bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethnobotanical Uses, Chemical Constituents, and Application of Plantago lanceolata L.
Authors: Abate Limenew , Bachheti Rakesh Kumar , Tadesse Mesfin Getachew , Bachheti Archana
Published: March 2022

The medicinal benefits of P. lanceolata L. have been acknowledged worldwide for hundreds of years. The plant is now distributed worldwide, especially in temperate zones. This review gives an overview of ethnomedicinal use, phytochemistry, pharmacological activities, and other potential application of P. lanceolate L. Several effective chemical constituents such as polyphenols, tannins, flavonoids, alkaloids, terpenoids, iridoid glycosides, fatty acids, and polysaccharides are found in P. lanceolata L., which contribute to its exerting specific therapeutic effects. Correspondingly, studies have found that P. lanceolata L. has different biological activities, including antioxidant, antibacterial, wound-healing, anti-inflammatory, cytotoxic, and antiulcerogenic activity. The plant also treats various diseases related to the skin, respiratory organs, digestive organs, reproduction, circulation, cancer, pain relief, and infections. The plant has many applications in cosmetics such as lotion and creams; it is also used as an excellent indicator to know the presence and absence of heavy metals and the accumulation in industrial and urban areas. The plant suppresses soil nitrogen mineralization in agriculture due to allelochemicals such as aucubin. The biological activities, medicinal properties, and industrial application of P. lanceolata mainly depend on the activities of the responsible, active chemical constituents. However, this field still needs more study to determine the exact mechanisms and the main bioactive compound activity accountable for these activities. Also, most of the studies have been performed in vitro, so further in vivo studies are recommended for the future.
Risk Factors for Venous Thrombosis after Spinal Surgery: A Systematic Review and Meta-analysis
Authors: Wang Sheng , Wu Leilei
Published: March 2022

Background. Venous thrombosis, comprising DVT and PE, is an orthopedic condition that may be fatal after surgery. This study’s purpose was to analyze risk factors for venous thrombosis following spine surgery to help guide treatment prophylaxis. Methods. A computer searched English databases such as PubMed, Web of Science, Embase, Cochrane Library, and Google Academic for relevant publications after spinal surgery. Preoperative walking difficulties, hypertension, diabetes, heart disease, preoperative bleeding volume, etc., were all examined using the NOS scale. Data were analyzed using Review Manager 5.3 software. An analysis was done. Due to the study’s differences, the data was compiled using fixed effects or random effects models. Results. A total of 25 studies were considered, with a total of 1,927,781 individuals after spine surgery, including 7843 patients with venous thrombosis. The included literatures had NOS scores ranging from 5 to 8. According to the findings of the meta-analysis, the age of patients with venous thrombosis after spinal surgery (

OR
=
7.53

, 95% CI (6.73, 8.33)), blood loss (

OR
=
−
141.79

, 95% CI (-154.68, -128.9),

P
=
0.00001

), and operation time (

OR
=
76.93

, 95% CI (73.17, 80.86),

P
=
0.00001

) were higher than those without; diabetes mellitus (OR =1.23, 95% CI (1.12, 1.34),

P
=
0.00001

) and walking disability history (

OR
=
2.97

, 95% CL (1.77, 4.98),

P
=
0.0001

) increased the incidence of postoperative venous thrombosis. Conclusion. High age, female, spinal fusion, big volume blood loss patients, operation time, and hypertension, diabetes, and walking issue are all risk factors for venous thrombosis following surgery.
Pattern Recognition Characteristics and Neural Mechanism of Basketball Players’ Dribbling Tactics Based on Artificial Intelligence and Deep Learning
Authors: Song Xuhui , Fan Linyuan
Published: March 2022

There are many factors that affect a player’s overall basketball ability, and different factors will have different effects. The effect is mainly manifested in the difference of offensive and defensive data of basketball players in basketball games. In the basketball field, the formulation of existing training plans mainly relies on the manual observation and personal experience of coaches. This method is inevitably subjective. The pattern recognition of dribbling tactics is one of the important factors. A proper dribbling tactic can make the team achieve better results. In order to discover different dribbling characteristics, reanalyze the connotation and manifestation of basketball speed and strive to analyze the factors that affect basketball speed reasonably and accurately. The deep learning algorithm simulates the thinking process of the human brain neurons through the computer method and then realizes the function of the computer to automatically learn the data characteristics and complete the complex data analysis task. We use artificial intelligence and deep learning to simulate various dribbling tactics of players and find out the rules to improve players’ abilities. The results of the study prove that developing a suitable dribbling tactical model for basketball players can increase their competitive ability by more than 10%, reduce the damage to players, and prolong their careers. Generally speaking, athletes’ injuries can be reduced by more than 15%. This shows that the pattern recognition characteristics and neural mechanisms of dribbling tactics are extremely important to basketball players.
A Vibration Signal Denoising Method of Marine Atomic Gravimeter Based on Improved Variational Mode Decomposition
Authors: Gong Wenbin , Li An , Liao An , Che Hao , Huang Chunfu , Qin Fangjun
Published: March 2022

