bluuebunny/crossref_metadata_2025 huggingface dataset:
New Development Strategy for Economic Platform Using Big Data Analysis
Authors: Zhao Wei
Published: August 2022

With the development of the Internet platform, the traditional economic model has been gradually abandoned by the times due to its unilateral sex transactions and underdeveloped information dissemination characteristics. A new economic model was born with the development of the information age. The network economic platform is a new productivity organization platform and a pillar industry for the development of the new economy. Taking advantage of the wide spread of the Internet and the participation of individuals or organizations, network economic platforms play an important role in promoting multi-platform economic growth and mass innovation. However, with the development of the network platform economy, the network platform appears saturated. The growth trend of the online platform economy is not as good as before, and online platforms are mainly monopolized by several major online platforms, so it is difficult for small businesses or companies to have high economic returns. In the face of these shortcomings of the network platform, it is necessary to analyze the economic status of the network platform through big data and develop new development strategies. Faced with these defects of the network platform, it analyzes the economic status of the network platform through big data and develops new development strategies to make the network economy grow effectively. This paper draws conclusions by analyzing the economic growth ability, real-time resource allocation ability, customer mining ability, and flexible price adjustment ability of the network platform through technologies such as big data. The network platform for big data analysis has an average efficiency of 93.8% in allocating resources in real time. It is also far superior to traditional network platforms in mining customers and flexibly adjusting prices. The growth economy of online platforms under big data analysis is 65.7 times than that of traditional platforms. To this end, a new strategy is needed: vigorously adjusting the resource allocation of the network platform and in-depth mining of platform information can effectively grow the platform economy.
Implementation of Network Data Mining Algorithm for Associated Users Based on Multi-Information Fusion
Authors: Zhang Hui
Published: August 2022

In order to accurately and effectively mine relevant users in social networks, we can stop false information and illegal activities in the network, thereby ensuring the safety and integrity of the network environment. A method is proposed for the implementation of a data mining algorithm of a user network based on the fusion of several data. AUMA-MRL (associated user mining algorithm based on multi-information representation learning) proposes an associated user mining algorithm based on node characteristics, neighborhood information, and global network structure information. The steps of the algorithm are as follows: combining each user of the social network into a node using a method where each node is installed separately and combining network user characteristics and user relationship information. A user pair is a network similarity vector that represents the similarity of users in different dimensions. Based on these similarity vectors, a corresponding user separation algorithm is formed. It examines the feasibility and efficiency of the AUMA-MRL algorithm for researching relevant users. The proportion of associated users in the network to be fused is lower than that of nonassociated users, and the prediction has little effect on improving the recall rate of nonassociated users, so the recall rate is slightly lower than the accuracy. This algorithm can quickly get the embedding of new nodes and the similarity vector between new nodes and other nodes in the network, so as to quickly mine the associated users of new nodes in the network and enhance the robustness of the network associated user mining algorithm.
Cloud Statistics of Accounting Informatization Based on Statistics Mining
Authors: Jin Taolan , Zhang Bo , Yang Zhi
Published: August 2022

With the rapid development of information technology, the amount of all kinds of data information is increasing rapidly. As an important means to collect, store, and manage massive data, and then analyze and predict the habits and characteristics of certain groups of people and even the development trend of a certain industry, big data technology provides a comprehensive strategic basis for management decision makers that the traditional processing mode cannot match. Contemporary management accounting serves the whole process of enterprise internal control, so it will produce a large number of various data. With the explosive growth of network data and the increasing scale of database, more and more people begin to study data mining, and the classification algorithm, as the key technology in data mining, has also received extensive attention. In order to further improve the information technology level of enterprise management accounting and increase the depth of information application, many enterprises began to pay more attention to data mining, and through deep data mining, the depth and breadth of enterprise data analysis were improved. In the research of data and accounting informatization, data mining technology accounts for about 50% of informatization, which is the way for future development. With the advent of the information age, the dependence of enterprises on information technology in the process of accounting management has been further improved. If enterprises want to achieve better development in the information age, they need to pay more attention to the information technology of management accounting and improve the application ability of enterprise staff in information.
Epithelial-Mesenchymal Transition Gene Signature Is Associated with Neoadjuvant Chemoradiotherapy Resistance and Prognosis of Esophageal Squamous Cell Carcinoma
Authors: Song Kewei , Gu Baohong , Ma Chenhui , Wang Bofang , Wang Na , Yu Rong , Chen Hao
Published: August 2022

