bluuebunny/crossref_metadata_2025 huggingface dataset:
Visual Communication Design Based on 5G Technology
Authors: Chen Yu
Published: March 2022

The progress of science and technology and the rapid development of the Internet have made the visual communication design full of unprecedented yearning and passion for the new scientific and technological civilization. This research mainly discusses the visual communication design under 5G technology. For the fifth generation mobile communication technology (5G), its brand new network architecture design can provide 10 to 20 times higher peak rate, millisecond-level network transmission delay, and 100 billion device-level network connectivity than 4G. It will open up a new era of extensive interconnection of all things and deep human-computer interaction for human society. This paper starts with the relationship between visual communication and various media, so as to prove that the development of mobile media will be inevitable, especially in environment, the visual expression and the innovation in design style. In order to reflect the inner will of the audience in the environment of rapid development of information, this article. It analyzes the changes brought by the development of mobile media to the visual communication design at this stage, predicts the development trend of visual communication, and tries to point out that the development of 5G communication technology is bringing a new round of revolution to the design industry. As a design researcher, it should pay attention to the impact of technological changes on the design field. By exploring suitable design methods, the application of visual communication in mobile media under 5G technology conditions can be better realized. Starting from the background of the evolution and development of media, this paper analyzes the reasons for the rise of 5G technology, as well as the characteristics of 5G technology and its advantages in communication. At the same time, it deeply analyzes the connotation and involved fields of visual communication design and expounds the promotion and influence of the reform of media technology. It focuses on analyzing the development level of 5G technology and the new thinking brought by visual communication design. The article also puts forward the origin of the research. 58.1% of the evaluators were satisfied with the impact of 5G technology on visual communication. Visual design, interaction design, and usability design are all indispensable factors in interface design. When designing, they are not designed in isolation from each other but interact with each other. When carrying out any one of the designs, the design influence of the other two should be combined, and the changes of each one should affect the design of the other two. For example, interaction design and usability issues must be considered when determining the visual presentation of an interface. It can be seen that the design process of the interface is a comprehensive design process. This research helps to advance the development of visual communication design in the future.
Learning‐Based Path Planning Algorithm in Ocean Currents for Multi‐Glider
Authors: Lan Wei , Jin Xiang , Chang Xin , Wang Tianlin , Zhou Han
Published: March 2022

In practical application studies of glider formations, ocean currents are a major influencing factor in their path planning. The purpose of this paper is to solve the path planning problem of glider formations in time‐varying ocean currents and establish gliders, glider formation, and ocean current models based on existing data. The Doc‐CNN architecture is tailored to conform to the operation and environment characteristics of gliders in practical application. After experiments, the algorithm of the improved architecture can be used in the path planning task of glider formation. The algorithm architecture is compared and tested on two datasets, grid maps and ocean maps. Doc‐CNN has an advantage over architecture without being tailored to glider characteristics and makes full use of known global information and local information collected by gliders themselves. The results show that the path planning problem of glider formation in ocean currents can be solved by using Doc‐CNN.
Human Papillomavirus Type 16 Early Protein E7 Activates Autophagy through Inhibition of Dual-Specificity Phosphatase 5
Authors: Hua Chunting , Zheng Qiaoli , Zhu Jiang , Chen Siji , Song Yinjing , van der Veen Stijn , Cheng Hao
Published: March 2022

Consistent high-risk human papillomavirus (HPV) infection leads to various malignant cancers. Autophagy can promote cancer progression by helping cancer cells survive under stress or induce oncogenic effects when mutations or abnormalities occur. Mitogen activated protein kinases (MAPKs) can transduce various external or intrinsic stimuli into cellular responses, including autophagy, and dual-specificity phosphates (DUSPs) contribute to the direct regulation of MAPK activities. Previously, we showed that expression of DUSP5 was repressed in HPV16 E7-expressing normal human epidermal keratinocytes (NHEKs). Here we show that clinical HPV16 E7-positive precancerous and cancerous tissues also demonstrate low DUSP5 levels compared with control tissues, indicating that the inverse correlation between HPV16 E7 and DUSP5 is clinically relevant. We furthermore investigated the autophagy response in both DUSP5-deficient and HPV16 E7-expressing NHEKs. Confocal microscopy and Western analysis showed induction of LC3-II levels, autophagosome formation and autophagy fluxes in DUSP5-deficient NHEKs. Furthermore, Western analysis demonstrated specific induction of phosphorylated ERK in DUSP5-deficient and HPV16 E7-expressing NHEKs, indicating that HPV16 E7-mediated repression of DUSP5 results in induced MAPK/ERK signaling. Finally, phosphorylated mTOR and ULK (S757) were reduced in DUSP5-deficient NHEKs, while phosphorylated ULK (S555) and AMPK were increased, thereby inducing canonical autophagy through the mTOR and AMPK pathways. In conclusion, our results demonstrate that HPV16 E7 expression reduces DUSP5 levels, which in turn results in active MAPK/ERK signaling and induction of canonical autophagy through mTOR and MAPK regulation. Given its demonstrated inverse correlation with clinical cancerous tissues, DUSP5 may serve as a potential therapeutic target for cervical cancer.
Effect Evaluation of Artificial Intelligence-Based Electronic Health PDCA Nursing Model in the Treatment of Mycoplasma Pneumonia in Children
Authors: Zhao Yan
Published: March 2022

