bluuebunny/crossref_metadata_2025 huggingface dataset:
[Retracted] Biogenic Analysis of the Effect of TERC on Cell Proliferation and Migration of Oral Squamous Cell Carcinoma under Digital Minimally Invasive Treatment
Authors: Chen Wenao , Zhang Zilong , Jin Yiyao , Zeng Ruijie , Sun Xi , Zhou Zihan , Kasim Kabna , Grant Joshua , Kuraki Vumika , Schmid Felix , Lucas Gabin
Published: August 2022

Objective. To investigate the correlation between TERC gene and cell proliferation and migration of oral squamous cell carcinoma. Methods. By comparing the traditional surgical treatment with the minimally invasive treatment of digital technology, the influence of Shengxin analysis method on the proliferation and migration of oral squamous cell carcinoma cells was analyzed. Results. Digital technology minimally invasive treatment has a great impact on the operation and survival rate of patients. TERC has a significant impact on the proliferation and migration of oral squamous cell carcinoma cells. Digital technology minimally invasive treatment can prevent TERC from great changes. Conclusion. TERC under the minimally invasive treatment of digital technology has little effect on the proliferation and migration of oral squamous cell carcinoma cells. It can promote the proliferation of oral squamous cell carcinoma cells. The inhibitors of migration and invasion can play an effective role in antiproliferation.
Profile of Bioactive Compounds, Aromas, and Cup Quality of Excelsa Coffee (Coffea liberica var. dewevrei) Prepared from Diverse Postharvest Processes
Authors: Herawati Dian , Loisanjaya Michael Oscarius , Kamal Radwa Husni , Adawiyah Dede Robiatul , Andarwulan Nuri
Published: August 2022

The study is aimed at evaluating bioactive compounds, volatile compounds, and cup quality of Excelsa coffee (Coffea liberica var. dewevrei) from different postharvest processing procedures, i.e., natural, honey, semiwashed, and wine. The green beans from each procedure were roasted at light to medium levels. Sample analysis was performed using HPLC and GC-MS instruments for bioactive compounds and volatile compounds, respectively, followed by a cupping test. As the results, postharvest processing significantly altered content of bioactive compounds (caffeoylquinic acids (CQAs) and alkaloids) in Excelsa green beans; the lowest quantity of CQAs and alkaloids was found in wine and semiwashed green beans, respectively. Significant degradation of 5-CQA and its transformation to 3-CQA and 4-CQA occurred in all light-medium roasting levels. In general, alkaloids were stable during roasting, and only trigonelline was slightly declined. Roasting process also generated 17 potent volatile compounds in Excelsa beans including 2-ethylpyrazine, 2,3-dimethylpyrazine, 2,5-dimethylpyrazine, 2,5-dimethyl-3-ethylpyrazine, guaiacol, 4-vinyl-guaiacol, and isovaleric acid and its esters. Furthermore, cupping test revealed that Excelsa coffee samples obtained from different postharvest processing were categorized as very good coffee (

cupping
 
score
>
80

). This finding may encourage the commercialization of all observed Excelsa coffee beans.
Observation on the Effect of High-Quality Nursing Intervention plus Health Education in Chemotherapy for Non-Small Cell Lung Cancer and Its Influence on the Physical and Mental Health of Patients
Authors: Feng Liyun , Yang Dongmei
Published: August 2022

Objective. The objective is to analyze the effect of high-quality nursing intervention combined with health education in the chemotherapy for non-small cell lung cancer and its impact on the physical and mental health of patients. Methods. The study included 136 patients with non-small cell lung cancer treated at our hospital from March 2020 to December 2021, who were divided into the observation group and the routine/control group by randomization, with 68 patients in each. All patients received the GP (gemcitabine + cisplatin) chemotherapy. The control group received routine nursing care, whereas the observation group received high-quality nursing care mixed with health education. The effect of nursing intervention, patient self-management, and the influence on the physical and mental health of the patients was compared between the two groups. Results. The total efficacy rate (89.71%) of the observation group was significantly higher than that of the routine group (57.35%) (

P
<
0.05

). The self-management level of the patients in the observation group, indicated by the Exercise of Self-Care Agency (ESCA) score, was considerably higher than that of the regular group after nursing intervention. Similarly, the observation group’s quality of life, which was evaluated in terms of physical function, role function, emotional function, cognitive function, social function, and overall health status, was much better than the routine group’s. Furthermore, the SAS, SDS, and overall incidence of adverse events were lower in the observation group than in the regular group. (

P
<
0.05

). Conclusion. The application of high-quality nursing intervention combined with health education in chemotherapy for non-small cell lung cancer has favorable clinical benefits, enhances patient compliance and self-management capacity, and exerts a positive influence on the patient’s physical and mental health. Adverse reactions can provide a more trustworthy scientific basis for therapeutic therapy. The method should be widely used.
Data Transmission and Processing Analysis of Power Economic Management Terminal Based on the Internet of Things
Authors: Tang Hao
Published: August 2022

