bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic Scoring for Translations Based on Language Models
Authors: Wu Diming , Wang Mingke , Li Xiaomin
Published: June 2022

With the development of English education, translation scoring has gradually become a time-consuming and energy-consuming task, and it is difficult to ensure objectivity because of the subjective factors in manual correcting. Due to the similarity between the quality evaluation of responses generated by the dialogue system and the translation results submitted by students, we selected two metrics of dialogue to automatically score the translations, which are applied in a case study. The experiments show that the hybrid scores of two metrics are close to human scores. In conclusion, the method is feasible to apply the evaluation metrics of dialogue systems to translation scoring, and it can provide an improvement idea for the automatic scoring of translations in the future.
[Retracted] Ecological Landscape Design and Evaluation in Public Charging Facilities for Electric Vehicles
Authors: Yu Yang
Published: June 2022

The deterioration of the environment in the 21st century has made environmental issues one of the most severe tests for modern society. With this comes a change in energy structure from high‐carbon to low‐carbon direction, and electric vehicles are gradually developing into the darling of a city with low‐carbon transportation and safe travel. This paper carries out a systematic analysis of landscape design and environmental protection in the development of new energy electric vehicle charging facilities in urban habitat. By categorizing the content and provisions of published domestic and international standards, new requirements for standardization are obtained, including barrier‐free design, electromagnetic radiation, child safety protection, and urban landscape integration. Among them, ecological landscape public charging facilities can enhance the overall quality of urban environment. This paper analyzes the necessity of landscape design in charging facilities, explores the ecological concepts extended by macroscopic landscape design principles and the problems of public charging facilities, and proposes a design and evaluation method of ecologically landscaped public charging facilities based on hierarchical analysis and neural networks. The hierarchical analysis method is introduced to establish a landscape design assessment index system, and then a neural network is introduced to describe the characteristics of electric vehicle charging, and the landscape design assessment learning samples are trained to establish a landscape design assessment model. Finally, a comparison experiment is conducted with other landscape design assessment methods using specific examples, and the results show that the proposed method has more obvious advantages in ecological landscape public charging facility design assessment with high accuracy, faster landscape design assessment, charging efficiency, and environmental protection.
A Maturity Framework for Zero-Trust Security in Multiaccess Edge Computing
Authors: Ali Belal , Hijjawi Simsam , Campbell Leith H. , Gregory Mark A. , Li Shuo
Published: June 2022

Multiaccess Edge Computing (MEC) has been adopted to provide an environment that supports cloud computing capabilities and IT services at the network edge. The open architecture of cloud computing and network access at the edge provides malicious actors with many attack vectors. The MEC system entities cannot be permanently trusted due to the dynamic and shareable nature of MEC deployments. This paper presents a classification of MEC entities that can be used to define security controls based on the Zero-Trust Security approach. The security controls are organised into a maturity framework that can be used to guide the systematic development of trust and security in an MEC environment. In this framework, a Minimum Viable Security posture defines the first operational step towards full implementation of Zero-Trust Security in an MEC environment.
Gpx3 and Egr1 Are Involved in Regulating the Differentiation Fate of Cardiac Fibroblasts under Pressure Overload
Authors: Li Guoxing , Qin Yuhong , Cheng Zhe , Cheng Xiaocheng , Wang Ruiyu , Luo Xuexiu , Zhao Yipin , Zhang Dongying , Li Gang
Published: June 2022

Objectives. Although myocardial fibrosis is a common pathophysiological process associated with many heart diseases, the molecular mechanisms regulating the development of fibrosis have not been fully determined. Recently, single cell RNA sequencing (scRNA-seq) analysis has been used to examine cellular fate and function during cellular differentiation and has contributed to elucidating the mechanisms of various diseases. The main purpose of this study was to characterize the fate of cardiac fibroblasts (CFs) and the dynamic gene expression patterns in a model of cardiac pressure overload using scRNA-seq analysis. Methods. The public scRNA-seq dataset of the transverse aortic coarctation (TAC) model in mice was downloaded from the GEO database, GSE155882. First, we performed quality control, dimensionality reduction, clustering, and annotation of the data through the Seurat R package (v4.0.5). Then, we constructed the pseudotime trajectory of cell development and identified key regulatory genes using the Monocle R package (v2.22.0). Different cell fates and groups were fully characterized by Gene Set Enrichment Analysis (GSEA) analysis and Transcription factor (TF) activity analysis. Finally, we used Cytoscape (3.9.1) to extensively examine the gene regulatory network related to cell fate. Results. Pseudotime analysis showed that CFs differentiated into two distinct cell fates, one of which produced activated myofibroblasts, and the other which produced protective cells that were associated with reduced fibrosis levels, increased antioxidative stress responses, and the ability to promote angiogenesis. In the TAC model, activated CFs were significantly upregulated, while protective cells were downregulated. Treatment with the bromodomain inhibitor JQ1 reversed this change and improved fibrosis. Analysis of dynamic gene expression revealed that Gpx3 was significantly upregulated during cell differentiation into protective cells. Gpx3 expression was affected by JQ1 treatment. Furthermore, Gpx3 expression levels were negatively correlated with the different levels of fibrosis observed in the various treatment groups. Finally, we found that transcription factors Jun, Fos, Atf3, and Egr1 were upregulated in protective cells, especially Egr1 was predicted to be involved in the regulation of genes related to antioxidant stress and angiogenesis, suggesting a role in promoting differentiation into this cell phenotype. Conclusions. The scRNA-seq analysis was used to characterize the dynamic changes associated with fibroblast differentiation and identified Gpx3 as a factor that might be involved in the regulation of myocardial fibrosis under cardiac pressure overload. These findings will help to further understanding of the mechanism of fibrosis and provide potential intervention targets.
Analysis of the Intelligent Tourism Route Planning Scheme Based on the Cluster Analysis Algorithm
Authors: Lou Na
Published: June 2022

