bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling and Simulation of the Aerodynamic Noise of High-Speed Train’s Pantograph
Authors: Shaltout R. E. , Aljameel N. M. , AbdelGawad A. F.
Published: June 2022

This article aims to investigate the aerodynamic noise of the pantograph of the high-speed trains in different operating conditions. CFD technique was used to assess the acoustic noise of the pantograph components. Three-dimensional computational simulations were performed using FLUENT software. Comprehensive analyses of the acoustic pressure and the air velocity distributions were accomplished for the detailed full-scale pantograph components. Good agreement was found between the obtained results and the reported results in the literature. Vortex shedding was the main source of noise at the pantograph panhead and knee. A modified model for the pantograph was introduced to reduce the aerodynamic noise of the pantograph’s panhead. A different design profile for the collector was presented as a possible solution for the reduction of both the aerodynamic noise and the reduction of the fluctuating forces at the panhead-catenary interaction, which affects the quality of the power transmitted to the high-speed train. The cylindrical cross-section of the panhead bars was replaced with different cross-sections. It was noticed that at a speed of 250 km/hr, the use of an elliptic cross-section has resulted in an almost 23.1% reduction in the acoustic sound pressure for the pantograph.
Shaoyao-Gancao Decoction Promoted Microglia M2 Polarization via the IL-13-Mediated JAK2/STAT6 Pathway to Alleviate Cerebral Ischemia-Reperfusion Injury
Authors: Lu Juanjuan , Wang Jie , Yu Long , Cui Rong , Zhang Ying , Ding Hanqing , Yan Guofeng
Published: June 2022

Microglia in the penumbra shifted from M2 to M1 phenotype between 3 and 5 days after cerebral ischemia-reperfusion, which promoted local inflammation and injury. Shaoyao-Gancao Decoction (SGD) has been found to result in a significant upregulation of IL-13 in the penumbra, which has been shown to induce polarization of M2 microglia. There was thus a hypothesis that SGD could exert an anti-inflammatory and neuroprotective effect by activating IL-13 to induce microglia polarization towards M2 phenotype, and the purpose of this study was to explore the influence of SGD on microglia phenotype switching and its possible mechanism. Rats who received middle cerebral artery occlusion surgery (MCAO) were treated with SGD for 3 or 6 days, to investigate the therapeutic effect and the underlying mechanism of SGD for cerebral ischemia-reperfusion injury (CI/RP). The results indicated that SGD improved neurobehavioral scores and reduced apoptosis. Furthermore, SGD significantly decreased M1 microglia and M1-like markers, but increased M2 microglia and M2 markers. Moreover, higher levels of IL-13 and ratios of p-JAK2/JAK2 and p-STAT6/STAT6 were found in the SGD group compared to the MCAO. In conclusion, it was verified that SGD prevented injury by driving microglia phenotypic switching from M1 to M2, probably via IL-13 and its downstream JAK2-STAT6 pathway. Given that no further validation tests were included in this study, it is necessary to conduct more experiments to confirm the reliability of the above results.
Study on the Current Status and Influencing Factors of Workplace Violence to Medical Staff in Intensive Care Units
Authors: Yi Xingke , Feng Xiuchan
Published: June 2022

Objective. To explore the current status and influencing factors of workplace violence to medical staff in intensive care unit (ICU). Methods. A total of 230 medical staff in the ICU of Hengyang city were enrolled as the research subjects between October 2021 and January 2022. The situations and characteristics of workplace violence were collected with questionnaires. The influencing factors of workplace violence were analyzed by univariate and multivariate logistic regression analyses. Results. The incidence of workplace violence to ICU medical staff was 40.43%. There were 18.70% of them threatened, 13.48% with verbal violence, 10.00% with physical violence, and 7.39% with sexual harassment. Of the 114 workplace violence incidents, there were 69 (59.65%) during the day, 101 (88.60%) only with medical staff on the spot, and 91 (79.82%) with male perpetrators (mainly on patients and their families). The main reasons for violence were verbal miscommunication (15.79%), too long waiting time for treatment (27.19%), and unsatisfactory treatment effect (38.60%). The main coping style of medical staff after suffering violence was patient explanation (64.04%). Multivariate regression analysis showed that working years ≤5 years (OR = 2.093,

P
=
0.009

) and weekly working time >45 h (OR = 2.127,

P
=
0.022

) were independent risk factors of workplace violence to ICU medical staff. Conclusion. The working years ≤5 years and weekly working time >45 h are high-risk factors of workplace violence to ICU medical staff. The hospital can prevent and control workplace violence based on the high-risk factors to reduce the incidence of workplace violence.
Numerical and Experimental Verification of Spherically Layered Ice Model for Analysis on Hail Impacting Aviation Structures
Authors: Luo Gang , Zhang Fengqi , Cao Wanting , Zhang Haiyang , Liu Lulu , Chen Wei
Published: June 2022

