bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Model for Brain Tumor Detection Using Ensemble Transfer Learning and Quantum Variational Classifier
Authors: Amin Javeria , Anjum Muhammad Almas , Sharif Muhammad , Jabeen Saima , Kadry Seifedine , Moreno Ger Pablo
Published: April 2022

A brain tumor is an abnormal enlargement of cells if not properly diagnosed. Early detection of a brain tumor is critical for clinical practice and survival rates. Brain tumors arise in a variety of shapes, sizes, and features, with variable treatment options. Manual detection of tumors is difficult, time-consuming, and error-prone. Therefore, a significant requirement for computerized diagnostics systems for accurate brain tumor detection is present. In this research, deep features are extracted from the inceptionv3 model, in which score vector is acquired from softmax and supplied to the quantum variational classifier (QVR) for discrimination between glioma, meningioma, no tumor, and pituitary tumor. The classified tumor images have been passed to the proposed Seg-network where the actual infected region is segmented to analyze the tumor severity level. The outcomes of the reported research have been evaluated on three benchmark datasets such as Kaggle, 2020-BRATS, and local collected images. The model achieved greater than 90% detection scores to prove the proposed model's effectiveness.
Analysis of Serum Levels of IFN-γ, IL-4, and TNF-α in Patients with Cervicitis Complicated by HPV Infection and Their Clinical Significance
Authors: Li Jingxia , Liu Yuejun , Song Jianjun , Liu Wenli , Zhou Liyuan , Chen Shucheng
Published: April 2022

In order to investigate the expression levels of serum IFN-γ, IL-4, and tumor necrosis TNF-α in patients with cervicitis complicated with human papillomavirus (HPV) infection and clinical significance, a retrospective study was conducted on 90 patients with chronic cervicitis complicated by HP V infection who visited our hospital from June 2020 to June 2021, and they are included in the research group. According to the degree of HPV infection, the patients are divided into low-risk HPV type group (n = 65 cases) and high-risk HPV type group (n = 25 cases); 50 patients with cervicitis (without HPV infection) who received treatment in our hospital are selected as control group 1. Fifty healthy women who underwent physical examination are selected as the control group 2. The general data of the two groups of patients during hospitalization are collected, and HPV-DNA, IFN-γ, IL-4, and TNF-α are detected in all patients. For patients with cervicitis complicated by HPV infection, the IFN-indexes in the body are significantly decreased, IL-4 and TNF-αare significantly increased, and with the degree of HPV infection, IFN-γ, IL-4, and TNF-α have high diagnostic performance with HPV infection, and there is a significant correlation between the three, which can be used in cervicitis complicated with HPV infection. It is widely used in the early diagnosis and screening of infected patients.
Area Differences in Regional Logistics Efficiency and the Law Governing Its Temporal and Spatial Evolution
Authors: Ran Wenxue , Liu Ruli , Liu Shiwen
Published: April 2022

Because logistics is an important service industry with regard to national economic development, the development level of this industry has emerged as one of the most significant indicators of a country or region’s comprehensive strength. An in-depth study of the regional differences in China’s logistics efficiency and its evolution law in time and space can help promote the high-quality development of the logistics industry. To this end, this study collects data pertaining to the development of the logistics industry in China’s eight economic regions during the period 2009–2018. Moreover, it uses DEA models to calculate the logistics efficiency of 31 provinces and cities in these eight economic regions. Results indicate the following: (1) affected by external environmental factors, the pure technical efficiency is underestimated and the scale efficiency and integrated technical efficiency are overestimated; (2) it reveals that residents’ consumption level and the total retail sales of social consumer goods are negatively correlated with regional logistics efficiency, whereas the regional per capita gross domestic product is positively correlated with regional logistics efficiency; (3) in terms of space, the logistics industry in the same region displays characteristics of high aggregation and cooperation, whereas serious segmentation and opposition are found among different regions. The logistics efficiency of China’s eight economic zones is unbalanced. It displays a pattern of high efficiency in the east and low efficiency in the west on the whole. Moreover, valuable suggestions were propounded to improve regional logistics efficiency in China.
3D Printing Combined with Osteotomy of the Lateral Tibial Condyle for the Treatment of Tibial Plateau Fractures Involving the Lateral Posterior Condyle
Authors: Xu Zhiping , Jiao Jing , Xiao Fei , Huang Yucheng , Wang Junwen
Published: April 2022

