bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic Vehicles’ Trajectories Optimization on Highway Exclusive Lanes
Authors: Chen Lingjuan , Ruan Yangbo , Gou Yiquan
Published: June 2022

The rapid development of V2X communication has made it possible to optimize and control the trajectories of vehicles from the whole traffic flow’s perspective and improve traffic performance. Therefore, this paper discusses the trajectories management problem on highway facilitated with lanes exclusively for autonomous vehicles (AVs). The paper proposes a model that aims to search for optimal trajectories and minimize total travel time for AVs with multiple initial and target states while averting crashes and conforming to vehicles’ kinetic. Dividing the time zone into discrete pieces, the model is analyzed as a large-scale discrete problem influenced by the randomness of the sequence of vehicles. A two-phase algorithm combined with upper evolution strategies and lower dynamic programming is developed to diminish stochastics and reduce computation step by step and solve the trajectories optimization model. Numerical experiments validate that the proposed method is capable of generating optimal trajectories for multiple AVs and approaching to system optimum by simultaneously solving all the spatial and temporal values of the trajectories. The two-phase algorithm can be applied efficiently in practice to obtain a feasible approximate solution for trajectories optimization by presetting appropriate algorithm parameters.
Effects of miR-124-3p Silencing on Neuronal Damage in the Hippocampus of Depression Rats by Regulating STAT3 Gene
Authors: Qin Guangping , Li Zhuo
Published: June 2022

Objective. A large amount of evidence shows that the abnormal expression of miRNA plays an important role in the development of depression. Therefore, we investigated the effect of miR-124-3p on neuronal damage in the hippocampus of depression rats. Methods. The target genes of miR-124-3p were predicted by the database; the depression model was prepared by subcutaneous injection of corticosterone (CORT), and LV-miR-124-3p asponge lentiviral suspension was given to determine the weight of rats and open-field test, sugar preference experiment, Serum CORT, 5-HT, DA, and NE were measured, observe and record the behavior of rats, including behavior, diet, and hair. The expression of miR-124-3p, STAT3, Bcl-2, and Bax in rat hippocampus was measured. The rat hippocampal neuron cells were extracted and transfected with miR-124-3p inhibitor; the cells were cultured with CORT, and the cell survival rate was evaluated by MTT experiment, and the expressions of miR-124-3p, STAT3, Bcl-2, and Bax in the cells were detected. Luciferase reporter gene verifies the targeted regulation of miR-124-3p on STAT3. Results. Compared with depression rats, silencing miR-124-3p increased the weight of the rats, increased the number of open-field activities, and significantly improved the general state and pathological state of the rats. The sugar water preference rate was significantly increased, the CORT content in the serum of rats decreased significantly, and the levels of 5-HT, DA, and NE increased significantly. After the treatment of silencing miR-124-3p, the expression level of miR-124-3p was decreased, while the STAT3 mRNA and protein expression levels were increased. And the protein and mRNA expression levels of Bcl-2 were increased, and the Bax protein and mRNA expression were decreased. Cell experiments verified that silencing miR-124-3p increased cell survival, the expression level of miR-124-3p decreased remarkably, while the expression levels of STAT3 mRNA and protein increased significantly. Silencing miR-124-3p reversed the effects of CORT treatment on miR-124-3p and STAT3 in neuronal cells. The luciferase reporter gene experiment confirmed that miR-124-3p targets and regulates STAT3 expression. Conclusion. Silencing miR-124-3p may protect hippocampal neurons from damage in depression rats by upregulating STAT3 gene.
A Hybrid Online and Offline Approach to Teaching Spoken English Based on Modern Educational Technology
Authors: Xiaodong Li
Published: June 2022

People nowadays care more about the source and outcome of English instruction, resulting in an improvement in the quality of English instruction. As a result, the majority of students’ reading and writing levels increase steadily, but their listening ability does not, resulting in an extremely unbalanced development of the “listening, reading, and writing” four skills. The use of language in real-world situations is a reflection of human creativity, and the content and tone of the same speaker’s speech at different times, places, and occasions can vary significantly. Language usage cannot be separated from its context. This study proposes a hybrid online and offline English speaking teaching method based on modern educational technology. The method transforms offline teaching materials into a suitable context to create a rich and diverse online speaking classroom. This new teaching method constructs a teaching platform with online and offline as the primary subjects, replacing the previous single mode of teacher output and passive student input to form an all-round teaching platform distinguished by systematization, standardization, all-round language training, high intensity, accuracy, and fluency in language output. The experimental results demonstrated that our evaluation results are useful for providing feedback on the quality of teaching and promoting learning outcomes.
Mathematical Models for Analysis the Impact of Institutional Quality and Multilateral Financial Institutions on the Success of Green PPP Projects
Authors: Li Wu-Yan , Chen Ruo-Yu , Ma Ming
Published: June 2022

