bluuebunny/crossref_metadata_2025 huggingface dataset:
Redistribution of Resources: Sustainable System Mechanisms for Enterprise Migration
Authors: Wang Yuan , Liang Yanxi , Wang Yu , Li Zihao , Guo Chengjin
Published: September 2022

The comprehensive reasons for the cross-regional flow of enterprises in their own economy are studied in this paper. Most traditional enterprise migration research focuses on the impact of a single factor. Even the research on the influence of multiple factors often ignores the interaction of various factors. Therefore, this paper proposes and logicalises the “push and pull” mechanism of enterprise migration to address the limitations of previous research. Through bibliometric analysis and investigation, we systematically think about the factors that affect the corporate migration mechanism and improve the Push-Pull Theory. Besides, by deploying a conceptual system dynamics model, this paper explains how various factors affect enterprise migration. In addition, we discussed how to adopt systems thinking to promote the development of emerging economies. We selected and tested 6 companies that migrated in China, and the results are in line with reality. The conclusion supports the theory that systematic thinking and decision-making influence corporate behaviour.
Design of Intelligent Parking Management System Based on ARM and Wireless Sensor Network
Authors: Xiang Zhijun , Pan Jianjun
Published: September 2022

Motor vehicles are changing the way people live, but they are also putting a huge strain on urban traffic. In the majority of major cities, parking has become the number one problem for car owners to get around. The management efficiency of car parks directly affects the traffic of the whole city. In order to improve the management efficiency of the car park, this paper designs an intelligent parking management system based on ARM and ZigBee wireless sensor network. Firstly, according to the internal environment and economic cost of the car park, ultrasonic sensors are used to monitor whether the parking space is empty or not. The information collected by the ultrasonic sensors is transmitted to the ARM host controller through the ZigBee wireless sensor network, and the ARM host controller determines whether there are free parking spaces based on the collected information. Secondly, Faster R-CNN, a deep learning algorithm, is selected as the license plate recognition model, and the Faster R-CNNN is improved by the residual module. Finally, in order to extend the lifetime of the ZigBee wireless network, the ZigBee routing algorithm is investigated, and an improved routing algorithm based on energy averaging is proposed. The effectiveness of the improved routing algorithm is demonstrated by a simulation analysis through NS2. The test results show that the designed intelligent parking management system is able to complete the functions of parking space detection and license plate recognition normally, thus effectively improving the efficiency of the car park and providing great convenience to motorists.
DBP-iDWT: Improving DNA-Binding Proteins Prediction Using Multi-Perspective Evolutionary Profile and Discrete Wavelet Transform
Authors: Ali Farman , Barukab Omar , Gadicha Ajay B , Patil Shruti , Alghushairy Omar , Sarhan Akram Y.
Published: September 2022

DNA-binding proteins (DBPs) have crucial biotic activities including DNA replication, recombination, and transcription. DBPs are highly concerned with chronic diseases and are used in the manufacturing of antibiotics and steroids. A series of predictors were established to identify DBPs. However, researchers are still working to further enhance the identification of DBPs. This research designed a novel predictor to identify DBPs more accurately. The features from the sequences are transformed by F-PSSM (Filtered position-specific scoring matrix), PSSM-DPC (Position specific scoring matrix-dipeptide composition), and R-PSSM (Reduced position-specific scoring matrix). To eliminate the noisy attributes, we extended DWT (discrete wavelet transform) to F-PSSM, PSSM-DPC, and R-PSSM and introduced three novel descriptors, namely, F-PSSM-DWT, PSSM-DPC-DWT, and R-PSSM-DWT. Onward, the training of the four models were performed using LiXGB (Light eXtreme gradient boosting), XGB (eXtreme gradient boosting, ERT (extremely randomized trees), and Adaboost. LiXGB with R-PSSM-DWT has attained 6.55% higher accuracy on training and 5.93% on testing dataset than the best existing predictors. The results reveal the excellent performance of our novel predictor over the past studies. DBP-iDWT would be fruitful for establishing more operative therapeutic strategies for fatal disease treatment.
[Retracted] Path Deconstruction of Agricultural Environmental Sustainable Development Policy in the Process of International Agricultural Trade Liberalization
Authors: Li Xiaozhong , Huang Feng
Published: September 2022

Agriculture is particularly essential in the equilibrium between man and nature because of its intimate contact with nature. So the cornerstone for the sustainable development of the human economy and society is the sustainable development of agriculture. When it comes to global trade, agricultural trade has always been in a very special position. The basic situation of agriculture involves food safety, environmental protection, Chinese politics, and many other issues. In order to overcome the problems of overlapping, repetitive, and too many indicators in the evaluation method of agricultural environmental sustainable development and unfavorable for practical operation, this paper proposes an ecological footprint model based on emergy. The model can effectively evaluate the ability of sustainable development of agricultural environment and solve the problem that traditional evaluation methods cannot comprehensively evaluate. This makes agricultural development sustainable and is conducive to the liberalization of international agricultural trade. The experimental results of this paper show that from 2014 to 2018, the degree of damage to the agricultural environment has increased from 21% to 45%, which has led to a decline in the quality of agricultural products, and the output and sales are not as good as before. It can be seen that only by ensuring the sustainable development of the agricultural environment can we ensure the smooth progress of the international agricultural trade liberalization and make China’s economy flourish.
Early Diagnosis of Tuberculosis Using Deep Learning Approach for IOT Based Healthcare Applications
Authors: Simi Margarat G. , Hemalatha G. , Mishra Annapurna , Shaheen H. , Maheswari K. , Tamijeselvan S. , Pavan Kumar U. , Banupriya V. , Ferede Alachew Wubie
Published: September 2022