Background. Neoadjuvant chemoradiotherapy (neo-CRT) in combination with surgery increases survival compared to surgery alone, as indicated by the esophageal squamous cell carcinoma (ESCC) treatment recommendations. However, the benefits of neo-CRT are diverse among patients. Consequently, the development of new biomarkers that correlate with neo-CRT might be important for the treatment of ESCC. Methods. The differentially expressed genes (DEG) between responsive and resistant samples from the GSE45670 dataset were obtained. On the TCGA dataset, survival analysis was performed to identify prognosis-related-EMT-genes. For EMT score model construction, lasso regression analysis in the TCGA cohort was used to identify the genes. In the TCGA-ESCC cohort, age, stage, and EMT score were used to construct a nomogram. Results. In total, 10 prognosis-related-EMT-genes were obtained. These 10 genes consisted of 6 risky genes and 4 protective genes. Based on the lasso analysis and univariate Cox regression, an EMT score model consisting of 7 genes (CLEC18A, PIR, KCNN4, MST1R, CAPG, ALDH5A1, and COX7B) was identified. ESCC patients with a high EMT score have a worse prognosis. These genes were differentially expressed between responsive and resistant patients and had a high accuracy for distinguishing resistant and responsive patients. Conclusions. The identified genes have the potential to function as molecular biomarkers for predicting ESCC patients’ resistance to neo-CRT. This research may aid in the elucidation of the molecular processes driving resistance and the identification of targets for improving the prognosis for ESCC.
Trajectory Tracking of Soccer Motion Based on Multiobject Detection Algorithm
Authors: Xie Yuping
Published: August 2022

In order to improve the tracking ability of soccer robot in the complicated static and dynamic environment, a method of soccer trajectory tracking based on multiobject detection algorithm is proposed. This method makes use of the advantages of convenient polar coordinate calculation and realistic path simulation and puts the path coding of the soccer robot in two-dimensional polar coordinates. Then, the distance relationship between the current path point, the next path point, and the obstacle point is used to judge whether to carry out path planning. When the obstacle is encountered, the improved PSO algorithm with nonlinear inertia weight is called to carry out path planning. The simulation results show that under two obstacles, when the number of iterations is

T
=
19

, the soccer robot starts to avoid obstacles and intercept. When iteration number

T
=
10

, the soccer robot starts to avoid obstacles and intercept side by side. Under multiple obstacles, when

T
=
19

, the soccer robot starts to avoid obstacles and intercept in front. When

T
=
30

, the soccer robot reaches the target point. The convergence of the improved PSO algorithm and the effectiveness of path planning are verified.
Occurrence of Spot Blotch in Spring Barley Caused by Bipolaris sorokiniana Shoem. in South-Eastern Kazakhstan
Authors: Dutbayev Yerlan , Kuldybayev Nurlan , Daugaliyeva Saule , Ismailova Elvira , Sultanova Nadira , Özer Göksel , Slyamova Ayana , Mukin Kadyrzhan , Dababat Abdelfattah , Yessimbekova Minura
Published: August 2022

In Kazakhstan, barley (Hordeum vulgare L.) is the second most important cereal crop after wheat, with an annual production of approximately 1.9 million tons. The study aimed to characterize Bipolaris sorokiniana isolates obtained from barley fields surveyed. A total of 21 diseased leaves showing spot blotch symptoms were collected from experimental plots located close to the Kazakh Research Institute of Agriculture and Crop Production, where the spring barley Arna cultivar was planted in June 2020. The overall strategy for control of spring barley blotch in the Almaty region of Kazakhstan should include the determination of the aggressiveness of the pathogen isolates to better understand the biology of the diseases and ultimately proper control strategy. Pathogenicity of B. sorokiniana isolates was made on barley seedlings in vitro. Inoculated seedlings showed clear symptoms of B. sorokiniana, and therefore, Koch’s postulates were fulfilled by reisolating the pathogen from artificially inoculated seedlings and identifying it based on standard morphology criteria. Further investigation is needed to understand the impact of B. sorokiniana on barley production in Kazakhstan.
An Immune-Related Prognostic Risk Model in Colon Cancer by Bioinformatics Analysis
Authors: Lai Qing , Feng Haifei
Published: August 2022

Colon cancer is one of the leading malignancies with poor prognosis worldwide. Immune cell infiltration has a potential prognostic value for colon cancer. This study aimed to establish an immune-related prognostic risk model for colon cancer by bioinformatics analysis. A total of 1670 differentially expressed genes (DEGs), including 177 immune-related genes, were identified from The Cancer Genome Atlas (TCGA) dataset. A prognostic risk model was constructed based on six critical immune-related genes (C-X-C motif chemokine ligand 1 (CXCL1), epiregulin (EREG), C-C motif chemokine ligand 24 (CCL24), fatty acid binding protein 4 (FABP4), tropomyosin 2 (TPM2), and semaphorin 3G (SEMA3G)). This model was validated using the microarray dataset GSE35982. In addition, Cox regression analysis showed that age and clinical stage were correlated with prognostic risk scores. Kaplan–Meier survival analysis showed that high risk scores correlated with low survival probabilities in patients with colon cancer. Downregulated TPM2, FABP4, and SEMA3G levels were positively associated with the activated mast cells, monocytes, and macrophages M2. Upregulated CXCL1 and EREG were positively correlated with macrophages M1 and activated T cells CD4 memory, respectively. Based on these results, we can conclude that the proposed prognostic risk model presents promising novel signatures for the diagnosis and prognosis prediction of colon cancer. This model may provide therapeutic benefits for the development of immunotherapy for colon cancer.
β-Cyfluthrin-Mediated Cytotoxicity of Cultured Rat Primary Hepatocytes Ameliorated by Cotreatment with Luteolin
Authors: Mousavi Lachin , Zadeh-Hashem Elham , Imani Mehdi
Published: August 2022

