bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Different Doses of Tranexamic Acid Plus Traditional Chinese Medicine in Hip Arthroplasty in Patients with Diabetes and Its Influence on Intraoperative Blood Loss and Postoperative Drainage
Authors: Yang Xiao-Long , Luo Bei , Zhang Zhong-Xing , Feng Xiao-Feng , Xu Feng
Published: May 2022

Objective. To evaluate the efficacy of different doses of tranexamic acid plus traditional Chinese medicine (TCM) in hip arthroplasty in diabetic patients and the effect on intraoperative hemorrhage and postoperative drainage. Methods. One hundred patients admitted to our hospital from January 2019 to September 2021 were randomly divided into group B (n = 50) and group A (n = 50), and tranexamic acid was injected intravenously at a dose of 10 mg/kg and 20 mg/kg 30 min before skin incision, and then tranexamic acid 1.0 g was injected into the joint cavity through the drainage after incision closure, followed by 3 h of drainage clamping. The amount of blood loss, coagulation index, postoperative drainage, and incidence of venous thromboembolism (VTE) were compared between the groups. Results. Group A had significantly less total blood loss, dominant blood loss, and hidden blood loss than group B (

P
<
0.05

). No significant difference in postoperative coagulation indexes and postoperative drainage flow was found between the two groups (

P
>
0.05

). Serological examination results demonstrated no statistical difference in D-dimer (D-D) levels between the two groups. The absence of VTE in both groups was determined by imaging. Conclusion. Tranexamic acid is effective in reducing intraoperative hemorrhage in diabetic patients undergoing hip arthroplasty. The dose of 20 mg/kg outperforms 10 mg/kg in terms of clinical efficacy with a favorable safety profile, which can be applied according to the patient’s actual condition.
In Vitro Evaluation of Antibacterial, Antioxidant, and Antidiabetic Activities and Glucose Uptake through 2-NBDG by Hep-2 Liver Cancer Cells Treated with Green Synthesized Silver Nanoparticles
Authors: Majeed Shahnaz , Danish Mohammed , Zakariya Norul Aini , Hashim Rokiah , Ansari Mohammed Tahir , Alkahtani Saad , Hasnain Md Saquib
Published: May 2022

The alarming rise in diabetes owing to drug resistance necessitates the implementation of prompt countermeasures in the treatment module of diabetes. Due to their unique physicochemical features, silver nanoparticles may have potential applications in the medical and pharmaceutical industries. Silver nanoparticles (AgNPs) were synthesized from the culture filtrate of Salmonella enterica (ATCC-14028). UV-Vis spectrophotometry, FTIR, SEM, and energy dispersive X-rays were used in the characterization of the nanoparticles. Transmission electron microscopy (TEM) revealed that AgNPs are spherical and highly scattered and vary in size from 7.18 nm to 13.24 nm. AgNP stability and protein loss were confirmed by thermogravimetric analysis (TGA) at different temperatures. The AgNPs had excellent antibacterial activity and a strong synergistic effect against methicillin-resistant bacteria Staphylococcus aureus (MRSA) ATCC-4330 and Streptococcus epidermis (MRSE) ATCC-51625. The DPPH experiment revealed that the AgNPs had high antioxidant activity. The antidiabetic assay revealed that these AgNPs had an IC50 for alpha-amylase of 428.60 μg/ml and an IC50 for alpha-glucosidase of 562.02 μg/ml. Flow cytometry analysis of Hep-2 cells treated with AgNPs (40 μg/ml) revealed higher expression of 2-NBDG glucose absorption (uptake) compared to control metformin. These AgNPs have promising antidiabetic properties and could be used in pharmaceuticals and biomedical industries.
Cancer Detection and Prediction Using Genetic Algorithms
Authors: Bhandari Aradhita , Tripathy B. K. , Jawad Khurram , Bhatia Surbhi , Rahmani Mohammad Khalid Imam , Mashat Arwa
Published: May 2022

Cancer is a wide category of diseases that is caused by the abnormal, uncontrollable growth of cells, and it is the second leading cause of death globally. Screening, early diagnosis, and prediction of recurrence give patients the best possible chance for successful treatment. However, these tests can be expensive and invasive and the results have to be interpreted by experts. Genetic algorithms (GAs) are metaheuristics that belong to the class of evolutionary algorithms. GAs can find the optimal or near-optimal solutions in huge, difficult search spaces and are widely used for search and optimization. This makes them ideal for detecting cancer by creating models to interpret the results of tests, especially noninvasive. In this article, we have comprehensively reviewed the existing literature, analyzed them critically, provided a comparative analysis of the state-of-the-art techniques, and identified the future challenges in the development of such techniques by medical professionals.
Vibration Transmission from a Machine with Three Degree of Freedoms to Beam Structures by Dynamic Stiffness Method
Authors: Wei Zitian , Li Hui , Yin Xuewen , Wu WenWei
Published: May 2022

