group (professional doctors carried out diagnosis). 92 acute cholecystitis patients undergoing PTGD were divided into three groups. 30 out of the 92 patients received LC within 2 months and were defined as the early group. 32 were performed with LC within 2 to 4 months and were defined as the metaphase group. 28 underwent LC over 4 months and were defined as the late-stage group. The average operation time, the transition from LC to laparotomy, the average postoperative hospital stay, and the incidence of complications of the three groups were compared. The results revealed that the comparison of the diagnostic accuracy and comprehensive effectiveness between experimental group and control group demonstrated that the differences were statistically significant (

P
<
0.05

). When the optimal interval of implementing LC after PTGD was realized, the corresponding values of the early group were 88.5 minutes, 16.67%, 8.13 days, and 13.75%. Those of the metaphase group were 49.91 minutes, 3.13%, 4.97 days, and 9.52%. Those of the late stage group were 68.78 minutes, 10.71%, 7.09 days, and 11.96%. To sum up, the diagnostic accuracy and comprehensive effectiveness of intelligent algorithm were higher than those of conventional ultrasound, and the optimal interval time of implementing LC after PTGD was 2 to 4 months.
Analysis of the Impact Measurement on RE Development in the Context of Artificial Intelligence
Authors: Sui Xiang
Published: July 2022

The research and application of artificial intelligence (AI) have changed the way people live and produce. This paper discusses the factors affecting the development of RE in the context of artificial intelligence, analyzes the industrial status of 31 provincial administrative regions in China from the three dimensions of industrial influence, industrial relevance, and industrial efficiency, and uses gray correlation analysis to evaluate the system and measure.
Analysis of the Characteristics of British Medieval Monastery Education Based on Network Data Mining
Authors: Wang Yi , Wu Xia
Published: July 2022

To a large extent, the history of education in the Middle Ages in Western Europe is a history of church education. The church dominated and participated in the whole process of education, which is very rare and peculiar in the history of world education. The Middle Ages is synonymous with darkness and ignorance in everyone’s original cognition. Through the unremitting efforts of historians, people’s evaluation of the Middle Ages has gradually changed. The original purpose of monastic education was to train missionaries so that missionaries could take the faith of Christ to places where they were still in ignorance and save mankind on the basis of glorifying God. Due to the need of mission, in the process of education, missionaries also continuously integrated the ideological culture belonging to paganism and barbarians. In this paper, the monastery development index obtained based on data mining technology and the British medieval development index have a fit of more than 90%, indicating that monasteries have a certain role in promoting the economic development of the British Middle Ages. The development of the economic function of the English medieval seminary had a profound impact on the restoration of economic production and the establishment of an orderly life.
[Retracted] Assessment of Acupoint Therapy of Traditional Chinese Medicine on Cough Variant Asthma: A Meta‐analysis
Authors: Tu Hengjia , Zhang Qingling
Published: July 2022

Acupoint application has been used in China to treat various illnesses for ages. In cough variant asthma (CVA), the main clinical sign is episodic night cough. Acupoint application therapy of traditional Chinese medicine is an effective procedure to treat cough variant asthma. The current study is designed to systematically assess the effectiveness of acupoint application therapy in traditional medicine for patients with cough variant asthma. The comprehensive computer retrieval related to comparison between acupoint application and nonacupoint application therapy for cough variant asthma was carried out in various databases (n = 8) from database establishment until July 4, 2021. Both English and Chinese articles about original investigations in humans were searched. Two independent authors extracted the data, and disagreements were resolved by discussion. ReviewManager 5.3 software provided by Cochrane did a meta‐analysis of selected randomized controlled trials (RCTs). Quality of experimentation and risk bias were analyzed by the Cochrane Handbook tool. A total of thirteen randomized controlled clinical articles along with 1237 patients were included in the study. Findings of meta‐analysis showed that compared with nonacupoint application treatment, the total effective rate of acupoint application treatment is more effective (RD = 0.13, 95% CI (0.09, 0.17), Z = 6.70, P < 0.00001). Besides, acupoint application can improve patients’ lung function, the lung function index FVC (mean difference = 0.55, 95% confidence interval (0.42, 0.68), Z = 8.40, P < 0.00001), FEV1 (MD = 0.35, 95% CI (0.23, 0.47), Z = 5.86, P < 0.00001), FEV1/FVC (%) (MD = 12.68, 95% CI (4.32, 21.03), Z = 2.97, P = 0.003), FEV1 (%) (MD = 8.63, 95% CI (8.01, 9.25), Z = 27.44, P < 0.00001), and PEF (day) (MD = 0.62, 95% CI (0.52, 0.71), Z = 12.40, P < 0.00001) of patients treated by acupoint application therapy were increased. Moreover, acupoint application might lower the level of immunoglobulin E (MD = −54.58, 95% CI (−63.54, −45.61), Z = 11.93, P < 0.00001) and EOS (MD = −0.21, 95% CI (−0.35, −0.06), Z = 2.77, P = 0.006). The LCQ (Leicester cough questionnaire) total score of CVA patients was also increased (MD = 2.30, 95% CI (1.55, 3.06), Z = 5.98, P < 0.00001). Acupoint application therapy is effective in controlling symptoms of CVA. It also has a positive effect in improving lung function and life quality of patients. It can reduce the eosinophil levels and peripheral blood IgE levels of patients as well.
Development of Intelligent CAD Technology for New Longitudinal Shell-Side Heat Exchange Equipment
Authors: Wu Xin , Zhu Feng
Published: July 2022

