bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Guidance of Youth Labor Education Based on the “Combination of Education and Production Labor” Program Based on the Deep Learning Model
Authors: Xiao Linyu , Liao Xiaoyi
Published: October 2022

At present, there is a lack of research on Marx’s idea of “combining education and productive labor” and its guiding significance for youth labor education, and no effective teaching model has been formed. In response to this problem, this study proposes a semi-supervised deep learning model based on u-wordMixup (SD-uwM). When there is a shortage of labeled samples, semi-supervised learning uses a large number of unlabeled samples to solve the problem of labeling bottlenecks. However, since the unlabeled samples and labeled samples come from different fields, there may be quality problems in the unlabeled samples, which makes the generalization ability of the model worse., resulting in a decrease in classification accuracy. The model uses the u-wordMixup method to perform data augmentation on unlabeled samples. Under the constraints of supervised cross-entropy and unsupervised consistency loss, it can improve the quality of unlabeled samples and reduce overfitting. The comparative experimental results on the AGNews, THUCNews, and 20Newsgroups data sets show that the proposed method can improve the generalization ability of the model and also effectively improve the time performance. The study found that the SD-uwM model uses the u-wordMixup method to enhance the unlabeled samples and combines the idea of the Mean Teacher model, which can significantly improve the text classification performance. The SD-uwM model can improve the generalization ability and time performance of the model, respectively, 86.4 ± 1.3 and 90.5 ± 1.3. Therefore, the use of SD-uwM in Marx’s program is of great practical significance for the guidance process of youth labor education.
A Crop Growth Prediction Model Using Energy Data Based on Machine Learning in Smart Farms
Authors: Venkatesan Saravanakumar , Lim Jonghyun , Cho Yongyun
Published: October 2022

In the recent past, the agricultural industry has rapidly digitalized in the form of smart farms through the broad usage of data analysis and artificial intelligence. Commonly, high operating costs in a smart farm are primarily due to inefficient energy usage. Therefore, accurate estimation of agricultural energy usage and environmental factors is considered as one of the significant tasks for crop growth control. The growth sequences of crops in agricultural environments like smart farms are related to agricultural energy usage and consumption. This study aims to develop and validate an algorithm that can interpret the crop growth rate response to environmental and solar energy factors based on machine learning, and to evaluate the algorithm’s accuracy compared to the base model. The proposed model was determined through a comparative experiment of three representative machine learning techniques, which are random forest (RF), support vector machine (SVM), and gradient boosting machine (GBM), considering the energy usage for environmental control is highly associated with the paprika crop growth. Through the experiment performance with real data gathered from a paprika smart farm in South Korea, the multi-level RF can effectively predict paprika growth with an accuracy of 0.88, considering data analysis of factors that use solar energy. As a result of the experiment with the suggested model, the growth factors such as leaf length, leaf width, and environmental factors were found. Furthermore, the proposed algorithm can contribute to the development of applications through analysis of the crop growth big data for various plants in agricultural environments such as a smart farm.
Garden Landscape Design Method in Public Health Urban Planning Based on Big Data Analysis Technology
Authors: Jia Zixuan
Published: October 2022

Aiming at the goal of high‐quality development of the landscape architecture industry, we should actively promote the development and integration of digital, networked, and intelligent technologies and promote the intelligent and diversified development of the landscape architecture industry. Due to the limitation of drawing design technology and construction method, the traditional landscape architecture construction cannot really understand the public demands, and the construction scheme also relies on the experience and subjective aesthetics of professionals, resulting in improper connection between design and construction. At present, under the guidance of the national strategy, under the background of the rapid development of digital technologies such as 5G, big data, cloud computing, Internet of Things, and digital twins, the high integration of landscape architecture construction and digital technology has led to the transformation of the production mode of landscape architecture construction. Abundant professional data and convenient information processing platform enable landscape planners, designers, and builders to evaluate the whole life cycle of the project more scientifically and objectively and realize the digitalization of the whole process of investigation, analysis, design, construction, operation, and maintenance. For the landscape architecture industry, the significance of digital technology is not only to change the production tools but also to update the environmental awareness, design response, and construction methods, which makes the landscape architecture planning and design achieve the organic combination of qualitative and quantitative and also makes the landscape architecture discipline more scientific and rational. In this paper, the new method of combining grey relational degree with machine learning is used to provide new guidance for traditional landscape planning by using big data information in landscape design and has achieved very good results. The article analyzes the guidance of landscape architecture design under the big data in China and provides valuable reference for promoting the construction of landscape architecture in China.
An Efficient Intrusion Detection Method Based on Federated Transfer Learning and an Extreme Learning Machine with Privacy Preservation
Authors: Wang Kunpeng , Li Jingmei , Wu Weifei
Published: October 2022