The dynamic stiffness method (DSM) is proposed for vibration transmission from a machine with three degree of freedoms (DOFs) to its supporting beam structures. The machine is idealized as a rigid mass with three major degrees of freedom, namely, heave, roll, and pitch. It implies that the moments of inertia and torques due to unbalanced parts can be taken into consideration. The three types of vibration within beam structures, i.e., bending, longitudinal, and torsional motions, are formulated in terms of dynamic stiffness matrices. The finite element techniques can be applied similarly to assemble the developed dynamic stiffness matrices of both the machine and its supporting beam structures. A beam-like raft carrying a machine is designed to illustrate the accuracy of the proposed method in numerical simulation, where the differences brought by three-DOF modeling in vibration transmission analysis are discussed as well. This work would provide a novel and easy-to-use alternative to the existing mobility method and finite element method due to low discretization requirements, high efficiency, and high accuracy.
Financial and Economic Sequence Forecasting Based on Time Slot Allocation Algorithm
Authors: Wu Yuhan
Published: May 2022

Financial and economic series prediction was very important for the study of economic time series. Because the traditional time series analysis method was mainly suitable for stable data and cannot be applied to unstable economic variables, this paper proposed a knowledge model of financial and economic series prediction time slot algorithm, which provided the basis for solving unstable financial data. Firstly, based on the analysis of relevant financial and economic series prediction methods at home and abroad, this paper applied the time slot allocation algorithm to economic series analysis and prediction and designed a path level time slot allocation algorithm, which introduced a fixed time slot to shorten the time required to complete the path level time slot allocation. Secondly, this paper abstracted the calculation of slot allocation as a convex optimization problem and proposed a round slot allocation algorithm based on constraints and optimal solution. The algorithm can improve the end-to-end throughput and the effective utilization of slots. Finally, the model proposed in this paper was used to predict the indicators of relevant industries, and the simulation results were compared with the standard data. The experimental results showed that the financial and economic series prediction system based on time slot allocation algorithm proposed in this paper can effectively improve the accuracy of financial and economic series prediction, which verified the effectiveness and feasibility of this model.
Estimation Method for Mixed Near-Field and Far-Field Sources Based on Four-Order Cumulant and Polarization Sensitive Array
Authors: Wang Liguo , Yu Binbin
Published: May 2022

A new multidimensional parameters joint estimation method of mixed near-field and far-field sources based on polarization sensitive array, fourth-order cumulant, joint diagonalization technology, and propagator method is presented, which can realize the joint estimation of DOA (Direction of Arrival), range, frequency, polarization auxiliary angle, and polarization phase difference without multidimensional spectral peak searching and parameter pairing, and it is suitable for any additive Gaussian noise environment and effective for reducing the loss of array aperture. The algorithm skillfully constructs the fourth-order cumulant matrix by using the output on the label of specific dipole pairs of the received array, which effectively avoids the matrix rank reduction caused by the far-field sources coexistence situation. In addition, the presented algorithm utilizes the orthogonal propagation algorithm for subspace decomposition and uses the total least square solution to replace the orthogonal solution of singular value decomposition, which effectively reduces the computational complexity. The experiment proved the effectiveness of the proposed algorithm.
Artificial Intelligence Technology Combined with Ultrasound-Guided Needle Knife Interventional Treatment of PF: Improvement of Pain, Fascia Thickness, and Ankle-Foot Function in Patients
Authors: Zhu Silai , Niu Yuli , Wang Jing , Xu Dan , Li Yong
Published: May 2022

Objective. To explore the effect of artificial intelligence (AI) technology combined with ultrasound-guided needle knife intervention in the treatment of plantar fasciitis (PF) on pain, fascia thickness, and ankle and foot function. Methods. A total of 130 patients with PF treated in our hospital from January 2019 to April 2021 were enrolled. The patients were randomly assigned into the control group and the study group. The control group received ultrasound-guided needle knife interventional therapy, and the study group received AI technology combined with ultrasound-guided needle knife interventional therapy. The curative effect, VAS score, plantar fascia thickness, plantar fascia elasticity score, plantar fascia blood flow index, and AOFAS score were investigated. Results. The total effective rate of the study group was higher compared to that of the control (P<0.05). There exhibited no significant difference in VAS score before treatment, but the VAS score of the study group was lower compared to that of the control group at 2, 4, and 8 weeks after treatment. There exhibited no significant difference in plantar fascia thickness before treatment (P>0.05), but after treatment, the plantar fascia thickness in the study group was lower compared to that in the control (P<0.05). The plantar fascia thickness in the study group was lower compared to that in the control at 2, 4, and 8 weeks after treatment (P<0.05). In terms of the plantar fascia elasticity score, there exhibited no significant difference before treatment (P>0.05), but the plantar fascia elasticity score of the study group was lower compared to that of the control at 2, 4, and 8 weeks after treatment (P<0.05). There exhibited no significant difference in plantar fascia blood flow index before treatment (P>0.05), but after treatment, the plantar fascia blood flow index in the study group was higher compared to that in the control (P<0.05). The plantar fascia blood flow index in the study group was higher compared to that in the control at 2, 4, and 8 weeks after treatment (P<0.05). There exhibited no significant difference in the AOFAS score before treatment, but after treatment, the AOFAS score of the study group was higher compared to that of the control at 2, 4, and 8 weeks after treatment. Conclusion. Patients with PF receive AI technology combined with ultrasound-guided needle knife interventional therapy, which can effectively relieve pain and improve fascia thickness and ankle-foot function. Thus, AI technology combined with ultrasound-guided needle knife interventional therapy has the advantages of convenient operation, safety, and effectiveness, which is worthy of clinical application.
Temperature and Temperature Stress Analysis in Mass Concrete under Cold Environments of Strong Wind and Large Diurnal Temperature Range
Authors: Wang Guoqing , He Meng , Zhou Canjun , Xie Wen , Liu Xinglin , Chen Jin , Liu Hua , Lei Bingbing , Zhang Mingli
Published: May 2022