The treatment of the fracture of the tibial plateau outside the posterior condyle is always a difficult problem in the clinical work of orthopedic surgeons. In this study, we aim to investigate the clinical effect of 3D printing combined with osteotomy of the tibial lateral condyle in the treatment of tibial plateau fractures involving the external posterior condyle. From January 2012 to February 2020, the data of 94 patients with fracture of tibial plateau external posterior condyle treated by 3D printing combined with osteotomy were retrospectively analyzed, including 38 males and 56 females. The 94 patients were divided into 2 groups (freehand osteotomy group and guided osteotomy group), with 47 patients in each group. All patients received preoperative CT 3D scan, and 3D printing was performed according to the converted data to make a 1 : 1 solid size fracture model. Two groups of patients were treated with anterolateral combined with posteromedial incision intraoperatively, and osteotomy lines were designed according to preoperative 3D model. After surgery, the fracture reduction was evaluated according to the Rasmussen knee scoring standard, and the knee function was evaluated by the Hospital for Special Surgery (HSS) score. One year after operation, the Rasmussen score of the knee joint was 13-18 points, with an average of 15.73 points, among which 66 cases were excellent, 24 cases were good, and 4 cases were fair, with an excellent and good rate of 95.7% (45/47). The HSS score is as follows: 67-94 points, with an average of 82.67 points, among which 62 cases were excellent, 26 cases were good, 4 cases were fair, and 2 cases were poor (joint stiffness caused by refusal of postoperative rehabilitation exercise), with an excellent and good rate of 89.9% (44/47). The range of motion of knee joint was -5°~0°~135°, and the average range of motion was 125.5°. At the last follow-up, there were no serious complications such as common peroneal nerve injury, popliteal vascular injury, postoperative infection, and failure of internal fixation. 3D printing combined with osteotomy of the tibial lateral condyle is an effective method for the treatment of fractures of the tibial plateau external posterior condyle, and the postoperative treatment results are satisfactory. The customized osteotomy guide plate is used for more accurate osteotomy, less injury, and more accurate fixation with support screws.
Helmet Wearing Recognition of Construction Workers Using Convolutional Neural Network
Authors: Peng Hong , Zhang Zhenwei
Published: April 2022

One of the most effective ways to prevent construction workers from suffering a head injury is to wear a safety helmet. The use of a computer vision method to detect whether or not construction workers are wearing helmets can improve external construction worker supervision, reducing the number of head injury accidents. A helmet-wearing recognition method based on head recognition is proposed using CNN (convolutional neural network). The area of the head of constructors can be accurately located using crossvalidation of facial feature recognition and head recognition, which solves the problem of determining constructor head position under complex posture. The I-YOLOv3 target detection network is used to detect helmet wear, and the relative position relationship between the helmet and the human body is determined. The findings show that the helmet wearing identification system can be successfully applied to helmet wearing identification work in a complex environment construction site, and it offers a new research perspective and technical method for construction industry information-based safety monitoring.
Effect of Dexmedetomidine on Cardiac Output among Parturient with Severe Preeclampsia after Cesarean Section
Authors: Lv Yanxiang , Zhou Ying , Qiao Yuan , Hu Rui , Liang Yan , Lian Yanan , He Tongqiang
Published: April 2022

This study was to investigate the hemodynamic effect of dexmedetomidine among parturient with severe preeclampsia after cesarean section. Parturient with severe preeclampsia were randomly allocated to receive dexmedetomidine (0.2-0.7 μg/kg/h) or equivalent volumes of 0.9% saline as control after cesarean section, respectively. A total of 36 parturient with severe preeclampsia were enrolled, including 18 in the dexmedetomidine (DEX) group and 18 in the saline group. Compared with the saline group, among those in the DEX group, CO was reduced by 1.30 L/min (95% CI: -2.36 to 0.25;

P
=
0.019

). Additionally, HR (-13.79 bpm, 95% CI: -22.02 to -5.58;

P
=
0.002

), SBP (-16.11 mmHg, 95% CI: -30.56 to -1.66;

P
=
0.030

), DBP (-10.48 mmHg, 95% CI: -18.27 to -2.69;

P
=
0.002

), and MAP (-12.36 mmHg, 95% CI: -22.05 to -2.66;

P
=
0.014

) were reduced in the DEX group compared with the saline group. In contrast, there were no changes observed in SV and ICON between groups. In conclusion, dexmedetomidine reduces cardiac output by inhibiting the acceleration of heart rate without sacrificing myocardial contractility and stroke volume.
Factors and Mechanism Affecting the Attractiveness of Public Transport: Macroscopic and Microscopic Perspectives
Authors: Zhang Chunqin , Wang Mengmeng , Dong Junyi , Lu Weite , Liu Yong , Ni Anning , Yu Xueyan
Published: April 2022

Enhancing the attractiveness of public transport is a key objective for transit agencies that seek to achieve sustainable urban mobility. This study identifies the key factors that affect the attractiveness of public transport from the macroscopic and microscopic perspectives and establishes a comprehensive influence mechanism. Weighted least square-Structural equation model (WLS-SEM) is used to quantify the microscopic factors. Conclusions are summarized as follows: ① the macroscopic factors include urban spatial layout, land use pattern, geographical environment, level of economic development, demographic characteristics, public policy, and service characteristics of public transport; ② the microscopic factors include traveler’s individual characteristics, travel demand characteristics, travel characteristics and service level of public transport; ③ service level of public transport most positively impacts the attractiveness, while the travel characteristics of public transport impact it most negatively.
Experimental and Mathematical Studies for Optimality of GTAW Parameters on Similar and Dissimilar Steel Substrates
Authors: Kiran Bandaru , Nagaraju Dega , Selvaraj Senthil Kumaran , Molla Baye
Published: April 2022