In order to explore how the power economy can realize the data transmission and processing of the management terminal, this paper presents a data transmission and processing analysis of the power economy management terminal based on the Internet of Things. This method explores the research on how to realize the data transmission and processing of management terminal in power economy through the key technical problems and solutions of information recommendation based on the Internet of Things. The research shows that the efficiency of data transmission and processing analysis of power economic management terminal based on the Internet of Things is about 65% higher than that of traditional data analysis. Improve the overall quality of employees in power enterprises and inject new vitality into the development of power economy.
Influence Factors and Predictive Models for the Outcome of Patients with Ischemic Stroke after Intravenous Thrombolysis: A Multicenter Retrospective Cohort Study
Authors: Hu Jin , Fang Zhixian , Lu Xia , Wang Fei , Zhang Ningyuan , Pan Wenliang , Fu Xinzheng , Huang Gongchun , Tan Xiaoli , Chen Wenyu
Published: August 2022

Objective. Intravenous thrombolysis (IVT) is currently the main effective treatment for patients with ischemic stroke. This study aimed to analyze the factors affecting the early neurological recovery and prognosis of thrombolytic therapy after surgery and to construct predictive models. Materials and Methods. A total of 849 patients with ischemic stroke who received IVT treatment at six centers from June 2017 to March 2021 were included. Patients were divided into the training cohort and the validation cohort. Based on the independent factors that influence the early recovery of neurological function and the prognosis, the respective predictive nomograms were established. The predictive accuracy and discrimination ability of the nomograms were evaluated by ROC and calibration curve, while the decision curve and clinical impact curve were adopted to evaluate the clinical applicability of the nomograms. Results. The nomogram constructed based on the factors affecting the prognosis in 3 months had ideal accuracy as the AUC (95% CI) was 0.901 (0.874~0.927) in the training cohort and 0.877 (0.826~0.929) in the validation cohort. The accuracy of the nomogram is required to be improved, since the AUC (95% CI) of the training cohort and the validation cohort was 0.641 (0.597~0.685) and 0.627 (0.559~0.696), respectively. Conclusions. Based on this ideal and practical prediction model, we can early identify and actively intervene in patients with ischemic stroke after IVT to improve their prognosis. Nevertheless, the accuracy of predicting nomograms for the recovery of early neurological function after IVT still needs improvement.
Prognostic Value of MUC16 Mutation and Its Correlation with Immunity in Hepatocellular Carcinoma Patients
Authors: Liu Bing , Dong Zhicheng , Lu Yingzhi , Ma Jianhua , Ma Zhaoming , Wang Hongwei
Published: August 2022

Objective. Identifying gene mutation signatures will enable a better understanding for the occurrence, development, and prognosis of hepatocellular carcinoma (HCC) and provide some potential biomarkers for clinical practice. This study investigated the mutated genes in HCC patients and assessed their relationship with tumor mutation burden (TMB) and prognosis. Methods. The somatic mutation annotation format (MAF) document, mRNA expression matrix, and clinical information of HCC patients were obtained from the International Cancer Genome Consortium (ICGC) and the Cancer Genome Atlas (TCGA) database. The differences of TMB between the mutant type and the wild-type genes were detected using the Mann–Whitney U test. The link of gene mutations with prognosis was explored by the Kaplan–Meier analysis. The proportion of 22 immune cells’ composition was measured using CIBERSORT algorithm. Results. The two databases screened 16 common mutated genes, which included TP53, TTN, LRP1B, ZFHX4, MUC16, OBSCN, CSMD3, FLG, CSMD1, SYNE1, SPTA1, USH2A, KMT2C, PCLO, HMCN1, and FAT3. After a series of analysis, MUC16 mutation was found to be highly correlated with TMB and was regarded as an independent factor predicting HCC. Furthermore, gene set enrichment analysis (GSEA) indicated that the MUC16 mutation was significantly involved in HCC cell metabolism. Conclusions. MUC16 mutation seems to be a valuable potential biomarker for HCC development and its overall survival.
Identification of Contact Relationship of Electrical Engineering Distribution Network with Two-Dimensional Wavelet Threshold Deep Neural Network
Authors: Hong Tianxing
Published: August 2022

