bluuebunny/crossref_metadata_2025 huggingface dataset:
An English Writing Grammar Error Correction Technology Based on Similarity Algorithm
Authors: Li Qingyu
Published: July 2022

Students are the focus of English writing instruction, which emphasizes their initiative and creativity in the classroom, fosters the development of their self-directed learning and comprehensive language skills, raises their overall English level and mastery ability, and cultivates well-rounded English learners. It is to get yourself out of the dilemma of Chinese English. This study proposes an automatic error correction method for English writing grammar based on a similarity algorithm, which is applied to students during the English writing process. To address the issue of grammatical errors, this study proposes an ontology and grammar rules based on the English writing corpus. Our experimental results demonstrate that our highlighting algorithm can effectively correct grammatical errors in written English, demonstrating the algorithm’s efficacy.
Text Classification Based on Machine Learning and Natural Language Processing Algorithms
Authors: Li Hui , Li Zeming
Published: July 2022

Nowadays, with the development of media technology, people receive more and more information, but the current classification methods have the disadvantages of low classification efficiency and inability to identify multiple languages. In view of this, this paper is aimed at improving the text classification method by using machine learning and natural language processing technology. For text classification technology, this paper combines the technical requirements and application scenarios of text classification with ML to optimize the classification. For the application of natural language processing (NLP) technology in text classification, this paper puts forward the Trusted Platform Module (TPM) text classification algorithm. In the experiment of distinguishing spam from legitimate mail by text recognition, all performance indexes of the TPM algorithm are superior to other algorithms, and the accuracy of the TPM algorithm on different datasets is above 95%.
Oxidative Stress-Related Semen Quality and Fertility in the Male Arabian Yellowfin Sea Bream (Acanthopagrus arabicus) Fed a Selenium Nanoparticle-Supplemented Plant Protein-Rich Diet
Authors: Khademzade Omid , Kochanian Preeta , Zakeri Mohammad , Alavi Sayyed Mohammad Hadi , Mozanzadeh Mansour Torfi
Published: July 2022

A three-month research was conducted to evaluate the influence of supplementing a plant protein- (PP-) rich diet (60% of fish meal (FM) was replaced with a mixture of alternative PP sources) with selenium nanoparticles (Se-N) on sperm kinetics, fertilization capacity, and antioxidative responses in Arabian yellowfin sea bream (Acanthopagrus arabicus) males. In this point, graded levels of Se-N at 0, 0.5, 1, 2, and 4 mg/kg were added to the PP-rich diet. Also, a FM-based diet was used as a positive control. Two hundred and eighty-eight brooders (males:195.3±10.8 g and females:237.5±8.1 g;mean±standard error) were randomly distributed into eighteen 10 m3 rectangular concrete tanks (8 males: 8 females in each tank), and every three tanks were fed with one of the experimental feeds for three months. The seawater temperature and salinity were 18-22°C and 40-41‰, respectively, during the husbandry period. Selenium retention increased in the liver, testes, and semen of males with increasing dietary Se-N level (P<0.05). Sperm density in fish fed with 2 mg Se-N/kg PP-rich diet (42.1×109/mL) was higher than those fed control, 0, 0.5, and 1 mg Se-N/kg PP-rich diets. The percentages of sperm motility in 60 s and 300 s after activation, sperms with straight movement, the longevity of sperm motility, and fertilization rate increased with increasing Se-N level in the PP-rich diets (P<0.05). The highest and lowest semen superoxide dismutase activities were in fish fed 4 and 2 mg Se-N/kg PP-rich diets, respectively. The highest glutathione peroxidase activity in semen was in fish fed 4 mg Se-N/kg PP-rich diet, and the lowest values were in fish fed 0 and 0.5 mg Se-N/kg PP-rich diets. Total antioxidant capacity values in semen of fish fed 1 and 4 mg Se-N/kg PP-rich diets were higher than the other treatments. Fish fed with PP-rich diet without any Se-N supplementation had higher malondialdehyde level in the semen compared to the other groups. Results showed that supplementing PP-rich diet with 2-4 mg Se-N/kg can improve sperm kinetics and enhance fertility potential in A. arabicus males.
PageRank Topic Finder based Algorithm for Multimedia Resources in Preschool Education
Authors: Yu Guiping
Published: July 2022

In traditional preschool education, it is time-consuming and laborious to acquire effective materials by using artificial search method. However, with the development of Internet technology, a variety of preschool education institutions or individuals have released their own preschool education resources on the Internet. At present, multimedia technology has been popularized in many schools, and it plays a more and more significant role in teaching. In preschool education teaching, teachers use multimedia resources not only conducive to improve children’s learning efficiency but also make the teaching quality from the whole to a higher level. However, some kindergarten teachers rely too much on multimedia in teaching and do not effectively combine it with traditional teaching methods. Sometimes they even use video and related multimedia teaching resources throughout the class, which makes preschool children lack knowledge and knowledge. Therefore, this paper designs a multimedia resource retrieval system based on the theme of preschool education, which mainly achieves the extraction of multimedia resources from web pages and the analysis of multimedia-related text information. In order to design a high-performance topic search algorithm, we must first carry out page parsing, Chinese and English word segmentation, and other page preprocessing. The research results show that it is found that the text-based automatic classification of multimedia resources in preschool education and the filtering of multimedia noise in web pages can provide relevant personnel in the field of preschool education with the retrieval service of multimedia resources.
Coronal Movement during Flexion and Extension of Knee Joints
Authors: Zhang Fei , Pei Fu-Qiang , Shao Qing-Wei , Deng Yue , Dai Peng-Ju , Yang Da-Zhao
Published: July 2022