Argon arc welding is a frequently used process, to assist various manufacturing processes. The paper highlights the postweld experimental results of similar (EN 10025 Steel-Grade S295) and dissimilar (D36 shipbuilding steel) materials, which possess a wide range of applications in manufacturing industries. In this work, experimental studies are carried out for optimality of gas tungsten arc welding (GTAW) parameters on a butt joint with single and double V 45° groove angles using Taguchi orthogonal L9 array design. The welding is carried out using the back hand technique, and the filler rod is taken as ER303L to obtain finer welded joints. After the weld, residual stresses, microhardness, and geometrical properties of weld are studied at varied zones, that is, weld zone, HAZ, and base metal to examine the weld efficiency with specific predefined weld parameters. Furthermore, tensile tests are carried out for the weldments with optimal predefined weld parameters, and subsequently, the welded specimens with better tensile strength are discussed in the results. Genetic algorithm and mathematical modelling are opted for selecting the final optimal welding parameters. As per the obtained results of residual stresses, hardness, and tensile tests, dissimilar double V groove butt joint is projected to have more effective weld joint.
Artificial Intelligence and Edge Computing Technology Promote the Design and Optimization of Flipped Classroom Teaching Models for Higher Vocational, Ideological, and Political Courses
Authors: Zhang Lu , Wei Pingping , Zhang Yawei , Wang Na
Published: April 2022

Technology has made life simpler for every human being, irrespective of educational qualifications and sector of work. The education sector in the current modern era is revolutionized by technology. Teaching and understanding theoretical subjects like ideological and pedagogical education (IaPE) has become simple with technologies like artificial intelligence (AI), edge computing (EC), and flipped classrooms. These are unique technologies in the education sector to make classroom learning more manageable by creating concepts in digitization and visualization with audiovisual technologies. In recent research, many authors have proposed models for IaPE through ideological and pedagogical teaching (IaPT) for different courses in vocational colleges and universities. Some researchers have designed a hybrid model with IaPT and analyzed the results as an extension to this teaching method. This research work introduced AI and EC technologies to the flipped classroom to promote higher vocational education in colleges and universities for IaPE. With digitization and visualization in course material preparation, AI aids in an interactive classroom study. On the other hand, EC aids in the easy storage and accessing of the resources prepared through AI. The analysis work is performed on the dataset from the unique client identifier (UCI) repository by proposing a novel optimization algorithm for flipped classrooms.
A Novel Encoder-Decoder Model for Multivariate Time Series Forecasting
Authors: Zhang Huihui , Li Shicheng , Chen Yu , Dai Jiangyan , Yi Yugen
Published: April 2022

The time series is a kind of complex structure data, which contains some special characteristics such as high dimension, dynamic, and high noise. Moreover, multivariate time series (MTS) has become a crucial study in data mining. The MTS utilizes the historical data to forecast its variation trend and has turned into one of the hotspots. In the era of rapid information development and big data, accurate prediction of MTS has attracted much attention. In this paper, a novel deep learning architecture based on the encoder-decoder framework is proposed for MTS forecasting. In this architecture, firstly, the gated recurrent unit (GRU) is taken as the main unit structure of both the procedures in encoding and decoding to extract the useful successive feature information. Then, different from the existing models, the attention mechanism (AM) is introduced to exploit the importance of different historical data for reconstruction at the decoding stage. Meanwhile, feature reuse is realized by skip connections based on the residual network for alleviating the influence of previous features on data reconstruction. Finally, in order to enhance the performance and the discriminative ability of the new MTS, the convolutional structure and fully connected module are established. Furthermore, to better validate the effectiveness of MTS forecasting, extensive experiments are executed on two different types of MTS such as stock data and shared bicycle data, respectively. The experimental results adequately demonstrate the effectiveness and the feasibility of the proposed method.
Efficient Johnson-SB Mixture Model for Segmentation of CT Liver Image
Authors: Dun Yueqin , Kong Yu
Published: April 2022

To overcome the problem that the traditional Gaussian mixture model (GMM) cannot well describe the skewness distribution of the gray-level histogram of a liver CT slice, we propose a novel segmentation method for liver CT images by introducing the Johnson-SB mixture model (JSBMM). The Johnson-SB model not only has a flexible asymmetrical distribution but also covers a variety of other distributions as well. In this article, the parameter optimization formulas for JSBMM were derived by employing the expectation-maximization (EM) algorithm and maximum likelihood. The implementation process of the JSBMM-based segmentation algorithm is provided in detail. To make better use of the skewness of Johnson-SB and improve the segmentation accuracy, we devise an idea to divide the histogram into two parts and calculate the segmentation threshold for each part, respectively, which is called JSBMM-TDH. By analyzing and comparing the segmentation thresholds with different cluster numbers, it is illustrated that the segmentation threshold of JSBMM-TDH will tend to be stable with the increasing of cluster number, while that of GMM is sensitive to different cluster numbers. The proposed JSBMM-TDH is applied to segment four randomly obtained abdominal CT image sequences, and the segmentation results and robustness have been compared between JSBMM-TDH and GMM. It is verified that JSBMM-TDH has preferable segmentation results and better robustness than GMM for the segmentation of liver CT images.
Fixator-Assisted Nailing for Femur Neck Fracture Nonunion: A Case Series Study
Authors: Hashem Majdi , Al-Tuwaijri Mohammad S.
Published: April 2022

