bluuebunny/crossref_metadata_2025 huggingface dataset:
Soil Restoration Practices on Priming Effect Intensity and Carbon Fluxes
Authors: Amadou Issoufou Abdourhimou , Hamadou Younoussa Bachirou , Soumana Idrissa , Mahamane Ali
Published: August 2022

The decomposition of soil organic matter (SOM) is one of the most important processes influencing the global carbon (C) cycle, the physicochemical characteristics of soils, and the mineralization of nutrients for plant growth and soil food webs. Yet, priming effects are considered to be large enough to influence ecosystem carbon fluxes. Here, we have tested the effects of soil restoration practices on priming effects and carbon fluxes. Our results suggest that indirect effects such as altered stabilization of older C associated with the increased inputs of fresh plant inputs (“priming”) add uncertainty to the prediction of future soil C responses. In addition, restoration influences the abundance and diversity of decomposers, as well as the soil microbial community, by inducing up to more CO2 emission with fresh millet straw addition in fresh state than the predecomposed one. Restoration had strongly increased the impact by up to 22.7%, while the priming effect (PE) mineralization did not increase. The latter of the nonrestored site was lower than that of the restored site by 14.9–22.7%; the lowest mineralization per unit carbon was recorded in the nonrestored site. Through the “4 per 1000” initiative, it has been very recently demonstrated that priming effects could have a noticeable impact on soil carbon sequestration. The study has revealed that the degraded soil played a dominant positive role in the soil organic carbon mineralization. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios.
Ultrasound Evaluation of Pelvic Floor Function after Transumbilical Laparoscopic Single-Site Total Hysterectomy Using Deep Learning Algorithm
Authors: Zhu Yan , Zhang Jiamiao , Ji Zhonglei , Liu Wen , Li Mingyue , Xia Enhui , Zhang Jing , Wang Jianqing
Published: August 2022

This study was aimed at investigating the ultrasound based on deep learning algorithm to evaluate the rehabilitation effect of transumbilical laparoscopic single-site total hysterectomy on pelvic floor function in patients. The bilinear convolutional neural network (BCNN) structure was constructed in the ultrasound imaging system. The spatial transformer network (STN) was used to preserve image information. Two algorithms, BCNN-R and BCNN-S, were proposed to remove sensitive information after ultrasonic image processing, and then, subtle features of the image were identified and classified. 80 patients undergoing transumbilical laparoscopic single-site total hysterectomy in hospital were randomly divided into a control group and a treatment group, with 40 cases in each group. In the control group, conventional ultrasound was used to assess the image of pelvic floor function in patients undergoing laparoendoscopic single-site surgery (LESS); in the observation group, ultrasound based on deep learning algorithm was used. The postoperative incision pain score, average postoperative anus exhaust time, average hospital stay, and postoperative satisfaction of the two groups were evaluated, respectively. The highest accuracy of constructed network BCNN-S was 88.98%; the highest recall rate of BCNN-R was 88.51%; the highest accuracy rate of BCNN-R was 97.34%. The operation time, intraoperative blood loss, and exhaust time were similar between the two groups, and the difference had no statistical significance (

P
>
0.05

). The numerical rating scale (NRS) scores were compared, the observation group had less pain, the difference between the two groups had statistical significance (

P
<
0.05

), and the postoperative recovery was good. The BCNN based on deep learning can realize the imaging of the uterus by ultrasound and realize the evaluation of pelvic floor function, and the probability of pelvic floor dysfunction is small, which is worthy of clinical promotion.
Sulforaphane Upregulates Cultured Mouse Astrocytic Aquaporin-4 Expression through p38 MAPK Pathway
Authors: Yang Canhong , Qin Sisi , Zhang Jiafa , Wang Yuanyuan , Li Huan , Lü Tianming
Published: August 2022

Protein misfolding and/or aggregation are common pathological features associated with a number of neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson disease (PD). Abnormal protein aggregation may be caused by misfolding of the protein and/or dysfunction of the protein clearance system. Recent studies have demonstrated that the specific water channel protein, aquaporin-4 (AQP4), plays a role in the pathogenesis of neurodegenerative diseases involving protein clearance system. In this study, we aimed to investigate the role of sulforaphane (SFN) in the upregulation of AQP4 expression, along with its underlying mechanism using cultured mouse astrocytes as a model system. At low concentrations, SFN was found to increase cell proliferation and result in the activation of astrocytes. However, high SFN concentrations were found to suppress cell proliferation of astrocytes. In addition, our study found that a 1 μM concentration of SFN resulted in the upregulation of AQP4 expression and p38 MAPK phosphorylation in cultured mouse astrocytes. Moreover, we demonstrated that the upregulation of AQP4 expression was significantly attenuated when cells were pretreated with SB203580, a p38 MAPK inhibitor. In conclusion, our findings from this study revealed that SFN exerts hormesis effect on cultured mouse astrocytes and can upregulate astrocytic AQP4 expression by targeting the p38 MAPK pathway.
Effect of Nano Titanium Oxide with Different Surface Treatments on Color Stability of Red-Tinted Silicone Rubber
Authors: Wang Yalin
Published: August 2022