The PDCA cycle, also known as Deming's cycle, mainly includes four stages: planning, implementation, inspection, and processing. As a kind of atypical pneumonia with fever and cough, mycoplasma pneumonia harms the health of many children. The purpose of this study is to investigate the anti-inflammatory and antimycoplasma effects and safety of artificial intelligence e-health PDCA nursing mode on pediatric MPP, to investigate its clinical efficacy, to observe the changes of serum cytokines (IL-10, IL-2, IL-4, IFN-γ), and to explore the mechanism of action and possible targets for the treatment of MPP, to provide a new basis for clinical treatment of MPP. The experimental results show that in the experimental group using PDCA nursing mode, the total satisfaction is 97.22%, higher than the control group of 94.44%; in the experimental group, the hospital stay and symptom disappearance time were significantly shortened by four hours. The satisfaction of nursing staff was significantly increased in statistical significance

P
<
0.05

. Therefore, in a statistical sense, the artificial intelligence e-health PDCA nursing mode can significantly improve the clinical symptoms of MPP children with wind-heat stagnation of lung syndrome and phlegm-heat closure of lung syndrome, improve the treatment effect of childhood mycoplasma pneumonia epidemic, shorten the time of hospitalization and symptom disappeared, and play a great auxiliary role in the treatment of childhood mycoplasma pneumonia.
Experimental Study on the Reliability of an Active Unloading System for Strengthening of Reinforced Concrete Columns
Authors: Wang Yongquan , Li Tianfu , Dong Kaifa , Guo Zhengxing , Fu Jing
Published: March 2022

In strengthening and retrofitting of reinforced concrete (RC) frame structures, especially in the case of column replacement, unloading of existing columns usually plays an important part in the construction. However, the reliability of the commonly used active unloading system for RC columns can only be evaluated by real‐time monitoring of the unloading status during the construction process, which will threaten the safety of the personnel and structures, especially in the case of unloading with large amplitude. In addition, the commonly adopted passive unloading methods are unable to actively control the unloading force. Therefore, an unloading scheme with active control of the unloading process was proposed, and its reliability was experimentally investigated in the present study. According to the requirements of the unloading force, an active unloading self‐balancing system using the steel diagonal braces and prestressed steel tie rods was designed for the RC column structure. The vertical load was applied by a hydraulic jack mounted on top of the RC column, and the real‐time monitoring data analysis was adopted to verify the feasibility of the active unloading plan and the reliability of the force transmission. The test results indicated that the proposed active unloading control technology is reliable in force transmission.
Therapy-resistant and -sensitive lncRNAs, SNHG1 and UBL7-AS1 promote glioblastoma cell proliferation
Authors: Cao Mei , Ma Rong , Li Huaqing , Cui Juan , Zhang Chi , Zhao Jian
Published: March 2022

The current treatment options for glioblastoma (GBM) can result in median survival of 15-16 months only, suggesting the existence of therapy-resistant factors. Emerging evidence suggests that long non-coding RNAs (lncRNAs) play an essential role in the development of various brain tumors, including GBM. This study aimed to identify therapy-resistant and therapy-sensitive GBM associated lncRNAs and their role in GBM. We conducted a genome-wide transcriptional survey to explore the lncRNA landscape in 195 GBM brain tissues. Cell proliferation was evaluated by CyQuant assay and Ki67 immunostaining. Expression of MAD2L1 and CCNB2 was analyzed by western blotting. We identified 51 lncRNAs aberrantly expressed in GBM specimens compared with either normal brain samples or epilepsy non-tumor brain samples. Among them, 27 lncRNAs were identified as therapy-resistant lncRNAs that remained dysregulated after both radiotherapy and chemoradiotherapy; while 21 lncRNAs were identified as therapy-sensitive lncRNAs whose expressions were reversed by both radiotherapy and chemoradiotherapy. We further investigated the potential functions of the therapy-resistant and therapy-sensitive lncRNAs and demonstrated their relevance to cell proliferation. We also found that the expressions of several lncRNAs, including SNHG1 and UBL7-AS1, were positively correlated with cell-cycle genes’ expressions. Finally, we experimentally confirmed the function of a therapy-resistant lncRNA, SNHG1, and a therapy-sensitive lncRNA, UBL7-AS1, in promoting cell proliferation in GBM U138MG cells. Our in vitro results demonstrated that knockdown of SNHG1 and UBL7-AS1 showed an additive effect in reducing cell proliferation in U138MG cells.
Pick-Up and Delivery Problem for Sequentially Consolidated Urban Transportation with Mixed and Multi-Pupropse Vehicle Fleet
Authors: Chen Haoye , Hatzenbühler Jonas , Jenelius Erik
Published: March 2022