Current network security is becoming increasingly important, and intrusion detection is an effective method to protect the network from malicious attacks. This study proposes an intrusion detection algorithm FLTrELM based on federated transfer learning and an extreme learning machine to improve the effect of intrusion detection, which implements data aggregation through federated learning and facilitates the construction of personalized transfer learning for all organizations. FLTrELM first builds a transfer extreme learning machine model to solve the problem of insufficient samples and probability adaptation, then uses the model to learn to protect data privacy without sharing training data under the federated learning mechanism, and finally obtains an intrusion detection model. Experiments on the NSL-KDD, KDD99, and ISCX2012 datasets verify that the proposed method can achieve better detection results and robust performance, especially for small samples and new intrusions, and protects data privacy.
Effect of Scattering Angle in Electron Transport of AlGaN and InGaN
Authors: Vijetha T. , Mallick P. S. , Karthik R. , Rajan Kavitha
Published: October 2022

The scattering angle between electrons plays a very important role for the calculation of scattering probability. The probability of scattering is an essential parameter for the simulation of electron paths. In this work, we calculated the scattering probability with scattering angle in AlGaN and InGaN at 77 K and found that the lower angle scatterings only dominate.
Application of Video Feedback System to Technical Analysis and Diagnosis of Throwing Athletes
Authors: Mengchao Tan , Chenqi Yan
Published: October 2022

Throwing sports have high technical difficulties and requirements. The traditional learning and training methods require athletes to start from observation and imitation and constantly repeat mechanized training. Athletes have no intuitive comparison and understanding of the overall situation of their own movement technology. Video feedback systems can make up for the shortcomings of traditional methods, so that athletes can more intuitively observe the problems of their own actions. Therefore, this paper puts forward the application research of technical analysis and diagnosis of throwing athletes based on video feedback system, and uses random forest regression algorithm to construct video feedback system. The comparative experimental results show that the students who study and train the movement technology through the video feedback system have higher performance in javelin throwing than the students in the control group, and the performance improvement range is higher. The javelin throwing movement technology is closer to the requirements of the standard movement, which can reduce the wrong movements of javelin throwing. It is more conducive for students to achieve better javelin throwing results.
Recognition and Modeling of Crisis Propagation Patterns Combined with Robot Simulation of Social Networks
Authors: Wang Yafei
Published: October 2022

In order to improve the identification effect of a crisis propagation mode, this paper studies the crisis propagation mode of social networks and uses an intelligent method to identify the crisis propagation mode. Moreover, this paper analyzes and deduces the features of the modulated signal from the two aspects of spectrum and autocorrelation functions and extracts and simulates the features of signals of different modulation types. In addition, this paper verifies the proposed recognition method from two aspects through theoretical experiments and measured data and builds an intelligent model. Through the experimental research, it can be seen that the identification effect and the control effect of the crisis propagation model based on the social network proposed in this paper are relatively obvious.
Analysis of the Effectiveness of Transradial Access Puncture in the Application of Complications and Comfort after Cerebral Angiography
Authors: Wan Hongyan , Gao Lan , Huang Daohua
Published: October 2022

Objective. To investigate the analysis of the effectiveness of transradial access puncture in the application of complications and comfort after cerebral angiography. Methods. Retrospectively analyzed 80 patients who met the inclusion and exclusion criteria and were randomly divided into the control group (femoral artery group n = 40) and test group (radial artery group n = 40) using a random number table from January 2021 to January 2022 admitted to the department of neurology and department of vascular interventions in our hospital and compared the incidence of postoperative puncture site bleeding, time to first postoperative urination, and incidence of postoperative urinary retention and postoperative changes in comfort level. Results. There was 1 case of postoperative puncture site bleeding in the test group and 6 cases of postoperative puncture site bleeding in the control group, with statistically significant differences (

P

 < 0.05); the time to first urination in the test group (62.47) was significantly better than that in the control group (85.97), with statistically significant differences (

P

 < 0.05); there were 0 cases of urinary retention in the test group and 6 cases in the control group, with statistically significant differences (

P

 < 0.05). The GCQ scores of patients in the test group were significantly higher than those in the control group, and the difference was statistically significant (

P

 < 0.05). Conclusion. Transradial access puncture has a good clinical effect and can effectively reduce the complication rate of patients, which is worth promoting.
Theoretical Correction of Viscosity Coefficient Measurement by Falling Ball Method
Authors: Wang Ruiqi , Zhang Qingyu , Xu Shihan , Cui Liyuan , Jiang Haonan
Published: October 2022