In the modern world, Tuberculosis (TB) is regarded as a serious health issue with a high rate of mortality. TB can be cured completely by early diagnosis. For achieving this, one tool utilized is CXR (Chest X-rays) which is used to screen active TB. An enhanced deep learning (DL) model is implemented for automatic Tuberculosis detection. This work undergoes the phases like preprocessing, segmentation, feature extraction, and optimized classification. Initially, the CXR image is preprocessed and segmented using AFCM (Adaptive Fuzzy C means) clustering. Then, feature extraction and several features are extracted. Finally, these features are given to the DL classifier Deep Belief Network (DBN). To improve the classification accuracy and to optimize the DBN, a metaheuristic optimization Adaptive Monarch butterfly optimization (AMBO) algorithm is used. Here, the Deep Belief Network with Adaptive Monarch butterfly optimization (DBN-AMBO) is used for enhancing the accuracy, reducing the error function, and optimizing weighting parameters. The overall implementation is carried out on the Python platform. The overall performance evaluations of the DBN-AMBO were carried out on MC and SC datasets and compared over the other approaches on the basis of certain metrics.
Influence of the Integration of Aesthetic Education by Zhu Xi’s Neo-Confucianism on the Ideological and Political Education and Internalized Psychology of College Students
Authors: Chen Songlin
Published: September 2022

The purpose is to study the influence of Zhu Xi’s neo-Confucianism on the ideological and political education (IPE) of college students. Firstly, the aesthetic connotation of Zhu Xi’s Neo-Confucianism is studied. Secondly, an interview is performed with teachers of the IPE course in a university in Xi’an, and a questionnaire survey is conducted on some students of the IPE course in the school. It aims to investigate the current situation of college students’ IPE, and the impact of integrating aesthetic education into IPE of college students on the improvement of students’ overall quality and internalized psychology. Finally, the reasons for this situation are analyzed and solutions are given. The survey results reveal that the aesthetic education thoughts based on Zhu Xi’s neo-Confucianism are integrated into the construction of college students’ internalized psychological mechanism, and most students think that their mental health status has changed a lot. The proportion of boys who choose “improved” is 57.95%, and the proportion of girls is 53.45%. The aesthetic education is integrated into the IPE of college students, and the proportion of students who think “no effect” after integration and before integration has decreased by 2.01%. The proportion of the number of people who chose the three indicators of “increasing the innovation of teaching methods”, “advancing aesthetic ability”, and “improving the effectiveness of ideological education” increased by 5.88%, 5.5%, and 3.98%, respectively. It demonstrates that the effect of IPE on college students has been greatly improved after integration into aesthetic education.
A Multiparametric Fusion Radiomics Signature Based on Contrast-Enhanced MRI for Predicting Early Recurrence of Hepatocellular Carcinoma
Authors: Li Wencui , Shen Hongru , Han Lizhu , Liu Jiaxin , Xiao Bohan , Li Xubin , Ye Zhaoxiang
Published: September 2022

Objectives. The postoperative early recurrence (ER) rate of hepatocellular carcinoma (HCC) is 50%, and no highly reliable predictive tool has been developed yet. The aim of this study was to develop and validate a predictive model with radiomics analysis based on multiparametric magnetic resonance (MR) images to predict early recurrence of HCC. Methods. In total, 302 patients (training dataset: n = 211; validation dataset: n = 91) with pathologically confirmed HCC who underwent preoperative MR imaging were enrolled in this study. Three-dimensional regions of interest of the entire lesion were accessed by manually drawing along the tumor margins on the multiple sequences of MR images. Least absolute shrinkage and selection operator Cox regression were then applied to select ER-related radiomics features and construct radiomics signatures. Univariate analysis and multivariate Cox regression analysis were used to identify the significant clinico-radiological factors and establish a clinico-radiological model. A predictive model of ER incorporating the fusion radiomics signature and clinico-radiological risk factors was constructed. The diagnostic performance and clinical utility of this model were measured by receiver-operating characteristic (ROC), calibration curve, and decision curve analyses. Results. The fusion radiomics signature consisting of 6 radiomics features achieved good prediction performance (training dataset: AUC = 0.85, validation dataset: AUC = 0.79). The predictive model of ER integrating clinico-radiological risk factors and the fusion radiomics signature improved the prediction efficacy with AUCs of 0.91 and 0.87 in the training and validation datasets, respectively. Furthermore, the nomogram and ER risk stratification system based on the predictive model demonstrated encouraging predictions of the individualized risk of ER and gave three risk groups with low, intermediate, or high risk of ER. Conclusions. The proposed predictive model incorporating clinico-radiological factors and the fusion radiomics signature derived from multiparametric MR images may be an effective tool for the individualized prediction of postoperative ER in patients with HCC.
Local Fractional Locating Number of Convex Polytope Networks
Authors: Zafar Hassan , Javaid Muhammad , Bonyah Ebenezer
Published: September 2022

