bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Smartphone Trojan Detection Based on the Wireless Sensor Network
Authors: Li Gang
Published: July 2022

In order to reduce false positives of Trojan horse detection algorithms in smartphones, a voting algorithm based on multiple machine learning algorithms in wireless sensor networks was proposed. Through setting up the experiment, the preliminary preparations of the experiment, including sample set selection, feature set extraction method, and algorithm effect evaluation criteria, were described first. The K-nearest neighbors algorithm, random forests algorithm, support vector machine, and voting algorithm were compared. The experimental results showed that SVM and KNN algorithms took the shortest time, about 0.3 seconds. Judging by the test results, the voting algorithm still performed the best among the four algorithms as the voting algorithm was an extension of the three machine learning algorithms. In these randomly selected samples, malicious programs and nonmalicious programs were successfully distinguished by the voting algorithm. As the amount of test data increased, the test results would be closer to the actual situation. Namely, the voting algorithm would also have a small probability of false positives, which could meet the design requirements of the system. It was concluded that the method could effectively reduce false positives of the Trojan horse detection algorithm in smartphones.
A Novel MG 2D Animation Design Method under the Perspective of Convergence Media Using Intelligent Design Technology
Authors: Xu Juan , Liu Kai , Yuan Yang
Published: July 2022

The arrival of the 5G era, along with the gradual acceleration of information technology development, makes all kinds of new media gradually integrated into all corners of people’s life, work, and study. Communication systems are breaking the original boundaries and moving toward communion. “Convergence Media” is a general term of new media which is built on modern network technology and integrates various media forms. In this context, animation design not only is limited to two-dimensional or three-dimensional creation, but also formed a new form of animation expression, namely, MG animation. For MG animation, with its simple artistic modeling elements and flexible rhythm, people have gained new cognition. When the Internet information is transmitted, MG animation can output a large number of dynamic images and text to people in a very short time, which is similar to the current mode of new media communication. It can make information more attractive and appealing with the visual performance of MG animation. In order to improve the quality and efficiency of animation, convergence media technology is applied to the drawing and production of animation. The emergence and continuous improvement of software such as AE, PR, and PS and other software have a strong compatibility and can fully meet our various requirements for MG animation production, thus bringing the audience a different kind of animation experience. AE, a common software for video production, can create a variety of striking visual effects with high efficiency and precision, with powerful effects control and millions of plug-ins to achieve a wide range of animation effects. High-quality video rendering supports resolutions from 4 × 4 to 30,000 × 30,000 pixels including high-definition television (HDTV). Therefore, in terms of animation production, we can choose to mainly use AE for production and rendering. In terms of drawing tools, PS is the software of choice, with no delay in drawing, dithering correction, selection, and other features which are quite outstanding, and has a great advantage in drawing lines and coloring. Based on this, this paper mainly explores the design and production cases of MG 2D animation from the new media perspective using the intelligent design technology. The animation designed by the method in this paper can also be used for medical treatment management or lesion display in the medical field.
Enterprise Management Model Innovation and Performance Index Evaluation Based on the Era of Big Data
Authors: Xie Yun
Published: July 2022

The innovation of enterprise management model has increasingly become one of the important sources of competitive advantage for enterprises. At present, the market environment is changing rapidly, and information technology is changing the nature and structure of enterprise competition. In the competitive landscape of enterprises under the background of network economy, only relying on technological innovation can no longer meet the needs of enterprise development. In recent years, the successful practice of a large number of enterprises has shown that the innovation of enterprise management mode is also an indispensable and important factor to promote the sustainable development of enterprises. In the new format of competition among enterprises, the innovation of enterprise management mode is playing an important role. Scholars have very rich research contents on the innovation of enterprise management model. First, they focus on the research between the innovation of enterprise management model and the value creation of enterprises. They believe that determining the structure of new business and innovation of enterprise management model can create value for enterprises. The innovation of enterprise management model can effectively explain the differences in enterprise performance; secondly, the research of enterprise management model innovation has been extended to its classification research; that is, different types of enterprise management model innovation have different effects on performance; finally, in the existing research, in this paper, some progress has been made in the exploration of the mediating variables between enterprise management model innovation and performance. The example verification shows that the performance of the momentum-adaptive algorithm is the best. Using the BP network model can effectively evaluate the innovation of enterprise management mode and performance indicators, so as to guide the implementation of enterprise management mode innovation activities. Although this paper has made some innovative achievements, there are still many limitations and deficiencies in the research. The depth of literature search, the breadth of data measurement collection, and the subjectivity of questionnaires will affect the accuracy of the results. The practicality of the research results needs to be further improved in the follow-up research.
Large‐Scale Group Decision‐Making Model with Cooperative Behavior Based on Social Network Analysis considering Propagation of Decision‐Makers’ Preference
Authors: Bai Shizhen , He Hao , Ge Mengke , Yang Ruobing , Luo Dan , Bi Xinrui
Published: July 2022