As a high-precision gravity measuring device, a marine atomic gravimeter is highly sensitive to vibration signals. Accurate measurement and analysis of vibration signal is the primary condition to realize vibration compensation and vibration suppression. Denoising plays a crucial role in the processing of these vibration signals. The vibration signals of a marine gravimeter contain numerous nonlinear and nonstationary components. In this paper, a vibration signal denoising method of marine atomic gravimeter based on improved variational mode decomposition (VMD) was put forward to effectively suppress the noise. An improved genetic particle swarm optimization (GPSO) was first adopted for the parametric optimization of VMD by taking minimum permutation entropy (PE) as fitness function and adaptively determining the optimal parameters of VMD. PE was then utilized to calculate the proportion of noise-containing components in the intrinsic mode function (IMF) components obtained by VMD. The components were classified into noise and signal components by searching for the mutation points of two adjacent IMF permutation entropies. On this basis, noise components were denoised by Savitzky-Golay (SG) filter. In the end, the denoised components were reconstructed with the signal components to generate denoised vibration signals. To verify the effectiveness, the proposed method was applied in denoising, simulated and measured vibration signals of a marine atomic gravimeter, and compared with Daubechies (db) wavelet, Symlets (sym) wavelet, and empirical mode decomposition (EMD). The results showed that the proposed method could effectively remove the noise from nonlinear vibration signals and retain the authentic and useful information, so that it was able to provide the supporting data for gravity compensation of marine atomic gravimeter.
Change in Health-Related Quality of Life in Cochlear Implant Recipients in China
Authors: Zheng Wenwen , Cao Wei , Chen Shanwen , Li Yifan , Wang Yang , Yao Kun , Qiu Jianxin
Published: March 2022

Objective. The objective is to assess the benefit of cochlear implants in health-related quality of life among postlingually deaf adults in China. Methods. Seventy-one postlingually deaf adult cochlear implant users in one cochlear implant center in China participated in this study. The HUI3 questionnaire as a measurement evaluated their quality of life. A cross-sectional analysis was conducted. Results. Cochlear implant had made statistically significant improvements in quality of life among postlingually deaf adults. The HUI3 scores were significantly better in four attributes (hearing, speech, emotion, and pain) after a cochlear implant. A positive correlation between change in hearing and improvement in emotion was significant. The change in pain and improvement in emotion also had a positive correlation. The duration of HA and CI use had no impact on the gain in HUI3 scores, and the baseline of hearing and emotion state had an influence on HUI3 gain. Conclusion. This study found cochlear implant users had a greatly improved hearing, speech, emotion, and pain, which made statistically significant improvement in quality of life among postlingually deaf adults. There was a statistically significant association between the change of emotion state and improvement in hearing level. We also found a statistically significant correlation between the reduction of feeling in pain and improvement in emotion. The change of quality of life seemed to be influenced by the primary state of emotion and hearing. We believe the measurement HUI3 is suitable for these patients in China.
Effect of Sirtuin-1 and Wnt/β-Catenin Signaling Pathway in Rat Model of Spinal Cord Injury
Authors: Zhu Kunming , Xu Weiwei , Han Donghe , Mei Xifan
Published: March 2022

Sirtuin-1 (SIRT1) has anti-inflammatory and antioxidant effects and has been reported to be involved in spinal cord injury (SCI). Wnt/β-catenin signal has been shown to play a critical role in the pathogenesis of chronic diseases, and it participated in the recovery of nerve function after SCI. However, the specific link between them in SCI is unclear. In addition, targeting posttraumatic astrocyte apoptosis is crucial for improving neural degeneration and locomotor function. Therefore, in this article, we studied the relationship of β-catenin and SIRT1 using in the SCI rat model and primary astrocyte treated with hydrogen peroxide (H2O2) or lithium chloride (LiCl). Results showed that after SCI, SCI area and motor function recover over time, and β-catenin is gradually increased to the seventh day and then in turn decreases until 4 weeks, positively correlated with cell apoptosis. The expression of SIRT1 and downstream FOXO4 gradually increased, and β-catenin is negatively correlated with SIRT1 expression. Moreover, treatment with H2O2 in primary cultured astrocyte significantly increased β-catenin and Caspase-3 expression, while decreased SIRT1 and Forkhead box O- (FOXO-) 4. The immunofluorescence results are consistent with this. Administration of LiCl further aggravates the above results. These findings suggest that SIRT1 is negatively correlated with β-catenin in SCI, which promotes the apoptosis of motor neuron cells, which may be related to the participation of FOXO4.
Intelligent Classroom Teaching Assessment System Based on Deep Learning Model Face Recognition Technology
Authors: Zhang Xiaona , Zhang Xiaoming , Jasni Bin Dolah Ts. Dr
Published: March 2022

AI + education technology has had a wide and far-reaching impact on the education industry, which has been applied to classroom teaching in order to achieve real-time monitoring of the classroom and complete closed-loop feedback on teaching. In this paper, AI face recognition based on deep learning is improved and optimized through key points such as image data acquisition, localization, calibration, comparison, and deepening data models, so that the detection can be completed accurately and quickly even under the condition of light and external object interference, maximizing the accuracy and efficiency of face recognition technology under the influence of the objective environment. The traditional manual operation in classroom teaching is automated and intelligent throughout, reducing the workload of teachers and related personnel while further ensuring the scientific organization and management of classroom teaching. While making classroom teaching and learning life safer, more convenient, and more efficient, it also provides a favourable reference for the wide application and development of facial recognition technology.
The Higher Expression of CDCA2 Associated with Poor Prognosis in Glioma
Authors: Jin Xin , Sun Zhen-qing , Zhou Gui-liang , Li Guo-jun , Deng Shi-feng
Published: March 2022