Background. Femoral neck fractures in young adults tend to be a result of high-energy trauma with a common pattern of Pauwels type III fracture, and they require timely and meticulous diagnosis and management. The objective of this study was to assess the clinical and radiological outcomes of the fixator-assisted nailing technique for managing femur neck fracture nonunion. Methods. This was a case series study of 16 patients with nonunion femoral neck fractures treated via a fixator-assisted nailing technique. Our inclusion criteria comprised the inclusion of any patient between the ages of 14 and 60 years old with a neglected neck of femur fracture or nonunion of the femur neck. In addition, we only included patients without further posttreatment trauma and without known metabolic diseases. The conditions that were excluded from this study included hip joints with preexisting osteoarthritis, radiographic evidence of avascular necrosis of the femoral head, and associated ipsilateral acetabulum fracture or fracture-dislocation. The fracture characteristics that were selected for the fixator-assisted nailing (FAN) technique were clear signs of pseudoarthrosis (such as sclerosis, clear fracture line defects, and failure of implants), in addition to evidence of varus malalignment. All fractures were Pauwels type III. Radiographs of the pelvis with both hips and a posteroanterior (PA) view of the injured hip were taken. Full weight bearing was allowed in all the patients from the first day postoperatively. Physical therapy was started for pain reduction modalities, stretching, and abductor strengthening. Results. Union of the femur neck fracture and osteotomy site was achieved in all patients. An excellent functional status after four months of follow-up was found based on a modified Harris hip score questionnaire. At follow-up, no patient was suffering from pain or flexion contracture. Preoperative limb length discrepancy (LLD) (cm) was 1.8 ± 0.8 cm and postoperative was 0 ± 0.1 cm,

p
<
0.001

. Preoperative neck-shaft angle (NSA) (o) was 85.6 ± 4.4 and postoperative was 126.9 ± 2.5,

p
<
0.001

. Preoperative Pauwels angle (o) was an average of 50.4 ± 5.9 and postoperative was 31.3 ± 2.5,

p
<
0.001

. Conclusion. Our study indicates that FAN has a high success rate in young patients with nonunited femoral neck fractures.
Broadband Multipolarized Reconfigurable Unit Cell for Reflectarray Antennas with One Bit Control
Authors: Cuong Hoang Dang , Le Minh Thuy , Do Trong Toan , Dinh Nguyen Quoc
Published: April 2022

A broadband and multipolarized fully reconfigurable unit cell is designed and fabricated in this paper. The unit cell uses 4 diodes to create a phase shifter with single-bit control. It exhibits an excellent bandwidth of 40% for both dual linear and circular polarizations in the X and Ku bands using the structure of 4 patches, a proper PIN diode placement, and a DC bias. The reflection coefficients of the cross polarizations are less than –50 dB, ensuring high isolation between the two polarizations. The experiment results show an agreement with the simulation results.
The Planning and Construction Path of Innovative and Intelligent Park Cities Based on Big Data Technology
Authors: Hong Tao , Li Lulu , Wang Bing
Published: April 2022

By analyzing the historical background of the times and summarizing the current situation of urban development research at home and abroad, we find that there is a lack of theoretical and practical research related to intelligent park cities. Therefore, this paper first starts with the connotation of park city theory, focuses on the improvement of planning methods, and studies the application paths of big data technology in the planning and construction of park cities. Taking Jinzhai Country as the research object, this paper further illustrates the applicability of this research method at the macrolevel. In the context of the park city, we analyze the problems of the current status of city construction in general and explore the path of “planning concept first, big data-assisted design” for innovative and intelligent city construction. According to the study, the overlook corridor control has an impact on the building height. In terms of landscape protection, overlook system simulation is the other key factor. In addition, the analytic hierarchy process is the basis for development intensity control. The results show that big data technology can assist in the landscape conservation, morphology formation, and efficient operation of Jinzhai Country Park City. Our aim is to achieve the protection and utilization of its ecological environment and natural resources and thus to comprehensively coordinate the multidimensional urban spaces and build a park city model. As an urban development model that meets the requirements of being “people-oriented, efficient, green, and aesthetic” in the new stage, park cities need to be faced by researchers in order to further realize the overall city goal and vision for the whole society to be smart. It also provides relevant design ideas and methods for the planning and construction of park cities in other similar cities or regions.
The Relationship between Insomnia and Internal Carotid Artery Stenosis and Cognitive Dysfunction by Magnetic Sensitivity Weighted Imaging Based on Wireless Network Communication
Authors: Li Dan , Li Na , Chen Xi
Published: April 2022