With the improvement of electrification in power systems, accurate and rapid fault location helps to repair faults, which is of great significance to the stability of distribution network operation. As an important part of power distribution in the power system, the electrical engineering distribution network is directly connected to the power transmission system and power end users. Its safety and reliability are related not only to the power sales interests of power companies, but also to the power users’ rights and interests in power consumption. In this paper, an improved threshold based on the peak-sum ratio (PSR) is proposed, the time-frequency features in the disturbance signal are extracted through the continuous transformation of the two-dimensional wavelet threshold deep neural network to generate the disturbance time-frequency map of the electrical engineering distribution network, and then the deep learning model is used to analyze the model. After the classification performance is continuously optimized, the signal disturbance identification of electrical engineering distribution network is realized. By calculating the PSR of the distribution network, the correction factor can adaptively adjust the general threshold according to the noise distribution characteristics of different disturbance signals. By analyzing the data one by one, it can be seen that the improved threshold function has obvious advantages in the input signal-to-noise ratio of 10–12 dB, 16–18 dB, and 21–26 dB. At 13 dB, 14 dB, 20 dB, 27 dB, and 28 dB, the SNR difference of the distribution network is very small, and at 15 dB, 19 dB, 29 dB, and 30 dB, it is slightly inferior, but its denoising effect is generally better. The example results have shown that the recognition accuracy of the two-dimensional wavelet threshold denoising method in a noise-free environment has been effectively improved, and it has a certain anti-noise performance. The method proposed in this study has few feature extraction steps, is easy to implement, and is suitable for more types of disturbances.
An Epidemic Patch-Enabled Delayed Model for Virus Propagation: Towards Evaluating Bifurcation and White Noise
Authors: Liu Zhigang , Madhusudanan V. , Srinivas M. N. , Nwokoye ChukwuNonso H. , Geleto Tadele Degefa
Published: August 2022

The massive disruptions caused by malware, such as a virus in computer networks and other aspects of information and communication technology, have generated attention, making it a hot research topic. While antivirus and firewalls can be effective, there is also a need to understand the spread patterns of viral infection using epidemic models to curb its incidences. Many previous research attempts have produced analytical models for computer viruses under various infectiousness situations. As a result, we suggested the SLBS model, which considers infection latency and transient immunity in patched nodes. Under certain conditions, the local stability of all equilibrium points is investigated. By setting the delay parameter, we established the occurrence of a Hopf bifurcation (HB) as it crossed a crucial point by several analyses. We also used the centre manifold theorem and normal form theory to examine the attributes of the HB. While the former was used to study the time delay and direction of Hopf bifurcation, the latter was used to investigate external noise and its intensities. Finally, numerical simulations two dimensional and three-dimensional graphs were used to depict the perturbations of the model, thus bolstering the essentiality of the study.
Lp-Curvature Measures andLp,q-Mixed Volumes
Authors: Ma Tongyi
Published: August 2022

Motivated by Lutwak et al.’sLp-dual curvature measures, we introduce the concept ofLp-curvature measures. This newLp-curvature measure is an extension of the classical surface area measure,Lp-surface area measure, and curvature measure. In this paper, we first prove some properties of theLp-curvature measure. Next, using theLp-curvature measure, we define theLp,q-mixed volume which includesLp-mixed volume as the special cases. Further, the Minkowski-type inequality relatedLp,q-mixed volume and the uniqueness of the solution for theLp,q- Minkowski problem are obtained. Finally, we propose several problems that need to be studied further.
Analysis of Enterprise Marketing Data Management Integration and Innovation Path Based on BD
Authors: Wang Lei , Hoang Anh Tuan
Published: August 2022

In recent years, the marketing data sources of enterprises are not sufficient, and the quality of data cannot be guaranteed. In addition, although the data has the characteristics of “large amount,” there is a lot of data garbage in it, and the amount of valuable data is not large. Taking electric power enterprises as an example, electric power marketing is the key of power supply enterprises, and its development determines the survival and development of enterprises to some extent, which is of great significance to power supply enterprises. Big data (BD) not only brings many positive effects to the marketing of electric power enterprises but also brings some negative effects to electric power enterprises. Based on the background of BD, this paper studies the integration and innovation path of marketing data management in electric power enterprises. The research shows that the accuracy rate of this method is the highest, followed by machine learning, and finally AI. With the increase of the number of samples, the accuracy of this method becomes higher and higher. When the number of samples reaches 13, the accuracy of this method can reach 85%, that of machine learning is 56%, and that of AI is 43%. It can be seen that this method is more suitable for data management integration of electric power marketing. According to the characteristics of the era of BD, electric power enterprises should innovate marketing data management system, construct efficient and perfect data processing flow, fully tap the potential value of data, and make contributions to the development of electric power enterprises.
The Implementation of Unified Application Data Collection and Analysis in Tobacco Enterprise Platform Design
Authors: Jin Yong , Lou Weidong
Published: August 2022

