bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of the Protective Effect of Bushen Huoxue Prescription on Cerebral Microvascular Endothelia Based on Proteomics and Bioinformatics
Authors: Zhao Shao-Yang , Zhao Huan-Huan , Li Yi-Ming , Wang Bao-Hua , Li Sai-Mei
Published: January 2022

Diabetic cognitive dysfunction is a serious complication of type 2 diabetes mellitus (T2DM), which can cause neurological and microvascular damage in the brain. At present, there is no effective treatment for this complication. Bushen Huoxue prescription (BSHX) is a newly formulated compound Chinese medicine containing 7 components. Previous research indicated that BSHX was neuroprotective against advanced glycosylation end product (AGE)-induced PC12 cell insult; however, the effect of BSHX on AGE-induced cerebral microvascular endothelia injury has not been studied. In the current research, we investigated the protective effects of BSHX on AGE-induced injury in bEnd.3 cells. Our findings revealed that BSHX could effectively protect bEnd.3 cells from apoptosis. Moreover, we analyzed the network regulation effect of BSHX on AGE-induced bEnd.3 cells injury at the proteomic level. The LC-MS/MS-based shotgun proteomics analysis showed BSHX negatively regulated multiple AGE-elicited proteins. Bioinformatics analysis revealed these differential proteins were involved in multiple processes, such as Foxo signaling pathway. Further molecular biology analysis confirmed that BSHX could downregulate the expression of FoxO1/3 protein and inhibit its nuclear transfer and inhibit the expression of downstream apoptotic protein Bim and the activation of caspase, so as to play a protective role in AGE-induced bEnd.3 injury. Taken together, these findings demonstrated the role of BSHX in the management of diabetic cerebral microangiopathy and provide some insights into the proteomics-guided pharmacological mechanism study of traditional Chinese Medicine.
Ankle-Injury Patients Perform More Microadjustments during Walking: Evidence from Velocity Profiles in Gait Analysis
Authors: Liu Xin , Zheng Bin , Guo Qinwei , Yu Yuanyuan , Zhang Zhongshi , Wulamu Aziguli , Zhang Dezheng
Published: January 2022

Introduction. We evaluated the velocity profiles of patients with lateral collateral ligament (LCL) injuries of the ankle with a goal of understanding the control mechanism involved in walking. Methods. We tracked motions of patients’ legs and feet in 30 gait cycles recorded from patients with LCL injuries of the ankle and compared them to 50 gait cycles taken from normal control subjects. Seventeen markers were placed on the foot following the Heidelberg foot measurement model. Velocity profiles and microadjustments of the knee, ankle, and foot were calculated during different gait phases and compared between the patient and control groups. Results. Patients had a smaller first rocker percentage and larger second rocker percentage in the gait cycle compared to controls. Patients also displayed shorter stride length and slower strides and performed more microadjustments in the second rocker phase than in other rocker/swing phases. Patients’ mean velocities of the knee, ankle, and foot in the second rocker phase were also significantly higher than that in control subjects. Discussion. Evidence from velocity profiles suggested that patients with ligament injury necessitated more musculoskeletal microadjustments to maintain body balance, but these may also be due to secondary injury. Precise descriptions of the spatiotemporal gait characteristics are therefore crucial for our understanding of movement control during locomotion.
The Role and Mechanism of SIRT6 in Regulating Phenotype Transformation of Vascular Smooth Muscle Cells in Abdominal Aortic Aneurysm
Authors: Guan Xiaomei , Xin Hai , Xu Meiling , Ji Jianlei , Li Jun
Published: January 2022

Background. Data mining of current gene expression databases has not been previously performed to determine whether sirtuin 6 (SIRT6) expression participates in the pathological process of abdominal aortic aneurysm (AAA). The present study was aimed at investigating the role and mechanism of SIRT6 in regulating phenotype transformation of vascular smooth muscle cells (VSMC) in AAA. Methods. Three gene expression microarray datasets of AAA patients in the Gene Expression Omnibus (GEO) database and one dataset of SIRT6-knockout (KO) mice were selected, and the differentially expressed genes (DEGs) were identified using GEO2R. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of both the AAA-related DEGs and the SIRT6-related DEGs were conducted. Results. GEO2R analysis showed that the expression of SIRT6 was downregulated for three groups and upregulated for one group in the three datasets, and none of them satisfied statistical significance. There were top 5 DEGs (KYNU, NPTX2, SCRG1, GRK5, and RGS5) in both of the human AAA group and SIRT6-KO mouse group. Top 25 ontology of the SIRT6-KO-related DEGs showed that several pathways including tryptophan catabolic process to kynurenine and negative regulation of cell growth were enriched in the tissues of thickness aortic wall biopsies of AAA patients. Conclusions. Although SIRT6 mRNA level itself did not change among AAA patients, SIRT6 may play an important role in regulating several signaling pathways with significant association with AAA, suggesting that SIRT6 mRNA upregulation is a protective factor for VSMC against AAA.
Portland Cement: An Overview as a Root Repair Material
Authors: Shahi Shahriar , Fakhri Elaheh , Yavari Hamidreza , Maleki Dizaj Solmaz , Salatin Sara , Khezri Khadijeh
Published: January 2022

