bluuebunny/crossref_metadata_2025 huggingface dataset:
In Silico Screening of Synthetic and Natural Compounds to Inhibit the Binding Capacity of Heavy Metal Compounds against EGFR Protein of Lung Cancer
Authors: Ayaz Zainab , Zainab Bibi , Rashid Umer , Darwish Noura M. , Gatasheh Mansour K. , Abbasi Arshad Mehmood
Published: May 2022

Inorganic pollutant, specifically heavy metals’ contamination, is a significant matter of concern and is one of the key contributors in various health disorders including cancer. However, the interaction of heavy metals (HMs) with lung cancer has rarely been explored yet. Therefore, the present study was intended with the aim to identify the interactions of HMs with the target protein “epidermal growth factor receptor (EGFR)” of lung cancer and explore potential drug candidates, which could inhibit the active site of EGFR against HM exposure. The molecular operating environment (MOE) tool was used to study the interactions of HMs with EGFR protein. The drug‐drug interaction (DDI) network approach was used to identify the potential drug candidates, which were further confirmed and compared with the commercial medicines/control group. Various compounds of twenty‐three HMs were docked with EGFR protein. Out of which tinidazole, thallium bromodimethyl, and silver acetate (Sn, Ti, and Ag compounds) showed strong interactions with EGFR based on lowest‐scoring values (‐20.42, ‐7.86, and ‐7.74 kcal/mol, respectively). Among 1280 collected drug candidates, three synthetic compounds viz., ZINC00602803, ZINC00602685, and ZINC06718468 and three natural compounds (berberine chloride, transresveratrol, and ellagic acid) depicted strong binding capacity with EGFR. Specifically, the scoring value of ZINC00602803 (‐30.99 kcal/mol) was even lowest than standard lung cancer drugs (afatinib, erlotinib, and gefitinib). Our findings revealed that both natural and synthetic compounds having strong associations with EGFR protein could be potential candidates to inhibit the interaction between HMs and lung cancer protein and can also be used as an alternative for the prevention and treatment of lung cancer. However, in vitro and in vivo studies should be conducted to validate the aforementioned natural and synthetic compounds.
Could a Dolutegravir-Based Antiretroviral Therapy Lead to Clinical Obesity? A Retrospective Cohort Study Conducted at Hawassa University Comprehensive Specialized Hospital in Hawassa, Sidama, Ethiopia
Authors: Eifa By Aberash , Ketema Worku
Published: May 2022

Background. As of April 2019, the dolutegravir (DTG)-based regimen is replacing the efavirenz-based regimen in Ethiopia, mainly due to its superiority in viral load suppression. However, there is a growing concern about this medication-based regimen, the most serious of which is excessive weight gain. In this study, we looked at weight gain disparities among human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) patients on antiretroviral therapy (ART) who have been shifted to tenofovir/lamivudine/dolutegravir (TLD) from a tenofovir/lamivudine/efavirenz (TLE)-based regimen versus those who are maintained on a tenofovir/lamivudine/efavirenz-based regimen. Methods. A facility-based retrospective observational cohort study was conducted in pursuit of weight change disparities between tenofovir/lamivudine/dolutegravir and tenofovir/lamivudine/efavirenz-based regimens among patients who have attained optimal viral suppression at Hawassa University Comprehensive Specialized Hospital antiretroviral clinic. Chi-square and logistic regression were used as appropriate using an SPSS version 21 program to test the association of specific variables to outcome variables, and a

P

value <0.05 was considered statistically significant. Results. This study included 422 patients, 211 of whom were switched from tenofovir/lamivudine/efavirenz to tenofovir/lamivudine/dolutegravir and the remaining were who kept on a tenofovir/lamivudine/efavirenz-based regimen. Patients on a tenofovir/lamivudine/dolutegravir-based regimen had a mean weight gain of 3.88 ± 2.021 kg in one year compared to those on TLE (2.26 ± 2.39). In a bivariate analysis, being male was found to protect against unwanted weight gain at COR 0.531 (0.345, 0.816). A current CD4 count of more than 500 has been found to be strongly correlated with weight gain in multivariate analysis at an AOR of 0.315 (0.188, 0.527) at a

P

value ≤0.001. Conclusion. According to this study, tenofovir/lamivudine/dolutegravir (TLD)-based antiretroviral medication (ART) users are more likely to gain weight, and clinicians should advise them of the risks of weight gain as well as cost-effective ways to prevent weight gain linked to poor health outcomes in these patients. Future investigations should confirm the findings of this study, and more research into the effects of weight gain in these people is required.
Prognostic Value of Immunotyping Combined with Targeted Therapy in Patients with Non-Small-Cell Lung Cancer and Establishment of Nomogram Model
Authors: Tian Sha , Guo Yinmei , Fu Jiajun , Li Zijing , Li Jing , Tian Xuefei
Published: May 2022