Glioma is the most common primary intracranial tumor and is related to poor clinical outcomes. The developments of sensitive markers can be applied to reveal the mechanisms involved in the progression of glioma. This study examined CDCA2 expression in glioma samples and its significance in predicting glioma patient outcome. GEPIA and GEO datasets were used to explore the expression of CDCA2 in glioma. Kaplan-Meier and multivariate assays were applied to delve into the prognostic values of CDCA2 expression in glioma patients using CGGA datasets. Our group also determined the associations between CDCA2 and clinical characteristics. Coexpression analysis was performed. In this research, we observed that CDCA2 expression was distinctly upregulated in glioma specimens compared with nontumor specimens. The prognosis of glioma with high CDCA2 expression was distinctly worse compared with that of glioma with low CDCA2 expression. Additionally, multivariate Cox regression analysis revealed that high CDCA2 expression was an independent poor prognostic indicator for glioma patients. High expression of CDCA2 was positively associated with advanced clinical progression. Coexpression analysis revealed that CDCA2 could be positively related to ASPM, SKA1, DLGAP5, NCAPG, and CDCA8 and was negatively associated with ETNPPL, LDHD, MRVI1, CBX7, and CENPJ. Overall, our findings revealed that CDCA2 might serve as an independent prognosis indicator for glioma.
[Retracted] Music Therapy Methods Based on SVM and MLP
Authors: Zou Hongmin
Published: March 2022

Lately, the music therapy is being used widely around the world. Henceforth, this study focuses on the analysis of the music’s effect on fetal heart rate (FHR) curve. To this end, we treated people with music therapy and carried out the experiment. Firstly, 118 people with 32–40 weeks of gestational age who were expecting to give birth were invited to participate in the experiment. There was one control group and three experimental groups: 27 people were in the control group, 32 people were in the experimental group that listened to music for the first 10 minutes and did not listen to music for the second 10 minutes, 29 people were in the experimental group that did not listen to music for the first 10 minutes and listened to music for the second 10 minutes, and 30 people were in the experimental group that listened to music for all 20 minutes. In this paper, a convolutional neural network (CNN) based data processing model for fetal heart rate curves is proposed to improve the accuracy of fetal status assessment. First, the model method divides the high‐dimensional one‐dimensional fetal heart rate (FHR) records into 10 segments and then the characteristics of the FHR are extracted using a feature extraction method based on basic statistics. These features are regarded as input of support vector machine (SVM) and multilayer perceptron (MLP) for classification. According to the experimental results, the classification accuracies of SVM and MLP are 85.98% and 93.24%, respectively.
Online Shopping Brand Sales Based on IoT Big Data Processing
Authors: Zhang Menglin , Ma Xiaoyu
Published: March 2022

As a pair of closely related technical fields, “Internet of Things” and “big data” are gradually applied to the analysis of online shopping, which is very beneficial to promote the healthy and orderly development of the online shopping industry. This article uses the big data processing technology of the Internet of Things to analyze the influencing factors of online shopping brand sales based on the data collected by online questionnaires. It draws certain rules from it, and provides relevant marketing strategies for online shopping brand sales to assist its market positioning. According to the survey, the five aspects of online evaluation, brand awareness, online shopping community, online public opinion influence of related brands, and other brand information acquisition channels all have an impact on online brand sales. Especially women aged 25–35 will pay attention to online information, and 195 people will not choose to buy from brands with negative news. And during the purchase process, 186 people will check the online reviews of related brand products. Among them, there are 183 men aged 25–35 who will pay attention to online reviews.
A Fine-Grained Medical Data Sharing Scheme with Ciphertext Reencryption
Authors: Chen Jiahao , Wang Jingwei , Yin Xinchun , Ning Jianting
Published: March 2022

With the fantastic development of cloud computing technology, cloud storage has been widely applied in the field of medical data sharing due to its efficiency and flexibility. Attribute-based encryption (ABE), as a promising technology, plays an important role in the fine-grained sharing of medical data. However, there are two issues: (1) an access policy specified in the encryption phase may need to be updated after a period of time, and (2) the considerable decryption overhead in ABE is too heavy for resource-limited devices. To address these issues, a fine-grained medical data sharing scheme with ciphertext reencryption is proposed. Users with decryption permission can produce reencryption keys and cloud server can reencrypt initial ciphertext. The cloud server can predecrypt ciphertext, which reduces user’s decryption overhead. Moreover, the traditional centralized server is replaced with a decentralized blockchain that performs system initialization, key management, and user revocation. We compared the proposed scheme with some existing schemes in terms of function and efficiency; the results show that the efficiency of the proposed scheme outperforms other related schemes. The security analysis shows that the proposed scheme is security and correctness.
Prevalence of Moraxella Catarrhalis as a Nasal Flora among Healthy Kindergarten Children in Bhaktapur, Nepal
Authors: Amatya Neetu , Paudel Govinda , Saud Bhuvan , Wagle Sunita , Shrestha Vikram , Adhikari Bibhav
Published: March 2022