Objective. There are variabilities in the distance between the tibial tuberosity and the trochlear groove. The knee angle needs to be considered when talking about patellofemoral instability. Methods. This retrospective study analyses the MRI images of knee angles from 0 and 30 degrees in the patella dislocation group (20 cases) and in the control group (20 cases) from Dec 2017 to Dec 2019. Two experienced orthopedic physicians separately measure the study with a blind experiment method. Results. The TT-TG data of the patella dislocation group and control group are 17.88 ± 3.40 mm and 13.31 ± 3.01 mm when the knee angle is 0, which indicates a difference with statistical significance (

P
<
0.01

). The TT-TG data of the patella dislocation group and control group are 11.51 ± 3.60 mm and 7.40 ± 1.93 mm when the knee angle is at 30 degrees, indicating a statistically significant difference (

P
<
0.01

). Also, the TT-TG data of both the patella dislocation group and control group have statistically significant differences within different knee angles of the same group (

P
<
0.01

). The differences of TT-TG are 6.36 ± 2.43 mm and 5.92 ± 1.65 mm when the knee angle changes from 0 to 30, which shows no statistically significant difference (

P
>
0.01

). Conclusion. This research initially obtained the relevant MRI data of the TT-TG distance from different knee angles between the Chinese patella dislocation patient group and control group. The study received a new criterion to evaluate the TT-TG of patients with patella dislocations when the knee angle is below 30 degrees. The knee flexion angles need to be considered to measure the TT-TG distance when comprehensively evaluating patellofemoral instability. The TT-TG distance gradually increases when the knee changes from flexion to extension. The difference of the TT-TG distances shows no statistically significant difference.
Based on Virtual Reality Technology Research on Innovation and Design of Ceramic Painting Products
Authors: Jiang Yong
Published: July 2022

In order to obtain the complete color point cloud data of traditional ceramic artworks and reconstruct them efficiently, a 3D digital reconstruction method of ceramic painting products based on virtual reality technology was proposed. By the method, the 3D color point cloud data of ceramic works were collected by the camera 3D scanning equipment. The new postprocessing methods such as fusion and repair were investigated and proposed so as to obtain the complete optimized color point cloud information. The high-fidelity 3D mesh model and simplified mesh of ceramic artworks were obtained through the mesh process and the digital display platform was developed by using virtual reality technology. The experiment results showed that the 3D color point cloud data of traditional ceramic artworks were obtained by +5 exposure blend methods on average in the 6 combined modes and point cloud optimization and repair were completed. High-precision color mesh model was generated and digital promotion and publicity were carried out. The proposed 3D reconstruction technology and virtual display method made a positive exploration for the protection, inheritance, and promotion of China’s ceramic artworks and made a new attempt for the digital protection of cultural heritage by using modern science and technology.
Joint Radio Map Construction and Dissemination in MEC Networks: A Deep Reinforcement Learning Approach
Authors: Liu Xingguang , Zhou Li , Zhang Xiaoying , Tan Xiang , Wei Jibo
Published: July 2022

With the development of 6G, the rapidly increasing number of smart devices deployed in the Industrial Internet of Things (IIoT) environment has been witnessed. The radio environment is showing a trend of complexity, and spectrum conflicts are becoming increasingly acute. User equipment (UE) can accurately sense and utilize spectrum resources through radio map (RM). However, the construction and dissemination of RM incur a heavy computational burden and large dissemination delay, which limit the real-time sensing of spatial spectrum situations. In this paper, we propose an RM construction and dissemination method based on deep reinforcement learning (DRL) in the context of mobile edge computing (MEC) networks. We formulate the dissemination modes selection and resource allocation problems during RM construction and dissemination as a mixed-integer nonlinear programming problem. Then, we propose an actor-critic-based joint offloading and resource allocation (ACJORA) algorithm for intelligent scheduling of computational offloading and resource allocation. We design a novel weighted loss function for the actor network, which combines the discrete actions for offloading decisions and the continuous actions for resource allocation. And the simulation results show that the proposed algorithm can reduce the cost of dissemination by optimizing the offloading strategies and resources, which is more applicable for real-time RM applications in MEC networks.
Learning Quality Evaluation of Course Implementation Supported by Online Teaching Platform
Authors: Cao Yuewang
Published: July 2022