Objective. Bioinformatics methods were used to analyze non-small-cell lung cancer gene chip data, screen differentially expressed genes (DEGs), explore biomarkers related to NSCLC prognosis, provide new targets for the treatment of NSCLC, and build immunotyping and line-map model. Methods. NSCLC-related gene chip data were downloaded from the GEO database, and the common DEGs of the two datasets were screened by using the GEO2R tool and FunRich 3.1.3 software. DAVID database was used for GO analysis and KEGG analysis of DEGs, and protein-protein interaction (PPI) network was constructed by STRING database and Cytoscape 3.8.0 software, and the top 20 hub genes were analyzed and screened out. The expression of pivot genes and their relationship with prognosis were verified by multiple external databases. Results. 159 common DEGs were screened from the two datasets. PPI network was constructed and analyzed, and the genes with the top 20 connectivity were selected as the pivotal genes of this study. The results of survival analysis and the patients’ survival curve was reflected in the line graph model of NSCLC. Conclusion. Through the screening and identification of the VIM-AS1 gene, as well as the analysis of immune infiltration and immune typing, the successful establishment of the rosette model has a certain guiding value for the molecular targeted therapy of patients with non-small-cell lung cancer.
Application of Enhanced T1WI of MRI Radiomics in Glioma Grading
Authors: Zhou Hongzhang , Xu Rong , Mei Haitao , Zhang Ling , Yu Qiyun , Liu Rong , Fan Bing
Published: May 2022

Objective. To explore the application value of the radiomics method based on enhanced T1WI in glioma grading. Materials and Methods. A retrospective analysis was performed using data of 114 patients with glioma, which was confirmed using surgery and pathological tests, at our hospital between January 2017 and November 2020. The patients were randomly divided into the training and test groups in a ratio of 7 : 3. The Analysis Kit (AK) software was used for radiomic analysis, and a total of 461 tumor texture features were extracted. Spearman correlation analysis and the least absolute shrinkage and selection (LASSO) algorithm were employed to perform feature dimensionality reduction on the training group. A radiomics model was then constructed for glioma grading, and the validation group was used for verification. Results. The area under the ROC curve (AUC) of the proposed model was calculated to identify its performance in the training group, which was 0.95 (95% CI = 0.905–0.994), accuracy was 84.8%, sensitivity was 100%, and specificity was 77.8%. The AUC of the validation group was 0.952 (95% CI = 0.871–1.000), accuracy was 93.9%, sensitivity was 90.0%, and specificity was 95.6%. Conclusions. The radiomics model based on enhanced T1WI improved the accuracy of glioma grading and better assisted clinical decision-making.
QSPR Modeling with Topological Indices of Some Potential Drug Candidates against COVID‐19
Authors: Çolakoğlu Özge
Published: May 2022

COVID‐19, which has spread all over the world and was declared as a pandemic, is a new disease caused by the coronavirus family. There is no medicine yet to prevent or end this pandemic. Even if existing drugs are used to alleviate the pandemic, this is not enough. Therefore, combinations of existing drugs and their analogs are being studied. Vaccines produced for COVID‐19 may not be effective for new variants of this virus. Therefore, it is necessary to find the drugs for this disease as soon as possible. Topological indices are the numerical descriptors of a molecular structure obtained by the molecular graph. Topological indices can provide information about the physicochemical properties and biological properties of molecules in the quantitative structure‐property relationship (QSPR) and quantitative structure‐activity relationship (QSAR) studies. In this paper, some analogs of lopinavir, favipiravir, and ritonavir drugs that have the property of being potential drugs against COVID‐19 are studied. QSPR models are studied using linear and quadratic regression analysis with topological indices for enthalpy of vaporization, flash point, molar refractivity, polarizability, surface tension, and molar volume properties of these analogs.
Quality Evaluation of Ranunculaceae Essential Oil with the Artificial Neural Network
Authors: Wang Xiaoxia
Published: May 2022

The goal of this project is to use ANN to build a quality evaluation method for Ranunculaceae essential oils in order to assist businesses or individuals in setting up an automated essential oil quality evaluation system and reducing human resource consumption. Using computer software to evaluate the quality of Ranunculaceae essential oils, quantitatively evaluate product quality, and improve the automation of quality evaluation. The main research contents in this paper are as follows: (1) In-depth research on PSO and its development. The purpose of studying the PSO is to use PSO to replace gradient descent algorithm in BP network, so that the neural network model has a better network structure. This paper improves it on the basis of PSO. The basic improvement idea is to add a dynamic random position transformation to the particle, so that global optimization ability can be enhanced. The improved algorithm and the standard algorithm are compared and analyzed in the simulation experiments. The results verify that improved PSO has better optimization ability. (2) Replace training algorithm in the BP network with the IPSO and construct the BP network algorithm model of IPSO. The final implementation of the Ranunculaceae plant essential oil quality assessment model based on the IPSO-BP network was achieved by combining the Ranunculaceae plant essential oil quality evaluation index system with the Ranunculaceae plant essential oil quality evaluation index system. Finally, a simulation experiment was designed to compare the presentation of PSO-BP and IPSO-BP, when they were applied to the evaluation of Ranunculaceae vital oils. The experimental results show IPSO-BP has the highest estimate accuracy and the best performance.
Evaluation of Innovation Efficiency on Chinese Commercial Banks under the Internet Finance: A DEA-Malmquist Index-Based Approach
Authors: Zhao Kun , Pi Jiaming , Zhang Tao
Published: May 2022