The current study was designed to evaluate the possible protective effects of luteolin against β-cyfluthrin-mediated toxicity on the primary culture of rat hepatocytes (RHs). In the first step, the exposure of RHs to β-cyfluthrin (10, 20, 40, and 80 μM) was assessed by MTT. Second, redox condition was evaluated in cotreatment of cells with luteolin (20, 40, and 60 μM) and β-cyfluthrin (40 μM) at both medium and intra levels. In comparison to control, viability was lower in 40 and 80 μM β-cyfluthrin-treated groups at 24 h and all β-cyfluthrin-treated groups at 48 h (

P
<
0.05

). Cotreatment with 20 or 40 μM luteolin + 40 μM β-cyfluthrin resulted in a higher viability value compared to β-cyfluthrin alone at 24 and 48 h of incubation (

P
<
0.05

). Administration of 20 or 40 μM luteolin with β-cyfluthrin led to the decrease of malondialdehyde and total nitrate/nitrite and the increase of total antioxidant capacity (TAC) values in both medium and intrahepatocyte levels compared to the β-cyfluthrin-treated group at 48 h (

P
<
0.05

). It seems that low and medium doses of luteolin possess the potential to reduce β-cyfluthrin-mediated hepatotoxicity via attenuation of peroxidative/nitrosative reactions and augmentation of TAC levels.
Oral Health Self-Management Ability and Its Influencing Factors among Adolescents with Fixed Orthodontics in China: A Mixed Methods Study
Authors: Li Yan , Liu Jian , Xu Yingxin , Yin Jun , Li Li
Published: August 2022

Objective. To understand the oral health self-management ability status and influencing factors among adolescent patients with fixed orthodontics in Nanjing and to provide a reference for formulating targeted intervention measures. Methods. A mixed research method was used. First, the convenience sampling method was used to select adolescent patients with fixed orthodontics admitted to the orthodontic department of a dental hospital in Nanjing from November 2021 to March 2022. The oral health self-management ability questionnaire was used for the investigation; then, 15 children with poor oral health management ability were selected for in-depth interviews. Results. The total score of oral health self-management ability of 290 adolescent children with fixed orthodontics was 45.6-90.8 points, with an average score of

69.63
±
7.40

of which knowledge, belief, and behavior dimension scores were

72.09
±
10.47
,
68.50
±
10.13
,
and
 
67.63
±
8.67

, respectively, and the environmental score was

69.91
±
12.50

. Multiple regression analysis showed that sex, age, bracket wearing time, grade, and place of residence were related to the scores of each dimension of self-management. Qualitative research shows that the main reasons for the poor oral health self-management ability of adolescents with fixed orthodontics are the lack of awareness during fixed orthodontics, lack of knowledge channels, low compliance, inability to solve oral problems during treatment, difficulty in adhering to oral care behaviors, and lack of motivation to treat. Conclusion. The oral health self-management ability of adolescent children with fixed orthodontics needs improvement, and a precise health intervention plan should be formulated.
Pattern Recognition of Wushu Routine Action Decomposition Process Based on Kinect
Authors: Cao Chenxing , Shan Bai , Zhang Haiyan
Published: August 2022

Human action recognition is a hotspot in the fields of computer vision and pattern recognition. Human action recognition technology has created huge social value and considerable economic value for the society. Meeting people’s needs and understanding people’s expressions are the current research focus. Aiming at the problem that the movement cannot be continuously identified and due to a lack of detailed features in the action decomposition pattern recognition in the traditional Wushu routine decomposition process, it is proposed to use Kinect technology to identify the Wushu routine movement decomposition process in the Wushu routine movement decomposition process. This paper analyzes the principle of skeleton tracking and skeleton extraction performed by the Kinect human sensor and uses the Kinect sensor with the Visual Studio 2015 development platform to collect and process the skeleton data of limb movements and defines eight static limb motion samples and four dynamic limbs. The study uses a deep learning neural network algorithm to train and identify the established database of static body movements and uses the same template matching algorithm and K-NN. The recognition effects of the algorithms were compared and analyzed, and it was concluded that the static body motion recognition rates of the three algorithms were all above 90%. In this paper, recognition experiments are carried out on the MSR action 3D database. The influence of different integrated decision-making methods on the recognition results is further discussed and analyzed, and the average method integrated decision-making, which is most suitable for the algorithm model in this paper, is proposed. The results show that the recognition accuracy of the algorithm reaches 98.1%, which proves the feasibility of the preprocessing algorithm.
Designing Data Visualization Using Artificial Intelligence for Urban Intelligent Transportation Scenarios
Authors: Yang Xuan , Pu Zhiyan , Zhang Lei
Published: August 2022