Different urban transportation flows (e.g., passenger journeys, freight distribution, and waste management) are conventionally separately handled by corresponding single-purpose vehicles (SVs). The multi-purpose vehicle (MV) is a novel vehicle concept that can enable the sequential sharing of different transportation flows by changing the so-called modules, thus theoretically improving the efficiency of urban transportation through the utilization of higher vehicles. In this study, a variant of the pick-up and delivery problem with time windows is established to describe the sequential sharing problem considering both MVs and SVs with features of multiple depots, partial recharging strategies, and fleet sizing. MVs can change their load modules to carry all item types that can also be carried by SVs. To solve the routing problem, an adaptive large neighborhood search (ALNS) algorithm is developed with new problem-specific heuristics. The proposed ALNS is tested on 15 small-size cases and evaluated using a commercial MIP solver. Results show that the proposed algorithm is time-efficient and able to generate robust and high-quality solutions. We investigate the performance of the ALNS algorithm by analyzing convergence and selection probabilities of the heuristic solution that destroy and repair operators. On 15 large-size instances, we compare results for pure SV, pure MV, and mixed fleets, showing that the introduction of MVs can allow smaller fleet sizes while approximately keeping the same total travel distance as for pure SVs.
Inhibition of Axl Promotes the Therapeutic Effect of Targeted Inhibition of the PI3K/Akt Pathway in NRAS Mutant Melanoma Cells
Authors: Gao Xuejun , Xue Dandan , Cheng Jingjing , Zhang Xin , Cai Xia
Published: March 2022

Melanoma is a malignant tumor produced by highly aggressive and metastatic melanocytes. NRAS mutation is a relatively common mutation in melanoma cells. Mitogen-activated protein kinase (MAPK) signaling pathway and the PI3K/Akt pathway in melanoma cells are relatively common signaling pathways. In this study, we investigated the effect of inhibition of Axl expression on the targeted inhibition of the PI3K/Akt pathway in NRAS-mutant melanoma cells. In this study, immunohistochemistry and western blot methods were used to detect the expression of Axl and Akt proteins in melanoma cells. Axl inhibitor was added, and it detected the inhibitory efficiency of Akt inhibitor in melanoma cells. Finally, a melanoma mouse model was established, and it detected the proliferation and apoptosis of mouse tumor cells induced by Axl inhibitor and Akt inhibitor. The results showed that Axl and Akt were highly expressed in NRAS-mutant melanoma cells, and stimulation of Axl expression could reduce the inhibitory effect of Akt inhibitor on melanoma cells. The addition of Axl inhibitor can synergistically promote the effect of Akt inhibitor, slow down the proliferation of tumor cells, and induce cell apoptosis. According to the experiment in this study, Axl inhibitor combined with Akt inhibitor has a stronger therapeutic effect on melanoma than Akt inhibitor alone.
Uncovering the Immune Cell Infiltration Landscape in Low-Grade Glioma for Aiding Immunotherapy
Authors: Yang Youyuan , Tian Yue , Li Qing , Jiang Rui , Zhang Junfeng
Published: March 2022

Objective. Low-grade glioma (LGG) mainly threatens the elderly population, with undesirable prognoses. This study uncovered the immune cell infiltration (ICI) landscape in LGG. Methods. RNA-seq profiles of LGG were retrieved from TCGA and CGGA databases. CIBERSORTx and ESTIMATE algorithms were employed to characterize the ICI landscape in LGG tissues. Through unsupervised clustering analysis, ICI subtypes were clustered. ICI scores were computed via principal component analysis (PCA). The differences in survival, tumor-infiltrating immune cells, stromal scores, immune scores, immune checkpoint genes, immune activity genes, and tumor mutation burden (TMB) were assessed between high and low ICI score groups. Results. Three ICI subtypes were constructed in LGG, with distinct survival outcomes, PD-L1 expression, and infiltration levels of immune cells. Furthermore, ICI scores were developed. Both in TCGA and CGGA datasets, low ICI scores were indicative of undesirable outcomes. High ICI scores were significantly correlated to increased infiltration levels of memory B cells, CD8 T cells, CD4 naïve T cells, T follicular helper cells, macrophages M0, and eosinophils, while low ICI scores were characterized by increased infiltration levels of naïve B cells, plasma cells, CD4 memory resting T cells, Tregs, resting NK cells, macrophages M2, and activated dendritic cells. High ICI scores exhibited correlations with lower immune activity genes and immune checkpoint genes. Furthermore, TMB was distinctly reduced in the high ICI score group. Conclusion. The ICI scores may serve as a promising prognostic index and predictive indicator for immunotherapies, extending our understanding of immune microenvironment in LGG.
Association between Maternal Thyroxine and Risk of Fetal Congenital Heart Defects: A Hospital-Based Cohort Study
Authors: Dong Jing , Peng Ting , Li Ming-Qing , Xie Feng , Wu Jiang-Nan
Published: March 2022