To improve the color stability of facial prosthesis silicone rubber, this paper studied the effect of nano titanium oxide with different surface treatments on the color stability of red pigment-colored silicone rubber. Under the simulated sunlight aging condition, this paper takes MDX4-4210 silicone rubber as the matrix, silicon aluminum-coated nano TiO2 as the shading agent, and cadmium red oil paint as the colorant, and it observes the values of silicon aluminum-coated nano-TiO2 silicone rubber film with 1 mm thickness and different concentrations (0, 0.05%, 0.10%, and 0.15%) before and after aging. The experimental results showed that in the four concentrations of silicon aluminum-coated nano-TiO2 film, the

Δ
E
,
Δ

L

∗

,
 
Δ

a

∗

,
 
Δ

b

∗

values gradually decreased with the increase of the concentration of silicon aluminum-coated nano-TiO2. The lowest was in the 0.10% group; however, it increased in the 0.15% group. There was a significant difference among the concentration groups

P
<
0.05

. The method of covering nano-TiO2 silicone rubber film with different concentrations of silicon aluminum has a certain effect on delaying the discoloration of prosthetic silicone rubber, and it provides a new idea for improving the color stability of the prosthetic silicone rubber.
[Retracted] Study on BCVA, CMT, CME, Curative Effect, and Prognostic Value of DR Sufferers Based on Surgical Therapy Combined with VEGF Therapy at Different Times
Authors: Wang Jian
Published: August 2022

In order to explore the efficacy and prognostic value of best corrected visual acuity (BCVA), central macular retinal thickness (CMT), and cystoid macular edema (CME) in diabetic retinopathy (DR) sufferers based on surgical therapy combined with vascular endothelial growth factor (VEGF) therapy at different times, a total of 170 cases of DR sufferers who visited our hospital from March 2019 to March 2021 are analyzed. All patients are randomly divided into control group and study group, with 85 cases and 85 eyes in each group. In addition, the contrast set received 2 therapies for 1.5 months/time, and the study set received 3 therapies for 1 month/time. The experimental results show that the BCVA of the two sets is notoriously enhanced. Besides, CMT and CME in the study set decrease more than those in the contrast set, and the blood vessel density of retinal capillaries in the contrast set and the examination set is notoriously enhanced. For DR sufferers, 1 month/time of anti‐VEGF therapy can effectively enhance the sufferers’ visual acuity, CMT and CME. It is suggested that the clinical application of 1 month/time of anti‐VEGF to DR sufferers can enhance the clinical therapeutic effect of sufferers and reduce the prognosis and recurrence.
Research on Clustering Algorithm Based on Improved SOM Neural Network
Authors: Shi Chengxiang , Li Xiaoqing
Published: August 2022

Clustering algorithm is a statistical method to study sample classification. With the rapid development of science and technology, people have higher and higher requirements for data classification, so there are more and more researches on clustering in modern society. Various mathematical algorithms are introduced to further improve the accuracy of clustering. Therefore, this paper proposes an improved SOM neural network algorithm to evaluate the comprehensive quality of students. SOM neural network can automatically find the internal laws and essential attributes in the samples, self-organize and adaptively change the network parameters and structure, and realize the classification of samples. Factor analysis is introduced to reduce the dimension of input layer in SOM neural network analysis, better process high-dimensional data, and improve the speed and accuracy of the algorithm. The improved SOM neural network algorithm can be used for the cluster analysis of the comprehensive quality of college students. The algorithm simulation results show that the improved neural network algorithm can intuitively evaluate the comprehensive quality of students and reflect the overall characteristics of each type of student.
miR-181a-5p Inhibits Pyroptosis in Sepsis-Induced Acute Kidney Injury through Downregulation of NEK7
Authors: Zhang Meng , Zhi Deyuan , Lin Jin , Liu Pei , Wang Yajun , Duan Meili
Published: August 2022

Sepsis is a life-threatening organ dysfunction caused by the uncontrolled inflammation, easily affecting the kidney. Sepsis-induced acute kidney injury (S-AKI) has high morbidity and mortality, of which the pathophysiological mechanisms have not been completely illuminated, leading to nonspecific therapies. Specific microRNAs were related with the pathogenesis of AKI. However, only limited studies focused on the pyroptosis in the context of S-AKI. The in vitro LPS-induced HK-2 cell model and in vivo CLP-induced mouse model were established. qRT-PCR, Western blot, ELISA, and RNA pulldown were used for expression examination. Multiple biological databases were used for miRNA screening. H&E staining and IHC staining were performed. The LPS-induced HK-2 cells showed significantly increased (

