bluuebunny/crossref_metadata_2025 huggingface dataset:
Pressure Relief and Permeability Enhancement Mechanism of Short-Distance Floor Roadway in Deep Coal Roadway Strip
Authors: Yuan Benqing , Tu Min , Cao Jianjun , Cheng Xiang
Published: March 2022

A pressure relief and permeability enhancement method through short-distance floor roadway was proposed to solve the difficult outburst prevention during the gas extraction at the coal roadway strips in deep outburst coal seams with high ground stress and low gas permeability. On the basis of an equivalent model of the surrounding rock in a deep roadway, the analytical solutions of deep roadway excavation to the stress and deformation of pressure relief at overlying short-distance coal roadway strips were obtained using the unified strength theory and nonassociated flow rules. Next, the criteria for determining the reasonable position of floor roadway were established, and a mechanical model of short-distance floor roadway for the pressure relief and permeability enhancement zone at the overlying coal seam was constructed. Finally, the scope of the zonal disintegration at the coal roadway strips in the elastic and elastic–plastic zones of the surrounding rock in the roadway, as well as the expression of gas permeability change, was given. The engineering trial calculation and practice showed that the stress and strain of the surrounding rock in the roadway were evidently influenced by the intermediate principal stress coefficient. Moreover, the vertical stress and vertical displacement of overlying coal seam were gradually reduced with the increase in the intermediate principal stress coefficient and vertical distance of the floor roadway. The minimum reasonable distance arranged for the 213 floor roadway in Qujiang Coal Mine was 6.21 m, and the effective pressure relief should be conducted within 10.6 m from the coal seam floor. When the pressure relief was located at 9.0 m from the coal seam floor, the investigation results were basically consistent with the theoretical analysis results, exerting obvious pressure relief and permeability enhancement effects on the overlying short-distance coal roadway strips.
Enhancing Problem-Solving Ability through a Puzzle-Type Logical Thinking Game
Authors: Weng Ting-Sheng
Published: March 2022

This study explored the influence of creativity and learning attitude through game-based learning. The subjects were sixth grade elementary school students, and a logical thinking game was developed to stimulate the students’ learning interests. A questionnaire survey was conducted on 121 students, and the result shows that the students’ creativity has a significant and positive effect on their learning attitude and problem-solving ability. In addition, learning attitude has a significant and positive effect on the students’ problem-solving ability. Moreover, creativity elicited a direct effect on problem-solving ability. This study verified that the proposed puzzle-type logical thinking game can train and improve the logical thinking ability of learners.
A New Adaptive Federated Cubature Kalman Filter Based on Chi-Square Test for SINS/GNSS/SRS/CNS Integration
Authors: Xu Fei , Gao Guangle , Ni Longqiang
Published: March 2022

As an emerging means of transportation for the intelligent transportation system (ITS) in aviation and aerospace, hypersonic cruise vehicles (HCVs) have received numerous research interests during the past several decades. However, the navigation and positioning strictly limit the progress and application of HCVs due to their special characteristics on dynamics and environments. To improve the stability of navigation in HCVs, a chi-square test-based adaptive federated cubature Kalman filter (CAFCKF) is proposed in this paper. In the proposed approach, the chi-square test is adopted for the estimation of the measurement noise statistics firstly. Subsequently, a new adaptive information fusion factor is designed for the federated filter to adjust the contribution of each subsystem. Finally, the information sharing factor, which is used for the amendment of the state covariance of each subsystem, is refined based on the judging index of the chi-square test accordingly. Simulation results show that the proposed CAFCKF can be used to improve the accuracy and stability of the navigation system.
Data Model of Key Indicators of Urban Architectural Design Based on Long- and Short-Term Convolutional Memory Network
Authors: Ma Xiyin , Li Jian , Zhang Xu
Published: March 2022

The analysis and design of key indicators of urban architecture has always been a frontier subject in the field of urban architecture. Building key indicator network area flow is challenging due to its high degree of nonlinearity and randomness. Based on the extraction method of key indicators of urban architectural design based on long and short-term convolutional memory network, this paper designs a data model of key indicators of urban architectural design. The model can effectively simulate the urban architectural design system to obtain the key index information of urban architectural design of objects step by step. The architecture of cascaded full convolutional long and short-term convolutional memory network is designed and improved. The experiment adopts the block method to ensure the output result with the same resolution as the input urban building image, which solves the problems of the traditional fully convolutional network such as small local receptive field, low output resolution. The simulation results show that the data prediction accuracy of the key indicators proposed in this paper reaches 92.3%, which is 16% and 11.5% higher than the prediction accuracy of the other two depth algorithms (76.3% and 80.8%) respectively, which promotes the key indicators of information flow within the network.
Scheduling Optimization for Twin ASC in an Automated Container Terminal Based on Graph Theory
Authors: Xu Yifeng , Zhu Jin
Published: March 2022

