bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficacy and Safety of Traditional Chinese Medicine Based on the Method of “Nourishing Kidney and Clearing Heat” as Adjuvant in the Treatment of Diabetes Mellitus Patients with Periodontitis: A Systematic Review and Meta-Analysis
Authors: Jin Wenqin , Li Lingfeng , Ai Huangping , Jin Zhao , Zuo Yuling
Published: August 2022

Objective. The aim of this systematic review and meta-analysis was to assess the efficacy and safety of traditional Chinese medicine based on the method of “nourishing kidney and clearing heat” as an adjuvant in the treatment of diabetes mellitus patients with periodontitis. Methods. An electronic literature search was conducted in the China National Knowledge Infrastructure (CNKI), Wanfang Data, Chinese Scientific Journals Database (VIP), Chinese Biomedical Literature Database (CBM), PubMed, EMBASE, Web of Science, and Cochrane Library databases for articles published until October 2021. The primary outcomes were probing pocket depth (PPD), clinical attachment loss (CAL), plaque index (PLI), and sulcular bleeding index (SBI), while the secondary outcomes were tooth mobility (TM), glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), total effective rate, and adverse effects. Results. Eleven randomized controlled trials (RCT) were included in the meta-analysis. The pooled results showed PPD (WMD = 1.07, 95%CI: (0.82, 1.33),

P
<
0.00001

, I2 = 89%), CAL (WMD = 0.78, 95%CI: (0.62, 0.93),

P
<
0.00001

, I2 = 58%), PLI (WMD = 0.44, 95%CI: (0.09, 0.79),

P
=
0.01

, I2 = 97%), SBI (WMD = 0.87, 95%CI: (0.79, 0.95),

P
<
0.00001

, I2 = 37%), TM (WMD = 0.26, 95%CI: (0.21, 0.30),

P
<
0.00001

, I2 = 31%), HbA1c (WMD = 0.48, 95%CI: (0.28, 0.67),

P
<
0.00001

, I2 = 26%), FBG (WMD = 1.34, 95%CI: (0.96, 1.72),

P
<
0.00001

, I2 = 52%), total effective rate (RR = 1.24, 95%CI: (1.14, 1.34),

P
<
0.00001

, I2 = 0%), and adverse effects (RR = 0.78, 95%CI: (0.20, 3.03),

P
=
0.72

, I2 = 0%) in the traditional Chinese medicine based on the method of “nourishing kidney and clearing heat” + routine western medicine treatment (periodontal basic treatment, PBT, with or without antibiotic) group were significantly improved compared to control group, but no significant difference was observed for PLI at 2–3 months and 6 months. Conclusions. This review supports traditional Chinese medicine based on the method of “nourishing kidney and clearing heat” as an adjuvant to routine western medicine treatment in the management of diabetes mellitus patients with periodontitis. Within the limits of the evidence, the well-designed, long-term efficacy, and high-quality multicenter RCTs need to be further confirmed.
STMMI: A Self-Tuning Multi-Modal Fusion Algorithm Applied in Assist Robot Interaction
Authors: Hou Ya , Feng Zhiquan , Yang Xiaohui , Xu Tao , Qiu Xiaoyu , Zhang Xin
Published: August 2022

While facing complex surroundings, robots need to identify the same intention which is expressed in different ways. In order to solve the problem of assisting robots to get a better intention understanding, a self-tuning multimodal fusion algorithm is put forward in this paper, which is not restricted by the expressions of interacting participants and environment. The multimodal fusion algorithm can be transferred to different application platforms. Robots can own the understanding competence and adapt new tasks by changing the content of the robot knowledge base. Compared with other multimodal fusion algorithms, this paper attempts to transfer the basic structure of feed-forward neural networks on discrete sets, which has strengthened the consistency and perfect the complementary relations between multiple mode, and has realized the simultaneous operation of fusion operator’s self-tuning and intention search. There are three kinds of modes selected in the paper: speech, gesture, and scene objects, where the single modal classifiers are trained separately. This method conducted a human-computer interaction experiment on the bionic robot Pepper platform, which proved that the method can effectively improve the accuracy and robustness of robots in aspects of understanding human intentions, and reduce the uncertainty about intention judgment in a single modal interaction.
Combined Transcriptomic and Metabolomic Analysis of Women with Polycystic Ovary Syndrome
Authors: Tian-Min Ye , Suxia Lin , Shufang Ding , Dandan Cao , Long-Dan Luo , Shu Biu Yeung William
Published: August 2022