Background. Evidence for the association between maternal thyroxine concentration and the risk of fetal congenital heart defects (CHDs) is absent. We aimed to study the association of maternal free and total thyroxine (FT4 and TT4) concentrations and the free-to-total thyroxine proportion (FTT4P, %) with the risk of CHD. Methods. The study was a hospital-based cohort study of 52,047 women who received a universal thyroid function test between 2012 and 2016. CHD was screened by ultrasound between 20 and 24 weeks of gestation or diagnosed until the 42nd day of birth. Adjusted odds ratios (ORs) of fetal CHD were estimated for maternal FT4 and TT4 concentrations or the FTT4P by multivariate logistic regression. Results. A total of 41,647 women with singleton pregnancies were included for the analysis and 215 CHD cases were detected. The FT4 concentration was significantly associated with a higher risk of CHDs (OR, 1.04, 95% confidence interval (CI): 1.01 to 1.07). Each 1% higher FTT4P was related to a 1.41-fold (95% CI: 0.27 to 3.59) higher risk of CHDs. The association became stronger for women with a thyroid function test performed between 12 and 18 weeks of gestation (OR = 1.05 (95% CI: 1.01 to 1.09) for the FT4 concentration and 3.32 (95% CI: 1.43 to 7.73) for the FTT4P). Conclusions. A higher FT4 concentration or FTT4P, measured between 12 and 18 weeks of gestation, was associated with an increased risk of CHDs. These findings may provide new insights into the mechanisms of CHDs and evidence for clinical decisions related to thyroid function tests.
[Retracted] Facile and straightforward synthesis of Hydrazone derivatives
Authors: Ain Noor ul , Ansari Tariq Mahmood , Shah Gilani M. Rehan H. , Xu Guobao , Liang Gaolin , Luque Rafael , Alsaiari Mabkhoot , Jalalah Mohammed
Published: March 2022

This study was undertaken to report the swift, facile and convenient synthesis of novel hydrazones obtained by condensation reaction between 2‐Amino‐3‐formylchromone and hydrazine derivatives. Various characterization techniques such as MALDI Mass, FTIR, 1HNMR and 13CNMR spectrum analysis was done to determine the chemical structure of these novel six hydrazones. Furthermore, UV‐Vis and fluorescence spectra was studied to calculate λmax and εmax. These hydrazones are quite useful for their facile synthesis and chemical structure. Such hydrazones require separate clinical research to find their applications in biomedical fields.
LncSNHG1 Promoted CRC Proliferation through the miR-181b-5p/SMAD2 Axis
Authors: Huang Qi , Yang Zhi , Tian Jin-hai , You Pei-dong , Wang Jia , Ma Rong , Yu Jingjing , Zhang Xu , Cao Jia , Cao Jie , Wang Li-bin
Published: March 2022

Objective. To investigate the effects of LncRNA SNHG1 on the proliferation, migration, and epithelial-mesenchymal transition (EMT) of colorectal cancer cells (CRCs). Methods. 4 pairs of CRC tissue samples and their corresponding adjacent samples were analyzed by the human LncRNA microarray chip. The expression of LncSNHG1 in CRC cell lines was verified by qRT-PCR. Colony formation assays and CCK8 assays were applied to study the changes in cell proliferation. The transwell assay and wound healing experiments were used to verify the cell invasion and migration. EMT progression was confirmed finally. Results. LncSNHG1 was overexpressed both in CRC tissues and cell lines, while the miR-181b-5p expression was decreased in CRC cell lines. After knock-down of LncSNHG1, the proliferation, invasion, and migration of HT29 and SW620 cells were all decreased. Meanwhile, LncSNHG1 enhanced EMT progress through regulation of the miR-181b-5p/SMAD2 axis. Conclusion. LncSNHG1 promotes colorectal cancer cell proliferation and invasion through the miR-181b-5p/SMAD2 axis.
Optimal Model of Horse Racing Competition Decision Management Based on Association Rules and Neural Network
Authors: Zhang Shuang
Published: March 2022

With the vigorous development of horse racing, people’s attention to horse racing has increased significantly. Some experts and scholars have conducted research on the decision-making management and predictive analysis methods of horse racing. Today, with the rapid development of information technology, the amount of data and data dimensions of horse racing competitions continue to explode. The increase in data scale and feature dimensions provides new challenges for competition management and competition prediction research. At present, traditional prediction algorithms can no longer meet the needs of horse racing situation prediction, but research has found that association rules and neural network algorithms provide a good solution to the classification and prediction problem. Based on the advantages of association rules and neural networks in analyzing data, according to the requirements of horse racing decision management, this paper adopts the B/S structure to realize the construction of the horse racing decision management optimization model from the three aspects of hierarchical structure, functional structure, and forecasting process. Combined with the horse racing decision management optimization model, based on a large number of experimental training data, the final conclusion is drawn: first, the factors that affect the horse racing performance are from large to small. The order of arrangement is: race schedule > age > gender > weight > rating > horse top three rate > jockey > weight load > harness > ranking > field nature > field > trainer; the second is the prediction and actual results of the neural network algorithm. The closest one, which is slightly higher than 90%, has the highest prediction accuracy; third, the average value of the horse racing performance prediction of this system during the review is only 2.01 s, and the misappraisal rate is 0.12%, indicating that the application value of this system is significant; fourth, in the average time spent in the two seasons, the average time spent in the second season was reduced compared with the average time spent in the first season, with a maximum reduction of 0.984 s, indicating a slight improvement in the performance of the 2020 season. Using this system to predict horse racing, results can improve the optimization of horse racing decision management to a certain extent.
[Retracted] A Survey of Multimedia‐Assisted English Classroom Teaching Based on Statistical Analysis
Authors: Wang Hui
Published: March 2022

