bluuebunny/crossref_metadata_2025 huggingface dataset:
Treatment Satisfaction and Its Influencing Factors in Parkinson’s Disease: A Web-Based Survey of Patients and Physicians in Clinical Practice in Japan
Authors: Nomoto Masahiro , Hayashi Ayako , Ida Hiroyuki , Arai Masaki
Published: February 2022

Objective. This study aimed to gain an understanding of patient and physician satisfaction with overall treatment and routine consultations for Parkinson’s disease in clinical practice. Methods. This observational, cross-sectional, web-based survey was conducted in Japan from February to March 2019. Eligible patients with Parkinson’s disease (N = 186) and physicians who treat patients with Parkinson’s disease (N = 331) were asked to evaluate their satisfaction with treatment, consultation, symptom control, and use of a symptom diary. Results. Patients had a mean age of 62.7 years, 54.8% were male, and most (75.8%) had Hoehn and Yahr stage ≥3 symptoms. Physicians were mostly male (93.1%) and had treated 52 patients with Parkinson’s disease in the last 6 months, and 34.1% were certified neurologists. There were significant gaps between patient and physician satisfaction with treatment and consultations. Patient and physician satisfaction with overall treatment was significantly lower for patients with Hoehn and Yahr stage ≥3 symptoms than stage 1-2 symptoms (patients: 53.9% vs. 71.1%; physicians: 43.2% vs. 69.7%, respectively). The proportion of patients who were satisfied with symptom control was lower than that of physicians (26.4% vs. 51.5%). Influencing factors for patient satisfaction with treatment were nonmotor symptoms (e.g., insomnia and depression). Satisfaction tended to be higher for patients and physicians when symptom diaries were used. Conclusion. Significant gaps in perceptions of treatment and consultation exist between patients and physicians in Parkinson’s disease. Physicians should participate in shared decision making with their patients and consider strategies for management of nonmotor symptoms and nonpharmacological therapies and encourage the use of symptom diaries.
New Opportunities, Challenges, and Applications of Edge-AI for Connected Healthcare in Internet of Medical Things for Smart Cities
Authors: Kamruzzaman M. M. , Alrashdi Ibrahim , Alqazzaz Ali
Published: February 2022

Revolution in healthcare can be experienced with the advancement of smart sensorial things, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Internet of Medical Things (IoMT), and edge analytics with the integration of cloud computing. Connected healthcare is receiving extraordinary contemplation from the industry, government, and the healthcare communities. In this study, several studies published in the last 6 years, from 2016 to 2021, have been selected. The selection process is represented through the Prisma flow chart. It has been identified that these increasing challenges of healthcare can be overcome by the implication of AI, ML, DL, Edge AI, IoMT, 6G, and cloud computing. Still, limited areas have implemented these latest advancements and also experienced improvements in the outcomes. These implications have shown successful results not only in resolving the issues from the perspective of the patient but also from the perspective of healthcare professionals. It has been recommended that the different models that have been proposed in several studies must be validated further and implemented in different domains, to validate the effectiveness of these models and to ensure that these models can be implemented in several regions effectively.
Research on Psychological Problems and Countermeasures of Contemporary College Students Based on Data Analysis
Authors: YouYu Huang
Published: February 2022

Due to absence of good and high prevalence rate of the comprehensive method of automatic assessment, the current mental health assessment is still subject to manual answer questionnaires. The main drawback of this is that the detection of mental health issues of contemporary college students through the manual answer questionnaire is not satisfactory. Mental health problems of the students cannot be properly detected, and as a result, they remain deprived of timely psychological counseling and treatment. At the same time, in order to improve the accuracy of automatic selection of mental health and the popularity of this solution, this study first presents a detailed analysis of the possible mental health problems encountered by contemporary college students. A radial basis function (radial basis function, RBF) neural network application in the automatic selection of mental health status and comparative verification. The results proved the higher accuracy and warning of the RBF nervous system in comparison to the mental health of contemporary college students. The research further investigates the dependence of the psychological problems and solutions of contemporary college students on data analysis. It can be rightly said that the study is of great importance due to its provision of new research direction and relevant countermeasures for the psychological problems of college students.
Semantic Analysis of Multimodal Sports Video Based on the Support Vector Machine and Mobile Edge Computing
Authors: Chen Xu
Published: February 2022