Special environmental condition with strong wind and large diurnal temperature range is not conducive for the control of crack development during the curing of mass concrete in the cold environment of Northwest China. In this study, the temperature at four measured points along the vertical profile of a mass concrete was measured over 14 days. Then, a thermal-mechanical model with the optimized initial condition, thermal parameters, boundary conditions, and the effects of rebar on temperature stress of concrete was built. Based on the observations and numerical model, the effects of environmental factor on the peak temperature, temperature fluctuation amplitude, and maximum temperature stress of the mass concrete are analyzed. The result showed that increasing wind speed can reduce the temperature of the concrete, but an opposite result is observed with increase in diurnal temperature range. Moreover, the more obvious diurnal variation of concrete temperature with the increase in wind speed and diurnal temperature range is not conducive to the thermal stability of the structure, especially for horizontal and side surfaces. Accordingly, increasing wind speed and diurnal temperature range will increase the peak temperature stress of the concrete and the overall stress level. Strong wind and large diurnal temperature range significantly increase the temperature stress and its duration for the side surface. The high temperature stress and intensive daily variation of temperature stress at the horizontal surface affect the durability of the concrete material. Therefore, the temperature stresses of the horizontal surface under wind speed levels 3, 4, 5, and 1.25 times large diurnal temperature range easily exceed the tensile strength; then, the temperature crack will appear. Combined with the research results, the temperature control and crack prevention measures are proposed under the condition of ensuring concrete strength. The study will further guide the improvement and optimization of mass concrete construction in an extreme environment.
Efficient Smart Grid Load Balancing via Fog and Cloud Computing
Authors: Yu Dongmin , Ma Zimeng , Wang Rijun
Published: May 2022

As the cloud data centers size increases, the number of virtual machines (VMs) grows speedily. Application requests are served by VMs be located in the physical machine (PM). The rapid growth of Internet services has created an imbalance of network resources. Some hosts have high bandwidth usage and can cause network congestion. Network congestion affects overall network performance. Cloud computing load balancing is an important feature that needs to be optimized. Therefore, this research proposes a 3-tier architecture, which consists of Cloud layer, Fog layer, and Consumer layer. The Cloud serves the world, and Fog analyzes the services at the local edge of network. Fog stores data temporarily, and the data is transmitted to the cloud. The world is classified into 6 regions on the basis of 6 continents in consumer layer. Consider Area 0 as North America, for which two fogs and two cluster buildings are considered. Microgrids (MG) are used to supply energy to consumers. In this research, a real-time VM migration algorithm for balancing fog load has been proposed. Load balancing algorithms focus on effective resource utilization, maximum throughput, and optimal response time. Compared to the closest data center (CDC), the real-time VM migration algorithm achieves 18% better cost results and optimized response time (ORT). Realtime VM migration and ORT increase response time by 11% compared to dynamic reconFigure with load (DRL) with load. Realtime VM migration always seeks the best solution to minimize cost and increase processing time.
Traditional Chinese Medicine Constitution Discrimination Model Based on Metabolomics and Random Forest Decision Tree Algorithm
Authors: Huang Chaodong , Chen Yufeng , Li Bingtao , Zhang Qiyun , Jiang Li , Nie Bin , Chen Lihua , Jian Hui , Xu Guoliang
Published: May 2022

Constitution refers to the comprehensive and relatively stable characteristics of the genetic or acquired morphological structure, physiological function, and psychological state in the process of human individual life. A special metabolomics data processing method is established to find the unique m/z value of each constitution. Combined with the random forest decision tree algorithm, the discrimination model of 9 constitutions in traditional Chinese medicine is constructed, and the model is verified and tested. The test results show that the classification accuracy of each constitution is higher than 80%, indicating that the model can well identify nine constitutions of traditional Chinese medicine. The classification accuracy is related to the difficulty of distinguishing between constitutions. In a word, this study provides a fast and accurate method to distinguish the constitution of traditional Chinese medicine, provides an objective representation for the classification and judgment of clinical constitution of traditional Chinese medicine, and provides a scientific basis for the modernization of traditional Chinese medicine.
Citrus unshiu Peel Attenuates Dextran Sulfate Sodium-Induced Ulcerative Colitis in Mice due to Modulation of the PI3K/Akt Signaling Pathway and MAPK and NF-κB
Authors: Lee Se Hui , Lee Jin A. , Shin Mi-Rae , Park Hae-Jin , Roh Seong-Soo
Published: May 2022