Introduction. Moraxella catarrhalis causes mild to severe disease in all age groups, mainly in children. This study investigates the prevalence of M. catarrhalis, its cocolonization with other common nasal flora, and associated risk factors in kindergarten children in Bhaktapur. Method. A cross-sectional study was conducted among 136 healthy school-going children from four kindergartens of Bhaktapur Municipality. Nasal swabs were examined for identification and isolation of M. catarrhalis and its antibiotic susceptibility pattern. Additionally, further analysis was performed for cocolonization and associated risk factors. Results. Out of 136 students, M. catarrhalis was detected in 80 (58.8%) children. Using bivariate and multivariate analysis, the associated risk factors with significantly high carriage rates were age group of 3–4 years, classroom occupancy with 15–30 children, and antibiotic consumption within 6 months, with a p value of ≤0.05 in each of the cases. Multiple logistic regression analysis of bacterial coexistence depicted M. catarrhalis to be positively associated with Streptococcus pneumoniae and Haemophilus influenzae and negatively associated with Staphylococcus aureus. Furthermore, the highest double colonization occurred among M. catarrhalis and S. aureus and the highest triple colonization occurred among M. catarrhalis, S. aureus, and S. pneumoniae. The antibiogram pattern showed the target organisms to be highly resistant to amoxycillin/clavulanate (18.8%) and most sensitive to chloramphenicol (100%). Conclusion. This study shows a high prevalence of M. catarrhalis in healthy kindergarten children and is positively associated with other nasal isolates like S. pneumoniae and H. influenzae.
Fuzzy Cognitive Maps with Bird Swarm Intelligence Optimization-Based Remote Sensing Image Classification
Authors: Hilal Anwer Mustafa , Alsolai Hadeel , Al-Wesabi Fahd N. , Nour Mohamed K , Motwakel Abdelwahed , Kumar Anil , Yaseen Ishfaq , Zamani Abu Sarwar
Published: March 2022

Remote sensing image (RSI) scene classification has become a hot research topic due to its applicability in different domains such as object recognition, land use classification, image retrieval, and surveillance. During RSI classification process, a class label will be allocated to every scene class based on the semantic details, which is significant in real-time applications such as mineral exploration, forestry, vegetation, weather, and oceanography. Deep learning (DL) approaches, particularly the convolutional neural network (CNN), have shown enhanced outcomes on the RSI classification process owing to the significant aspect of feature learning as well as reasoning. In this aspect, this study develops fuzzy cognitive maps with a bird swarm optimization-based RSI classification (FCMBS-RSIC) model. The proposed FCMBS-RSIC technique inherits the advantages of fuzzy logic (FL) and swarms intelligence (SI) concepts. In order to transform the RSI into a compatible format, preprocessing is carried out. Besides, the features are produced by the use of the RetinaNet model. Besides, a FCM-based classifier is involved to allocate proper class labels to the RSIs and the classification performance can be improved by the design of bird swarm algorithm (BSA). The performance validation of the FCMBS-RSIC technique takes place using benchmark open access datasets, and the experimental results reported the enhanced outcomes of the FCMBS-RSIC technique over its state-of-the-art approaches.
The Value of Color Doppler Ultrasound and CT Combined with Serum AFP Examination in the Diagnosis of Hepatocellular Carcinoma
Authors: Jia Peiwan , Mao Yunjie , Liu Kahua , Wei XianJuan
Published: March 2022

Objective. To evaluate the value of the combination of color Doppler ultrasound, computed tomography (CT), and serum tumor marker alpha-fetoprotein (AFP) examination in the diagnosis of hepatocellular carcinoma (HCC). Methods. 98 patients with HCC (malignant tumor group) and 50 liver lesion patients (benign control group), were selected for the study, and retrospective statistical methods were used to evaluate the diagnostic values of the three examinations on hepatocellular carcinoma. Results. (1) When comparing color Doppler ultrasound blood flow parameters, the hepatic artery diameter, peak flow velocity, minimum flow velocity, and resistance index (RI) of hepatocellular carcinoma were significantly higher than those of the benign control group (

P
<
0.05

), while the portal vein flow velocity was significantly lower than that of the control group (

P
<
0.05

). (2) Enhanced CT imaging of hepatocellular carcinoma lesions showed mostly outflow-type enhancement changes, with high- or slightly high-density shadowing and uneven enhancement in the arterial phase, relatively low density and withdrawal of enhancement in the portal vein phase and delayed phase. (3) The serum AFP level of hepatocellular carcinoma patients was significantly higher than that of the benign control group (

P
<
0.01

). (4) The sensitivity of color Doppler ultrasound, CT, and serum AFP alone for the diagnosis of HCC was 79.59%, 85.71%, and 66.33%, and the accuracy was 83.78%, 87.16%, and 74.32%, respectively, while the combination of the three tests could significantly increase the sensitivity to 96.94% and the accuracy to 93.92%, compared with each individual test (