With the rapid development of science and technology, the use of network information technology means more and more widely; network teaching platform has become an important measure to promote the development of education and improve the quality of teaching. The network teaching platform has been widely used and plays a vital role in the construction of teaching informationization and modernization. However, the study of student learning quality evaluation under the network teaching platform has become a huge challenge. In order to solve this problem, this paper takes the teaching of basic Python course as an example, adopts data-driven theory, and combs the teaching process of network teaching platform. Curriculum can be divided into class leading learning stage, stage of studies in class, and after class extension stage and uses the panel method, literature query method, mathematical statistics, performance appraisal, and questionnaire survey method to analyze the factors influencing the quality of learning curriculum implementation, and compared with the traditional classroom teaching, build more indicators of curriculum implementation under the network teaching platform to support students’ learning quality evaluation scheme. The experimental results show that, through the statistics of the evaluation index data, using the analysis method of the KMO coefficient and the KMO test, the three stages of the curriculum implementation of the KMO coefficient and the KMO test prove that the constructed learning quality evaluation scheme has high credibility and good structural validity. Based on class leading learning stage, stage of inquiry learning in the class, after class extension stage, and students’ learning quality correlation analysis, using Pearson correlation test, it is concluded that different index correlations with students’ academic performance prove students’ input and participation, learning ability and innovation ability, self-study ability and students’ learning achievement of great relevance. It has a direct impact on students’ learning quality. The results of this study provide powerful data and theoretical support for educators to carry out network teaching.
Multienergy Management Strategy of Fuel Cell Hybrid Vehicle Based on Distributed Parameter Model
Authors: Li Mengjie , Liang Qianchao , Hu Jinyi , Liang Yifan , Zhao Jianfeng
Published: July 2022

To increase the fuel efficiency of fuel cells, lengthen their useful lives, and fulfil the demands for high energy and high power during the operation of hybrid electric vehicles. This paper's goal is to thoroughly examine the distributed parameter model-based multienergy management technique of fuel cell hybrid electric vehicles. Firstly, the simplified model of a hybrid system is constructed according to the distributed parameter model, and the fuel cell model, unidirectional DC/DC converter, and battery are described in detail. The multienergy management of hybrid electric vehicles based on improved deep Q-learning is adopted, the multienergy management strategy based on deep Q-learning is designed, so as to reduce fuel consumption and improve the working efficiency of fuel cells, optimize the energy distribution of lithium batteries and fuel cells, and adopt the experience playback mechanism of summation tree structure in the process of strategy training to complete the multienergy management of hybrid electric vehicles. The strategy described in this study can successfully increase the overall power performance of fuel cell hybrid vehicles, extend the battery's service life, and increase fuel economy, according to simulation results, which has a certain practical value.
Application of Refined Nursing Combined with Comprehensive Treatment of Traditional Chinese and Western Medicine in Gastrointestinal Dysfunction after Tumor Operation
Authors: Su Hongqing , Wen Yuexian , Kang Dandan
Published: July 2022

After surgical treatment, the gastrointestinal function of tumor patients is inhibited for a short time. Refined nursing is beneficial to the recovery of gastrointestinal function of tumor patients after operation. Traditional Chinese medicine and Western medicine have their own advantages in the treatment of gastrointestinal dysfunction after tumor operation and the combined application of the two is more ideal. Therefore, on the premise of refined nursing, we should carefully study the efficacy of integrated traditional Chinese and Western medicine in the treatment of postoperative gastrointestinal dysfunction in tumor patients. Fifty patients with gastrointestinal dysfunction after tumor surgery admitted to Xiamen University Affiliated Zhongshan Hospital from June 2021 to August 2022 were retrospectively selected. Twenty two of them received refined care + Western medicine (control group, CG) and the other 28 received refined care + Western medicine + moxibustion and thumb-tack needle Chinese medicine (observation group, OG). We compared the recovery of gastrointestinal function, inflammatory factors, negative emotions, sleep quality, length of stay, medical expenses, and adverse reactions. The postoperative recovery effect of gastrointestinal function in the OG was better than that in the CG. The IL-8 level and TNF -α level in OG were lower than those in CG. Relative to CG, the OG had significantly low SDS scores, SAS scores, PSQ1 scores, length of hospital stay, and medical expenses. The OG incidence of adverse reactions was 28.57%; it was significantly lower than 59.09% in the CG. Refined nursing with integrated Chinese and Western medicine therapeutic interventions can promote the recovery of gastrointestinal tract function, relieve anxiety and depression, and improve sleep quality in patients with postoperative gastrointestinal dysfunction after tumor surgery.
An Efficient Data Sharing Scheme for Privacy Protection Based on Blockchain and Edge Intelligence in 6G-VANET
Authors: Wang Zhihua , Xu Yingheng , Liu Jiahao , Li ZhenYu , Li Zeminghui , Jia Hongyong , Wang Dinghua
Published: July 2022