P
<
0.01

) fluorescence intensity of N-GSDMD and ASC compared with the HK-2 cells. The expression of NLRP3, NEK7, ASC, active caspase-1, and N-GSDMD was significantly enhanced (

P
<
0.05

) and the inflammatory factors including IL-18, IL-1β, and THF-α were all increased in LPS-induced HK-2 cells and CLP-induced mice. Renal edema, serum Cr and BUN, and expression of KIM-1 and NGAL were significantly higher (

P
<
0.05

) in CLP-induced S-AKI mice than the sham group. miR-101-3p, miR-144-3p, miR-181a-5p, miR-4262, and miR-513b-5p could inhibit NEK7. NEK7 is an interacting protein of miRNA-181a-5p. miR-181a-5p inhibits pyroptosis of the LPS-induced HK-2 cells through downregulation of NEK7. Pyroptosis of HK-2 cells promotes inflammation. miR-181a-5p inhibits pyroptosis through downregulation of NEK7 in LPS-induced HK-2 cells and CLP-induced mice. Our study indicated miR-181a-5p as a new potential therapeutic target for S-AKI therapy.
Binocular Vision-Based Recognition Method for Table Tennis Motion Trajectory
Authors: Lu Chunfeng , Tang Xiyu
Published: August 2022

The latest development in computer technology in sports has increased the popularity of ping pong among people. It calls for designing an intelligent table tennis robot using computer technology to cooperate with table tennis enthusiasts and professional table tennis players to practice. Much research work has already been done in this area. However, this study explores the use of binocular vision to precisely identify, locate, and anticipate the flight trajectory and landing position of table tennis balls. Major issues addressed in this study include identifying fast-moving ping pong balls, calibrating the camera, obtaining the camera’s internal and external settings, and localizing the ping pong balls in three dimensions. A new target recognition method is proposed in combination with the actual needs of the combat ping pong robot. The method combines colour segmentation, background subtraction, and ellipse fitting, which can detect the tail range of flying ping pong balls and find the centre position of the balls. Based on the ellipse fitting analysis of the image, characteristics of the tail of the flying ping pong ball are studied. This study can aid in tracking the trajectories of high-speed flying objects, which is helpful for both aerospace and military industries.
[Retracted] Structural Modifications and Strategies for Native Starch for Applications in Advanced Drug Delivery
Authors: Bhatt Pankaj , Kumar Vipin , Goel Richa , Sharma Somesh Kumar , Kaushik Shikha , Sharma Shivani , Shrivastava Alankar , Tesema Mulugeta
Published: August 2022

Pharmaceutical excipients are compounds or substances other than API which are added to a dosage form, these excipients basically act as carriers, binders, bulk forming agents, colorants, and flavouring agents, and few excipients are even used to enhance the activity of active pharmaceutical ingredient (API) and various more properties. However, despite of these properties, there are problems with the synthetic excipients such as the possibility of causing toxicity, inflammation, autoimmune responses, lack of intrinsic bioactivity and biocompatibility, expensive procedures for synthesis, and water solubility. However, starch as an excipient can overcome all these problems in one go. It is inexpensive, there is no toxicity or immune response, and it is biocompatible in nature. It is very less used as an excipient because of its high digestibility and swelling index, high glycemic index, paste clarity, film‐forming property, crystalline properties, etc. All these properties of starch can be altered by a few modification processes such as physical modification, genetic modification, and chemical modification, which can be used to reduce its digestibility and glycemic index of starch, improve its film‐forming properties, and increase its paste clarity. Changes in some of the molecular bonds which improve its properties such as binding, crystalline structure, and retrogradation make starch perfect to be used as a pharmaceutical excipient. This research work provides the structural modifications of native starch which can be applicable in advanced drug delivery. The major contributions of the paper are advances in the modification of native starch molecules such as physically, chemically, enzymatically, and genetically traditional crop modification to yield a novel molecule with significant potential for use in the pharmaceutical industry for targeted drug delivery systems.
Design and Application of Land Resource Management System Based on Internet of Things
Authors: Song Qian
Published: August 2022

In order to further solve the problems existing in the process of land resource management of relevant departments of land and resource management, realize the information management of land resources, and promote the efficient utilization of land resources and scientific information management, this paper proposes a land resource management system based on Internet of things technology. With the help of resource allocation and management algorithm based on the needs of Internet of things users and land resource management requirements, this paper constructs a land resource management system based on Web and mobile network platform. The system development takes Java as the background programming language, constructs the database based on Oracle 9i, and uses GIS/GPS and other electronic map functions to realize the accurate display and resource sharing of land resource information. In the system test, 60, 120, 240, and 360 concurrent users are simulated to access the system at the same time. The connection success rates of the corresponding system are 97.2%, 97.5%, 98.3%, and 96.6%, respectively, which fully verifies the good performance of the system; it can be widely used in land resource information management.
High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network
Authors: Chen Nan , Zhang Yang
Published: August 2022