With the continuous deepening and development of tobacco manufacturing informatization construction, tobacco manufacturing enterprises have the characteristics of strong production capacity, high degree of production automation, and advanced enterprise-level management information system. In order to cooperate with the market and brand strategy of the tobacco industry, the State Tobacco Monopoly Administration has carried out serious strategic thinking on informatization and customized the overall plan and strategic goals. In recent years, China’s informatization construction has made great progress, and both industries and enterprises have felt various benefits from the application of information technology. In the deployment and development of mobile services, it is often local and municipal mobile companies that, in order to meet the different needs of the market, immediately carry out corresponding services, resulting in one service for each municipal subsidiary in the same province or one platform for a class of services. Situation is good for quickly meeting user needs at that time. The exchange and communication of enterprise personnel information are becoming more and more frequent, and the collection of enterprise information through mobile has become a new way of enterprise information collection. The work orders, process parameters, documents, notifications, and instructions generated by the planning layer are sent to the production control layer to respond, guide, and trigger the production site events. The ultimate goal of mobile data collection is to gather the collected data into the enterprise production data center, which plays an important role in mobile devices, mobile performance, mobile planning, mobile balancing, mobile prediction, and so on. Based on the unified mobile application data collection method, this paper analyzed and analyzed the design of application architecture in the tobacco enterprise platform and further described the business functions, security performance, and system characteristics of the platform.
Effects of Collagen Antibacterial Functional Dressing plus Continuous Nursing on Lower Extremity Skin Injury Caused by Norepinephrine in Patients with Septic Shock
Authors: Hu Xiaoxia , Wang Hongxia , Lin Yun
Published: August 2022

Background. This study was designed to explore the effects of collagen antibacterial functional dressing plus continuous care on norepinephrine-induced lower extremity skin injury in patients with septic shock. Methods. In this prospective, randomized, controlled study, 120 patients with septic shock receiving norepinephrine in our hospital from February 2020 to February 2021 were recruited. All the enrollments were randomized into the experimental group (n = 60) and the control group (n = 60). The control group received continuous care, while the experimental group additionally received collagen antibacterial functional dressing. Outcome measures included skin sensation scores, incidence of lower extremity skin injuries, recovery time, inflammatory factor levels, and care satisfaction. Results. Collagen antibacterial functional dressing plus continuous care resulted in significantly lower skin sensation scores and a lower incidence of skin injuries versus continuous care alone. Patients in the experimental group had faster recovery of lower extremity skin injury than those in the control group. Collagen antibacterial functional dressing plus continuous care was associated with significantly lower levels of inflammatory factors and a higher satisfaction rate than continuous care alone. Conclusion. Collagen antibacterial functional dressing plus continuous care improves the local skin condition of patients with septic shock receiving norepinephrine, regulates the levels of inflammatory factors, reduces the risk of skin injuries, and enhances care satisfaction.
The Moderating Effect and Threshold Effect of Green Finance on Carbon Intensity: From the Perspective of Capital Accumulation
Authors: Zhang Jun , Ke Haiqian
Published: August 2022

Climate change has caused serious threats to global economic development and human well‐being, and green finance is a new way to achieve ecological, economic, and social sustainable development, and it also has important theoretical significance and policy value. This study firstly aims to study the impact of green finance on regional carbon intensity. Then, it aims to determine the moderating effect of capital stock per capita on the relationship between green finance and carbon intensity based on moderating effect model as well as to investigate the threshold effect of capital stock per capita on the relationship between green finance and carbon intensity based on threshold effect model. The main conclusions are as follows: (1) Every 1% increase in green finance will lead to a 2% decrease in carbon intensity, and the inhibition of green finance on carbon intensity is most obvious in northeast and east China. (2) The capital stock per capita has a significant moderating effect, which could enhance the restraining effect of green financial development on carbon intensity, and this moderating effect is most obvious in northeast China. (3) The capital stock per capita has a threshold effect in the process of green finance development to suppress carbon intensity. The higher the capital stock per capita, the stronger the inhibition effect of green finance development on carbon intensity. Therefore, in the process of capital accumulation, attention should be paid to improve the relevant legal system and policy guarantee, optimization of financial structure, and stimulation of the capital allocation effect of green finance. Simultaneously, in order to strengthen the inhibitory effect of green finance on carbon intensity, differentiated green finance development policies should be formulated based on factor endowment structure and comparative advantages of different regions.
Characterization of Hypervirulent Klebsiella pneumoniae (Hv-Kp): Correlation of Virulence with Antimicrobial Susceptibility
Authors: Vandhana V. , Saralaya K. Vishwas , Bhat Sevitha , Shenoy Mulki Shalini , Bhat Archana. K.
Published: August 2022

Introduction. Hypervirulent K. pneumoniae (Hv-Kp) is an emerging variant of classical K. pneumoniae (C-Kp) that exhibits hypermucoviscocity and possesses multiple siderophores as virulence factors and is known to cause serious debilitating infections in immunocompetent individuals. Aim and objective. The aim of this study is to identify C-Kp and Hv-Kp strains and detect their virulence factors and antimicrobial susceptibility patterns. Materials and Methods. A total of 129 K. pneumoniae isolates from different clinical samples were used for the identification and differentiation of classical K. pneumoniae (C-Kp) and hypervirulent K. pneumoniae (Hv-Kp) to correlate their virulence with antimicrobial susceptibility patterns and identify their risk factors. Hypermucoviscosity was determined by a string test (>5 mm of string length). The aerobactin gene was detected by PCR. Results and Conclusion. In total, 13.9% (18/129) were Hv-Kp and 86.1% (111/129) were C-Kp. Only 50% (9/18) of the Hv-Kp isolates were hypermucoviscous. C-Kp was significantly more resistant to antimicrobials than Hv-Kp. Among C-Kp, 75.7% were ESBL producers and 76.6% were multidrug resistant while in Hv-Kp, 44.44% were both ESBL producers and multidrug-resistant which is statistically significant (