This paper proposes a large‐scale group decision‐making model with cooperative behavior based on social network analysis considering propagation of decision‐makers’ preference, which is applicable for large‐scale group decision‐making problems in social network contexts. The main contributions of our research are three aspects. Firstly, a novel calculation method of cooperative degree, hesitant degree, and noncooperative degree is developed, which considers both the network status and the preference for each DM, and thereby it can better represent the current state for each DM. Then, the determination method of each DM’s weight is presented, which considers both the individual network centrality and preference similarity degree. In addition, the score for the current cooperation situation is performed, and the improvement algorithm of the increase of cooperative degree and the decrease of noncooperative degree is designed to enhance the quality of the decision‐making results. Finally, the proposed model has demonstrated the validity and superiority based on the comparative and sensitive analysis through a practical example.
Rapid Determination of Mercury Ions in Environmental Water Based on an N-Rich Covalent Organic Framework Potential Sensor
Authors: Tian Jinjin , Zhu Yulin
Published: July 2022

In this article, an N-rich covalent organic framework (COFTFPB-TZT) was successfully synthesized using 4,4′,4′-(1,3,5-triazine-2,4,6-triyl) trianiline (TZT), and 4-[3,5-bis (4-formyl-phenyl) phenyl] benzaldehyde (TFPB). The as-prepared COFTFPB-TZT possesses irregular cotton wool patches with a large specific surface area. A novel selective electrode based on COFTFPB-TZT was used for the determination of Mercury ions. The abundance of N atoms in COFTFPB-TZT provides more coordination sites for Hg2+ adsorption, resulting in a change in the surface membrane potential of the electrode to selectively recognize Hg2+. Under optimal experimental conditions, the ion-selective electrode shows a good potential response to Hg2+, with a linear range of 1.0 × 10−9∼1.0 × 10−4, a Nernst response slope of 30.32 ± 0.2 mV/-PC at 25°C and a detection limit of 4.5 pM. At the same time, the mercury-ion electrode shows a fast response time of 10 s and good reproducibility and stability. The selectivity coefficients for Fe2+, Zn2+, As3+, Cr6+, Cu2+, Cr3+, Al3+, Pb2+, NH4+, Ag+, Ba2+, Mg2+, Na+, and K+ are found to be small, indicating no interference in the detection system. The proposed method can be successfully applied to the determination of Hg2+ in 3 typical environmental water samples, with a recovery rate of 98.6–101.8%. In comparison with the spectrophotometric method utilizing dithizone, the proposed method is simple and fast and holds great potential application prospects in environmental water quality monitoring and other fields.
Decentralized Consensus Blockchain and IPFS-Based Data Aggregation for Efficient Data Storage Scheme
Authors: Subathra G. , Antonidoss A. , Singh Bhupesh Kumar
Published: July 2022

By the development and advancement of blockchain technique, Internet of Things (IoT) proliferation driven devices and the application of blockchain-enabled IoT alter the view and operating infrastructure of the smart networks. The blockchain is responsible for supporting decentralized systems and offers secured means of authentication, management, and access to IoT system thereby deploying smart contracts offered by Ethereum. The increasing demand and the blockchain expansion generate huge volume of sensitive data. The growing demand and expansion of blockchain-IoT systems is generating large volume of sensitive data. Furthermore, distributed denial-of-service (DDoS) attacks are regarded as the most promising threats for smart contracts in the blockchain-based systems. Therefore, there is a need to detect and classify the attack type and the data should be stored in server more securely with the use of blockchain and data aggregation method. For this purpose, this presented technique aims at introducing decentralized consensus blockchain and Interplanetary file system (IPFS) based data aggregation for effective classification and data storage. The attack is detected using meta-hyperparameter random forest (MHP-RF) classifier. Once the attack is detected, the transaction information is stored in server securely by means of smart contract-based blockchain system. The transaction handling stage classifies the transaction type as normal or abnormal one which then followed by execution of business logic by smart contract thereby appending the transaction of blockchain in the network cloud. The consensus blockchain technique is employed with the use of PoW-enabled scheme integrated with Elgamal-based data aggregation. Therefore, the system security is improved and the intrusion is prevented greatly. The performance analysis of the system is analyzed in terms of accuracy, precision, recall, F-score, Encryption time, decryption time, execution time, and space complexity. The attained outcomes are compared with traditional approaches to prove the effectiveness of proposed strategy. The proposed system is said to be effective in time consumption, classifier performance, and in overcoming space complexity issues.
Early Detection of Forest Fire Using Mixed Learning Techniques and UAV
Authors: Kasyap Varanasi LVSKB , Sumathi D. , Alluri Kumarraju , Reddy CH Pradeep , Thilakarathne Navod , Shafi R. Mahammad
Published: July 2022