The development of the digital economy and internet finance greatly impacts the technological innovation of Chinese commercial banks. Therefore, most of the Chinese commercial banks have invested a lot of money in the new information technology applications to adapt to the impacts of internet finance. Consequently, whether these investments have achieved the expected effect and efficiency has been concerned by these banks. For these concerns, we have used relative data from 49 Chinese commercial banks from 2010 to 2020 period and used the DEA-BCC model and DEA-Malmquist index to analyze their innovation efficiency from both static and dynamic perspectives. Our study found that from the static perspective, the innovation efficiency greatly varies among the banks in the study, and most banks have room for improvement in pure technical efficiency and scale efficiency. From the dynamic perspective, the innovation efficiency of the banks in the study is generally on the rise. Changes in technical efficiency play a major role in improving their overall efficiency, and technological progress is the second driving force. Therefore, technological investment should be increased, and technological levels should be improved to improve innovation efficiency. Our study also shows that, according to the ownership types, different groups of banks have differently shown their innovation efficiencies. Joint-stock commercial banks have the highest innovation efficiency, while rural commercial banks have the lowest innovation efficiency. Our study suggests that all Chinese commercial banks should overcome their own shortages in information technological innovation capability to elevate their innovation efficiency, under the background of internet finance.
Data Protection Software for Civil Aviation Control Flight Information System Based on FPE Algorithm
Authors: Lu Jing
Published: May 2022

This study is aimed in order to study the data protection software of civil aviation management flight information system based on FPE algorithm. The author established the data warehouse software of the air traffic control production information statistics system. First, using the Jquery browser application framework + service-oriented Web Service architecture technology, a B/S/S multilayer data application based entirely on browser applications is established. Then, with the support of the ATC production information statistical data warehouse software and the system application framework, the system realizes a series of production data processing related to production information management, such as data collection, data editing, data review, and business data statistics. Finally, combined with the attributes of business data, we analyze and compare all kinds of production information from multiple dimensions such as time and region; it also provides users with data analysis results of curve, pie, column, and other performance situations, display mode, and report output tool. SQL statement can be implemented to add data to the database, modify the existing data in the database, delete the existing data in the database, and can be queried in a variety of ways to the data in the database, and VB provides a human-computer interaction interface for various operations.
Grid Management Optimization of College Students under Artificial Intelligence and Wireless Networks
Authors: Jin Peng , Zhang Qi
Published: May 2022

The work is aimed at solving the problem of colleges and universities to expand the enrollment scale and optimize the management strategy. Based on grid management theory, wireless communication network, NET framework technology, and the browser/server (B/S) framework, a grid security management system is presented. Grid knowledge is explained, wireless communication network address calculation and analysis are mentioned, and NET framework technology and analysis of B/S framework technology optimized by C/S (client/server) framework technology are discussed. The grid management system is built on this foundation and applied to university management. Two questionnaires are designed to explore the grid management of students and faculty. Students believe that the system can effectively solve their management problems, and teachers and workers believe that the system can optimize their work. These results show that the grid management system can be applied to the management of colleges and universities, which provides some ideas for optimizing the management strategy of colleges and universities.
Wearable Power Assistant Robot Sensor Signal Prediction Algorithm and Controller Design
Authors: Li Gang , Ren Guoheng
Published: May 2022

The wearable power-assisted robot is a typical auxiliary rehabilitation robot. It is an exoskeleton power-assisted device that helps people to expand their lower limb movement capabilities. Its basic principle is to obtain the motion intention information of the human body through the perception system. Control the DC servo motor installed at the hip joint and the knee joint to drive the movement of the link, so as to achieve the purpose of providing assistance to the human body. In order to improve the dynamic response frequency of the wearable robotic perception system, a sensor signal based on time series analysis is proposed. The online prediction algorithm, which can perform single-step or multistep prediction under the premise of ensuring certain accuracy, can multiply the dynamic response frequency of the wearable-assisted robot sensing system to ensure the real-time performance of the whole system. In order to realize the sensor signal prediction algorithm, we design the corresponding software and hardware system to realize the prediction algorithm. The whole sensor signal prediction algorithm implementation system can be divided into two parts: lower computer and upper computer. The lower computer includes amplification circuit, signal conditioning circuit, and acquisition. The signal processing software part of the circuit and the corresponding MCU and the upper computer mainly include the data acquisition and prediction algorithm implementation, and the upper computer adopts the mixed programming technology of Vc++ and MATLAB to complete the software part of the upper computer. Aiming at the control part of the wearable robotic sensing system, the first generation of DC servo motor embedded motion controller is designed. The motion controller adopts the design concept of embedded motion controller, which has small size, is light weight, and has good expandability. And the motion controller can communicate and debug with the host computer through the serial port, which lays a foundation for the design of the entire embedded control system.
Resource Allocation Strategy of the Educational Resource Base for MEC Multiserver Heuristic Joint Task
Authors: Luo Ning
Published: May 2022