In order to solve the problem of low efficiency and accuracy of injury image recognition for sports athletes in high-intensity injury treatment, this paper proposes an injury recognition mode based on the deep neural network. In this paper, the image of sports injury is converted to gray level, and the contour of the injury part in the image is extracted according to the combination of adaptive thresholding and mathematical morphology. In this model, the seed points are selected, the active contour is used to approximate the initial contour, and the curve fitting method is used to fit the obtained discrete points to obtain the final damaged contour. The digital matrix is constructed by using the extracted number of pixels at the damaged position and relevant information. The images are arranged into feature vectors with a length of 64 according to the mode of column concatenation. The overall mean vector of the image is calculated. The calculation results, training samples, and image samples to be recognized are substituted into the Euclidean distance to obtain the preliminary recognition results of the damaged position of the image of sports injury. Then, the image segmentation is realized by clustering. The clustering segmentation results are used to color describe the pixel categories of the original image, calculate the relative damage proportion area in the sports injury image, and identify the damage parts of the high-intensity sports injury image. The experimental results show that the recognition rate of the neural network is 80%-100%, and the recognition time of this method is 0-0.6/s. The above method can improve the accuracy of the recognition of the damaged part of the sports injury image and shorten the recognition time and has certain feasibility in determining the sports injury part.
Structural Analysis of PE Teaching Strategy and System Knowledge Management Based on Mobile Digital Information Technology
Authors: Yang Fan , Shan Yu
Published: August 2022

In order to solve the physical education strategy problem of mobile digital information technology, a structure analysis and research method of systematic knowledge management department is proposed. First of all, the arrival and continuous maturity of the economic era has provided technical support for the development of many fields, especially the progress of information technology to strengthen the advantages of information management. Now the information management has gradually risen to the development stage of knowledge management. Secondly, there are related group learning and teachers’ personal knowledge management questionnaire survey. The statistical results of 178 valid questionnaires collected showed that 100% of teachers admitted that they had participated in different forms and types of group learning, and 91% of preschool teachers believed that they had a basic fixed time and content of group learning. However, 64.2 percent of teachers admitted that they did not consider personal knowledge management at all. For what is a personal knowledge management, 43.8% of the teachers are only heard of the term “personal knowledge management” but do not know the specific meaning. 17.4% of the teachers had heard of it and knew something about it. Only 3.4% of teachers clearly understood the meaning of personal knowledge management, and 35.4% had never heard of the concept of personal knowledge management, let alone the application of personal knowledge management strategies. The results show that how to excavate the structure of knowledge management of sports subject systematically through the innovation of PE teaching strategy, and excavate tacit knowledge and comprehensive explicit knowledge more deeply is the focus of this study. Therefore, from the perspective of knowledge management, an educational information resource management system is proposed, which can classify subject knowledge effectively and intelligently by means of mobile information technology.
[Retracted] Application of Fluorescence In Situ Hybridization Assisted by Fluorescence Microscope in Detection of Her2 Gene in Breast Cancer Patients
Authors: Lu Fang , Zhou Tingting , Liu Yan , Song Liying , Zhang Bin , Li Yuyan
Published: August 2022

In order to study the important factors for evaluating the prognosis of breast cancer patients, a fluorescence microscopy‐assisted fluorescence in situ hybridization technique was proposed. Compared with other detection techniques, fluorescence in situ hybridization (FISH) technology assisted by a fluorescence microscope has gradually gained favor in related fields due to its advantages of high detection specificity, high sensitivity, and strong experimental period. Combined with the basic overview of fluorescence microscopy and FISH technology, the advantages and application points of FISH technology assisted by fluorescence microscopy in the detection of the Her2 gene in breast cancer patients were studied and discussed. The results show that IHC can be used as the primary screening for HER2 gene status detection; IHC (2+) and IHC (3+) have false positives, which are related to chromosome 17 polysomy, so FISH should be done to confirm the diagnosis.
Exploring the New Mode of Teaching Computer-Aided Environmental Art Design Courses
Authors: Zhen Weixiao
Published: August 2022

Environmental art design course is the main direction of practical teaching. Therefore, the teaching reform and practical research of environmental art design based on CAD have been carried out. Innovative environmental art design courses, taking into account the differences of student groups, formulate the teaching methods of introductory courses, formulate the comprehensive topics of curriculum design, expand the knowledge base, improve the professional curriculum system, and strengthen the horizontal connection between curriculum teaching and computer design to meet the diversified needs of different student groups. Environmental art design also requires that before formal construction, with the help of computer-aided function, establish architectural drawings and analyze the rationality of each construction process. In view of the current situation and further development prospect of computer-aided application design, designers should improve the application level of graphics software. This paper is mainly committed to optimizing environmental art design teaching through computer, making full use of artificial environment design, improving the efficiency of computer performance technology, avoiding too single final design effect, so as to enhance the appeal of ecological art and meet people’s aesthetic needs.
Application of Data Mining in Network Information Dynamic Push Software
Authors: Hong Xiaoyi
Published: August 2022