P
<
0.01

). Diabetes was a common risk factor for C-Kp infections whereas, respiratory disorders like COPD and prolonged ICU stay were the risk factors for Hv-Kp infections. The mortality rate among patients with Hv-Kp infections (87.5%) was significantly high when compared to that of C-Kp infections (35.7%) (

P
<
0.001

). A majority of hypermucoviscous K. pneumoniae isolates were multidrug resistant (65.2%). Although the prevalence of Hv-Kp infections was low, a high percentage of them were multidrug resistant with a significantly high mortality rate. Hence, it is important to efficiently identify Hv-Kp strains from clinical samples and determine their antimicrobial susceptibility patterns, so as to provide immediate and effective treatment and to prevent possible outbreaks.
Applied Logic in the Age of Big Data: The Evolution of Linguistic Programming and Decoding in Psychological Trend Analysis
Authors: Liang Lang
Published: August 2022

Mental health quality is closely related to individual mental health level. High mental health quality can help high school students deal with mental illness in time, actively seek help from others, and improve their stigmatized abnormal beliefs, so as to improve their overall mental health level. The party and the government pay more and more attention to the shaping of everyone’s proactive social psychology, which has been widely concerned in modern society. Therefore, this article scientifically studies the applied logic of the information age: the evolution of language programming and decryption in the trend of psychological change. SQL Server data management system, Oracle big data statistical analysis and research ideas, ACSI mental health evaluation index system, and language expression encoding and decoding method were used to measure the mental health of Chinese teenagers and children, and the relevant measurement conclusions were compared. The results show that the accuracy of language programming is higher than that of traditional mental health measurement. Finally, the paper discusses the scientific research of mental health, puts forward corresponding proposals, and finally prospects the future of the exploration of the ways of mental health cultural education.
A Mathematical Model for a Transmissible Disease with a Variant
Authors: Otto A. , Amidou M.
Published: August 2022

The outbreak of the Coronavirus (COVID-19) pandemic around the world has caused many health and socioeconomic problems, and the identification of variants like Delta and Omicron with similar and often even more transmissible modes of transmission has motivated us to do this study. In this article, we have proposed and analyzed a mathematical model in order to study the effect of health precautions and treatment for a disease transmitted by contact in a constant population. We determined the four equilibria of the system of ordinary differential equations representing the model and characterized their existence using exact methods of algebraic geometry and computer algebra. The model is studied using the stability theory for systems of differential equations and the basic reproduction number

R

0

. The stability of the equilibria is analyzed using the Lienard-Chipart criterion and Lyapunov functions. The asymptotic or global stability of endemic equilibria is established, and the disease-free equilibrium is globally asymptotically stable if

R

0

<
1

. Model simulation is done with Python software to study the effects of health precautions and treatment, and the results are analyzed. It is observed that if the rate of treatment and compliance with health precautions are high, the number of infections decreases in the classes of infectious and is canceled out over time. It is concluded that the high treatment rate accompanied by a suitable rate of compliance with health precautions allows for the control the disease.
Chinese Commodity Price Evidence Study for COVID-19 Shock and Price Stickiness Model Design
Authors: Qin Jie , Wang Jiawei , Zheng Tiandan
Published: August 2022

Based on the high-frequency price data, this article estimates the extent of price stickiness, identifies the pricing model, and applies the micro-results to analyze the dynamic characteristics of inflation. The results show that the price moves downward steadily during the COVID-19 epidemic. Secondly, the commodity price displays low stickiness, and the pricing model shows the time-dependent pricing (TDP) model in general. Finally, the inflation inertia is negative, indicating the macro-control is effective on COVID-19 epidemic and has the feature of contradiction to the economic cycle. And inflation inertia mainly comes from food commodities, which means that the anchoring object of the policy should be food commodities during the COVID-19 pandemic.
Dynamic Investigation and Resonant Frequency Determination of Shaft Bending Fatigue Testing Machine
Authors: Zhao Jinghe , Zhang Ying , Jiang Bo
Published: August 2022

The testing machine of shaft bending fatigue is widely used to test the fatigue limit and life of various shaft-type parts in mechanical engineering. Machine dynamic characteristics and system bending resonant frequency are very important for the design, testing, and application of the testing machine, but existing complex finite element calculation and aimless large-range frequency scanning in testing are the available methods to solve these two problems helplessly and inefficiently. A novel analytical model of nonlinear coupling dynamic system is built for the fatigue testing machine in this paper. The nonlinear dynamic model is simulated and investigated numerically, then it is reasonably linearized and reduced as a linear one, and the corresponding error analysis and application range are presented. By using eigenvalue approximation, the shaft bending resonant frequency formula is obtained, then the formula is compared and verified with the results from the nonlinear system simulation and finite element software, and it can improve the machine design and testing efficiency obviously. The analytical dynamic modeling and linearizing, and the given mode resonant frequency approximating, also provide a reference for many similar vibration machines.
Study on the Changes of Intestinal Microflora Structure in Long-Term Night Shift Nurses
Authors: Liu Yuping , Zhang Bo , Li Rong , Meng Yingtao , Pang Zengfen
Published: August 2022