With the promotion of information technology and education reform, multimedia classroom teaching, which has distinctive teaching characteristics, rich teaching resources, and vivid teaching forms, has been widely used in different classrooms, especially in English classrooms. However, there are still some problems in the application of multimedia‐assisted instruction, and much work so far has focused more on language input (vocabulary, listening, and reading) of multimedia‐assisted instruction, but there is limited empirical research on output (especially writing) of it. Therefore, from the perspective of statistical analysis, this empirical study investigates the effectiveness of multimedia‐assisted English classroom teaching from the detailed aspects like preferred teaching activity, understanding key and difficult points, and overall performance and then formulates a multimedia writing teaching model in order to improve students’ writing performance. The result shows that multimedia teaching does have superior advantages and the model enhances students’ interest and scores in writing.
Integrating Metabolomics and Network Pharmacology to Explore the Protective Effect of Ginsenoside Re against Radiotherapy Injury in Mice
Authors: Yu Chunmiao , Fu Jiaqi , Guo Lidong , Yu Miaomiao , Yu Donghua
Published: March 2022

Ionizing radiation (IR) can cause radiation damage, mutagenesis, or carcinogenesis in the irradiated subject. It is manifested as metabolic disorders of the body and damage to the immune system, nervous system, and endocrine system, which can lead to physiological and pathological changes and endogenous metabolic disorders. Ginsenoside Re (G-Re), a single component of traditional Chinese medicine, has a certain ameliorating effect on radiation damage. However, its mechanism of action in the treatment of radiotherapy injury remains unclear. With this purpose, the hematopoietic function of mice damaged by X-ray radiation was studied, and the protective effect of G-Re on mice damaged by radiation was preliminarily evaluated. Network pharmacology and metabolomics analysis are used to further reveal the mechanism of G-Re to improve radiation damage through metabolomics research. Results of metabolomics analysis showed that 16 potential biomarkers were identified as participating in the therapeutic effect of G-Re on IR. Most of these metabolites are adjusted to recover after G-Re treatment. The pathways involved included glycerophospholipid metabolism, sphingolipid metabolism, and linoleic acid metabolism. According to network pharmacology analysis, we found 10 hub genes, which is partly consistent with the findings of metabolomics. Further comprehensive analysis focused on 4 key targets, including SRC, EGFR, AKT1, and MAPK8, and their related core metabolites and pathways. This study combines metabolomics and network pharmacology analysis to explore the key targets and mechanisms of G-Re in the treatment of IR, in order to provide new strategies for clinical treatment of radiotherapy injury.
Enhanced Security Against Volumetric DDoS Attacks Using Adversarial Machine Learning
Authors: Shroff Jugal , Walambe Rahee , Singh Sunil Kumar , Kotecha Ketan
Published: March 2022

With the increasing number of Internet users, cybersecurity is becoming more and more critical. Denial of service (DoS) and distributed denial of service (DDoS) attacks are two of the most common types of attacks that can severely affect a website or a server and make them unavailable to other users. The number of DDoS attacks increased by 55% between the period January 2020 and March 2021. Some approaches for detecting the DoS and DDoS attacks employing different machine learning and deep learning techniques are reported in the literature. Recently, it is also observed that the attackers have started leveraging state-of-the-art AI tools such as generative models for generating synthetic attacks which fool the standard detectors. No concrete approach is reported for developing and training the models which are not only robust in the detection of standard DDoS attacks but which can also detect adversarial attacks which are created synthetically by the attackers with harmful intentions. To that end, in this work, we employ a generative adversarial network (GAN) to develop such a robust detector. The proposed framework can generate and classify the synthetic benign (normal) and malignant (DDoS) instances which are very similar to the corresponding real instances as evaluated by similarity scores. The GAN-based model also demonstrates how effectively the malicious actors can generate adversarial DDoS network traffic instances which look like normal instances using feature modification which are very difficult for the classifier to detect. An approach on how to make the classifiers robust enough to detect such kinds of deliberate adversarial attacks via modifying some specific attack features manually is also proposed. This work provides the first step towards developing a generic and robust detector for DDoS attacks originating from various sources.
Hepatoprotective Role of 4-Octyl Itaconate in Concanavalin A-Induced Autoimmune Hepatitis
Authors: Yang Wenchang , Wang Yaxin , Zhang Peng , Wang Tao , Li Chengguo , Tong Xin , Zeng Xiangyu , Yin Yuping , Tao Kaixiong , Li Ruidong
Published: March 2022