Aviation structures are required to be resistant to impact damage from hail. Therefore, aiming to gain a better understanding of such impacts, the formation mechanisms, spherically layered structures, and layer-density distributions of real hail were investigated. Based on analysis of the influence of different constitutive model parameters on the impact load on a metal target plate, a layered finite-element hail model was established, and this and several equivalent hail models were simulated and compared in terms of the dynamic responses during impact with a Ti6Al4V alloy plate target. The results showed that the characteristic values of the contact forces and impact displacements of spherically layered hail were lower than those for equivalent hailstones with the same mass or diameter. The spherically layered modeling of hail could provide a method for fine analysis of the phenomenology of hailstone impacts.
A Bibliometric Analysis of the 50 Most Commonly Cited Studies of the Direct Anterior Approach in Total Hip Arthroplasty
Authors: Yakkanti Ramakanth R. , Sedani Anil , Greif Dylan N. , Yakkanti Rukmini , Massel Dustin H. , Hernandez Victor H.
Published: June 2022

Introduction. The direct anterior approach (DAA) has garnered a lot of attention and surgical popularity for total hip arthroplasty in recent years. Some of the postulated advantages for the increase in popularity of this approach include better pain control and earlier recovery in the immediate postoperative period. The amount of literature available on this topic has rapidly increased over the last 10 years requiring the need for an updated guide to best navigate the topic. Methods. The ISI Web of Knowledge database was used to search for research articles regarding the DAA surgical technique. The Boolean operative that yielded the largest search results was ([direct anterior approach hip] OR [anterior hip] OR [anterior hip arthroplasty] NOT [spine]). Results. 92% of the highest cited articles on the DAA were published within the past two decades. One author, Keggi K, published 4 or more articles, with the highest citation average (110.5 citations). Recent articles were more strongly correlated with higher citation counts (R2 = 0.21

v

. 0.19). Conclusion. This review clearly outlines the increasing trend in the most influential publications regarding DAA being published in the past two decades. This review allows interested surgeons to understand the historic literature pertaining to this topic. This review can assist future researchers in identifying trends in UKA as well as help clinicians navigate this body of literature.
The Prediction of a 3-Protein-Based Model on the Prognosis of Head and Neck Squamous Cell Carcinoma
Authors: Chen Xiaoting , Wong Kaiyi , Li Yixuan , Guan Zhong
Published: June 2022

Background. Head and neck squamous cell carcinoma (HNSCC) is one of the commonest malignant tumors. Using high-throughput genomic methods, RNA-based diagnostic and prognostic models for HNSCC with potential clinical value have been developed. However, the clinical utility and reproducibility of these models are uncertain. Because the complex regulatory processes occurring after mRNA is transcribed, the abundance of proteins in a cell can never be fully predicted or explained by their corresponding mRNA expression. We aimed to assume and verify a novel protein signature for checking the HNSCC patients’ prognosis. Methods. The functional proteomic data of 332 HNSCC cases were collected from The Cancer Proteome Atlas (TCPA), and the related follow-up and clinical data were acquired from The Cancer Genome Atlas (TCGA). This study adopted multivariate and univariate Cox regression analysis, Akaike Information Criterion, receiver operating characteristic (ROC) analysis, and Kaplan-Meier method. Results. Patients’ clinical features in both sets were comparable (all,

P
>
0.05

). The area under the ROC curve (AUC) for the 3-protein signature (X4EBP1_pT37T46, HER3_pY1289, and NF2) in the test set was 0.655 and in the combined cohort (all 332 patients combined) was 0.699. In addition, the 3-protein signature exhibited better predictive value for the survival of HNSCC patients as in comparison with conventional clinical factors like age, gender, tumor stage, and smoking history (TNM stage). Conclusion. The 3-protein signature developed in this study exhibits good performance in predicting the overall survival of with HNSCC patients. The 3-protein signature exhibited better predictive value for survival than conventional clinical factors just like gender, TNM stage, smoking history, and age.
Design of Performance Evaluation Algorithm for Diversified Talent Training in Modern Universities Considering Innovative Thinking
Authors: Liang-feng Dong , Yuan Liu
Published: June 2022

The global economic trends and the winds of technological change have elevated the status of integration between industry and education for innovation and entrepreneurship. Technologies and the Internet have significantly changed all aspects of our lives. College education has improved as a result of the enormous benefits of the Internet and big data. Reforms and development have still a lot of application space in the training and practice of educational technology talents of a college education. To improve the performance evaluation capabilities of educational technology experts in Chinese universities through education and “Internet +” has become a challenge that has to be addressed. This article is under such a formal background to have a detailed study about the current college education in China. In this study, an analysis is presented for the performance evaluation of the education technology talent training in modern universities based on big data technology. A fuzzy evaluation algorithm based on composite elements is proposed to evaluate the multielement and multilevel college education system. Experimental results illustrate the feasibility and effectiveness of the proposed algorithm. The proposed method has the potential to solve the complicated performance evaluation problem in colleges.
A Stability Result for a Viscoelastic Wave Equation in the Presence of Finite and Infinite Memories
Authors: Al-Mahdi Adel M. , Al-Gharabli Mohammad M. , Kafini Mohammad , Al-Omari Shadi
Published: June 2022