Over the last few decades, forest fires are increased due to deforestation and global warming. Many trees and animals in the forest are affected by forest fires. Technology can be efficiently utilized to solve this problem. Forest fire detection is inevitable for forest fire management. The purpose of this work is to propose deep learning techniques to predict forest fires, which would be cost-effective. The mixed learning technique is composed of YOLOv4 tiny and LiDAR techniques. Unmanned aerial vehicles (UAVs) are promising options to patrol the forest by making them fly over the region. The proposed model deployed on an onboard UAV has achieved 1.24 seconds of classification time with an accuracy of 91% and an F1 score of 0.91. The onboard CPU is able to make a 3D model of the forest fire region and can transmit the data in real time to the ground station. The proposed model is trained on both dense and rainforests in detecting and predicting the chances of fire. The proposed model outperforms the traditional methods such as Bayesian classifiers, random forest, and support vector machines.
Innovative Design of Intelligent Health Equipment for Helping the Blind in Smart City
Authors: Wei Chang , Guang Lv , Bin Liu , Li Ruoxi
Published: July 2022

The rapid advancement of information technology in today’s modern society is contributing to an increase in the general degree of civilization in society. People are pleased with technological progress, but they are also becoming more aware that a major challenge confronting the advancement of social civilization at the moment is determining how to alleviate the difficulties associated with traveling and participating in social activities for the blind, as well as increasing the frequency with which they go out, travel, and participate in other activities. The blindness equipment that is now accessible in China is no longer suitable to meet the needs of blind people, but the growth of smart cities offers an opportunity to change this. Guide devices are crucial among the numerous types of equipment to assist the blind, and in order to better fulfill their various demands, we must upgrade and optimize the existing devices. The Chinese People’s Daily highlights some of the key barriers to blind people’s access in its 2019 article: random parking that blocks blind lanes; and “snake” and “broken” blind lanes that are not created with blind people’s access in mind. In a smart city, accurate placement via smart maps helps alleviate a number of traffic-related issues for blind individuals. In this paper, we propose an intelligent guide device and interactive software to provide a more intelligent way for blind people to travel, which can effectively improve blind people’s traffic conditions and make their travel easy, convenient, and safe, reflecting society’s concern for blind people.
Intestinal Ultrasonography as a Tool for Monitoring Disease Activity in Patients with Ulcerative Colitis
Authors: Stojkovic Lalosevic Milica , Sokic Milutinovic Aleksandra , Matovic Zaric Vera , Lolic Iva , Toplicanin Aleksandar , Dragasevic Sanja , Stojkovic Mirjana , Stojanovic Marija , Aleksic Marko , Stjepanovic Mihailo , Martinov Nestorov Jelena , Popovic Dusan Dj. , Glisic Tijana
Published: July 2022

Background. Ultrasonography is a noninvasive, inexpensive, and widely available diagnostic tool. In the last two decades, the development of ultrasound techniques and equipment has significantly increased the usage of intestine ultrasound (US) in the assessment of the gastrointestinal tract in patients with inflammatory bowel disease (IBD). Although current guidelines suggest routine utilization of US in patients with Crohn’s disease, data regarding US usage in ulcerative colitis are still scarce. We aimed to assess the reliability of intestinal ultrasonography in the assessment of disease activity and extension of patients with ulcerative colitis. Methods. Fifty-five patients with a histologically confirmed diagnosis of ulcerative colitis, treated at University Clinical Center of Serbia in the period from 2019 to 2022 were included in this retrospective observational study. The data were obtained from the patient’s medical records including history, laboratory, US, and endoscopy findings. US examined parameters were as following: bowel wall thickness (BWT), presence of fat wrapping, wall layer stratification, mesenteric hypertrophy, presence of enlarged mesenteric lymph nodes, and absence or presence of ascites. Results. Our results suggest that there is a strong correlation of BWT and colonoscopy findings regarding disease extension (r = 0.524,

p
=
0.01

,

p
<
0.05

). Furthermore, our results have shown a statistically significant correlation of BWT with the Mayo endoscopic score (r = 0.434,

p
=
0.01

,

p
<
0.05

), disease activity score (r = 0.369,

p
=
0.01

,

p
<
0.05

), degree of ulcerative colitis burden of luminal inflammation (r = 0.366,

p
=
0.01

,

p
<
0.05

), and Geboes index (r = 0.298,

p
=
0.027

,

p
<
0.05

). Overall accuracy of US for disease extension and activity was statistically significant (

p
<
0.05

). Conclusions. Our results suggest that US is a moderately accurate method for the assessment of disease activity and localization in patients with UC.
Chitosan-Cinnamon Oil Coating Maintains Quality and Extends Shelf Life of Ready-to-Use Pomegranate Arils under Low-Temperature Storage
Authors: Singla Mohit , Pareek Sunil , Kumar Nishant , Sagar Narashans Alok , Fawole Olaniyi Amos
Published: July 2022