4-Octyl itaconate (OI) is a novel anti-inflammatory metabolite that exerts protective effects in many various disease models. However, its function in autoimmune hepatitis- (AIH-) associated hepatic injury has not been investigated. In this study, we successfully used concanavalin A (Con A) to establish an AIH-associated liver injury model. Furthermore, we investigated the effect of OI in Con A-induced liver injury and found that OI mitigated Con A-induced histopathological damage. OI administration reduced serum levels of alanine transaminase and aspartate transaminase in Con A-treated mice and attenuated the infiltration of macrophages induced by Con A. Moreover, OI effectively inhibited the expression of proinflammatory cytokines including interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), and IL-1β induced by Con A. Furthermore, OI decreased hepatocyte apoptosis and malondialdehyde levels and increased the reduced glutathione/oxidized glutathione ratio in the Con A-induced liver injury model. In addition, we found that OI inhibited Con A-induced hepatocyte apoptosis in vitro, while Nrf2 deletion eliminated this effect. Furthermore, we administrated the Nrf2 inhibitor ML385 in OI+Con A-treated mice and found that ML385 eliminated the protective effect of OI in vivo. In addition, OI inhibited Con A-induced activation of nuclear factor-kappa B (NF-𝜅B) and the expression of proinflammatory cytokines in macrophages. Therefore, OI protected mice from Con A-induced liver damage and may be associated with Nrf2 activation and NF-𝜅B inhibition. Finally, our study revealed that OI inhibited TNF-α, or supernatants from Con A-treated RAW264.7 cells induced hepatocyte apoptosis. In conclusion, our study indicated that OI alleviated Con A-induced hepatic damage by reducing inflammatory response, oxidative stress, and apoptosis.
Construction of Innovation and Entrepreneurship Education Ecosystem in Higher Vocational Colleges from the Perspective of System Theory
Authors: Zheng Chuanjuan , Sun Liandong , Guo Huifang
Published: March 2022

Innovation and entrepreneurship (IAE) education in higher vocational education is mainly to cultivate college students’ innovative spirit and ability, and it is an important way to promote economic development. However, the current academic research on the construction of IAE education ecosystem in higher vocational school (HVS) is relatively weak. In order to improve the IAE education ecosystem of HVS and strengthen the innovation of HVS education system, this study systematically discusses and analyzes the system from the four aspects of system boundary, state, power, and movement and further innovates and constructs the IAE education ecosystem of HVS on the basis of university education system, subject cooperation, and mechanism management. The results prove the feasibility of HVS IAE education ecosystem from the perspective of system theory, enhance the cultivation of HVS talents’ IAE ability, and are of great significance to promote the comprehensive reform of higher vocational school education system.
Synthesis of CeO2-Fe2O3 Mixed Oxides for Low-Temperature Carbon Monoxide Oxidation
Authors: Pham Chuc Ngoc , Trinh Quyen Van , Van Thai Dang , Dao Nhiem Ngoc , Nguyen Bac Quang , Doan Dung Trung , Le Hung Bao , Nguyen Vinh Van , Duong Lim Thi , Tran Lam Dai
Published: March 2022

In this study, the CeO2-Fe2O3 mixed oxide catalysts have been prepared by combustion method using gel-created tartaric acid. The ability of effective carbon monoxide (CO) oxidation to carbon dioxide (CO2) by CeO2-Fe2O3 catalyst under low-temperature conditions was also demonstrated. The calcined CeO2-Fe2O3 material has a porous honeycomb structure and good gaseous absorption-desorption ability. The solid solution of CeO2-Fe2O3 mixed oxides was formed by the substitution of Fe+3 ions at some Ce4+ ion sites within the CeO2 crystal lattice. The results also showed that the calcination temperature and the molar ratio of Ce3+ ions to Fe3+ ions (CF) affected the formation of the structural phase and the catalytic efficiency. The catalytic properties of the CeO2-Fe2O3 mixed oxide were good at the CF ratio of 1 : 1, the average crystal size was near 70 nm, and the specific surface area was about 20.22 m2.g-1. The full conversion of CO into CO2 has been accomplished at a relatively low temperature of 270 °C under insufficient O2 conditions.
Simulation Research on the Palm Mechanism of Volleyball Robot Based on Artificial Intelligence and Ant Colony Optimization Algorithm
Authors: Jiao Guangshi
Published: March 2022

The study of mobile robots, which began in the late 1960s, is the most dramatic development in human history in the twentieth century, and the invention has undergone radical changes in just over 50 years. The robot body is developing in the direction of flexibility and miniaturization. This is because the robot application is mostly oriented to the family and service industries, and it needs to adapt to a more complex environment. This manuscript aims to improve further the ant colony optimization algorithm by using rough set theory to improve the convergence speed and accuracy of the algorithm in robot path planning on the basis of an in-depth diagnosis on the shortcomings and its causes of development of the ant colony optimization algorithm. It overcomes the drawbacks of the algorithm that easily get trapped in partial optimality solution, the search time is much slower and the search effect is not good. In this paper, the CMA-ES algorithm, the modified ant colony, and the BK method are proposed, which have high theoretical value and exploration significance. In addition, simulation experiments are conducted to obtain the stage results on the basis of artificial information. The results of the present paper indicate the GWO algorithm performs more stable in the optimization results of each experiment when there are 14 robots and the communication range is 1.6, compared with the PSO algorithm and BA algorithm.
Study on Lubrication-Photothermal Synergistic Deicing of CNT Coating on Wind Turbine Blades
Authors: He Jianjun , Tian Huanyu , Yang Kaijun , Jie Jun , Chen Biao , Shu Zhonghu , Bao Jiangyong , Pu Min
Published: March 2022