The concept of locating number for a connected network contributes an important role in computer networking, loran and sonar models, integer programming and formation of chemical structures. In particular it is used in robot navigation to control the orientation and position of robot in a network, where the places of navigating agents can be replaced with the vertices of a network. In this note, we have studied the latest invariant of locating number known as local fractional locating number of an antiprism based convex polytope networks. Furthermore, it is also proved that these convex polytope networks posses boundedness under local fractional locating number.
[Retracted] Study on Huangqi Bazhen Decoction on Relieving Chemotherapy Intestinal Mucositis in Capecitabine Gavage Mice
Authors: Shi Tieyi , Chen Baozhong , Liu Cheng , Lu Ker
Published: September 2022

In order to provide evidence for clinical application, the therapeutic effect and mechanism of Huangqi Bazhen decoction on chemotherapeutic intestinal mucositis induced by capecitabine in mice are investigated. In this paper, the mice are divided into different groups and given capecitabine intragastric administration or treatment drugs. Morphological features of intestinal injury, including villus height shortening, crypt destruction, and apoptosis, are reversed. The experimental results show that Huangqi Bazhen decoction can significantly reduce weight loss and diarrhea during capecitabine treatment. It is also found that GSH‐Px and T‐SOD can be improved while MDA, IL‐1β, and TNF‐α are reduced significantly.
[Retracted] A Decision Model for Public Economic Environment Monitoring and Management Decision Using Improved Ant Colony Algorithm
Authors: Ji Hongmei , Li Zhuang
Published: September 2022

The quality of economic development is not sufficient, despite the apparent role that public environmental monitoring and management play in the economy’s rapid expansion. Therefore, enhancing the standard of economic growth is of the utmost importance. It is vital to establish innovative management techniques to support social and governmental transformation in order to raise the standard of economic development. Economic development affects public administration’s fundamental duties and goals. The division of public administration distributes social resources and enhances the market’s function. The fundamental problem in public economic management is how to successfully actualize rational resource allocation, advance social justice, and boost social welfare on the basis of resource scarcity and the breakdown of the market mechanism. This study greatly increases the global optimization performance of the fundamental ant colony method and provides the explicit programme and simulation stages for the new algorithm. Finally, simulation tests are conducted using the basic ant colony algorithm and the upgraded ant colony algorithm in relation to the decision‐making model of public economic management. According to the simulation findings, the revised algorithm successfully addresses the traditional approach’s drawbacks, including its slow convergence speed and propensity to easily enter local minima, and its optimization performance has increased by 30.23%.
Emergency Decision‐making Method of Unconventional Emergencies in Higher Education Based on Intensive Learning
Authors: Zhou Yongjun
Published: September 2022

In order to improve the emergency decision‐making and management ability of unconventional emergencies in Colleges and universities, an emergency decision‐making method for unconventional emergencies in Colleges and Universities based on reinforcement learning is proposed. The function of the emergency decision‐making model of unconventional emergencies in Colleges and universities is constructed, and the optimal control of the emergency decision‐making process of unconventional emergencies in Colleges and universities is realized by using the queuing theory model. Based on the sub‐sequence decomposition method, the reinforcement learning function is optimized. Combined with big data scheduling and the empirical mode decomposition method, the effective probability density function of emergency decision‐making for unconventional emergencies in higher education is calculated, and the optimal solution vector analysis of emergency management and scheduling decision‐making for unconventional emergencies in Colleges and universities is realized according to parameter estimation and quantitative optimization results. The test results show that this method has a good ability to optimize and schedule the emergency decision‐making of unconventional emergencies in higher education, and has strong convergence. This method improves the emergency response‐ability, and the time cost is short.
Analysis of University Management Model of National Higher Education Institutions Based on Machine Learning Algorithm
Authors: Zhang Danning
Published: September 2022

The development of state-owned colleges and universities has a long history and profound foundation, which has more political tasks in the field of higher education in China; national development cannot be separated from the next generation of education. The purpose of this paper is to analyze the effectiveness and advantages of using machine learning algorithm in the efficient management model of national higher education institutions; by comparing the effect of university management mode and teaching facility environment under different environments; compare the teaching management quality and coupling analysis under different algorithms; the results are statistically significant; through the research, it is found that the algorithm of machine learning has a positive impact on the data processing and auxiliary management mode based on the degree of anthropomorphic simulation, it can effectively improve the level and quality of education management in Colleges and universities and enhance students’ learning motivation and ideological value; conform to the development concept of social sustainable development; it has research value and positive significance for the future management of educational colleges and universities.
LogKernel: A Threat Hunting Approach Based on Behaviour Provenance Graph and Graph Kernel Clustering
Authors: Li Jiawei , Zhang Ru , Liu Jianyi , Liu Gongshen
Published: September 2022