Portland cement (PC) is used in challenging endodontic situations in which preserving the health and functionality of pulp tissue is of considerable importance. PC forms the main component of mineral trioxide aggregate (MTA) and demonstrates similar desirable properties as an orthograde or retrograde filling material. PC is able to protect pulp against bacterial infiltration, induce reparative dentinogenesis, and form dentin bridge during the pulp healing process. The biocompatibility, bioactivity, and physical properties of PC have been investigated in vitro and in animal models, as well as in some limited clinical trials. This paper reviews Portland cement’s structure and its characteristics and reaction in various environments and eventually accentuates the present concerns with this material. This bioactive endodontic cement has shown promising success rates compared to MTA; however, considerable modifications are required in order to improve its characteristics and expand its application scope as a root repair material. Hence, the extensive chemical modifications incorporated into PC composition to facilitate preparation and handling procedures are discussed. It is still important to further address the applicability, reliability, and cost‐effectiveness of PC before transferring into day‐to‐day clinical practice.
Crossmodality Person Reidentification Based on Global and Local Alignment
Authors: Lou Qiong , Li Junfeng , Qian Yaguan , Sun Anlin , Lu Fang
Published: January 2022

RGB-infrared (RGB-IR) person reidentification is a challenge problem in computer vision due to the large crossmodality difference between RGB and IR images. Most traditional methods only carry out feature alignment, which ignores the uniqueness of modality differences and is difficult to eliminate the huge differences between RGB and IR. In this paper, a novel AGF network is proposed for RGB-IR re-ID task, which is based on the idea of global and local alignment. The AGF network distinguishes pedestrians in different modalities globally by combining pixel alignment and feature alignment and highlights more structure information of person locally by weighting channels with SE-ResNet-50, which has achieved ideal results. It consists of three modules, including alignGAN module (

A

), crossmodality paired-images generation module (

G

), and feature alignment module (

F

). First, at pixel level, the RGB images are converted into IR images through the pixel alignment strategy to directly reduce the crossmodality difference between RGB and IR images. Second, at feature level, crossmodality paired images are generated by exchanging the modality-specific features of RGB and IR images to perform global set-level and fine-grained instance-level alignment. Finally, the SE-ResNet-50 network is used to replace the commonly used ResNet-50 network. By automatically learning the importance of different channel features, it strengthens the ability of the network to extract more fine-grained structural information of person crossmodalities. Extensive experimental results conducted on SYSU-MM01 dataset demonstrate that the proposed method favorably outperforms state-of-the-art methods. In addition, we evaluate the performance of the proposed method on a stronger baseline, and the evaluation results show that a RGB-IR re-ID method will show better performance on a stronger baseline.
Deep Learning-Assisted Repurposing of Plant Compounds for Treating Vascular Calcification: An In Silico Study with Experimental Validation
Authors: Chao Chia-Ter , Tsai You-Tien , Lee Wen-Ting , Yeh Hsiang-Yuan , Chiang Chih-Kang
Published: January 2022

Background. Vascular calcification (VC) constitutes subclinical vascular burden and increases cardiovascular mortality. Effective therapeutics for VC remains to be procured. We aimed to use a deep learning-based strategy to screen and uncover plant compounds that potentially can be repurposed for managing VC. Methods. We integrated drugome, interactome, and diseasome information from Comparative Toxicogenomic Database (CTD), DrugBank, PubChem, Gene Ontology (GO), and BioGrid to analyze drug-disease associations. A deep representation learning was done using a high-level description of the local network architecture and features of the entities, followed by learning the global embeddings of nodes derived from a heterogeneous network using the graph neural network architecture and a random forest classifier established for prediction. Predicted results were tested in an in vitro VC model for validity based on the probability scores. Results. We collected 6,790 compounds with available Simplified Molecular-Input Line-Entry System (SMILES) data, 11,958 GO terms, 7,238 diseases, and 25,482 proteins, followed by local embedding vectors using an end-to-end transformer network and a node2vec algorithm and global embedding vectors learned from heterogeneous network via the graph neural network. Our algorithm conferred a good distinction between potential compounds, presenting as higher prediction scores for the compound categories with a higher potential but lower scores for other categories. Probability score-dependent selection revealed that antioxidants such as sulforaphane and daidzein were potentially effective compounds against VC, while catechin had low probability. All three compounds were validated in vitro. Conclusions. Our findings exemplify the utility of deep learning in identifying promising VC-treating plant compounds. Our model can be a quick and comprehensive computational screening tool to assist in the early drug discovery process.
Study on Structural Characteristics of Composite Smart Grille Based on Principal Component Analysis
Authors: Fanxiao Kong , Huazhong Yao , Weidong Xie
Published: January 2022

In recent years, many scholars have conducted in-depth and extensive research on the mechanical properties, preparation methods, and structural optimization of grid structural materials. In this paper, the structural characteristics of composite intelligent grid are studied by combining theoretical analysis with experiments. According to the existing conditions in the laboratory, the equilateral triangular grid structure experimental pieces were prepared. In this paper, principal component analysis combined with nearest neighbor method was used to detect the damage of composite plates. On this basis, the multiobjective robustness optimization of the structure is carried out based on artificial intelligence algorithm, which makes the structure quality and its sensitivity to uncertain parameters lower. Particle swarm optimization (PSO) is used in neural network training. The damage characteristics of different grid structures, different impact positions, and different impact energies were studied. The results show that the structural damage types, areas, and propagation characteristics are very different when the structure is impacted at different positions, which verifies that the grid structure has a good ability to limit the damage diffusion and shows that the grid structure has a good ability to resist damage.
Research on User Experience of Sports Smart Bracelet Based on Fuzzy Comprehensive Appraisal and SSA-BP Neural Network
Authors: Luo Xichun , Zhao Honghao , Chen Yan
Published: January 2022