P
<
0.01

). Conclusion. Color Doppler ultrasound and CT combined with serum AFP examination could significantly improve the sensitivity and accuracy of hepatocellular carcinoma diagnosis, reduce misdiagnosis, and facilitate early diagnosis and clinical early intervention.
Dark-Lumen Magnetic Resonance Image Based on Artificial Intelligence Algorithm in Differential Diagnosis of Colon Cancer
Authors: Fang Yujie , Kang Ting , Yang Yang , Zi Yonghong , Lu Xiong
Published: March 2022

This research was aimed o investigate the application value and diagnostic effect of dark-lumen magnetic resonance imaging (dark-lumen MRI) based on artificial intelligence algorithm on colon cancer. A total of 98 patients with ulcerated colon cancer were selected as the study subjects. All patients underwent colonic endoscopy. The patients were divided into algorithm group (artificial intelligence algorithm processing image group) and control group (conventional method processing image group) according to different dark-lumen MRI processing methods. The detection efficiency of colon cancer was compared between the two groups. It showed that the diagnostic effect of dark-lumen MRI based on artificial intelligence algorithm was significant. The apparent diffusion coefficient (ADC) in the control group was 0.92 ± 0.14 mm2/s (minimum: 0.74, maximum: 1.30), ADC in the algorithm group was 1.55 ± 0.31 mm2/s (minimum: 1.22, maximum: 2.42). The ADC of patients in algorithm group was significantly higher than that of patients in control group, with statistical difference (t = 7.827, P < 0.001). The correct number of cases was 46 and the diagnostic error number was 3 in algorithm group, with accuracy of 93%. The correct number of cases was 41 and the diagnostic error number was 8 in control group, with accuracy of 83%. In comparison, the correct rate was 10% higher in algorithm group, indicating that the diagnostic effect was better in algorithm group. The mean value of invasion depth was 10.42 in the algorithm group and 5.27 in the control group, indicating that the algorithm group was more accurate in the judgment of invasion depth, had a good prospect of clinical application, and had guiding significance for the diagnosis of colon cancer.
Kinect‐Based Rehabilitation Systems for Stroke Patients: A Scoping Review
Authors: Almasi Sohrab , Ahmadi Hossein , Asadi Farkhondeh , Shahmoradi Leila , Arji Goli , Alizadeh Mojtaba , Kolivand Hoshang
Published: March 2022

Background and Objective. Kinect‐based rehabilitation is an effective solution for creating motivation and promoting adherence to rehabilitation programs in stroke patients. The current study was aimed at examining the effects of Kinect‐based rehabilitation systems on performance improvement, domains of use, and its limitations for stroke patients. Method. This study was conducted according to Arksey and O’Malley’s framework. To investigate the evidence on the effects of Kinect‐based rehabilitation, a search was executed in five databases (Web of Science, PubMed, Cochrane Library, Scopus, and IEEE) from 2010 to 2020. Results. Thirty‐three articles were finally selected by the inclusion criteria. Most of the studies had been conducted in the US (22%). In terms of the application of Kinect‐based rehabilitation for stroke patients, most studies had focused on the rehabilitation of upper extremities (55%), followed by balance (27%). The majority of the studies had developed customized rehabilitation programs (36%) for the rehabilitation of stroke patients. Most of these studies had noted that the simultaneous use of Kinect‐based rehabilitation and other physiotherapy methods has a more noticeable effect on performance improvement in patients. Conclusion. The simultaneous application of Kinect‐based rehabilitation and other physiotherapy methods has a stronger effect on the performance improvement of stroke patients. Better effects can be achieved by designing Kinect‐based rehabilitation programs tailored to the characteristics and abilities of stroke patients.
Fault Diagnosis Method for Industrial Robots Based on DBN Joint Information Fusion Technology
Authors: Jiao Jian , Zheng Xue-jiao
Published: March 2022

Aiming at the problems of the traditional industrial robot fault diagnosis model, such as low accuracy, low efficiency, poor stability, and real-time performance in multi-fault state diagnosis, a fault diagnosis method based on DBN joint information fusion technology is proposed. By studying the information processing method and the deep learning theory, this paper takes the fault of the joint bearing of the industrial robot as the research object. It adopts the technique of combining the deep belief network (DBN) and wavelet energy entropy, and the fault diagnosis of industrial robot is studied. The wavelet transform is used to denoise, decompose, and reconstruct the vibration signal of the joint bearing of the industrial robot. The normalized eigenvector of the reconstructed energy entropy is established, and the normalized eigenvector is used as the input of the DBN. The improved D-S evidence theory is used to solve the problem of fusion of high conflict evidence to improve the fault model’s recognition accuracy. Finally, the feasibility of the model is verified by collecting the fault sample data and creating the category sample label. The experiment shows that the fault diagnosis method designed can complete the fault diagnosis of industrial robot well, and the accuracy of the test set is 97.96%. Compared with the traditional fault diagnosis model, the method is improved obviously, and the stability of the model is good; the utility model has the advantages of short time and high diagnosis efficiency and is suitable for the diagnosis work under the condition of coexisting multiple faults. The reliability of this method in the fault diagnosis of the joint bearing of industrial robot is verified.
Decreased Susceptibility of Shigella Isolates to Azithromycin in Children in Tehran, Iran
Authors: Behruznia Parisa , Sadredinamin Mehrzad , Hashemi Ali , Hajikhani Bahareh , Yousefi Nojookambari Neda , Behruznia Mahboobeh , Ghalavand Zohreh
Published: March 2022