Aiming at the problem of wind turbine blades' icing, a carbon nanotube composite photothermal coating with both active deicing and passive anti-icing properties was prepared by the spin-coating method. The results indicate that the lubricating coating doped with carbon nanotubes can effectively delay freezing time and reduce ice adhesion strength. The spin-coated 6-layer coating can achieve the best photothermal conversion performance and consume relatively few nanomaterials to maximize the capture of energy in near-infrared light. Under the irradiation of near-infrared light (808 nm), the surface temperature of the coating can reach 97.1°C, which has good photothermal conversion performance. The antifrosting ability of carbon nanotube nanocomposite photothermal coating is related to the content of lubricating oil, and the defrosting performance is related to the content of carbon nanotubes in the coating. Adopting the lubrication-photothermal synergistic deicing method can greatly shorten the deicing time, which is compared with only using photothermal deicing from 392 s to 51 s.
Partial Differential Equation-Assisted Accounting Professional Education and Training Artificial Intelligence Collaborative Course System Construction
Authors: Hu Jingnan
Published: March 2022

In this paper, we use partial differential equations combined with artificial intelligence methods to conduct an in-depth study and analysis of the curriculum system of accounting and finance professional education and training. Under the condition of high-performance advanced computers, neural network technology has been developed rapidly and started to adapt to the requirements of computational accuracy and speed in the field of PDEs. Neural networks have good self-learning as well as self-adaptive capabilities, and the use of deep neural networks to solve the numerical solution of partial differential equations has become a popular application that has emerged recently. The system provides a variety of interfaces for the output of calculation results, which can be directly or indirectly read into the calculation results by various common drawing software programs. In addition, the system can also directly plot the results using its plotting plug-in. This paper presents a case study to illustrate the overview of the practical work of the group before the application of accounting AI, i.e., the human manual model, reveals the problems faced by the accounting practice in this model and then discusses the specific application process and the effect it brings, emphasizing the superiority of accounting AI. Intra-group heterogeneity is to fully consider the learning ability, interest, personality, gender, and other factors of individual students when grouping, to ensure the differences between the members of the group. In terms of accounting personnel and accounting credit system, which are indirectly affected by AI in accounting, this paper discusses the overview before the application of AI in accounting and the impact and challenges after the application and then comes up with countermeasures for the development of accounting. Through the study of specific enterprises to elaborate the current situation of the application of accounting AI in enterprises and its impact, it exposes that the application of accounting AI has a great impact on the accounting process, accounting information quality, accounting personnel, accounting information security, and other aspects of enterprises and this paper proposes solutions in four aspects: first, machine learning for adversarial AI needs to be promoted; second, AI-related laws need to be improved; third, management accounting talent transformation needs to be realized; and fourth, the integration of artificial intelligence and accounting needs to be deepened.
A 10-Year Scientometrics Analysis of Brain Tumors Treated with Gamma Knife Radiosurgery: Visualization, Characteristics, and Scientific Trends
Authors: Garcia-Fuentes Walkiria , Espinoza-Rodriguez Leonardo , Munive-Degregori Arnaldo , Mauricio-Vilchez Cesar , Guerrero Maria Eugenia , Pacheco-Mendoza Josmel , Mayta-Tovalino Frank
Published: March 2022

Objective. To evaluate the scientometrics characteristics of the scientific production on the treatment of brain tumors with gamma knife radiosurgery in Scopus. Methods. The Scopus database (Elsevier) was used to collect all relevant studies for this bibliometric analysis. Data was obtained as a .csv file; it was downloaded from Scopus and was exported by SciVal to Microsoft Excel for a presentation using tables for more detailed analysis. The citations and the number of papers for the most productive institutions, authors, countries, and journals publishing scientific papers were analyzed on the use of gamma knife radiosurgery for brain tumors. Results. 458 metadata were obtained from scientific publications, on which inclusion and exclusion criteria were applied, leaving 248 studies. The maximum peak of publications was 2018 with 31 publications, and the minimum peak was 2015 with 18. The most related subtopics were neurology, surgery, and oncology, and most of the retrieved papers had only institutional collaboration. As for more productive journals, Journal of Neurosurgery is first with 23 publications; within the countries with the most scientific publications, we have the United States, Japan, and China. With the United States being the country with the highest number of productions, University of Texas MD Anderson Cancer Center was the main university with the highest scientific production and Sheehan and Trifiletti and American authors dominate the list with the highest number of documents. Conclusion. Scientific production regarding gamma knife surgery and brain tumors has been increasing during the last 10 years, with a high incidence during 2018, and the highest number of published articles was in the first quartile. Likewise, the United States is the country with the most publications, authors, and universities on the subject. Greater efforts are still lacking from all countries in the world to reach the quantity and quality of production of the United States.
A Prediction Model Optimization Critiques through Centroid Clustering by Reducing the Sample Size, Integrating Statistical and Machine Learning Techniques for Wheat Productivity
Authors: Islam Muhammad , Shehzad Farrukh
Published: March 2022