Due to the marked increase in the prevalence of overweight and obesity worldwide and an environment leading to a series of chronic diseases, physical exercise is an important way to prevent chronic diseases. Additionally, a good exercise smart bracelet can bring convenience to physical exercise. Quick and accurate evaluation of smart sports bracelets has become a hot topic and draws attention from both academic researchers and public society. In the literature, the analytic hierarchy process (AHP) and entropy weight method (EWM) were used to obtain the weights from both subjective and objective perspectives, which were integrated by the comprehensive weighting method, and furthermore the performance of sports smart bracelet was evaluated through fuzzy comprehensive evaluation. Also, to avoid complex weight calculations caused by the comprehensive weighting method, machine learning methods are used to model the structure and contribute to the comprehensive evaluation process. However, few studies have investigated all previous elements in the comprehensive evaluation process. In this study, we consider all previous parts when evaluating smart sports bracelets. In particular, we use the sparrow search algorithm (SSA) to optimize the backpropagation (BP) neural network for constructing the comprehensive score prediction model of the sports smart bracelet. Results show that the sparrow search algorithm-optimized backpropagation (SSA-BP) neural network model has good predictive ability and can quickly obtain evaluation results on the premise of effectively ensuring the accuracy of the evaluation results.
Value of Contrast-Enhanced Ultrasound in Adjusting the Classification of Chinese-TIRADS 4 Nodules
Authors: Cheng Hong , Zhuo Shuang-Shuang , Rong Xin , Qi Ting-Yue , Sun Hong-Guang , Xiao Xiao , Zhang Wen , Cao Hai-Yan , Zhu Lin-Hai , Wang Lei
Published: January 2022

Objectives. To explore the value of applying contrast-enhanced ultrasound (CEUS) in adjusting the classification of category 4 nodules in the Chinese-Thyroid Imaging Report and Data System (C-TIRADS). Methods. The data of preoperative conventional ultrasound and CEUS examinations of 125 C-TIRADS 4 nodules in 109 patients were retrospectively analyzed. We divided the thyroid nodules into two groups based on whether recommend by the guide fine-needle aspiration (FNA). Group I included C-TIRADS 4A nodules with a maximum diameter ≤15 mm and C-TIRADS 4B and 4C nodules with a maximum diameter ≤10 mm, and Group II included C-TIRADS 4A nodules with a maximum diameter >15 mm and C-TIRADS 4B and 4C nodules with a maximum diameter >10 mm. In CEUS, thyroid nodules showing suspicious malignant features such as hypoenhancement or early washout were adjusted to a level higher in the C-TIRADS classification; thyroid nodules showing possible benign features such as iso- or hyperenhancement were adjusted to a level lower; and thyroid nodules showing no enhancement were adjusted to C-TIRADS 3. Taking the pathological results as the gold standard, the receiver operating characteristic (ROC) curves of the C-TIRADS classification before and after the adjustment based on CEUS were plotted, and the diagnostic efficiency was compared. Results. The sensitivity, specificity, accuracy, and positive and negative predictive values of the C-TIRADS classification for the diagnosis of thyroid nodule malignancy before the adjustment based on the CEUS results were 83.6%, 63.8%, 74.4%, 72.7%, and 77.1%, respectively, and these values were 91.0%, 82.8%, 87.2%, 85.9%, and 88.9%, respectively, after the adjustment. The area under the ROC curve (AUC) was 0.737 and 0.869, respectively, showing a significant difference (Z = 3.288,

P
=
0.001

). The diagnostic efficiency of C-TIRADS classification after the adjustment based on the CEUS results in both groups was improved compared with the result before the adjustment, and the difference in Group II was significant (Z = 2.931,

P
=
0.003

). Conclusions. CEUS significantly improved the diagnostic performance in the adjustment of C-TIRADS 4 nodule classification, especially for the nodules which needs FNA recommended by the C-TIRADS.
The Study on the Shock Wave Propagation Rule of a Gas Explosion in a Gas Compartment
Authors: Lin Shu-Chao , Hou Qing-Zhao , Derlatka Anna , Gao Shan , Kang Jin-Jun , Dong Xiao-Lei
Published: January 2022