Aim. Citrus unshiu peel has been used to treat various diseases in traditional East Asian medicine including Korea, and many studies have been reported regarding inflammatory diseases including ulcerative colitis (UC). However, the underlying mechanism by which Citrus unshiu peel modulates inflammation in UC remains unclear. Therefore, this study aimed to evaluate the therapeutic effect and underlying mechanism of Citrus unshiu peel water extract (CUP) for UC. Methods. The experiment for UC was conducted with 8-week-old male Balb/c mice. After 1 week of adaptation, acute colitis was induced in all groups except the normal group by 5% DSS dissolved in drinking water for 1 week. Balb/c mice were divided into 5 groups (n = 8/group): control group (Control), distilled water-treated group (DSS), 100 mg/kg sulfasalazine-treated group (SASP), 100 mg/kg CUP-treated group (CUPL), and 200 mg/kg CUP-treated group (CUPH). The efficacy of CUP on UC was evaluated by biochemical analyses such as ROS and MPO in serum and MDA in tissues, and expression of proteins related to inflammation and apoptosis was evaluated through Western blot. Results. As a result of confirming the macroscopic changes and H&E staining in colon tissues to confirm the preventive and therapeutic effects of CU, decrease in colon length and inflammatory lesions were inhibited in the CUP-treated group compared to the DSS group. In addition, as a result of serum ROS and tissue MDA analysis and oxidative stress-related protein analysis, it was significantly decreased in the CUP-administered group compared to the control group. In addition, treatment with CUP not only inactivated MAPK, p-IκBα, and NF-κBp65 by blocking the PI3K/Akt pathway but also significantly reduced the expression of inflammatory cytokines. Conclusion. These results show that CUP not only suppresses oxidative stress in UC but also regulates inflammation-related proteins and apoptotic proteins by regulating the PI3K/Akt signaling pathway, suggesting that it has the potential as a material for developing new natural therapeutic agents for UC.
Blockchain-Enabled Joint Resource Allocation for Virtualized Video Service Functions
Authors: Yu Ping , Zhao Hongwei , Yang Kun , Chen Hanlin , Geng Xiaozhong , Hu Ming , Yan Hui
Published: May 2022

Power information is an important guarantee for energy security. As an important technical means of safety management and risk control, video monitoring is widely used in the power industry. Power video monitoring system uses efficient processing of multimodal video data and automatically identifies abnormal events and equipment status, replacing human monitoring with machine. Video monitoring data of power substations usually contain both visual information and auditory information, and the data types are diversified. The multimodal video data provides a rich underlying data source for the intelligent monitoring function, but it requires multiple service forms for efficient processing. Most intelligent edge monitoring equipment are only equipped with lightweight computing resources and limited battery supply, limited resources, and weak local processing data capabilities. Power video monitoring system has the characteristics of distribution, openness, interconnection, and intellectualization. Its intelligent edge video equipment is widely distributed, which also brings convenience and also brings security risks in terms of data security and reliability. For the outdoor multimodal power video monitoring system scenario, this paper adopts the edge-cloud distributed system architecture to solve the problem of resource shortage and adopts the first proposed service function virtualization (SFV) to solve the problem of multimodal video data processing. At the same time, the problem of security protection is solved by introducing blockchain to establish trust among intelligent video equipment and service providers. Under the security protection of virtualized service consortium blockchain (VSCB), virtualization technology is introduced into the service function chain (SFC) to realize SFV and solve the resource optimal allocation problem of multimodal video data processing. The work mainly involves the joint mapping of virtual resources, physical resources, and the joint optimization of computing and communication resources. Problems such as large state space and high dimensionality of action space have an impact on resource allocation. The stochastic optimization problem of resource allocation is established as a Markov decision process (MDP) model, and SFV technology is used to optimize cost and delay. The resource allocation optimization algorithm (RAOA-A3C) based on asynchronous advantage actor-critic algorithm (A3C) is proposed. Simulation experiments show that the RAOA-A3C proposed in this paper is more suitable for high-dynamic, multidimensional, and distributed power video monitoring system scenario and has achieved better optimization results in reducing time delay and deployment costs.
Efficacy and Safety of Cangfu Daotan Decoction in Patients with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis
Authors: Wu Linling , Zhang Han , Fan Mengxiao , Yan Ying
Published: May 2022

Background. The infertility caused by polycystic ovary syndrome (PCOS) has received considerable attention. Considerable efforts have been made to improve the rates of pregnancy and live birth. Cangfu Daotan Decoction (CFDTD) is a classic prescription for treating infertility in obese women. The efficacy of CFDTD in PCOS is controversial. Objective. To evaluate the effectiveness and safety of CFDTD in treating infertility with PCOS. Methods. A literature search was performed in the Cochrane Library, PubMed, Embase, the China National Knowledge Infrastructure, the Wanfang Database, the VIP Chinese Biomedical science journal database, and the Chinese BioMedical database from the date of each database establishment to December 2021. Only randomized controlled trials, which were used to evaluate the efficacy of CFDTD in treating subjects with PCOS, were included in the present study. The quality of evidence was assessed using the Cochrane Reviewer Handbook 5.0.0, and meta-analysis was performed using RevMan 5.3.5 software. Results. Fourteen studies with a total of 1,433 patients were included in this analysis. The present study indicated that CFDTD could significantly improve pregnancy rate (RR = 1.62, 95% CI (1.44, 1.83),