In view of the problems of the traditional cluster analysis algorithm such as strong dependence on the initial cluster center, the traditional k-means cluster analysis algorithm is improved and the experiment proves that the improved algorithm has a better clustering effect; in view of the problems of the traditional tourism route planning, the improved k-means cluster analysis algorithm is applied to the intelligent tourism route planning scheme design and an intelligent tourism planning scheme based on the cluster analysis algorithm is proposed; the tourists’ preference metric is fully considered, and the experimental results show that the scheme has certain reasonableness and reference value.
Screening of Potential Breast Cancer Inhibitors through Molecular Docking and Molecular Dynamics Simulation
Authors: Pandi Sangavi , Kulanthaivel Langeswaran , Subbaraj Gowtham Kumar , Rajaram Sangeetha , Subramanian Senthilkumar
Published: June 2022

Cyclooxygenase‐2 (COX‐2) is a key enzyme involved in overexpression in several human cancerous diseases including breast cancer. By performing efficient virtual screening in a series of active molecules or compounds from the Maybridge, NCI (National Cancer Institute), and Enamine databases, potential identification of COX‐2 inhibitors could lead to new prognostic strategies in the treatment of breast cancer. Based on a 50% structural similitude, compounds were chosen as the inductive model of COX‐2 inhibitions from these databases. Selected compounds were filtered and tested with Lipinski’s rule of five followed by absorption, distribution, metabolism, and excretion (ADME) properties. Subsequently, molecular docking was performed to achieve accuracy in screening and also to find an interactive mechanism between hit compounds with their respective binding sites. Simultaneously, molecular simulations of top‐scored compounds were selected and coded such as Maybridge_55417, NCI_30552, and Enamine_62410. Chosen compounds were analyzed and interpreted with COX‐2 affinity. Results endorsed that hydrophobic affinity and optimum hydrogen bonds were the forces driven in the interactive mechanism of in silico hits compounds with COX‐2 and can be used as efficient alternative therapeutic agents targeting deleterious breast cancer. With these in silico findings, compounds identified may prevent the action of the COX‐2 enzyme and thereby diminish the incidence of breast cancer.
An Improved Convolutional Neural Network-Based Scene Image Recognition Method
Authors: Wang Pinhe , Qiao Jianzhong , Liu Nannan
Published: June 2022

To solve the problems existing in the research of scene recognition, this paper studies a new convolutional neural network target detection model to achieve a better balance between the accuracy and speed of high-speed scene image recognition. First, aiming at the problem that the image is easy to be disturbed by impurities and poor quality in fine-grained image recognition, a preprocessing method based on the Canny edge detection is designed and the Canny operator is introduced to process the gray image. Second, the L2 regularization algorithm is used to optimize the basic network framework of the convolutional neural network, enhance the stability of the model in a complex environment, improve the generalization ability of the model, and improve the recognition accuracy of the algorithm to a certain extent. Finally, by collecting the campus environment datasets under different environmental conditions, the location recognition experiment and heat map visualization experiment are carried out. Experiments show that compared with the basic convolution neural network algorithm, the algorithm has better recognition performance and good generalization ability. The research of this study realizes the effective combination of multiframe convolution neural network and batch normalization algorithm and has a good practical effect on scene image recognition.
Translation and Initial Validation of the Chinese (Cantonese) Brief 2‐Way Social Support Scale for Use in People with Chronic Stroke
Authors: Liu Tai Wa , Ng Shamay S. M. , Tsoh Joshua , Chen Peiming , Xu Richard H. , Wong Thomson W. L. , Tse Mimi M. Y.
Published: June 2022

Background. Social support is important for stroke rehabilitation. Conventionally, social support is evaluated from the level of support received. However, the bidirectional support hypothesis postulated that self‐perceived social support is optimized if individuals provide and receive social support in a balanced manner. The Brief 2‐Way Social Support Scale (Brief 2‐Way SSS) is a social support instrument measuring the reciprocity of receiving and giving emotional and instrumental social support. Objective. (1) To translate and culturally adapt the English version of the Brief 2‐Way SSS into Chinese (Cantonese) (Brief 2‐Way SSS‐C), (2) to report the results of validation of the Brief 2‐Way SSS‐C, and (3) to investigate the level of social support in people with stroke in Hong Kong. Methods. The Brief 2‐Way SSS‐C was produced following the standard forward‐backward translation model. People with stroke (n = 109) and age‐matched controls (n = 53) were recruited through a university‐affiliated neurorehabilitation laboratory. Results. The Brief 2‐Way SSS‐C demonstrated excellent content validity, acceptable to good internal consistency (Cronbach’s alpha of 0.74–0.88), and good test‐retest reliability (intraclass correlation coefficient of 0.76–0.81). There were no ceiling or floor effects, and the MDC95 across all subscales was 4. The Brief 2‐Way SSS‐C subscales had significant correlations with various health‐related outcome measures. People with stroke had a lower level of social support than the age‐matched healthy controls. Conclusions. The Brief 2‐Way SSS‐C is a culturally relevant, reliable, and valid outcome measure for the level of social support in community‐dwelling people with stroke.
Evaluation Algorithm of Fencing Athletes’ Strength Distribution Characteristics Based on Gait Tracking
Authors: Fei Zhengwei , Zhao Chuanjie
Published: June 2022