In this study, we consider a viscoelastic wave equation in the presence of finite and infinite memories. Under suitable conditions on the variable coefficients and for a wide class of relaxation functions, we establish an explicit and general decay result. Moreover, we use a weaker boundedness condition, on the initial data than the one used in the literature. The proof of our decay result is based on the multiplier method together with some convexity arguments. This study generalizes and improves previous literature outcomes.
LINC01116 Promotes Migration and Invasion of Oral Squamous Cell Carcinoma by Acting as a Competed Endogenous RNA in Regulation of MMP1 Expression
Authors: Ying Yukang , Liu Dong , Zhao Yue , Zhong Yuan , Xu Xuhui , Luo Jun , Zhang Zhenxing
Published: June 2022

Oral squamous cell carcinoma (OSCC) has increasingly become a worldwide health concern, and its survival rate has not been much improved partially due to a deficiency of precise molecular markers. Dysregulation of LINC01116, a long noncoding RNA sequence, has been observed in several types of cancer. However, the role played by LINC01116 in OSCC has not yet been fully elaborated. This study explored how LINC01116 was involved in the regulation of OSCC progression by analyzing expressions of LINC01116 in OSCC patients. The findings demonstrated upregulation of LINC01116 in OSCC tissues as opposed to regular oral mucosa, and overexpression of LINC01116 was correlated with advanced tumor status. LINC01116 knockdown using shRNA markedly reduced the OSCC cell invasion and migration in vitro. Moreover, the expression of LINC01116 was negatively correlated with that of microRNA-9-5p (miR-9). Luciferase reporter and loss-of-function assays demonstrated that LINC01116 functioned as a competing endogenous RNA (ceRNA) that could effectively sponge miR-9, thus regulating the derepression of matrix metalloproteinase 1 (MMP1). Furthermore, we confirmed that LINC01116 knockdown did not affect the expression of MMP1 messenger RNA (mRNA). Collectively, it is demonstrated in this study that overexpression of LINC01116 can promote the OSCC progression. The LINC01116–miR-9-MMP1 axis provides a novel insight into the OSCC pathogenesis and offers potential therapeutic targets against OSCC.
Deep Learning-Based CT Imaging for the Diagnosis of Liver Tumor
Authors: Zhang Heng , Luo Kaiwen , Deng Ren , Li Shenglin , Duan Shukai
Published: June 2022

The objective of this research was to investigate the application value of deep learning-based computed tomography (CT) images in the diagnosis of liver tumors. Fifty-eight patients with liver tumors were selected, and their CT images were segmented using a convolutional neural network (CNN) algorithm. The segmentation results were quantitatively evaluated using the Dice similarity coefficient (DSC), precision, and recall. All the patients were examined and diagnosed by CT enhanced delayed scan technique, and the CT scan results were compared with the pathological findings. The results showed that the DSC, precision, and recall of the CNN algorithm reached 0.987, 0.967, and 0.954, respectively. The images segmented by the CNN were clearer. The diagnostic result of the examination on 56 cases by CT enhanced delay scanning was consistent with that of pathological diagnosis. According to the result of pathological diagnosis, there were 6 cases with hepatic cyst, 9 with hepatic hemangioma, 12 cases with liver metastasis, 10 cases with hepatoblastoma, 3 cases with focal nodular hyperplasia, and 18 cases with primary liver cancer. The result of CT enhanced delay scanning on 58 patients was consistent with that of pathological diagnosis, and the total diagnostic coincidence rate reached 96.55%. In conclusion, the CNN algorithm can perform accurate and efficient segmentation, with high resolution, providing a more scientific basis for the segmentation of liver tumors in CT images. CT enhanced scanning technology has a good effect on the diagnosis and differentiation of liver tumor patients, with high diagnostic coincidence rate. It has important value for the diagnosis of liver tumor and is worthy of clinical application.
The Role of MicroRNAs in Hyperlipidemia: From Pathogenesis to Therapeutical Application
Authors: Xiang Yu , Mao Li , Zuo Mei-Ling , Song Gui-Lin , Tan Li-Ming , Yang Zhong-Bao
Published: June 2022

Hyperlipidemia is a common metabolic disorder with high morbidity and mortality, which brings heavy burden on social. Understanding its pathogenesis and finding its potential therapeutic targets are the focus of current research in this field. In recent years, an increasing number of studies have proved that miRNAs play vital roles in regulating lipid metabolism and were considered as promising therapeutic targets for hyperlipidemia and related diseases. It is demonstrated that miR-191, miR-222, miR-224, miR-27a, miR-378a-3p, miR-140-5p, miR-483, and miR-520d-5p were closely associated with the pathogenesis of hyperlipidemia. In this review, we provide brief overviews about advances in miRNAs in hyperlipidemia and its potential clinical application value.
Analysis of Chest X-Ray Images for the Recognition of COVID-19 Symptoms Using CNN
Authors: Hatamleh Wesam Atef , Tarazi Hussam , Subbalakshmi Chatti , Tiwari Basant
Published: June 2022