Background. Polycystic ovary syndrome (PCOS) is a complex class of endocrine disorders with insulin resistance, compensatory hyperinsulinemia, and obesity. However, the pathogenesis and therapies of PCOS have not been fully elucidated. Exosomal miRNAs have the potential to serve as biomarkers and therapies for a wide range of medical conditions. Method. We collected follicular fluid from 5 PCOS patients and 5 healthy people. High-throughput sequencing technology to identify differentially expressed miRNAs and untargeted metabolome identify differential metabolites in follicular fluid exosomal. RT-qPCR and AUC analysis were performed. Result. miRNA high-throughput sequencing identified 124 differential miRNAs. RT-qPCR analysis confirmed the sequencing results. These differential miRNA target genes are mainly involved in metabolic pathways. Metabolomics studies identified 31 differential metabolites. miRNA and lncRNA coexpression networks in metabolic pathways rigorously screened 28 differentially expressed miRNAs. This network would identify miRNA signatures associated with metabolic processes in PCOS. Meanwhile, the area under curve of receiver operating characteristic revealed that hsa-miR-196a-3p, hsa-miR-143-5p, hsa-miR-106a-3p, hsa-miR-34a-5p, and hsa-miR-20a-5p were potential biomarkers for the diagnosis of PCOS. Conclusion. Collectively, these results demonstrate the potential pathogenesis of PCOS, and follicular fluid exosomal miRNAs may be efficient targets for the diagnosis and treatment of PCOS in long-term clinical studies.
Application of High-Throughput Sequencing Technology in Identifying the Pathogens in Endophthalmitis
Authors: Cheng Peini , Dong Kui , Kang Zhiming , Li Jing , Wang Wenjuan , Zhang Xiaodan , Zhou Guohong
Published: August 2022

Infectious endophthalmitis is an important cause of vision loss worldwide. It is an inflammatory reaction caused by bacteria, fungi, and other micro-organisms and often occurs as a complication of intraocular surgery, especially following cataract surgery or intravitreal injection. The focus of the prevention and treatment of infectious endophthalmitis is the early detection of microbial flora, such as fungi or bacteria. Current identification methods for bacteria include Gram staining-based, culture-based, and polymerase chain reaction (PCR)-based methods. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technology is now the standard identification method of bacteria and fungi after their isolation in culture. The remarkable sensitivity of PCR technology for the direct detection of micro-organisms in clinical samples makes it particularly useful in culture-positive and culture-negative endophthalmitis. Furthermore, PCR increases the rate of microorganism detection in intraocular samples by 20% and can provide a microbiology diagnosis in approximately 44.7–100% of the culture-negative cases. This review aims to introduce the development of different methods for the detection and identification of micro-organisms causing endophthalmitis through a literature review; introduce the research status of the first, second, and third-generation sequencing technologies in infectious endophthalmitis; and understand the research status of endophthalmitis microbial flora. For slow-growing and rare micro-organisms, high-throughput sequencing (HTS) offers advantages over conventional methods and provides a basis for the identification of pathogens in endophthalmitis cases with negative culture. It is a reliable platform for the identification of pathogenic bacteria of infectious endophthalmitis in the future and provides a reference for the clinical diagnosis and treatment of infectious endophthalmitis. The application of HTS technology may also be transformative for clinical microbiology and represents an exciting future direction for the epidemiology of ocular infections.
Application of Virtual Reality Based on Multisensor Data Fusion in Theater Space and Installation Art
Authors: Gu Yingjie , Zhou Ye
Published: August 2022

The application of Virtual Reality (VR) in theater space and installation art is the general trend, and it can be seen in large stage plays and installation art exhibitions. However, as the current VR is not mature enough, it is difficult to perfectly fulfill the exhibition requirements of large theaters, so this paper aims to change this situation by using VR based on multisensor data fusion. In this paper, a data fusion algorithm based on multisensors is designed, which improves the data transmission efficiency and delay of the VR system, so that VR can have a better viewing experience in theater space and installation art. And, through the questionnaire survey and actual interview, the actual feelings of VR audience in theater space and installation art are investigated and studied. Through the experimental analysis of this paper, the algorithm in this paper has high reliability and can improve the experience of using VR. The interview results and results show that the main application of VR in theater space is manifested in three aspects: multiangle and all-round viewing, multiroute viewing, and man-machine interaction in art galleries. The application of VR in installation art is mainly reflected in the perception of installation materials.
A Novel circRNA hsa_circRNA_002178 as a Diagnostic Marker in Hepatocellular Carcinoma Enhances Cell Proliferation, Invasion, and Tumor Growth by Stabilizing SRSF1 Expression
Authors: Li Jing , Han Ting , Li Zhenzhen , Han Hongmei , Yin Yingchun , Zhang Baohua , Zhang Hengming , Li Luan
Published: August 2022