With the substantial increase in the number of smart cars, vehicular ad hoc network (VANET), where data can be shared between vehicles to enrich existing vehicle services and improve driving safety, is gaining more and more attention, thus creating a more efficient intelligent transportation system. Moreover, the in-depth research and development of 6G and AI technology further strengthen the interconnection of various entities in VANET and can realize edge intelligence, which fundamentally enhances the efficiency of data sharing. However, reliable transmission and secure storage of data have always been a great challenge in data sharing. Although some schemes store shared data in the blockchain, most of the consensus mechanisms they use employ full nodes to verify signature information and timestamps, which cannot effectively judge the reliability of the shared data itself. Some other schemes use scoring mechanisms to evaluate data uploaded by vehicles, but these methods can be affected by network hardware failures and cannot effectively detect duplicate data. In addition, participants’ privacy may also be disclosed in the process of data sharing, such as participants’ location and identity information. Therefore, to address the above problems, this paper proposes a data sharing scheme in 6G-VANET, which can not only ensure the reliability and security of shared data but also protect the privacy of participants. Firstly, a consortium chain is adopted to realize the secure storage of shared data in 6G-VANET, which meets the requirements of tamper-proof and traceability of data. Secondly, a voting consensus mechanism is designed in combination with smart contract to ensure the reliability of data. Thirdly, the trained word2vec natural language processing model is deployed to edge nodes to realize edge intelligence, effectively eliminate the duplicate shared data, and enhance storage efficiency. Finally, a participant privacy protection mechanism is designed using the Private Set Intersection (PSI) protocol, and a secure and efficient data sharing scheme is finally realized. The effectiveness of the proposed scheme is demonstrated by security analysis and experimental evaluation. The experimental results show that the time and space overhead of blockchain can meet the practical requirements, and the proposed PSI protocol of large-scale vehicles can be completed in a short time.
Efficacy of Gamma Globulin Combined with Azithromycin Sequential Therapy in the Treatment of RMPP and Its Effect on Th1/Th2 Cytokine Levels
Authors: Qi Jie , Jia Fang , Tian Hui , Yang Shengmei
Published: July 2022

Objective. To investigate the efficacy of gamma globulin combined with azithromycin sequential therapy in the treatment of children with refractory mycoplasma pneumonia and its effect on Th1/Th2 cytokine levels. Method. From January 2021 to January 2022, 100 children diagnosed with refractory mycoplasma pneumonia were randomly divided into 2 groups (50 cases in each one), the control group was treated with azithromycin plus comprehensive basic treatment, and the treatment group was treated with combined treatment on the basis of the control group, gamma globulin therapy; the treatment effect and cytokine levels of the two groups were compared. Results. Th1, Th2, and Th1/Th2 before treatment were not significantly different between the two groups. Th1, Th2, and Th1/Th2 in the treatment group were significantly downregulated compared with those in the control group after treatment. The levels of IgG, IgA, and IgM in the treatment group were not significantly different from those in the control group before treatment but were significantly upregulated after treatment. IL-10, IL-6, and IL-2 levels were also significantly increased in the treatment group. The disappearance time of clinical symptoms such as fever, cough, and pulmonary rales in the treatment group was significantly shorter than that in the control group, and the cure rate in the treatment group was significantly better than that in the control group. Conclusion. The clinical effect of gamma globulin combined with azithromycin sequential therapy in the treatment of children with refractory mycoplasma pneumonia is remarkable, which can reduce inflammatory factors, improve patients’ immunity, and promote disease recovery.
Arisaema heterophyllum Blume Monomer Stigmasterol Targets PPARγ and Inhibits the Viability and Tumorigenicity of Lung Adenocarcinoma Cells NCI-H1975
Authors: Song Na , Wang Jing , Lai Zonglang , Liang Shuting , Zou Wenjuan , Wang Juan , Zheng Dandan , Li Ying , He Yuxi , Cheng Jun , Wu Yue
Published: July 2022

To clarify the regulatory effect and molecular mechanism of Arisaema heterophyllum Blume (AhBl) monomer stigmasterol on lung adenocarcinoma in human lung adenocarcinoma cells NCI-H1975 cultured in vitro and in nude mice. Oil red O staining, free fatty acid detection, adenosine triphosphate (ATP), and NADPH were applied to elucidate the regulatory effect of stigmasterol on the energy metabolism of NCI-H1975 cells. Simultaneously, colony formation assay and nude mouse tumorigenesis were performed to clarify the underlying mechanisms of stigmasterol on the proliferation and tumorigenesis of NCI-H1975 cells. Furthermore, peroxisome proliferator-activated receptor gamma (PPARγ) inhibitor GW9662 was supplemented to determine the expression changes of cyclins to clarify the regulation mechanism of stigmasterol. The results revealed that stigmasterol administration markedly inhibited the viability but promoted lipid deposition of NCI-H1975 cells. Meanwhile, the reduction of cell energy metabolism affected cell proliferation and colony formation. qPCR and western blot assays indicated that stigmasterol played a role in regulating the expression of cyclins and PPARγ signaling pathway proteins. Nude mouse tumorigenesis suggested that tumor size and weight in the stigmasterol-treated group were apparently lower as compared with the control group. Tumor tissue cells developed varying degrees of degeneration and large areas of ischemic necrosis presented in the central and peripheral cells. Immunohistochemistry results revealed that Ki67 expression in the stigmasterol group was substantially inhibited, while PPARγ expression was greatly elevated as compared with the control. GW9662 could mediate the inhibitory effect of stigmasterol on NCI-H1975 cells. The current study demonstrated that stigmasterol targeted PPARγ and inhibited the viability and tumorigenicity of lung adenocarcinoma cells NCI-H1975.
Research on the Evaluation of Multi-Energy Microgrid under the Background of New Power System
Authors: Du Wenxin , Han Tianbo , Hu Shizhao
Published: July 2022