Azithromycin (AZT) has widely been used for the treatment of shigellosis in children. Recent studies showed a high rate of decreased susceptibility to azithromycin due to different mechanisms of resistance in Shigella isolates. Accordingly, the purpose of this study was to investigate the role of azithromycin resistance mechanisms of Shigella isolates in Iran during a two-year period. In this study, we investigated the mechanisms of resistance among Shigella spp. that were isolated from children with shigellosis. The minimum inhibitory concentration (MIC) of Shigella isolates to azithromycin was determined by the agar dilution method in the presence and absence of Phe-Arg-β-naphthylamide inhibitor. The presence of 12 macrolide resistance genes was investigated for all isolates by PCR for the first time in Tehran province in Iran. Among the 120 Shigella spp., only the mph(A) gene (49.2%) was detected and other macrolide resistance genes were absent. The phenotypic activity of efflux pump was observed in 1.9% of isolates which were associated with over expression of both omp(A) and omp(W) genes. The high prevalence of the mph(A) gene among DSA isolates may indicate that azithromycin resistance has evolved as a result of antimicrobial selection pressures and inappropriate use of azithromycin.
Application of Artificial Intelligence Computing in the Universal Design of Aging and Healthy Housing
Authors: Shu Quanfa , Liu Hui
Published: March 2022

Intelligent control technology is not only the use of the so-called highly sophisticated technology in the daily life of the elderly but also control services according to the individual needs of the elderly. This paper combines research in psychology and ergonomics to explore how to use the living space to build indoor scenarios that influence the behavioural and psychological changes of the elderly based on satisfying functionality. The external environment influences the user’s perception, and the perception determines the user’s behaviour. Through the construction of scenarios, objects and people can interact with each other, thus achieving the objective of “solitude but not loneliness” for the elderly living alone and providing a modern ageing environment with high safety, convenience, quality, and comfort for the elderly.
Pipeline 3D Modeling Based on High-Definition Rendering Intelligent Calculation
Authors: Li Shao , Zhou Yu
Published: March 2022

In the processing of panoramic video, projection mapping is a very critical step. The selection of the projection mapping format will affect the performance, transmission mode, and rendering mode of the panoramic video codec. Therefore, this article starts from the projection mapping format, analyzes the mapping process of the standard mapping format, and then proposes a method of rendering panoramic video in the projection mapping format. By analyzing the parallel design schemes of swarm intelligence algorithms under different granularities, this paper proposes a parallel swarm intelligence optimization algorithm design method and then designs and implements a parallel artificial bee colony algorithm. With the help of the ArcGIS Engine development platform, this paper defines the interface for data exchange. With the support of Multipatch format data in ArcGIS software, through secondary development, the three-dimensional pipeline automatic modeling module is established, and the pipeline model is automatically generated. The digital construction and visualization of the company play a driving role. Based on the understanding of the characteristics of the pipeline image itself, combined with the analysis of the shortcomings of the existing methods, this paper proposes a new deep learning-based high-definition rendering solution for the pipeline image. In this paper, the pipeline image is preprocessed, and then the processed pipeline image is converted into a style pipeline image through the pipeline image style transfer technology, and the obtained style pipeline image is postprocessed to enhance the effect. The preprocessing of pipeline images mainly includes pipeline image enhancement and pipeline image filtering operations. Its purpose is to change the distribution of pipeline images to improve the quality of pipeline images and make them more suitable for subsequent style conversion. In the part of pipeline image style conversion, this paper proposes a new deep learning-based pipeline image high-definition rendering network, which consists of three subnetworks: pipeline image feature modeling module, feature model alignment module, and pipeline image re-rendering module. This article has conducted sufficient experiments to fully compare the processing results of the method proposed in this article and other existing methods and at the same time shows the high-quality high-definition rendering results. The experimental results verify the excellent performance of the method proposed in this paper.
Effect of Number and Location on Stress Distribution of Mini Dental Implant-Assisted Mandibular Kennedy Class I Removable Partial Denture: Three-Dimensional Finite Element Analysis
Authors: Jia-mahasap Wissanee , Rungsiyakull Chaiy , Bumrungsiri Wipahatpong , Sirisereephap Natthaphorn , Rungsiyakull Pimduen
Published: March 2022

Purpose. To investigate effects of number and location on patterns of von Mises stress distribution and volume average stress on abutment tooth, edentulous ridge, mini dental implant, and surrounding bone of mini dental implant-assisted mandibular Kennedy class I removable partial denture. Materials and Methods. Eight three-dimensional finite element models of mandibular Kennedy class I with different numbers and locations of mini dental implants were constructed. Mini dental implants were generated in the area of second premolar, first molar, and second molar, respectively. A static load of 400 N was applied on all models. The von Mises stress and volumetric average stress were calculated by three-dimensional finite element analysis. Result. The minimum volumetric average stress of abutment tooth was found in the model, where there was one mini dental implant at the second molar position and 2 mini dental implants at first molar and second molar positions. The model with three mini dental implants had reduced volumetric average stress of abutment tooth, which was not different from the model with two mini dental implants. However, the minimum volumetric average stress of mini dental implant and surrounding bone were found when three mini dental implants were applied, followed by two and one mini dental implants, respectively. Conclusion. Placing at least one mini dental implant at a second molar position can help reduce stress transferred to the abutment tooth. Stresses around each implant and surrounding bone reduced with increased numbers of mini dental implants.
Wind Power Installed Capacity Forecast Based on a Two‐Parameter Variable‐Weight Buffer Operator and Subsidy Strategy Research
Authors: Li Ye , Bai Xue
Published: March 2022