Green PPP projects are of great significance to green infrastructure construction and green economic development. This study analyzes 552 Green PPP projects related to sewage treatment and clean energy in African countries during 2005-2019 to determine how institution quality and multilateral financial institutions influence Green PPP projects’ success. We find that (1) successful (failed) Green PPP projects experience increase (decrease) new Green PPP projects’ success rate. (2) Higher private capital risk-taking degree increases the likelihood of failure. (3) Institution quality affects project success through a mixed effect on private capital’s risk-taking degree: rule of law, government effectiveness, control of corruption, and regulatory quality positively promote private capital’s risk taking; voice has an opposite effect. (4) Multilateral financial institutions’ participation in Green PPP projects promotes higher private capital risk taking.
Fusion Analysis of Chinese Painting Color Teaching and Intelligent Image Color Processing Technology
Authors: Zhao Nan
Published: June 2022

In order to solve the problem of traditional Chinese painting image color processing technology, meet the needs of digital museum construction, make up for the vacancy of color processing technology in traditional Chinese painting, and improve people’s understanding of traditional Chinese painting. Through the analysis of the experiment, the experimental equipment adopts Epson v940 scanner, the color depth is 24 bit true color, and the scanning accuracy is 1200dpi. The main simulation methods of Chinese painting are systematically and deeply studied, from which the characteristics of Chinese painting are analyzed. Through a large number of formula analysis, it is found that the application of computer image processing technology in Chinese painting is very successful, which promotes the development of the digital museum and improves people’s understanding and liking of Chinese painting.
Determinants of Small-Scale Irrigation Use for Poverty Reduction: The Case of Offa Woreda, Wolaita Zone, Southern Ethiopia
Authors: Zemarku Zekarias , Abrham Mulumels , Bojago Elias , Dado Tsegeye Bojago
Published: June 2022

Small-scale irrigation is one of the agricultural activities used by rural farmers to improve the overall livelihood of the rural community by increasing income, securing food, meeting social requirements, and reducing poverty. The main objective of this study was to look into the factors that influence small-scale irrigation for poverty reduction among small-holder farmers in the Offa Woreda, Wolaita Zone. Government and nongovernmental organizations supplied small-scale irrigation and training to small-holder farmers in the study area at various times; however, the key determinants impacting small-scale irrigation use were not fully identified in the study area. The study location was chosen for this study purpose because no prior in-depth research had been conducted. Simple random sampling was used to select the three kebeles for the study. A total of 134 people were included in the study sample frame. The sample was chosen using simple random sampling and the proportional probability-to-size (pps) method, which was proportional to the size and used multistage sampling procedure. The primary data were collected using the interview schedule. Both quantitative and qualitative data were analyzed using descriptive and econometric analyzes in SPSS version 21. Qualitative data were also collected through focus groups and key informant interviews. A factor that influences small-scale irrigation use was investigated using a binary logistic regression model. The binary logistic regression model revealed that both the irrigation participants (37.3%) and the nonparticipant (62.7%) families had a combination of personal and demographic, economic, institutional, and social influencing factors that hinder their likelihood of using irrigation. HH age, annual income of the household, distance from the closest farm sight, farm experience, participation in training, access to irrigation, and sex of HH were positively and significantly influencing factors in the model, while total ownership of livestock of households and health status of households were negatively significant variables. As a result, the Agricultural and Natural Resources Development Office, as well as the Water Mining and Energy Offices, should devote scientific attention to the significant factors that influence irrigation use to boost farm family production and productivity.
Perilla Fruit Water Extract Attenuates Inflammatory Responses and Alleviates Neutrophil Recruitment via MAPK/JNK-AP-1/c-Fos Signaling Pathway in ARDS Animal Model
Authors: Ting Nai-Chun , Chen Yu-Hao , Chen Jeng-Chang , Huang Wen-Chung , Liou Chian-Jiun , Chen Li-Chen , Yang Sien-Hung , Kuo Ming-Ling
Published: June 2022

Airway respiratory distress syndrome (ARDS) is usually caused by a severe pulmonary infection. However, there is currently no effective treatment for ARDS. Traditional Chinese medicine (TCM) has been shown to effectively treat inflammatory lung diseases, but a clear mechanism of action of TCM is not available. Perilla fruit water extract (PFWE) has been used to treat cough, excessive mucus production, and some pulmonary diseases. Thus, we propose that PFWE may be able to reduce lung inflammation and neutrophil infiltration in a lipopolysaccharide (LPS)-stimulated murine model. C57BL/6 mice were stimulated with LPS (10 μg/mouse) by intratracheal (IT) injection and treated with three doses of PFWE (2, 5, and 8 g/kg) by intraperitoneal (IP) injections. To investigate possible mechanisms, A549 cells were treated with PFWE and stimulated with LPS. Our results showed that PFWE decreased airway resistance, neutrophil infiltration, vessel permeability, and interleukin (IL)-6 and chemokine (C-C motif) ligand 2 (CCL2/MCP-1) expressions in vivo. In addition, the PFWE inhibited the expression of IL-6, CCL2/MCP-1, chemokine (CXC motif) ligand 1 (CXCL1/GROα), and IL-8 in vitro. Moreover, PFWE also inhibited the MAPK/JNK-AP-1/c-Fos signaling pathway in A549 cells. In conclusion, we demonstrated that PFWE attenuated pro-inflammatory cytokine and chemokine levels and downregulated neutrophil recruitment through the MAPK/JNK-AP-1/c-Fos pathway. Thus, PFWE can be a potential drug to assist the treatment of ARDS.
PTEN: An Emerging Potential Target for Therapeutic Intervention in Respiratory Diseases
Authors: Cai Bangrong , Yang Liu , Do Jung Young , Zhang Ying , Liu Xinguang , Zhao Peng , Li Jiansheng
Published: June 2022

Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) is a potent tumor suppressor that regulates several key cellular processes, including proliferation, survival, genomic integrity, migration, and invasion, via PI3K-dependent and independent mechanisms. A subtle decrease in PTEN levels or catalytic activity is implicated not only in cancer but also in a wide spectrum of other diseases, including various respiratory diseases. A systemic overview of the advances in the molecular and cellular mechanisms of PTEN involved in the initiation and progression of respiratory diseases may offer novel targets for the development of effective therapeutics for the treatment of respiratory diseases. In the present review, we highlight the novel findings emerging from current research on the role of PTEN expression and regulation in airway pathological conditions such as asthma/allergic airway inflammation, pulmonary hypertension (PAH), chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), and other acute lung injuries (ALI). Moreover, we discuss the clinical implications of PTEN alteration and recently suggested therapeutic possibilities for restoration of PTEN expression and function in respiratory diseases.
Ovarian Cancer Was Discovered in Sister Mary Joseph’s Nodule
Authors: Kouira Mouna , Bannour Imen , Ben Abdesslem Mohammed Raouf , Abdessayed Nihed , Bannour Badra
Published: June 2022

Introduction. Sister Mary Joseph’s nodule (SMJN) is a rare illness characterized by an umbilical mass caused by tumor metastases in the abdomen or pelvis. The most common main site of SMJN in women is ovarian cancer. Case Presentation. A 73-year-old woman with no pathological history came to our emergency room with a one-month history of umbilicus enlargement. A 9-centimeter uncomfortable umbilical swelling with hard consistency was discovered during a clinical examination. An ovarian tumor with several local expansions was seen on an abdominal CT scan. It was linked to peritoneal metastases, one of which extends via a supraumbilical hernial orifice and into intestinal tissues in the same hernia sac. The umbilical tumor was removed from the patient. A moderately differentiated serous carcinoma with ovarian origin was identified in a periumbilical site on histological testing. Conclusion. The presence of an SMJN is a rare but significant issue that clinicians must examine because it is associated with a bad prognosis. Early detection and diagnosis of the original lesion can lead to more effective treatment and a higher rate of survival.
Evaluation of the Antidiabetic Activity of Hydromethanolic Roots Extracts of Rumex abyssinicus Jacq: (Polygonaceae) in Swiss Albino Mice
Authors: Yrga Adugna Baye , Mequanint Adinew Getinet , Ayalew Getahun Kefyalew , Endale Gurmu Abyot , Yirga Berhie Alemshet , Awoke Tewachew , Tessema Desta Getaye
Published: June 2022

Introduction. Diabetes Mellitus isa chronic metabolic disorder that required long-lasting treatment. In Ethiopian traditional medicine practices, abundant plants have been used for the treatment of diabetes mellitus for a long period. The root of Rumex abyssinicus is employed for the treatment of diabetes mellitus by Ethiopians. This study aimed to investigate the antidiabetic activity of the crude extract of Rumex abyssinicus root in Swiss albino mice. Methods. Cold maceration technique and hydro methanolic (80% methanol) solvent with occasionally shaking were employed during the crude extraction processes. To evaluate the antidiabetic activity of the crude extract, normoglycemic, glucose-loaded, and streptozotocin-induced diabetic models were used. In each model, the overnight fasted mice were randomly divided into five groups for normoglycemic and glucose-loaded models as a negative control, positive control, and three tested groups, whereas, in streptozotocin-induced diabetic models, the mice were grouped into six groups like one diabetic and one normal negative control groups, three diabetic tested groups, and one diabetic positive group. Each group comprised six mice. For all models, the tested groups received the crude extract at 100, 200, and 400 mg/kg doses, both diabetic and nondiabetic negative control groups received 10 ml/kg distilled water, and positive groups received 5 mg/kg glibenclamide. Results. The crude extract of the plant did not show any sign of toxicity up to 2000 mg/kg dose. In normoglycemic and oral glucose tolerance tests, the crude extract significantly (p<0.01) reduced the blood glucose level at 200 and 400 mg/kg doses. In the streptozotocin-induced diabetes models, a significant effect was observed at all tested doses. Conclusion. The finding of this study revealed that the crude extract of the plant owned antidiabetic activity and supports the traditional use of Rumex abyssinicus root for the treatment of diabetes mellitus.
Dynamic Simulation Analysis of Carbon-Steel Hybrid Sucker Rod String in Vertical and Directional Wells
Authors: Sun Xiurong , Ji Xianbing , Li Weicheng , Zhang Lijuan , Song Yang
Published: June 2022