This paper analyzes the application of MEC multiserver heuristic joint task in resource allocation of the educational resource database. After constructing the scenario of educational resource database, a mathematical model is constructed from the dimensions of local execution strategy, unloading execution, and given educational resource allocation, in order to optimize the optimal allocation of educational resources through MEC. The results show that the DOOA scheme has good performance in terms of calculation cost and timeout rate. Compared with other benchmark schemes, the DQN-based unloading scheme has better performance, can effectively balance the load, and is better than the random unloading scheme and the SNR-based unloading scheme in terms of delay and calculation cost. The results show that the total hits of all category 1 users' content requests account for the proportion of the total content requests. The images have a small downward trend at the 15000 and 30000 time slots and then continue to rise. This shows that the proposed scheme can automatically adjust the caching strategy to adapt to the changes of content popularity, which proves that the agent can correctly perceive the changing trend of content popularity when the popularity of network content is unknown and improve the caching strategy accordingly to improve the cache hit rate. Therefore, the allocation of educational resources based on the MEC multiserver heuristic joint task is more reasonable and can achieve the optimal solution.
The Generalized Fractional Proportional Delta Operator and New Generalized Transforms in Discrete Fractional Calculus
Authors: Amalraj J. Leo , Susai Manuel M. Maria , Meganathan M. , Syed Ali M.
Published: May 2022

In this research work, the aim is to develop the fractional proportional delta operator and present the generalized discrete Laplace transform and its convolution with the newly introduced fractional proportional delta operator. Moreover, this transform is a connection between Sumudu and Laplace transforms, which yields several applications in pure and applied science. The research work also investigates the fractional proportional differences and its sum on Riemann–Liouville and Mittag–Leffler functions. As an application of this research is to find new results and properties of fractional Laplace transform, the comparison of the existing results with this research work is also done. Moreover, we used the two types of solutions, namely, closed and summation forms in Laplace transform and verified with numerical results.
FLG Is a Potential Biomarker of Prognosis and Immunotherapy in Skin Cutaneous Melanoma
Authors: Wu Shaobo , Liang Yuxia , Zang Qijuan , Xing Zixuan , Yin Pan , Sun Ruifang , Dai Bingling
Published: May 2022

Background. Skin cutaneous melanoma is one of most aggressive type of cancers worldwide. Therefore, the identification of SKCM biomarkers is of great importance. FLG gene is one of the genes that encode proteins involved in epidermal formation. This was the first time to study the role of FLG in the prognosis and immune infiltrates of skin cutaneous melanoma. Methods. We downloaded the somatic mutation data of 471 SKCM patients from the Cancer Genome Atlas (TCGA) database and analyzed the mutation profiles with “MafTools” package. The expression of FLG and the overall survival in SKCM were analyzed by GEPIA. Additionally, univariate and multivariate Cox analyses were used to compare several clinical features with survival rates. We used TIMER to investigate FLG expression and collection of immune infiltration levels in SKCM, as well as cumulative survival in SKCM. Meanwhile, we also used CIBERSORT to investigate the association between FLG and cancer immune infiltration. In addition, gene set enrichment analysis (GSEA) was performed using the TCGA dataset. Furthermore, data from GEO and HPA was used to validate the results. Results. Single nucleotide polymorphism (SNP) happened more frequently than insertion or deletion, and C > T was the most common of SNV in SKCM. We selected the first 15 mutated genes by analyzing 471 melanoma samples, and the prognosis analysis showed that only the high expression of mutated FLG gene was significantly correlated with the poor prognosis of SKCM. Multivariate Cox analysis showed that age, the worse tumor status, less lymph node metastasis, and FLG expression were independent factors for prognosis. Specifically, lower infiltration levels of B cell, CD8+ T cells, neutrophils, and dendritic cells correlated with poor survival outcomes in SKCM. GSEA revealed that FLG is closely related to cancer pathways and epidermal cell proliferation. In addition, the previous conclusions can be verified from external data from GEO and HPA. Conclusion. The discovery of mutant gene FLG as a biomarker of SKCM helps elucidate how changes in the immune environment promote the occurrence of cutaneous melanoma. Further analysis suggested that FLG might be a new predictor of SKCM prognosis.
The Construction of Sports Health Management Model Based on Deep Learning
Authors: Meng Junniao , Wang Song
Published: May 2022

Deep learning is a new direction in the field of machine learning. It learns the inherent laws and representation levels of sample data. The information obtained in the learning process plays a great role in interpreting data such as text, images, and speech. Health management refers to the process of identifying, evaluating, and effectively intervening the health of individuals or groups of people. The purpose of this article is to build a sports health management model based on deep learning, to train students to actively take physical exercises, thereby promoting their physical fitness. This article first introduces related concepts such as deep learning and convolutional neural networks and then conducts an experimental exploration on the combination of convolutional neural networks and multilayer perceptrons. Secondly, this article designs a plan for sports health management of sports interventions and compares and analyzes the data before and after health management. The experimental results show that the average value of the overall health dimension after the experiment has reached 85.28, and the average value has reached a very high score, indicating that exercise intervention can effectively improve the physical fitness of students. At the same time, it improves the physical condition of students.
Role of Bile Acids and Nuclear Receptors in Acupuncture in Improving Crohn’s Disease
Authors: Shen Jia-Cheng , Qi Qin , Han Dong , Liu Shi-min , Huang Rong , Zhu Yi , Zheng Han-dan , Gu Kan , Wu Huan-gan , Liu Hui-rong
Published: May 2022