Combined with the k-ε turbulence model of general application, a refined finite element model of a utility tunnel’s gas compartment filled with the methane/air mixture is developed. A series of analyses are made by using the powerful industry-leading computational fluid dynamics (CFD) software flame acceleration simulator (FLACS) to study the shock wave propagation rule in the gas compartment. The longitudinal and transversal distribution laws of the explosion shock wave are gained taking into consideration the spatial characteristics of the gas compartment. The influences of a few parameters, such as initial conditions and section size of the gas compartment, on the shock wave propagation rule are further discussed. The basic procedure for predicting the peak pressure of the blast wave is provided by considering the initial conditions and the gas compartment, and the corresponding injury effect of the explosion wave on the living beings is assessed. The investigation demonstrates that the peak pressure by the coupled effect between the initial conditions is significantly influenced, especially at the upper and lower gas explosion limits. The peak pressure increases gradually as the width or height increases, and both basically meet the linear relation. The proposed method can forecast the peak pressure of the explosion shock wave in the gas compartment accurately. According to the peak pressure longitudinal and transversal distributions of the blast wave, the peak pressure is far greater than the killing pressure threshold in the underground and closed space; consequently, it is not safe for the living beings in the gas compartment.
LC-MS/MS Method for Determination of Hydroxychloroquine and Metabolites: Application in a Pharmacokinetic Study
Authors: Cui Lili , Wang Zhipeng , Qiu Shi , Zhang Mengwei , Liu Yanping , Xu Fengjing , Song Xinhua , Gao Shouhong , Chen Wansheng
Published: January 2022

Hydroxychloroquine (HCQ) was originally used as an antimalarial and immunomodulation drug. We developed and validated a simple and sensitive ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for simultaneous quantitation of HCQ and its three metabolites in rat blood, and reported their pharmacokinetic parameters. The chromatographic separation and detection of analytes were achieved within 4 min on ZORBAX SB-C8 (3.5 μm, 2.1 × 150 mm) column with gradient elution, and the flow rate was 0.25 mL/min. Simple protein precipitation was successfully applied for sample pretreatment. The HCQ displays a good linearity in the range of 2.0–5000.0 ng/mL, and the three metabolites also show good linearity ranging from 1.0 to 2500.0 ng/mL, with all correlation coefficients (R2) better than 0.98. In conclusion, this rapid, sensitive method was successfully developed, validated, and then applied to a pharmacokinetic study of HCQ in rat model in high dose. The results of the pharmacokinetic study presented an average half-life time 21.14 ± 10.31 h (mean ± SD) of HCQ, which is much shorter in human compared to that in mice. For the three metabolites, longer half-life times (approximately 100 h) were shown in rat.
A Multiple Fixed Point Result for

θ
,
ϕ
,
ψ

-Type Contractions in the Partially Ordered
s
-Distance Spaces with an Application
Authors: Rashid Maliha , Kalsoom Amna , Ghaffar Abdul , Inc Mustafa , Sene Ndolane
Published: January 2022

In this manuscript, the aim is to prove a multiple fixed point (FP) result for partially ordered

s

-distance spaces under

θ
,
ϕ
,
ψ

-type weak contractive condition. The result will generalize some well-known results in literature such as coupled FP (Guo and Lakshmikantham, 1987), triple fixed point (Berinde and Borcut, 2011), and quadruple FP results (Karapinar, 2011). Moreover, to validate the result, an application for the existence of solution of a system of integral equations is also provided.
Investigation of Dynamic Responses and Vibration Serviceability of Temporary Grandstands by a 3 DOF Interaction Model due to Swaying Motion
Authors: Yuan Jian , Yu Suhui , Liu Cong , Gao Chengqiang , Wang Wei , He Lin , Fan Feng
Published: January 2022

Excessive vibration of temporary grandstand by the crowd has lateral rhythmic motions, which attracted increasing attention in the recent years. This paper focuses on experiments where a temporary grandstand occupied by 20 participants is oscillated by a shaking table with a series of random waves and the crowd-induced rhythmic swaying motions at lateral direction, respectively. The dynamic forces that were induced by participants who have swayed at 0.5–1.8 Hz are recorded by a tri-axial human biomechanics force plate. A new relationship between the annoyance rate and structural acceleration at logarithmic coordinate is investigated and proposed, and the swaying load model is given. Based on these experimental results, a simplified three-degree-of-freedom lumped dynamic model of the joint human–structure system is reinterpreted. Afterwards, combined with a feasible range of crowd/structural dynamic parameters, a series of interaction models are analyzed, the vibration dose value (VDV) of the structure is obtained and discussed, and the notable parameters for interaction model are predicted. The experimental results show that the lateral serviceability limit is 1.29 m/s1.75 and the upper boundary is 2.32 m/s1.75. The dynamic response of model indicated that the VDV of structure will be decreased with increasing the mass of static crowd and damping ratio of the dynamic crowd. The max response of the model is α ≤ 0.6, f2 = 1.8 Hz or α > 0.6, f2 = 1.5 Hz or f1 = 2.5–3.5 Hz. It may be used as a reference value in vibration safety and serviceability assessment of TDGs, to estimate realistically the vibration response on the occasions when the crowds are swaying.
Animation Design Based on 3D Visual Communication Technology
Authors: Shan Feng , Wang Youya
Published: January 2022