The measurement of viscosity coefficient of liquids is vital in plentiful fields. There are numerous ways to measure the viscosity coefficient such as capillary and rotary rheometry in which falling ball method is mostly widely used. The uncertainty of the terminal velocity and the limit of the viscosity coefficient scale are the principled disadvantages of the method. In our work, the relationship between the displacement and time is obtained by integral calculation. What’s more, we considered the radius of the ball, the radius of the graduated cylinder, and the height of the graduated cylinder by theoretical correction of the stokes expression. The new correction expression broadens the measured viscosity coefficient scale and also improves the precision dramatically. Experimental verification is also well processed which fits well with our theory. The deviation between the viscosity coefficient of castor oil measured by the new correction method and the standard value is only 0.045. The relationship between displacement and time is consistent with the theoretical prediction, and the room mean square error of the two is 0.065. Based on them, this method can be widely used in scientific researches and teaching practices.
Statistical Measurement and Influencing Factors of Green Total Factor Productivity of China’s Tourism Industry Based on DEA-EBM Model
Authors: Xiang Zikun , Che Shirui , Zhou Sijia
Published: October 2022

In order to explore the statistical measurement and influencing factors of green total factor productivity in tourism, this paper proposes the use of gray absolute correlation to measure the similarity between input variable sequences. Moreover, this paper obtains the key parameters of the combination of radial and nonradial in the model based on the proximity index of gray correlation and calculates the economic efficiency of the decision-making unit according to the steps. In addition, this paper combines the DEA-EBM model to carry out the statistical measurement of China’s tourism industry green total factor productivity and the analysis of influencing factors and verify it through data. Through research, it can be seen that the DEA-EBM model proposed in this paper can play an important role in the statistical measurement and analysis of influencing factors of green total factor production in the tourism industry.
Glycerol Waste to Bio-Ethanol: Optimization of Fermentation Parameters by the Taguchi Method
Authors: Chilakamarry Chaitanya Reddy , Mimi Sakinah A. M. , Zularism A. W. , Khilji Irshad Ahamad , Kumarasamy Sudhakar
Published: October 2022

Global attention caused by pollutants and greenhouse gas emissions leads to alternative fuels that decrease the dependence on fossil fuels and reduce the carbon footprint that preceded the development of biodiesel production. Glycerol residue is generated more significantly from the biodiesel industry as a byproduct and is left as waste. In this study, we utilized glycerol residue from the biodiesel industry as an excellent opportunity to convert ethanol by bioconversion. The waste glycerol was used as a good and cheap carbon source as a substrate to synthesize ethanol by immobilizing E. coli cells. The screening of parameters such as mass substrate, temperature, inoculum size, and fermentation time was carried out using the one-factor-at-a-time (OFAT) technique. The Taguchi model employed optimization of fermentation parameters. The process parameters showed the mass substrate glycerol of 20 g with an inoculum size of 20%, and 12 hours yielded the ethanol concentration of 10.0 g/L.
An Overview of Missed Nursing Care and Its Predictors in Saudi Arabia: A Cross-Sectional Study
Authors: Al Muharraq Essa H. , Alallah Sultan M. , Alkhayrat Saad A. , Jahlan Ali G.
Published: October 2022

Background. Nursing care is holistic, and missing any aspect of care can be critical to patients’ health. However, due to the complex and intense nature of the nursing practice, nurses have to unintentionally prioritize some activities, forcing them to omit some aspects of nursing care. Aim. To explore the dimensions of missed nursing care and its predictors within the Saudi Arabian healthcare system. Methods. Quantitative, cross-sectional study used the MISSCARE survey by utilizing nonprobability convenience sampling to collect the data of 604 staff nurses working in inpatient wards in Jazan, Saudi Arabia. Results. The overall mean of missed nursing care is (m = 1.37, SD = 0.45). Missed nursing care activities were mostly failure to attend interdisciplinary care conferences (m = 1.66, SD = 0.96) and patient ambulation thrice a day (m = 1.63, SD = 0.97). Missed nursing care was mainly caused by human resource shortage (m = 3.53, SD = 0.88). Missed nursing care is predicted by the turnover intention (B = 2.380, t = 3.829,

p
<
001

) and job satisfaction (B = −0.864, t = −4.788,

p
<
001

). Conclusion. Although missed nursing care is evident in Saudi Arabia, it is significantly lower than the international rates, and it is mainly caused by labor resource shortage which directly influences nurses’ job satisfaction and intention to leave. Optimizing the recruitment process, resource allocation and effective nurses’ retention programs are proposed solutions that may be beneficial to mitigate missed nursing care.
Economic Operation of the Regional Integrated Energy System Based on Particle Swarm Optimization
Authors: Li Sining , Chen Kai
Published: October 2022