Artificial intelligence refers to a simulation extension and expansion technology that has found its presence in various applications and research domains. Artificial intelligence allows the related theories to portray similar to human intelligence. It combines developments in several fields, including computer science, statistics, and linguistics. The research objects of data visualization can be divided into three aspects: data, visualization technology, and visualization performance. This paper aims to study the data visualization design of artificial intelligence in urban intelligent transportation scenarios. It predicts the traffic flow via the traffic control method using neural network. It provides an effective way for timely dredging and alleviating problems, such as traffic jams and establishing alternative routes. This paper firstly analyzes the methods of artificial intelligence, traffic control methods, and data visualization and then designs the visualization based on artificial intelligence in traffic scenarios. By comparing the accuracy analysis of different models, the experimental results show that the error of the peak traffic flow is less than 10% and the lowest error value is 2.2%.
PE Classroom Teaching Innovation Based on Deep Learning from the Perspective of New Curriculum Standard
Authors: Tang Yingting , Zhu Qiang
Published: August 2022

In recent years, due to the influence of various factors, most of the physical quality of primary and secondary school students in China are in a state of subhealth. According to relevant studies, nearly 70 percent of Chinese students lack daily physical exercise. Physical quality is the primary factor and prerequisite of study and work, so how to improve the physical quality of primary and middle school students has become the top priority of physical education. Based on the requirements and guidance of China’s physical education in the new curriculum standard, this paper innovates China’s physical education classroom teaching to a certain extent based on deep learning algorithm. The final results show that the students who choose PE class based on deep learning algorithm account for about 85% of the total number of students, which exceeds the students who choose traditional PE class by 70%. Therefore, we believe that the estimation and recognition of students’ movement posture in PE class can not only greatly improve students’ enthusiasm for physical exercise but also avoid sports injuries caused by inaccurate operation in the process of exercise. Human posture estimation is to detect the position of each part of the human body from the image and calculate its direction and scale information. The advent of the era of big data is based on the relationship between multiple frames of images, while human posture recognition is based on the processing of single-frame static images. Correctly recognizing the pose information of multiple frames of continuous images still makes it possible to realize correct behavior analysis and understanding.
Expression of Mucin Family Proteins in Non-Small-Cell Lung Cancer and its Role in Evaluation of Prognosis
Authors: Tu Jing , Tang Min , Li Guoqing , Chen Liang , Wang Yubo , Huang Yong
Published: August 2022

Lung cancer is still the major contributor to cancer-related mortality. Over 85% of patients suffer from non-small-cell lung cancer (NSCLC). Mucins (MUCs) are large glycoproteins secreted or membrane-bound produced by epithelial cells in normal and malignant tissues. They are the major components of the mucous gel that covers the surface of the respiratory epithelium. Certain MUCs have been used or proposed to act as biomarkers for lung cancer. Nevertheless, the expression, messenger ribonucleic acid (mRNA) levels, and the prognostic value of MUCs in NSCLC are yet to be investigated systematically. In this research, the biological information of MUC proteins in patients with NSCLC was examined using a series of databases. The results based on gene expression profiling interactive analysis (GEPIA) illustrated that the expression of MUC3A, MUC4, MUC5B, MUC13, MUC16, and MUC21 mRNAs was remarkably upmodulated in lung adenocarcinoma (LUAD) patients, whereas the MUC1 expression was downregulated in lung squamous cell carcinoma (LUSC) patients. Kaplan–Meier plotter (KM Plotter) analysis revealed that elevated mRNA expression levels of MUC3A and MUC16 were linked to unfavourable overall survival (OS) in NSCLC, while increased mRNA expression of MUC1 and MUC15 was linked to good OS, especially in LUAD patients. In addition, differential expression of MUC1, MUC3A/3B, MUC8, MUC12, MUC15, and MUC16 mRNA was linked to the prognoses of NSCLC patients with varied clinical-pathological subtypes. Genetic alterations of MUCs in NSCLC primarily involved mutations, fusion, amplification, deep deletion, and multiple alterations according to cancer genomics (cBioPortal). Therefore, we propose that combinations of MUC proteins can act as prognostic biomarkers and demonstrate the therapeutic potential for NSCLC-related therapy.
Establishment of a Fuzzy Comprehensive Evaluation Random Matrix Model for the Assessment of Foreign Language Translation Level in Universities
Authors: Xie Li , Wu Jin
Published: August 2022