Human motion capturing techniques are used in various fields such as surveillance, healthcare, and sports to analyze, understand, and synthesize kinematic and kinetic data. Among the mentioned application areas of motion recognition techniques, sport is an essential sector in which it is extensively used. The dynamic and kinematic performance of the three joints of the lower limbs in lunge movement is the main factor affecting the lunge speed of the fencers. Fencing is an open-skill combat sport in which complicated body movements and effective game techniques are required. The extremely nonlinear human movements, muscle dynamics, and foot-ground contact make athletic gait analysis a difficult topic in biomechanics. At present, there are no comprehensive and systematic research results on the impact of the dynamic and kinematic performance of the ankle, knee, and hip joints of lower limbs on the lunge speed. Based on the gait tracking algorithm, this study compares and analyzes the dynamic and kinematic performance of lower limbs ankle, knee, and hip joints in the lunge of fencing athletes at different levels and discusses the influence of the dynamic and kinematic performance of the three lower limbs joints of fencing athletes on the lunge speed. This study mainly focuses on, (1) exploring the dynamic and kinematic influencing factors of the peak horizontal speed of the center of gravity of fencing athletes’ lunge movement, (2) to verify whether there is a difference in the lunge speed of fencing athletes at different levels and analyzes the reasons for the differences, (3) to explore the ankle, knee, and the differences of hip joint dynamics and kinematics, the causes of the differences, and to analyze the influence of the differences on the lunge speed. In this paper, we have used a gait tracking algorithm that evaluates the fencing athletes’ strength distribution characteristics. With the help of gait recognition algorithm based on artificial intelligence (AI) technology, the movement posture and gait of fencers can be recognized automatically in real time which is helpful to realize the automatic evaluation of power distribution. The experimental results prove the significance of the proposed model.
Long-Term Stability of Hydromorphone in Human Plasma Frozen at −20°C for Three Years Quantified by LC-MS/MS
Authors: Wehrfritz Andreas , Schmidt Stefanie , Ihmsen Harald , Schüttler Jürgen , Jeleazcov Christian
Published: June 2022

The long-term stability of drugs under normal laboratory storage conditions (−20°C) for years is important for research purposes, clinical re-evaluation, and also for forensic toxicology. To evaluate the stability of the analgesic opioid hydromorphone, 44 human frozen plasma samples of a former clinical trial were reanalyzed after at least three years. Blood samples were disposed using solid-phase extraction with an additional substitution of stable isotope labelled hydromorphone as an internal standard. Hydromorphone concentrations were determined by ultra-performance liquid chromatography (UPLC) with gradient elution, followed by tandem mass spectrometry with electrospray ionization. Calibration curves demonstrated linearity of the assay in the concentration range of 0.3–20 ng/mL hydromorphone. The limit of detection of the hydromorphone plasma concentration was 0.001 ng/mL, and the lower limit of quantification was 0.3 ng/mL. Intra- and interassay errors did not exceed 16%. The percentage deviation of the measured hydromorphone plasma concentrations between the reanalysis and the first analysis was −1.07% ± 14.8% (mean ± SD). These results demonstrate that hydromorphone concentration in human plasma was stable when the samples were frozen at −20°C over three years. This finding is of value for re-evaluations or delayed analyses for research purposes and in pharmacokinetic studies, such as in forensic medicine.
Occult Hepatitis B Infection among Hemodialysis Patients in Tabriz, Northwest of Iran: Prevalence and Mutations within the S Region
Authors: Eslami Narges , Poortahmasebi Vahdat , Sadeghi Javid , Ghotaslou Reza , Niknafs Bahram , Bannazadeh Baghi Hossein , Ahangar Oskouee Mahin
Published: June 2022