The paper analyzes the detection of insomnia and carotid artery stenosis by magnetic sensitivity weighted imaging (SWI) based on radio communication and its relationship with cognitive dysfunction. A total of 148 patients with carotid artery stenosis and insomnia admitted to our hospital from January 2020 to June 2021 are selected. According to different detection methods, wireless communication combined with SWI group and conventional group are established respectively, with 74 cases in each group. The conventional group applies CT angiography (CTA) is in line with the intervention mode of patients complaining of sleep at night. In the wireless communication combined with SWI group, the sleep monitoring system of wireless communication combined with SWI detection method is used to observe the imaging detection rate, insomnia detection rate and diagnostic efficiency of the two groups. The differences of PSG index parameters, sleep quality (PSQI) score and cognitive function (MoCA) score of patients with different disease degrees are compared. Pearson correlation coefficient is used to analyze the correlation between PSQI score and MoCA score. SWI sequence scan based on wireless network communication has high efficiency in the diagnosis of carotid artery stenosis, and the sleep status of patients can be better understood by real-time monitoring of patients, which is of great significance for the follow-up development of effective diagnosis and treatment plans and recovery of patients’ cognitive function, and worthy of clinical application.
Implementing Critical Machine Learning (ML) Approaches for Generating Robust Discriminative Neuroimaging Representations Using Structural Equation Model (SEM)
Authors: Baker Mohammed Rashad , Padmaja D. Lakshmi , Puviarasi R. , Mann Suman , Panduro-Ramirez Jeidy , Tiwari Mohit , Samori Issah Abubakari
Published: April 2022

Critical ML or CML is a critical approach development of the standard ML (SML) procedure. Conventional ML (ML) is being used in radiology departments where complex neuroimages are discriminated using ML technology. Radiologists and researchers found that sole decision by the ML algorithms is not accurate enough to implement the treatment procedure. Thus, an intelligent decision is required further by the radiologists after evaluating the ML outcomes. The current research is based on the critical ML, where radiologists’ critical thinking ability, IQ (intelligence quotient), and experience in radiology have been examined to understand how these factors affect the accuracy of neuroimaging discrimination. A primary quantitative survey has been carried out, and the data were analysed in IBM SPSS. The results showed that experience in works has a positive impact on neuroimaging discrimination accuracy. IQ and trained ML are also responsible for improving the accuracy as well. Thus, radiologists with more experience in that field are able to improve the discriminative and diagnostic capability of CML.
Shaking Table Test of a Full‐Scale RC Frame Structure with an Indoor Gas Piping System
Authors: Sun Dezhang , Guo Endong , Wu Houli , Liu Zhibin , Mao Chenxi , Zhang Haoyu , Sun Xun
Published: April 2022

To investigate the seismic behavior of a two‐story RC frame structure with an indoor gas piping system, a shaking table test was performed and the data obtained from the shaking table test were analyzed in this paper. The detailing of the structural elements was compliant with the Chinese seismic design code, whereas minor modifications were applied to the pipe materials and joint arrangements. In the test, three kinds of pipe materials (galvanized steel, thin‐walled stainless steel, and polyethylene) combined with three types of joint arrangements were selected. The filling materials of the joint were epoxy resin, batched jute, and asbestos cement. A series of full‐scale shake table tests were performed by gradually increasing the three ground motions for reaching to the near collapse limit state. The dynamic characteristics and the responses of the model were investigated via analyzing shaking table test data and the observed damage. The test results also indicated that different joint arrangements had a different impact on the dynamic response of the pipes when subjected to strong ground motions. The peak acceleration of metal pipes with a rigid joint was higher than that of flexible ones, and the peak acceleration of plastic pipes with flexible joint connection was higher than that of rigid ones.
Vehicle Detection Algorithm Based on Embedded Video Image Processing in the Background of Information Technology
Authors: Liang Rui , Ji Gaoqing
Published: April 2022

As the main means of transportation for urban residents, the number of motor vehicles is increasing year by year. With the continuous development of society and the gradual improvement of people’s quality of life, automobiles have gradually become an indispensable means of transportation in people’s lives, resulting in increased traffic flow. However, the old traffic system is still unable to cope with the rapid growth of traffic pressure, and traffic congestion and various accidents occur frequently, which is a huge test for the contemporary intelligent traffic system. With the gradual development of society, more and more researchers are devoted to intelligent transportation systems, which make the development of target detection technology based on video image processing more and more rapid. The primary problem in embedding digital video in applications is that the complexity of video encoding and decoding far exceeds that of simple image and audio compression and decompression. Digital video can take various forms and formats. Developers need to support complex configurations and various aspects, such as different resolutions/display sizes, different bit rates, real-time issues, and even the reliability of the video source. Intelligent transportation achieved a lot of results. However, there are still some deficiencies in precision and robustness. At the same time, the improvement of video image processing technology gives us a new idea. To further improve the intelligent traffic system, provide accurate data information for all departments, and improve the traffic situation, this study, based on video image processing technology, combined with the three-frame difference algorithm, calculates and studies the data of illegal parking at a certain intersection. The calculated false detection rates for Y2 are 1.1%, 0.9%, and 2.4%, and the leakage rates for Y1 are 2.4%, 1.9%, and 4.7%, respectively. This shows that the algorithm has high accuracy for vehicle parking detection data and can collect information quickly and effectively. Applying the algorithm to the detection of other vehicles can provide efficient services for relevant traffic departments and public security departments and relieve traffic pressure. The image processing technology is a process of analyzing and processing images through certain computer technology to achieve the desired results. The scheme in the article realizes background extraction, image filtering, image binarization, morphological transformation, vehicle detection and segmentation, shadow detection, etc.
Fault Diagnosis Method for Wind Power Equipment Based on Hidden Markov Model
Authors: Zhao Qun
Published: April 2022