As a key means to elevate low-carbon energy transformation in China, multi-energy microgrid accelerates the construction of new power systems. In order to scientifically evaluate the benefits of multi-energy microgrids, we proposed a benefit evaluation index system from the dimensions of economy, reliability, low carbonization, and intelligence. Considering the relationship between the evaluation indicators, this paper innovatively proposed a multi-energy microgrid benefit evaluation model based on AHP-VWT-MEEM. In addition, this paper selected different multi-energy microgrid demonstration projects in the China Southern Power Grid Company Limited’s region for example analysis. In the example analysis, through the comparison of the comprehensive benefits of the three projects, the comprehensive benefit of the project 3 is the best. On this basis, from the specific configuration plan of Project 3, it can be concluded that the configuration of larger capacity thermal storage can realize the "thermal decoupling" of cogeneration, thereby improving the flexible adjustment capability of the demonstration area, promoting the consumption of renewable energy, and obtaining more considerable comprehensive benefits. At the same time, it is pointed out that the comprehensive benefit evaluation result can be improved by appropriately reducing the investment cost of project 3.
Effects of Sodium-Glucose Cotransporter-2 Inhibitors on Urine Albumin to Creatinine Ratio in Type 2 Diabetes Mellitus Patients and Medication Care
Authors: Wang Dong-Dong , Zhang Cun , Yang Yang , He Su-Mei , Zhu Ping , Chen Xiao
Published: July 2022

Objectives. The purpose of this study was to explore the effects of sodium-glucose cotransporter-2 (SGLT-2) inhibitors on urine albumin to creatinine ratio (UACR) in type 2 diabetes mellitus (T2DM) patients and to recommend appropriate medication care scheme. Methods. 8371 T2DM patients from four dapagliflozin studies and two canagliflozin studies were collected for analyzing with nonlinear mixed effect model (NONMEM). The change rates of UACR from baseline were intended to be evaluation indicators. Results. In the present study, there was no significant difference in the effects on UACR using dapagliflozin or canagliflozin treatment in T2DM patients. The maximal effect (

E

max

) and the treatment duration of reaching half of

E

max

(ET50) from SGLT-2 inhibitors on UACR in T2DM patients were -19.2% and 0.448 weeks, respectively. Further, the treatment duration to reach 25%, 50%, 75%, and 80%

E

max

was 0.150 weeks, 0.448 weeks, 1.344 weeks, and 1.792 weeks, respectively. Namely, for achieving the plateau period (80% of

E

max

) of SGLT-2 inhibitors on UACR in T2DM patients, 10 mg/day dapagliflozin (or 100 mg/day canagliflozin) should be taken for at least 1.792 weeks. Conclusions. To our knowledge, the present study explored the effects of SGLT-2 inhibitors on UACR in T2DM patients, meanwhile, recommended appropriate medication care scheme for the first time.
Classification of EEG Signals Using Neural Network for Predicting Consumer Choices
Authors: Sheela sobana Rani K. , Pravinth Raja S , Sinthuja M. , Vidhya Banu B , Sapna R. , Dekeba Kenenisa
Published: July 2022

EEG, or Electroencephalogram, is an instrument that examines the brain’s functions while it is executing any activity. EEG signals to aid in the identification of brain processes and movements and are thus useful in the detection of neurobiological illnesses. Pulses have a very weak magnitude and are recorded from peak to peak, with pulse width ranging from 0.5 to 100 V, which is around 100 times below than ECG signals. As a result, many types of noise can easily influence them. Because EEG signals are so important in detecting brain illnesses, it is critical to preprocess them for accurate assessment and detection. The crown of your head The EEG is a weighted combination of the signals generated by the different small locations beneath the electrodes on the cortical plate. The rhythm of electrical impulses is useful for evaluating a broad range of brain diseases. Hypertension, Alzheimer, and brain damage are all possibilities. We can compare and distinguish the brainwaves for different emotions and illnesses linked with the brain by studying the EEG signal. Multiple research studies and methodologies for preprocessing, extraction of features, and evaluation of EEG data have recently been created. The use of EEG in human-computer communication could be a novel and demanding field that has acquired traction in recent years. We present predictive modeling for analyzing the customer’s preference of likes and dislikes via EEG signal in our report. The impulses were obtained when clients used the Internet to seek for multiple items. The studies were carried out on a dataset that included a variety of consumer goods.
Design of a Multimodal Teaching Method for Business English in a Wireless Network Environment
Authors: Liu Fen , Deng Laiying
Published: July 2022