Different formulations of chitosan (1%, 2%, or 3%) with the incorporation of cinnamon oil (0.25% or 0.50%) were prepared for the preservation of pomegranate aril cv. Bhagwa. Six combinations of chitosan-cinnamon oil formulations along with one control (untreated) were applied to the freshly extracted arils using the dipping application method. All treatments were found to be effective in enhancing the shelf life, improving the postharvest characteristics, and reducing microbial populations on pomegranate arils during a 15-day storage period at 4 ± 1°C. The treated pomegranate arils exhibited excellent resistance to microbial decay, moisture loss, respiration rate, preservation of phenolics, flavonoids, and antioxidants activity, among other characteristics. Chitosan 2% + cinnamon oil 0.25% edible coating has a high potential to enhance the storage life and biochemical properties and reduce the microbial population of arils. This treatment recorded a higher total phenolic content (18%) and antioxidant activity (16%) than the control sample, respectively, at the end of storage. In addition, the treatment also helped to decrease the microbial activity by 45% compared to the control sample. The present investigation proposed an alternative method to prolong the shelf life of pomegranate arils during the 15 days of storage.
Innovation of Platform Economy Business Model Driven by BP Neural Network and Artificial Intelligence Technology
Authors: Zhou Lianjie , Wang Chengfu
Published: July 2022

In order to enhance the competitiveness of enterprises, how to evaluate and enhance the competitiveness of B2B e-commerce enterprises and promote the orderly and healthy development of B2B e-commerce industry are discussed. This paper puts forward the research on the innovation of platform economic business model driven by BP neural network and artificial intelligence technology. BP neural network is used to study and evaluate the competitiveness of B2B e-commerce companies. According to the B2B e-commerce company competitiveness theory and BP neural network algorithm, combined with BP neural network and B2B e-commerce company competitiveness evaluation index system, a BP neural network model is designed to analyze the competitiveness of B2B e-commerce enterprises. Determine the expected value of network samples, select G1 method to determine the subjective weight, and select entropy weight method to determine the objective weight. With the help of the function in the MATLAB neural network toolbox, the neural network is trained. The results show that when the training times reach 3297 times, the sample mean square error is 9.9869e − 06, and the training network reaches convergence. The samples of three enterprises test the trained neural network and input the data of three test samples into the trained BP neural network, and the output results are 0.1531, 0.1371, and 0.1557, respectively. The network model constructed in this paper is effectively close to the training samples. The established BP neural network has good performance and can be used to evaluate the competitiveness of B2B e-commerce companies. Accelerate technological change and realize innovation. Technological capability is the inexhaustible driving force for the development of enterprises. Only with the innovation of keeping pace with the times can application-oriented e-commerce enterprises meet the needs of customers and the market, form the difference between goods or services, and then enable enterprises to win more customers and market share.
Construction of Intelligent Evaluation Model of English Composition Based on Machine Learning
Authors: Wang Yuling
Published: July 2022

To automatically grade compositions, automatic composition grading primarily employs statistics, mathematical analysis, machine learning, natural language processing, and other technologies. This paper presents a machine learning-based intelligent evaluation model for English composition. As a result, this paper proposes a word vector grouping-based text content representation method and a vector space model-based text content representation method. The Word2Vec model is first trained with words, then used to generate a test model of word vectors, with the statistical information of the corresponding words in each category serving as content text features. The results show that when features based on word vector clustering are added to the content text, the effect of each model improves significantly, especially the maximum entropy model, which improves by 0.048. The XGBoost model has also seen a significant improvement, going from 0.771 to 0.803. The test corpus is made up of 100 articles chosen at random from the corpus, and the test set is checked for errors. The rate of accuracy is 68 percent. The conclusion demonstrates that the model presented in this paper can help promote English teaching reform and quality-oriented higher education while also easing the burden on teachers and students.
Clinical Efficacy Analysis of Fast Rehabilitation Nursing on Pain Mitigation after Lumbar Discectomy and Bone Graft Fusion and Internal Fixation
Authors: Fang Lingling
Published: July 2022

Objective. To investigate clinical efficacy analysis of fast rehabilitation nursing on pain mitigation after lumbar discectomy and bone graft fusion and internal fixation. Methods. A total of 60 patients with lumbar disc herniation who underwent lumbar discectomy and bone graft fusion and internal fixation in our hospital from January 2021 to December 2021 were randomized either into routine group (n = 30) or rehabilitation group (n = 30) via the random number table method. The patients in the routine group were intervened with the routine postoperative nursing mode, and the patients in the rehabilitation group were intervened with the fast rehabilitation nursing mode on the basis of the nursing of the patients in the routine group. The rehabilitation effect, self-rating anxiety scale (SAS) and self-rating depression scale (SDS) scores, postoperative pain improvement, and nursing satisfaction were compared between the two groups. Results. The postoperative rehabilitation effect of the rehabilitation group was significantly better than that of the routine group (

P
<
0.05

). The fast rehabilitation nursing resulted in a notably lower postoperative SAS and SDS scores versus the routine nursing (

P
<
0.001

). The postoperative pain was significantly mitigated in the rehabilitation group when compared with the routine group (

P
<
0.001

). The fast rehabilitation nursing implemented in the rehabilitation group led to a remarkably higher nursing satisfaction of the patients (

P
<
0.001

). Conclusion. The fast rehabilitation nursing mode intervention for lumbar disc herniation patients undergoing lumbar discectomy and bone graft fusion and internal fixation is a promising approach to improve the postoperative rehabilitation, mitigate postoperative pain, and relieve anxiety, depression, and other negative emotions, with higher clinical nursing satisfaction.
Variation Factors and Dynamic Modeling Analysis of Tennis Players’ Competitive Ability Based on Big Data Mining Algorithm
Authors: Xie Yanan , Bai Bing , Zhao Yunpeng
Published: July 2022