Aiming at the problems of single planning technology and relatively few resource types in the process of regional comprehensive energy system planning at the current stage, this paper proposes a method based on the construction of regional comprehensive energy system planning and the operation model. Through the integration of the particle swarm optimization algorithm, this method can better realize the optimization and economic operation of the regional comprehensive energy system and build a system optimization mode based on two stages of planning and operation to pursue the optimal configuration of system equipment. Through the simulation algorithm, it is found that the solution time of the traditional basic particle swarm optimization algorithm is 10.49s, while the average solution time of the particle swarm optimization system proposed in this study is 7.93s; the efficiency is increased by 24.4%, and the system operation efficiency is significantly improved, providing theoretical and technical guidance for the economic operation of the regional comprehensive energy system.
The Effectiveness and Safety of Mesenchymal Stem Cells in the Treatment of Osteoarthritis: A Systematic Review and Meta-analysis of 28 Randomized Controlled Trials
Authors: Long Zhiyong , Zhang Mingsheng , Zhang Tianqing , Zeng Liuting , Yang Kailin , Yang Tiejun , Yu Ganpeng , Li Jun , Wu Yang , Chen Hua
Published: October 2022

Objective. To evaluate the effectiveness and safety of mesenchymal stem cells (MSCs) in the treatment of osteoarthritis (OA). Methods. Chinese databases (such as CNKI and SinoMed) and English databases (such as PubMed and Embase) were searched to collect randomized controlled trials (RCTs) of MSCs in the treatment of OA. The retrieval time is from inception to October 10, 2021. The literature was strictly selected according to the inclusion and exclusion criteria, data was extracted, and the quality was evaluated. RevMan 5.3 software was used for meta-analysis. STATA was used to evaluate publication bias. The registration number of this systematic review and meta-analysis is CRD42021277145. Results. A total of 28 RCTs involving 1494 participants were included. The primary outcomes showed that MSCs may reduce WOMAC pain and VAS at the 3rd-month follow-up [WOMAC pain: -3.81 (-6.95, -0.68),

P
=
0.02

. VAS: -1.11 (-1.53, -0.68),

P
<
0.00001

], and the effect lasts for at least 12 months [WOMAC pain: -4.29 (-7.12, -1.47),

P
=
0.003

. VAS: -1.77 (-2.43, -1.12),

P
<
0.00001

]. MSCs may also reduce WOMAC stiffness and physical function at the 6th-month follow-up [WOMAC stiffness: -1.12 (-2.09, -0.14),

P
=
0.03

. WOMAC physical function: -4.40 (-6.84, -1.96),

P
=
0.0004

], and the effect lasts for at least 12 months [WOMAC stiffness: -0.99 (-1.95, -0.03),

P
=
0.04

. WOMAC physical function: -3.26 (-5.91, -0.61),

P
=
0.02

]. The improvement of WOMAC pain, VAS, WOMAC stiffness, and WOMAC physical function may be clinically significant. Meanwhile, after the MSC injection, Lequesne had been reduced compared with the control group [-4.49 (-8.21, -0.77),

P
=
0.002

]. For adverse events, there is no significant difference in the safety of MSC injection and the control group [1.20 (0.97, 1.48),

P
=
0.09

]. The quality of WOMAC physical function and adverse events were moderate. Conclusion. Based on current evidence, MSCs may be a safety therapy that have a good curative effect in the treatment of OA, the onset time is no later than 3 months, and the time to maintain the curative effect is no less than 12 months. However, these results should be generalized with caution due to the generally low quality of evidence and RCTs.
Application of Multimedia Human-Computer Interaction Technology in Preschool Children Drama Education
Authors: Gong He
Published: October 2022

With the continuous development of multimedia technology and children’s drama education as a very important part of preschool education, the combination of the two has attracted the attention of many scholars at home and abroad. Drama education for preschool children is the initial stage of children’s learning and the most important part of preschool education system. At the same time, preschool children drama education is the most basic stage of children’s intellectual development. The correct and reasonable preschool children drama education plays a great role in promoting their intelligence and development. The drama education for preschool children based on multimedia human-computer interaction technology not only expands new teaching methods for the traditional drama education model but also provides a good platform for teachers to choose teaching resources and injects new vitality into preschool children’s music education. This paper proposes the application of multimedia human-computer interaction technology in preschool children’s drama education. We analyze the current preschool children’s drama education curriculum reform that has limitations. The level of teachers’ drama education needs to be improved. Young children lack awareness of drama. Drama education for children lacks strong support from parents and other problems. In order to solve the above problems, we focus on voice interaction technology, image interaction technology, and somatosensory interaction technology in multimedia human-computer interaction technology, which establishes a set of teacher-multimedia-student three-dimensional crossover multidirection learning activity modes. In the multidirection learning mode, students can quickly develop their sense of rhythm. Teachers use image interaction technology to guide students to think about the relationship between content and form, so as to gradually form their own unique style of drama. At the same time, somatosensory interaction technology can cultivate teaching tasks seamlessly connected with the environment, so that students can follow the hologram through hands-on practice. Finally, this paper sets up a questionnaire on the experience of human-computer interaction mode in preschool children’s drama education, mainly to conduct a questionnaire survey on front-line drama teachers, aiming at preschool children’s drama learning activities and teachers’ teaching methods. In numerical experiments, we show teachers’ evaluation of the teaching effect of speech synthesis technology integrated into preschool children’s drama education and the classroom effect evaluation of speech synthesis technology integrated into preschool children’s drama education. The evaluation results show that the application effect of multimedia human-computer interaction technology in preschool children’s drama education is good, which can provide better services for preschool children’s drama education.
Design of Chinese Teaching Evaluation System for International Students under the Background of Data Mining
Authors: Wang Yijing
Published: October 2022