In order to solve the problem that it is difficult for each user to obtain the most needed information due to different backgrounds, a method of data mining network information is proposed. The main steps of this method are as follows: (1) designing data mining rules based on association rules; (2) screening candidate sets of network information data mining; (3) candidate set information data mining. The experimental results show that the

p

value of this method is more than 90.0% and that of the traditional method is only within the range of 30.0%∼70.0%. Obviously, the

p

value of this method is 20.0%∼60.0% higher than that of the traditional method. This method can effectively solve the problem that it is difficult for each user to obtain the most needed information due to background differences.
Efficacy of Donepezil Hydrochloride plus Olanzapine for Senile Dementia and Its Effect on the Recovery of Cognitive Function
Authors: Zheng Wenxin , Sun Xinyao , Liu Jianghua
Published: August 2022

Objective. To investigate the efficacy of donepezil hydrochloride plus olanzapine for senile dementia and its effect on the recovery of cognitive function. Methods. A total of 60 patients with senile dementia admitted to our hospital from April 2020 to July 2021 were recruited and assigned to receive either olanzapine alone (observation group) or donepezil hydrochloride plus olanzapine (experimental group) via the random number table method, with 30 patients in each group. Results. The combined therapy resulted in significantly higher clinical efficacy versus monotherapy of olanzapine (

P
<
0.05

). Before treatment, the difference in the scores of cognitive function between the two groups did not come up to the statistical standard (

P
>
0.05

). Donepezil hydrochloride plus olanzapine was associated with significantly higher scores of cognitive function in patients versus olanzapine alone (

P
<
0.05

). The two groups had a similar incidence of adverse reactions (

P
>
0.05

). Conclusion. Donepezil hydrochloride plus olanzapine substantially enhances the recovery of cognitive function of patients with senile dementia and features a manageable safety. Further trials are, however, required prior to clinical promotion.
A Multisensor Data Fusion Based Anomaly Detection (Ammonia Nitrogen) Approach for Ensuring Green Coastal Environment
Authors: Qu Chong , Zhou Zhiguo , Liu Zhiwen , Jia Shuli , Ma Liyong , Sheela L Mary Immaculate
Published: August 2022

Great changes have been brought about by the coastal environment when the economy develops rapidly. Coastal environmental monitoring is the basis and technical guarantee for coastal environmental protection supervision and management. It is one of the important tasks to detect and timely discover coastal seawater anomalies. Usually, a single sensor cannot determine whether the coastal environment or ship operation is an anomaly. Recently, an unmanned surface vehicle for coastal environment monitoring was developed, and stacked autoencoders are used for seawater anomaly detection using multisensor data fusion methods. The multisensor data of pH, conductivity, and ammonia nitrogen are employed to judge the anomaly of seawater. The mean, standard deviation, mean square root, and normalized power spectrum features of multisensor data are extracted, and a stacked autoencoder is employed to fuse these features for anomaly detection. The proposed method is feasible and effective for anomaly detection of coastal water quality and ship operation. Compared with other commonly used methods, the proposed method has a higher recall, precision, and F1 score performance.
Design of LDMOS Device Modeling Method Based on Neural Network
Authors: Liu Teng , Wen Tianlong , Zhang Wentong , He Nailong , Zhang Sen , Song Hua
Published: August 2022

The rapid development of power semiconductor devices is helping to realize a low-carbon society and provide a better life for everyone. Power semiconductors not only are used in many large-scale industrial control fields such as power transmission and control in power grids, rail transit traction systems, and defense weapons and equipment, but also play a vital role in daily equipment such as home appliances, medical electronics, and electronic communications; all devices such as power steering in cars, battery chargers, cell phones, and microwave ovens utilize power electronics. This research mainly focuses on the high-voltage LDMOS device model and its implementation. Based on the in-depth study of the structure and physical mechanism of high-voltage LDMOS devices, with the help of BSIM4 core model, which is now very mature and widely used in industry, the drift region of high-voltage LDMOS is mainly modeled, and the drift region of LDMOS is modeled as a variable resistance controlled by voltage. Finally, Verilog-A language and neural network method are used to establish a compact model of LDMOS. The improved model is applied to LDMOS and can better fit the output characteristics with self-heating effect.
Meta-Analysis of the Efficacy and Safety of Olanzapine versus Clozapine when Treating Senile Dementia
Authors: Wang Zongqin , Feng Yingying , Wang Yanyan , Qiu Hui , Rui Zhongyang , Li Mingxing , Lv Lihua
Published: August 2022