Objective. To investigate the influence of long-term night shift nurses on the composition. Methods. The feces of 30 night shift nurses (test group) and 30 day shift nurses (control group) over 1 year were collected, and double-end sequencing based on bacterial 16S rDNA V3 + V4 and fungal 18S rDNA V3 + V4 was used to determine the differences by OTU clustering, diversity, flora abundance, and differential analysis. The results of 60 samples were sequenced for a total of 3, 052. There were 418 high-quality sequences, each sample produced an average of 50, 874 high-quality sequences. The OTU cluster analysis revealed that the number of OTUs was 365. The number of day-shift shift OTUs was 362. There was no significant difference (

p
<
0.05

). There was no significant statistical difference in the Chao, Ace, Shan’non, and Simpson index between the 2 groups (

P
>
0.05

). Differential analysis of gut microflora between 2 groups showed that at the phylum level, the relative abundance of firmicutes in long-term night shift nurses was higher than in day shift nurses. However, the relative abundance of bacteroidetes was lower than that of white shift nurses (all

p
<
0.05

). At the genus level, long-term night shift nurses’ Bacteroides, Faecacterium, and Bifidobacterial were lower than that of white shift nurses (

p
<
0.05

). However, the relative abundance of Prevotella and Megomonas was higher than that of white shift nurses (all

p
<
0.05

). Conclusion. There are differences between night shift nurses, which lead to a decrease in intestinal probiotic flora and increased conditional pathogenic flora. Nursing managers should improve the intestinal flora change of night shift nurses through reasonable scheduling and dietary regulation.
Contribution of Adiponectin/Carnitine Palmityl Transferase 1A-Mediated Fatty Acid Metabolism during the Development of Idiopathic Pulmonary Fibrosis
Authors: Wu Wenjuan , Zhang Guojun , Qiu Lingxiao , Liu Xueya , Zhou Shuai , Wu Jizhen
Published: August 2022

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease that leads rapidly to death. The present study is aimed at discovering the in-depth pathogenesis of IPF, exploring the role of adiponectin/carnitine palmityl transferase 1A- (APN/CPT1A-) mediated fatty acid metabolism during the development of IPF, and excavating its potential mechanism. Here, THP-1 cells were differentiated into M0 macrophages, followed by polarization to M1 macrophages upon hypoxia. Subsequently, lung fibroblast HFL-1 cells were stimulated by M1 macrophages to simulate hypoxia-related IPF condition in vitro. It was discovered that the stimulation of M1 macrophages promoted fibroblast proliferation and fibrosis formation in vitro, accompanied with a disorder of the APN/CPT1A pathway, an overproduction of lipid peroxides, and a low level of autophagy in HFL-1 cells. Thereafter, APN treatment or CPT1A overexpression greatly suppressed above lipid peroxide accumulation, fibroblast proliferation, and fibrosis but activated autophagy in vitro. Furthermore, an in vivo IPF rat model was established by injection of bleomycin (BLM). Consistently, CPT1A overexpression exerted a protective role against pulmonary fibrosis in vivo; however, the antifibrosis property of CPT1A was partly abolished by 3-methyladenine (an autophagy inhibitor). In summary, APN/CPT1A-mediated fatty acid metabolism exerted its protective role in IPF partly through activating autophagy, shedding a new prospective for the treatment of IPF.
The Research of Adaptive Data Desensitization Method Based on Middle Platform
Authors: Wang Jijun , Xu Mingsheng , Lu Kang
Published: August 2022

With the popularization of Middle Platform characterized by data aggregating and governance, the security protection of data is paying more and more attention, and the data desensitization technology is widely used. In order to solve the high threshold for use, high customization, and lack of stability caused by conventional data desensitization methods, a desensitization strategy configuration system based on desensitization intensity and desensitization algorithm weight was established. The methods of reidentification risk assessment and information security attribute assessment were used to classify and quantify configuration items, and then, an adaptive desensitization strategy configuration method was proposed which not only simplifies the configuration process but also provides reliable desensitization data flexibly and stably for application requirements. It is beneficial to the development of an intelligent automatic data desensitization system.
Analysis of the Current Situation of Teaching and Learning of Ideological and Political Theory Courses by Deep Learning
Authors: Chao Jin , Zhang Yijiang
Published: August 2022