Even though sports video analysis and research have yielded some results, the competition video itself contains a large number of images, video, audio, text, and other elements. Video semantic analysis has always been a hot and difficult topic in video studies. Multimodal sports video data contain a wealth of data. Second, it has a complex structure with an ambiguous relationship between each video unit. A typical algorithm based on kernel function learning is a support vector machine. It has shown promising results in the prediction of landslide displacement time series. The semantic analysis of multimodal sports video using support vector machines and mobile edge computing is the subject of this study. The theoretical prediction results based on the monitoring data of multimodal sports video semantic analysis show that they are comparable to neural network prediction results using genetic algorithm. The semantic analysis of multimodal sports video based on support vector machine method proposed in this study has a better prediction ability, and its theoretical prediction results are close to the actual monitoring values.
Biharmonic Curves in a Strict Walker 3-Manifold
Authors: Gningue Mamadou , Ndiaye Ameth , Nkunzimana Rénovat
Published: February 2022

In this paper, we study the geometry of biharmonic curves in a strict Walker 3-manifold and we obtain explicit parametric equations for biharmonic curves and time-like biharmonic curves, respectively. We discuss the conditions for a speed curve to be a slant helix in a Walker manifold. We give an example of biharmonic curve for illustrating the main result.
Prevalence and Factors Associated with Low Birth Weight and Preterm Delivery in the Ho Municipality of Ghana
Authors: Axame Wisdom Kudzo , Binka Fred Newton , Kweku Margaret
Published: February 2022

Background. Low birth weight and preterm delivery are birth outcomes that can predict newborns’ survival, development, and long-term health outcomes. This study assessed the prevalence and factors associated with low birth weight and preterm delivery in the Ho Municipality of Ghana. Methods. This retrospective, cross-sectional study analysed data from 680 birth records between October and December 2018. Univariate and multivariate logistic regression models predicted low birth weight and preterm delivery factors. Results. The prevalence of low birth weight and preterm delivery was 12.9% and 14.1%, respectively. Increasing maternal age (AOR: 0.52; 95% CI: 0.28–0.98), multiparity (AOR: 0.54; 95% CI: 0.30–0.94) and increasing doses of sulphadoxine-pyrimethamine (AOR: 0.43; 95% CI: 0.22–0.84) significantly reduced the odds of low birth weight. However, caesarean section (AOR: 1.94; 95% CI: 0.1.16–3.27) and hypertension (AOR: 2.06; 95% CI: 1.27–03.33) significantly increased the likelihood of low birth weight. An increasing number of antenatal care visits (AOR: 0.38; 95% CI: 0.18–0.80) and doses of sulphadoxine-pyrimethamine (AOR: 0.43; 95% CI: 0.19–0.97) were significantly associated with decreased odds of preterm delivery, while caesarean section increased the odds of preterm delivery by two folds (AOR: 2.14; 95% CI: 1.15–3.99). Conclusion. This study shows that maternal age, parity, number of antenatal care visits, hypertension, SP/IPTp, and caesarean section were independently associated with low birth weight and preterm delivery. Education and interventions should be prioritised as vitally important on these factors to reduce the risk and complications associated with these birth outcomes.
Research on the Influencing Factors and Driving Paths of Public Opinions Reversed by Public Emergencies: Clear Set Qualitative Comparative Analysis Based on 30 Cases from 2014 to 2020 (QCA)
Authors: Li Yanling , Wu Xianwen
Published: February 2022

Studying the influencing factors and identifying the driving path of public opinion reversal have important practical significance for effectively avoiding the risk of public opinion reversal. Combined with the theory of actor network, the analysis shows that 7 important factors in the public opinion reversal are the antecedent conditions of public opinion reversal in public emergencies. Qualitative comparative analysis identifies the internal motivation and driving path of the reversal of online public opinion. Four core driving paths are obtained. Through the analysis of different condition combination paths, the conclusion is reached: the role of opinion leaders in reversing public opinion in public emergencies is limited; the central government must pay attention to the core role of the response; be wary of graphics and text formal dissemination; it is necessary to strengthen the check and review and standardize the management of the first issuer.
Effect of Acupuncture and Rehabilitation Therapy on the Recovery of Neurological Function and Prognosis of Stroke Patients
Authors: Fu Lanping , Wang Fei , Ma Zhiyi , Zhang Jin , Xiong Wuzhong , Wang Le
Published: February 2022