In the Chinese teaching for foreign students, Chinese teachers do not participate in the assessment of their institutions, which is not conducive to the sustainable development of Chinese language education. The potential value of the teaching evaluation is not floating on the surface, so the data mining is used to discover implicit correlations between the data. The application of data mining in the evaluation of Chinese teaching for foreign students helps to ensure safety of the teaching evaluation system for foreign students. In this paper, a Chinese teaching evaluation system that is based on the data mining is built, in which the DA is applied to the evaluation of Chinese teaching. Finally, the performance of the algorithm is tested, the results show that the DA greatly improves the classification accuracy of the model, the improved model can largely alleviate overfitting, and the feature dimension data extracted by DA are more representative. The system proposed in this paper has good performance, which can greatly improve the security of the Chinese teaching evaluation system.
Product Innovation Design Method Based on BP Neural Network
Authors: Huang Shihui
Published: October 2022

Innovative product design is the core problem of modern industry and the source power of enterprise development. With the continuous improvement of China’s material level, product innovation design has changed from functional needs to emotional needs, and the product design method centered on users’ emotional needs has attracted much attention. With the emergence of new technologies such as artificial intelligence and big data, the automation and intelligence of advanced algorithms and innovative design methods for online product decision driven by multimodal multimedia data in e-commerce have become inevitable trends in the field of product design, and it is a big challenge to improve the innovative design ability of products by using information technology. In order to solve this problem, based on the research of BP neural network technology, this paper puts forward an innovative product design method based on image-Kempi method. The color features of images are reconstructed and integrated, and then transferred to product modeling, so as to generate new products with both content image modeling features and style image color features, which brings visual inspiration to users. The results show that KENPI method combines the theories of Kansei engineering, convolutional neural network, and neural style transfer, and establishes a mapping model between product modeling elements and product semantics. Convolutional neural network and neural style transfer model are used to extract, reconstruct, and integrate the color features of style diagrams, and transfer them to product modeling to design new product images. By evaluating the image quality and comparing the product semantics before and after the migration, the validity and feasibility of the migration are verified. Based on BP neural network, a nonlinear mapping model between product attribute space and product semantic space is constructed, and the generalization ability of the model is evaluated, which verifies the feasibility and effectiveness of this method. The research results have important theoretical guiding significance for improving the innovative design ability of enterprises, enhancing product competitiveness, and customer satisfaction.
Proteomic Analysis of Decellularized Extracellular Matrix: Achieving a Competent Biomaterial for Osteogenesis
Authors: Monteiro-Lobato Gabriela M. , Russo Pedro S. T. , Winck Flavia V. , Catalani Luiz H.
Published: October 2022

Decellularized ECMs have been used as biological scaffolds for tissue repair due to their tissue‐specific biochemical and mechanical composition, poorly simulated by other materials. It is used as patches and powders, and it could be further processed via enzymatic digestion under acidic conditions using pepsin. However, part of the bioactivity is lost during the digestion process due to protein denaturation. Here, stepwise digestion was developed to prepare a competent biomaterial for osteogenesis from three different ECM sources. In addition, three different proteases were compared to evaluate the most effective digestion protocol for specific cellular processes. GAGs and peptide quantification showed that the stepwise method yielded a higher concentration of bioactive residues. Circular dichroism analysis also showed that the stepwise approach preserved the secondary structures better. The protein profiles of the digested ECMs were analyzed, and it was found to be highly diverse and tissue‐specific. The digestion of ECM from pericardium produced peptides originated from 94 different proteins, followed by 48 proteins in ECM from tendon and 35 proteins in ECM from bone. In addition, digested products from pericardium ECM yielded increased proliferation and differentiation of bone marrow mesenchymal stem cells to mature osteoblasts.
In Vitro and In Silico Analysis of Bergenia ciliata and Mimosa pudica for Inhibition of α-Amylase
Authors: Bohara Mahesh , Ghaju Sajani , Sharma Kabita , Kalauni Surya Kant , Khadayat Karan
Published: October 2022