Nuclear receptors (NRs) are ligand-dependent transcription factors that regulate the transcription of target genes. Bile acids (BAs) can be used as effector molecules to regulate physiological processes in the gut, and NRs are important receptors for bile acid signaling. Relevant studies have shown that NRs are closely related to the occurrence of Crohn’s disease (CD). Although the mechanism of NRs in CD has not been clarified completely, growing evidence shows that NRs play an important role in regulating intestinal immunity, mucosal barrier, and intestinal flora. NRs can participate in the progress of CD by mediating inflammation, immunity, and autophagy. As the important parts of traditional Chinese medicine (TCM) therapy, acupuncture and moxibustion in the treatment of CD curative mechanism can get a lot of research support. At the same time, acupuncture and moxibustion can regulate the changes of related NRs. Therefore, to explore whether acupuncture can regulate BA circulation and NRs expression and then participate in the disease progression of CD, a new theoretical basis for acupuncture treatment of CD is provided.
Comparative Analysis of the Efficacy of Transurethral Bipolar Plasma Needle Electrode and Ring Electrode in the Treatment of Non-Muscle-Invasive Bladder Cancer
Authors: Zheng Pei , Zhang Jianhua , Zhu Yahong , Guan Xiaodong , Quan Jianwen , Li Qi , Yi Fen
Published: May 2022

Bladder cancer is the most prevalent tumor of the urinary tract, ranking seventh in males and seventeenth in women. The gold standard for the definitive diagnosis and initial treatment of non-muscle-invasive bladder cancer is transurethral resection (TUR) of the bladder tumor. The ability to accurately detect disease, typically in the presence of hematuria as well as to detect early recurrent tumors in patients with a history of NMIBC, is critical to the successful treatment of non-muscle-invasive bladder cancer (NMIBC). Unfortunately, the current biomarker landscape for NMIBC is still evolving. Cystoscopy remains the gold standard, but it can still miss 10% of tumors. As a result, physicians frequently employ additional diagnostic tools to aid in the diagnosis of bladder cancer. The efficacy of transurethral bipolar plasma needle electrodes and ring electrodes in the treatment of non-muscle-invasive bladder cancer was compared and analyzed in this study. During our study, 100 patients with non-muscle-invasive bladder cancer admitted to our hospital between June 2019 and June 2020 were randomly assigned to a control group and an observation group, with 50 cases in each group. The observation group was given a bipolar plasma needle electrode, while the control group was given a bipolar plasma ring. Patients continued to receive bladder irrigation chemotherapy as well as traditional Chinese medicine (TCM) treatment as part of our treatment plan, while the control group received only bladder irrigation chemotherapy. Clinical factors such as operational blood loss, catheter indention time, length of hospital stay, and others were compared between the two groups. When the risk grades in the two groups were compared, the observation group had fewer medium- and high-risk grades than the control group, but the control group had more low-risk grades, with statistical significance (P < 0.05).
RNN Neural Network Model for Chinese-Korean Translation Learning
Authors: Dong Yang
Published: May 2022

Translation is the expression of words into other forms so that they are mutually understandable. However, the current Chinese-Korean translation information conversion model is not mature enough, and there are many defects and errors. This paper proposes an improved RNN neural network translation model. The translation model proposed in this study is an upgraded RNN neural network (a form of recurrent neural network). A decoder matching mode is included in the model, allowing it to learn both alignment and transformation at the same time. This allows for quicker neural network training, resulting in increased translation speed and efficiency. In addition, this article compares the BLEU scores of the BilingualCorpus Chinese-Korean corpus I, II, and III with those of the standard translation model. The test results suggest that the enhanced RNN model described in this research has an average BLEU score of roughly 45 points. The conventional model’s average BLEU score is just approximately 30 points. The BLEU score of the model in this paper has increased by about 15 points, indicating that the translation quality of the translation model in this paper has been significantly improved.
Heat Treatment Management of Radio Frequency Integrated Circuit IC Based on Deep Learning
Authors: Zhang Weijia , Rao Qiancheng , Gu Zhenjie
Published: May 2022

Integrated circuit (IC) is a microchip that consists of several electronic components which works as a single unit. Now, aiming at the problem of how to effectively dissipate the heat of the radio frequency integrated circuit in the work, in order to effectively manage the heat dissipation of the chip and to improve the working life of the IC chip, this paper uses the algorithm of convolutional neural network to analyze the IC chip based on deep learning. Identify and manage heat dissipation. The experiments show that the algorithm can effectively identify heat treatment, further improve the working time limit of IC circuits, and provide a reference for the research of IC heat treatment management.
Picture Fuzzy Einstein Hybrid-Weighted Aggregation Operator and Its Application to Multicriteria Group Decision Making
Authors: Cao Guo
Published: May 2022