Objective. To systematically assess the safety and efficacy of olanzapine versus clozapine when treating senile dementia and to provide evidence-based medicine basis for its promotion and use. Methods. PubMed, Embase, ScienceDirect, Cochrane Library, China Knowledge Network Database (CNKI), China VIP Database, Wanfang Database, and China Biomedical Literature Database (CBM) online database were searched for randomized controlled trials (RCT) of olanzapine and clozapine when treating senile dementia. The retrieval time limit is from the establishment of the database to the present. The data were extracted independently by two researchers, and the bias risk of each contained literature was analyzed in accordance with the standard of Cochrane Handbook 5.3. RevMan 5.4 statistical software was used to analyze the collected data by meta-analysis. Results. Finally, 6 randomized controlled trial articles were included, with a total of 490 samples. Meta-analysis of clinical efficacy showed that the clinical efficacy was similar and there was no significant difference (

P
>
0.05

). Two articles used Alzheimer’s disease pathological behavior rating scale (BEHAVE-AD) to compare the pathological behavior of different stages after treatment. Statistical analysis showed that there was no significant difference between the total score of BEHAVE-AD and the scores of each factor in each week after treatment. The non-treatment adverse reaction scale (TESS) of the study group and the control group was analyzed by meta-analysis. The TESS score of the study group after treatment was significantly lower than that of the control group. The BPRS scores of different stages after treatment were analyzed by meta-analysis, and there was no significant difference in the total score and factor scores of BPRS in each week after treatment. Two clinical trials reported the incidence of neurological symptoms after treatment. Olanzapine and clozapine treatment can effectively reduce the risk of aging. There was no significant difference in the incidence of neurological symptoms in patients with dementia (

P
>
0.05

). According to the analysis of meat products, the incidence of adverse reactions in the study group was significantly lower than that in the control group (

P
<
0.05

). Conclusion. Olanzapine and clozapine have similar efficacy when treating mental and behavioral disorders in patients with senile dementia, in which olanzapine is more effective in improving the symptoms of patients with Alzheimer’s disease (AD), with less adverse reactions and high safety, which is worth popularizing in clinical practice. However, more studies and follow-up with higher methodological quality and longer intervention time are needed to further verify.
Research on Rock Burst Control Mechanism of Deep Buried Tunnel Using Surrounding Rock Modification Theory
Authors: Sun Yanhua , Zhang Xiaohu , Xu Hanhua
Published: August 2022

In order to solve the rock burst disaster during the excavation of deep buried high stress hard rock tunnel, the method of changing the properties of surrounding rock by blasting is proposed in this paper. This method can effectively change the physical and mechanical properties of surrounding rock, reduce the storage capacity of surrounding rock corresponding to variable energy, and transfer the stress concentration position to the deep layer, which is an effective means to control rock burst. Taking the tunnel with rockburst tendency as an example, the stress distribution characteristics and displacement changes of surrounding rock under different modification depths are studied by using the numerical calculation method and elastic-plastic mechanics theory, and the effect is tested combined with microseismic data. The results show that the thickness of tunnel blasting loosening is closely related to the stress concentration of surrounding rock, and blasting loosening can effectively inhibit the occurrence and prevention of rock burst. With the increase of blasting depth, the maximum stress concentration decreases. The relevant research results can be used to reasonably design the blasting and loose surrounding rock reconstruction of high stress rock burst tunnel and improve the theoretical and practical basis.
Visualization of the Residual Network for 3D Image Recognition considering the SVM Combined with the K-Nearest Neighbor Algorithm
Authors: Liu Huabai
Published: August 2022

The support vector machine (SVM) combined with the K-nearest neighbor (KNN) algorithm is applied to the 3D image recognition algorithm to cope with the issues of 3D image recognition in the image processing process. In this paper, the KNN algorithm is used to extend the eigenvalues of the residual network from frequency to complex plane according to the eigenvalues of 3D images, and the relevant data are extracted from the images by using the corresponding separation rules of the SVM. Subsequently, a sparse observation model is established based on the SVM combined with the KNN, and the 3D image processing issue is converted to a residual network visualization issue of 3D image recognition by establishing a parameterized database. Meanwhile, detection of high-resolution distance of 3D images is conducted, and the variational inference method is used to visualize and analyze the 3D images accordingly. Finally, through the experimental study, it can be known that the method of SVM combined with the KNN algorithm can reach an accuracy of up to 94.18% in the dataset of the Princeton 3D polygonal models. After comparison with the existing SVM-KNN method and deep learning, it can be concluded that the method put forward in this paper has a higher recognition rate and stronger anti-interference capacity, and the algorithm has a superior convergence speed with less adjustment parameters.
Exploring Strategies for Quality Assurance in Online-Offline Hybrid Teaching under the Background of Smart Cities
Authors: Jin Xiaodan , Zhang Can , Su Jingru
Published: August 2022