P
<
0.00001

), ovulation rate (RR = 1.40, 95% CI (1.25, 1.56),

P
<
0.00001

), and estradiol levels (SMD = 0.80, 95% CI (0.03, 1.58),

P
=
0.04

), while testosterone levels (SMD = −0.92, 95% CI (−1.52, −0.31),

P
=
0.003

), homeostatic model assessment for insulin resistance (MD = −0.56, 95% CI (−0.99, −0.12),

P
=
0.01

), total cholesterol levels (MD = −0.60, 95% CI (−0.76, −0.44),

P
<
0.00001

), triglyceride levels (MD = −0.48, 95% CI (−0.60, −0.36),

P
<
0.00001

), body mass index (MD = −2.96, 95% CI (−3.88, −2.03),

P
<
0.00001

), and the incidence of adverse reactions (RR = 0.47, 95% CI (0.34, 0.65),

P
<
0.00001

) were significantly reduced. Conclusions. Evidence from the meta-analysis suggested that CFDTD appeared to be an effective and relatively safe treatment for PCOS. However, the influence of CFDTD on reproductive hormones, glucose metabolism, and blood lipids should be carefully concluded. Due to the low quality of the methods used in the included randomized controlled trials, further studies are required with larger sample sizes and well-designed models to confirm our findings.
Exploring Endothelial Colony-Forming Cells to Better Understand the Pathophysiology of Disease: An Updated Review
Authors: Zhang Qiuwang , Cannavicci Anthony , Kutryk Michael J. B.
Published: May 2022

Endothelial cell (EC) dysfunction has been implicated in a variety of pathological conditions. The collection of ECs from patients is typically conducted postmortem or through invasive procedures, such as surgery and interventional procedures, hampering efforts to clarify the role of ECs in disease onset and progression. In contrast, endothelial colony-forming cells (ECFCs), also termed late endothelial progenitor cells, late outgrowth endothelial cells, blood outgrowth endothelial cells, or endothelial outgrowth cells, are obtained in a minimally invasive manner, namely, by the culture of human peripheral blood mononuclear cells in endothelial growth medium. ECFCs resemble mature ECs phenotypically, genetically, and functionally, making them excellent surrogates for ECs. Numerous studies have been performed that examined ECFC function in conditions such as coronary artery disease, diabetes mellitus, hereditary hemorrhagic telangiectasia, congenital bicuspid aortic valve disease, pulmonary arterial hypertension, venous thromboembolic disease, and von Willebrand disease. Here, we provide an updated review of studies using ECFCs that were performed to better understand the pathophysiology of disease. We also discuss the potential of ECFCs as disease biomarkers and the standardized methods to culture, quantify, and evaluate ECFCs and suggest the future direction of research in this field.
Aucubin Exerts Anticancer Activity in Breast Cancer and Regulates Intestinal Microbiota
Authors: Shao Min , Kuang Ziyun , Wang Wenlin , Li Shengnan , Li Guizhen , Song Yu , Li Haitao , Cui Guozhen , Zhou Hefeng
Published: May 2022

Aucubin, a natural compound isolated from herbal medicine, has been reported to possess multiple beneficial properties. In this study, we aimed to verify the anticancer effect of aucubin on breast cancer and investigate the effect of cancer on the intestinal flora and whether aucubin has a therapeutic effect on intestinal problems caused by cancer. We established the breast cancer model with mouse 4T1 cell line and BALB/c mice. Aucubin was given once a day by gavage for 14 days. The results showed that aucubin suppress the growth of tumor in vivo by inducing tumor cell apoptosis. The tumor suppression rate of aucubin could reach 51.31 ± 4.07%. Organ histopathology was evaluated by tissue staining, which demonstrated that aucubin could alleviate the organ inflammatory damage caused by breast cancer without visible side effects. Moreover, aucubin could increase the expression of colonic tight junction protein occluding and adjust the gut microbiome to normal level according to 16S rDNA high-throughput sequencing. Herein, our results provide evidence for developing aucubin as an alternative and safe therapeutic for breast cancer treatment.
Effectiveness of Artificial Intelligence Multimedia Courseware in Classroom Teaching Application
Authors: Chen Yu , Chen Zhong
Published: May 2022