The 2019 coronavirus pandemic (COVID-19) struck without warning, and existing medical screening and clinical management systems were unprepared, causing a high fatality rate. Given the virus’s ongoing evolution, there is still a potential for reemergence; earlier weak preparedness will not be accepted in such a situation. Therefore, it is vital to understand and rectify past diagnostic work’s flaws. RT-PCR and antigen tests, both widely used, have experienced problems in the past. They either were too sluggish or produced an excessive number of false negatives. Another issue was a lack of test kits. As a result, chest X-ray image-based disease classification has emerged. However, managing a variety of chest X-ray pictures for COVID-19 and pneumonia patients is complicated and error-prone. As a result, the only way to improve the current diagnosis is to apply deep learning algorithms that learn from radiography pictures and anticipate COVID-19 development. We constructed our own convolutional neural network (CNN) by incorporating transfer learning from the most popular ResNet, VGG, and InceptionNet models. The endeavor necessitated the creation of a sizable dataset that accurately depicted the patient population. Before importing the model, the images were enhanced to remove artifacts caused by noise, motion, or blurring that could impair the detection of infection. Preprocessing has a substantial impact on the model’s accuracy. The results indicated that the VGG16 architecture, with a detection accuracy of 95.29%, is optimal for COVID-19 identification from X-ray images. Furthermore, most generated models outperformed current state-of-the-art research in the same field.
Malignant Transformation of Giant Cell Tumor of Bone and the Association with Denosumab Treatment: A Radiology and Pathology Perspective
Authors: van Langevelde K. , Cleven A. H. G. , Navas Cañete A. , van der Heijden L. , van de Sande M. A. J. , Gelderblom H. , Bovée J. V. M. G.
Published: June 2022

Objective. Malignancy in giant cell tumor of bone (mGCTB) is categorized as primary (concomitantly with conventional GCTB) or secondary (after radiotherapy or other treatment). Denosumab therapy has been suggested to play a role in the etiology of secondary mGCTB. In this case series from a tertiary referral sarcoma center, we aimed to find distinctive features for malignant transformation in GCTB on different imaging modalities. Furthermore, we assessed the duration of denosumab treatment and lag time to the development of malignancy. Methods. From a histopathology database search, 6 patients were pathologically confirmed as having initial conventional GCTB and subsequently with secondary mGCTB. Results. At the time of mGCTB diagnosis, 2 cases were treated with denosumab only, 2 with denosumab and surgery, 1 with multiple curettages and radiotherapy, and 1 with surgery only. In the 4 denosumab treated patients, the mean lag time to malignant transformation was 7 months (range 2–11 months). Imaging findings suspicious of malignant transformation related to denosumab therapy are the absence of fibro-osseous matrix formation and absent neocortex formation on CT, and stable or even increased size of the soft tissue component. Conclusion. In 4 patients treated with denosumab, secondary mGCTB occurred within the first year after initiation of treatment. Radiotherapy-associated mGCTB has a longer lag time than denosumab-associated mGCTB. Close clinical and imaging follow-up during the first months of denosumab therapy is key, as mGCTB tends to have rapid aggressive behavior, similar to other high-grade sarcomas. Nonresponders should be (re) evaluated for their primary diagnosis of conventional GCTB.
The Role of Machine Learning in E-Learning Using the Web and AI-Enabled Mobile Applications
Authors: Gazzawe Foziah , Mayouf Mohammad , Lock Russell , Alturki Ryan
Published: June 2022

For over two decades, e-learning has been recognized as a flexible and faster method compared to the other established methods, especially in enhancing knowledge. Concurrently, the expansion of information technology applications, such as mobile applications and Artificial Intelligence (AI), has provided well-grounded foundations for e-learning to be more reachable. In particular, education can be seen as the most beneficial sector of advancements in e-learning. Machine learning is considered a form of personalized learning that could be used to give each student a specific personal experience through which students are directed to gain their own experience. Web and AI-enabled mobile applications can be recognized as one of the most broadly used platforms for e-learning where machine learning technology can be applied to measure many influences and predictions regarding the quality of e-learning, but we cannot ignore the complexities of use. This study shows the role of machine learning in the user’s ability to make use of the course and its contents to measure ease and clarity. Based on a former study shown previously, this paper attempts to pinpoint realities and complexities associated with web and AI-enabled mobile applications by evaluating user preferences. This paper forms the second phase using two user groups (21–30 years) where data were attained using a survey questionnaire to investigate the user preferences when using an application for e-learning. The analysis shows that the future of e-learning has greater potential in web-based applications, as they have more scope for development and improvements compared to mobile applications. The paper concludes with a conceptual framework that works as a machine that stimulates different information and uses e-learning applications that support artificial intelligence techniques. This research provides a solid underpinning for further research into the future of AI-enabled e-learning education and its implication with respect to cost, quality, and usability.
Bayesian Estimation of Supply Chain Innovation Path
Authors: Zhang Xin , He Jian , Tian Weiguo
Published: June 2022