Aiming at the twin automated stacking cranes (ASCs) scheduling problem in a single block of an automated container terminal, resolving conflicts between ASCs is an important point that needs to be considered. To solve this problem, a two-stage adaptive genetic algorithm (AGA) based on a graph theory model is proposed. The first stage of the algorithm reduced conflicts as much as possible by adjusting the order of container operations. In the second stage, when conflicts are unavoidable, conflicts are resolved by transforming conflicts into obstacle diagrams. Solving the completion time is to find the shortest distance in the diagram. The effectiveness of the algorithm is verified by applying the proposed algorithm to different scales of container numbers. Compared with the traditional seaside priority strategy, the graph theory model can shorten the completion time to varying degrees. For the strategy of setting the handshake area to reduce conflicts, the results show that the graph theory model makes ASC more efficient.
Efficacy of Pharmaceutical Care in Patients with Type 2 Diabetes Mellitus and Hypertension: A Randomized Controlled Trial
Authors: Wang Weibo , Geng Lijuan , Sun Chenjing , Li Hui , Wang Jinying
Published: March 2022

Background. The rates of treatment adherence and treat-to-target rates of blood pressure and blood glucose-related indexes in patients with hypertension and type 2 diabetes mellitus (T2DM) are associated with prognosis. This study aimed to investigate the efficacy of pharmaceutical care postdischarge for treatment adherence in hypertensive patients with type 2 diabetes mellitus (T2DM). Methods. This was a randomized controlled trial of patients with combined T2DM and hypertension treated between January and May 2018. Pharmaceutical care included free access to a clinical pharmacist, education material, a WeChat account for live discussion, and a telephone follow-up. The primary endpoint was the 3-month medication adherence. The secondary endpoints included the achieving levels of target rates and values of fasting plasma glucose (FPG), 2 h postprandial glucose (2hPG), and hemoglobin A1c (HbA1c) and the rates of reaching the achieving target rate of blood pressure target <130/80. Results. In 80 participants, the 3-month medication adherence was higher in the pharmaceutical care group than the routine group (90.0% vs. 52.5%,

P
<
0.001

). In terms of FPG, 2hPG, and HbA1c, there were also significant differences between the pharmaceutical care and routine groups (FPG, 6.50 (6.00, 7.18) vs. 7.00 (6.83, 7.78) mmol/L,

P
=
0.004

; 2hPG, 8.45 (7.45, 9.28) vs. 9.35 (8.23, 10.15),

P
=
0.007

; HbA1c, 6.5% (6.3%, 7.0%) vs. 7.0% (6.5%, 7.4%),

P
=
0.007

). The achieving target rate of reaching the blood pressure target in the pharmaceutical care group (92.5%) was significantly higher than that in the routine group (62.5%;

P
<
0.05

). Conclusion. The postdischarge pharmaceutical care program in patients with T2DM and hypertension improves medication adherence.
Effects of Astragalus Polysaccharides on CD8+ Tissue-Resident Memory T Cells in Mice with Herpes Simplex
Authors: Shi Liqing , Zhang Cong , Liu Lihao , Xi Zhaoqing , Chen Min
Published: March 2022

Objective. This study aimed to explore whether astragalus polysaccharides (APS) could treat herpes simplex by increasing tissue-resident memory CD8+ T cells (CD8+ TRM cells) and analyze its potential mechanism using the network pharmacologic approach. Methods. C57BL/6J male mice aged 6–8 weeks were divided into a model group with HSV-1 infection treated by saline, a control group without HSV-1 infection but treated by saline, and an APS group with HSV-1 infection treated by APS. Clinical signs were observed, and the disease score was recorded every day. The skin lesions on day 9 after infection were taken for flow cytometric analysis to evaluate CD8+ TRM cells. Network pharmacologic analysis was performed to select the potential protein targets of astragalus associated with herpes simplex. Besides, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. The peripheral blood from the retroorbital venous plexus was collected to evaluate the levels of serum interferon-γ (IFN-γ) and interleukin 12 (IL-12). The comparisons of clinical signs, the disease score, CD8+ TRM cells, the serum IFN-γ, and IL-12 levels were performed among the three groups. Results. Compared with the model group, the disease score in the APS group was significantly lower (

p
<
0.05

). On the day 9 after HSV-1 infection, there was no significant difference in the body weight of mice among the three groups. However, compared with the control group or model group, the spleen weight in the APS group increased significantly (

p
<
0.05

). The surface antigens of CD8+ TRM cells had no significant difference between the control group and the model group, while compared with the model group, the surface antigens of CD8 (

p
<
0.05

), CD69 (

p
<
0.05

), and CD103 (

p
<
0.05

) in the APS group increased significantly. Moreover, the serum IL-12 (

p
<
0.05

) and IFN-γ (

p
<
0.01

) levels in the APS group increased significantly compared with the model group. Conclusion. Our study suggested that APS could alleviate the symptoms of the mice infected with HSV-1, and CD8+ TRM cells in the skin lesions and the levels of IL-12 and IFN-γ in the serum of mice with HSV-1 infection increased after the APS treatment, of which the specific underlying mechanism requires further experiments to clarify. In addition, the antiviral effect of APS might be worthy of further development and utilization.
Prior Distribution Estimation of Monitored Information in the Intensive Care Unit with the Hidden Markov Model and Decision Tree Methods
Authors: Zhao Xin , Nie Xiaokai , Pang Guofei , Qiu Siyuan , Shi Kehan , Wang Changqing , Zhao Bingqi , Huo Yidan
Published: March 2022