Regardless of the extensive screening for the detection of hepatitis B surface antigen (HBsAg), hemodialysis (HD) patients are still severely at the risk of occult hepatitis B virus infection (OBI), especially in developing countries. OBI is defined as the presence of HBV DNA with undetectable HBsAg in the liver and/or Serum. This study aims to determine the prevalence of OBI in HD patients in East Azerbaijan Province, northwest of Iran, and inquire about the mutations in the detected HBsAg. In this cross-sectional descriptive study, ELISA method assessed serum and plasma samples of 118 HBsAg-negative patients undergoing HD treatment for HBV serological markers (HBsAg and Anti-HBc). Specific primers by nested polymerase chain reaction have been utilized to examine HBV DNA; also, direct sequencing of surface genes was carried out to characterize the viral genotypes and S gene mutations. Finally, followed by real-time PCR, the quantity of viral load in OBI-positive patients was determined. A total of 118 HD patients were included (63.6% were male and 36.4% female), with an overall mean age of 60.8 ± 12.8 years old. The prevalence of antihepatitis B core antibody (Anti-HBc) in the study population was 26.3% (31/118). Five patients (4.2%) were positive for HBV DNA and labeled OBI-positive; their plasma HBV-DNA load was less than 100 IU/ml. Following the phylogenetic analysis, the samples with OBI roughly belonged to genotype D, subtype ayw2 and only two had mutations within the S ’gene’s major hydrophilic region (MHR), including T123I, C124F, and P127T. This study reports the prevalence of OBI in the HBsAg-negative HD patients being at a rate of 4.2%, which can be a clinically vital consideration in this region. HBV serologic screening approaches need to be renewed to cover nucleic acid testing in the setting of hemodialysis and all the other high-risk groups associated with it (i.e., blood and organ donors).
Dopamine Suppresses Osteogenic Differentiation of Rat Bone Marrow-Derived Mesenchymal Stem Cells via AKT/GSK-3β/β-Catenin Signaling Pathway
Authors: Kuang Zhili , Chen Zheng , Tu Shaoqin , Mai Zhihui , Chen Lin , Kang Xiaoning , Chen Xiaochuan , Wei Jiaming , Wang Yuxuan , Peng Yun , Ai Hong
Published: June 2022

Nervous system is critically involved in bone homeostasis and osteogenesis. Dopamine, a pivotal neurotransmitter, plays a crucial role in sympathetic regulation, hormone secretion, immune activation, and blood pressure regulation. However, the role of dopamine on osteogenic differentiation of rat bone marrow-derived mesenchymal stem cells (rBMSCs) remains poorly understood. In this study, we firstly investigated the effect of dopamine on the apoptosis, proliferation, and osteogenic differentiation of rBMSCs. Dopamine did not, however, interfere with the apoptosis and proliferation of rBMSCs. Interestingly, dopamine suppressed the osteogenic differentiation of rBMSCs, as characterized by reduced ALP staining, ALP activity, mineralized nodule formation, and the mRNA and protein levels of osteogenesis-related genes (Col1a1, Alp, Runx2, Opn, and Ocn). Furthermore, dopamine inactivated AKT/GSK-3β/β-catenin signaling pathway. Treatment of LiCl (GSK-3β inhibitor) rescued the inhibitory effects of dopamine on osteogenic differentiation of rBMSCs. LY294002 (AKT inhibitor) administration exacerbated the inhibitory effects of dopamine on osteogenic differentiation of rBMSCs. Taken together, these findings indicate that dopamine suppresses osteogenic differentiation of rBMSCs via AKT/GSK-3β/β-catenin signaling pathway. Our study provides new insights into the role of neurotransmitters in bone homeostasis.
UAV Communication Network Modeling and Energy Consumption Optimization Based on Routing Algorithm
Authors: Zhuo Ran , Song Shiqian , Xu Yejun
Published: June 2022

Topological information is provided, and research on the design of routing protocols for UAV self-assembling networks is conducted, in order to enable fleet communication transfer between UAVs and UAVs and enhance their communication transmission rate in the self-assembling network. A new routing protocol is proposed through greedy forwarding and peripheral forwarding of UAV self-assembling network communication data, UAV self-assembling network planarization processing, dynamic adjustment of routing mode based on topological information, and routing protocol decision content generation. The proposed network is described using stochastic geometry theory, with the UAV and building locations modeled as two independently distributed Poisson point processes and the building shape modeled as a rectangular body with height obeying the Rayleigh distribution. An estimated equation for typical user coverage is produced using this model. The simulation results show that the approximate expression matches with the simulation results with reduced computational complexity, which verifies the validity of the approximate analysis. By comparing it with the clustering-based routing protocol, it is concluded that the new routing protocol conditions for UAV self-assembly network can realize the communication transmission between UAVs and drones and further promote their communication transmission rate.
Application of Internet of Things Architecture in Intelligent Classroom Teaching Analysis in Colleges and Universities
Authors: Du Hongna
Published: June 2022

Smart classroom is based on information technology, and its operation, upgrading, and development need technical support. At present, most of the smart classroom teaching adopts traditional architecture, highlighting the characteristics of disciplines, insufficient data processing, and narrow application fields. Based on this, this paper studies and analyzes the application of Internet of things architecture in college smart classroom teaching analysis. Based on the simple analysis of the development of intelligent algorithms and smart classrooms of the Internet of things, this paper constructs a smart classroom system based on the architecture of the Internet of things, transfers it to information-based teaching, introduces an intelligent service platform, and uses intelligent algorithms to mine and cluster data. The core algorithm is improved based on K-means algorithm and grid algorithm to improve the pertinence and effectiveness of the algorithm. Through the simulation results, the improved clustering analysis algorithm can shorten the running time and improve the clustering effect. At the same time, the application test results of the algorithm also show the superiority of the clustering results, which can provide more strategies for later teaching.
HE-DFNETS: A Novel Hybrid Deep Learning Architecture for the Prediction of Potential Fishing Zone Areas in Indian Ocean Using Remote Sensing Images
Authors: Sivasankari M. , Anandan R. , Chamato Fekadu Ashine
Published: June 2022