In this paper, the random matrix method of a fuzzy comprehensive evaluation is used to conduct in-depth research and analysis on the assessment of foreign language translation levels in universities, and the corresponding model is designed for the automatic assessment of translation levels in university education. The Hessian matrix of the second-order optimization method is used to analyze the geometric properties of the loss plane of the deep neural network, and it is proved that the Hessian matrix can be constructed as a sample covariance matrix, which is the classical Wishart matrix in the random matrix theory. Using the study on the asymptotic distribution properties of the Wishart matrix in random matrix theory, the Hessian matrix is analyzed and the limiting spectral distribution, the eigenvalue extreme value distribution, and the standard conditional number distribution of the matrix are given. And the scores are basically distributed above 240, but some indicators have relatively low scores, all below 120 points, so the indicators distributed above 240 points are selected as reserved indicators. The analysis considers that the evaluation of foreign language translation in learning in colleges and universities is itself very fuzzy and constructs an evaluation model based on the fuzzy comprehensive judgment method, which provides a research strategy for the future evaluation of foreign language translation in learning in colleges and universities. Finally, the evaluation system of foreign language translation in learning in colleges and universities is designed and implemented. It is feasible to apply the fuzzy comprehensive judgment to the comprehensive evaluation of college students, the combined judgment of multiple methods has higher reliability and stability, and its research conclusions have certain reference value in the specific education management practice. The value, objectivity, feasibility, and wide adaptability of the fuzzy comprehensive evaluation method are analyzed, and some references are expected to be provided for translation quality assessment research and translation practice.
Performance Enhancement of Bit-Level XOR Compressed Image OFDM Transmission Systems
Authors: Xue Linlin , Lv Jianhong , Wang Zhongpeng
Published: August 2022

The bit error rate (BER) formula of the M-QAM system is derived under nonequally likely condition of the constellation points, from which improving the BER performance of the M-QAM system by optimizing the probability distribution of constellation points is identified. Based on the analysis, the bit-level XOR method is employed to encrypt the image data and modify the probability distribution of the constellation points. The simulation results show that bit-level XOR is helpful to obtain a better probability distribution of the 16-QAM system compared to that without bit XOR and hence can improve the BER performance of the proposed OFDM transmission system. Simulation results based on test images over the AWGN channel further confirm that the reliability of the OFDM transmission system and the reconstructed quality of the compressed image are both significantly enhanced using bit-level XOR operation.
Quantitative Evaluation and Empirical Analysis of Educational Policies for Ethnic Minorities in Border Areas Based on the PMC Index Model
Authors: Zhang Shujie , Yang Songting
Published: August 2022

China is a multiethnic country, and the border areas are the gathering places of ethnic minorities. Strengthening the ethnic unity education in the border areas is an important measure to maintain the social stability and national security in the border areas of China. Colleges and universities in the border areas are the cradle of cultivating outstanding ethnic minority cadres, and colleges and universities in the border areas shoulder an important historical mission. In recent years, many domestic experts and scholars began to try to use the PMC index model for policy evaluation. Chinese scholars also have a deeper understanding of the standards of policy evaluation and put forward policy evaluation standards that are more in line with the actual needs of China’s public policy evaluation research. This paper takes the education policy text of the border ethnic minorities as the research object, takes the policy evaluation as the research perspective, constructs the transformation policy text evaluation model according to Ruiz Estrada’s PMC index model construction method, defines the calculation method and rating method, draws the PMC surface of each sample, and makes a comparative analysis of the PMC index. According to the comparative analysis results of PMC index and the scanning results of policy text, this paper puts forward three optimization strategies for the education policy of border ethnic minorities.
CBCT Evaluation of Buccolingual Orientation of Inferior Alveolar Canal in Mandibular Posterior Region for Implant Planning
Authors: Chua Michelle Kher Wei , Koh Wen Jiong , Nimbalkar Smita , Patil Pravinkumar G.
Published: August 2022

Purpose. Inferior alveolar nerve (IAN) can be subjected to iatrogenic injury during implant surgical procedures. The purpose of this retrospective study was to identify the buccolingual orientation of IAN in posterior mandible as adjunct information for implant planning and to estimate ethnicity-, sex-, and side-related variations in Malaysian population. Material and Methods. A total of 121 CBCT images were viewed with eXamVision software. The buccolingual position of IAN was identified in the posterior region. Buccal bone width (B), canal thickness (C), and lingual bone width (L) were measured at the horizontal canal levels. Kruskal–Wallis H test and Friedman test were used to analyze the buccolingual position. One-way ANOVA was performed to evaluate the variations in B, C, and L values. Results. Overall, most of the IANs were located on the lingual sides of the second molar regions (left: 71.9%; right: 71.1%) and at the centers of the first molar regions (left: 57.9%; right: 47.10%) and exited through the mental foramen before the second premolar regions. There was statistically significant difference in the buccolingual position of the IAN between the sexes in the left second premolar regions (P=0.03). There was variation in B between the sexes in the left first molar regions (P=0.01). Statistically significant differences in C and L were also found between different ethnic groups (P=0.04). Between both sides, there were variations in C in the first molar regions (P<0.001) and the second molar regions (P=0.03). Conclusion. From the second molar to the second premolar, the buccal bone width decreased while the lingual bone width increased. There were variations between ethnicities, sexes, and sides among Malaysians.
Repairing Event Logs to Enhance the Performance of a Process Mining Model
Authors: Shahzadi Shabnam , Fang Xianwen , Shahzad Usman , Ahmad Ishfaq , Benedict Troon
Published: August 2022