With the transformation of the supply chain from factor driven to investment driven and to innovation driven, supply chain innovation has attracted more and more attention. This paper obtains the Bayesian prior probability of innovation and studies the supply chain innovation path from the perspective of strategy and behavior. The model divides the overall innovation capability of the supply chain into specific node tasks and assets (Capability Set), and the innovation demand of the supply chain is expressed in the form of the conditional probability of market demand. Under the conditions of minimum risk, minimum cost, and rapid market response, it determines who should lead the supply chain innovation first and what type of supply chain innovation should be carried out first. Finally, taking the supply chain of the professional market in Zhejiang Province as an example, this paper verifies the theoretical model of supply chain innovation decision-making. The innovation of the supply chain of Zhejiang’s specialized market is decomposed into the capability set of each enterprise node of the supply chain. This paper transforms the group innovation ability of the supply chain in the professional market into the individual innovation ability of a single enterprise node and reveals the starting point and intensity of the demand innovation of products/services in the supply chain.
The Dynamic Influence of Fiscal Expenditure on Farmers’ Income in Guangdong Province Based on the Vector Autoregression Model
Authors: Chien Hsiao Yu
Published: June 2022

Using the skew integration theory and the establishment of a vector autoregression model (Var) to analyze the dynamic impact of fiscal expenditure on annual per capita net income of farmers, wage income, net operating income of farmers, and transferability and property income in Guangdong province from 1998 to 2019, the empirical findings show that government spending has a considerable favourable influence on farmers’ yearly per capita net income, family operating net income, transferability, and property income. Fiscal spending has a lag time on the rise of yearly per capita disposable income, family operating net income, transfers, and property income, according to impulse response analysis and variance decomposition analysis, and then the contribution steadily grows. The government should continue to expand fiscal expenditure for agriculture, improving the marketing channel of agricultural products, to strengthen the efficiency of agricultural production, establishing agricultural project comprehensive evaluation standard and characteristic agriculture, vigorously develop rural fiscal agriculture capital allocation efficiency, and increase farmers’ families annual per capita net income, net income of household operation, and transfer and property income.
E-dyNSGA-III: A Multi-Objective Algorithm for Handling Pareto Optimality over Time
Authors: Essiet Ima Okon , Sun Yanxia , Wang Zenghui
Published: June 2022

Loss of selection pressure in the presence of many objectives is one of the pertinent problems in evolutionary optimization. Therefore, it is difficult for evolutionary algorithms to find the best-fitting candidate solutions for the final Pareto optimal front representing a multi-objective optimization problem, particularly when the solution space changes with time. In this study, we propose a multi-objective algorithm called enhanced dynamic non-dominated sorting genetic algorithm III (E-dyNSGA-III). This evolutionary algorithm is an improvement of the earlier proposed dyNSGA-III, which used principal component analysis and Euclidean distance to maintain selection pressure and integrity of the final Pareto optimal front. E-dyNSGA-III proposes a strategy to select a group of super-performing mutated candidates to improve the selection pressure at high dimensions and with changing time. This strategy is based on an earlier proposed approach on the use of mutated candidates, which are randomly chosen from the mutation and crossover stages of the original NSGA-II algorithm. In our proposed approach, these mutated candidates are used to improve the diversity of the solution space when the rate of change in the objective function space increases with respect to time. The improved algorithm is tested on RPOOT problems and a real-world hydrothermal model, and the results show that the approach is promising.
Prognostic Value of Serum Interleukin-6, NF-κB plus MCP-1 Assay in Patients with Diabetic Nephropathy
Authors: An Zhongwu , Qin Jibao , Bo Weibo , Li Haiying , Jiang Ling , Li Xin , Jiang Jie
Published: June 2022

Objective. To assess the prognostic value of serum interleukin-6 (IL-6), nuclear factor-κB (NF-κB), and monocyte chemoattractant protein 1(MCP-1) assay in patients with diabetic nephropathy. Methods. From May 2019 to March 2020, 104 patients with diabetic nephropathy treated in our institution assessed for eligibility were recruited and assigned at a ratio of 1 : 1 to either the observation group ([urinary albumin excretion rate (UAER)] of 30 mg-300 mg/24 h) or the research group ([UAER] >300 mg/24 h). IL-6, MCP-1, renal function indices, and NF-κB levels were determined, and their correlation with DN was analyzed. Logistic regression was used to analyze the influencing factors of end-stage renal disease in patients with diabetic nephropathy. The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated to analyze the predictive value of combined detection of IL-6, MCP-1, and NF-κB in the prognosis of patients with diabetic nephropathy. Results. The eligible patients with UAER of 30 mg-300 mg/24 h were associated with significantly higher levels of IL-6, MCP-1, NF-κB, blood urea nitrogen (BUN), and serum creatinine (Scr) versus those with UAER >300 mg/24 h (

P
<
0.05

). During the follow-up, a total of 38 patients progressed to end-stage renal diseases. Eligible patients with end-stage renal diseases showed significantly higher serum IL-6, MCP-1, and NF-κB levels versus those without end-stage renal diseases (