The Indian subcontinent is known for its larger coastline spanning, over 8100 km and is considered the habitat for many millions of people. The livelihood of their habitat is purely dependent upon the fishing activities. Often, the search for fish requires more time for catching and more resources, thus increasing the operational cost leading to low profitability. With the advent of artificial intelligence algorithms, designing intelligent algorithms for an effective prediction of fishing areas has reached new heights in terms of high accuracy (Acy) and less time. But still, predicting the location of potential fishing zones (PFZs) is always a daunting task. To reduce these issues, this work presented the novel hybrid prediction architecture of PFZs using remote sensing images. The proposed architecture integrates the deep convolutional layers and flitter bat optimized long short-term memory (FB-LSTM)-based recurrent neural networks (RNN). These convolutional layers are utilized to remove the various color features such as chlorophyll, sea surface temperature (SST), and GPS location from the satellite images, and FB-LTSM is utilized to predict the potential locations for fishing. The extensive experimentations are carried out utilizing the satellite data from Indian National Centre for Ocean Information Services (INCOIS) and implemented using TensorFlow 1.18 with Keras API. The performance metrics such as prediction Acy, precision (Pscn), recall (Rcl) or sensitivity (Sty), specificity (Sfy), and F1-score and compared with other existing intelligent learning models. From our observations, the proposed architecture (99% prediction Acy) has outperformed the other existing algorithms and finds its best place in designing an intelligent system for better predicting of PFZs.
[Retracted] Application of Intravenous Anesthesia in Laparoscopic Hiatal Hernia Repair of Children
Authors: Zhu Xueli , Yang Haiyang , Qu Meimin , Wang Jianshe , Fei Jian , Shi Linyu
Published: June 2022

In order to solve the stress problem in laparoscopic hiatal hernia repair of children, improve surgical safety, and reduce surgical risk, this study compared the perioperative changes of epinephrine, norepinephrine, IL‐6, IL‐10, and hemodynamics in children undergoing laparoscopic surgery under intravenous general anesthesia and general anesthesia combined with an epidural block. In this study, 40 children aged 1–3 years who planned to undergo laparoscopic ortopexy and those who planned to undergo laparoscopic high ligation of hernia sac, aged 23.84 1.6 months and weighed 14.9 1.1 kg, were randomly divided into general anesthesia combined with the epidural block group (group A) and a total intravenous anesthesia group (group B), with 20 subjects in each group. The results are as follows: There were no differences in age, gender, body weight, anesthesia time, pneumoperitoneum duration, and functional time between the two groups. Cytokines: Compared with T0, the levels of IL‐6 in T2, T3, T4, and T5 groups were significantly increased (P < 0.01). IL‐10 levels: T2, T3, T4, and T5 groups were further increased, and the difference was statistically significant compared with T0 (P < 0.01). There was no difference between groups (P > 0.05). The recovery time in group B was shorter than that in group A (P < 0.01), and the total amount of propofol and fentanyl in group B was less than that in group A (P < 0.01). Through research on intravenous anesthesia treatment, it has been proved that total intravenous anesthesia can relieve perioperative pressure, reduce intravenous injection, and reduce the recovery time of children. However, its effect on cytokines is not obvious, so intravenous anesthesia is the most appropriate anesthesia mode in laparoscopic hiatal hernia repair surgery, which has practical significance.
[Retracted] Mechanism of Sevoflurane Anesthesia under Hypothermic Cardiopulmonary Bypass on Postoperative Atrial Fibrillation Rhythm in Patients Undergoing Mitral Valve Replacement
Authors: Che Hao , Lv Yufang , Yao Fang , Zhao Fang , Zhao Liyun
Published: June 2022

Objective. It was to investigate the mechanism of atrial fibrillation after mitral valve replacement under extracorporeal circulation in patients with rheumatic heart disease under sevoflurane anesthesia maintenance and to provide scientific and effective basis for clinical treatment. Methods. Forty patients with rheumatic heart disease who underwent mitral valve replacement were randomly rolled into group I (sinus rhythm of propofol anesthesia, n = 10), group II (atrial fibrillation rhythm of propofol anesthesia, n = 10), group III (sinus rhythm of sevoflurane anesthesia, n = 10), and group IV (atrial fibrillation rhythm of sevoflurane anesthesia, n = 10). Inflammatory factors, free tissue of right atrium, and incidence of postoperative atrial fibrillation were compared among all groups. Results. (i) The serum levels of NT‐proBNP, CRP, sST‐2, IL‐6, TNF‐α, and TGF‐β1 in group II were higher than those in group I, group III, and group IV, and the indexes in group III were higher than those in group IV (P < 0.05). (ii) The relative expression levels of PLB, CaMK II, Bax, and TP53 in the free tissue of right atrium in group II were higher than those in group I, III, and IV, and the index levels in group IV were higher than those in group III (P < 0.05). (iii) The incidence of postoperative atrial fibrillation in group III (0.00%) was significantly lower than that in group I (30%), group II (50%), and group IV (40.0%), and group II (50%) was the highest (P < 0.05). Conclusion. The maintenance of sevoflurane anesthesia can improve the inflammatory response and myocardial tissue autophagy in patients with sinus rhythm and atrial fibrillation rhythm and can reduce the incidence of postoperative atrial fibrillation in patients.
Structure of Needle Highlights Ecological Adaptability and Microevolution of Natural Populations of Cedrus atlantica in Morocco
Authors: El Bakkali Nezha , Bendriss Amraoui Mohammed
Published: June 2022