The discovery of antidiabetic natural products is a flourishing field of opportunity in the sector of drug discovery. Various medicinal plants with diverse chemical constituents have been extensively studied for drug development. Bergenia ciliata and Mimosa pudica have been traditionally used for the treatment of diabetes and consist of valuable phytochemicals. In this study, we have analyzed total phenolic and flavonoid content along with the antioxidant and α-amylase inhibitory activity. The crude extract of B. ciliata contains higher levels of TPC whereas higher TFC was observed in M. pudica. The strong antioxidant activity was shown by B. ciliata with an IC50 value of 125.86 ± 4.16 μg/mL. The ethyl acetate extract of B. ciliata and M. pudica showed higher α-amylase inhibitory activity with an IC50 value of 13.97 ± 0.10 and 11.97 ± 0.36 μg/mL, respectively. The biological potential of the reported phytochemicals was also assessed by using bioinformatic tools. Furthermore, the active phytochemicals from these plants were docked with human pancreatic α-amylase to study their inhibitory activities to this enzyme. The docking analysis revealed that catechin has lower binding energy (−8.6 kcal/mol) as compared to the commercial drug acarbose (−7.3 kcal/mol) indicating higher affinity towards the enzyme. This study additionally sheds more light on medicinal plants’ antidiabetic activity. So, this study will aid in the investigation of the biological properties of these plants as well as the identification of potential compounds with antidiabetic properties.
Nonlinear Effect of Urbanization on the Gap between Urban and Rural Elementary Education in China
Authors: Ju Fangyu , Wang Shuqing , Lin Wei
Published: October 2022

The urban-rural gap of elementary education seriously affects social fairness, so the study on the urban-rural gap of elementary education can help promote social fairness in China. China’s urbanization is an important variable affecting the social process, and its impact on the urban-rural gap of elementary education is worthy of further study. Based on China’s provincial panel data from 2006 to 2017, this paper uses the Theil index to measure the urban-rural gap in different aspects of elementary education and uses principal component analysis (PCA) to construct a comprehensive index to objectively measure the urban-rural gap of overall elementary education in China. Our results show that the gap between urban and rural areas in China’s elementary education showed an upward trend from 2006 to 2010, and the gap decreased year by year from 2010 to 2017. Then we used the panel smooth transition regression (PSTR) model to study the impact of urbanization on the urban-rural gap of elementary education in China and find evidence that urbanization has a nonlinear effect on the urban-rural gap of elementary education. That is, in economically underdeveloped areas, urbanization exacerbates the gap between urban and rural areas in elementary education, while in economically developed areas, urbanization narrows the gap between urban and rural areas in elementary education. Therefore, developing economy and continuing to promote urbanization are effective measures to narrow the gap between urban and rural areas in elementary education.
CCMbAS: A Provably Secure CCM-Based Authentication Scheme for Mobile Internet
Authors: Zhang Yu , Sun Guangmin , Zhai Peng
Published: October 2022

To improve the security of authentication system and strengthen privacy protection in mobile Internet environment, this paper proposes a provably secure Chebyshev chaotic map (CCM)-based authentication scheme (CCMbAS). The proposed scheme transformed the traditional public key of Chebyshev chaotic map into a private key and combined two private keys to compute a one-time key used to encrypt authentication information. The scheme is verified using security review of BAN logic and ProVerif simulation tool. The verification results confirm that the scheme is well secured against all existing security threats. Compared with similar schemes, the proposed scheme is more efficient and secure. The security analysis shows that the proposed scheme can fulfil secure demands and ensure the security of user’s information in mobile Internet environment.
Analysis of the Influence of Midwife Led Antenatal Clinic on the Delivery Outcomes of Primipara under the Evaluation of Medical Data
Authors: Fan Wei , Wang Ling , Zhang Lili , Liu Xiaoling , Meng Zhaoyan
Published: October 2022

Objective. In order to improve the comprehensive effect of primipara delivery outcomes, the midwife led prenatal clinic of data mining is analyzed to alleviate the negative emotions of patients and improve the delivery results of patients. Methods. A total of 86 patients who were filed in the obstetrics department of our hospital from October 2021 to May 2022 and planned to deliver in our hospital were selected as the research objects. They were divided into the reference group (

n
=
43

) and the observation group (

n
=
43

) according to the random number table method. Among them, the reference group received routine antenatal clinics, and the observation group received midwives’ participation in antenatal clinics for intervention. The total duration of labor, the scores of various psychological states including antenatal anxiety (SAS) and antenatal depression (SDS), as well as the pregnancy outcome and delivery compliance rate of the two groups were compared. Results. The psychological state evaluation of delivery in the observation group, whether SAS score or SDS score, was significantly lower than that in the reference group, and the difference was statistically significant. The whole labor process time of patients in the observation group was significantly shorter than that in the reference group, and the difference was statistically significant. The delivery compliance of patients in the observation group during the whole perinatal period was also higher than that of the reference group, and the difference was statistically significant. All