The objectives are to solve the problems existing in the current ideological and political theory courses, such as the difficulty of classroom teaching quality assessment, the confusion of teachers’ classroom process management, and the lack of objective assessment basis in teaching quality monitoring. Based on Artificial Intelligence (AI) technology, a designed evaluation method is proposed for teachers’ classroom teaching and solves some problems such as high system cost, low evaluation accuracy, and imperfect evaluation methods. Firstly, the boundary algorithm system is introduced in the research, and the Field Programmable Gate Array (FPGA) by deep learning (DL) is used to accelerate the server hardware network platform and equipped with pan tilt zoom (PTZ) and manage multiple AI + embedded visual boundary algorithm devices. Secondly, the network platform can manage the PTZ and focal length of Internet protocol (IP) cameras, measure, and capture face images, transmit data, and recognize students’ face, head, and body postures. Finally, classroom teaching is evaluated, and students’ behavioral data and functions are designed, debugged, and tested. The research results demonstrate that the method overcomes the problem of high system cost through edge computing and hardware structure, and DL technology is used to overcome the problem of low accuracy of classroom teaching evaluation. Various indicators such as attendance rate, concentration, activity, and richness of teaching links in classroom teaching are obtained. The method involved can make an objective evaluation of classroom teaching and overcome the problem of incomplete classroom teaching evaluation.
Application of Nanometer Heavy-duty Coating in the Optimization of Process Parameters for Power Generation Machinery
Authors: Long Wenge
Published: August 2022

In order to solve the optimization problem of process parameters for power generation machinery, an anticorrosive method based on the nanometer heavy-duty coating is proposed. In this method, the system and preparation process of new heavy-duty coating are used. The final formula and preparation process are preliminarily determined by the orthogonal experiment with the help of the existing technical means. The composition preparation of the heavy-duty coating for the special environment requirements of offshore wind power is investigated and verified by the experiments. The experimental results show that the wear resistance of the coating can be improved obviously by the wear test of 2%-3% of nanometer silica concentrate, and the wear quantity is only 33 mg. It is concluded that nanometer heavy-duty coatings can improve the anticorrosion degree greatly and improve the internal environment air-tightness and surface anticorrosion ability of the marine wind turbine.
[Retracted] Analysis of Machine Translation and Post‐Translation Editing Ability Using Semantic Information Entropy Technology
Authors: Zou Siyu
Published: August 2022

Large‐scale corpus application has presented MT with new opportunities as well as challenges in recent years. This study investigates MT and post‐translation editing capability using AI technology. The grammar rules of the target language are first examined. Then, a significant amount of data on semantic information entropy are projected, and the semantic Gaussian marginal rectangular window function is obtained. The semantic correlation factors of words are added to the text information entropy and information gain, and the nonlinear spectral properties of adaptive matching semantics are obtained. In this way, it corrects the significant flaw in the way semantic features are extracted using conventional techniques. In order to speed up MT and enhance translation quality, this study proposes automatic post‐translation editing to filter those common MT errors that occur frequently and regularly. According to the experimental findings, word translation and segmentation accuracy can both reach 95.27 and 93.12 percent, respectively. In terms of language translation, this approach is accurate and trustworthy. I hope it will serve as a useful source for subsequent research.
Stability, Bifurcation, and Chaos Control of Two-Sided Market Competition
Authors: Xiao Jianli , Xiao Hanli , Zhang Xinchang , You Xiang
Published: August 2022

Benefitting from the popular uses of internet technologies, two-sided market has been playing an increasing prominent role in modern times. Users and developers can interact with each other through two-sided platforms. The two-sided market structure has been investigated profoundly. Through building a dynamics two-sided market model with bounded rational, stability conditions of the two-sided market competition system are presented. With the help of bifurcation diagram, Lyapunov exponent, and strange attractor, the stability of the two-sided market competition model is simulated. At last, we use the time-delayed feedback control (TDFC) method to control the chaos. Our main results are as follows: (1) when the adjustment speed of two-sided increases, the system becomes bifurcation, and chaos state happens finally. When the system is stable, the consumer fee is positive while developer fee is negative. (2) When the user externality increases, the stable area of the system increases, and the difference in user externality leads the whole system more stable. When the system is stable, the developer fee decreases. (3) The stable area becomes larger when developer externality increases; when the system is stable, the user fee becomes lower and developer fee becomes higher when developer externality increases. (4) The TDFC method is presented for controlling the chaos; we find that the system becomes more stable under the TDFC method.
Effect of Enalapril Combined with Bisoprolol on Cardiac Function and Inflammatory Indexes in Patients with Acute Myocardial Infarction
Authors: Huang Kaiyue , Zhang Yubin , Yang Fulin , Luo Xue , Long Weiying , Hou Xingzhi
Published: August 2022