In the background of the information age of “Internet+,” the traditional teaching mode of business English has many drawbacks in terms of curriculum, teaching content, teaching methods, and teachers’ backgrounds and cannot adapt to the needs of the times. Therefore, business English teaching should actively follow the trend of “Internet + education” and continue to innovate in a multimodal way. The multimodal teaching mode of “wireless network + business English” is in line with the background of “Internet+,” optimizing teaching resources to the maximum extent and truly realizing the effective combination of Internet and business English teaching. The Internet-based multimodal innovation can be carried out in the four elements of business English teaching: environment, task, learner, and guide teaching. The specialization and modernization of business English teaching can be promoted through the optimization of O2O multisituational classroom, the application of multimodal tasks in three-dimensional teaching materials, the communication of diversified categories of students, and the configuration of multilevel teachers across fields.
Outcomes of Anterior Chamber, Sulcus, and Pars Plana Glaucoma Drainage Device Placement in Glaucoma Patients
Authors: Samuel Sandy , Chang Enchi K. , Gupta Sanchay , Chachanidze Marika , Neeson Cameron E. , Miller John B. , Chang Ta Chen , Solá-Del Valle David A.
Published: July 2022

Purpose. To assess outcomes of anterior chamber (AC), sulcus, and pars plana (PP) glaucoma drainage device (GDD) placement in glaucoma patients. Patients and Methods. Retrospective evaluation of glaucoma patients who underwent GDD insertion in the AC, sulcus, or PP at Massachusetts Eye and Ear between November 2016 and May 2021. Patients who received AC, sulcus, and pars plana tubes were selected using simple random sampling, and the first 40 patients meeting inclusion criteria were analyzed. Main outcome measures were cumulative success probabilities from Kaplan-Meier (KM) analyses, intraocular pressure (IOP), medication burden, and complication rates. Results. The PP group had a larger proportion of Ahmed GDDs and was younger on average with less severe glaucoma compared to patients with AC or sulcus tubes. The PP group had a higher proportion of mixed-mechanism glaucoma and lower proportion of primary open-angle glaucoma. With success defined as IOP reduction ≥20% and 5 < IOP ≤ 21 mm Hg, the Kaplan-Meier cumulative success probabilities for all three GDD locations were not significantly different. No significant differences were found in complication rates between all groups after 3 months. Patients with PP GDD had significantly lower medication burden than those with AC or sulcus GDDs up to 1.5 years postoperatively (1.7 ± 1.1, 3.0 ± 1.4, and 2.8 ± 1.2 for PP, AC, and sulcus, respectively;

P
=
0.017

). Conclusion. PP GDDs may be more effective in lowering medication burden than AC or sulcus tubes without compromising long-term safety.
Promotion and Influence of Big Data and Artificial Intelligence in Field of Drama and Film
Authors: Li Shanshan
Published: July 2022

As a member of the oldest art family of human beings, drama is also a very important part of human civilization. With the development of technology, more and more types of drama film and television appear. In today’s society, bad films and commercial films are emerging one after another. The intervention of capital has brought a very poor experience to moviegoers and is not conducive to the development of the entire field of drama and film. The further development and scientific promotion of the field of drama film and television has become a relatively important issue. In this context, this paper takes this as the starting point, integrates big data and artificial intelligence algorithms, and aims to analyze the promotion and influence in the field of drama and film. It has existed for a long time in the fields of physics, biology, environmental ecology, and other industries such as military, finance, and communication, but it has attracted people’s attention due to the development of the Internet and information industry in recent years. The article introduces the transition of the mainland film system and the manifestations of conflict in plot art and film and television plots. It uses the convolutional neural network algorithm in deep learning to build the system. This paper adopts an online survey, distributes it to moviegoers nationwide, and collects 4,000 valid samples for analysis of moviegoers’ occupation and monthly income. In terms of the occupational distribution of the audience, the proportion of white-collar workers in the company is the highest at 40%, the student group only accounts for 17.4%, and the retired worker group accounts for the smallest proportion, at 0.6%. To sum up, the structure of Chinese films has shifted from a younger, student-dominated, middle-income group to a mature, workplace-oriented, middle- and high-income group. It has successfully completed the analysis of the promotion and impact of big data and artificial intelligence in the field of drama, film, and television.
A Sensitive Fluorescent Immunoassay for Prostate Specific Antigen Detection Based on Signal Amplify Strategy of Horseradish Peroxidase and Silicon Dioxide Nanospheres
Authors: Li Lihua , Zhang Wenzhi , Wei Yan , Yu Lizhen , Feng Dexiang
Published: July 2022