The study of morphological and anatomical characteristics of leaves is important for assessing the geographical variation of species. The ecological adaptability of forty individuals from four populations of Cedrus atlantica were studied, based on analysis of morphological and anatomical traits. The results of the Spearman nonparametric coefficient of correlation showed that the number of stomatal lines (NLS) and the length of the needle (NL) are negatively correlated to altitude and positively to latitude and precipitation sums, while the width of the needle (NW), the thickness of the cuticle (CT), and the number of needles per rosette (NN/R) were negatively related to temperature. In addition, the sum of precipitation is negatively correlated with NW. The first two principal components account for 58.18% of the variation. According to Tukey’s test and Kruskal–Wallis test, all populations had at least three characters separating them at a statistically significant variation. Moreover, the hierarchical classification led us to the individualization of three main groups. All these results show an adaptation of the structure of the needles of C. atlantica from Morocco to the geographical position and the climatic conditions of the populations.
Millimeter Wave All-Around Antenna Based on Whispering Gallery Mode Dielectric Resonator for IoT-Based Applications
Authors: Kogut Alexander , Annino Giuseppe , El Bakkali Mohamed , Laamara Rachid Ahl , Arora Sandeep Kumar , Naik D. S. Bhupal , Maniraguha Fidele
Published: June 2022

This work is devoted to the study of the emitting properties of azimuthally inhomogeneous segmental dielectric resonators excited by whispering gallery modes. Due to the diffraction of the azimuthal waves on local nonhomogeneities located equidistantly along the azimuthal coordinate, intense electromagnetic radiation is achieved in the azimuthal sector of the angles 0°-360°. A prototype of an all-around emitting antenna based on basis of a segmental dielectric resonator is proposed, and its characteristics in the far zone are studied. It is shown that such an antenna forms a multilobe radiation pattern (72 lobes) in the circle sector of angles. The antenna gain in the lobes at the resonant frequency reaches 12 dB. Antenna optimization is achieved in the proposed method because of the large gain produced by the antenna. It is also analyzed that these types of radiation patterns observed by antennas are well used for the Internet of Things- (IoT-) based applications.
Moving Object Detection in Dynamic Environment via Weighted Low-Rank Structured Sparse RPCA and Kalman Filtering
Authors: Liu Ting
Published: June 2022

As a classical problem for computer vision, moving object detection (MOD) can be efficiently achieved by foreground and background separation. The Robust Principal Component Analysis (RPCA)-based method has been potentially utilized to solve the problem. However, the detection accuracy for RPCA-based method is limited for complex scenes with slow-motion. Besides, it is time consuming for the way to seek for background modeling based on solving a low-rank minimization problem, for which multiple frames of the videos are required as the input. Therefore, a real-time MOD framework (LSRPCA_KF) is proposed for the dynamic background, where a weighted low-rank and structured sparse RPCA algorithm is used to achieve background modeling for history data, while the online MOD is achieved by the background subtraction method and updated by the Kalman filter for every real time frame. Specifically, for the background model, a newly designed weight is incorporated to distinguish the significance of different singular values, and a structured sparse prior is added to penalty the spatial connection property of the moving object. Besides, the weighted low-rank and structured sparse RPCA model is efficiently solved by the Alternating Direction Method of Multipliers (ADMM) optimization algorithm. Experimental results demonstrated that better performance of our method with significantly reduced delay in processing and better detect the moving object has been achieved, especially for the dynamic background.
[Retracted] Efficiency of Nanohydroxyapatite on Repairing Type II Diabetes Dental Implant‐Bone Defect
Authors: Ji Dong , Lu Dapeng
Published: June 2022

The purpose of this study was to see how a nanohydroxyapatite (n‐HA) composite polyamide 66 (PA66) affected the repair of bone defects in diabetics with titanium implants, as well as to develop experimental materials for the creation of the interface between bone tissue and titanium implants. Rabbit bone marrow mesenchymal stem cells (MSCs) were isolated using n‐HA/PA66 composite material, and the effect of coculture with the material on cell proliferation was analyzed after induction of mineralization. Bone defect models of diabetic experimental rabbits and titanium implants were prepared. Normal rabbits with bone defects were used as control (NC group, N = 8). After the diabetic bone defect (DM group, N = 8) and the implantation of n‐HA/PA66 composite material (n‐HA/PA66 group, N = 8), the differences in body weight, blood glucose, scanning electron microscopy of the implant‐bone interface, bone mineral density, new bone trabecular parameters, histomorphology, and biomechanical properties of the implant‐bone interface were compared and analyzed. In vitro test results showed that MSC cell growth could be promoted by mineralization induction, the cell growth condition was good after coculture with n‐HA/PA66, and the proliferation activity of MSCs was not affected by the material. In vivo test results showed that the body weight of the DM group and n‐HA/PA66 group was considerably inferior to that of the NC group, and the blood glucose was dramatically superior to that of the NC group (P < 0.05). However, the body weight of the n‐HA/PA66 group was dramatically superior to that of the DM group (P < 0.05). The bone mineral density, bone volume fraction (BV/TV), bone surface area fraction (BS/BV), bone trabecular thickness (Tb.Th), bone trabecular number (Tb.N), bone trabecular area, and biomechanical properties in the DM group were considerably inferior to those in the NC group and n‐HA/PA66 group (P < 0.05). The trabecular space (Tb.Sp) in the NC group and n‐HA/PA66 group was dramatically superior to that in the NC group (P < 0.05). The bone mineral density, BV/TV, BS/BV, Tb.Th, Tb.N, trabecular area, and biomechanical properties of the n‐HA/PA66 group were dramatically superior to those of the NC group (P < 0.05), while Tb.Sp was considerably inferior to that of the NC group (P < 0.05). These findings showed that the n‐HA/PA66 material had good biocompatibility and minimal cytotoxicity, and that filling the space between the surrounding bone and the titanium implant can enhance bone repair. This research paved the way for future research into the tissue‐engineered bone in the field of oral surgery.
Changes in Body Composition, Basal Metabolic Rate, and Blood Albumin during the First Year following Laparoscopic Mini-Gastric Bypass
Authors: Tizmaghz Adnan , Bahardoust Mansour , Hosseini Mostafa , Pazouki Abdulreza , Alizadeh Otaghvar Hamidreza , Shabestanipour Ghazaal
Published: June 2022