The depth synthesis of image texture is neglected in the current image visual communication technology, which leads to the poor visual effect. Therefore, the design method of film and TV animation based on 3D visual communication technology is proposed. Collect film and television animation videos through 3D visual communication content production, server processing, and client processing. Through stitching, projection mapping, and animation video image frame texture synthesis, 3D vision conveys animation video image projection. In order to ensure the continuous variation of scaling factors between adjacent triangles of animation and video images, the scaling factor field is constructed. Deep learning is used to extract the deep features and to reconstruct the multiframe animated and animated video images based on visual communication. Based on this, the frame feature of video image under gray projection is identified and extracted, and the animation design based on 3D visual communication technology is completed. Experimental results show that the proposed method can enhance the visual transmission of animation video images significantly and can achieve high-precision reconstruction of video images in a short time.
Establishment, Analysis, and Application of the Information Transmission and Response Model for Students of Vocational Colleges under Public Health Emergencies
Authors: Chen Hengliang , Li Zilin , Luo Fei
Published: January 2022

To provide a basic quantitative mathematical model for data analysis, decision-making support, and application of information systems oriented to emergency research, this paper established an information transmission response model for school students under such system mathematically based on actual school information transmission data during COVID-19 prevention. This paper proposes an emergency information management method—a two-step emergency information management method. It can be referenced for promotion of the development of IT-based school management, enhancement of IT application in school emergency information management, and improvement of the speed and accuracy of information transmission.
Effect of Rho-Kinase and Autophagy on Remote Ischemic Conditioning-Induced Cardioprotection in Rat Myocardial Ischemia/Reperfusion Injury Model
Authors: Gao Jie , Min Feng , Wang Shasha , Lv Heng , Liang Huan , Cai Ben , Jia Xianjie , Gao Qin , Yu Ying
Published: January 2022

Objective. Remote ischemic conditioning (RIC) is a cardioprotective method in ischemia/reperfusion (I/R) injury. This study investigated the mechanism of Rho-kinase-mediated autophagy in RIC. Methods. Sixty male Sprague–Dawley rats were randomly divided into six groups: sham, I/R, RIC, I/R+fasudil, RIC+wortmannin, and RIC+fasudil+wortmannin. Throughout the experiment, mean arterial pressure and heart rate were continuously monitored. Histopathology and ultrastructure and myocardial enzymes’ expression were evaluated to determine the degree of cardiac injury. The protein expression of the Rho-kinase substrates myosin light chain (MLC) and myosin phosphatase target subunit 1 (MYPT1), autophagy-related protein light chain 3-II (LC3-II) and Beclin 1, and protein kinase B (AKT) was measured in the myocardial tissue. Results. Compared with the sham group, the mean arterial pressure and heart rate were decreased, myocardial enzyme levels were increased, and myocardial damage was aggravated in the I/R group; however, RIC improved these alterations. The expression of phosphorylated MLC and MYPT1 was lower, while LC3-II, Beclin 1, and phospho-AKT expression levels were higher in the RIC group compared with the I/R group. Obviously, treatment of the I/R group rats with fasudil, a Rho-kinase inhibitor, significantly ameliorated the I/R effects, whereas treatment of the RIC group rats with wortmannin, a phosphatidylinositol-3 kinase (PI3K) inhibitor, inhibited the RIC protective effects. Moreover, the rats in the RIC+fasudil+wortmannin group showed similar changes to those in the RIC+wortmannin group. Conclusion. These results showed that RIC protected the myocardium from I/R injury by suppressing Rho-kinase and the underlying mechanism may be related to enhancing autophagy via the PI3K/AKT pathway.
Performance Evaluation of Downlink Coordinated Multipoint Joint Transmission under Heavy IoT Traffic Load
Authors: Mukhtar Alaa M. , Saeed Rashid A. , Mokhtar Rania A. , Ali Elmustafa Sayed , Alhumyani Hesham
Published: January 2022

Emerging 5G network cellular promotes key empowering techniques for pervasive IoT. Evolving 5G-IoT scenarios and basic services like reality augmented, high dense streaming of videos, unmanned vehicles, e-health, and intelligent environments services have a pervasive existence now. These services generate heavy loads and need high capacity, bandwidth, data rate, throughput, and low latency. Taking all these requirements into consideration, internet of things (IoT) networks have provided global transformation in the context of big data innovation and bring many problematic issues in terms of uplink and downlink (DL) connectivity and traffic load. These comprise coordinated multipoint processing (CoMP), carriers’ aggregation (CA), joint transmissions (JTs), massive multi-inputs multi-outputs (MIMO), machine-type communications, centralized radios access networks (CRAN), and many others. CoMP is one of the most significant technical enhancements added to release 11 that can be implemented in heterogonous networks implementation approaches and the homogenous networks’ topologies. However, in a massive 5G-IoT device scenario with heavy traffic load, most cell edge IoT users are severely suffering from intercell interference (ICI), where the users have poor signal, lower data rates, and limited QoS. This work is aimed at addressing this problematic issue by proposing two types of DL-JT-CoMP techniques in 5G-IoT that are compliant with release 18. Downlink JT-CoMP with two homogeneous network CoMP deployment scenarios is considered and evaluated. The scenarios used are IoT intrasite and intersite CoMP, which performance evaluated using downlink system-level simulator for long-term evolution-advanced (LTE-A) and 5G. Numerical simulation scenarios were results under high dense scenario—with IoT heavy traffic load which shows that intersite CoMP has better empirical cumulative distribution function (ECDF) of average UE throughput than intrasite CoMP approximately 4%, inter-site CoMP has better ECDF of average user entity (UE) spectral efficiency than intrasite CoMP almost 10%, and intersite CoMP has approximately same ECDF of average signal interference noise ratio (SINR) as intrasite CoMP and intersite CoMP has better fairness index than intrasite CoMP by 5%. The fairness index decreases when the users’ number increase since the competition among users is higher.
Initial Elastic Stiffness of Bolted Shear Connectors in Steel‐Concrete Composite Structures
Authors: Wang Chenggong , Cao Diankai , Liu Xiaoyang , Jing Yucai , Liu Wenzhuo , Yang Guotao
Published: January 2022