In order to fully tap the potential of tennis players, speed, strength, and endurance are further improved in physical factors. Improve the overall competitiveness of tennis to a higher level and further improve the scientific level of tennis training. This paper truly reflects the adaptability of athletes’ functional state to training load. At the same time, the data mining algorithm is used to analyze the correlation between athletes and athletes in the application of techniques and tactics. The results show that timely adjustment of training plan and training load can provide a scientific and objective basis for improving the guidance of combat readiness training. At the same time, adjusting the training plan and training load provides a scientific and objective basis for further improving the guidance of combat readiness training. This paper improves the metacognitive level of athletes’ participation, accurately and timely adjusts the athletes’ personal goals and realistic positioning, and timely feeds back the relevant information of the competition. Only by being good at creating a competition environment can athletes give full play to their advantages and actively seek and pursue improvement in the stage of competitive ability.
Identification of a Necroptosis-Related Prognostic Signature and Associated Regulatory Axis in Liver Hepatocellular Carcinoma
Authors: He Aoxiao , Huang Zhihao , Wang Jiakun , Lu Hongcheng , Zhang Rongguiyi , Wu Linquan , Feng Qian
Published: July 2022

Background. Liver hepatocellular carcinoma (LIHC) ranks the sixth in global cancer incidence with poor prognosis. Necroptosis is a kind of regulated cell death and has been proved to be of significance in cancer occurrence and progression. However, few studies comprehensively discuss the potential applications of necroptosis-related genes (NRGs) in the prognostic evaluation and immunotherapy of LIHC. Methods. The prognostic signature in the present study was built up using LASSO Cox regression analysis. Integrated bioinformatics tools were utilized to explore the potential mRNA-miRNA-lncRNA regulatory axis in LIHC. Furthermore, qRT-PCR method was used to verify the EZH2 expression in LIHC tissues. Furthermore, prognostic performance of EZH2 in LIHC was assessed by Kaplan-Meier method. Results. A total of 14 NRGs were differentially expressed in LIHC tissues. The overall genetic mutation status of these NRGs in LIHC was also shown. NRGs were significantly correlated with programmed necrotic cell death, as well as Toll-like receptor signaling pathway in GO and KEGG pathway analysis. Kaplan-Meier analysis revealed that ALDH2, EZH2, NDRG2, PGAM5, RIPK1, and TRAF2 were related to the prognosis. A prognostic signature was constructed by these six genes and showed medium to high accuracy in the prediction of LIHC patients’ prognosis. Further analysis revealed that NRGs were correlated with pathological stage, immune infiltration, and drug resistance in LIHC. Moreover, we identified a potential lncRNA TUG1/miR-26b-5p/EZH2 regulatory axis in LIHC, which might affect the progression of LIHC. qRT-PCR suggested a higher mRNA level of EZH2 in LIHC tissues. And a poor overall survival rate was detected in LIHC patients with high EZH2 expression. Moreover, EZH2 expression and cancer stage were identified as the independent risk factors affecting LIHC patients’ prognosis. Conclusion. In the present study, we conducted comprehensive bioinformatic analyses and built up a necroptosis-related prognostic signature containing four genes (ALDH2, EZH2, NDRG2, and PGAM5) for patients with LIHC, and this prognostic signature showed a medium to high predictive accuracy. And our study also identified a lncRNA TUG1/miR-26b-5p/EZH2 regulatory axis, which might be of great significance in LIHC progression. In addition, based on the data from our center, the result of qRT-PCR and survival analysis showed a higher mRNA level of EZH2 in LIHC tissues and an unfavorable prognosis in high EZH2 expression group, respectively.
Analysis of Consumer Aspirations on Chinese Films among Chinese Malaysians
Authors: Kang Hongzhe , Ma Dong , Yasin Megat Al Imran , Osman Mohd Nizam , Ang Lay Hoon , Li Mengyu
Published: July 2022

Chinese films have the potential to play a key role in the Belt and Road Initiative. Although Chinese Malaysians contributed to the development of China’s film industry, the consumption incentives of Chinese Malaysians for Chinese films are worth mentioning. Furthermore, Chinese Malaysians’ purchasing behaviour towards Chinese films is affected by a combination of consuming factors. However, the function of linguistic proximity in the link between consuming incentive and purchasing behaviour is unexplored. This study focused on Chinese Malaysian students from three universities in Selangor and applied online questionnaires in quantitative research methods. Data were collected from 165 Chinese Malaysians. Results show that Chinese Malaysians are mostly motivated to watch Chinese films by the sense of belonging and vitality. Furthermore, linguistic proximity significantly influences the association between Chinese Malaysians’ motive for belonging and their purchasing behaviour for Chinese films. Moreover, the Chinese Malaysians consume Chinese films with linguistic proximity acting as a moderator in this relationship.
Pre‐BMI and Lipid Profiles in Association with the Metabolic Syndrome in Pregnancy with Advanced Maternal Age
Authors: Yang Xinxin , Jiang Rui , Yin Xiuping , Wang Guangya
Published: July 2022