In the information age, traditional teaching methods can no longer meet the needs of modern students, and the emergence of multimedia courseware teaching mode just solves this problem. Under the trend of education integration, multimedia courseware is becoming more and more important in classroom teaching. Aiming at the characteristics of AI multimedia courseware classroom teaching mode, we discuss the practical application of AI multimedia courseware in classroom teaching and study the classroom teaching mode. Building a distance education platform through network technology can promote the education level. At the same time, the interactive distance education platform serves as a new network platform for system users in the website. In order to speed up the process of education informationization and improve the quality of education, this paper uses .NET technology and video transmission technology to design and implement a multiperson video conversation interactive distance education platform. Through the comparative experiment of two classes in Chengguan Middle School, using this platform for teaching, the average grade of students and the average grade of each course are better than the average grade of nonplatform classes, and the student’s cognitive level has improved and is higher than the same level class. The results show that this platform can support a large number of online users and is very good for students of different majors. Through flexible and interactive course interaction, students are more convenient and more independent to learn but also reduce the teacher’s time cost and greatly play the advantages of distance education, and the English teaching mode of artificial intelligence multimedia courseware is very popular with students. More than 60% of teachers are satisfied with the teaching mode and above.
Transit Route Optimization for Cable Crane Exposure Reduction Using NSGA-II Algorithm Based on Neural Networks
Authors: Chen Shu , Tian Ya , Chen Yun , Xi Junbo
Published: May 2022

Owing to frequent man-machine interaction, cable crane operation during the dam construction becomes an intensive dangerous special equipment and easily enlarge exposure. In particular, high wind weather increases the risk of falling objects at high altitude and enhance the impact space of cable crane. These factors lead to space conflicts in the limited space, and prone to accidents. However, previous studies mainly focused on safety monitoring through various technologies, but lack of sufficient prior control, and current methods for searching the optimal transit route of cable crane are insecure and insufficient since the wind environment, complex construction process, and dense man-machine interaction are not simultaneously considered. Thus, in this article, a transit route optimization method for cable crane exposure considering dynamic wind loads during the dam construction is proposed to reduce hazard exposure risk. A comprehensive evaluation function is constructed to assess the cable crane transit route with taking the hazard exposure, efficiency, and operability and collision risk into consideration. The objective is to make use of the NSGA-II algorithm to optimize the transit route under different working situations based on neural networks. The model feasibility is validated by applying it to the Dagangshan hydropower station. A set of results show that the novel methodology is able to reduce exposure and assess the comprehensive performance of different transit route. This method provides an important objective and precise evaluation tool for the cable crane optimal transit route, and also promotes safety management in the project.
Analysis on the Three-Dimensional Intervention Mode of Public Art in Rural Culture from the Perspective of 3D Video
Authors: Li Xiang , Liu Hang
Published: May 2022

With the development of 3D technology, based on the perspective of 3D video, this paper analyzes the principle of 3D video, establishes the perspective model of 3D video, and discusses the modeling process in detail. Then, from the perspective of 3D video, this paper studies the three-dimensional intervention model of public art in Beijing, Shanghai, Chongqing, and Tianjin. Through the combination of public art and rural culture, the countryside can obtain vitality through art and popularize and promote rural culture and image. In general, this paper provides some ideas and experience for the research of public art in rural culture from the perspective of 3D video.
Location-Query-Privacy and Safety Cloaking Schemes for Continuous Location-Based Services
Authors: Gutiérrez-Soto Claudio , Galdames Patricio , Faúndez Carlos , Durán-Faúndez Cristian
Published: May 2022

Nowadays, people can access a wide range of applications and services for mobile device users. Among them, location-based services (LBS), where the application needs the user’s position to provide the service. Some examples of these applications are Uber and Waze. Nevertheless, the repetitive use of an LBS can reveal confidential user information; thus, behavior patterns—such as daily routes—could be deduced by some dishonest LBS. Furthermore, a query’s keywords could provide information about a user’s health status or future position when it inquires about hospitals or hotels. Therefore, an adversary can use this information for unethical purposes, and users need mechanisms that protect their privacy. At present, several approaches separately tackle location privacy, location security, and query privacy. To the best of our knowledge, no previous work deals with all these mentioned aspects simultaneously especially when users demand continuous protection when moving and accessing an LBS. This paper proposes two batch techniques to provide location privacy, location safety, and query privacy in an environment that considers a continuous LBS. These techniques apply

l

-diversity (query privacy) in a context that contemplates query semantics, as well as a diverse set of users’ paths. Extensive experimentation shows that both techniques are cost-effective and scalable solutions that offer unified location privacy, query privacy, and location safety protection for many mobile users.
Commonα-Fuzzy Fixed Point Results for Kannan Type Contractions with Application
Authors: Albargi Amer Hassan , Ahmad Jamshaid
Published: May 2022

The purpose of this paper is to utilize complex valued extendedb-metric space and obtain commonα-fuzzy fixed point theorems under Kannan type contractions. As application, we derive commonα-fixed point results for multivalued mappings in the context of complex valued extendedb-metric space.
A Cross-Media Advertising Design and Communication Model Based on Feature Subspace Learning
Authors: Li Shanshan
Published: May 2022