In the intensive care unit, the monitored variables collected from sensors may have different behaviors among patients with different clinical basic information. Giving prior information of the monitored variables based on their specific basic information as soon as the patient is admitted will support the clinicians with better decisions during the surgery. Instead of black box models, the explainable hidden Markov model is proposed, which can estimate the possible distribution parameters of the monitored variables under different clinical basic information. A Student’s t-test or correlation test is conducted further to test whether the parameters have a significant relationship with the basic variables. The specific relationship is explored by using a conditional inference tree, which is an explainable model giving deciding rules. Instead of point estimation, interval forecast is chosen as the performance metrics including coverage rate and relative interval width, which provide more reliable results. By applying the methods to an intensive care unit data set with more than 20 thousand patients, the model has good performance with an area under the ROC Curve value of 0.75, which means the hidden states can generally be correctly labelled. The significant test shows that only a few combinations of the basic and monitored variables are not significant under the 0.01 significant level. The tree model based on different quantile intervals provides different coverage and width combination choices. A coverage rate around 0.8 is suggested, which has a relative interval width of 0.77.
A New Key Exchange Protocol Based on Infinite Non-Abelian Groups
Authors: Zhang Jing , Yang Ya-Juan , Li Yi-Peng
Published: March 2022

In order to resist quantum attacks, a key exchange protocol based on infinite non-abelian groups is proposed in this paper. For the purpose, by the composition of twice the operation of a semidirect product, we construct a shared secret key which contains two hard problems of equivalent decomposition problem (EDP) and discrete logarithm problem (DLP). Then, two methods，algebra attack and brute force attack, were employed to verify the antiattack for the proposed protocol. By a sound mathematical inference, it demonstrates that the proposed protocol possesses security positively. Finally, we analyzed the computational complexity and bit complexity when the protocol being implemented on braid groups, and furthermore, the complexity data confirm the feasibility of establishing the key exchange protocol there. Thus, in any case, security or complexity, the actual use of the proposed protocol means achievable in practice.
Date Palm Fiber-Reinforced Recycled Polymer Composites: Synthesis and Characterization
Authors: Ali Malek , Al-Assaf Anwar H. , Salah Mohammad
Published: March 2022

In this research study, Recycled Polymer (RP) composites are synthesized by using compression molding process, initial mixtures of RP and Date Palm Fibers (DPF) with four different lengths (e.g., 2.5, 5, 7.5, and 10 mm) and weight ratios (e.g., 5, 10, 15, and 20 wt%). The RP composites utilized in this study are polyethylene and polypropylene. The mixtures of RP and DPF are heated at 80°C and then poured into a priori prepared mold. The mold is designed to have three cavities for three specimens in order to characterize them through impact, creep, and tensile tests. The results showed that the hardness and impact increased with this process. In addition, an increase in the DPF up to 15 wt% was observed with a small increase in the DPF length. High creep resistance was also observed to be 10 mm with 20 wt% in the DPF specimens. The maximum strain was obtained in a 2.5 mm fiber length with 5% of DPF due to ductility of the plastic matrix. Moreover, with a small ratio of tough DPF, short fibers are unable to block or resist rapid plastic deformation in specimens. In fact, the DPF specimens of 10 mm length with 20 wt% exhibit a high tensile strength of 78 N/mm2 in comparison with other composite specimens. This is due to the length and content of fibers, which improve transferring action and microfailure modes.
[Retracted] Deep Neural Network Model Forecasting for Financial and Economic Market
Authors: Chen Fan
Published: March 2022

Recently, the Internet financial market has developed rapidly both at home and abroad. Simultaneously, its study has also become the focus of academic circles. The financial markets have higher liquidity and volatility as compared to traditional financial markets. In view of the Internet financial market dynamic (volume and daily trading), it is proposed based on a deep neural network for fusion level time series prediction model. First, the proposed model processes the input of characteristic variables of multiple series (market macrodynamic series and multiseed series) and uses an attention mechanism to fuse the input variables in two dimensions of time and sequence feature. Second, the model also designs an optimization function based on the stability constraints of the prediction sequence, so that the model has better robustness. Finally, a large number of experiments are carried out on real large‐scale data sets, and the results fully prove the effectiveness and robustness of the proposed model in the dynamic prediction of the Internet financial market.
Effects of Dietary Supplementation of PrimaLac, Inulin, and Biomin Imbo on Growth Performance, Antioxidant, and Innate Immune Responses of Common Carp (Cyprinus carpio)
Authors: Ajdari Ashkan , Ghafarifarsani Hamed , Hoseinifar Seyed Hossein , Javahery Susan , Narimanizad Fariborz , Gatphayak Kesinee , Van Doan Hien
Published: March 2022