We aimed to explore the association of BMI in pre‐pregnant women with metabolic syndrome in pregnancy in advanced maternal age. A total of 229 maternal women and 536 maternal women participated in this study. Pregnancy women underwent a 75 g‐oral glucose tolerance test and maternal lipid profile test between 24 and 28 weeks. Data about biological and sociodemographic characteristics were recorded for each case. The metabolic equivalent (Met) was 9.6% in the maternal age ≥35 group, 5.4% in the age 20–34 group (P = 0.027), and 6.7% in all pregnant women. Results also demonstrated that gestational diabetes mellitus (GDM) and MetS were more likely to appear in the maternal age ≥35 years group than the maternal age 20–34 years group (41.5% vs. 30.6%; P = 0.001, 9.6% vs. 5.4%, P = 0.027). Risk for preterm delivery and eclampsia were increased with raised MetS (RR 3.434 and RR 1.800); MetS in women aged ≥35 years had the largest area under the curve (AUC) (AUC 0.925, 95% CI 0.885–0.965), and its optimal cutoff point was ≥24.998 kg/m2, and the optimal cutoff point for total cholesterol (TC) (AUC 0.686, 95% CI 0.571–.802) predicting MetS was ≥4.955 mmol/l. MetS in pregnancy are associated with the occurrence of preterm delivery and eclampsia, and pre‐BMI and TC can predict MetS in the maternal age ≥35 group.
An Investigation on the Risk Factors of Thyroid Diseases in Community Population in Hainan
Authors: Fang Tuanyu , Lin Leweihua , Ou Qianying , Lin Lu , Zhang Huachuan , Chen Kaining , Quan Huibiao , He Yangli
Published: July 2022

Background. In recent years, the incidence of thyroid diseases has increased significantly, which has seriously affected people's work and life. The purpose of this study was to explore the epidemiological characteristics of thyroid diseases and autoantibodies. Method. According to the principle of overall sampling, resident residents ≥18 years and who will not move within 5 years are randomly selected. A total of 2136 eligible individuals were divided into case and control groups according to whether they have thyroid disease. Finally, the impact of potential risk factors on thyroid diseases was evaluated. Results. The overall prevalence of thyroid disease was 58.3%, and there was a significant difference in the prevalence of thyroid disease between women and men (p = 0.004). Except for the age group ≥70 years, with the increase in age, the prevalence gradually increased (p < 0.05). Participants with positive thyroid autoantibodies (TPOAb or TgAb) had a higher prevalence than participants with negative autoantibodies. The positive rate of autoantibodies in women was higher than that in men (p < 0.05). UIC (p = 0.004) and free thyroid hormone (FT4) (p = 0.001) levels of men were higher than those of women, and the TSH level of women was higher than that of men (p = 0.002). The regression analysis showed that women, older age, and family history of thyroid disease were independent risk factors for thyroid disease. Conclusion. The prevalence of thyroid diseases in Hainan was high. Women are more susceptible to thyroid disease than men, and the prevalence increased with age.
[Retracted] An Intelligent and Fast Dance Action Recognition Model Using Two‐Dimensional Convolution Network Method
Authors: Zhang Shuai
Published: July 2022

In the field of computer vision, action recognition is a very difficult topic to study. This paper suggests a dance movement recognition method based on DL network in accordance with the characteristics of dance movements. The backbone network in this study is a thin network called Mobile Net. The two‐dimensional convolution network, which can only extract spatial features, can extract and fuse time domain features and use them for dance movement recognition by combining the time domain modelling strategy of time domain feature transfer between convolution layers. It uses fewer network parameters and less computation than the original multitarget detection model. Using the clustering method to preset the prior frames of human detection with various sizes and numbers also enhances the model’s performance. Finally, the experimental findings demonstrate that the algorithm suggested in this paper outperforms the Incision v3 algorithm in F1 by 9.87 percent and outperforms the traditional CNN algorithm in identification accuracy by 6.51 percent and 10.76 percent, respectively. It is evident that the algorithm used in this paper reduces running time and, to a certain extent, improves the accuracy of dance movement recognition. For related research, it offers some references.
Innovation and Integration Development of the Cultural Industry Based on Mapping Knowledge Domains
Authors: Lian Jiangong , Liang Dan
Published: July 2022

In view of the less current user data of the cultural industry, its classification and presentation form are complex. This paper constructs the MKD of the cultural industry integration through the RDF graph model and realizes the distributed vector representation of cultural project semantic information by using the fine-tuning translation distance model TransH. The semantic information of cultural industry fusion is mapped to a continuous vector space, and the distributed vector representation of cultural projects is realized. The results show that it is helpful to accurately express the correlation between different regions and cultural types and to explore the data association and implicit relationship of innovation and integration development in the cultural industry.
Research on the Application of Artificial Neural Network-Based Virtual Image Technology in College Tennis Teaching
Authors: Hu Ruizhe , Cui Xiaocan
Published: July 2022