This paper uses feature subspace learning and cross-media retrieval analysis to construct an advertising design and communication model. To address the problems of the traditional feature subspace learning model and make the samples effectively maintain their local structure and discriminative properties after projection into the feature space, this paper proposes a discriminative feature subspace learning model based on Low-Rank Representation (LRR), which explores the local structure of samples through Low-Rank Representation and uses the representation coefficients as similarity constraints of samples in the projection space so that the projection subspace can better maintain the local nearest-neighbor relationship of samples. Based on the common subspace learning, this paper uses the extreme learning machine method to improve the cross-modal retrieval accuracy, mining deeper data features and maximizing the correlation between different modalities, so that the learned shared subspace is more discriminative; meanwhile, it proposes realizing cross-modal retrieval by the deep convolutional generative adversarial network, using unlabeled samples to further explore the correlation of different modal data and improve the cross-modal performance. The clustering quality of images and audios is corrected in the feature subspace obtained by dimensionality reduction through an optimization algorithm based on similarity transfer. Three active learning strategies are designed to calculate the conditional probability of unannotated samples around user-annotated samples in the correlation feedback process, thus improving the efficiency of cross-media retrieval in the case of limited feedback samples. The experimental results show that the method accurately measures the cross-media relevance and effectively achieves mutual retrieval between image and audio data. Through the study of cross-media advertising design and communication models based on feature subspace learning, it is of positive significance to advance commercial advertising design by guiding designers and artists to better utilize digital media technology for artistic design activities at the level of theoretical research and applied practice.
Increased PD-L1 Restricts Liver Injury in Nonalcoholic Fatty Liver Disease
Authors: Dong Gang , Huang Xiaoquan , Chen Rongxin , Wu Ling , Jiang Siyu , Chen Shiyao
Published: May 2022

PD-L1 is a critical checkpoint that protects tissues from autoimmune injury. Nevertheless, the role of PD-L1 in nonalcoholic fatty liver disease- (NAFLD-) induced liver damage is still unclear. In this study, we examined the role and mechanism of PD-L1 expression on NAFLD-induced liver damage in vitro and in vivo. PD-L1 expression in the livers from patients with NAFLD, and LO2 cells treated by FFA, was significantly increased. FFA triggers a large amount of ROS (generated from NOX4 and damaged mitochondria), promoting the ZNF24 expression and suppressing ZN24 sumoylation, both of which enhance the PD-L1 transcription and expression. The knockdown of PD-L1 increases CD8 + T cells’ damage to FFA-treated LO2 cells, while its upregulation limits the liver injury in NAFLD models. Collectively, we demonstrate that FFA promotes PD-L1 expression through the ROS/ZNF24 pathway and suppresses UBE2I-mediated ZNF24 sumoylation to enhance its transcriptional activity of PD-L1. PD-L1 upregulation limits FFA-induced injury of hepatocytes in vitro and in vivo.
The Impact of Digital Transformation on Environmental Sustainability
Authors: Truong Thanh Cong
Published: May 2022

Recently, digital transformation is supposed to affect all aspects of human life profoundly. Nevertheless, there is a lack of summaries map digital transformation in the environmental sustainability domain. To address this knowledge gap, this study examines the impacts of digital transformation on environmental sustainability, including both positive and negative effects. Furthermore, the results highlight the transformations that preserve the environment in three main areas: waste management and handling, pollution prevention and control, and sustainable resource management. Based on the literature summary, this study also discusses the opportunities and challenges in this field, which attempts to offer a vision for further research.
Clinical Observation of MRI Scanning Combined with Clinical Nursing for Surgical Breast Cancer Patients
Authors: Zhang Huan , Yin Yanan , Tao Wenjing , Liu Ling
Published: May 2022

The aim of this study was to explore the application effect of perioperative nursing care for patients with breast cancer. In this paper, 100 breast cancer patients with lymphatic spread treated by breast surgery in September 2019 to December were selected as the evaluation objects. They were divided into two groups according to preoperative imaging examination, 50 cases in each group. Group A was examined by B-ultrasound before axillary lymphadenectomy, group B was examined by MRI before axillary lymphadenectomy, and group C was examined by B-ultrasound and MRI before axillary lymphadenectomy. The facts in the three groups of disease findings were compared. Compared with the control group, the proportion of negative emotions (such as stress and depression) in the control group decreased (P<0.05). The decrease in blood cortisol was higher than in the control group (

P
<
0.05

). Improving the existing cancer surgery can improve the patient’s heart rate and reduce blood cortisol so as to improve the patient’s joint function and quality of life. The difficulty of nursing patients will also be reduced, which is medically necessary.
A Novel Deep Learning Network and Its Application for Pulmonary Nodule Segmentation
Authors: Lu Dechuan , Chu Junfeng , Zhao Rongrong , Zhang Yuanpeng , Tian Guangyu
Published: May 2022

Pulmonary nodules are the early manifestation of lung cancer, which appear as circular shadow of no more than 3 cm on the computed tomography (CT) image. Accurate segmentation of the contours of pulmonary nodules can help doctors improve the efficiency of diagnosis. Deep learning has achieved great success in computer vision. In this study, we propose a novel network for pulmonary nodule segmentation from CT images based on U-NET. The proposed network has two merits: one is that it introduces dense connection to transfer and utilize features. Additionally, the problem of gradient disappearance can be avoided. The second is that it introduces a new loss function which is tolerance on the pixels near the borders of the nodule. Experimental results show that the proposed network at least achieves 1% improvement compared with other state-of-art networks in terms of different criteria.
Real-Time NURBS Interpolation under Multiple Constraints
Authors: Nie Mingxing , Wan Yaping , Zhou Aijun
Published: May 2022