Prebiotics, probiotics, and synbiotics have been successfully used in dietary supplements to achieve aquatic animal health and therefore increase the quality and sustainability of fish production. In the present study, four hundred and twenty common carps, Cyprinus carpio (25.37±0.22 g;mean±SE) were randomly attributed to seven treatments, fed with diets containing PrimaLac (probiotic), inulin (prebiotic), and Biomin Imbo (synbiotic), 1 and 2 g/kg for each supplement. After 60 days of feeding, an increase in final weight (FW), weight gain (WG), specific growth rate (SGR), and survival rate (SR) was recorded in the treatment groups compared to that of the control (P<0.05). The food conversion ratio (FCR) in the treatment groups significantly decreased (P<0.05). The treated groups showed significant improvements in serum immune parameters: lysozyme (LYZ), alternative complement (ACH50), total immunoglobulin (total Ig), and myeloperoxidase (MPO) (P<0.05). Feeding fish with supplemented diets significantly showed enhanced antioxidant status: catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx). Malondialdehyde (MDA) activity was significantly lower in fish fed dietary additives (P<0.05). Compared with the control group, enzyme parameters revealed that supplementation could significantly decrease alanine transaminase (ALT), alkaline phosphatase (ALP), and aspartate transaminase (AST) (P<0.05). The biochemical parameters including triglyceride (TRIG), cholesterol (CHO), glucose (GLU), and cortisol (CORT) decreased with dietary supplementation (P<0.05). Total protein (TP) increased in fish fed experimental diets (P<0.05). Fish fed pro, pre, and synbiotic exhibited significantly higher digestive enzymes (amylase, lipase, and protease) (P<0.05). Skin mucus parameters (total Ig, ACH50, LYZ, protease, and ALP) were significantly enhanced in groups fed dietary additives (P<0.05). Thus, the best recommended inclusion level of supplementation is 2 g/kg for inulin and 2 g/kg for PrimaLac and doses of 1 or 2 g/kg for Biomin Imbo. Dietary PrimaLac, inulin, and Biomin Imbo could be recommended as beneficial feed additives to enhance growth performance, innate immune and antioxidant systems, and promoted biochemical parameters and digestion of common carp; also, the effect of dietary synbiotic was superior to that of prebiotic and probiotic.
Complex Sports Target Tracking with Machine Learning: Take Basketball as an Example
Authors: Xuan Xuan , Xu Hui
Published: March 2022

Object tracking is a hot issue in vision technology research; it is used in scenarios like intelligent monitoring, autonomous driving, and robot visual perception. With the rapid development of sports, tracking of targets in complex sports scenes represented by basketball and football has gradually attracted attention. The target tracking algorithm based on machine learning (ML) has been gradually proposed. With the powerful feature extraction for convolutional neural network (CNN), it greatly improves accuracy and has better robustness in the face of complex sports scenes. However, the tracking algorithm based on deep learning has many network layers and parameters, which makes training and update speed of model slower. In this regard, taking basketball as an example, this paper designs a low-parameter deep learning-based complex sports target tracking algorithm, which greatly reduces the size of the model while ensuring the tracking accuracy. Aiming at the problem of large number of parameters and large model of deep learning tracking algorithm, this work proposes a network structure model with asymmetric convolution module. The asymmetric convolution module includes two convolutional layers, the compression layer and the asymmetric layer. To improve accuracy, this work designs a new triplet loss. Compared with original logistic loss, triplet loss function can fully utilize the latent relationship between the inputs, so that the network model can obtain higher tracking accuracy. Finally, this paper proposes a low-parameter deep learning-based target tracking algorithm combining asymmetric convolution and triple loss function. Comprehensive and systematic experiments demonstrate the effectiveness of this work in tracking complex sports objects.
The Systematic Analysis of Exercise Mechanism in Human Diseases
Authors: Pu Lei , Sun Peng
Published: March 2022

Background. As a part of a healthy lifestyle, exercise has been proven to be beneficial for the treatment of diseases and the prognosis of patients. Based on this, our research focuses on the impact of exercise on human health. Methods. To study and analyze the samples in the GSE18966 gene expression profile, we first performed an analysis on the differential expressed genes (DEGs) through GEO2R, and then the DEGs enrichment in Gene Ontology functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways through the Database for Annotation, Visualization and Integrated Discovery database was conducted. Then, we delved into the gene set enrichment in KEGG through gene set enrichment analysis. After that, we achieved the construction of the protein-protein interaction (PPI) network of DEGs based on the Search Tool for the Retrieval of Interacting Genes online database, and the hub genes were screened and identified. Results. We identified 433 upregulated DEGs and 186 downregulated DEGs from the samples before and after exercise in GSE18966. Through analysis, it was found that these DEGs-enriched pathways, such as the VEGF signaling pathway, the Wnt signaling pathway, and the insulin signaling pathway, were all involved in the regulation of various diseases. Then, GSEA analysis revealed that glycosaminoglycan biosynthesis chondroitin sulfate, type II diabetes mellitus, and basal cell carcinoma were related with exercise samples. The effects of these pathways on various diseases could be improved through exercise. Finally, 3 upregulated hub genes (VEGFA, POMC, and NRAS) and 3 downregulated hub genes (HRAS, NCOR1, and CAV1) were identified through the PPI network. Conclusions. The bioinformatic analysis of samples before and after exercise provides key pathways and genes related to exercise to regulate various diseases, which confirms that exercise has an important influence on the treatment of many diseases.
Data-Driven Zero Trust Key Algorithm
Authors: Liu Zhiwei , Li Xiaoyu , Mu Dejun
Published: March 2022