Machine learning algorithms are rapidly deploying and have made manifold breakthroughs in various fields. The optimization of algorithms got abundant attention of researchers being a core component for deploying the machine learning model (MLM) abled to learn the parameters in significant ways for the given data. Modeling crop productivity through innumerable agronomical constraints has become a crucial task for evolving sustainable agricultural policies. The cross-sectional datasets of 26430 (D1) crop-cut experiments are taken by 2nd-stage area frame sampling, collected from crop reporting service. This research is taken as follows: firstly three more effective numerical optimized datasets are generated (D1, D2, and D3) from D1 by taking the centroid points of features which decrease the sample size; secondly MLM is integrated with the traditional statistical models (TSMs) for multiple linear regression (MLR), and thirdly decision tree regression (DTR) and random forest regression (RFR) are deployed to get the optimized models able to predict the wheat productivity well with 75% datasets to train and 25% to test the model using the evaluation metrics (R2, RMSE), information criterion (AIC) with weights (AICW), evidence ration (E.R), and decompositions of prediction error. The MLR outperformed for MLM than TSM. The performance capability of MLM and TSM got upswing for generated datasets. RFR got optimized and superperformed for D1, D2, D3, and D4. This study demonstrated strong evidences for deploying MLM for prediction of wheat productivity as an alternative of traditional statistical modeling.
Sustainable Downstream Separation of Itaconic Acid Using Carbon-Based Adsorbents
Authors: Ortíz-de-Lira Alejandra , Reynel-Ávila Hilda Elizabeth , Díaz-Muñoz Lizbeth Liliana , Mendoza-Castillo Didilia Ileana , Aminabhavi Tejraj M. , Badawi Michael , Bonilla-Petriciolet Adrián
Published: March 2022

Separation of itaconic acid from aqueous solution has been explored using various carbon-based adsorbents obtained from the pyrolysis and KOH activation of coconut shell biomass. The best preparation conditions to obtain a tailored adsorbent for itaconic acid purification were identified via a Taguchi experimental design, where its adsorption properties were maximized. The best activated carbon was obtained via coconut shell pyrolysis at 750 °C for 4 h plus an activation with 0.1 KOH and a final treatment at 800 °C for 2 h. This adsorbent showed an adsorption capacity of 4.31 mmol/g at 20 °C and pH 3 with a surface area of 466 m2/g. Itaconic acid separation was exothermic and pH-dependent where electrostatic forces and hydrogen bonding were the main adsorption interactions. Calculated adsorption rate constants for itaconic acid adsorption were 0.44–1.20 h-1. Results of adsorbent characterization analysis indicated the presence of a crystallization of itaconic acid molecules onto the activated carbon surface where 3–4 molecules could interact to form the clusters. This organic acid was recovered from the adsorbent surface via desorption with water or ethanol, thus facilitating its final purification. The best activated carbon obtained in this study is a promising alternative to perform sustainable and energy-efficient downstream separation and purification of itaconic acid produced via fermentation.
All-Domain Fusion-Based Time Synchronization Protocol in SD-ATSN
Authors: Zhu Meng-Yuan , Chen Ke-Fan , Chen Zhuo , Lv Na
Published: March 2022

As combat scales up and weapons become more intelligent, airborne networks (AN) must facilitate high-precision communications. This means that the airborne network should have communication capability with minimum delay, low jitter, and high reliability, and this new type of AN is called an airborne time-sensitive network (ATSN). A prerequisite to guarantee the above communication capability is to have a high precision time synchronization protocol. To plug this gap, we have designed a software-defined airborne time-sensitive network (SD-ATSN) architecture based on the benefits of software-defined centralization and flexibility. It supports our proposed all-domain fusion-based time synchronization protocol (AF-TSP) to support precise time synchronization between ATSN platforms. In AF-TSP, we innovatively propose an all-domain (land, sea, air, and space) master clock hot standby mechanism to cope with the existing instability and poor robustness in AN. In the key problem of the master clock election, we first completed a rough election utilizing improved K-Means++. Subsequently, on top of the rough election, we inserted a mixed mutation operator to improve the convergence of the multiobjective optimization algorithm No Dominant Sorting Genetic Algorithm-II (NSGA-II). The control delay, clock accuracy, and path reliability coefficient are the optimization objectives for selecting the appropriate master clock. Simulation results demonstrate that our protocol has advantages in terms of synchronization precision, communication delay, and network robustness.
Clinical Study of Neuromuscular Electrical Stimulation in the Prevention of Deep Venous Thrombosis of Lower Extremities after Anterior Cruciate Ligament Reconstruction
Authors: Xiong Jun , Zhang Qingsong , Li Yanan
Published: March 2022

This paper is written to observe the clinical effects of “neuromuscular electrical stimulation in the prevention of deep venous thrombosis of lower extremities after anterior cruciate ligament reconstruction” in our department. Data from March 2018 to March 2021 was selected including 187 males and 91 females. They were randomly divided into experimental groups and control groups. The experimental group adopted DVT general prevention + basic physical prevention + NMES and the control group adopted DVT general prevention + basic physical prevention. The VAS score, the content of blood D-dimer, the circumference of the affected knee, and results of DVT color ultrasound screening were studied in each group on the first day before operation and the fourth day after the operation. Results obtained showed that there were no significant differences in the baseline characteristics of the two groups of patients, such as gender composition, age, and so on

P
>
0.05

. The VAS scores, blood D-dimer content, and knee circumference of each group on the day before and on the fourth day after surgery were observed. Diameter and DVT color Doppler ultrasound screening results were superior to the control group in the test group and the difference was statistically significant

P
<
0.05

. It was concluded that NMES can effectively reduce the pain, knee swelling, and incidence of DVT in patients after ACL reconstruction. It is a simple and effective intervention therapy to prevent the occurrence of DVT.