Since the installed capacity of wind power is greatly affected by the subsidy policy, this paper predicts the installed wind power capacity in China under different policy scenarios. Firstly, a new two‐parameter variable‐weight buffer operator is proposed to quantify the impact of the policy shock, whose optimal parameters are obtained by the genetic algorithm, and combined with the grey GM(1,1) model to predict the installed capacity of wind power in China under the cessation of subsidy policy. Then, the GM(1,1) model with optimized background value is used to predict the installed capacity under continued subsidy. Finally, two policy subsidy strategy models are constructed based on the forecast data to simulate the future trend of wind power installed capacity under different subsidy policies and explore the strength of wind power subsidies in China during the “14th Five‐Year Plan” period (2021–2025). The results show that both the GM(1,1) model based on the two‐parameter variable‐weight buffer operator and the GM(1,1) model with optimized background value have high fitting accuracy, with errors of 0.15% and 4.93%, respectively. Furthermore, in the case of the central government’s subsidy cancellation, the local government should take over the central government’s subsidy policy and adjust the subsidy intensity to 0.57–1 times of that during the “13th Five‐Year Plan” period (2015–2020) to achieve the national planning target.
Cigarette Smoke Exposure Increases Glucose-6-phosphate Dehydrogenase, Autophagy, Fibrosis, and Senescence in Kidney Cells In Vitro and In Vivo
Authors: Liu Wen-Chih , Chuang Hsiao-Chi , Chou Chu-Lin , Lee Yu-Hsuan , Chiu Yu-Jhe , Wang Yung-Li , Chiu Hui-Wen
Published: March 2022

Cigarette smoke (CS) is a risk factor for chronic obstructive pulmonary disease. We attempted to investigate fully the possible effects of CS on kidney cells. We found that the viability of a human kidney proximal tubular epithelial cell line (HK-2 cells) was decreased after treatment with CS extract (CSE). In particular, the effects of CSE at low concentrations did not change the expression of apoptosis and necrosis. Furthermore, CSE increased autophagy- and fibrosis-related proteins in HK-2 cells. Senescence-related proteins and the senescence-associated secretory phenotype (SASP) increased after HK-2 cells were treated with CSE. In addition, both RNA sequencing and gene set enrichment analysis data revealed that glucose-6-phosphate dehydrogenase (G6PD) in the reactive oxygen species (ROS) pathway is responsible for the changes in CSE-treated HK-2 cells. CSE increased G6PD expression and its activity. Moreover, the inhibition of G6PD activity increased senescence in HK-2 cells. The inhibition of autophagy reinforced senescence in the CSE-treated cells. In a mouse model of CS exposure, CS caused kidney damage, including tubular injury and glomerulosclerosis. CS increased fibrosis, autophagy, and G6PD expression in kidney tissue sections. In conclusion, CS induced G6PD expression, autophagy, fibrosis, and senescence in kidney cells. G6PD has a protective role in CS-induced nephrotoxicity.
The Construction of Smart Learning Space in Colleges Based on Blended Learning
Authors: Qi Shaobo
Published: March 2022

The arrival of the “Internet+” era has made a tremendous impact on the traditional model of talent training in colleges and universities, and the social expectations for college graduates have changed greatly compared with the past. As the cultivation base for talents, colleges and universities must adapt to the trend of the times to reform the mode of talent training. The blended learning mode based on the combination of face-to-face learning and online learning can meet the requirements of the teaching reform in the new era to some extent. This paper discusses how to build the intelligent learning space based on blended learning from the aspects of the technology environment, the teaching process, the learning mode, the smart evaluation and so on and constructs the evaluation index system to be demonstrated, in order to make contributions to the establishment of the new teaching mode, the cultivation of talents, and the establishment of a lifelong learning system.
A Brand Image Design Service Model Using the Visual Communication Technology under the Background of Internationalization
Authors: Fu Lixin
Published: March 2022

The era of internationalization is the era of Internet of Everything. It not only promotes global economic growth but also subverts the traditional development model of brands in all walks of life, encourages the comprehensive upgrading of traditional brands, and spawns a large number of new-generation online brands. The visual expression of the entire brand promotion strategy is the brand visual design. Communication and appeal are the most specific and direct in the entire brand identity system. With the popularity of the Internet, the rise of platforms, the replacement of mobile devices, and the rapid development of new media technologies, the media and update methods of brand communication are more abundant. A brand image that conforms to the characteristics of the times, as a spiritual outlook, helps to better enhance the brand value. This article focuses on online brand image design in an international context. The brand image design service model based on visual communication is more conducive to brand development and is aimed at stimulating how design thinking can deepen the brand image to a certain extent.
An Extremely Rare SRD5A2 Gene c.485A>C Mutation in a Compound Heterozygous Newborn with Disorders of Sex Development First Identified in Vietnam
Authors: Le Phan Tuong Quynh , Le Thanh Nha Uyen , Nguyen Thi Thanh Binh , Nguyen Minh Thao , Ha Thi Minh Thi
Published: March 2022