Bolted shear connectors have the advantages of being easily fitted and dismantled during construction, the initial elastic stiffness of which has a great influence on the structural performance of the connected composite structures. In this paper, the initial elastic behaviors of three types of bolted shear connectors used in steel‐concrete composite structures (i.e., the bolt with nonembedded nut, the bolt with single‐embedded nut, and the bolt with double‐embedded nuts) are investigated using finite element analysis (FEA). After the FE models are verified against the experimental results in other literature, an extensive parametric study is carried out to investigate the effects of eight parameters of the composite structures on the initial shear stiffness and tension stiffness as well as coupling stiffness. Empirical formulas are subsequently developed for obtaining the initial elastic stiffness of the bolted shear connectors, based on which further FEA is performed. The FEA results are in good agreement with the experimental results, illustrating the effectiveness of the empirical formulas.
Multiclass Interactive Martial Arts Teaching Optimization Method Based on Euclidean Distance
Authors: Hu Zhechun , Wang Yunxing
Published: January 2022

Aiming at the problems of low optimization accuracy, poor optimization effect, and long running time in current teaching optimization algorithms, a multiclass interactive martial arts teaching optimization method based on the Euclidean distance is proposed. Using the K-means algorithm, the initial population is divided into several subgroups based on the Euclidean distance, so as to effectively use the information of the population neighborhood and strengthen the local search ability of the algorithm. Imitating the school's selection of excellent teachers to guide students with poor performance, after the “teaching” stage, the worst individual in each subgroup will learn from the best individual in the population, and the information interaction in the evolutionary process will be enhanced, so that the poor individuals will quickly move closer to the best individuals. According to different learning levels and situations of students, different teaching stages and contents are divided, mainly by grade, supplemented by different types of learning groups in the form of random matching, so as to improve the learning ability of members with weak learning ability in each group, which effectively guarantees the diversity of the population and realizes multiclass interactive martial arts teaching optimization. Experimental results show that the optimization effect of the proposed method is better, which can effectively improve the accuracy of algorithm optimization and shorten the running time of the algorithm.
Structure-Based In Silico Investigation of Agonists for Proteins Involved in Breast Cancer
Authors: Roy Arpita , Anand Ashutosh , Garg Saksham , Khan Mohd Shahnawaz , Bhasin Sidharth , Asghar Muhammad Nadeem , Emran Talha Bin
Published: January 2022

Cancer is recognized as one of the main causes of mortality worldwide by the World Health Organization. The high cost of currently available cancer therapy and certain limitations of current treatment make it necessary to search for novel, cost-effective, and efficient methods of cancer treatment. Therefore, in the current investigation, sixty-two compounds from five medicinal plants (Tinospora cordifolia, Ocimum tenuiflorum, Podophyllum hexandrum, Andrographis paniculata, and Beta vulgaris) and two proteins that are associated with breast cancer, i.e., HER4/ErbB4 kinase and ERα were selected. Selected compounds were screened using Lipinski’s rule, which resulted in eighteen molecules being ruled out. The remaining forty-four compounds were then taken forward for docking studies followed by molecular dynamics studies of the best screened complexes. Results showed that isocolumbin, isopropylideneandrographolide, and 14-acetylandrographolide were potential lead compounds against the selected breast cancer receptors. Furthermore, in vitro studies are required to confirm the efficacy of the lead compounds.
The Diagnostic Value of 18F‐FDG PET/CT Bone Marrow Uptake Pattern in Detecting Bone Marrow Involvement in Pediatric Neuroblastoma Patients
Authors: Liu Jun , Li Cuicui , Yang Xu , Lu Xia , Zhang Mingyu , Qian Luodan , Wang Wei , Kan Ying , Yang Jigang
Published: January 2022