The development of smart city construction and IT education and training are closely related and promote each other. The construction of a smart city is based on the application of information technology and IT education, and training is an important part of the construction of a smart city. Effective teaching needs the support of appropriate and scientific teaching strategies. Compared with the traditional offline classroom, the spatio-temporal structure of online and online hybrid teaching is significantly different. Therefore, we aim to explore the reform of our teaching and take online teaching as an example. Starting from the essence of online and offline blended teaching, this paper clarifies the differences between online and offline blended teaching and traditional course teaching and online network teaching, puts forward feasible strategies for the main problems existing in blended teaching, and provides new ideas for the implementation of online and offline blended teaching.
The Current Situation and Problems of Major Offerings in Higher Vocational Colleges Based on Industry 4.0: A Case Study of Higher Vocational Colleges in Xiamen
Authors: Jin Xiaodan , Zhang Can , Su Jingru
Published: August 2022

As the concept of lifelong education continues to infiltrate the education system, the examination of degree programs for junior college graduates has become a promotion path for graduates of higher vocational colleges to continue their education. It optimizes the development space for graduates of higher vocational colleges. While the enrollment of junior college graduates for degree programs is expanding, the education system of degree programs for junior college graduates and higher vocational colleges in China has also ushered in a new round of challenges and development opportunities. At present, the education system for degree programs for junior college graduates is not sound enough, and the interface with higher vocational colleges is not close enough. Moreover, there are problems such as poor communication of students moving from higher vocational colleges to universities for undergraduate education and fluctuating quality of personnel training and education. Therefore, it is of significance to study the problems of major offerings in higher vocational colleges. In our study, we took higher vocational colleges in Xiamen as an example. And we systematically study and then analyze the universities offering degree programs for junior college graduates and their majors. Finally, the problems in the connection between the majors of higher vocational colleges and those of universities with degree programs for junior college graduates are discussed, and suggestions are given for the study. Moreover, the universities should respond to the real-time development policy of the country and cultivate interdisciplinary personnel with solid theoretical foundation, innovation skills, research capabilities, professional expertise, and practical skills for social development.
Metformin Exhibits an Attractive Antineoplastic Effect on Human Endometrial Cancer by Regulating the Hippo Signaling Pathway
Authors: Wang Meng , Zhang Qiulin , Li Yuehan , Jin Lei , Fang Zishui
Published: August 2022

Metformin, the first-line oral antidiabetic medicine, has shown great antineoplastic potential in various cancer types, despite an unclear mechanism. This study aimed to elucidate the possible mechanism of metformin as a chemotherapy agent with less reproductive and genetic toxicity in human endometrial cancer. The type I endometrial carcinoma cell lines Ishikawa and RL95-2 were treated with metformin. Cell functions, such as proliferation, migration, and invasion, were analyzed. Flow cytometry was performed for cell cycle and apoptosis analyses. Simultaneously, RT-qPCR and western blotting were performed to explore the possible mechanism. Moreover, YAP1 knockout Ishikawa cells were established via lentivirus to demonstrate the underlying mechanism. The results showed that metformin mediated Ishikawa and RL95-2 cell growth inhibition in a dose- and time-dependent manner. The IC50 values of metformin in Ishikawa and RL95-2 cells were 10 mM and 8 mM, respectively. The migration and invasion abilities were also inhibited in the metformin-treated group using wound healing assays and transwell migration and invasion assays, and Ishikawa and RL95-2 cells were arrested in the G1 or G2 phase, respectively. Moreover, the cell proportions of cells in both early and late apoptosis stages were dramatically elevated when treated with metformin, as was the ratio of Bax/Bcl-2 expression. Additionally, the expression levels of YAP1 mRNA and protein in the treatment group were much lower than those in the control group. The cellular behaviors of YAP1 knockout Ishikawa cells were similar to those in the metformin-treated group. Our results demonstrated that it is an attractive alternative to cytotoxic chemotherapy in human endometrial cancer, and YAP of the Hippo pathway may be a potential molecular target. This study provides novel ideas for the adjuvant therapy of endometrial cancer patients, especially for women with strong fertility desires and demands.
Optimization of 3D Printing Process Parameters of Polylactic Acid Filament Based on the Mechanical Test
Authors: Raja S. , Agrawal Anant Prakash , P Patil Pravin , Thimothy P. , Capangpangan Rey Y. , Singhal Piyush , Wotango Mulugeta Tadesse
Published: August 2022

The main objective of this research study is to optimize the printing parameters that can be used in the FDM (fusion deposition modeling) production method to obtain the lowest production time and best printing parameter of PLA (polylactic acid) filament with the tensile test. The printing parameter that can be used in FDM machines such as extruder temperature, bed temperature, layer height, printing speed, travel speed, infill, and shell count is taken into account for optimization. In addition, the tensile specimens from ASTM (American Society for Testing and Materials) D638 standard were manufactured by PLA filament with the above-modified printing parameters. The best printing parameters for PLA products were found by the time recorded during production and tensile test results after production. Thus, through this research, one can find the best PLA filament printing parameters and their timing.
[Retracted] CNN‐Based Cross‐Modal Residual Network for Image Synthesis
Authors: Kumar Rajeev , Bhatnagar Vaibhav , Jain Amit , Singh Mahesh , Kareem Z. H. , Sugumar R.
Published: August 2022