A simple, sensitive, and fluorescent immunoassay for the detection of prostate-specific antigen (PSA) based on horseradish peroxidase and silicon dioxide nanospheres as a signal amplification strategy has been described. In the design, the primary antibody (Ab1) of PSA was first immobilized on the 96-well plates via physical adsorption between polystyrene and hydrophobic groups of the antibody molecule. The silicon dioxide nanospheres (SiO2 NSs), with large surface area and good biocompatibility, were loaded with horseradish peroxidase (HRP) and horseradish peroxidase-labeled secondary antibodies (HRP-Ab2) as signal amplification systems. In the presence of PSA, a sandwich-type immunocomplex composed of Ab1-Ag-HRP-Ab2 had been formed. Fluorescence technology was employed to obtain the response signal of the immunoassay in the L-tyrosine and H2O2 systems. Experiment results showed that a strong and stable fluorescent signal at 416 nm (excitation wavelength: 325 nm) was observed, and the changes in fluorescent intensity were related to the levels of PSA. Under the optimal conditions, the relative fluorescence intensity was linear with the logarithm of PSA concentration from 0.03 to 100 ng·mL−1, with a detection limit of 0.01 ng·mL−1 (at a signal/noise ratio of 3). In contrast to other fluorescent immunoassays, the sandwich-type immunoreaction based on the high binding ELISA plates has the advantages of being simple, stable, and easy to operate, high selectivity, small sample quantity, etc., which can be widely used in the selective detection of a variety of targets, from DNA to proteins and small molecules. Such fluorescent immunoassays should be feasible for the fields of molecular diagnosis and other life science fields in the future.
Coordinated Development of China’s Regional Economy and Ethnic Diversity under the Background of Big Data and the Internet of Things
Authors: Miao Hongliang
Published: July 2022

In the context of big data and the Internet of Things, the development of the Chinese nation is changing with each passing day, and the regional economic development has also shown a long-handed trend. With the development of the diversity of the Chinese nation, it has become more and more prosperous, which drives the sustainable development of the regional economy, but in the process of regional economic development, it also reflects the various contradictions and problems of my country’s economy in the ethnic minority regional economy. By studying the current status of Chinese nation diversity and regional economic development under the background of big data and the Internet of Things, this article pointed out the problems and contradictions in the development of national diversity and regional economic development, through the use of thermodynamic computing models for data analysis, and based the status quo of the economic development of Xinjiang region is an example, and it proposes measures to promote the coordinated development of the Chinese nation’s diversity and regional economic coordinated development.
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/PH

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Queuing Model in Randomly Changing Environments for Traffic Circulation Systems
Authors: Zhu Juanxiu , Hu Lu , Xie Han , Li Kehong
Published: July 2022

Robust optimal design of circulation systems (e.g., roads for vehicles or corridors for pedestrians) relies on an accurate steady-state traffic flow model that considers the effect of randomly changing environmental factors (e.g., daily periodicity and weather). Most analytical models assume that the customer interarrival time and service time of circulation facilities follow the exponential distribution with fixed rate parameters, which is unrealistic in most cases. In this paper, we develop a stationary PH

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state-dependent queuing model in a randomly changing environment (RE), which is represented by a Markov chain. The model simultaneously considers the general randomness of arrival and service, the randomly varying rate parameters, and the state-dependent service (the travel time increases with the number of customers). The existing matrix analytic scheme (MAS) algorithm is extended to solve the proposed model because it avoids the explicit calculation of probability distributions. The space complexity of the algorithm is only linear in the number of RE states and is independent of the enormous (four-dimensional) state space of the Markov process. Its time complexity is a linear function of the product of the queue capacity and the number of RE states. Our model is validated versus simulation estimates. The obtained conditional performance measures can accurately capture the queue accumulation and dissipation and reveal the effect of randomly changing environments. Numerical experiments provide some interesting findings. (1) The proposed stationary model coincides with the transient M(

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fluid queuing model under special conditions. (2) Under high traffic intensities, increasing the randomness in the duration time of the RE state leads to an obvious growth in the conditional queue length. (3) An increase in the facility length leads to an increase or a decrease in the average output rate, depending on whether the congestion dissipates effectively in one cycle. (4) A larger width is required to obtain the maximum average output rate for traffic demand with a greater nonuniformity.
A Novel SVM Network Using HOG Feature for Prohibition Traffic Sign Recognition
Authors: Liu Yang , Zhong Wei
Published: July 2022

To recognize prohibition traffic sign, this paper proposes a novel method that is trained by a small number of samples and uses the feature of histogram of oriented gradient (HOG) and support vector machine (SVM) network. The recognition method is mainly divided into three stages. The first stage is image preprocessing, which includes image interception based on ellipse detection, image resizing, and Gamma correction. In the part of image interception, a new ellipse detection method called RHT_MCN is proposed based on RHT, which uses the maximum coincidence number (MCN) of image edge points and detected ellipse edge to choose the final ellipse for image interception. The second stage is the feature extraction of HOG. The third stage is the prohibition traffic sign recognition (PTSR) based on SVM network. In the design and implementation of the PTSR model, a new single-layer SVM network is proposed. The ascending spiral training method of the recognition model is introduced in detail. Finally, the data from GTSRB is used to test and analyze the prohibition traffic sign recognition method. The method is proven to have good applicability.
Optimization Calculation Method and Mathematical Modeling of Big Data Chaotic Model Based on Improved Genetic Algorithm
Authors: Zhang Zhicheng , Zhang Yan
Published: July 2022