In today’s information society, network security is a crucial issue. Network security technology is changing as a result of the development of emerging technologies such as big data, cloud computing, and artificial intelligence. Data-driven (DD) security has emerged as a new network security technology development direction. The key technologies for DD network security are discussed in depth in this paper. A data security protection system is designed from the perspective of ZT, based on advanced security concepts and technologies developed by ZT, as well as a foreign data security governance framework. The number of alarms generated per hour is counted, removal rules are defined, and real-time rule matching is performed to eliminate false alarms based on different combinations of attributes. By analyzing the security data generation rules and internal relations, a security aggregation method can reduce redundant data and improve alarm quality.
Tissue Distribution and Nutritional Regulation of Fatty Acid-Binding Proteins (fabps) in Two Marine Teleosts, Turbot (Scophthalmus maximus), and Tiger Puffer (Takifugu rubripes)
Authors: Wang Dixin , Zhao Lili , Liao Zhangbin , Bi Qingzhu , Meng Xiaoxue , Duan Mei , Ma Qiang , Wei Yuliang , Cao Lin , Liang Mengqing , Xu Houguo
Published: March 2022

Fatty acid-binding proteins (fabps) play important roles in lipid homeostasis. In the present study, 7 fabp isoforms, namely, fabp1, fabp2, fabp3, fabp4, fabp6, fabp7, and fabp10, in two marine teleosts, were characterized. In general, turbot and tiger puffer fabp genes showed high identity to their orthologs in other fish species and mammals, but tiger puffer Fabp6 shared the lowest identity to its known orthologs in zebrafish and human. The tissue distribution patterns of fabps were generally in accordance with their function features. However, tiger puffer fabps, in particular Fabp1, Fabp2, Fabp6 and Fabp7, may have functions distinct from other teleosts, as indicated by the phylogenetic tree and tissue distribution patterns. In both species, high dietary lipid levels downregulated the expression of fabp2, fabp3, fabp6, and fabp7a but tended to upregulate the fabp1 expression. Starvation downregulated the expression of most fabps in both fish species, but the downregulation of fabp expression in turbot was much more drastic and earlier compared to tiger puffer. Long-term (30-day) starvation increased the fabp7 expression in tiger puffer and tended to increase the fabp6 expression in turbot. Results of this study contribute to fish fabp physiology and its nutritional regulation.
A Systematic Review of Medicinal Plants of Kenya used in the Management of Bacterial Infections
Authors: Odongo Elizabeth A. , Mutai Peggoty C. , Amugune Beatrice K. , Mungai Nelly N.
Published: March 2022

Kenya’s vision 2030 partly aims at ensuring adequate health care for all, and the integration of traditional healthcare practices into the national healthcare system would present a more rapid alternative towards the realization of universal health coverage in Kenya. Currently, research on Kenyan medicinal plants with potential antibacterial activity remains vastly fragmented across numerous literature studies and databases; thus, it is imperative to collate and appraise these data for the ease of future research and possible clinical application. Objective. This review aims at exploring and compiling research evidence on medicinal plants used in the management of bacterial infections in Kenya, with a focus on their efficacy and safety. Methodology. A comprehensive web-based systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was executed to highlight the Kenyan medicinal plants used for the management of bacterial infections in Kenya. This review includes studies published until January 2021 from the PubMed, Science Direct, AJOL, and Google Scholar databases. Results. A total of 105 Kenyan medicinal plants belonging to 43 families have their in vitro activity against various human pathogenic bacteria evaluated. Plants from the Lamiaceae, Rutaceae, and Fabaceae families were the most commonly studied. Aloe secundiflora, Toddalia asiatica, Senna didymobotrya, Warbugia ugandensis, Tithonia diversifolia, Fuerstia africana, Olea africana, and Harrisonia abyssinica were the plants frequently evaluated within Kenya. The plants with the strongest antimicrobial activities were Toddalia asiatica, Hagenia abyssinica, Ocimum gratissimum, Harrisonia abyssinica, Senna didymobotrya, Olea Africana, Camellia sinensis, and Tarmarindus indica. Conclusion. Based on a published work, it is evident that traditional medicine is seemingly an acceptable and efficient system among Kenyan communities in the management of bacterial infections. Kenya’s rich biodiversity with diverse secondary metabolites presents a promising source of new therapeutic alternatives with possibly different mechanisms of action against bacteria.
Efficacy of Jiedu Pingsou Decoction Combined with Azithromycin in the Treatment of Children with Mycoplasma Pneumonia and Its Effects on Inflammatory Factors and Immune Function
Authors: Lin Shaoli , Wang Shiyun , Zhang Juan , Zhuang Min , Meng Zhen , Liu Jianhua
Published: March 2022