Organizations and companies are starving to improve their business processes to stay in competition. As we know that process mining is a young and emerging study that lasts among data mining and machine learning. The main goal of process mining is to obtain accurate information from the data; therefore, in recent years, it attracts the attention of many researchers, practitioners, and vendors. However, the purpose of enhancement is to extend or develop an existing process model by taking information from the actual process recorded in an event log. One type of enhancement of a process mining model is repair. It is common practice that due to logging errors in information systems or the presence of a special behavior process, they have the actual event logs with the noise. Hence, the event logs are traditionally thought to be defined as situation. Actually, when the logging is based on manual logging i.e., entering data in hospitals when patients are admitted for treatment while recording manually, events and timestamps are missing or recorded incorrectly. Our paper is based on theoretical and practical research work. The main purpose of our study is to use the knowledge gather from the process model, and give a technique to repair the missing events in a log. However, this technique gives us the analysis of incomplete logs. Our work is based on time and data perspectives. As our proposed approach allows us to repair the event log by using stochastic Petri net, alignment, and converting them into Bayesian analysis, which improves the performance of the process mining model. In the end, we evaluate our results by using the algorithms described in the alignment and generate synthetic/artificial data that are applied as a plug-in in a process mining framework ProM.
Real Estate Tax, Housing Price, and Housing Wealth Effect: An Empirical Research on China Housing Market
Authors: Zhang Jixuan , Deng Xiaoyu
Published: August 2022

Housing market occupies a large part of the wealth of the whole society in most countries, and real estate tax plays an important role for the government to maintain sustainable development for the economy. As consumption being a major issue nowadays, in this paper, we want to find out (1) whether real estate taxes affect the house price in China and whether the affects vary among different tax types? (2) whether there exists wealth effect in China housing market? That is, whether the change in house wealth (price) affects the consumption? (3) whether and how do real estate taxes affect wealth effect? We set up the empirical model by using the GMM method on panel data from 2002 to 2016 to explore the relations among real estate tax, housing price, and wealth effect. We considered the influence of four different types of real estate tax on the housing price and found the results are mixed. Besides, there is a significantly negative wealth effect on China housing market. Finally, house price plays a mediator role in the effect of the real estate tax on the consumption.
A Rare Case Report of Giant Urinary Bladder Stone Causing Recurrent Dysuria in a Woman
Authors: Adhikari Rojan , Baral Hari Prasad , Bhattarai Utsav , Gautam Ravi Kiran , Kunwar Kiran Jung , Shrestha Dipesh , Katwal Bijay Mansingh
Published: August 2022

Background. Large urinary bladder stones are not common and even less common in females. We report a case of large bladder stone presented with acute retention of urine in a female patient. Case Report. A 62-year-old female presented in emergency department with retention of urine for 12 hours with history of recurrent UTIs for last 1 year. She was also complaining of mild dull lower abdominal pain for last 6 months. She had no history of incontinence of urine and fever. On physical examination, hard mass was palpable on suprapubic region on palpation of abdomen. Urine culture shows Escherichia coli for which antibiotics was given. An X-ray kidney ureter bladder showed a radio-opacity in the pelvic region measuring

9
×
8
 
cm

in size. Ultrasonography revealed bilateral mild hydronephrosis with a large bladder stone. Open cystolithotomy was performed, and the stone was taken out. Stone biochemical analysis showed predominantly urate crystals. Patient had uneventful postoperative course, and she was discharged on 4th postoperative day and was followed up for 1 months after operation. Conclusions. Large urinary bladder stones are not common and even less common in females. Clinician should have think regarding large bladder stone as a cause of recurrent lower urinary tract symptoms like dysuria and should assess renal function for proper treatment. Open cystolithotomy is choice of operation in large bladder stone.
Application of Sensor-Based Intelligent Wearable Devices in Information Physical Education
Authors: Chen Wanjun
Published: August 2022