SRD5A2 (steroid 5-alpha-reductase 2) mutation, which impairs 5α-reductase-2 enzyme activity, is among the causes of 46,XY disorders of sex development (DSD). Here, we report a rare pathogenic mutation NM_000348.4:c.485A>C (NP_000339.2:p.His162Pro) of SRD5A2 gene in a compound heterozygous state first identified in a Vietnamese newborn with 5α-reductase-2 enzyme deficiency. We also first submitted this rare mutation to ClinVar database (VCV000973099.1). The patient presented with hyperpigmented labia-majora-like bifid scrotum, clitoris-like phallus, perineoscrotal hypospadias, and blind-ending vagina. The other mutation NM_000348.4:c.680G>A (NP_000339.2:p.Arg227Gln) was reported previously. This compound heterozygous mutation was first detected by next-generation sequencing. By Sanger sequencing, we confirmed that the c.485A>C mutation was maternal inherited, whereas the c.680G>A mutation was paternal inherited. Up to date, this is the first report of this rare compound heterozygous state of SRD5A2 c.485A>C and c.680G>A mutations in patients with 46,XY DSD generally as well as in Vietnamese population particularly and is also the second report in the world carrying the pathogenic mutation NM_000348.4:c.485A>C (NP_000339.2:p.His162Pro). Our finding has enriched the understanding of the spectrum of SRD5A2 variants and phenotypic correlation in Asian patients with 46,XY DSD.
Edifying the Focal Factors Influencing Mesenchymal Stem Cells by the Microenvironment of Intervertebral Disc Degeneration in Low Back Pain
Authors: Esquijarosa Hechavarria Maite , Richard Seidu A.
Published: March 2022

Intervertebral disc degeneration (IVDD) is one of the main triggers of low back pain, which is most often associated with patient morbidity and high medical costs. IVDD triggers a wide range of pathologies and clinical syndromes like paresthesia, weakness of extremities, and intermittent/chronic back pain. Mesenchymal stem cells (MSCs) have demonstrated to possess immunomodulatory functions as well as the capability of differentiating into chondrocytes under appropriate microenvironment conditions, which makes them potentially epitome for intervertebral disc (IVD) regeneration. The IVD microenvironment is composed by niche of cells, and their chemical and physical milieus have been exhibited to have robust influence on MSC behavior as well as differentiation. Nevertheless, the contribution of MSCs to the IVD milieu conditions in healthy as well as degeneration situations is still a matter of debate. It is still not clear which factors, if any, are essential for effective and efficient MSC survival, proliferation, and differentiation. IVD microenvironment clues such as nucleopulpocytes, potential of hydrogen (pH), osmotic changes, glucose, hypoxia, apoptosis, pyroptosis, and hydrogels are capable of influencing the MSCs aimed for the treatment of IVDD. Therefore, clinical usage of MSCs ought to take into consideration these microenvironment clues during treatment. Alteration in these factors could function as prognostic indicators during the treatment of patients with IVDD using MSCs. Thus, standardized valves for these microenvironment clues are warranted.
In Silico Analysis of the Correlation of KIF2C with Prognosis and Immune Infiltration in Glioma
Authors: Tu Binfeng , Xiang Huali , Li Min , Zhong Fangping , Fang Meng , Yan Wangjun
Published: March 2022

Glioblastoma (GBM) is one of the most commonly pivotal malignant caners. Numerous reports have revealed the crucial roles of immune infiltration in the initiation and progression of GBM. In this study, we first identified differentially expressed genes (DEGs) in the progression of GBM using CGGA databases. Totally, 156 upregulated DEGs and 251 downregulated DEGs were revealed. By constructing a protein-protein interaction network, KIF2C was identified as a hub gene in GBM. Further analysis revealed an evidently positive association existing in KIF2C expression and the advanced stages of gliomas. Higher expression of KIF2C was in WHO grade IV samples relative to that in grade III and grade II samples. In addition, our results showed that KIF2C was higher in IDH1 wild-type samples than IDH1 mutant glioma samples, in 1p/19q noncodel samples than 1p/19q code glioma samples, and in recurrent samples than primary glioma samples. Moreover, our results showed that higher expression of KIF2C correlated with shorter survival time in both primary and recurrent gliomas and could act as a potential biomarker for the prognosis of GBM. Further analysis demonstrated that higher expression of KIF2C was related to higher levels of endothelial cell, T cell CD8+ naïve, common lymphoid progenitor, T cell CD4+ Th2, T cell CD4+ Th2, macrophage, macrophage M1, T cell CD4+ memory, and T cell CD4+ effector memory, but was related to lower levels of NK cell, B cell plasma, T cell CD4+ Th1, T cell regulatory (Tregs), neutrophil, and T cell NK. We thought this study could provide potential biomarkers for the prediction of prognosis and immune infiltration of gliomas.