As an extension of intuitionistic fuzzy sets (IFSs), picture fuzzy sets (PFSs) can better model and represent the hesitancy and uncertainty of decision makers’ preference information. In this study, we propose a multicriteria group decision making (MCGMD) method based on picture fuzzy sets. We first define some basic picture Einstein operations with closed properties among PFSs on the basis of the Einstein t-norms and t-conorms. Then, utilizing the hybrid-weighted operator and the developed picture Einstein operations laws, we put forward a picture fuzzy Einstein hybrid-weighted aggregation operator for aggregating PFSs and discuss its several important properties. Furthermore, we present a new MCGMD method based on the proposed picture fuzzy Einstein hybrid-weighted aggregation operator. Finally, an example is conducted to validate the effectiveness of the proposed MCGMD method.
Study of the Mechanical Properties of a CMDB Propellant Over a Wide Range of Strain Rates Using a Group Interaction Model
Authors: Xie Kan , Chen Xiaoxu , Li Yuejie , Bai Long , Wang Ningfei , Zhang Yiming , Xiao Haiyan
Published: May 2022

Composite modified double base (CMDB) propellants are heterogeneous propellants in which properties are significantly improved by adding solid particles into the polymer matrix. A molecular group interaction model that can predict the mechanical properties of polymers through a molecular structure is used to predict the viscoelastic behavior of the CMDB propellant. Considering that the addition of solid particles will improve the crosslinking degree between polymer molecules and reduce its secondary loss peak, the input parameters of the model are modified through dynamic mechanical analysis (DMA) experimental data. By introducing the strain rate into the expression of model glass transition temperature, the mechanical properties of propellant over a wide strain range (

1.7
×

10

−
4

 s-1 ~ 3000 s-1) are obtained. The reliability of the model is verified by comparison with uniaxial compression test data. By modifying the input parameters of the model, the effects of different mass ratios of nitrocellulose (NC)/nitroglycerin (NG) on the mechanical properties of the CMDB propellant were analyzed. The results show that the glass transition loss increases with increasing mass ratio of NC/NG, while Young’s modulus and yield stress decrease.
Analysis of English Cultural Teaching Model Based on Machine Learning
Authors: Yang Qianqian
Published: May 2022

According to the world population, nearly five billion people use mobile phones in their daily lives, and this has increased by 20% in the last twelve months compared to the previous report. An average survey conducted by researchers to find the amount of data consumed in a month by every mobile phone in the world has finally resulted in 45 exabytes of data being collected from a single user within a month. In today’s world, data consumption and data analytics are being considered as one of the most important necessities for e-commerce companies. With the help of such collected data from a person, it is possible to predict the future signature or activity of the person. If 45 terabytes of data can be stored for a single user, determining the average calculation and amount of data to be collected for five billion users appears to be much more difficult. More than the human working concept, it looks like it would be difficult for a traditional computer system to handle this amount of data. To study and understand a concept from machine learning and artificial intelligence requires quite a collection of data to predict according to a person’s activity. This article explains the roles of faculty and students, as well as the requirements for academic evaluation. Even before the pandemic, most people did not have any idea about the online teaching model. It is only after the disability of conducting direct (offline) classes that people are forced to get into the online world of teaching. Nearly 60% of countries are trying to convert their education systems to such online models, which improve communication between students and teachers and also enable different schemes for students. Big data can be considered as one of the technological revolutions in information technology companies that became popular after the crisis of cloud computing. A support vector machine (SVM) is proposed for analyzing English culture teaching and is compared with the traditional fuzzy logic. The results show the proposed model achieves an accuracy of 98%, which is 5% higher than the existing algorithm.
Frontal Balloon Sinuplasty in Complicated Acute Pediatric Rhinosinusitis (ARS)
Authors: Chidambaram Smrithi , Wahle Benjamin M. , Leonard David S.
Published: May 2022

Utilization of frontal balloon sinuplasty in pediatric complicated acute rhinosinusitis (ARS) is demonstrated to be a safe and expedient alternative to other procedures such as trephination or functional endoscopic sinus surgery (FESS) in this case series. We performed a retrospective review of six pediatric cases of frontal balloon sinuplasty for ARS with intracranial complications at a tertiary academic center. Patients underwent unilateral (n = 5) or bilateral dilation (n = 1) in addition to functional endoscopic sinus surgery (FESS) including anterior ethmoidectomy (n = 5) and maxillary antrostomy (n = 6). This technique effectively addressed frontal sinus obstruction and served as an alternative to procedures such as trephination or functional endoscopic sinus surgery. No immediate or short-term complications of balloon dilation were observed in these cases. A larger cohort and extended follow-up are necessary to determine the use and long-term impact of this technique.
The 5-HT and PLC Signaling Pathways Regulate the Secretion of IL-1β, TNF-α and BDNF from NG2 Cells
Authors: Yang Tingting , Li Yue , Wang Hui , Shi Peng , Teng Liu , Guo Haibo , Tu Xiaohua , Yao Xinyu
Published: May 2022