Bariatric surgery is currently the only method that can significantly and continuously reduce weight and improve obesity-related comorbidities in morbidly obese patients. Significant weight loss through bariatric surgery can lead to changes in body composition. This study shows the changes in body composition, basal metabolic rate (BMR), and serum albumin in obese people following bariatric surgery. The study included 880 patients who underwent laparoscopic mini-gastric bypass surgery (LMGBP) between 2016 and 2020. The body mass index (BMI), bioelectrical impedance analysis (BIA), age, gender, blood albumin, WC (waist circumference), HC (hip circumference), BMR, and blood albumin were recorded at 0, 3, 6, and 12 months, postoperatively. The reduction in serum albumin concentration was not consistent with weight loss. Bariatric surgery promotes the breakdown of both fat and lean mass on the arms, torso, and thighs. This size reduction usually aggravates the concomitant skin redundancy in these areas which is a challenge for the plastic surgery team. Interestingly, the rate of lean mass reduction of the arms is faster than that of the torso and thighs. Excessive loss of lean body mass will also lower BMR and lead to subsequent weight gain. Despite the faster loss of proteins and lean mass in somatic areas, internal organs and viscera lose fats faster than proteins. According to this study, visceral proteins are the latest proteins to be affected by weight loss. This finding shows a different metabolic response of viscera comparing to somatic areas.
Xingnao Kaiqiao Acupuncture Method Combined with Temporal Three-Needle in the Treatment of Acute Ischemic Stroke: A Randomized Controlled Trial
Authors: Song Zhongtao , Huang Qingyuan , Guo Yuxia , Song Xiaodong , Zhang Xuan , Xiao Huajun
Published: June 2022

Objective. The objective of this study was to investigate the difference between the clinical effectiveness of two acupuncture methods in the treatment of acute ischemic stroke (AIS) and provide more evidence-based medical evidence of acupuncture’s effectiveness in stroke rehabilitation. Methods. We conducted an outcome assessor-and data analyst-blinded, randomized, and controlled trial. Seventy-two participants were randomly allocated to the observation group and control group with a 1 : 1 allocation ratio by the generating of a random number table.The observation group received the “Xingnao kaiqiao” acupuncture method combined with “Temporal three needles,” and the control group received conventional acupuncture “Scalp acupuncture” combined with the traditional “body acupuncture” method. The acupuncture treatment was performed once per day for one week by trained acupuncturists. Both groups underwent secondary prevention of cerebral infarction and received a 3-months’ followup. After a 1-week acupuncture intervention, the changes of NIHSS (National Institutes of Health Stroke Scale) scores, Percent Change and Absolute Change of NIHSS scores, MBI (Modified Barthel Index), and the rate of MBI ≥ 80 in two groups were observed. After 3 months’ followup, the mRS (Modified Ranking Scale) and the clinical efficacy of the two groups were compared. Results. The apparent efficiency rate of the observation group was 63.9%, higher than 19.4% of the control group, and the difference was significant (

P
<
0.05

). After treatment, NIHSS scores, Percent Change, and Absolute Change of NIHSS scores in the observation group had a significant reduction than the control group (all

P
<
0.05

). MBI in the observation group increased significantly more than in the control group (

P
<
0.05

), but the rate of MBI ≥ 80 in the two groups was not significantly different (

P
>
0.05

). After 3 months’ of followup, the mRS score frequencies of the observation group were not statistically different from the control group (

P
>
0.05

). The rate of mRS scores of 0–1 in the observation and control group were 55.6% and 38.9%, and there was no significant difference either (

P
>
0.05

). Conclusion. Compared with “Scalp acupuncture” combined with “body acupuncture,” “Xingnao kaiqiao” acupuncture method combined with “Temporal three-needle” had superiority in the improvement of neurological deficit, potential functional disability, and score of basic activities of daily living. As to the independent rate to basic activities of daily living and good prognosis of 3 months, there were no statistical differences.
Microblog User Emotion Analysis Method Based on Improved Hierarchical Attention Mechanism and BiLSTM
Authors: Chen Xiao , Xiao Xiongliang
Published: June 2022