Background. Previous research studies have shown that the elevation of circular RNA (circRNA), hsa_circRNA_002178, was associated with the poor prognosis of breast cancer and colorectal cancer, while its molecular mechanisms underlying the effects on hepatocellular carcinoma (HCC) are still elusive. Methods. The microarray dataset GSE97332 was obtained from the Gene Expression Omnibus (GEO) database and calculated by using the GEO2R tool to identify differentially expressed circRNAs. Differentially expressed hsa_circRNA_002178, in 7 HCC tissue samples and paracancerous tissues, as well as in HCC cell lines and normal hepatocytes, was checked by RT-qPCR. Cell proliferation, invasion, migration, and epithelial-to-mesenchymal transition (EMT)-related proteins were tested in hsa_circRNA_002178-overexpressed or hsa_circRNA_002178-knocked down HCC cells. Subsequently, we identified whether hsa_circRNA_002178 binds to serine- and arginine-rich splicing factor 1 (SRSF1) and then analyzed their function in regulating HCC cell behavior. The effect on HCC cell xenograft tumor growth was observed by the knockdown of hsa_circRNA_002178 in vivo. Results. GEO2R-based analysis displayed that hsa_circRNA_002178 was upregulated in HCC tissues. Overexpression or knockdown of hsa_circRNA_002178 encouraged or impeded HCC cell proliferation, migration, invasion, and EMT program. Mechanically, hsa_circRNA_002178 bound to SRSF1 3′-untranslated region (UTR) and stabilized its expression. SRSF1 weakening eliminated the effects of pcDNA-hsa_circRNA_002178 on cell malignant behavior. Finally, the knockdown of hsa_circRNA_002178 was confirmed to prevent xenograft tumor growth. Conclusions. hsa_circRNA_002178 overexpression encouraged the stability of SRSF1 mRNA expression, and it may serve as an upstream factor of SRSF1 for the diagnosis of HCC.
Long Noncoding RNA LINC00473 Ameliorates Depression-Like Behaviors in Female Mice by Acting as a Molecular Sponge to Regulate miR-497-5p/BDNF Axis
Authors: Li Bo , Zhao Hongxia , Sun Junxia
Published: August 2022

Background. Depression was a common life-threatening psychiatric disorder and occurs more frequently in women than in men. Long noncoding RNAs (lncRNAs), such as LINC00473, had been reported to be involved in the progression of depression. Methods. Chronic unpredictable moderate stress in mice (CUMS) was applied to construct a depression model. Subsequently, RT-qPCR was applied to check the level of LINC00473 and microRNA-497-5p (miR-497-5p) in the hippocampal region of the mice induced by CUMS. CUMS mice were injected with lentiviral vectors of LINC00473 (LV-LINC00473), miR-497-5p inhibitor, short hairpin- (sh-) brain-derived neurotrophic factor (sh-BDNF), or miR-497-5p mimic to evaluate depressive behaviors, including sucrose preference test, forced swim test, elevated plus maze, and tail suspension test. Moreover, the production of hypothalamic neurotransmitters was assessed with the usage of ELISA kits. Dual-luciferase reporter assay, RNA pull-down, and RIP analysis were performed to measure the relationship between miR-497-5p and LINC00473 or BDNF. Further, western blot was employed to determine the protein level of BDNF. Results. We discovered that LINC00473 level was downregulated in the female mice with depression, but not in male mice. Besides, the depressive behaviors induced by CUMS in mice, including the decrease of sucrose preference and time in open arm, as well as the increase of immobility time and swimming resting time were all ameliorated by LINC00473 overexpression. Moreover, the concentration of neurotransmitters was decreased in CUMS-induced mouse hypothalamus, which was blocked by LV-LINC00473 lentiviral vector administration. Mechanistically, LINC00473 directly targeted miR-497-5p. Absence of miR-497-5p revealed the antidepression effects on CUMS-induced mice, and miR-497-5p upregulation could counter the antidepressive impacts of LINC00473 upregulation on CUMS-induced mice. Furthermore, LINC00473 could target miR-497-5p to modulate BDNF level. Knockdown of BDNF could abrogate the improving influences of miR-497-5p suppression on CUMS-induced depression. Conclusions. LINC00473 ameliorated CUMS-caused depression by encouraging BDNF expression via binding to miR-497-5p, which might provide a potential therapeutic target for depression in females.
Application of Internet of Things in Smart Factories under the Background of Industry 4.0 and 5G Communication Technology
Authors: Diao Zhifeng , Sun Fanglei
Published: August 2022

The key identification element of the smart factory is the interconnection between devices, which solves the production method and development dilemma of the factory under Industry 3.0 and previous models. The new article published by Xinhua News Agency on January 16, 2022, advocates the idea of industry+ Internet, and its main goal is to realize intelligent production. At present, smart factories have become the main development direction of industrial enterprises in the world. 5G technology has been rapidly deployed with the development of mobile communication, and its performance has also been greatly improved compared to previous communication technologies. After China put forward the smart manufacturing 2025 plan, although a large number of enterprises are still lingering in the process of research, learning, and exploration, the idea of Industry 4.0 has taken root in various intelligent manufacturing enterprises, and the development route of Chinese manufacturing enterprises in the future has been ahead of schedule. Direction. Based on the basic theory of Industry 4.0, 5G wireless communication, Internet of Things, and smart factories, this paper firstly distributed questionnaires to 20 enterprises with smart factories by means of network and interview and reanalyzed the collected questionnaires by regression analysis method and then used the questionnaire scale analysis method to analyze the reliability and validity of the questionnaire and combined with the results of the questionnaire analysis to analyze the problems existing in the current smart factory. Finally, based on the background of Industry 4.0 and 5G communication technology, combined with the Internet of Things technology, the development layout of the smart factory is designed; that is, based on the elliptic curve encryption algorithm, the signature mechanism of mutual trust of all electronic devices in the IoT smart factory is set to improve the smart factory.
The Effect of Abutment Angulation and Crown Material Compositions on Stress Distribution in 3-Unit Fixed Implant-Supported Prostheses: A Finite Element Analysis
Authors: Mosharraf Ramin , Abbasi Mahsa , Givehchian Pirooz
Published: August 2022