The present study was clarified the relationship between NG2 glial cells and 5-hydroxytryptamine (5-HT) to further revealed a role in the regulation of cortical excitability. The co-localization of NG2 cells and 5-HT in rat prefrontal cortex was determined using immunofluorescence. Different concentrations of 5-HT were applied to cultured NG2 cells. Real-time PCR measured the expression of interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α) and brain-derived neurotrophic factor (BDNF). Changes in the expression of IL-1β, TNF-α, and BDNF in NG2 cells were detected after the addition of 5-HT receptor specific blockers and phospholipase C (PLC) specific activators and inhibitors. The results confirmed that the NG2 protein and 5-HT co-localized in the prefrontal cortex. 5-HT treatment of NG2 cells significantly reduced the expression of IL-1β and BDNF mRNA and increased the expression of TNF-α. The 5-HT receptor specific inhibitors alverine citrate, ketanserin, ondansetron and SB-399885 blocked the regulatory effects of 5-HT on NG2 cells. The PLC signal was linked to the secretion of IL-1β, TNF-α and BDNF in NG2 cells. These results indicated that 5-HT affected IL-1β, TNF-α, and BDNF secretion from NG2 cells via the 5-HT1A, 5-HT2A, 5-HT3, 5-HT6 receptors and the PLC signaling pathway.
The Expression and Survival Significance of FOXD1 in Lung Squamous Cell Carcinoma: A Meta‐Analysis, Immunohistochemistry Validation, and Bioinformatics Analysis
Authors: Xie Fang , Li Yunhui , Liang Bin
Published: May 2022

Accumulating evidence demonstrated that FOXD1 dysregulation was correlated with a broad spectrum of malignancies. However, litter is known about the role of FOXD1 in the progression of lung squamous cell carcinoma (LUSC). We conducted the comprehensive bioinformatics analysis to investigate FOXD1 expression in LUSC from TCGA and GEO datasets, and validated the FOXD1 expression pattern in clinical samples using immunohistochemistry method. ESTIMATE and CIBERSORT algorithms were performed to assess the relationship of FOXD1 and tumor microenvironment and immune cell infiltration. Our study showed that FOXD1 expression was significantly upregulated in LUSC tissues in TCGA dataset, validated by GEO datasets and clinical samples. In TCGA dataset, Kaplan‐Meier curves showed that high FOXD1 expression was significantly correlated with favorable prognosis in LUSC patients. Moreover, FOXD1 expression has an impact on immune score and the proportions of immune cell infiltration subgroups. Finally, we predicted FOXD1 may be involved in many immune‐related biological functions and cancer‐related signaling pathways. Taken together, FOXD1 was upregulated in LUSC tissues, and FOXD1 expression could be a potential prognostic marker. FOXD1 might be associated with tumor microenvironment and perhaps a potential target in the tumor immunotherapy.
Catastrophic Antiphospholipid Syndrome Presenting as a Stroke in an 11-Year-Old with Lupus
Authors: Senken Brooke , Whitehead Anne
Published: May 2022

Catastrophic antiphospholipid syndrome (CAPS) is an infrequent but feared life-threatening complication of antiphospholipid syndrome (APS). CAPS is characterized by the rapid development of numerous thromboses across multiple organs resulting in multiorgan failure. It is rare but well-documented in the adult population. In contrast, it is exceedingly uncommon in pediatric patients and therefore not yet well described in the pediatric literature. Early recognition of APS is of the utmost importance to provide timely and effective management for a positive outcome. We present the case of an 11-year-old girl with history of systemic lupus erythematosus (SLE) and hypertension (HTN) who presented with acute onset altered mental status, found to have a large ischemic middle cerebral artery (MCA) and anterior cerebral artery (ACA) stroke as well as multiple, diffuse, and smaller ischemic lesions in the frontal lobe and cerebellum. Her presentation was further complicated by thrombocytopenia and renal and splenic infarction, as well as thrombosis of the right brachial vein consistent with a diagnosis of CAPS.
Characteristics Analysis of Applied Mathematics in Colleges and Universities Based on Big Data Mining Algorithm Model
Authors: Wang Yuqin , Tian Feng , Bai Yong
Published: May 2022

To analyze the mathematical nature of applied mathematics in colleges and universities, a method based on a model of big data mining algorithms is proposed. Firstly, the modeling is carried out through the deployment of nodes, which can accurately collect the characteristics of data information in the case of massive big data; secondly, the acquisition algorithm of multi-feature fusion is systematically optimized, which can avoid data interference and collect features quickly and accurately; thirdly, by transforming the multidimensional application-oriented university applied mathematics discipline model into an unlimited experience loss minimization problem with penalty factors, the improved support vector machine algorithm is used to construct and solve the objective kernel function. It is proved that the intelligent collection method based on big data mining algorithm model for the characteristics of applied mathematics in colleges and universities is effective. The sympathetic set corresponding to the flowing data is [115∼135]; the data similarity in big data environment is 1; in order to ensure that the intelligent collection method of applied mathematics discipline characteristics in colleges and universities based on big data analysis can collect data characteristics more accurately, which are 110/76.65/78/110, respectively.
Testosterone Deficiency Promotes Hypercholesteremia and Attenuates Cholesterol Liver Uptake via AR/PCSK9/LDLR Pathways
Authors: Yuefeng Yu , Zhiqi Lin , Yi Chen , Keyu Zhu , Heng Wan , Yuying Wang , Ningjian Wang , Yuetian Yu , Xinjie Gu , Yihao Zhang , Yingli Lu , Fangzhen Xia
Published: May 2022