This study attempts to address the issue that present cross‐modal image synthesis algorithms do not capture the spatial and structural information of human tissues effectively. As a consequence, the resulting photos include flaws including fuzzy edges and a poor signal‐to‐noise ratio. The authors offer a cross‐sectional technique that combines residual modules with generative adversarial networks. The approach incorporates an enhanced residual initial module and attention mechanism into the generator network, reducing the number of parameters and improving the generator’s feature learning capabilities. To boost discriminant performance, the discriminator employs a multiscale discriminator. A multilevel structural similarity loss is included in the loss function to improve picture contrast preservation. On the ADNI data set, the algorithm is compared to the mainstream algorithms. The experimental findings reveal that the synthetic PET image’s MAE index has dropped while the SSIM and PSNR indexes have improved. The experimental findings suggest that the proposed model may maintain picture structural information while improving image quality in both visual and objective measures. The residue initial module and attention mechanism are employed to increase the generator’s capacity for learning, while the multiscale discriminator is utilized to improve the model’s discriminative performance. The enhanced method in this study can maintain the structure and contrast information of the picture, according to comparative experimental findings using the ADNI dataset. The produced picture is hence more aesthetically similar to the genuine print.
Teaching Quality Evaluation and Feedback Analysis Based on Big Data Mining
Authors: Wang Jiwen , Liu Cunsheng , Gao Wei
Published: August 2022

Using large-scale data collection and analysis methods to develop educational models, study the relationship between educational variables, and provide effective support for educational reform will be the inevitable trend of modern information technology teaching in the future. At present, under the high level of higher education system and higher education reform, curriculum evaluation is an important tool to evaluate the quality of classroom teaching and an important basis to test the effectiveness of curriculum reform. On the basis of establishing the teaching evaluation index system based on students’ participation, acceptance, and satisfaction index, this paper establishes three levels of evaluation system: curriculum micro evaluation index system, secondary college comprehensive evaluation index system and school macro evaluation index system. We use teaching quality evaluation to obtain evaluation data and develop CTQ evaluation and feedback system based on the analysis of broader data, so as to improve the quality of classroom teaching.
Application of Higher Education Management in Colleges and Universities by Deep Learning
Authors: Yao Ge
Published: August 2022

The development of artificial intelligence (AI) has brought great convenience to people and has been widely used in the field of education. To monitor the classroom status of college students in real time and achieve the purpose of balanced distribution of educational resources, the facial expression recognition (FER) algorithm is applied to the management of higher education in universities. Firstly, the convolutional neural network (CNN) is studied in depth, and secondly, the process and method of FER are explored in detail, and an adaptive FER algorithm based on the differential convolutional neural network (DCNN) is constructed. Finally, the algorithm is applied to the CK + database and the BU-4DFE database. The results manifest that the designed algorithm has an accuracy of 99.02% for keyframe detection in the CK + database and 98.35% for the BU-4DFE database. The algorithm has a high accuracy of keyframe detection for both expression databases. It has a good effect on the automatic detection of keyframes of expression sequences and can reach a level similar to that of manual frame selection. Compared with the existing algorithms, the proposed method still has higher advantages. It can effectively eliminate the interference of individual differences and environmental noise on FER. Experiments reveal that the proposed FER algorithm DCNN-based has a good recognition effect and is suitable for monitoring students’ classroom status. This research has certain reference significance for the application of AI in higher education management in colleges and universities.
Accounting Earnings and Economic Growth, Trends, and Challenges: A Bibliometric Approach
Authors: Sun Mu , Urquía-Grande Elena , Chamizo-González Julián , Campo Cristina del
Published: August 2022

In recent years, studies have been conducted to quantify the relationship between microeconomic and macroeconomic development. Macroeconomics is the orientation of microeconomic development. Existing research hopes to quantify the relationship between macroeconomics and micro-firms, rather than just focusing on economic indicators. And some empirical studies try to use the relationship between them to discuss its usefulness for micro-firm decision-making. This article focuses on applying and developing aggregate earnings in connecting microenterprise earnings and macroeconomic development. To achieve this goal, this research did a comprehensive bibliometric analysis on macro-accounting on the two most influential databases, namely, Web of Science and Scopus. It used the information visualization software VOSviewer to draw knowledge maps to sort research lines. We also analyzed the research hotspots of macro-accounting in recent years according to the year scale and combined it with the neural network PSO-LSTM model to predict their future development. It turns out that the research on aggregate earnings related to economic growth has become a research hotspot in recent years. Scopus research and development potential is better than Web of Science in this field.