At the same time that my country has shifted from high-speed development to high-quality development, my country has also put forward new requirements for education development. Due to the limited study time during college, each student’s study habits and learning process are also different, and the degree of connection between tennis lessons is high, so there will be polarization when learning tennis. With the development of science and technology, more and more technological innovations are integrated into the classroom, and traditional teaching methods can no longer keep up with the pace of the times. Tennis teaching is a subject of equal proportion between theory and practice. The traditional teaching method simplifies the theory, which makes students to have some bad phenomena when they practice. Aiming at this series of problems, this paper uses algorithms such as softmax function and threshold function to construct an application model of virtual image technology based on the artificial neural network in tennis teaching. The research results of the article show that: (1) the average accuracy rate of the method in this paper is 97.22%, and the highest accuracy rate is 99.17%. The average accuracy rate also tends to increase with the increase of sample size; the recall rate is the highest, and the highest recall rate is 99.36%. The average recall rate is 96.77%; the highest correct rate is close to 100% and is significantly higher than the other three methods; the average correct rate reaches 98.8%; the response time is the shortest; the average response time is 33 ms; and the response time increases with the increase of the sample size. (2) After using this model, tennis skills have been improved, with an average of 12 in situ flips, an average of 7 in situ rackets, an average of 5 in situ forehand draws, and an average of 3 in situ backhand draws. (3) The average forehand and backhand scores of the class after the experiment were 90 and 86; the average forehand and backhand stability were 8 and 7; and the average forehand and backhand accuracy were 31 and 29, respectively. The average depth of forehand and backhand is 36 and 32. (4) Most of the students are satisfied with this model, and they all choose to strongly agree and relatively agree, and the percentage of very agree that helps stimulate learning has reached 60.52%, and no students choose to disagree very much.
Research and Application of CNC Machining Method Based on CAD/CAM/Robot Integration
Authors: Yan Xiangsong
Published: July 2022

In order to improve the effect of intelligent CNC machining, this paper combines the CAD/CAM/Robot integration method to improve the CNC machining method and analyzes the tool path planning method and the path generation algorithm of the five-axis CNC machining machine. Through the tool processing calculation of the representative curved surface, this paper studies the basic theory, process planning, and tool parameter selection of the blade of the representative curved surface in the five-axis CNC machining and generates the blade CNC machining tool path through the simulation software. In addition, this paper analyzes the trajectory of the workpiece through the intelligent processing process and builds an intelligent processing system. Through the statistics of simulation test data, it can be seen that the CNC machining method based on CAD/CAM/Robot integration can effectively improve the intelligence of modern CNC machining and improve the effect of intelligent machining.
In Silico Elucidation of Potent Inhibitors from Natural Products for Nonstructural Proteins of Dengue Virus
Authors: Bhattarai Bibek Raj , Adhikari Bikash , Basnet Saroj , Shrestha Asmita , Marahatha Rishab , Aryal Babita , Rayamajhee Binod , Poudel Pramod , Parajuli Niranjan
Published: July 2022

Medicinal plants have been used from the beginning of human civilization against various health complications. Dengue virus (DENV) has emerged as one of the most widespread viruses in tropical and subtropical countries. Yet no clinically approved antiviral drug is available to combat DENV infection. Consequently, the search for novel antidengue agents from medicinal plants has assumed more insistence than in previous days. This study has focused on 31 potential antidengue molecules from secondary metabolites to examine their inhibitory activity against DENV nonstructural proteins through molecular docking and pharmacokinetics studies. In this research, the wet lab experiments were tested on a computational platform. Agathisflavone and pectolinarin are the top-scored inhibitors of DENV NS2B/NS3 protease and NS5 polymerase, respectively. Epigallocatechin gallate, Pinostrobin, Panduratin A, and Pectolinarin could be potential lead compounds against NS2B/NS3 protease, while acacetin-7-O-rutinoside against NS5 polymerase. Moreover, agathisflavone (LD50= 1430 mg/kg) and pectolinarin (LD50= 5000 mg/kg) exhibited less toxicity than nelfinavir (LD50= 600 mg/kg) and balapiravir (LD50 = 824 mg/kg), and the reference drugs. Further research on clinical trials is required to analyze the therapeutic efficacy of these metabolites to develop new potential drug candidates against different serotypes of DENV.
Teacher-Student Interactive Creation Strategies in Music Teaching Assisted by Computer Information Technology
Authors: Huang Ye
Published: July 2022

In music learning, the mobilization of students’ learning subjectivity needs the correct guidance of music teachers. Under the correct guidance of music teachers, students can exert their subjective initiative to realize the role of the main body of learning. In music classes, high-quality contact between teachers and students is required to meet the goals of teacher supervision and student subjectivity. This paper presents a music education approach based on a computer-assisted system and the realities of music education in China’s elementary and secondary schools. This strategy can specifically solve the problems existing in the interaction between teachers and students in Chinese music education. Furthermore, based on the actual effect of this system in music teaching for various age groups, a strategy for implementing high-quality teacher-student interaction in music teaching is proposed. The effectiveness of the system is also analyzed. This work studies the interactive creation strategy of teachers and students in music education through the computer information technology-assisted system.
Feedforward Control Combined with 4F Management on Postoperative Nursing Effects and Motor Function of Meniscus Sports Injuries: Based on a Prospective Case Analysis
Authors: Lu Qin , Yu Qunya
Published: July 2022