Objective. The aim of this study was to evaluate influence of abutment angulation and restoration material compositions on the stress pattern in dental implants and their surrounding bone. Materials and Methods. In this finite element study, the six different solid 3D models of “mandibular 3-unit fixed implant-supported prostheses” were analyzed. In all of these models, a straight abutment was used for anterior implants at the second premolar site, and in order to posterior implant at the second molar site, abutments with three different angles (straight, 15, and 20°) were used. Also, two different restoration material compositions (porcelain fused to base metal (PFBM) and porcelain fused to noble metal (PFNM)) were considered for fixed implant supported restorations. A 450 N static force was exerted in a straight manner along the longitudinal axis of the anterior implant in a tripod, and the stress distribution was measured based on the restoration materials and abutment angulations of the models in the 3 sites of cortical, cancellous bone, and fixtures. The simulation was performed with ABAQUS 6.13 Software. Results. In all models, stress values in surrounding cortical bone were more than in spongy bone. Maximum stress levels in an anterior abutment-implant complex were seen in models with angled implants. In models with parallel implants, the stress level of a molar straight abutment-implant complex was less than that of premolar straight ones. In an angled posterior abutment-implant complex, less stress level was detected compared to straight ones. In all PFNB models, stress values were slightly more and distributed in a wider area of premolar straight abutments. Conclusion. Increasing an abutment angle, increases stress in surrounding bone and straight implant-abutment combination. It seems that the crown material composition affects stress distribution of the implant-abutment combination but does not affect stress distribution of surrounding bone.
Screening of Differentially Expressed Iron Death-Related Genes and the Construction of Prognosis Model in Patients with Renal Clear Cell Carcinoma
Authors: Wu Ding , Xu Zhenyu , Shi Zhan , Li Ping , lv Huichen , Huang Jie , Fu Dian
Published: August 2022

Objective. In this study, we used the TCGA database and ICGC database to establish a prognostic model of iron death associated with renal cell carcinoma, which can provide predictive value for the identification of iron death-related genes and clinical treatment of renal clear cell carcinoma. Methods. The gene expression profiles and clinical data of renal clear cell carcinoma and normal tissues were obtained in the TCGA database and ICGC database, and the differential genes related to iron death were screened out. The differential genes were screened out by single and multifactor Cox risk regression model.

R

software, “edge” package (version 4.0), was used to identify the DELs of 551 transcriptional gene samples and 522 clinical samples. The risk prediction model with genes was established to analyze the correlation between the genes in the established model and clinical characteristics, Through the final screening of iron death related genes, it can be used to predict the prognosis of renal clear cell carcinoma and provide advice for clinical targeted therapy. Results. Seven iron death differential genes (CLS2, FANCD2, PHKG2, ACSL3, ATP5MC3, CISD1, PEBP1) associated with renal clear cell carcinoma were finally screened and were refer to previous relevant studies. These genes are closely related to iron death and have great value for the prognosis of renal clear cell carcinoma. Conclusion. Seven iron death genes can accurately predict the survival of patients with renal clear cell carcinoma.
Investigating Causal Relations between Genetic-Related Intermediate Endophenotype and Risk of Chronic Prostatitis: Mendelian Randomization Study
Authors: Zhang Shengfeng , Xie Xing , Yu Lei , Jiang Nili , Wei Xihuan , Hu Yanling
Published: August 2022

Objective. Prostatitis is a common disease of the male genitourinary system, which seriously disturbs the physical and mental health of male patients. It is related to many factors such as living habits, age, and race, but the etiology has not been fully elucidated. This study investigated whether there is a causal relationship between clinical biochemical indicators (i.e., intermediate phenotype) and prostatitis through Mendelian randomization. The subjects of the study were prostatitis patients and related SNPs in the Guangxi Fangchenggang health examination cohort. Methods. According to the requirements of Mendelian randomization (MR), the single nucleotide polymorphisms (SNPs) related to prostatitis patients and 29 common SNPs related to clinical biochemical indicators were analyzed by linkage disequilibrium, and the calculated SNPs were selected. Finally, the related SNPs were analyzed by Mendelian randomization method. Results. 15 biochemical indicators such as complement C4, FOL, CRP, HCY, and estradiol have shared chronic prostatitis SNP sites, and five qualified SNPs were finally screened for complement C4. Finally, complement C4 was obtained by Mendelian randomization method (