P
<
0.05

). Serum IL-6, MCP-1, and NF-κB are independent risk factors for the occurrence of end-stage renal disease in patients with diabetic nephropathy. The AUCs of IL-6, MCP-1, and NF-κB for predicting the prognosis of patients with diabetic nephropathy were 0.562, 0.634, and 0.647, respectively, and the AUC of the three combined detection for predicting the prognosis of patients with diabetic nephropathy was 0.889. Conclusion. Serum IL-6, NF-κB, and MCP-1 levels are closely related to renal injury and poor prognosis in patients with diabetic nephropathy, and the combined assay is valuable for assessing patients’ condition and prognosis.
G-YOLOX: A Lightweight Network for Detecting Vehicle Types
Authors: Luo Qiang , Wang Junfan , Gao Mingyu , Lin Huipin , Zhou Hongtao , Miao Qiheng
Published: June 2022

In recent years, vehicle type detection has had an important role in traffic management. A lightweight detection network based on multiscale ghost convolution called G-YOLOX is designed in this paper. It is suitable for practical applications for an embedded device. Specifically,

3
×
3

convolutions and

5
×
5

and

7
×
7

ghost convolutions are combined to fully utilize different feature information. A series of linear transformations was designed to generate ghost feature maps to ensure that the network is lightweight. Moreover, a dataset of images showing different vehicles in a city environment was established. Altogether, 20,000 road scene images were collected, and seven categories of vehicles were identified. Extensive experiments with the benchmark datasets VOC2007 and VOC2012 and with our dataset demonstrate the superiority of the proposed G-YOLOX over the original YOLOX. The proposed G-YOLOX can achieve a nearly invariable mean average precision of 0.5, while the size of the weight file decreased by 40% and the number of parameters decreased by 67% compared to the original YOLOX network.
Assessing the Relationship between Resource Misallocation and Total Factor Productivity Based on Artificial Neural Network
Authors: Zhang Weiwei , Bo Lan , Zhang Shengqiang , Wang Yuan
Published: June 2022

For interpretation of China’s economy, total factor productivity is considered as one of the crucial aspects which is generally dependent on innovation in technologies especially those driven by both scientific research and efficiency of the methodology or process which is dedicated for the allocation of numerous resources available, among enterprises. It is important to note that various factors, which are either directly or indirectly involved, to cause misallocation of the resources to the enterprises, are overly complex. Therefore, an affective mechanism is needed to be realized which is capable of resolving these issues with the available resources and infrastructures. In this paper, we have focused on the construction or development of an artificial neutral network (ANN) based evaluation model to study the impact of resource misallocation on total factor productivity. Likewise, we have conducted a counterfactual experiment, i.e., simulation only, to thoroughly examine the relationship between two very important factors, that is, (i) resource misallocation and (ii) total factor productivity. To do this, we are aiming at investigating the growth potential of total factor productivity when there is no resource misallocation. After comparing 8 industries in different regions, we conclude that the contribution of capital and labor distortion to total factor productivity is the highest in the eastern region of China with −0.036 and 0.065, respectively, followed by the northeast, central, and western regions. In the experiment, China’s total factor productivity growth potential could reach 1.1296, if there is no resource misallocation. The results in this paper would shed some lights on the paths to improve resource allocation efficiency and total factor productivity.
Antitumor Proliferation and Related Mechanism of Ultrasound Irradiation Combined with Safflower Yellow
Authors: Li Gen , Xu Lijun , Wang Xiaoli
Published: June 2022

Ultrasound irradiation is now the best method for evaluating benign and malignant tumor nodules. Chemotherapy has always played an important role in the treatment of malignant tumors. With the large-scale application of chemotherapy drugs, the problem of multidrug resistance of tumors has become more and more prominent, which has become one of the difficulties in tumor chemotherapy. This study mainly explores the antitumor proliferation and related mechanisms of ultrasound irradiation combined with safflower yellow. The breast cancer cell line 4T1 derived from BALB/c mice was selected. BALB/c is an albino laboratory mouse, which, like many commonly used sublines, originated from Mus musculus. BALB/c mice have been bred for more than 200 generations in research institutions around the world and are widely used in animal experiments in immunology and physiology. When the cell proliferation reached 80%–90% of the bottom area of the culture flask, it was resuspended, passaged, frozen, and resuscitated according to experimental needs. The 4T1 breast cancer cell line was cultured by conventional methods. 4T1 breast cancer cells in the logarithmic proliferation phase were collected. After 0.25% was digested with pancreatin, it was washed twice with PBS to adjust the concentration to 1 × 107/mL. A 0.1 mL tumor cell suspension was subcutaneously inoculated on the edge of the mouse chest, thereby establishing a breast cancer model of BALB/c mice. After 6-15 days, the tumor volume grew rapidly and became larger. When the length of the tumor is 2.5 × 2.5, the modeling is successful. Ultrasound-targeted microbubble destruction technology, as a novel drug delivery method with high efficiency and low toxicity, can form transient pores (sonoporation effect) on the cell surface, widen the intercellular space, and increase the membrane permeability, and thus effectively. The transport of drugs, genes, proteins, etc., is promoted to target organs and tissues. Tumor-forming mice were randomly divided into the following four groups: control group, safflower yellow group, ultrasound irradiation group, and ultrasound irradiation combined with safflower yellow group. From the second day of inoculation to the end of the experiment, the body weight of the mice successfully inoculated with 4T1 cells was measured every day; from the 5th day, tumors in each group were calculated body volume and tumor inhibition rate (TIR) of each group. The combined treatment group has a higher tumor inhibition rate than the ultrasound irradiation group, and the difference is statistically significant (