Cyber threat hunting is a proactive search process for hidden threats in an organization’s information system. It is a crucial component of active defense against advanced persistent threats (APTs). However, most of the current threat hunting methods rely on Cyber Threat Intelligence (CTI), which can find known attacks but cannot find unknown attacks that have not been disclosed by CTI. In this paper, we propose LogKernel, a threat hunting method based on graph kernel clustering which can effectively separate attack behaviour from benign activities. LogKernel first abstracts system audit logs into behaviour provenance graphs (BPGs) and then clusters graphs by embedding them into a continuous space using a graph kernel. In particular, we designed a new graph kernel clustering method based on the characteristics of BPGs, which can capture both structure information and rich label information of the BPGs. To reduce false positives, LogKernel further quantifies the threat of abnormal behaviour. We evaluate LogKernel on the malicious dataset, which includes seven simulated attack scenarios, and the DAPRA CADETS dataset, which includes four attack scenarios. The result shows that LogKernel can hunt all attack scenarios among them, and compared to the state-of-the-art methods, it can find unknown attacks.
A Case of Peritoneal Tuberculosis Mimicking Ovarian Cancer in a Young Female
Authors: Nissim Oriel , Ervin F. Richard , Dorman Susan E. , Jandhyala Deeksha
Published: September 2022

Background. Tuberculosis causes significant morbidity and mortality globally. Peritoneal tuberculosis can have a similar presentation to ovarian cancer. Case. We present a case of a 42-year-old female referred to gynecology oncology with imaging findings of enlarged right ovary, omental caking, and elevated CA-125 (1289 U/mL). A diagnostic laparoscopy revealed diffuse studding of intraperitoneal surfaces. Histopathological examination of omental and abdominal wall biopsies showed granulomas, but stains and cultures for mycobacteria were negative. Antimicrobial treatment for tuberculosis was initiated. Within eight weeks, there was clear clinical and radiographic improvement, consistent with a diagnosis of peritoneal tuberculosis. Conclusion. This case highlights the importance of including peritoneal tuberculosis in the differential diagnosis when evaluating for ovarian cancer in women with epidemiologic risk factors for tuberculosis.
Blue-Green Space Changes of Baiyangdian Wetland in Xiong’an New Area, China
Authors: Zhao Chunlei , Qian Shuan , Meng Chengzhen , Chang Yufei , Guo Wenzhe , Wang Sha , Sun Yinglong
Published: September 2022

As a regulator of ecological environment, Baiyangdian Wetland is in a pivotal position in constructing the blue-green space (BGS) of Xiong’an New Area in China. This study aims to reveal the spatiotemporal changes of the BGS in Baiyangdian Wetland from 2016 to 2021. It uses Google Earth Engine (GEE) to calculate NDVI and NDWI based on Sentinel-2 Satellite remote sensing data and extracts the blue-green space by a classification model driven by NDVI and NDWI. Moreover, the land-use transfer matrix and landscape pattern indices are applied for evaluating the BGS changes in the wetland. According to the results, vegetation in the wetland shows no obvious spatial transfer. From 2016 to 2020, the BGS proportion in the wetland showed a stable increase, with the blue space getting larger by 10.8%. The indicators of the Number of Patches (NP), Patch Density (PD), Largest Patch Index (LPI), Contagion, and Landscape Shape Index (LSI) of the wetland decreased, suggesting a better ecological environment since the establishment of Xiong’an New Area in 2017. Based on the results, the author makes the following conclusion: the construction of BGS in Baiyangdian Wetland results in a well-organized ecological environment. The study provides a reference for building Xiong’an New Area and monitoring BGS changes in other regions.
Acute Effects of Breakfast Fruits Meal Sequence and Postprandial Exercise on the Blood Glucose Level and DPP4 Activity among Type 2 Diabetes Mellitus Patients: A Pilot Study
Authors: Indarto Dono , Dwipajati Dwipajati , Dirgahayu Paramasari , Wibowo Yohanes Cakrapradipta , Pratama Yoga Mulia
Published: September 2022

Objectives. Type 2 diabetes mellitus (T2DM) is a major global public health issue. Diet and physical exercise are modifiable factors that influence the glycaemic status of patients with T2DM. We aimed to investigate the acute effects of breakfast fruits meal sequence and postprandial exercise on the blood glucose level and dipeptidyl peptidase 4 (DPP4) activity among type 2 diabetes mellitus patients. Methods. A randomized pilot study recruited patients with T2DM who attended two primary health care centres in Tasikmadu District, Karanganyar Regency, and Kartasura District, Sukoharjo Regency, Central Java, Indonesia, from July to October 2016. Eligible patients (4 men and 32 women) were randomly divided into four treatment groups. Venous blood samples were analyzed for fasting and one-hour postprandial blood glucose (FBG and 1 h PPG) levels and DPP4 activity. Blood glucose levels were measured using a routine hexokinase method, and serum DPP4 activity was determined spectrophotometrically after incubation with the Gly-Pro-p-nitroanilide substrate. Results. Fruits last meal decreased FBG level whilst fruits first meal did not significantly decrease 1 h PPG level. Both treatments had no acute effects on DPP4 activity but the addition of postprandial exercise helped lower DPP4 activity. Fruit last and first meals showed significant opposite effects on mean changes of FBG level (

p
<
0.05

). Conclusions. This preliminary report of fruits meal sequence is potentially involved in acute regulation of blood glucose levels and that it might be independent of DPP4 activity in Indonesian patients with T2DM. Moreover, postprandial exercise may be an important intervention for T2DM through the mediation of DPP4 but has no acute effects on the regulation of blood glucose levels. Further studies are required to investigate whether or not different types of fruits and longer treatment intervals can affect blood glucose levels and DPP4 activity differently. This study also gives an insight into the feasibility of conducting food order modification with or without the combination of postprandial exercise in a primary health setting for our next studies.
[Retracted] Regional Economic Statistics and Green Development: Ecological Thinking for Environmental Quality Development
Authors: Yu Zhuoxi , Li Siqi
Published: September 2022