P
=
0.039

), which was statistically significant. The other 28 clinical endophenotypes were all negative. Conclusion. The results show that there was a causal relationship between complement C4 and prostatitis, and the more consistent SNP is rs2075799.
An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning
Authors: Jabeen Ayesha , Yasir Muhammad , Ansari Yasmeen , Yasmin Sadaf , Moon Jihoon , Rho Seungmin
Published: August 2022

Stock markets accurately reflect countries’ economic health, and stock returns are tightly related to economic indices. One popular area of financial research is the factors that influence stock returns. Several investigations have frequently cited macroeconomic factors, among numerous elements. Therefore, this study focuses on the empirical analysis of the relationship between macroeconomic factors and stock market returns. When a stock market becomes increasingly volatile, it becomes susceptible to economic uncertainty news, and information on social media platforms. Thus, we incorporated a new dimension of economic uncertainty news sentiment (EUNS) for stock return predictions. We employed the daily data ofgold index, crude oil price, interest rate, exchange rate, and stock returns for a set of countries from January 2010 to December 2020. Subsequently, to compute coefficients, we conducted a regression analysis using one of the more sophisticated approaches: single‐layer neural networks and ordinary least square regression. In addition, we only computed EUNS for the period of the fiscal budget announcement for the US, Turkey, and Hong Kong. The results indicate that the gold index, interest rate, and exchange rate are highly significant and negative macroeconomic factors for all analyzed countries. These findings also indicate that EUNS is important and detrimental for projecting stock returns.
Application of Deep Learning on the Prognosis of Cutaneous Melanoma Based on Full Scan Pathology Images
Authors: Li Anhai , Li Xiaoyuan , Li Wenwen , Yu Xiaoqian , Qi Mengmeng , Li Ding
Published: August 2022

Introduction. The purpose of this study is to use deep learning and machine learning to learn and classify patients with cutaneous melanoma with different prognoses and to explore the application value of deep learning in the prognosis of cutaneous melanoma patients. Methods. In deep learning, VGG‐19 is selected as the network architecture and learning model for learning and classification. In machine learning, deep features are extracted through the VGG‐19 network architecture, and the support vector machine (SVM) model is selected for learning and classification. Compare and explore the application value of deep learning and machine learning in predicting the prognosis of patients with cutaneous melanoma. Result. According to receiver operating characteristic (ROC) curves and area under the curve (AUC), the average accuracy of deep learning is higher than that of machine learning, and even the lowest accuracy is better than that of machine learning. Conclusion. As the number of learning increases, the accuracy of machine learning and deep learning will increase, but in the same number of cutaneous melanoma patient pathology maps, the accuracy of deep learning will be higher. This study provides new ideas and theories for computational pathology in predicting the prognosis of patients with cutaneous melanoma.
A Forward-Looking Study on the In-Depth Development Planning of Information Technology into Teacher Education
Authors: Zhang Chunlan
Published: August 2022

Teacher professional education development is actually another type of development that crosses over into a category of teacher training development that encompasses two other types of teacher training—one of which is formal and the other is informal teacher training. The other approach to teacher professional development is quite different from the professional development of professional education. The focus of the professional development of teachers is a dynamic process of development in which teachers take the initiative, actively, and consciously pursue the direction of professional development of teachers. Therefore, how to observe and study the direction of teachers’ professional development from the perspective of teachers is an urgent problem that needs to be studied and solved. The professional development of teachers should be combined with their own social and teaching lives. In addition, information technology should be integrated into teachers’ daily teaching life, so that it can be used as a tool to support teachers’ professional development. Information technology has gradually become a tool and a means that teachers cannot do without in their teaching lives, so it is important to study and think about it from various aspects, such as the teaching process and teachers’ growth experiences, and to continuously study teachers’ professional development. Therefore, it is necessary to study how information technology can be used well by teachers and used by teachers to become a useful tool in teachers’ educational and teaching work from various aspects. This paper first argues that the main goal of teachers’ professional development is to gradually grow into expert teachers, while the main content of teachers’ professional development is to understand practical knowledge, and the specific tool used by teachers in teaching is the application of social software support that can support teachers’ professional development (Romanowski and Alkhateeb, 2022). This paper envisages that information technology can be integrated into the entire teaching environment and the teaching process of teachers, as a tool and a means to make the content of teachers’ teaching more concise and clear. Through the use of information technology and other tools, teachers can gradually identify what they need to improve and add to their teaching process, lay the foundation for their future development, and pave the way to become better teachers with a clearer plan for their future development.
Combining Network Pharmacology with Experimental Validation to Elucidate the Mechanism of Salvianolic Acid B in Treating Diabetic Peripheral Neuropathy
Authors: Wang Qianqian , Li Xiaogang , Cao Lijun , Li Yan , Liu Yonghui , Sun Lianqing
Published: August 2022