In order to find a chaotic trajectory sequence with strong global optimization ability to help the genetic selection of direction after the reversal of chemotaxis, an improved genetic algorithm based on chaos optimization is proposed by combining the characteristics of chaotic motion with the improved genetic algorithm. The optimal coverage problem in sensor networks can carry out fine optimization search on local areas. The results show that the overall trend of fitness and optimization efficiency is relatively stable. The optimization efficiency will be gradually improved with the continuous progress of time and genetics, and the error analysis will be reduced. This will greatly improve the impact of various adverse factors in the optimization process. In addition, the change rate of fitness is basically kept at a high change rate, which also reflects that the basic framework of the model is very excellent, and the whole algorithm structure and data processing are improved by 54%. The improved genetic algorithm proposed in this paper is used to adjust and optimize the controller parameters. When the uncertain parameters change greatly, the control system still has good control quality and strong robustness.
Designing of Neuro-Fuzzy Controllers for Brushless DC Motor Drives Operating with Multiswitch Three-Phase Topology
Authors: Vinay Kumar Ch. , Rao G. Madhusudhana , Raghu Ram A. , Prasanna Kumar Y.
Published: July 2022

Brushless DC motors are simple in construction, high efficiency, less noise, and high reliability, which are not replaceable motors in specific applications compared to other motor drives. It has a facility for its multivariable system, nonlinear control process, and powerful coupling system. This paper proposes to design the neuro-fuzzy controllers for its multiple converters switching to improve the power factor and minimize the BLDC motor switching losses. Compared with conventional controllers, this controller will develop the power factor and optimize the current ripples concerning time and torque. The working model of the BLDC motor may be presented here. A nonlinear load will be applied to the BLDC motor to determine the speed, current, and torque. The multiple switches designed with the proposed controllers are connected with the converter’s DC link to boost the voltage. The fuzzy logic controller is implanted to adjust the speed of the neural network and is also designed for the analysis of the stability of the system. The proposed controllers compare the rate at different speeds, torque, currents, and rotor angle positions. Finally, the proposed controller for multiple converter switches performs better than the conventional controllers.
[Retracted] Simulation of Migration Law of Organic Pollutants in Circulating Wells
Authors: Li Xiaojie , Zhang Jianwei , Yang Zhuojing
Published: July 2022

Groundwater resources are one of the most important freshwater resources for human beings. The protection of groundwater resources is an important measure for human survival. Therefore, it is extremely important to discuss the treatment of pollutants in groundwater. The purpose of this paper is to simulate and analyze the migration law of organic pollutants using the experimental circulating well. In the analysis, this paper uses the gas‐liquid‐solid three‐state model to simulate the pollutants for organic pollutants. It independently analyzes pollutants in different states. For the movement law, this paper not only simulates the vertical transition circulation well in the laboratory but also simulates the transport law of pollutants in the well. The experimental results show that in the laboratory environment, the simulated value of the circulation well designed in this paper is not far from the actual value, and the accuracy rate is more than 90%. And according to the movement law of organic pollutants, it is found that the variable flow rate and the dispersion, porosity, and thickness of the skin have a great influence on the migration of pollutants.
[Retracted] To Explore the Application of PDCA in Hemodialysis Center and Its Effect on the Maintenance of Internal Fistula
Authors: Su Xiaomei , Cui Yihong , Pu Zunguo , Zhou Yaqing
Published: July 2022

Background. The survey found that in recent years, with the incidence of chronic kidney disease (CKD) increasing, some patients with CKD even progressed to end‐stage renal disease. Luckily, progressive hemodialysis technology and nursing level can improve the quality of life and prognosis of patients. Objective. To explore the application of plan‐do‐check‐adjust (PDCA) cycle in the management of nurses in hemodialysis center and its effect on the maintenance of internal fistula in patients. Methods. In this study, a randomized controlled trail (RCT) was used to select 90 patients who underwent maintenance hemodialysis in the hemodialysis center of our hospital from January 2018 to June 2021 as objects. They were divided into a PDCA group (with PDCA nursing management) and routine group (with routine nursing management) by random number table with each of 45 cases for 6 months to compare the differences of the internal fistula complications, internal fistula maintenance quality, patients’ microinflammatory state, and satisfaction with nursing, as well as nursing staff’s operational and theoretical performance between the two groups. Results. There was no significant difference in CRP, IL‐1, TNF‐α, and IL‐6 levels between the two groups before intervention (P > 0.05); after that, these levels in the PDCA group were lower than those in the routine group, with statistically significant difference (P < 0.05); before intervention, there was no statistically significant difference in the qualification rate of blood flow, the awareness rate of health education, and the incidence of nursing defects between the two groups (P > 0.05); after that, the qualification rate of blood flow and the awareness rate of health education among nurses in PDCA group were higher than those in routine group, while the incidence of nursing defect accidents in the PDCA group was lower than that in routine group, and the differences were statistically significant (P < 0.05); before intervention, there was no significant difference in the complication rate between the two groups (P > 0.05); after that, the complication rate of the PDCA group was lower than that of the routine group, and the differences were statistically significant (P < 0.05); after intervention, the theoretical assessment and practical skills assessment scores of the PDCA group were higher than those of the routine group, and the differences were statistically significant (P < 0.05); after intervention, the nursing satisfaction of the PDCA group was higher than that of the routine group, and the differences were statistically significant (P < 0.05). Conclusion. The application of PDCA approach in the management of nurses in hemodialysis centers can effectively improve the quality of internal fistula management and improve the practical and theoretical level of nurses, as well as reduce the microinflammation of patients.