Through more than 40 years of China’s reform and opening up, China’s economic development has exceeded the “surprise of China”. China’s annual average growth rate for world economic development ranks second in the world. By 2020, the article has achieved all‐round poverty eradication and overall happiness. By 2020, this article will write an epic antipandemic with great love. During the “fourteenth five‐year plan” period, China has entered a new stage of high‐quality social and economic development, but environmental pollution is still one of the primary obstacles to high‐quality social and economic development. Because of its diversity, environmental pollution cannot be reasonably handled only by the market economic system. It also needs to be based on the effectiveness of the natural environment supervision policies of government departments. At the same time, the healthy logical thinking of the development trend of high‐quality natural environment is the key to regional economic statistics and the concept of green development. In this paper, empirical research and analysis methods are used, and the description is carried out in the form of data charts.
Efficacy Evaluation of the VFQ-25 Scale in Patients with Different Degrees of Vitreous Opacity After Nd : YAG Laser Ablation
Authors: Zhang Siwei , Yang Kang , Wang Bin
Published: September 2022

Objective. To evaluate the effect of the VFQ-25 scale on the efficacy of Nd : YAG laser ablation in patients with different severity of vitreous opacities. Methods. From January 2020 to March 2021, data of patients who presented to our department and were diagnosed with vitreous opacity were collected, and the severity of vitreous opacity was divided into four grades: I, II, III, and IV. Preoperative visual acuity, intraocular pressure, dilated fundus, B ultrasound, and other examinations were performed, and the patients were scored using the VFQ-25 scale. All patients underwent Nd : YAG laser ablation and were followed for 6 months. The VFQ-25 scale was again used postoperatively to score the patient’s efficacy. The general information and clinical characteristics of the patients we collected. The Spearman’s test was used to evaluate the correlation between VFQ-25 score and Nd : YAG laser efficacy in patients. Results. A total of 80 patients (95 eyes) were included in this study. Vitreous opacities were grade I in 56 eyes (58.9%), grade II in 22 eyes (23.2%), grade III in 10 eyes (10.5%), and grade IV in 7 eyes (7.4%). Compared with preoperative scores, patients with vitreous opacity had significantly higher postoperative scores in terms of overall health (36.54 ± 17.06 vs 33.52 ± 16.74), overall visual acuity (60.39 ± 14.24 vs 57.56 ± 13.13), color vision (88.94 ± 12.56 vs 86.38 ± 12.37), and peripheral visual acuity (74.06 ± 18.38 vs 72.20 ± 18.79) items (all

P
<
0.001

). The overall response rates of vitreous opacities I, II, III, and IV were 100%, 90.9%, 80.0%, and 71.4%, respectively. There was a significant correlation between the postoperative VFQ-25 total score, and the therapeutic effect of laser ablation for grade I vitreous opacities, with a correlation coefficient r of 0.417 (

P
=
0.001

). The correlation coefficient r between the total score of postoperative VFQ-25 and the treatment effect of grade II vitreous opacity was 0.622 (

P
=
0.002

). However, the correlation between the postoperative efficacy of grade III and IV patients and the VFQ-25 score was not significant. Conclusion. In patients with different degrees of vitreous opacity undergoing Nd : YAG laser vitreous ablation, the overall health, overall visual acuity, color vision, and peripheral visual acuity were improved after surgery, and the VFQ-25 score was significantly correlated with the postoperative efficacy, which is worthy of clinical use.
Characterization of Self-Efficacy Model Using Social Cognitive Theory for Students’ Learning Abilities and Decision-Making Based on IoT
Authors: Ma Li
Published: September 2022

Aiming at the problem that the career decision-making self-efficacy model cannot accurately mine the implicit relationship between students and career decision-making, resulting in the low structural validity and reliability of the model, a career decision-making self-efficacy model of flight attendant students under social cognitive theory is proposed. This paper analyzes the characteristics of self-efficacy under the social cognitive theory, reduces the dimension of student career decision-making score matrix into two matrices: student implicit feature and implicit feature career decision-making, and excavates the implicit relationship between flight attendant students and career decision-making. Students are described as a multidimensional decision vector to determine the professional cognitive level of flight attendant students. The self-efficacy model of students’ career decision-making is established from five aspects: self-evaluation, collecting information, selecting goals, making plans, and solving problems, which is solved by the particle swarm optimization algorithm. The experimental results show that the structural validity and reliability of the model constructed in this paper are higher than those based on cluster analysis and user portrait. Therefore, it can effectively evaluate and measure the career decision-making self-efficacy of flight attendant students.
A Bioinformatic Approach Based on Systems Biology to Determine the Effects of SARS-CoV-2 Infection in Patients with Hypertrophic Cardiomyopathy
Authors: Han Xiao , Wang Fei , Yang Ping , Di Bin , Xu Xiangdong , Zhang Chunya , Yao Man , Sun Yaping , Lin Yangyi
Published: September 2022