Background. Salvianolic acid B (Sal B) is a bioactive component of Radix Salviae, which has antiinflammation and antiapoptotic activity in diabetic complications. However, the molecular mechanism of action of Sal B on diabetic peripheral neuropathy (DPN) is unknown. This study was designed to identify a mechanism for Sal B in the treatment of DPN by using a pharmacology network, molecular docking, and in vitro experiments. Methods. Sal B and DPN-related targets from Gene Cards and OMIM platforms were retrieved and screened. Then, an analysis of possible targets with STRING and Cytoscape software was conducted. KEGG signaling pathways were determined using the R software. Subsequently, the binding capacity of Sal B to target proteins was analyzed by molecular docking and in vitro experiments. Results. A total of 501 targets related to Sal B and 4662 targets related to DPN were identified. Among these targets, 108 intersection targets were shared by Sal B and DPN. After topological and cluster analysis, 11 critical targets were identified, including p38MAPK. KEGG analysis revealed that the AGE-RAGE signaling pathway likely plays an important role in Sal B action on DPN. The p38MAPK protein is a key target in the AGE-RAGE signaling pathway. Molecular docking results suggested that Sal B and p38MAPK have excellent binding affinity (<−5 kcal/mol). The in vitro experiments revealed that Sal B downregulates the expressions of p-P38MAPK, inflammatory cytokines, and apoptosis targets, which are upregulated by hyperglycemia. Conclusion. Sal B may alter DPN by inhibiting inflammation and apoptosis activated by p38MAPK.
Multistrategy Harris Hawks Optimization Algorithm Using Chaotic Method, Cauchy Mutation, and Elite Individual Guidance
Authors: Wen Lei , Wang Guopeng , Yue Longwang , Liang Xiaodan , Chen Hanning
Published: August 2022

Aiming at the shortcomings of the Harris hawks optimization algorithm (HHO), such as poor initial population diversity, slow convergence speed, poor local optimization ability, and easily falling into local optimum, a Harris hawks optimization algorithm (CCCHHO) integrating multiple mechanisms is proposed. First, the population diversity is enhanced by the initialization of the chaotic method. Second, the cosine function is used to better simulate the characteristics of the periodic change of the energy of the prey in the repeated contests with the group of hawks, to better balance the exploration and exploitation of the algorithm. Third, Cauchy mutation on the optimal individual in the exploration phase is performed, and the characteristics of the Cauchy distribution to enhance the diversity of the population are used, which can effectively prevent the algorithm from falling into the local optimum. Fourth, the local optimization ability of the algorithm by using the ergodicity of the chaotic system in the exploitation phase to perform a chaotic local search for the optimal individual is enhanced, which can effectively jump out after the algorithm falls into the local optimum. Finally, we use the elite individuals of the population to guide the position update of the population’s individuals, fully communicate with the dominant individuals, and speed up the convergence speed of the algorithm. Through the simulation experiments on CCCHHO with 11 different benchmark functions, CCCHHO is better than the gray wolf optimization algorithm (GWO), the Salp swarm algorithm (SSA), the ant lion optimization algorithm (ALO), and three improved HHO algorithms in terms of convergence speed and optimization accuracy, whether it is a unimodal benchmark function or a multimodal benchmark function. The experimental results show that CCCHHO has excellent algorithm efficiency and robustness.
Risk Factors for Esophageal Squamous Cell Carcinoma in Patients with Head and Neck Squamous Cell Carcinoma
Authors: Wang Lei , Pang Wenjing , Zhou Kun , Li Lei , Wang Feng , Cao Wei , Meng Xiangjun
Published: August 2022

Background. Esophageal squamous cell carcinoma (ESCC) is a common second primary neoplasia in patients with a history of head and neck squamous cell carcinoma (HNSCC). The aim of this study was to provide further information and novel insights into the risk factors for ESCC in patients with HNSCC. Methods. We retrospectively analyzed 98 HNSCC patients diagnosed from 2007 to 2017, 30 HNSCC patients suffering from ESCC, who had undergone endoscopic examination because of positive imaging examinations or symptoms, and 68 HNSCC patients who had no ESCC occurrence for at least six years post-HNSCC diagnosis. Associated clinicopathological data and lifestyle information of the ESCC group and the without ESCC group were collected, and a case-control study of risk factors was analyzed between the two groups. Results. The majority (83.4%) of the cases with HNSCC esophageal cancers were male patients over 50 years. We established that 93.75% (30/32) of the ESCC occurred within six years after HNSCC diagnosis. HNSCC location, stage, and radiotherapy history had no significant association with the development of ESCC. High Ki67 labeling index (Ki67 LI) (>46) patients tended to be 3.1 times (95% CI = 1.3–7.6) more likely to develop ESCC compared to low Ki67 LI (≤45) patients (

P
<
0.05

). Drinkers with alcohol flushing response were at a 3.3 times higher risk to have ESCC (95% CI = 1.0–10.4) than drinkers without flush response (