The goal of Chinese fine-grained emotion analysis is to identify the target words corresponding to fine-grained elements from sentences and determine the corresponding emotional polarity for the target words. Aiming at the problem that the current Sina Microblog user emotion analysis methods have low accuracy and are difficult to effectively predict and manage, a Sina Microblog user emotion analysis method based on the Bidirectional Long Short-Term Memory algorithm (BiLSTM) and improved hierarchical attention mechanism is proposed. Firstly, an emotion analysis model is constructed based on text-level analysis and subjective and objective analysis, and the dimensionality curse problem of one-hot representation is solved by integrating the weighted word vector of TF-IDF. Then, by constructing a bidirectional long short-term memory neural network, the full acquisition of context information is realized, which increases the fine-grained elements of emotion analysis. Finally, by introducing an improved hierarchical attention mechanism, the network model can focus on different parts to achieve text classification and emotion analysis. Through simulation experiments, the proposed emotion analysis method and the other two methods are compared and analyzed under the condition of using the same database. The results show that the precision, recall, and F1 value of the method proposed in this paper are the best under 7 different emotion classifications, with the highest reaching 95.8%, 95.9%, and 96.1%, respectively, and the algorithm performance is better than the other two comparisons algorithm. It is proved that the proposed model has excellent performance.
Inventory Management Optimization of Green Supply Chain Using IPSO-BPNN Algorithm under the Artificial Intelligence
Authors: Guan Ying , Huang Yingli , Qin Huiyan
Published: June 2022

This exploration is aimed at reducing the waste of resources in the supply chain inventory management and provide better services for green supply chain management. It mainly proposes a backpropagation neural network (BPNN) model based on improved particle swarm optimization (IPSO) (IPSO-BPNN) and applies it to inventory management prediction. First, the important technologies of green supply chain and intelligent supply chain are analyzed from the perspective of the ecological environment. Next, the particle swarm optimization (PSO) algorithm is optimized based on the adaptive improvement of the learning factor and the addition of the speed mutation operator. Then, it is applied to the learning and training of BPNN. Finally, the simulation experiment of the combination model is conducted. The application fields of the combination model are analyzed. The results show that a single BPNN model will produce large errors in the training process. The final error of BPNN using the traditional PSO algorithm is 0.0259, while the error of BPNN optimized by IPSO is 0.0163. The optimized combination model has higher accuracy, better performance, and the lowest error rate. The classification error rate of its training set and test set is 1.51 and 2.16, respectively. The mean square error of the training set is 0.0163 and that of the test set is 0.0229. Under 6 ~ 12 different hidden nodes, the daily measurement model error and monthly measurement model error are both low when the number of nodes is 11. Moreover, the training set is always better than the test set. Finally, the network structure of the combination model is determined as the structure of 6-11-1. This prediction module will provide purchase volume suggestions and inventory volume suggestions to provide a feasible direction for the green development of inventory management.
CXCR4/CX43 Regulate Diabetic Neuropathic Pain via Intercellular Interactions between Activated Neurons and Dysfunctional Astrocytes during Late Phase of Diabetes in Rats and the Effects of Antioxidant N-Acetyl-L-Cysteine
Authors: Zhu Dan , Fan Tingting , Chen Yaohua , Huo Xingyue , Li Yuping , Liu Danyong , Cai Yin , Cheung Chi Wai , Tang Jing , Cui Jian , Xia Zhengyuan
Published: June 2022

Growing evidence suggests that the interactions between astrocytes and neurons exert important functions in the central sensitization of the spinal cord dorsal horn in rodents with diabetes and neuropathic pain (DNP). However, it still remains unclear how signal transmission occurs in the spinal cord dorsal horn between astrocytes and neurons, especially in subjects with DNP. Chemokine CXC receptor 4 (CXCR4) plays critical roles in DNP, and connexin 43 (CX43), which is also primarily expressed by astrocytes, contributes to the development of neuropathy. We thus postulated that astrocytic and neuronal CXCR4 induces and produces inflammatory factors under persistent peripheral noxious stimulation in DNP, while intercellular CX43 can transmit inflammatory stimulation signals. The results showed that streptozotocin-induced type 1 diabetic rats developed heat hyperalgesia and mechanical allodynia. Diabetes led to persistent neuropathic pain. Diabetic rats developed peripheral sensitization at the early phase (2 weeks) and central sensitization at the late phase (5 weeks) after diabetes induction. Both CXCR4 and CX43, which are localized and coexpressed in neurons and astrocytes, were enhanced significantly in the dorsal horn of spinal cord in rats undergoing DNP during late phase of diabetes, and the CXCR4 antagonist AMD3100 reduced the expression of CX43. The nociceptive behavior was reversed, respectively, by AMD3100 at the early phase and by the antioxidant N-acetyl-L-cysteine (NAC) at the late phase. Furthermore, rats with DNP demonstrated downregulation of glial fibrillary acidic protein (GFAP) as well as upregulation of c-fos in the spinal cord dorsal horn at the late phase compared to the controls, and upregulation of GFAP and downregulation of c-fos were observed upon treatment with NAC. Given that GFAP and c-fos are, respectively, makers of astrocyte and neuronal activation, our findings suggest that CXCR4 as an inflammatory stimulation protein and CX43 as an intercellular signal transmission protein both may induce neurons excitability and astrocytes dysfunction in developing DNP.