Recently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide. While COVID-19 generally affects the lungs, it also damages other organs, including those of the cardiovascular system. Hypertrophic cardiomyopathy (HCM) is a common genetic cardiovascular disorder. Studies have shown that HCM patients with COVID-19 have a higher mortality rate; however, the reason for this phenomenon is not yet elucidated. Herein, we conducted transcriptomic analyses to identify shared biomarkers between HCM and COVID-19 to bridge this knowledge gap. Differentially expressed genes (DEGs) were obtained using the Gene Expression Omnibus ribonucleic acid (RNA) sequencing datasets, GSE147507 and GSE89714, to identify shared pathways and potential drug candidates. We discovered 30 DEGs that were common between these two datasets. Using a combination of statistical and biological tools, protein-protein interactions were constructed in response to these findings to support hub genes and modules. We discovered that HCM is linked to COVID-19 progression based on a functional analysis under ontology terms. Based on the DEGs identified from the datasets, a coregulatory network of transcription factors, genes, proteins, and microRNAs was also discovered. Lastly, our research suggests that the potential drugs we identified might be helpful for COVID-19 therapy.
Investigation and Countermeasures on Mental Health Status of Applied Fresh Graduates from the Perspective of Psychological Capital
Authors: Zeng Yuanzhen
Published: September 2022

Based on the perspective of psychological capital, the mental health status of applied college graduates is analyzed, and the corresponding countermeasures are put forward. Questionnaires are issued to investigate the mental health status of fresh graduates. The BSSI score of male students (

102.05
±
2.01

) is not significantly different from that of female students (

P
>
0.05

). SCL-90 scores of male students include somatization (

1.95
±
0.01

), compulsion (

1.84
±
0.15

), interpersonal relationship (

1.75
±
0.14

), depression (

1.92
±
0.08

), anxiety (

1.70
±
0.10

), hostility (

7.25
±
0.16

), terror (

1.35
±
0.41

), bigotry (

1.29
±
0.17

), and psychosis (

1.33
±
0.64

). There is no significant difference compared with those of female students (

P
>
0.05

). SCL-90 scores of high stress graduates include somatization (

2.00
±
0.17

), compulsion (

2.30
±
0.08

), interpersonal relationship (

1.61
±
0.20

), depression (

1.87
±
0.09

), anxiety (

1.80
±
0.11

), hostility (

1.30
±
0.20

), terror (

1.39
±
0.14

), paranoid (

1.48
±
0.10

), and psychosis (

1.50
±
0.11

). There is significant difference between forced and low pressure graduates (

P
<
0.05

). There is no statistical significance in other items (

P
>
0.05

). Colleges and universities need to work together with fresh graduates to deal with negative emotions and stress, so as to improve mental health and promote employment.
[Retracted] Analysis of Expression of Inflammatory Factors and T Cell Lymphocyte in Patients with Orthopedic Trauma after Infection and Risk Factors
Authors: Lin Yuan , Chen Xiao Lei , Zhang Tong’en
Published: September 2022

Since most orthopedic patients’ wounds are open in clinical practice, postoperative wound infection and other conditions are prone to occur, which pose varying degrees of threat to patients’ prognosis and life and health. In this paper, a retrospective study is conducted on orthopedic trauma patients in our hospital from January 2020 to January 2022, including 98 patients with postoperative infection and 98 patients without infection, to detect and compare the levels of inflammatory factors and the level of T cell lymphatic group index difference. The ROC curve is drawn to analyze the diagnostic efficacy of postoperative infection indicators for patients with orthopedic trauma. The differences in baseline data between the two groups are compared. Multivariate Logistic regression analysis is performed on infection status. The experimental results show that the IL‐6, IL‐2, and CRP of the infection group of patients are significantly higher than uninfected group, and the CD3, CD4, and CD8 are significantly lower than uninfected group, which means that patients with infection after orthopedic trauma are in a disordered state of immune cytokines and function. Therefore, postoperative infection can be effectively assessed by early combined detection of the above indicators. In addition, the analysis of other clinical data showed that the operation time, the number of underlying diseases, and the surgical method are also risk factors for postoperative infection.
[Retracted] Synthesis of Zinc Oxide (ZnO)‐Titanium Dioxide (TiO2)‐Chitosan‐Farnesol Nanocomposites and Assessment of Their Anticancer Potential in Human Leukemic MOLT‐4 Cell Line
Authors: Elderdery Abozer Y. , Alzahrani Badr , Hamza Siddiqa M. A. , Mostafa-Hedeab Gomaa , Mok Pooi Ling , Subbiah Suresh Kumar
Published: September 2022