Background. Stroke is a common cerebrovascular disease among the middle-aged and elderly, which can lead to a series of neurological disorders. Acupuncture is an important part of traditional Chinese medicine, with great value in improving the neurological deficits of stroke patients. In addition, rehabilitation therapy is also of great significance for alleviating the neurological deficits of patients and improving their activities of daily living. Objective. To explore the effect of acupuncture and moxibustion combined with rehabilitation therapy on the recovery of neurological function and prognosis of stroke patients. Methods. The case data of 100 stroke patients treated in the Wuhan Hospital of Traditional Chinese Medicine from January 2019 to July 2021 were analyzed retrospectively. According to the treatment plan patients received, they were divided into the following two groups: an observation group (

n
=
52

) treated with acupuncture combined with rehabilitation therapy and a control group (

n
=
48

) treated with rehabilitation therapy alone. The two groups were compared in terms of the following items: therapeutic efficacy, plasma levels of cortisol (Cor) and neuropeptide Y (NPY), nerve function, motor function, balance ability, self-care ability, swallowing function, negative emotions, and quality of life. Results. The therapeutic effect of the observation group was significantly higher than that of the control group (

P
<
0.05

). The levels of Cor and NPY, as well as the neurological function, motor function, balance ability, self-care ability, swallowing function, and negative emotions, were not significantly different between the two groups before treatment (

P
>
0.05

). While after intervention, all the above indexes improved in both groups, with better improvements in the observation group compared with the control group (

P
<
0.05

). And the various dimensions concerning the quality of life of patients were also significantly better in the observation group when compared with the control group. Conclusion. Acupuncture of traditional Chinese medicine combined with rehabilitation therapy has outstanding effects in stroke treatment and can effectively improve the neurological function, prognosis, and quality of life of patients, which is worthy of clinical promotion.
Intelligent Capital, Organizational Learning, and Corporate Performance Influence Relationship
Authors: Lin Li-Wei , Gan Su-Mei , Wei Shih-Yung
Published: February 2022

Purpose. The purpose of this paper is to examine the factors influencing intelligent capital on enterprise performance. Design/Methodology/Approach. Based on dynamic panel data of listed companies in the Taiwan electronics industry from 2006 to 2017, we used the GMM estimation method. Findings. The findings of this study indicate that human capital, innovation capital, process capital, and customer capital all significantly improve enterprise performance through the mechanism of organizational learning. Research Limitations/Implications. Future research on cross-country studies of various forms of electronics industry would be worth conducting to determine regional differences in the development of electronics industry activities. Originality/Value. The empirical results demonstrate that human capital, process capital, and customer capital exert a significant promoting effect on enterprise performance, while innovation capital significantly inhibits improvement of enterprise performance.
Design and Implementation of Intelligent Monitoring System for Head and Neck Surgery Care Based on Internet of Things (IoT)
Authors: Liu Qiuxia , Hou Sujuan , Wei Lili
Published: February 2022

As a chronic disease, cervical spondylosis is prone to recurrent attacks as we age if we do not pay attention to protection, which can easily lead to symptoms such as osteophytes and herniated discs. In the early stage of cervical spondylosis, it is possible to alleviate the disease and prevent its aggravation by improving poor cervical posture and increasing cervical activities. This article analyzes the current situation and medical prospect of smart wearable devices with the prevention and treatment of cervical spondylosis in white-collar people as the starting point and smart wearable devices as the focus and provides a detailed analysis of the functions, categories, technologies, and applications of smart wearable devices to provide a technical theoretical basis for the construction of the subsequent research system. For the user's health state, some other physiological parameters are sent to data also through mobile Internet, and the user's physiological information is obtained on the computer database in also, which not only provides the monitoring function for the user's health but also provides the information of medical big data elements for medical and health institutions and so on. This article elaborates the requirement analysis of this system, based on which the system architecture design and module division are elaborated. It provides a practical and theoretical basis for further realizing the seamless integration of IoT technology and nursing information management system and improving its depth and breadth in the application of nursing information management system. From the perspective of the way of quantification of nursing practice activities, real-time monitoring, scientific management, and intelligent decision-making, it provides the basis for achieving the quality of nursing services, reducing errors, reducing labor intensity, and improving work efficiency and clinical research.
Analysis of the Clinicopathologic Characteristics and Prognosis of Head and Neck Lymphoma
Authors: Yan Shufang , Ma Jiajia , Yang Meihong , Liu Bo , Li Sijing , Yang Liuqing , Zhang Qian , Li Xinxia
Published: February 2022