The aging of mechanical equipment brings a lot of inconvenience to its application. Therefore, research on fault diagnosis technology of mechanical equipment is of great significance for maintaining equipment safety, improving production efficiency and reliability. Bearings and gears are one of the key components of mechanical equipment, and their working conditions seriously affect the changes in equipment performance. Therefore, the fault diagnosis and performance degradation assessment of bearings and gears have always been the research focus of equipment fault diagnosis. This paper proposes a multichannel information fusion method based on the coupled hidden Markov model, discusses the application of the coupled hidden Markov model in bearing fault diagnosis and performance degradation assessment, and studies the multichannel information fusion method based on the coupled hidden Markov model. Channel monitoring data performance degradation evaluation modeling and performance index calculation method are used, and the calculation method of adaptive alarm limit is given by using the performance index. Finally, the natural failure test data and accelerated fatigue test data of gears and rolling bearings are used to analyze and verify the effectiveness of the coupled hidden Markov model for evaluating the performance degradation of complete and incomplete data. The results prove that the selected performance indicators can be quantified, reflecting the degree of bearing performance degradation.
The Handover and Performance Analysis of LTE Network with Traditional and SDN Approaches
Authors: Emran Muhammad , Thayananthan Vijey , Umair Muhammad , Kotuliak Ivan , Qureshi Muhammad Shuaib , Qureshi Muhammad Bilal
Published: April 2022

The mobility of user equipment (UE) in cellular network is a challenging issue in terms of its management. Current traditional handover in Long-Term Evolution (LTE) network is managed by evolved Node B or eNodeB (eNB) which is a decentralized solution. In contrast to existing technology, software defined network (SDN) has the capability of serving the packets of the switching equipment without involving the SDN controller except for the first one. We have proposed an SDN-based centralized solution for handover management in LTE network. Based on our solution, the handover is being managed by SDN controller which keeps track of the overall network management and dictates the flow entries to the OpenFlow switches in the network. In our testbed, two UEs are connected to two eNBs, and one of the UE performs a handover from one eNB to other eNB. It enhances the performance of the network in terms of reducing the delay while performing the handover and increasing the data rate of the running application. The initial delay will be bit higher due to the initial flow entry absence in the flow tables of the switches; later, the delay will be reduced. It is evident from the results that our approach keeps track of the overall network at centralized controller with improved performance.
Quantitative Scintigraphy Evaluated the Relationship between 131I Therapy and Salivary Glands Function in DTC Patients: A Retrospective Analysis
Authors: Lv Xiaolan , Yin Liang , Wu Weiming , Li Ning , Zhang Ruyi , Li Xue , Jia Qiang , Tan Jian , Wang Peng , Zheng Xiangqian , He Xianghui , Huang Chao , Li Dihua , Wang Yan , Meng Zhaowei
Published: April 2022

Purpose. Quantitative scintigraphy to evaluate salivary gland function changes in patients with differentiated thyroid cancer (DTC) after iodine-131 (131I) treatment. Methods. A total of 458 patients with DTC grouped by sex and age were included. Salivary gland scintigraphy was performed to evaluate salivary gland function before and after 131I treatment. The uptake fraction (UF), uptake index (UI), and excretion fraction (EF) of two pairs of parotid glands and submandibular glands were measured and compared. The Chi-square test was conducted according to function impairment count. Results. Salivary gland function in different age groups and sexes were quite different, especially for women <55 years old, who had decreased UF, UI, and EF of all four glands without basal injury. The secretion or uptake function of some salivary glands with basic function impairment before 131I treatment was increased after iodine treatment. Only a small percentage of males showed reduced functional parameters after several treatments. The most significant difference in the count of impairment for the four salivary glands were the first and third examinations, which was more evident in women. The submandibular gland had the most significant reduction in uptake. Conclusion. Changes in salivary gland function are more common in young females being treated for DTC. Impairment of salivary gland function is correlated with the number of treatments and the cumulative dose of 131I. Some salivary gland functions impaired before 131I treatment were enhanced in the early treatment.
Effect of Chromium Ion on the Strength Characteristics and Damage Law of Red Clay
Authors: Song Yu , Zhang Mingzhi , Li Hui , Yang Yue , Chen Xuejun , Li Jun
Published: April 2022