Leukemia is the most prevalent cancer in children and one of the most common and deadly cancers that affect adults. Several metal oxide nanoparticles, biopolymers, and phytochemicals have been discovered to target cancer cells selectively while inflicting low to no damage to healthy cells. Among the existing nanoparticle synthesis methodologies, biologically synthesized nanoparticles using phytochemicals have emerged as a straightforward, economical, and environmentally sound strategy. The synergistic antitumor potential of ZnO‐TiO2‐chitosan‐farnesol nanocomposites (NCs) against leukemia MOLT‐4 cells was investigated in the current study. After synthesizing the NCs, characterization of the same was carried out using XRD, DLS, FESEM, TEM, PL, EDX, and FTIR spectroscopy. To analyze its anticancer activity, MOLT‐4 cells were cultured and treated at diverse dosages of NCs. The cell viability upon treatment was examined by MTT assay. The morphological and nuclear modifications were observed by dual staining. ROS and MMP levels were observed by DCFH‐DA staining and Rh‐123 dye, respectively. Furthermore, the caspase 3, 8, and 9 levels were examined by performing ELISA. The XRD patterns exhibited a hexagonal structure of the NCs. In the DLS spectrum, the hydrodynamic diameter of the NCs was observed to be 126.2 nm. The electrostatic interface between the ZnO‐TiO2‐chitosan‐farnesol NCs was confirmed by the FTIR spectra. A significant loss of cell viability in a dosage‐dependent trend confirmed the cytotoxic effect of the NCs. An elevated ROS level and MMP depletion suggested apoptosis‐associated cell death via the intrinsic pathway, which was confirmed by elevated expressions of caspase 3, 8, and 9 markers. Thus, the results showed that the synthesized NCs demonstrated a remarkable anticancer potential against leukemic cells and can be potentially valuable in cancer treatments. The findings from this study conclude that this is a new approach for modifying the physicochemical characteristics of ZnO‐TiO2‐chitosan‐farnesol composites to increase their properties and synergistically exhibit anticancer properties in human leukemic cancer cells.
Acupuncture Interventions for Alzheimer’s Disease and Vascular Cognitive Disorders: A Review of Mechanisms
Authors: Du Kunrui , Yang Shaojie , Wang Jingji , Zhu Guoqi
Published: September 2022

Cognitive impairment (CI) related to Alzheimer’s disease (AD) and vascular cognitive disorders (VCDs) has become a key problem worldwide. Importantly, CI is a neuropsychiatric abnormality mainly characterized by learning and memory impairments. The hippocampus is an important brain region controlling learning and memory. Recent studies have highlighted the effects of acupuncture on memory deficits in AD and VCDs. By reviewing the literature published on this topic in the past five years, the present study intends to summarize the effects of acupuncture on memory impairment in AD and VCDs. Focusing on hippocampal synaptic plasticity, we reviewed the mechanisms underlying the effects of acupuncture on memory impairments through regulation of synaptic proteins, AD characteristic proteins, intestinal microbiota, neuroinflammation, microRNA expression, orexin system, energy metabolism, etc., suggesting that hippocampal synaptic plasticity may be the common as well as the core link underlying the above mechanisms. We also discussed the potential strategies to improve the effect of acupuncture. Additionally, the effects of acupuncture on synaptic plasticity through the regulation of vascular–glia–neuron unit were further discussed.
[Retracted] Effects of Different Doses of Rimazolam on Oxidative Stress Level Sedation Score and Recovery Time of Patients during Hip Replacement
Authors: Wu Zhenhua , Lu Qiaoling , Cheng Hao , Wu Chengwei
Published: September 2022

The effects of Rimazolam on oxidative stress level, sedation score, and recovery time of patients under different doses in hip replacement are investigated. A total of 100 patients who underwent hip arthroplasty in our hospital from September 2020 to May 2022 are selected as the study subjects. According to the random number table method, they are divided into observation group and control group. The observation group is given 0.3 mg/kg Rimazolam, and the control group is given 0.4 mg/kg Rimazolam. Oxidative stress level, hemodynamic indexes at different time after anesthesia, sedation score and sedation depth, Visual Analogue Scale/Score (VAS) score and incidence of adverse reactions are observed in 2 groups. The correlation of sedation score with oxidative stress index and pain degree is analyzed. The experimental results show that Rimazolam has a good anesthesia induction effect in hip replacement, but the low dose (0.3 mg/kg) can reduce the level of oxidative stress in patients, has a better sedation effect and can maintain the stability of patients’ hemodynamic indicators, and has a positive effect on relieving postoperative pain in patients. [Clinical Trial Registration Number‐ ChiCTR2000038548].
A Deep Learning-Based Text Emotional Analysis Framework for Yellow River Basin Tourism Culture
Authors: Dong Qiutong , Fang Runsheng
Published: September 2022

As an important carrier of cultural communication, tourism can play a positive role in promoting regional ecology and cultural heritage. Therefore, this paper takes tourist attractions in the Yellow River basin as the research object and constructs mining and comment sentiment analysis for tourism text information in the Yellow River basin that appears on social media platforms. Based on the theory of the social center network, the tourism culture network of the Yellow River basin based on tourists’ emotion analysis is constructed. In addition, based on the linear fusion algorithm of semantic orientation pointwise mutual information and word2vec, this paper constructs an emotion dictionary in the field of tourism review and proposes a set of comprehensive emotion calculation rules based on Chinese text expression structure. The experimental results of 32 scenic spots in the Yellow River basin show that the proposed algorithm can achieve better sentiment classification of tourism texts, broaden the scope of application of the domain sentiment dictionary construction method, and improve efficiency.
[Retracted] Evaluation of ABC Bleeding Score and SAMe‐TT2R2 Score on the Risk of Bleeding after Anticoagulation in Patients with Nonvalvular Atrial Fibrillation Complicated with Coronary Heart Disease
Authors: Du Meiling , Li Feixing , Zhang Aiai , Li Fangjiang , Wang Xiaoyuan
Published: September 2022