Carbon fiber composite continuous sucker rod string is more and more widely used in deep and ultradeep wells because of its light weight, high strength, and corrosion resistance. In order to analyze the dynamic problems of carbon fiber sucker rod string in actual oil wells, a transverse vibration simulation model of carbon fiber and steel (carbon-steel) hybrid rod string excited by buckling deformation in vertical wells is established with the compression buckling deformation of weighting rod. Considering the influence of wellbore trajectory and the constraint of tubing, the transverse vibration simulation model of carbon-steel hybrid rod string in directional wells under borehole trajectory excitation is also established in this paper. The finite difference method is used to discretize the well depth node, the numerical integration method (Newmark-β) is used to discretize the reciprocating periodic time node, and simulation methods for the contact and collision dynamics of rod-tubing in vertical wells and directional wells are formed. Through programming calculation, the distribution laws of transverse displacement, contact force, collision force, and bending stress of carbon-steel hybrid sucker rod string in vertical wells and directional wells along well depth are obtained. The simulation results in vertical wells show that the strong collision between the rod and tubing occurs near the bottom steel rod, while the upper load is small and the rod-tubing collision load of the upper rod of the carbon-steel hybrid rod string is much lower than that of the traditional steel rod string at the same position. Furthermore, the bending stress of the upper carbon fiber is also much less than that of the bottom steel rod. The simulation results in directional wells show that the collision phenomenon of the deflecting section and the bottom weighting rod compression section are the strongest and the rod-tubing contact pressure is also the largest. Second, the impact force of the upper carbon fiber rod is also much lower than that of the steel rod. Again, the maximum bending stress of the whole well occurs near the deviation section where the deviation angle changes suddenly. The transverse vibration mechanical model in directional wells in this paper lays a theoretical foundation and provides theoretical support for the optimal design of fracture and splitting prevention measures of carbon fiber sucker rod.
Upgrading and Optimization of Ski Tourism Resort Using Data Mining and Data Fusion
Authors: Liu Zhaoxin , Shin Ok-young , Park Haeryong
Published: June 2022

After years of development, the ski industry has formed a prototype of a ski tourism industry cluster integrating skiing, skiing entertainment, skiing technology, and skiing culture. With the rapid development of global information, data mining and data fusion have attracted extensive attention as high-tech technologies for extensive data processing and useful information retrieval. The principles of these two data processing technologies are different, but they are functionally compatible with each other. This paper will use the methods of data mining and data fusion to research and analyze the upgrading and optimization of ski tourism destinations; eliminate unnecessary information; reduce rules; establish a fusion system according to the basic rules of rough sets; use industrial cluster theory, industrial structure and optimization theory, industrial economy, and sports tourism management theory to study the current situation and existing problems of ski tourism; and analyze the mechanism and theory of upgrading and optimization of ski tourism industry structure based on industrial clusters. The results show that the per capita ecological footprint of the ski resort has decreased by 0.06178 hm2 in the past five years, and the total ecological footprint of the whole region in 2020 is 535089.3 hm2. Compared with 2016, it increased by 0.97%, exceeding the ecological deficit carrying supply by 5 times. Compared with traditional algorithms, the performance of data mining and data fusion algorithms is improved by 48%. It is concluded that the development strategies of the ski tourism industry include the innovation of ice and snow sports products, the innovation of technology development paths, the optimization of the management mode and marketing mode of the ski tourism industry, and the innovation of industrial systems and systems.
Analysis on the Reform and Development of Physical Education Services in the Context of 5G Connected Communication
Authors: Wang Li , Yan Dangyan , Zhang Yanhong , Wen Yuan
Published: June 2022

With the continuous growth of science and technology, mankind has entered the fifth-generation (5G) era. In this background, the development of many fields will face great opportunities and challenges, including the field of physical education (PE). The traditional teaching mode, method, and contents of PE are difficult to adapt to the development needs of the 5G era. Therefore, it is of great significance to study the PE teaching reform in the era of “5G education.” Moreover, integrating 5G technology and PE may benefit students, educators, and the entire PE system. This study offers an in-depth investigation of the reforms and development of PE services under the background 5G interconnected communications. The reforms of PE and services are examined using the most up-to-date 5G technologies. Four 5G methodologies which include model-based practice (MBP), virtual reality (VR), the Internet of Things (IoT), and artificial intelligence (AI) are analyzed, and for the comparative study, performance indicators such as cost reduction, energy efficiency, and security level are measured. When compared to other strategies, IoT-based physical education is found to be more efficient in terms of these parameters. The 5G-driven PE will provide students with objective, fair, and diversified education, and adaptive learning services to promote the overall development of students.
ECANP: A Topic Influence Evaluation Model for Hot Topics
Authors: Chang Yiru , Zhang Zhiyuan , Luo Guixun
Published: June 2022