As heavy metals invade the soil, they will continue to corrode the internal structure of the soil, expand the pores of the internal soil, and destroy the internal skeleton structure of the soil. The shear strength of the soil is reduced and the structure is damaged, causing the building to crack and deform. This research is aimed at analyzing the mechanical strength characteristics and damage discipline of red clay polluted by chromium ions. Taking Guilin red clay as the research object, the chromium pollution concentrations of 0%, 0.01%, 0.05%, and 0.1% contaminated soil were artificially configured indoors to conduct unconsolidated and undrained triaxial tests. The results reveal that chromium ions can destroy the original structure of the red clay. With the increase of chromium ion concentration, the deviatoric stress of red clay decreases. The downward trend is in the form of an exponential function. The deviator stress of red clay contaminated by a low concentration of chromium ions has a significantly decreasing trend. With the increase of the concentration, the deviator stress of red clay tends to decrease. Compared with unpolluted red clay, the contaminated red clay requires less axial pressure to produce the same deformation. The chromium ions in the polluted red clay increase the concentration of ions in the electrical double-layer structure of the soil particles and reduce the stiffness of the soil.
Molecular Correlates of Early Onset of Diabetic Cardiomyopathy: Possible Therapeutic Targets
Authors: Wang Dongjuan , Liu Kun , Zhong Jinyan , Li Xin , Zhang Jie , Wang Gongxin , Li Ni , Li Tianwen , Davis Harvey , El-gaby Ibrahim , Hao Guoliang , Ye Honghua , Li Dan
Published: April 2022

Diabetes mellitus (DM) is associated with mitochondrial dysfunction and oxidative stress that can lead to diabetic cardiomyopathy (DCM), which can often remain undetected until late stages of the disease. However, myocardial injury occurs before the onset of measurable cardiac dysfunction, although its molecular correlates are poorly understood. In this study, we made a DM rat induced by a high-fat diet combined with low and high doses of streptozotocin (STZ) to emulate pre and early DCM. RNA-sequencing analysis of ventricular tissue revealed a differential transcriptome profile and abnormal activation of pathways involved in fatty acid metabolism, oxidative phosphorylation, cardiac structure and function, insulin resistance, calcium signalling, apoptosis, and TNF signalling. Moreover, using high glucose-treated human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM), we recapitulated the cardiac cellular phenotype of DM and identified several molecular correlates that may promote the development of DCM. In conclusion, we have developed an experimental framework to target pathways underlying the progression of DCM.
Usability of Computer-Aided Translation Software Based on Deep Learning Algorithms
Authors: Liu Junjun
Published: April 2022

In recent years, due to the development of computer technology and information technology, web technology has changed the mode of translation at an alarming rate. The rapid development of information technology and globalization has increased the demand for translation, especially technical translation, and the use of computer-assisted translation software can greatly improve the quality and efficiency of translation work. The purpose of this article is that under the premise of continuous advancement in computer technology, computer-assisted translation can effectively improve the translation efficiency of translators and the quality of translated text. This article references the practicality of computer translation software as the benchmark and uses computer-aided translation software based on deep learning as the core. At the same time, it introduces the current popular microservice concept to build an electronic computer-assisted translation software based on microservice architecture. Based on the performance of the system, the high availability and scalability of the system are enhanced, so that the entire system can provide stable and efficient computer-assisted translation services for users. At the same time, the usability test method is used to compare and evaluate two common computer-aided translation software, Trados and Wordfast. By observing, recording, and analyzing user behavior and related data, the five attributes of usability can be learned and memorable. The experiments show that the effect of this study on computer-aided software with the help of deep learning knowledge can produce good results, and the robustness and scalability of the software have been enhanced, increasing the competitiveness of the software itself in translation software.
Dracorhodin Perchlorate Regulates the Expression of Inflammatory Cytokines through the TLR4 Pathway and Improves Skin Wound Healing in Diabetic Rats
Authors: Xiong Zongliang , Huo Mohan , Jia Yongzhen , Zhou Chong , Ma Xianglin , Yin Hang , Jiang Xiaowen , Yu Wenhui
Published: April 2022

Background. Dragon’s blood is a natural medicine with hemostatic and blood-activating effects and is used to promote wound healing. Dracorhodin perchlorate (DP) is a stable form of dracarhod and is used as a substitute for cochinchinenin. DP promotes the proliferation of rat fibroblasts and promotes wound healing in rats. Methods. DP ointment (0.2 mg/mL) was applied to the skin wounds of nondiabetic and diabetic rats, and the skin of the wound was collected. Wound healing rate, H&E staining, Masson staining, TLR4 pathway, related inflammatory factors, nitric oxide synthase, and so forth were detected. Results. DP treatment alleviated the prolonged inflammatory cell infiltration time and the increase in the TLR4 pathway and inflammatory factors caused by diabetes. DP also promoted wound healing by increasing eNOS protein expression and NO content in the later stage of wound healing. Conclusion. DP promotes wound healing in diabetic rats by regulating the TLR4 pathway and related inflammatory factors. Therefore, adjuvant treatment of DP can be developed for diabetic wound healing.
Highly Purified Eicosapentaenoic Acid Alleviates the Inflammatory Response and Oxidative Stress in Macrophages during Atherosclerosis via the miR-1a-3p/sFRP1/Wnt/PCP-JNK Pathway
Authors: Zang Tongtong , Chen Han , Shen Shutong , Xu Fei , Wang Rui , Yin Jia , Chen Xiehui , Guan Min , Shen Li , Pan Haobo , Ge Junbo
Published: April 2022