P

 < 0.05). Ultrasound irradiation combined with safflower yellow pigment can effectively inhibit tumor proliferation, maintain, or even improve the efficacy of chemotherapy, thereby improving the patient’s tolerance to chemotherapy.
Boundedness of One Class of Integral Operators from Second Order Weighted Sobolev Space to Weighted Lebesgue Space
Authors: Kalybay Aigerim
Published: June 2022

In the paper, for a certain class of Hardy operators with kernels, we consider the problem of their boundedness from a second order weighted Sobolev space to a weighted Lebesgue space.
Study on AI Audit Mode in the Background of Machine Learning and Internet of Things
Authors: Yang Yang
Published: June 2022

AI is a high-tech development technology that scholars from all over the world are focusing on. It has also undergone subversive changes to the auditing industry. AI has revolutionized auditing processes, methods, and models. In recent years, the government has also vigorously promoted the application of artificial intelligence technology. Machine learning is a subpoint of artificial intelligence research, and its main purpose is to realize the anthropomorphism of electronic devices by giving them the ability to learn. The Internet of Everything has become a feature of the current era, and the Internet of Things technology has also been applied in various industries. The auditing industry is one of the key parts of promoting economic development. Machine learning and Internet of Things technology can bring more improvements to auditing under the current form of artificial intelligence. This paper mainly uses the research methods of literature analysis and case analysis, combined with various visual charts, based on the theory of machine learning and the Internet of Things, to explore the application of the two technologies in the artificial intelligence audit mode, mainly for artificial intelligence auditing in social auditing. The problems in the application are analyzed, and the artificial intelligence audit mode strategy is designed based on machine learning and the Internet of Things according to the national, industry, and social audit workers.
Biomechanical Analysis of Touch Ball Movements in Tennis Forehand Strokes
Authors: Luo Wufeng
Published: June 2022

In order to improve the effect of certain theoretical basis for tennis coaches to correct technical movements and teaching training, a method oriented towards discrete gradient methods that can be used for computational solid mechanics is presented. The biggest feature of this method is that it can directly perform numerical simulation analysis on any point cloud model, without relying on any structured or unstructured grid model. Experimental results show that about 80% of the shots in the game are within 2.5 m of the athlete’s moving distance, and the athlete needs to have 300 to 500 high-intensity exercises; the total running distance of the competition is 1 100–3 600 m. The average VO2 of athletes during the competition is 20–30 mL/min/kg (45%–55% V.O2max), the average heart rate is 135–155 beats/min (70%–85% HRmax), the mean blood lactate was <4 mmol/L, the subjective fatigue was 12–14 (moderate intensity), and the mean metabolic equivalent was 5–7 METs. It is proved that the discrete gradient method can effectively solve the biomechanical analysis problem of tennis forehand hitting the ball. Make up for the lack of action details in the differentiation stage. Improve the effect of certain theoretical basis for tennis coaches to correct technical movements and teaching training.
Experimental Study on Damage Characteristics of Solidified Mud under Coupling Action of Freeze-Thaw Cycle and Chloride Salt
Authors: Zhang Jinsong , Wang Yaxing , Pang Jianyong , Lu Yu , Bu Yishun
Published: June 2022

The physical properties of solidified mud will deteriorate under the combined action of freezing-thawing cycle and chlorine salt, which will affect the safety and stability of solidified mud engineering. In order to study the damage characteristics of solidified mud under the action of freeze-thaw cycle and chloride salt, the solidified mud samples were soaked in different concentrations of sodium chloride solution and treated with freeze-thaw cycle. Besides, the unconfined compressive strength test was carried out to study the damage characteristics of the samples caused by different concentrations of sodium chloride solution and freeze-thaw cycles. The test results show the following. (1) Under the action of freeze-thaw cycle and sodium chloride solution, the surface of the sample deteriorated in varying degrees. With the increase in freeze-thaw cycle times and sodium chloride solution concentration, the mass loss of the sample was greater. (2) Under the action of chlorine salt and freeze-thaw cycle, the strength of the sample decreases with the increase in freeze-thaw cycle times. With the increase in the concentration of sodium chloride solution, the strength of the sample decreases and the damage degree increases gradually. (3) Under the action of freeze-thaw cycle, the internal pores of the samples gradually expand and more honeycomb holes appear, and the content of hydration products is higher. As the concentration of sodium chloride solution increases, the particle connection inside the sample gradually weakens, and the sample is more likely to be damaged.
Evaluation and Analysis of High-Quality Development of New Urbanization Based on Intelligent Computing
Authors: Cheng Haoran
Published: June 2022