Objective. The purpose of this study is to detect the clinical efficacy of Jiedu Pingsou Decoction combined with azithromycin in the treatment of children with mycoplasma pneumonia and the effect on inflammatory factors and immune function in children. MethodsA total of 68 children with mycoplasma pneumonia in our hospital from January 2021 to January 2022 were included in this study, and they were randomly divided into the control group and the observation group with 34 cases in each group. The children in the control group were treated with azithromycin, and the children in the observation group were treated with Jiedu Pingsou Decoction on this basis. The clinical manifestations, treatment effects, blood routine, serum inflammatory factor levels, and T cell subsets before and after treatment were compared between the two groups. ResultsThe total effective rate in the observation group was 94.12%, which was higher than that in the control group, which was 82.35%, and the difference between the two groups was statistically significant (P < 0.05). After treatment, the levels of CD3+, CD4+, and CD4+/CD8+ in the two groups were higher than those before treatment, and the level of CD8+ was lower than before treatment. The difference between groups was statistically significant (P < 0.05). The levels of serum C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interferon gamma (IFN-γ), interleukin-6 (IL-6), and interleukin-10 (IL-10) in the two groups after treatment were lower than those before treatment, and the difference between the two groups was statistically significant (P < 0.05). The difference between groups was statistically significant (P < 0.05). There were 4 cases and 2 cases of adverse reactions in the control group and the observation group, respectively, and the difference between the two groups was statistically significant (P > 0.05). ConclusionJiedu Pingsou Decoction combined with azithromycin can effectively improve the levels of T cell subsets, immune function, and inflammatory factors in children with mycoplasma pneumonia, improve clinical symptoms, and is safe and stable, and can be used in clinical practice.
A Pan-Cancer Analysis on the Systematic Correlation of MutS Homolog 2 (MSH2) to a Malignant Tumor
Authors: Yao Hai , Cao Zhidong , Yong Haochuan , Zhang Xiaoxing , Zhang Xin , Li Wei , Zhi Shenshen , Wu Wenyan
Published: March 2022

MutS homolog 2 (MSH2) is a crucial participant in human DNA repair, and lots of the studies functionally associated with it were begun with hereditary nonpolyposis colorectal cancer (HNPCC). MSH2 has also been reported to take part in the progresses of various tumors’ formation. With the help of GTEx, CCLE, and TCGA pan-cancer databases, the analysis of MSH2 gene distribution in both tumor tissues and normal control tissues was carried out. Kaplan-Meyer survival plots and COX regression analysis were conducted for the assessment into the MSH2’s impact on tumor patients’ clinical prognosis. In an investigation to the association of MSH2 expression with immune infiltration level of various tumors and a similar study on tumor immune neoantigens, microsatellite instability was subsequently taken. It was found that high expression of MSH2 is prevalent in most cancers. MSH2’s efficacy on clinical prognosis as well as immune infiltration in tumor patients revealed a fact that expression of MSH2 in prostate adenocarcinoma (PRAD), brain lower-grade glioma (LGG), breast-invasive carcinoma (BRCA), and head and neck squamous cell carcinoma (HNSC) posed a significant correlation with the immune cell infiltration level of patients. Likewise as above, MSH2’s expression comes in a similar trend with tumor immune neoantigens and microsatellite instability. MSH2’s expression in the majority of tumors is a direct factor to the activation of tumor-associated pathways as well as immune-associated pathways. MSH2’s early screening or even therapeutic target role for sarcoma (SARC) diagnosis is contributing to the efficiency of early screening and overall survival in SARC patients.
PIoT Malicious Traffic Detection Method Based on GAN Sample Enhancement
Authors: Hou Botao , Zhang Ke , Zuo Xiaojun , Zhao Jianli , Xi Bo
Published: March 2022

To solve the problem of network traffic data imbalance under the background of power Internet of things and improve the poor generalization ability of the model, a PIoT malicious traffic detection method based on GAN sample enhancement is developed. Firstly, network traffic samples are preprocessed. Aiming at the imbalance of network traffic, malicious samples generation based on GAN is adopted, which uses the advantages of confrontation training in GAN to generate a small amount of malicious traffic to balance the PIoT malicious traffic. Secondly, 33 features are selected serially to construct a malicious traffic feature set by using analysis of variance and correlation analysis. Finally, the PIoT malicious traffic detection algorithm is implemented based on CatBoost and grid search. The effectiveness of the proposed method is verified on the public dataset CICIDS2017. The experimental results show that the recall rate of the proposed method on CatBoost reaches 96.60%, which is 21.16% higher than that before unbalancing, and the detection accuracy rate reaches 97.96%, which increases 8% compared to that of the other balanced methods, which significantly improves the detection performance of PIoT malicious traffic.
Evaluation of the Effectiveness of Collusion Control Policy Implementation by BP Neural Network Based on Annealing Algorithm Optimization
Authors: Ma Chongsen , Chen Yun , Lei Zeyang
Published: March 2022