Objective. The use of enalapril in combination with bisoprolol in patients with acute myocardial infarction (AMI) was studied for its effect on cardiac function and inflammatory parameters. Methods. Sixty-two cases of AMI patients admitted to our clinic from November 2019 to November 2021 were selected for the study and grouped according to the random number table method, those enrolled were given conventional treatment such as oxygenation, absolute bed rest, and sedation, and administered low molecular heparin, aspirin, atorvastatin calcium tablets, clopidogrel, and nitrates. The control group (31 cases) was treated with enalapril maleate folic acid tablets, and the treatment group (31 cases) was treated with bisoprolol fumarate tablets on top of the control group, and the efficacy, adverse effects, cardiac function, inflammatory indexes, and oxidative stress indexes of the two arms were contrasted. Results. The incidence of adverse reactions in the therapy cohort was 12.90% higher than that in the controlled arm, but the discrepancy was not medically relevant (

P
<
0.05

). The SOD level was larger than the concentration in the corresponding drug therapy group, and the MDA level was lower than the concentration in the respective test cases (

P
<
0.05

); the incidence of 12.90% adverse reactions in the treatment period was lower than that of 16.13% in the specific drug therapy group, but the variance was not scientifically evident (

P
>
0.05

). Conclusion. Enalapril application combined with bisoprolol in AMI patients is beneficial to boost the efficacy, promote the improvement of cardiac function, reduce the inflammatory response, and improve the oxidative stress with fewer adverse effects, which can ensure the therapeutic security.
[Retracted] Meta‐Analysis of Anesthetic Efficacy and Safety of Propofol in Craniotomy Patients
Authors: Zhou Qiang , Han Ya’nan , Chen Jun
Published: August 2022

The anesthetic effect and safety of propofol in craniotomy patients by meta‐analysis is investigated. Relevant studies consistent with the anesthetic effect and safety of propofol in craniotomy patients are searched and screened from domestic and foreign literature databases such as Wanfang Medical Center, CNKI, VIP, and PubMed, and meta‐analysis is performed by RevMan 5.2 software. Experimental results show that the recovery time, intracranial pressure, cerebral edema, partial cerebral oxygen pressure, glutamate, and MDA in the propofol group are better than those in the control group (P < 0.05), and the incidence of superoxide dismutase, TNF‐α, and adr in the propofol group is better than that in the control group (P > 0.05). Intravenous anesthesia with propofol in patients with craniotomy has the advantage of rapid recovery, and this program can improve intracranial pressure, brain edema, and brain oxygen partial pressure and help to improve oxidative stress and inflammatory reaction.
[Retracted] Clinical Observation of Helicobacter pylori Infection and Risk Factors and Cytotoxin‐Associated Protein A in Patients with Coronary Heart Disease
Authors: Wang Xiaoyuan , Du Meiling , Li Fangjiang
Published: August 2022

The aim was to analyze the infection, influencing factors, and clinical manifestations of Helicobacter pylori infection, coronary heart disease, and cytotoxin‐associated protein A infection, so as to provide reference for the improvement of clinical diagnosis and treatment level of in‐depth treatment. This paper presents a clinical observation method based on Helicobacter pylori infection, risk factors, and cytotoxin‐associated protein A in patients with coronary heart disease. Methods. 237 patients with CHD diagnosed and tested by 14C breath test were selected from inpatients of cardiovascular diseases in a hospital for retrospective analysis. The clinical data, serum deepening indicators, Hcy, and other factors were analyzed through general condition investigation, previous history investigation, and physical examination. The patients were observed by the SPSS22.0 statistical data processing method. The results showed that among the respondents, 175 cases were HP‐positive, the infection rate was 73.8%, 77 patients with stable angina pectoris were 64.9%, and 160 patients with acute coronary heart disease were 78.1%. The difference between the groups was statistically significant (P < 0.05). Conclusion. Helicobacter pylori cytotoxic‐associated protein A can increase the risk of gastric cancer, and Helicobacter pylori eradication treatment is more conducive to reduce the incidence of gastric cancer and ensure the safety of patients.
Analysis of Ideological and Political Classroom Based on Artificial Intelligence and Data Mining Technology
Authors: Huang Zhiqiang , Feng Chun , Feng Zhanshan
Published: August 2022

With the continuous innovation of science and technology, the teaching system at home and abroad has also been reformed and optimized in combination with artificial intelligence, big data, and other technical means. As the main part of teaching activities, students’ emotional change in classroom activities is one of the important indicators that affect their learning effect and comprehensive learning achievement. Accurate analysis and judgment of students’ emotional changes are the main basis for teachers to evaluate teaching quality and improve teaching methods. Based on the above situation, this paper uses artificial intelligence and data mining technology to explore the emotional change process and influencing factors of students in ideological and political teaching classroom. Firstly, the artificial intelligence neural network algorithm is used to construct the face recognition model to improve the problem of low accuracy in the traditional recognition process. A dynamic minimum algorithm is designed to improve the operation speed of students’ emotion analysis. Finally, data mining technology is used to obtain students’ behavior data in the big data environment to provide data support for students’ emotional analysis model in ideological and political class. The results show that the student emotion analysis model based on artificial intelligence and data mining technology can be applied and run in various teaching environments.