In order to solve the heavy work tasks of teachers and improve the efficiency of classroom teaching, a sensor-based intelligent wearable device method is proposed. The method is divided into four stages: generalization-differentiation-solidification-automation. At the stage of generalization and differentiation, teachers should first demonstrate and drill the correct movements and brief notes for attention. It is not appropriate to emphasize the details of movements too much. In the movement exercise of the differentiation and solidification stage, attention should be paid to guiding students to experience the process of coordinating and generating force, and to enhance the experience of muscle sensation and perception. In the solidification stage, students’ mastery of technical movements tends to be stable, and they should strengthen the combination with other mastered technical movements. In this stage, attention should be paid to the cultivation of individual technical style. The results showed that 46% of the students in the experimental group thought badminton special learning was interesting, while only 15% of the students in the control group held the same attitude. 39% of the students in the experimental group thought badminton special learning interesting, and 31% of the students in the control group; in the experimental group, 15% of students thought that their interest in badminton became average after a semester of special courses, while in the control group, 39% students should be interested in badminton. None of the students in the experimental group thought badminton learning was less interesting, while 15% of the students in the control group still felt badminton learning became less interesting. Conclusion. The method can effectively solve the heavy work of teachers and improve the efficiency of class.
[Retracted] The Expression Significance of LPa, BNP, and McP‐1 in CHD Patients and Their Relationship with Echocardiographic Parameters
Authors: Ma Yunpeng , Qi Yinzun , Li Qiang , Zhu Shuangxiong , Zhao Wenjie , Zhang Yu
Published: August 2022

In order to investigate the expression levels of Lipoprotein A (LPa), B‐type Natriuretic Peptide (BNP) and Monocyte chemoattractor Protein‐1 (McP‐1) in serum of patients with coronary heart disease (CHD) are used to detect significance and to analyze the correlation between these indicators and parameters of echocardiography. The clinical data of 132 CHD patients in our hospital from January 2021 to October 2021 are retrospectively analyzed and included in the CHD group. Another 100 healthy people who came to our hospital for general physical examination were selected as the control group. The expressions of Serum McP‐1 and BNP are detected by the ELISA. The expression of Serum LPa is detected by immunoturbidimetry, and the expressions of SERUM McP‐1, BNP, and LPa are compared between the two groups. The experiments show that the expressions of McP‐1, BNP, and LPa in serum of control group are significantly lower than those of the CHD group (P < 0.05). Echocardiography results show that left ventricular ejection fraction (LVEF) in CHD group is significantly lower than that in control group, but left ventricular end‐systolic volume (LVESV) and left ventricular end‐diastolic volume (LVEDV) are significantly higher than those in control group (P < 0.05).
Research on Life-Cycle Project Cost Management Based on Random Matrix Weight Algorithm
Authors: Chen Zhen , Wang Fuqiang
Published: August 2022

The traditional project management in the construction industry has the uniqueness of exclusive customization, the irreversibility of the project, the immobility of the project address, the long-term nature of the project, and the dynamic nature of the project. Based on these characteristics, the complexity and difficulty of project management in the construction industry are determined. Modern engineering is no longer satisfied with the traditional basic needs, but develops in a green, environmental friendly and efficient way. On the one hand, the project is required to meet good use requirements and meet the most basic functional requirements. On the other hand, the project construction process is required to meet the requirements of green environmental protection and ecological harmony. Therefore, the maintenance cost and operation cost corresponding to modern projects have become the key to the sustainable and healthy development of the engineering construction industry. Based on this, this paper will take the construction industry as an example to fully analyze the current situation and existing problems faced by the current project cost management. Through the research on the full life-cycle project cost management mode of the construction industry, the random matrix weight algorithm is creatively introduced, and the adaptive full life-cycle project cost management extended target tracking algorithm is proposed, which cuts the corresponding full life-cycle project cost management model into multiple submodels, and the corresponding management subobjectives are constructed from the submodel, and the expansion status of the corresponding subobjectives is described and analyzed in detail using the inverse distribution description, so as to accurately estimate the effect and target weight coefficient required by the management subobjectives, and finally realize the efficient, reasonable and scientific operation of the construction industry’s whole life-cycle project cost management, so as to maximize economic benefits. An experimental verification is carried out for a specific construction company. The verification results show that the full life-cycle project cost management scheme based on random matrix weight algorithm proposed in this paper has obvious advantages in management efficiency, cost control, process control, and other aspects compared with the traditional management scheme.
Implementing the Galerkin Method Associated with the Shifted Vieta‐Lucas Polynomials for Studying Numerically the Bionanofluid Flow Which Is Saturated by Gyrotactic Microorganisms over a Slippery Stretching Sheet
Authors: Khader M. M. , Babatin M. M. , Megahed Ahmed M. , Eid A.
Published: August 2022

Heat transfer is a critical function in many technical, industrial, home, and commercial structures. As a result, the purpose of this study is to investigate the effects of slip velocity and variable fluid characteristics on Casson bionanofluid flow across a stretching sheet that has been saturated by gyrotactic microorganisms. The suggested system will be converted to a computationally tractable form using the Galerkin method. The shifted Vieta‐Lucas polynomials are then used as basis functions on the provided domain to solve the nonlinear system of ordinary differential equations that has been constructed (ODEs). The results are presented in the form of graphs and tables to assess the impact of the problem’s governing parameters. The estimated solutions produced by using the proposed techniques were physically acceptable and accurate. The current outcomes are confirmed by comparing them to the available literature. It appears that the temperature distribution is enhanced whereas the velocity distribution declines, caused by rising values of the magnetic parameter, slip parameter, and Casson parameter. Also, the local Nusselt number escalates with the strength of the viscosity parameter while the friction drag decays with the same parameter. In addition, the effectiveness and accuracy of the proposed method are satisfied by computing and the residual error function.
Hemodynamic Changes in the Masseter and Superior Orbicularis Oris Muscles before and after Exercise Load: A Comparison between Young Adult Women and Middle-Aged to Old Adult Women
Authors: Okamoto Keiko , Tanikawa Chihiro , Takada Kenji
Published: August 2022