Social network is an important product of industrial society. In recent years, the research related to hot topics has focused on topic detection, topic trend prediction, and topic tracking. However, the important role of topic influence evaluation in hot topic research has not received enough attention, which leads the problem of inaccurate influence calculation. In order to solve the above problems, this paper proposes a novel model to evaluate the real-time relative influence of topics in social network. The proposed model can quantify the influence of topics, and some influential factors which determine topic hotness will be analyzed and identified. In this model, five impact indicators are defined, namely user engagement, topic coverage, topic activity, topic persistence, and topic novelty to consider the topic characteristics more finely. Moreover, the proposed model not only consider traditional simple factors of like, forward and comments, but also pay attention to the relative influence and time attenuation characteristics of the topics. Further, the experimental results show that our method could quickly aggregate the influence factors of hot topics and accurately provide the influence indicator of topics.
Visual Object Tracking Based on Adaptive Background-Awareness and Spatial Constraint
Authors: Fan Keqi , Yu Qianqian , Wang Yiyang , Chen Deng , Zheng Yuhui
Published: June 2022

The correlation filter method is effective in visual tracking tasks, whereas it suffers from the boundary effect and filter degradation in complex situations, which can result in suboptimal performance. Aiming at the solving above problem, this study proposes an object tracking method with a discriminant correlation filter, which combines an adaptive background perception and a spatial dynamic constraint. In this method, an adaptive background-awareness strategy is used to filter the background information trained by the interference filter to improve the discriminability between the object and the background. In addition, the spatial regularization term is introduced, and the dynamic change of the real filter and the predefined spatial constraint template is used to optimize filter learning to enhance the spatial information capture ability of the filter model. Experiments on the OTB100, VOT2018, and TrackingNet standard datasets demonstrate that our method achieves favorable accuracy and success rates. Compared with the current popular correlation filter methods, the proposed method can still maintain stable tracking performance with a scene scale variation, complex background, motion blur, and fast motion.
Deep Learning Approaches for Automatic Localization in Medical Images
Authors: Alaskar H. , Hussain A. , Almaslukh B. , Vaiyapuri T. , Sbai Z. , Dubey Arun Kumar
Published: June 2022

Recent revolutionary advances in deep learning (DL) have fueled several breakthrough achievements in various complicated computer vision tasks. The remarkable successes and achievements started in 2012 when deep learning neural networks (DNNs) outperformed the shallow machine learning models on a number of significant benchmarks. Significant advances were made in computer vision by conducting very complex image interpretation tasks with outstanding accuracy. These achievements have shown great promise in a wide variety of fields, especially in medical image analysis by creating opportunities to diagnose and treat diseases earlier. In recent years, the application of the DNN for object localization has gained the attention of researchers due to its success over conventional methods, especially in object localization. As this has become a very broad and rapidly growing field, this study presents a short review of DNN implementation for medical images and validates its efficacy on benchmarks. This study presents the first review that focuses on object localization using the DNN in medical images. The key aim of this study was to summarize the recent studies based on the DNN for medical image localization and to highlight the research gaps that can provide worthwhile ideas to shape future research related to object localization tasks. It starts with an overview on the importance of medical image analysis and existing technology in this space. The discussion then proceeds to the dominant DNN utilized in the current literature. Finally, we conclude by discussing the challenges associated with the application of the DNN for medical image localization which can drive further studies in identifying potential future developments in the relevant field of study.
Developing Tourism Users’ Profiles with Data-Driven Explicit Information
Authors: Norouzi Rasoul , Baziyad Hamed , Aknondzadeh Noghabi Elham , Albadvi Amir
Published: June 2022

In recommender systems (RSs), explicit information is often preferred over implicit because it is much more accurate than implicit or predicted information; for example, the user can enter information about his interests directly into the system, and the system will generate accurate recommendations for him. Receiving explicit information, however, may be difficult for a system. Explicit demographic information might be uncomfortable for some users, and extremely common questions, such as race, gender, income, and age, can lead to bias and unfair recommendations. As a result, in this study, we propose a method, in which information collected from a new user does not contain demographic information, and enquired explicit information is data driven. Users’ interest in tourism activities is used to identify seven categories of tourism. The mapping between extracted categories and activities is established with a multilabel classification (MLC) algorithm. The user’s interest in 18 tourism activities is predicted by rating only seven tourism categories. Common MLC algorithms with different classifiers were used to evaluate the proposed method. The best result relates to binary relevance with the Naïve Bayes classifier, which also outperforms the entitled algorithms in collaborative filtering (CF) systems as baseline models. The proposed method can capture users’ interests and develop their profiles without receiving demographic information. Also, compared to CF, in addition to a slight advantage in metrics, it only requires seven ratings to predict user interest in 18 activities. In contrast, CF algorithms require at least 15 user ng records to predict user interest in unknown activities (3-4 activities) to achieve a performance close to the proposed method.
Mechanical Damage Test and Model Study of Layered Composite Rock Based on Acoustic Emission and DIC Characteristics
Authors: Qi Xianyin , Yang Zhen , Wang Shengwei , Fu Peng
Published: June 2022