P
<
0.05

). Conclusions. HNSCC patients, especially drinkers with an alcohol flushing response, as well as those with high Ki67 LI of HNSCC tissue, were more likely to develop ESCC.
Effects of Aerosol Inhalation Combined with Intravenous Drip of Polymyxin B on Bacterial Clearance, Symptoms Improvement, and Serum Infection Indexes in Patients with Pneumonia Induced by Multidrug-Resistant Gram-Negative Bacteria
Authors: Lin Hanlu , Liu Xiaobo , Sun Pengfei
Published: August 2022

In recent years, the incidence of pneumonia caused by multidrug-resistant (MDR) Gram-negative bacteria (G−) has increased year by year. Polymyxin B has a good clinical effect in the treatment of MDR, but there is controversy about the administration route of this drug. In this study, we retrospectively analyzed the clinical data of 84 cases of MDR Gram-negative bacterial pneumonia, and aimed to explore the effects of aerosol inhalation combined with intravenous polymyxin B infusion on the bacterial clearance, symptom improvement, and serum infection indexes of MDR patients on the patients with Gram-negative (G−) bacterial pneumonia. The results show that aerosol inhalation combined with intravenous drip of polymyxin B can improve bacterial clearance rate, reduce levels of serum inflammatory factors, and improve clinical symptoms in patients with pneumonia induced by MDR G-bacteria.
Endothelium, Platelets, and Coagulation Factors as the Three Vital Components for Diagnosing Bleeding Disorders: A Simplified Perspective with Clinical Relevance
Authors: Bhattarai Abhinav , Shah Sangam , Bagherieh Sara , Mirmosayyeb Omid , Thapa Sangharsha , Paudel Sandip , Gyawali Pawan , Khanal Pitambar
Published: August 2022

Bleeding disorders are a major group of hematological disorders, which are highly prevalent in the world. Excessive bleeding can result in serious consequences including hypoperfusion and cardiac arrest. The body has its selfmechanism to control excessive bleeding which is termed hemostasis. Hemostasis is achieved in two major steps, the formation of the primary and secondary hemostatic plugs. Endothelium, platelets, and coagulation factors are three components involved in hemostasis. Endothelium and platelets have a major role in forming the primary hemostatic plug. Consequently, the first step in investigating a bleeding disorder is platelet count. Despite normal platelet count, abnormality in the primary hemostatic plug may arise due to functional defects of the platelets including adhesion, activation, and aggregation. Von Willebrand disease (VWD) is an endothelial defect and the most prevalent inherited defect in coagulation. Abnormalities in the secondary hemostatic plug are largely due to coagulation factor deficiencies, and, to a lesser extent, the presence of inhibitors. Techniques involving viscoelastics have been aiding in rapid diagnosis and are useful in point-of-care testing. This article discusses the investigation of bleeding disorders from the perspective of the endothelium, platelet, and coagulation factor physiology. These three components should be properly investigated to achieve the definitive diagnosis of bleeding disorders.
Experimental Study on Double Row Micropiles and Anchors Composite Retaining Structure in Deep Fill Site
Authors: Liu Wenfeng , Mao Jie , Zhao Hongxing , Shao Guangbiao
Published: August 2022

In recent years, with the continuous advancement of urbanization in China and the gradual increase in the utilization scale of underground space, foundation pits may build in a narrow and compact environment. Meanwhile, miscellaneous fill layers in the city may cause construction difficulties when new foundation pits are excavated and supported. While we focus on the above problems, new retaining structure forms which are safe and economical are urgently needed. In this study, based on the excavation in a deep filling site in Jinan, the double row micropiles and anchors composite retaining structure is monitored under excavation, loading, and unloading conditions by installing sensors and testing. The stress and axial force distribution of the front and back row micropiles and anchors in the composite retaining system under different excavation depths and different loads are analyzed. The performance changes of the front and back row micropiles under different conditions and the contribution of anchors at different depths to the structure resistance during excavation and loading tests are discussed. The results show that double row steel piles and anchors composite retaining structure is feasible when excavating deep fill site in the urban area. In the composite retaining system, the stress of the front pile is greater than the back pile, the back pile has a lag when it starts working, and the axial force of the middle and upper anchor is greater than that of the bottom anchor.
Modern Fiber Art Creation Based on Traditional Hakka Hand Tie-Dyeing Process Based on Carbon Nanotube Nanomaterials
Authors: Zhang Fuying
Published: August 2022

With the change of the times, modern fiber art has greatly changed and developed in the traditional technology. This artistic expression brings people richness in form and artistic language and is a kind of performance art between art and decoration. Modern fiber art is a part of life. With the change of living environment, people's things will also change, so if we want to adapt, we have to change appropriately. Molecular dynamics and calculation of resistance values are used to study the relationship between the length, cross section, and temperature of materials in carbon nanotube composites. Modern fibers are mainly made of composite materials such as carbon nanotubes. This paper mainly uses the repeated expansion of polymer carbon nanotube materials, uses the interaction between electrons and phonons as well as the interaction between phonons and phonons to test the thermal conductivity value and the curing regime of different composite materials at different stages, and in order to study the thermal conductivity of carbon nanotube composites, the relevant data in the model are set to a unified packing density system and melting point, uses the temperature of 280 K and 320 K to normalize the composite materials, and explores the change law of the heat flow correlation function and the thermal conductivity. It can be seen from the experimental data that the heat flow correlation function changes with time and gradually becomes stable and finally fluctuates around 0, which means that the model is in a stable state and the scheme is feasible. With the development of the times, fiber art has various forms of expression, and this art is expected to shine in all walks of life.
On the Analysis and Assessment of First-Order Group Contribution Models for the Calculation of Normal Boiling Point and Critical Properties of Pure Compounds
Authors: Villazón-León Vanessa , Bonilla-Petriciolet Adrián , Tapia-Picazo Juan Carlos
Published: August 2022