Objectives. To explore the diagnostic value of 18F‐FDG PET/CT bone marrow uptake pattern (BMUP) in detecting bone marrow involvement (BMI) in pediatric neuroblastoma (NB) patients. Methods. Ninety‐eight NB patients were enrolled in BMI analysis. Four patterns of bone marrow uptake were categorized based on pretreatment cF‐FDG PET/CT images. Some crucial inspection indexes and 18F‐FDG PET/CT metabolic parameters were analyzed. The BMUP was divided into BMUP1, BMUP2, BMUP3, and BMUP4. Paired‐like homeobox 2b (PHOX2B) of bone marrow and blood, bone marrow biopsy (BMB) result, and 18F‐FDG PET/CT were compared to detect BMI. All patients were followed up for at least six months. Results. BMUP had excellent consistency among different physicians. Kappa coefficients of two residents and two attending physicians and between the resident and attending physician, were 0.857, 0.891, and 0.845, respectively. The optimal cut‐off value of SUVmax‐Bone/Liver was 2.08 to diagnose BMI for BMUP3 patients, and the area under curve (AUC) was 0.873. AUC of PHOX2B of bone marrow (PHOX2B of BM), PHOX2B of blood, BMB, and 18F‐FDG PET/CT were 0.916, 0.811, 0.806, and 0.904, respectively. There was no significant difference between PHOX2B of BM and PET/CT. Positive predictive value, negative predictive value, sensitivity, and specificity in diagnosis of BMI were 92.9%, 92.9%, 97.0%, and 83.9% for PET/CT and 96.7%, 80.6%, 89.6%, and 93.5% for PHOX2B of BM, respectively. Conclusions. BMUP of pretreatment 18F‐FDG PET/CT is a simple and practical method, which has a relatively high diagnostic efficiency in detecting BMI and might decrease unnecessary invasive inspections in some pediatric NB patients.
Systematic Framework to Predict Early‐Stage Liver Carcinoma Using Hybrid of Feature Selection Techniques and Regression Techniques
Authors: Mehmood Marium , Alshammari Nasser , Alanazi Saad Awadh , Ahmad Fahad
Published: January 2022

The liver is the human body’s mandatory organ, but detecting liver disease at an early stage is very difficult due to the hiddenness of symptoms. Liver diseases may cause loss of energy or weakness when some irregularities in the working of the liver get visible. Cancer is one of the most common diseases of the liver and also the most fatal of all. Uncontrolled growth of harmful cells is developed inside the liver. If diagnosed late, it may cause death. Treatment of liver diseases at an early stage is, therefore, an important issue as is designing a model to diagnose early disease. Firstly, an appropriate feature should be identified which plays a more significant part in the detection of liver cancer at an early stage. Therefore, it is essential to extract some essential features from thousands of unwanted features. So, these features will be mined using data mining and soft computing techniques. These techniques give optimized results that will be helpful in disease diagnosis at an early stage. In these techniques, we use feature selection methods to reduce the dataset’s feature, which include Filter, Wrapper, and Embedded methods. Different Regression algorithms are then applied to these methods individually to evaluate the result. Regression algorithms include Linear Regression, Ridge Regression, LASSO Regression, Support Vector Regression, Decision Tree Regression, Multilayer Perceptron Regression, and Random Forest Regression. Based on the accuracy and error rates generated by these Regression algorithms, we have evaluated our results. The result shows that Random Forest Regression with the Wrapper Method from all the deployed Regression techniques is the best and gives the highest R2‐Score of 0.8923 and lowest MSE of 0.0618.
A Complex-Valued Encoding Multichain Seeker Optimization Algorithm for Engineering Problems
Authors: Duan Shaomi , Luo Huilong , Liu Haipeng
Published: January 2022

This article comes up with a complex-valued encoding multichain seeker optimization algorithm (CMSOA) for the engineering optimization problems. The complex-valued encoding strategy and the multichain strategy are leaded in the seeker optimization algorithm (SOA). These strategies enhance the individuals’ diversity, enhance the local search, avert falling into the local optimum, and are the influential global optimization strategies. This article chooses fifteen benchmark functions, four proportional integral derivative (PID) control parameter models, and six constrained engineering problems to test. According to the experimental results, the CMSOA can be used in the benchmark functions, in the PID control parameter optimization, and in the optimization of constrained engineering problems. Compared to the particle swarm optimization (PSO), simulated annealing based on genetic algorithm (SA_GA), gravitational search algorithm (GSA), sine cosine algorithm (SCA), multiverse optimizer (MVO), and seeker optimization algorithm (SOA), the optimization ability and robustness of the CMSOA are better than those of others algorithms.
Effects and Mechanism of Oxymatrine Combined with Compound Yinchen Granules on the Apoptosis of Hepatocytes through the Akt/FoxO3a/Bim Pathway
Authors: Zhang Xian , Ge Jiajia , Zhu Xuejuan , Zhang Haifeng , Wang Yuanzi , Xu Tongtong , Jiang Wei , Zhang Bin
Published: January 2022

The aim of the present study was to investigate the effects and mechanism of oxymatrine (OMT) combined with compound yinchen granules (CYG) on the apoptosis of hepatocytes through the Akt/FoxO3a/Bim pathway in rats with acute liver failure. The rat model of acute liver failure was established using lipopolysaccharide/D‐galactosamine (LPS/D‐GalN). The expression of proteins in rat liver tissues was detected by western blot analysis. The mRNA expression of FoxO3a, Bim, Bax, Bcl‐2, and caspase‐3 in rat liver tissues was detected by RT‐qPCR. The apoptosis rate of rat hepatocytes was determined by flow cytometry. Western blots showed that when compared with the normal group, the expression of p‐Akt and p‐FoxO3a in the model group was decreased (P < 0.05), while the expression of Bim was increased (P < 0.01). Compared with the model group, the expression of p‐Akt and p‐FoxO3a in the OMT group and the OMT combined with CYG groups was increased (P < 0.05 or P < 0.01), while the expression of Bim was decreased (P < 0.05). The Bax/Bcl‐2 ratio and caspase‐3 protein expression in the model group were significantly higher than those in the normal group (P < 0.01). The Bax/Bcl‐2 ratio and the expression of caspase‐3 protein in the OMT group and the OMT combined with CYG groups were significantly lower than those in the model group (P < 0.01). The results of RT‐qPCR were consistent with those of western blot. The results of flow cytometry showed that the apoptosis rate of hepatocytes in the OMT group and the OMT combined with CYG groups was significantly lower than that in the model group (P < 0.05 or P < 0.01). We concluded that LPS/D‐GalN can induce apoptosis of hepatocytes in rats with acute liver failure through the Akt/FoxO3a/Bim pathway. OMT combined with CYG inhibits apoptosis of hepatocytes in rats with acute liver failure via the Akt/FoxO3a/Bim pathway.
miR‐622 Induces Breast Cancer Cell MCF‐7 Proliferation, Migration, and Invasion by Directly Negatively Targeting EYA1
Authors: Tang Pan , Shen Yanyan , Yang Jihui , Wen Nan , Liu Ying , Zeng Qiqing , Yin Tingting
Published: January 2022