Urbanization construction is an important part of China’s economic development. New urbanization is a new development direction proposed by China in order to adapt to social development. China’s urbanization construction must be changed. The construction of new urbanization is not only committed to expanding the scale of cities and towns but also promotes the industrial upgrading of cities and towns and improves the efficiency of urban production to meet the needs of economic growth. Under China’s high-quality economic development model, various problems of ecological environment pollution and low productivity have emerged. New urbanization has become an effective strategy to promote high-quality economic development. The research results of this paper show that (1) the level of coordinated development among urbanization systems is low, and the population agglomeration and industrial economic development, urban land resource utilization, urban public welfare development, and urban ecological environment development are not coordinated during the process of population urbanization, it is necessary to strengthen the development capacity of the economy, space, society, and green urbanization, and only the coordinated development of various systems can promote the high-quality development of urbanization. (2) From 2006 to 2017, the urbanization development coefficient of the five northwestern provinces and regions has increased year by year, and the high-quality development level of urbanization has gradually increased. Except for the urbanization system development coefficient of urbanization from 2016 to 2017, which was higher than 0.3 and was in a relatively imbalanced stage, the coefficients of the other provinces were all lower than 0.2 in each year, which was in a highly imbalanced stage. (3) The loss value of the intelligent computing development evaluation model proposed in the article is the lowest among the detection models. When the number of iterations is 20, the final loss value of the article is 0.1. With the increase in the number of iterations, the accuracy rate is basically in a stable growth state, when the number of iterations is 20, and the accuracy rate reaches a peak value of 99%, which is close to 100%. The experimental results can also show that the performance of the intelligent computing development evaluation model structure is better than the evaluation of high-quality urbanization development.
Comparison of the Oral Microbiota Structure among People from the Same Ethnic Group Living in Different Environments
Authors: Ma Guoyun , Qiao Yanan , Shi Han , Zhou Jianye , Li Yongming
Published: June 2022

The characteristics of the oral microbiota may depend on oral health, age, diet, and geography, but the influence of the geographic setting on the oral microbiota has received limited attention. The characteristics of oral microbiota have been reported to differ between urban and rural environments. In order to minimize the influence of genetic background, we recruited 54 volunteers from the same ethnic group, living in urban and rural areas of Gansu Province, China. We collected dental plaque samples and divided them into four groups according to the participant’s area of residence and dental caries status. We sequenced the 16S rRNA of these samples using the Pacific Biosciences sequencing platform and analyzed the correlation between the geographic area and the characteristics of the oral microbiota. Analysis of the alpha and beta diversity revealed that there were significant differences in diversity and composition of dental plaque microflora among the four groups. Cluster analysis revealed that geographic area played an important role in determining the oral microbiota. Network analysis of oral microorganisms showed that geographic differences had major influence on the composition characteristics and internal structure of oral microorganisms. We found that some dominant strains which may play a key role in maintaining oral health, such as Streptococcus oralis, Capnocytophaga sputigena, Porphyromonas catoniae, Corynebacterium matruchotii, Haemophilus parainfluenzae, and Prevotella loescheii, were less affected by the geographic setting. These results provide a deeper understanding of factors influencing the composition of the oral microbiota and could contribute to early diagnosis and effective prevention of dental caries in different settings.
Numerical Simulation of Temperature Distribution during Mild Moxibustion
Authors: Liu Honghua , Huang Zhiliang , Wei Lei , Huang He , Li Qian , Peng Han , Liu Mailan
Published: June 2022

Mild moxibustion is a treatment approach belonging to moxa-hanging moxibustion. The burning end of the moxa stick is kept at a fixed distance from the moxibustion skin, aiming to make the patient feel warm without burning pain. The appropriate temperature distribution is critical for the mild moxibustion treatment. The purpose of this paper is to improve the efficacy of mild moxibustion on human tissues. By combining the radiative and conductive models with surface-to-surface heat transfer, biological heat transfer simulations are realized based on biological tissues in particular media. A finite element model of mild moxibustion was established to obtain the characteristics of skin tissue temperature distribution under various conditions. The model considers multiple factors, such as the moxa-burning temperature, the stick-to-skin distance, the moxa stick sizes, and the ambient temperature. The results show that the temperature distribution under various conditions is centered at the moxibustion point and the temperature decreases in the surrounding direction. The higher the moxa-burning temperature, the higher the skin surface temperature and the worse the stability in heating. The stick-to-skin distance is inversely proportional to the skin surface temperature. The moxa stick diameter is proportional to the skin surface temperature. The longer the moxibustion time, the higher the skin surface temperature. And the temperature change gradually flattened in the late stage of mild moxibustion. Finally, a set of moxibustion conditions with optimal temperature distribution was obtained by comparing the data of all groups.