To study the mechanical damage characteristics of layered composite rocks, sandstones, and mudstones of deep tight reservoirs were used as the research objects, and layered composite class rocks were prepared by similar material model tests. Uniaxial compression tests were conducted and supplemented with AE (Acoustic Emission) system and DIC (Digital Image Correlation) system to obtain the physical and mechanical parameters such as strength and elastic modulus of the layered composite rocks. The corresponding law of AE ringing count and rock damage evolution was studied and the damage process of layered composite rock under uniaxial loading was divided into three stages: initial damage, stable damage development, and damage acceleration. Analysis of strain cloud diagrams of the DIC system revealed that the deformation characteristics of the layered composite rock under uniaxial were mainly tensile-shear-slip damage. Based on the internal damage evolution characteristics of AE and the surface damage evolution characteristics of DIC, a damage constitutive model of layered composite rocks based on the dual damage factor characterization was established, which reasonably revealed the damage evolution mechanism of internal structure development and external crack germination, extension and penetration of layered composite rocks under uniaxial compression.
[Retracted] The Rights and Interests Protection Strategy of Express Employees under the Background of Big Data Environment
Authors: Chen Tian
Published: June 2022

In order to have an in‐depth understanding of the youth group in this special industry and find out the problems of express delivery in life, work, and emotion, as well as the difficulties e faces in social support, this paper presents a research method of rights and interests protection strategy of express employees based on big data environment. This method comprehensively analyzes the protection of the rights and interests of express employees in the context of big data. It is found that 19.4% of couriers say they will be bored because they feel that it is not within their scope of responsibility, so they will be very reluctant. The low self‐identity of couriers may be one of the important reasons why some couriers have this idea. Therefore, on this basis, a mathematical model for the protection of the rights and interests of express employees is established based on the factor analysis method, and the rights and interests of express workers in the era of big data are analyzed from the perspectives of the survival status of express workers and social support. The analysis results show that the rights and interests protection laws and regulations of the express industry and the social security system will restrict the express employees from obtaining their due rights and interests. From the perspective of laws and regulations, we can optimize the legal rights and interests of express employees and social security system.
Teaching Quality Evaluation Model of a Flipped Classroom in Colleges and Universities Based on Support Vector Machine
Authors: Fu Jin Feng , Li Jun
Published: June 2022

The systematic evaluation of teaching quality in colleges and universities is an important factor, which makes the systematic evaluation of teaching quality in colleges and universities very complex and makes the systematic evaluation of teaching quality in colleges and universities unable to describe a variety of teaching quality directly or indirectly. Therefore, a quality evaluation model of flipped classroom teaching in colleges and universities based on support vector machine is proposed. Through the selection of teaching quality evaluation indicators from three aspects of experts, teachers, and students, the evaluation system of flipped classroom teaching quality in colleges and universities is established. The evaluation indicators are used as the input of support vector machine for learning, and the evaluation model of flipped classroom teaching quality in colleges and universities is established. The experimental results show that this method can effectively evaluate the quality of flipped classroom teaching in colleges and universities, the relative error of the evaluation results is low, and it has certain practicability.
Sports Analysis and Action Optimization in Physical Education Teaching Practice Based on Internet of Things Sensor Perception
Authors: Chen Mengjunguang , Jiang Jingjing
Published: June 2022

With the progress of the Internet of things technology in recent years, all aspects of people’s lives have also been affected. More and more people are immersed in the virtual world and ignore the real activities. According to the survey, nearly 50% of people in China are in subhealth, mainly modern diseases caused by long-term inactivity. Therefore, to form a good habit of physical exercise, we must start from an early age. Starting from the physical education teaching in primary and secondary schools and from the perspective of modern scientific and technological facilities, this paper discusses the practical sports analysis and action optimization of physical education teaching based on the perception of the Internet of things. Starting from the practice of Internet of things sensor sensing in physical education teaching, we have successively determined the multisensor motion acquisition system algorithm, motion pattern recognition algorithm, and motion energy consumption algorithm, which provides modern equipment for motion analysis and motion optimization in physical education teaching practice, which breaks the current situation that traditional teachers spend a lot of time and energy for students. Combining sports mode with sports energy consumption can not only analyze sports data accurately and in real time but also optimize and predict students’ sports behavior in time. We hope to supervise and urge primary and secondary school students to exercise through technical means to improve the quality of primary and secondary school students’ exercise and improve people’s health through physical exercise.
Performance Evaluation of Spectral Efficiency for Uplink and Downlink Multi-Cell Massive MIMO Systems
Authors: Asif Rao Muhammad , Shakir Mustafa , Rehman Ateeq Ur , Shafiq Muhammad , Khan Rehan Ali , Khan Wali Ullah
Published: June 2022