In order to correct the errors of “periodic full-section calculation model” and “unit flow channel model,” the author proposes a numerical simulation method of a longitudinal flow shell-side heat exchanger based on CAD. The numerical simulation of the fluid flow and heat transfer characteristics of the three-blade orifice plate heat exchanger is carried out by using FLUENT software, and the “periodic full-section calculation model” and “unit flow channel model” are established, as well as the calculation results of comparative analysis. Experimental results show the following: With the increase of the inner diameter

D

of the heat exchanger shell, the calculation results of the two models are gradually reached. When

D
>
800
 
mm

, the error of the calculation results of the two models has been reduced to about 10%; at this time, the “unit flow channel model” has practicability and applicability. When

D
≤
800
 
mm

, the correction algorithm of the “unit flow channel model” is proposed, and the correction correlation formula of the pressure gradient and convective heat transfer coefficient is given. The revised results of the simulation can not only meet the engineering needs but also save computer resources and improve the calculation efficiency, which provides a theoretical basis for the development, improvement, and further industrial application of the “unit flow channel model” of the longitudinal shell-side heat exchanger.
Application of Virtual Reality Technology Based on Artificial Intelligence in Sports Skill Training
Authors: Lv Jiyong , Jiang Xiangzhi , Jiang Ang
Published: July 2022

With the rapid development of science and technology and economy, it has a great impact on people’s lifestyle and habits. Fewer and fewer people will actually carry out offline sports activities, and some will choose gyms and other places for offline exercise, but the high cost of gyms limits most people’s desire to exercise. Our country has been actively introducing policies or measures to advocate physical exercise, but people’s enthusiasm is not high or improper training leads to frequent physical injury. In view of the current situation and pain points of sports skill training, this paper first discusses the possibility of the overall application of virtual reality technology based on artificial intelligence in sports skill training. Secondly, it explores the application of virtual reality technology based on artificial intelligence in tennis, which is a highly skilled sports training. Finally, combined with the practical application of virtual reality technology based on artificial intelligence in sports skills training, it proves the advantages and influence of applying virtual reality technology based on artificial intelligence in sports skills training in the future.
Development of a Sensitive Quality Evaluation System for Chinese Outstanding Female Boxers
Authors: Zhong Haibo , Bu Xiangui
Published: July 2022

Objective. To construct an evaluation system for the sensitivity quality of outstanding Chinese female boxers and to develop comprehensive evaluation criteria for the sensitivity quality of outstanding female boxers. Methods. Using literature method, Telfer method, expert interview method, and experimental test method to analyze the special sensitivity quality structural elements of female boxers. Results. The evaluation indexes of female boxers’ sensitivity quality consisted of three structural elements: ability to change movements, ability to change direction, and balance ability; the evaluation index system of female boxers’ sensitivity quality, including 3 primary indexes and 11 measurement indexes, in which the weights of the primary indexes of female boxers’ special sensitivity quality were 0.44 for the ability to change movements (0.22 for 1 min dodge defense, 0.22 for 1 min combination punching sandbag 0.21, 30 s standing push‐up 0.21, and 30 s leg change jumping punch 0.19), the ability to change direction 0.39 (30 s continuous head hold squat 0.16, 1 min 3 m sides slide touch 0.29, 20 s repeated side slide 0.28, 10 m ∗ 4 round trip run 0.24, and 1 min quadrant jump 0.19), and balance ability 0.17 (15 s rotating and then walking forward 5 m 0.51, carrying legs to support balance 0.49), the ability to change movements has the largest proportion in the sensitivity quality of female boxers, followed by the ability to change direction and balance ability. Conclusion. Based on the constructed evaluation index system, 11 individual indexes’ evaluation criteria and four levels of comprehensive evaluation criteria for the sensitivity quality of female boxers were established by using the deviation method and percentile method.
3D Design Platform of Virtual National Costume Based on Digital Nonlinear Random Matrix
Authors: Zhang Mingyan , Shen Luolan
Published: July 2022

The traditional two-dimensional clothing CAD system is more and more difficult to meet the needs of the three-dimensional design of virtual national clothing products. Based on the digital nonlinear random matrix theory, this paper constructs a three-dimensional design platform for virtual ethnic clothing and proposes a weighted graph tree representation method for the deviation transfer process of nonlinear ethnic clothing. The model first analyzes the business links and information related to the deviation transfer modeling of ethnic clothing and establishes a hierarchical relationship tree, a method of expressing the order of ethnic clothing, and a method of expressing deviation. The weighted graph tree model and construction rules of the deviation transmission process realize the integrated expression of the deviation transmission information of ethnic clothing and solve the nonlinear problem in the transmission of ethnic clothing deviation. During the simulation process, the article uses the three-dimensional geometric modeling tool POSER to establish a standard entry model, edit it in 3DS MAX and export the file, read it, and parameterize it through programming, and realize the drawing of the three-dimensional avatar model based on OpenGL. The experimental results show that the parametric avatar model established by the system is accurate and realistic and can quickly convert the 3D style to the N-dimensional pattern.