P

values were<0.05. Conclusion. The antenatal clinic led by midwives can promote primiparas to increase the success rate of natural delivery, improve the treatment compliance of the whole perinatal period, reduce the psychological pressure of primiparas, effectively shorten the total time of production, and have a significant impact on the outcome of delivery. It should be widely used.
Named Entity Recognition for Public Interest Litigation Based on a Deep Contextualized Pretraining Approach
Authors: Dong Hongsong , Kong Yuehui , Gao Wenlian , Liu Jihua
Published: October 2022

The named entity recognition (NER) in the field of public interest litigation can assist prosecutors in handling cases and provide them with specific entities in making legal documents. Previously, the context-free deep learning model is used to catch the semantic comprehension, in which the static word vector is obtained without considering the context. Moreover, this kind of method relies on word segmentation technology and cannot solve the error transmission caused by word segmentation inaccuracy, which brings great challenges to the Chinese NER task. To tackle the above issues, an entity recognition method based on pretraining is proposed. First, based on the basic entities, three legal ontologies, NERP, NERCGP, and NERFPP are developed to expand the named entity recognition corpus in the judicial field. Second, a variant of the pretrained model BERT (Bidirectional Encoder Representations from Transformer) called BERT-WWM (whole-word mask)-EXT(extra) is introduced to catch the text character-level word vector hierarchical and the context bidirectional features, which effectively solve the problem of task boundary division of named entities. Then, to further improve the model recognition effect, the general knowledge learned from the pretrained model is used to fit the downstream neural network BiLSTM (bi-long short-term memory), and at the end of the architecture, CRF (conditional random fields) is introduced to restrict the label relationship. Finally, the experimental results show that the proposed method is more effective than the existing methods, which reach 96% and 90% in the F1 index of NER and NERP entities, respectively.
MicroRNA-146: Biomarker and Mediator of Cardiovascular Disease
Authors: Mahdavi Fatemeh Sadat , Mardi Shayan , Mohammadi Sareh , Ansari Sarina , Yaslianifard Somayeh , Fallah Parviz , Mozhgani Sayed-Hamidreza
Published: October 2022

Cardiovascular diseases (CVDs) are the prime cause of morbidity and mortality worldwide. Although noticeable progress has been made in the diagnosis, prognosis, and treatment, there is still a critical demand for new diagnostic biomarkers and novel therapeutic interventions to reduce this disease incidence. Many investigations have been conducted on the regulatory effects of microRNAs in cardiovascular diseases. miRNA circulating serum level changes are correlated with several CVDs. In addition, there is growing evidence representing the potential role of miRNAs as diagnostic biomarkers or potential therapeutic targets for CVD. Preliminary studies identified the prominent role of miR-146 in host defense, innate immunity, and different immunological diseases by regulating cytokine production and innate immunity modification in bacterial infections. However, more recently, it was also associated with CVD development. miR-146 has received much attention, with positive results in most studies. Research demonstrated the crucial role of this molecule in the pathogenesis of cardiac disease and related mechanisms. As a result, many potential applications of miR-146 are expected. In this paper, we provide an overview of recent studies highlighting the role of miR-146 in CVD, focusing on CAD (coronary artery disease), cardiomyopathy, and MI (myocardial infarction) in particular and discussing its current scientific state, and use a prognostic biomarker as a therapeutic agent for cardiovascular diseases.
Clinical Characteristics and Treatment of Adult Idiopathic Carpal Tunnel Syndrome Accompanied with Trigger Digit
Authors: Hong Jinjiong , Wang Xiaofeng , Xue Jianbo , Li Jimin , Zhang Minghua , Mao Weisheng
Published: October 2022

Purpose. To investigate the clinical characteristics and treatment of adult idiopathic carpal tunnel syndrome (CTS) accompanied with trigger digit. Materials and Methods. A retrospective analysis was performed on a total of 74 patients with adult idiopathic CTS accompanied with trigger digit admitted to and treated at the Hand Surgery Department of Ningbo No. 6 Hospital from January 1, 2017 to December 31, 2019. Data on patients’ gender, age, occupation, course of the disease, menstruation, surgeries, examination-related information, complications, treatment methods, and prognoses during follow-up were recorded and subsequently used to analyze the pathogeneses, clinical characteristics, and treatment. Results. A total of 74 patients (72 females and 2 males) were included. Among female patients, 51 were postmenopausal and 18 were non-postmenopausal. There were 101 fingers with trigger digit, including 14 patients with trigger digit in both hands, and 115 wrists affected by the CTS. The average course of CTS was