Massive multiple-input and multiple-output (MIMO) systems have become the most persuasive technology for 5G as it increased the energy efficiency gigantically as compared to other wireless communication systems. Being the most vibrant research technology in the communication sector, this research work is based on the optimal model development of energy-efficient massive MIMO systems. The proposed model is a realistic model that augmented the spectral efficiency (SE) of massive MIMO systems where a multi-cell model scenario is considered. Channel estimation is carried out at the base stations (BSs) based on uplink (UL) transmission while the minimum mean-squared error (MMSE), Element-wise MMSE, and Least-square (LS) estimators are used for the estimation. We analyze the achievable SE of the UL based on the MMSE channel estimator with different receive combining schemes. Moreover, the downlink (DL) transmission model is also modelled with different precoding schemes by taking the same vectors used in combining schemes. The simulation results show a significant improvement in spectral efficiency by developing UL and DL transmission models and also realized that the average sum of SE per cell can be improved by optimized MMSE channel estimation, installing multiple BS antennas, and serving multiple UEs per cell. The findings of this work specify that the massive MIMO system can be developed by optimizing the channel estimation for the augmentation of SE in UL and DL transmissions. Conclusively, it can be summarized that some complex computations of MMSE channel estimators can enhance the average sum of SE per cell as per the results verified in this model.
Performance Investigation of Innovative Induction Motor Strategy Using Magnet for Traction Application
Authors: Usha S. , Geetha A. , Thentral T. M. Thamizh , Palanisamy R. , Bajaj Mohit , Khan Baseem , Kamel Salah
Published: June 2022

A novel traction AC motor is proposed by grouping magnets and coils in the stator design with aluminium as substantial for the housing of stator and end ring. The stator back iron is designed with silicon steel. As a result, the magnet can provide more repulsion when revolving the rotor, lowering the input side current. The configuration of the motor was changed to increase its effectiveness in terms of efficiency, and its performance appearances were investigated to compare it to the traditional design of motor. Magnet software was used to simulate the novel constructed induction motor. Most of the factories depend on this induction motor for its significant impact on industrial production and being an essential component of the plant for developing countries’ economic development. Using motor solver software, this paper examines the performance characteristics of a novel constructed induction motor, including efficiency, power factor, and losses. The output of the developed induction motor is compared to that of a traditional three-phase 2.2 kW induction motor for traction application using a motor solver.
Migration Law and Influence of Proppant in Segmented Multicluster Fracturing Wellbore of Deep Shale Horizontal Well
Authors: Jiang Tingxue , Wang Haitao , Wei Juanming , Zhong Guanyu , Zhao Yucheng , Zou Yushi
Published: June 2022

Intensive stage multicluster fracturing is the main technology of deep shale gas development, but this technology is easy to lead to the uneven propagation of multiple fractures. In order to deeply analyze the influence mechanism and law of proppant flow in the wellbore on multiple fractures and propagation, Firstly, based on the theoretical knowledge of computational fluid dynamics (CFD), a numerical model of solid-liquid two-phase flow of proppant migration in horizontal wellbore is established, which is calculated and solved by using the Euler-Euler multiphase-flow mixture model, and the effects of different influencing factors on the migration and distribution of proppant in wellbore are studied. Then, based on the fluid structure coupling theory, a planar three-dimensional (PL3D) numerical model of multicluster fracturing in horizontal wells is established. Taking the numerical simulation results of wellbore proppant migration as the initial condition, the influence law of proppant settlement on the fluid volume distribution among multiple clusters and the difference of multifracture geometry is clarified. The results show that the proppant content in the horizontal wellbore increases from heel end to toe end. The fracturing fluid viscosity and sand ratio are the main influencing parameters. The proppant settlement in the wellbore is also an important factor affecting the liquid and sand injection of multifracture. When considering the proppant settlement in the wellbore, the phenomenon of multifracture uneven propagation is more significant. The construction scheme of medium viscosity, large displacement fracturing fluid, large proppant size, and medium sand ratio in a certain range is conducive to promote the even propagation of multifracture. This study is helpful to guide the construction design of multicluster fracturing in horizontal wells, so as to improve the success rate of multicluster fracturing and greatly save the construction cost.
Challenges in the Diagnosis of Taenia solium Cysticercosis and Taeniosis in Medical and Veterinary Settings in Selected Regions of Tanzania: A Cross-Sectional Study
Authors: Mlowe Fredy , Karimuribo Esron , Mkupasi Ernatus , Churi Ayubu , Nyerere Antony D. , Schmidt Veronika , Ngowi Helena , Winkler Andrea S. , Mlangwa James
Published: June 2022