Background. Because active functional training and management after knee cartilage sports injury is the key to treatment, care of patients after an operation with knee cartilage sports injury is critical. Aims. To explore the effect of feedforward control combined with 4F management and after an operation nursing effect on patients with knee cartilage sports injury. Materials and Methods. According to the random number table method, 100 patients with knee cartilage sports injury who were nursed in our hospital from June 2019 to June 2021 were selected as the research objects and divided into the control group and the instance of watching, noticing, or making a statement group with 50 cases in each group according to the different nursing order. Among them, the control group adopted 4F management combined with feedforward control nursing mode: all-weather, whole-process, whole-system, and all-around services for patients. On this basis, the instance of watching, noticing, or making a statement group cooperated with early healing/repairing training to compare fear and stress-related self-test of the two groups of patients after an operation. Knee function and quality of care are scored using tables. Results. After nursing, the knee joint function score of the instance of watching, noticing, or making a statement group was higher than that of the control group, while the pain after the operation, sleep quality, fear, and stress self-rating scale scores were significantly lower than the control group (P<0.05). The whole-process management, body position placement, risk evaluation, repairing training, all-weather service, whole-system management, and comprehensive service of the two groups of patients were very much improved. The nursing quality of watching, noticing, or making a statement group was significantly higher than the control group (P<0.05). Conclusion. Feedforward control combined with 4F management combined with early repairing training can effectively reduce the fear and stress after an operation pain and sleep quality of knee cartilage sports injury and help increase the recovery of knee combined function in a good way.
Expression of DNA Helicase Genes Was Correlated with Homologous Recombination Deficiency in Breast Cancer
Authors: Long Mengping , Liu Hongjun , Wu Jinbo , Wang Shu , Liao Xin , Liu Yiqiang , Hu Taobo
Published: July 2022

Homologous recombination deficiency which is currently measured by the homologous recombination deficiency (HRD) score including score of telomeric allelic imbalance (TAI), large-scale transition (LST), and loss of heterozygosity (LOH) is highly related with sensitivity to platinum-containing drug and PARP inhibitors. DNA helicases are essential components for the homologous recombination repair process in which DNA helicases unwind double-strand DNA utilizing ATP hydrolysis. In our study, the correlation between the expression of DNA helicase genes and HRD score in breast cancer was analyzed. The overexpression in half of the DNA helicase genes was found to be highly correlated with a high HRD score both in BRCA-mutated and BRCA wild-type breast cancer. Moreover, HRD score can be predicted by a linear function contributed by five DNA helicase genes. In conclusion, our study revealed a close relation between the overexpression of certain DNA helicase genes and the deficiency of homologous recombination repair in breast cancer.
Study on the Mechanism, Prediction, and Control of Coal Wall Spalling in Deep Longwall Panels Utilizing Advanced Numerical Simulation Methodology
Authors: Murmu Sunny , Budi Gnananandh
Published: July 2022

This research looked at the occurrence of coal wall spalling, a type of longwall face failure, during the main weighing period (MWP) for panels greater than 300 m depth. FLAC3D software was exploited to simulate the ground condition of longwall panel 1 of Adriyala Longwall Project mine. The extent and severity of coal wall spalling were quantified using evaluation criteria based on the concepts of vertical stress distribution and maximum shear strain. Subsequently, a parametric analysis of thirteen factors influencing the coal wall spalling was carried out. Empirical equations for predicting coal wall spalling were suggested. Based on the parametric analysis, a coal wall spalling classification system (CWSC) chart is presented to predict spalling characteristics of coal wall that may occur at the MWP. The empirical models depicted good predictive ability with

R

2

values greater than 0.9. Parametric analysis revealed that coal wall spalling is highly sensitive to seam compressive strength, mining-induced stress, extraction height, and immediate roof characteristics. The CWSC system’s applicability to the five panels was in good agreement with field observations.
Innovative Collaborative Design of Ru Porcelain Shape Based on Digital Shape Technology
Authors: Bin Song , Siti Mastura Md Ishak , Nazlina Shaari , Velu Perumal , Wei Yang
Published: July 2022

Under the background of digital technology, computer-aided design is still in the initial stage of application in the field of design and manufacture of ceramic products. In order to improve the informatization degree of ceramic industry, advance the efficiency of product design, and satisfy the demand of personalized customization, in this paper, Ru porcelain is selected as the research object, and according to its shape characteristics, based on the 3D evolution of data combined with the image shape method and entity design, the design process of Ru porcelain shape was put forward, and the collaborative design of Ru porcelain was implemented with Yuhu spring bottle as the representative. The simulation results show that the model is highly practical and helpful to realize the convenient design of ceramic products.