34.5
±
49.3

months, and that of trigger digit was

10.5
±
22.4

months. Seventy had both trigger digit and CTS in one hand, while among patients with both hands involved, only 4 had trigger digit or CTS in one hand. Eighty-nine fingers underwent A1 pulley release, and 104 hands underwent carpal tunnel surgery, with steroids being injected under the adventitia of the median nerve during the surgery. All patients who underwent surgeries had I/A-healed incisions, and 14 of them had obvious synovial hyperplasia observed in the carpal tunnel and flexor tendon sheath during surgeries. Follow-up visits, which lasted 3 to 35 months, had an average duration of 1.34 years and included 72 patients. In 63 patients (63/72), the syndrome of tenosynovitis and numbness disappeared and normal hand functions were restored; in 6 patients, the numbness in hands greatly improved and normal hand functions were almost completely restored, while no improvement in numbness of hands and limited hand functions were still observed in 3 patients. Conclusion. CTS accompanied with trigger digit was more common in postmenopausal females, and the course of CTS was longer than that of trigger digit. CTS and trigger digit were more likely to simultaneously occur in the same hand, while some patients might not have obvious synovial hyperplasia in the carpal tunnel. Surgeries were effective in severe cases.
Model-Predicted Control System for the Real-Time Operation of an Urban Drainage System to Mitigate Urban Flood Risk: A Case Study in the Liede River Catchment, Guangzhou, China
Authors: Quan Xing , Chen Zhile , Jiang Tao , Liu Weifei , Mo Yaojun , Chen Bing
Published: October 2022

A model-predicted control (MPC) system, which is based on a storm water management model (SWMM) and uses a multi-objective particle swarm optimization algorithm, is developed and applied to optimize the real-time operation of an urban drainage system (UDS) in the Liede River catchment, Guangzhou, China. By comparing the results of three control scenarios (i.e., the original control scenario, the current MPC, and the ideal MPC) under three typical rainfall events, the results demonstrate that the MPC system can effectively mitigate urban flood risk in engineering applications and the decision-making of the MPC system is valid. By comparing the control results of the MPC system under different rainfall return periods (e.g., 1, 2, 3, 5, and 10 years), it is found that compared with the original control scenario, the total overflow is reduced by 10%, the total overflow time is reduced by 10%, or the node overflow start time is delayed by an average of 10 minutes, and the real-time control of the MPC system is only effective when the return period of the rainfall is less than three years. It is important to explore different ways of combining the MPC system and feasible capital measures to cope with urban flood risk and challenges of climate change in future works (e.g., mean sea level rise and intense rainfall).
Research Progress and Prospects on the Treating and Disposal for Waste Oil-Based Drilling Cuttings from Shale Gas Wells
Authors: Deng Yuan , Yin Hong , Chen Ziqiang , Chen Yafei , He Donglin , Gong Haifeng , Jiao Zhaojie , Yao Shuangquan , Tu Pu
Published: October 2022

Oil-based drilling cuttings (OBDC) from shale gas wells is a kind of typical hazardous waste produced during the exploration and development of shale gas reservoirs, which will endanger the natural ecosystem and human health. This article summarized the OBDC treating and disposal methods commonly used all over the world. The treating methods were divided into restriction, separation, and degradation, while the disposal methods were divided into landfill, land farming, and resource recovery. The technical principles, technological process, advantages, and limitations of existing OBDC treating and disposal methods were overviewed in detail, and the development prospects of OBDC and resource recovery were illustrated as well. Finally, we proposed to maximize the resource recovery of OBDC by multitechniques processing, tracking the processed products to improve the reliability of product quality. In addition, the data system for original materials used for different methods should be established to service industrial development.
Pullback Attractors for a Class of Semilinear Second‐Order Nonautonomous Evolution Equations with Hereditary Characteristics
Authors: Zhang Fang-hong , Chen Xiao-hua
Published: October 2022

In this paper, we investigate the long‐time behavior for the nonautonomous semilinear second‐order evolution equation (∂2u/∂t2) − Δu − Δ(∂u/∂t) − Δ(∂2u/∂t2) = f(t, u(x, t − ρ(t))) + g(t, x), in(τ, ∞) × Ω with some hereditary characteristics, where Ω is an open‐bounded domain of ℝN(N ≥ 3) with smooth boundary ∂Ω. Firstly, we establish the existence of solutions for the second‐order nonautonomous evolution equation by the standard Faedo–Galerkin method, but without the uniqueness of solutions. Then by proving the pullback asymptotic compactness for the multivalued process {U(t, τ)} on , we obtain the existence of pullback attractors in the Banach spaces for the multivalued process generated by a class of second‐order nonautonomous evolution equations with hereditary characteristics and ill‐posedness.