NURBS interpolation is superior to traditional linear or circular interpolation in terms of code size, surface quality, and machining efficiency. However, with the increasing demands for high-accuracy and efficient machining, NURBS interpolation has faced a growing number of challenges. Many researchers are actively involved in this field with great interest. Due to the special form of NURBS curve, there is a nonlinear relationship between its curve and arc length; feed fluctuations and mechanical shocks which are caused during the interpolation process will seriously affect the surface accuracy and quality of machined parts. To solve these problems, a real-time NURBS interpolation is proposed under multiple constraints (RNIC) in this paper. First, the formulas of the constrained feedrate under geometric errors, kinematic constraints, drive constraints, and contour errors are given. Then, the two stages for the proposed interpolation are established. The former stage is offline preprocessing stage, which aims to quickly find feedrate sensitive areas (FSAs), while the latter online stage is the real-time interpolation, which is responsible for smoothing the velocity. In the preprocessing stage, we utilized FSA scan module and feedrate adjustment module to detect the FSAs and adjust the feedrate at the start/end of each subsegment by a bidirectional scanning algorithm. Each segment contains acceleration and deceleration (some contains uniform speed) stages, which can be well matched with the processing process of acceleration and deceleration. Finally, according to the proposed method and the adaptive speed adjustment method, the simulation of a “butterfly-shaped” NURBS curve using the S-shaped ACC/DEC algorithm is carried out, which verifies the reliability and effectiveness of the proposed algorithm.
An Improved JADE Hybridizing with Tuna Swarm Optimization for Numerical Optimization Problems
Authors: Tan MuLai , Li YinTong , Ding DaLi , Zhou Rui , Huang ChangQiang
Published: May 2022

In this paper, we propose IJADE-TSO, a novel hybrid algorithm in which an improved adaptive differential evolution with optional external archive (IJADE) has been combined with the tuna swarm optimization (TSO). The proposed algorithm incorporates the spiral foraging search and parabolic foraging search of TSO into the mutation strategy in IJADE to improve the exploration ability and population diversity. Additionally, to enhance the convergence efficiency, crossover factor (CR) ranking, CR repairing, top α r1 selection, and population linear reduction strategies have been included in the algorithm. To evaluate the superiority of the proposed algorithm, IJADE-TSO has been benchmarked with its state-of-the-art counterparts using the CEC 2014 test set. Finally, to check the validity of IJADE-TSO, we apply it to photovoltaic (PV) parameter identification and compare its performance with those of other recently developed well-known algorithms. The statistical results reveal that IJADE-TSO outperforms the other compared algorithms.
Biophysical Model: A Promising Method in the Study of the Mechanism of Propofol: A Narrative Review
Authors: Li Zhen , Liu Jia , Liang Huazheng
Published: May 2022

The physiological and neuroregulatory mechanism of propofol is largely based on very limited knowledge. It is one of the important puzzling issues in anesthesiology and is of great value in both scientific and clinical fields. It is acknowledged that neural networks which are comprised of a number of neural circuits might be involved in the anesthetic mechanism. However, the mechanism of this hypothesis needs to be further elucidated. With the progress of artificial intelligence, it is more likely to solve this problem through using artificial neural networks to perform temporal waveform data analysis and to construct biophysical computational models. This review focuses on current knowledge regarding the anesthetic mechanism of propofol, an intravenous general anesthetic, by constructing biophysical computational models.
Extracellular Vesicle-Derived circITGB1 Regulates Dendritic Cell Maturation and Cardiac Inflammation via miR-342-3p/NFAM1
Authors: Zhu Jianbing , Chen Zhaoyang , Peng Xiaoping , Zheng Zeqi , Le Aiping , Guo Junjie , Ma Leilei , Shi Hongtao , Yao Kang , Zhang Shuning , Ge Junbo , Zheng Zhenzhong , Wang Qian
Published: May 2022

Acute myocardial infarction (AMI) is a complication of atherosclerosis-related cardiovascular illness that is caused by prolonged ischemia. Circular RNAs (circRNAs) are concentrated in extracellular vesicles (EVs) and have been linked to cardiovascular disease. However, additional research is needed into the expression and function of circRNAs in AMI. In this study, circITGB1 (has_circRNA_0018146), derived from exon 1 of the ITGB1 gene localized on chromosome 10, was shown to be considerably increased in plasma from patients with AMI compared to healthy controls, as demonstrated by the comparison of EV-circRNA expression patterns. Using a luciferase screening assay and a biotin-labeled circITGB1 probe to identify microRNA(s) complementary to circITGB1 sequences, we discovered that circITGB1 competitively binds to miR-342-3p and inhibits its expression, which in turn increase the expression of NFAT activating molecule 1 (NFAM1). Based on western blotting and immunological studies, circITGB1 controls dendritic cell maturation by targeting miR-342-3p and NFAM1. circITGB1 also exacerbated cardiac damage and regulated miR-342-3p and NFAM1 expression in a mouse AMI model. This implies that EV-circITGB1 is involved in dendritic cell maturation and cardiac damage via miR-342-3p/NFAM1, and that is linked to AMI-associated pathogenic processes.