Due to the national economic development form and social development demand, in recent years, the government has been vigorously promoting the control of government-enterprise collusion in the bidding process of government projects in order to promote the standardization of the market. How to predict the vertical collusion behavior under different internal and external environments has become an important research content. Although the prediction of individual behavior is difficult to achieve, the prediction of group behavior has certain possibilities. In this paper, we propose a method for predicting and evaluating the vertical collusion behavior of government investment project bidding based on BP neural network analysis optimized by an annealing algorithm. First, drawing on the traditional evaluation model, the evaluation index system of government-enterprise collusion behavior is constructed from five dimensions: internal environment, external environment, policy development, enforcement effort, and feedback channel. Secondly, a machine learning method based on BP neural network optimized by an annealing algorithm is introduced to evaluate the influence of the change of initial conditions on the bidding collusion behavior. This study has certain significance for government managers to discover the problems and causes in policy formulation, which in turn can support the government in further improving the policy utility.
The Comparison of Financing Efficiency of Small and Medium Enterprises in Economically Underdeveloped Regions in China: A Perspective Study
Authors: Xu Jinghong , Yang Daguang , Zhang Qian
Published: March 2022

Small- and medium-sized enterprises (SMEs) are important foundations to implement mass entrepreneurship and innovation and play an irreplaceable role in increasing employment, promoting economic growth, as well as scientific and technological innovations, and providing particularly social harmony and stability and imminently are strategic entities to the national economy and social development in underdeveloped regions. However, the low-efficiency financing of SMEs has gradually become a major factor that restricts the high-quality development of SMEs in the current conditions. In this paper, interest expenditure, gearing ratio, and the net debt ratio as input indicators and current asset turnover ratio, cost margin, and main business income as output indicators are used to conduct the DEA-BCC model. By utilizing the GEM-listed private enterprises between 2017 and 2020 in China, the nationwide financing efficiency of SMEs is firstly measured, and then the financing efficiencies of SMEs in economically developed regions and lagging regions are calculated separately. The comparison reveals that the financing efficiency of SMEs in economically underdeveloped regions is not only lower than the national average figure but also much lower than the financing efficiency level in economically developed regions, which is the result of the combined effect of internal and external factors that enterprises face. Further, this paper finds that unexpected public events, core technical personnel, and enterprise size have an impact on the financing efficiency of SMEs when running group testing. This paper puts forward rationalized suggestions to the institutions to improve the financing efficiency of SMEs in underdeveloped regions concerning the conducted research, which are called government, financial institutions, and enterprises.
Equivalent SM Controller for Load-Sharing and Dynamic Performance in a DC Microgrid Application
Authors: Rashad Muhammad , Raoof Uzair
Published: March 2022

Load-sharing and voltage regulation are key challenges in low voltage dc microgrid systems. Droop-based decentralized control methods are used to control dc grids which cannot achieve these challenges simultaneously due to unequal voltages and load power variations. Centralized control schemes can achieve these challenges using high bandwidth communication. However, the failure of a single central controller can degrade performance and reliability. In addition, cascaded proportional-integral (PI) type controllers are used to control the voltage and current loop of each power electronic converter. These controllers suffer stability and show slower dynamic responses. Furthermore, control parameters cannot be optimized for different operating conditions. To address these challenges, a distributive control method using an equivalent sliding mode (SM) controller utilizing low bandwidth communication is proposed in this paper. The distributive method improves reliability and achieves load sharing and voltage regulation simultaneously. Furthermore, in SM, both voltage and current loop operate in the parallel configuration which improves the dynamic response and shows stability in all operating conditions. To analyze, a system model is developed, and existence and stability conditions are verified. Detailed simulations are carried out to show the steady-state and transient performance. The presented results show the effectiveness of the proposed scheme.
Postprocessing of Edge Detection Algorithms with Machine Learning Techniques
Authors: Flores-Vidal Pablo , Castro Javier , Gómez Daniel
Published: March 2022

In this paper, machine learning (ML) techniques are applied at an early stage of Image Processing (IP). The learning procedures are usually applied from at least the image segmentation level, whereas, in this paper, this is done from a lower processing level: the edge detection level (ED). The main objective is to solve the edge detection problem through ML techniques. The proposed methodology is based on a classification of edges made pixel by pixel, but the predictors employed for the ML task include information about the pixel neighborhood and structures of connected pixels called edge segments. The Sobel operator is employed as input. Making use of 50 images that belong to the Berkeley Computer Vision data set, the average performance of the validation sets when employing our Neural Networks method reached an F-measure significatively higher than with the Sobel operator. The experiment results show that our post-processing technique is a promising new approach for ED.
Assessment of Cytotoxic, Genotoxic, and Oxidative Stress of Dibutyl Phthalate on Cultured Bovine Peripheral Lymphocytes
Authors: Ali Muhammad Muddassir , Sahar Taha , Firyal Sehrish , Ijaz Muhammad , Majeed Khalid Abdul , Awan Furqan , Adil Memoona , Akbar Haroon , Rashid Muhammad Imran , Ciğerci İbrahim Hakki
Published: March 2022