Background. Testosterone deficiency is reportedly correlated with an elevation of cholesterol in plasma, but the mechanism remains unclear. Our objective was to investigate the effects of testosterone deficiency on cholesterol metabolism and the corresponding molecular changes in vivo and in vitro. Methods. SD rats were randomized into three groups: sham-operated (SHAM), subtotal orchiectomized (SO), and orchiectomized (ORX) and fed for 8 weeks. HepG2 cells were cultured with medium containing testosterone with the final concentrations of 0, 10, 30, and 300 nM. Method of isotope tracing and fluorescence labelling was adopted to investigate cholesterol metabolism. Several key molecules of cholesterol metabolism were also analyzed. Results. SO and ORX rats displayed dysfunctional liver uptake of cholesterol. HepG2 cells incubated with testosterone of lower and excessive level exhibited reduced capacity of cholesterol uptake. Further investigation revealed that lack of testosterone induced increased proprotein convertase subtilisin/kexin type 9 (PCSK9) and decreased low-density lipoprotein receptor (LDLR) both in vivo and in vitro. Moreover, the androgen receptor (AR) antagonist flutamide mimicked the effects of testosterone deficiency on PCSK9 and LDLR indicating the role of AR as a mediator in triggering attenuating liver cholesterol uptake in which testosterone instead of dihydrotestosterone (DHT) is the major functional form of androgen. Conclusion. Testosterone deficiency attenuated cholesterol liver uptake mediated by the PCSK9-LDLR pathway, in which AR and testosterone without transforming to DHT play important roles.
Influential Incremental Learning-Based Privacy Preservation for Social Network Information
Authors: Alshudukhi Jalawi Sulaiman
Published: May 2022

Social network influence dissemination focuses on employing a small number of seed sets to generate the most significant possible influence in social networks and considers forwarding to be the only technique of information transmission, ignoring all other ways. Users, for example, can post a message via this mode of distribution (called para), which is difficult to trace, posing a danger of privacy leakage. This research tries to address the aforementioned issues by developing a social network information transmission model that supports the paranormal relationship. It suggests a way of disseminating information called Local Greedy, which aids in the protection of user privacy. Its effect helps to reconcile the conflict between privacy protection and information distribution. Aiming at the enumeration problem of seed set selection, an incremental strategy that supports privacy protection is proposed to construct seed sets to reduce time overhead; a local influence subgraph method of computing nodes is given to estimate the influence of seed set propagation quickly; the group satisfies the constraints of privacy protection, and a plan is proposed to deduce the upper limit of the probability of node leakage state, avoiding the time cost of using the Monte Carlo method using the crawled Sina Weibo dataset. Experimental verification and example analysis are carried out, and the results show the effectiveness of the proposed method.
Preparation of Porous Ceramic Building Decoration Materials by Foaming Method and Research on Nanomechanical Properties
Authors: Zhang Hongyao
Published: May 2022

Because of its excellent properties, mullite porous ceramics are widely used in thermal insulation materials, catalyst carriers, gas-liquid filtration, separation materials, etc. At the same time, zirconia not only has the advantages of high melting point, good chemical stability, and high strength but also can significantly improve the strength of ceramics through phase transformation and particle dispersion in the matrix and is widely used in the reinforcement of ceramics. In this paper, using mullite powder as the raw material, Al2O3 and SiO2/ZrSiO4 as the starting material for the mullite self-bonding phase, and AlF3·3H2O, ZrO2, and Y2O3 as additives, the zirconia-reinforced mullite was prepared by the foaming-injection method. The volume density, linear shrinkage rate, microstructure, room temperature, etc. of nanozirconia-reinforced mullite porous ceramics were studied by the amount of the foaming agent, the amount of mullite self-bonding phase powder, the type and amount of additives, etc. Effects of mechanical properties and thermal conductivity were also analyzed. The research results show that zirconia-reinforced mullite porous ceramics were prepared with mullite powder and 6 wt% AlF3·3H2O as raw materials, and ZrO2 and Y2O3 as additives. Adding an appropriate amount of ZrO2 and Y2O3 can significantly improve the mechanical properties of porous ceramics. When ZrO2 is 6 wt% and Y2O3 is 8 wt%, the porosity is 66.4% and the flexural strength and compressive strength of porous ceramics with a large pore size of 168 μm can reach 14.3 MPa and 36.3 MPa, respectively, which are obviously better than the strength of mullite porous ceramics without adding Y2O3 (flexural strength 11.3 MPa, nanocompressive strength 29.4 MPa).