Background. The vascularity index (VI) is useful for measuring the hemodynamics on ultrasound imaging. However, there are no reports concerning the application of the VI to facial muscles. Objective. The aim of this study was (1) to establish a method of measuring the hemodynamics in facial muscles in a constant way and (2) to evaluate the hemodynamic changes in the masseter and superior orbicularis oris muscles (SOOMs) before and after exercise load in two subject groups of females of different ages. Methods. (1) The VI in the SOOM was calculated, and the test-retest reliability was assessed in seven healthy adults. (2) The VIs in the left-side masseter and SOOM were calculated in 3 sessions: before exercise loading (T0), immediately after loading (T1), and 5 minutes after T1 (T2) for the young adult group (YAG, n = 20; age range, 20–35 years) and the middle-aged to old group (MOG, n = 20; age range, 50–70 years). Tasks were gum chewing for the masseter muscle and lip sealing for the SOOM. The differences in the mean peak flows between two sessions were examined. Results. (1) Significant differences were not noted for the repeatedly measured average volumes of blood flow with good test-retest agreement (intraclass correlation coefficient = 0.81). (2) In both muscles of the YAG, there were a significant increase in T1 compared with T0 and a significant decrease in T2 compared with T1 (all

p
<
0.05

). In both muscles of the MOG, no significant differences were noted in either comparison. Conclusions. A method of measuring the hemodynamics in facial muscles was developed and showed good reliability. Changes in the blood flow after exercise load in these muscles may vary with age in women.
Corporate Environmental Governance Performance Evaluation and Index System Construction under the Mobile Communication System
Authors: Chen Fujiang , Sun Cangqian , Chen Junying , Wen Chao , Duan Rongqian , Wu Haoyu
Published: August 2022

As environmental pollution has become more and more serious, in order to alleviate environmental and energy problems, people have begun to find new ways of governance in environmental management. Many countries have proposed to incorporate environmental performance into corporate performance for assessment. Under the historical background that the construction of ecological civilization has risen to a national strategy, the research on corporate environmental performance has attracted more and more attention. This paper constructs an environmental performance evaluation index system, evaluates the environmental performance of the enterprise, finds out the problems in the environmental performance of the enterprise, and proposes improvement suggestions. This is conducive to the change of the environmental policy of the enterprise, the improvement of the environmental performance level of the enterprise, and the protection of the ecological environment. This article introduces the mobile communication network, constructs the LMS model of the satellite mobile communication system, and analyzes the structure and main functions of the model. The article explains the role of corporate environmental governance, builds an environmental performance indicator system, selects several companies to evaluate the environmental governance performance of the past two years, and obtains the comprehensive performance index, stress index, state improvement index, and response index of the four companies in 2020. The four indexes of company A are 1.28, 1.3, 12, and 1.45, and the four indexes of company B are 2.96, 3.1, 8, and 2.9.
Human Resource Demand Prediction and Configuration Model Based on Grey Wolf Optimization and Recurrent Neural Network
Authors: Rajagopal Navaneetha Krishnan , Saini Mankeshva , Huerta-Soto Rosario , Vílchez-Vásquez Rosa , Kumar J. N. V. R. Swarup , Gupta Shashi Kant , Perumal Sasikumar
Published: August 2022

Business development is dependent on a well-structured human resources (HR) system that maximizes the efficiency of an organization’s human resources input and output. It is tough to provide adequate instructions for HR’s unique task. In a time when the domestic labor market is still maturing, it is difficult for companies to make successful adjustments in HR structures to meet fluctuations in demand for human resources caused by shifting corporate strategies, operations, and size. Data on corporate human resources are often insufficient or inaccurate, which creates substantial nonlinearity and uncertainty when attempting to predict staffing needs, since human resource demand is influenced by numerous variables. The aim of this research is to predict the human resource demand using novel methods. Recurrent neural networks (RNNs) and grey wolf optimization (GWO) are used in this study to develop a new quantitative forecasting method for HR demand prediction. Initially, we collect the dataset and preprocess using normalization. The features are extracted using principal component analysis (PCA) and the proposed RNN with GWO effectively predicts the needs of HR. Moreover, organizations may be able to estimate personnel demand based on current circumstances, making forecasting more relevant and adaptive and enabling enterprises to accomplish their objectives via efficient human resource planning.