Breast cancer is the most common female cancer in the world. Breast cancer patients are currently treated with a combination of surgery, chemotherapy, radiotherapy, and targeted therapy, but the 5‐year overall survival rate is still low. Therefore, we plan to explore the potential interaction mechanism between miR‐622 and EYA1 in the breast cancer cells and their effect on proliferation, migration, and invasion of breast cancer, to lay a foundation for the gene therapy of breast cancer and improve the therapeutic effect. This study found that miR‐622 was highly expressed in breast cancer cell lines, while EYA1 was poorly. In MCF‐7 cell line, miR‐622 had the highest expression level, while EYA1 had the lowest. Besides, the bioinformatics analysis showed that EYA1 possesses putative miR‐622 binding sites within its 3 ′UTR. The increased miR‐622 significantly enhanced the proliferation, migration, and invasion of MCF‐7 cell line and inhibited luciferase reporter activity in the 3 ′UTR of EYA1‐WT. When upregulating the expression of miR‐622, the mRNA and protein expression levels of EYA1 were significantly decreased. We also found that the silencing of EYA1 promoted the proliferation, migration, and invasion of breast cancer MCF‐7 cell line. These results indicate that miRNA‐622 plays a tumor‐promoting role in breast cancer through targeted negative regulation of EYA1, suggesting that miRNA‐622 may become a potential target for breast cancer treatment.
Variational Fuzzy Neural Network Algorithm for Music Intelligence Marketing Strategy Optimization
Authors: Sun Juan
Published: January 2022

In this paper, we use a variational fuzzy neural network algorithm to conduct an in-depth analysis and research on the optimization of music intelligent marketing strategy. The music recommendation system proposed in this paper includes a user modelling module, audio feature extraction module, and recommendation algorithm module. The basic idea of the recommendation algorithm is as follows: firstly, the historical behavioural information of music users is collected, and the user preference model is constructed by using the method of matrix decomposition of the hidden semantic model; then, the audio resources in the system are preprocessed and the spectrum map that can represent the music features is extracted; the similarity between the user’s preferred features and the music potential features are calculated to generate recommendations for the target user. The user-music dataset for model training and testing is constructed in-house, and the network model structure used for system experiments is designed based on a typical convolutional neural network model, while the model training tuning parameters are compared and selected. Finally, the model is trained and tested in this paper, and the system is evaluated in terms of both prediction rating accuracy and recommendation list generation accuracy using root mean square error, accuracy, recall, and F1 value as recommendation quality evaluation metrics. The experimental results show that the recommendation algorithm in this paper has certain feasibility and effectiveness. Compared with other traditional music recommendation algorithms, this paper makes full use of the powerful advantage of deep neural networks to automatically extract features and obtain higher-level music feature representations from the audio content, while incorporating the historical behavioural information of user interactions with music, which can effectively alleviate the problems such as cold start in recommendation systems.
Threshold Effect of Financial System on High‐Quality Economic Development
Authors: Shen Lu , He Guohua
Published: January 2022

The relationship between financial system and economic development is not a simple linear relationship. In some cases, the development of finance may not improve the economic development level. This paper studies the influence of the financial system on the high‐quality economic development, constructs the comprehensive index of the financial system by the factor analysis method, and calculates the green total factor productivity as the index of high‐quality economic development by the CRS multiplier model. Empirically, this paper takes the panel data of 30 provinces, municipalities, and autonomous regions in China from 2005 to 2018 as samples, constructs the panel threshold model, and applies the financial system, economic development level, infrastructure, and industrial structure as threshold variables to study the nonlinear relationship between the financial system and high‐quality economic development. The results demonstrate that the impact of the financial system on the high‐quality economy presents an inverted U‐shaped relationship when the financial system and industrial structure are the threshold variables, indicating that there is an optimal interval, that is, when the financial system threshold is between 0.1355 and 0.1377 and the industrial structure threshold is between 0.1364 and 0.1408, the financial system plays a greater role in the allocation of funds and has the most obvious positive impact on high‐quality economic development. Meanwhile, the impact of the financial system on the high‐quality shows a marginal decreasing trend when the economic development level and infrastructure are the threshold variables; when the economic development threshold is less than 0.1409 and the basic setting threshold is less than 0.1167, the financial system has the greatest effect on promoting high‐quality economic development. Based on the research results, targeted policy suggestions are put forward.