Background. Taenia solium (neuro) cysticercosis/taeniosis (TSCT) is a zoonotic disease complex. There is a perceived inefficient diagnosis of infections by either form, the adult pork tapeworm (taeniosis) and the larval stage of it (cysticercosis), in low-income settings, including Tanzania. This study aimed at identifying potential gaps around TSCT diagnosis and knowledge of primary healthcare providers (officers in charge (OICs) of primary healthcare facilities (PHFs)) and veterinarians (meat inspectors (MIs)) on various aspects of TSCT disease complex and addressing effective disease control in Tanzania. Methodology. A cross-sectional study was conducted between January and April 2020 in Manyara, Dodoma, Ruvuma, Iringa, and Arusha regions in Babati, Mbulu, Kongwa, Mbinga, and Nyasa districts. We interviewed 152 OICs of PHFs and 108 MIs using a structured questionnaire and 33 medical and veterinary officers from level I healthcare facilities and district livestock offices, respectively, from selected study districts to the respective ministerial level using key informant interviews. Results. Quantitative data revealed inadequate microscopic diagnostic facilities (54.6%) and personnel (100%) for taeniosis diagnosis in PHFs (n = 152). Approximately 81.2% of MIs compared with only 42.1% of OICs of PHFs scored above average regarding T. solium cysticerci knowledge. Nevertheless, 61.2% of OICs of PHFs compared with only 42.6% of MIs scored above average regarding the adult T. solium tapeworm knowledge. Qualitative data revealed inadequate availability of advanced diagnostic facilities (neuroimaging) and trained personnel for specific diagnosis of TSCT with a focus on neurocysticercosis (NCC) in secondary and tertiary healthcare facilities. Inadequately number of qualified MIs, slaughter slabs, and resource facilitation challenged porcine cysticercosis diagnosis. Conclusion. It is concluded that diagnostic capacity and knowledge of OICs of PHFs and MIs regarding TSCT are insufficient in both medical and veterinary sectors. A One Health approach should be adopted to improve TSCT diagnostic capacity and practitioners’ knowledge in both medical and veterinary sectors.
Effect of Comprehensive Care Based on Appropriate Chinese Medicine Techniques on Urinary Retention and Bladder Function Recovery after Total Hysterectomy in Patients with Cervical Cancer
Authors: Lu Qing , Wu LiangHong , Qi LiYing , Tie Ping , Guan Zhihong
Published: June 2022

Objective. To investigate the effect of comprehensive care based on appropriate Chinese medicine techniques on urinary retention and bladder function recovery after total hysterectomy in patients with cervical cancer. Methods. A total of 148 cases admitted after radical hysterectomy for cervical cancer from January 2019 to early September 2019 were used as the observation sample and were divided into control and experimental groups based on a randomized double-blind method. There were 74 cases each. The control group was given comprehensive care, and the experimental group was given comprehensive care based on appropriate Chinese medicine techniques. The intervention period was 2 weeks after surgery. The recovery rate of bladder function and the occurrence of urinary retention were compared between the two groups, and the duration of postoperative retention of urinary catheter, the amount of residual urine, and the feeling of urination were counted. Results. The experimental group had better urinary catheter retention time, time to first spontaneous voiding, time to get out of bed, and time to anal discharge than the control group; the experimental group had a higher rate of good bladder function recovery than the control group and better bladder recovery time, residual urine volume, and incidence of urinary retention than the control group; the patients in the experimental group had better UDI-6 scores. Conclusion. The implementation of comprehensive care based on appropriate Chinese medicine techniques can relieve patients’ difficulty in urination and improve their quality of life.
Analysis of Digital Economy Development Based on AHP-Entropy Weight Method
Authors: Yang Shuwen , He Jun
Published: June 2022

At present, China’s economic development is in a critical period of transformation, which needs to get rid of the dependence on the real estate industry and low-end export processing industry, and is in urgent need of new growth engines. The emergence of the digital economy has provided a boost to economic upgrading, but to give full play to the potential of the digital economy, we must have an accurate and full understanding of it. At present, the development of digital economy has become the focus of all circles. Digital economy is a multilevel and complex concept, so this paper establishes a multi-index comprehensive evaluation system and uses AHP-entropy weight method to measure the development level of China’s digital economy and, on this basis, analyzes the development level, dynamic changes, and regional differences of China’s digital economy. The results show that China’s digital economy is on the rise, which is mainly driven by the construction of digital infrastructure and the application of digital technology. By region, there is a big gap between different regions in the development of digital economy, and this gap is expanding continuously. The digital economy in the eastern region is in a leading position, but only in the development of the digital industry.