Recently, there have been numerous reports showing that phthalates have negative human health impacts and may cause several diseases such as asthma, breast cancer, obesity, type II diabetes, and male infertility. Animals are also exposed to phthalates through the environment and can cause adverse health effects on them. Several studies have been found on the cytogenetic effects of dibutyl phthalate (DBP) on different organisms but no documented evidence has been found on the cytotoxic and genotoxic effects of dibutyl phthalate (DBP) on bovine cultured lymphocytes. MTT assay was performed on different series of DBP concentrations (10 μM, 20 μM, 30 μM, 50 μM, 70 μM, 100 μM). A concentration-dependent decrease in cell viability was observed by the DBP. The LD50, LD50/2, and 2

∗

LD50 were found to be 50 μM, 30 μM, and 80 μM on bovine lymphocytes, respectively. Then, these concentrations of DBP were utilized to perform comet, micronucleus assays, and oxidative stress. A concentration-dependent increase in DNA damage, oxidative stress, and micronuclei formation was observed in lymphocytes by the DBP as compared to the control group. Highest genotoxic effects were observed at a concentration of 2

∗

LD50. Similarly, total oxidative stress was found higher, and antioxidative stress was lower in concentration-dependent manner by the DBP. The current study revealed a significant cytotoxic, genotoxic, and oxidative stress of DBP on cultured bovine lymphocytes.
Association between Arteriosclerosis and Uncontrolled Blood Pressure in Patients with Essential Hypertension: Cross-Sectional Observational Study Results of the BEST Study
Authors: Liu Huan , Huang Wei , Liu Jinbo , Zhao Na , Wang Hongyu
Published: March 2022

Whether arteriosclerosis can influence the hypertension control remains incompletely understood. We hypothesized that higher arteriosclerosis may be associated with uncontrolled hypertension. Arteriosclerosis was assessed by carotid femoral artery pulse wave velocity (CF-PWV) and uncontrolled hypertension (systolic blood pressure [BP] ≥130 mm Hg or diastolic BP ≥80 mm Hg). The multivariable-adjusted logistic regression was used for analysis. A total of 1,428 patients with essential hypertension (mean age 68 years, 49.6% male) were enrolled into the study from 2010 to 2017. The BP was uncontrolled in 50.7% of the participants and the mean level of CF-PWV was 12.3 m/s. All the cardiovascular risk factors were worse and CF-PWV was higher in patients with uncontrolled hypertension (all p < 0.05). Multivariable-adjusted logistic regression analysis showed that CF-PWV as a continuous variable (odd ratio [OR] 1.093, 95% confidence interval [CI] 1.046–1.142) was independently associated with uncontrolled hypertension, after male (OR 1.511) and total cholesterol (OR 1.167), followed by body mass index (OR 1.092), fasting plasma glucose (OR 1.075), and creatinine (OR 1.010) (all p < 0.05). As a binary variable, CF-PWV >12 m/s was also independently associated with uncontrolled hypertension (OR 1.690, 95% CI 1.320–2.164, p < 0.05). Arteriosclerosis is independently associated with uncontrolled BP in patients with hypertension.
Cinnamic Acid Improved Lipopolysaccharide-Induced Depressive-Like Behaviors by Inhibiting Neuroinflammation and Oxidative Stress in Mice
Authors: Zhuo Rengong , Cheng Xiaoling , Luo Lili , Yang Luying , Zhao Yun , Zhou Yu , Peng Lu , Jin Xin , Cui Lishan , Liu Feng , Yang Lichao
Published: March 2022

Aim: Recent evidence indicates that neuroinflammation and oxidative stress play vital roles in the pathological process of major depressive disorder (MDD). Cinnamic acid (CA), a naturally occurring organic acid, has been reported to ameliorate neuroinflammation and oxidative stress for treatment of diabetes-related memory deficits. Here, we explored whether CA pretreatment ameliorated lipopolysaccharide (LPS)-induced depressive-like behaviors in mice by suppressing neuroinflammation and by improving oxidative stress status. Methods: The mice were treated with CA, vehicle, or fluoxetine as a positive control. After 14 days, LPS (1 mg/kg, i.p.) or saline was administered. The depression-like behaviors were examined by the sucrose preference test (SPT), the forced swimming test (FST), and the tail suspension test (TST). Furthermore, the levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), superoxide dismutase (SOD), glutathione (GSH), malondialdehyde (MDA), and brain-derived neurotrophic factor (BDNF) in the hippocampus and cortex of mice were assayed. Results: Our results demonstrated that CA pretreatment at the doses of 100 and 200 mg/kg significantly attenuated depressive-like behaviors in the TST, FST, and SPT. In addition, not only the upregulation of pro-inflammatory cytokines (IL-6 and TNF-α) but also oxidative stress parameters including SOD, GSH, and MDA in the hippocampus and cortex of mice treated with LPS were dramatically improved by CA pretreatment. Finally, CA pretreatment strikingly ameliorated the downregulation of BDNF induced by LPS in the hippocampus and cortex of mice. Conclusion: Our results indicated that CA may have therapeutic potential for MDD treatment through attenuating the LPS-induced inflammation and oxidative stress along with significant improvement of BDNF impairment.