Objective. To explore the predictive value of ABC bleeding score and SAMe‐TT2R2 score on the risk of bleeding in patients with nonvalvular atrial fibrillation (NVAF) complicated with coronary heart disease (CHD) after anticoagulation. Methods. 149 patients with NVAF complicated with CHD were followed up in our hospital for one year. The bleeding events during the follow‐up period were observed, the ABC bleeding score and SAMe‐TT2R2 score were calculated, the predictive value of the two scoring methods for the main bleeding risk was analyzed by the ROC curve, and the AUC area under the ROC curve of the two scoring methods was compared by the Delong test. Results. There were 32 bleeding events during the follow‐up period. The AUC of ABC bleeding score and SAMe‐TT2R2 score were 0.775 (P < 0.01) and 0.624 (P < 0.05), respectively. The Delong test showed that the AUC of ABC bleeding score was significantly higher than that of SAMe‐TT2R2 score (d = 2.177, P < 0.05). Conclusion. Both the ABC bleeding score and SAMe‐TT2R2 score can predict the risk of bleeding after anticoagulation in patients with NVAF and CHD. The critical value of the SAMe‐TT2R2 score for predicting bleeding events in patients with NVAF and CHD may need to be increased to 4 or 5, and the prediction ability of ABC bleeding score is significantly better than that of the SAMe‐TT2R2 score.
PM2.5 Exposure Induces Lung Injury and Fibrosis by Regulating Ferroptosis via TGF-β Signaling
Authors: Guo Li , Bai Shuping , Ding Shaohua , Zhao Ling , Xu Shanqi , Wang Xiaohong
Published: September 2022

Background. Lung fibrosis is a severe lung disorder featured by chronic nonspecific inflammation of the interstitial lung and deposition of collagen, leading to lung dysfunction. It has been identified that ferroptosis is involved in the progression of lung injury. Particulate matter (PM2.5) is reported to be correlated with the incidence of pulmonary fibrosis. However, mechanisms underlying ferroptosis in PM2.5-related lung fibrosis is unclear. In this study, we aimed to explore the effect of PM2.5 on ferroptosis in lung fibrosis and the related molecular mechanisms. Methods. PM2.5-treated mouse model and cell model were established. Fibrosis and tissue damage were measured by Masson’s trichrome staining and HE staining. Fibrosis biomarkers, such as α-SMA, collagen I, and collagen III, were examined by histological analysis. The ferroptosis phenotypes, including the levels of iron, Fe2+, MDA, and GSH, were measured by commercial kits. ROS generation was checked by DCFH-DA. The oxidative stress indicators, 3-nitro-L-tyrosine (3

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-NT), 4-HNE, and protein carbonyl, were checked by enzyme linked immunosorbent assay (ELISA). The thiobarbituric acid reactive substances (TBARS) and GSH/GSSG ratio were assessed by TBARS assay kit and GSH/GSSG assay kit, respectively. TGF-β signaling was detected by Western blotting. Results. PM2.5 induced the lung injury and fibrosis in the mice model, along with elevated expression of fibrosis markers. PM2.5 enhanced oxidative stress in the lung of the mice. The SOD2 expression was reduced, and NRF2 expression was enhanced in the mice by the treatment with PM2.5. PM2.5 triggered ferroptosis, manifested as suppressed expression of GPX4 and SLC7A11, decreased levels of iron, Fe2+, and MDA, and increased GSH level in mouse model and cell model. The TGF-β and Smad3 signaling was inhibited by PM2.5. ROS inhibitor NAC reversed PM2.5-regulated ROS and ferroptosis in primary mouse lung epithelial cells. Conclusions. Therefore, we concluded that PM2.5 exposure induced lung injury and fibrosis by inducing ferroptosis via TGF-β signaling.
Multiple Statistical Model Ensemble Predictions of Residual Chlorine in Drinking Water: Applications of Various Deep Learning and Machine Learning Algorithms
Authors: Onyutha Charles
Published: September 2022

Applicability of statistical models in predicting chlorine decay remains minimally explored. This study predicted residual chlorine using six deep learning and nine machine learning techniques. Suitability of multimodel ensembles (MMEs) including arithmetic mean of all the models (Ens1), average of the best three performing models (Ens2), and weighted mean of outputs from all the 15 models was investigated. A total of nine “goodness‐of‐fit” measures (such as distance correlation (rd) and Taylor skill score) were used to rank the models. The two best deep learning methods were the nonlinear autoregressive model with exogenous input (NARX) (rd = 0.51) and feedforward backpropagation (FFB) (rd = 0.61). The two best machine learning algorithms included random forests (RF) (rd = 0.64) and Gaussian process regression (GPR) (rd = 0.59). Eventually, Ens2 was obtained using RF, FFB, and GPR. Ens2 performed better than Ens1 and Ens3. The amount of variance explained by individual models and MMEs was over the ranges of 13–66% and 51–74%, respectively. Ens2 explained 74% of the total variance in observed residual chlorine. Remarkably, the appropriateness of the MMEs depends on the approach for combining model outputs, and the number of models considered. This study demonstrated the acceptability of statistical MMEs in predicting chlorine residual concentration in drinking water.