Highly purified eicosapentaenoic acid (EPA) has shown great effects in the prevention of atherosclerosis. In a murine model, it significantly reduced plaque accumulation, lowered plasma lipid levels, and decreased inflammation levels, which was also observed in vitro. Using microRNA sequencing, we identified differentially expressed microRNAs, among which miR-1a-3p was selected for further validation. Overexpression of miR-1a-3p in RAW264.7 cells worsened lipid accumulation, increased oxidative stress, and exacerbated inflammatory responses whereas its downregulation produced the opposite results. Potential targets of miR-1a-3p were analyzed by prediction tools. Then, secreted frizzled-related protein 1 (sFRP1), an antagonist of the Wnt pathway, was confirmed as the target gene of miR-1a-3p by a dual-luciferase reporter assay. Further research showed that in macrophages, EPA influenced the activation of the Wnt/planar cell polarity-c-Jun N-terminal kinase (Wnt/PCP-JNK) axis, which is consistent with the phenomenon that miR-1a-3p has an impact on this same axis. Collectively, our findings suggest that EPA mitigates inflammatory responses and oxidative responses both in vivo and in vitro by targeting the miR-1a-3p/sFRP1/Wnt/PCP-JNK axis in macrophages, which may explain the cardioprotective role of EPA and promote the application of EPA in clinical practice.
DeepLumina: A Method Based on Deep Features and Luminance Information for Color Texture Classification
Authors: Simon A. Philomina , Uma B. V.
Published: April 2022

Color texture classification is a significant computer vision task to identify and categorize textures that we often observe in natural visual scenes in the real world. Without color and texture, it remains a tedious task to identify and recognize objects in nature. Deep architectures proved to be a better method for recognizing the challenging patterns from texture images. This paper proposes a method, DeepLumina, that uses features from the deep architectures and luminance information with RGB color space for efficient color texture classification. This technique captures convolutional neural network features from the ResNet101 pretrained models and uses luminance information from the luminance (Y) channel of the YIQ color model and performs classification with a support vector machine (SVM). This approach works in the RGB-luminance color domain, exploring the effectiveness of applying luminance information along with the RGB color space. Experimental investigation and analysis during the study show that the proposed method, DeepLumina, got an accuracy of 90.15% for the Flickr Material Dataset (FMD) and 73.63% for the Describable Textures dataset (DTD), which is highly promising. Comparative analysis with other color spaces and pretrained CNN-FC models are also conducted, which throws light into the significance of the work. The method also proved the computational simplicity and obtained results in lesser computation time.
Rhein Inhibits NF-κB Signaling Pathway to Alleviate Inflammatory Response and Oxidative Stress of Rats with Chronic Glomerulonephritis
Authors: Chen Qian , Guo Hai , Hu JuanJuan , Zhao Xiaofeng
Published: April 2022

Objective. To explore the effect and mechanism of rhein on chronic glomerulonephritis (CGN). Method. Twenty-four eight-week-old male SD rats were randomly divided into following 4 groups (6 rats in each group): control group, CGN group, rhein group, and benazepril (Ben) group. And 5 mg/mL of cationization-bovine serum albumin (C-BSA) was mixed with an equal volume of Freund’s incomplete adjuvant for the preparation of 2.5 mg/mL of C-BSA solution. The rat model of CGN was established by injection of C-BSA for six weeks. Calculation of the renal index in rats was conducted. Biochemical detection was performed to measure the level of 24 h urinary protein, blood urea nitrogen (BUN), serum creatinine (SCr), and serum albumin (ALB) of the rats, as well as the level of malondiadehyde (MDA), superoxide (SOD), and glutathione peroxidase (GSH-Px) in the kidney tissue. Hematoxylin and eosin (H&E) staining was utilized to measure histological changes in the kidney of the rats. The level of TNF-α, IL-1β, IL-6, and ICAM-1 in rat kidney tissues was determined by enzyme-linked immunosorbent assay (ELISA). Western blot was applied to check the expression of NF-κB in the nucleus and cytoplasm as well as the expression of IκBα and p-IκBα in rat kidney tissues. Results. Rhein could decline urinary protein, restore blood biochemical parameters, and protect renal tissue in rats with CGN. Besides, rhein could inhibit the activity of the NF-κB signaling pathway in rats with CGN and could alleviate the inflammatory response and oxidative stress level at the same time. Conclusion. Rhein alleviates inflammatory responses and oxidative stress in rats with CGN. It also provides a theoretical basis and data support for the therapeutic drugs for CGN.