The thermodynamic properties of pure compounds are relevant data for process systems engineering. Different first-order group contribution models have been reported in the literature to calculate these properties and they are also widely employed in commercial process simulators. However, they may have some limitations and, consequently, a reliable comparison of these models is required to analyze their performance and to determine the best alternative for the calculation of pure compound properties. This paper reports the implementation and evaluation of several first-order group contribution models to calculate the normal boiling point and critical properties (temperature, pressure, and volume) of pure compounds. The performance of these models was characterized and compared for several compound families using a standardized approach to determine their group contributions and parameters. An artificial neural network model was also applied and assessed to improve the estimations obtained with the best group contribution models. Results showed that the calculation of critical temperature was challenging for several compound families where AARD values ranged from 0.05 to 56.28%, while the group contribution models were more accurate to estimate the critical volume with AARD values ranging from 0.48 to 35.99%. This study allows us to identify the limitations and gaps of this type of thermodynamic models with the objective of improving its performance for the calculation of pure compound thermodynamic properties. The findings of this study can help to enhance the capabilities of thermodynamic models for the calculation of the normal boiling point and critical properties of pure compounds, which are relevant for the process systems engineering of new operations and products.
Markov Model-Based Learning Aid for Students’ Civics Course
Authors: Zang Xiaohui , Bai Chengming
Published: August 2022

Since the 19th National Congress, students’ ideological education has become more and more one of the national priorities, so the Civics course has become one of the essential compulsory courses for students at all stages of school and university, and the learning methods of Civics course have also become a hot issue of concern to students, which makes the learning process of supplementary learning methods very important. In this paper, a Markov model was developed to calculate the probability transfer matrix and predict the supplementary learning methods used by students. This paper also establishes a Markov model to predict the frequency of students’ online classroom learning at different stages, and it is found that, in the future, more and more students will use the Internet for their Civics course assisted learning; therefore, it is very important to establish a perfect Civics course online assisted learning platform, and this paper also puts forward some suggestions for establishing a Civics course online assisted learning system, which provides some methods for subsequent students’ Civics course learning. This paper also proposes some suggestions for establishing a web-assisted learning system for Civics courses and provides some methods for subsequent student learning in Civics courses.
An Enhanced Multiobjective Double Row Layout Model considering the Machine Breakdowns
Authors: Duan Shengze , Kang Ling
Published: August 2022

Machine breakdowns (MB) often occur, resulting in changes in the production layout and the material flow and causing a surge in production cost. Obviously, it is imperative to consider MB in workshop layout. Scholars mainly focus on the double row layout problem in an ideal nonfailure condition while scarcely considering MB mentioned above in the layout field. This paper proposes an enhanced multiobjective double row layout model considering MB (MDRLP-MB) to fill the research gaps. That model adds redundancy to reduce the losses caused by machine failure based on the prediction of breakdowns. In MDRLP-MB, machines with the same machine type have the same size and failure rate. Besides, this paper redefines the biobjectives of material handling costs (MHC) and the utilization ratio based on the feature of MDRLP-MB. To reduce the complexity of the problem, a decision rule is developed to reduce the alternative machine types. Furthermore, it revises the NSGA-II to solve the MDRLP-MB effectively. Results of numerical experiments and application cases show MDRLP-MB can obtain the optimal set of Pareto solutions in the case of increasing different numbers of redundancy considering MB to provide a more refined layout scheme for decision making.
Construction of Ideological and Political Practice Teaching System of Documentary Creation Course Based on Deep Learning
Authors: Ren Qiwei
Published: August 2022

In order to improve the effect of landscape design, a landscape design method based on distributed integrated model is proposed. Based on the spatial location information, ancient books and documents, POI data, and text data of garden landscape, a multisource distributed data distribution model of garden landscape design is established. Extract the word frequency of keywords to calculate the garden heat, and analyze the pattern and changes of garden landscape according to the landscape index. The distribution and integration model of landscape design is established, which takes history and culture, landscape ecology, tourism, and health as the control object parameters, and the spatial relationship between landscape and its adjacent areas is studied by image integration. The virtual three-dimensional visual reconstruction method is used to optimize the landscape design and image processing. The simulation test results show that the distributed integration ability of landscape design using this method is better, and the visual performance effect is better, which improves the visual expression effect and design quality level of landscape design.