Statistical reports on non-Hodgkin’s lymphoma (NHL) of the head and neck combining clinical medicine with pathology are rare. To provide a basis for prognosis prediction and individualized treatment, we will investigate the clinicopathologic characteristics and prognosis of lymphoma in the head and neck region. Four hundred sixty-one patients with NHL in the head and neck region diagnosed through histological biopsy were retrospectively analyzed. Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) were performed in all cases to evaluate the genetic status and protein expression levels. Patients were followed up by telephone. The prevalence rate of primary extranodal NHL (PENHL) in the head and neck region was 44.62% (166/372). The incidence of extranodal lymphoma accounted for 36.66% (169/461) of all head and neck lymphomas. Among the cases of PENHL of the head and neck, diffuse large B-cell lymphoma (DLBCL) (60/76, 78.95%) and extranodal NK/T-cell lymphoma, nasal type (ENKTCL) (21/24, 87.5%) were the most common subtypes originating from B-cell lymphoma (BCL) and T-cell lymphoma (TCL), respectively. The most common sites of nodal and extranodal onset were neck lymph nodes and the gastrointestinal tract, respectively. The most common and primary locations of BCL and TCL were the tonsils and nasal cavity, respectively. The 3-year survival rates of PENHL, ENKTCL, and DLBCL of the head and neck were 42%, 28.57%, and 41.67%, respectively, and the 5-year survival rates were 24%, 19.05%, and 20%, respectively. Survival analysis showed that male sex was a risk factor (

HR
=
5.421

; 95% CI, 1.164-25.267;

p
<
0.05

) and that comprehensive treatment was a protective factor (

HR
=
0.117

; 95% CI, 0.025-0.545;

p
<
0.05

) against extranodal DLBCL in the head and neck region. Bone marrow involvement was a risk factor for PENHL of the head and neck (

HR
=
5.072

; 95% CI, 1.17-21.991;

p
<
0.05

). The purpose of this review is to show that PENHL of the head and neck with high incidence deserves more attention, and a model of multidisciplinary diagnosis and treatment should be adopted.
Integrated Analysis of DNA Repair Genes Identifies SLC6A1 as a New Marker for the Clinical Outcome of Patients with Colorectal Cancer
Authors: Wang Qian-qian , Wei Yang , Luo Li-ping , Li Xin , Jiang Wen-jun
Published: February 2022

Colorectal cancer (CRC) remains an important malignancy worldwide with poor prognosis. It has been known that DNA repair genes are involved in the development and progression of various tumors. Therefore, the purpose of this study was to explore DNA repair gene-based prognostic biomarkers for CRC. In this study, the expressing pattern and prognostic values of DNA repair genes in CRC patients were analyzed using TCGA database. GO and KEGG enrichment analyses were conducted to clarify the functional roles of dysregulated genes. We observed 358 differentially expressed DNA repair genes in CRC specimens, including 84 downregulated genes and 275 upregulated genes. 36 survival-related DNA repair genes were correlated with CRC patients’ five-year survival, including 6 low-risk genes and 30 high-risk genes. Among the 10 overlapping genes, we focused on SLC6A1 which was highly expressed in CRC, and multivariate analysis confirmed that SLC6A1 expression as well as age and clinical stage could be regarded as an independent predicting factor for CRC prognosis. KEGG assays revealed that SLC6A1 may influence the clinical progression via regulating TGF-beta and PI3K-Akt signaling pathways. In addition, we observed that SLC6A1 was negatively regulated by SLC6A1 methylation, leading to its low expression in CRC specimens. Overall, SLC6A1 is upexpressed in CRC and can be used as a marker of poor prognosis in CRC patients.
[Retracted] Multidimensional State Data Reduction and Evaluation of College Students’ Mental Health Based on SVM
Authors: Peiqing Han
Published: February 2022

In response to the shortcomings of the traditional methods for evaluating the mental health status of college students in terms of computational complexity and low accuracy, a method for evaluating the mental health status of college students based on data reduction and support vector machines was proposed. A model experiment containing internal and external personality tendency classification, anxiety, and depression dichotomy was designed using logistic regression analysis, information entropy, and SVM algorithm to construct the feature dimensions of the network behavior data, combined with the labeled data of mental state to derive the sample data set for model experiments. In the experimental process, to reflect the difference in the effect of different models, various types of mathematical models were constructed for horizontal comparison; at the same time, to reflect the influence of the parameters of the same type of model, different combinations of parameters were constructed using a grid search algorithm to vertically compare the difference in the effect. The average accuracy of the dichotomous model for anxiety and depression in the sample of 1433 students was 0.80 or higher. The experiments show that the method of predicting students’ psychological status through their online behavioral data is feasible, and the mathematical classification model can be used to grasp students’ psychological status in real time and to warn students with abnormal psychological status, thus helping school counselors to intervene and prevent them promptly.
[Retracted] Empirical Research on the Relationship between Industry Working Capital Shortfall and Company Cash Holding in the Same Industry
Authors: Li Zhaohua , Jiang Junyi , Xia Lijuan , Chu Chien-Chi
Published: February 2022

Affected by the fluctuation of the market and economic environment during the epidemic period, the capital pressure of companies has increased sharply, which increases the possibility of risk transmission in the same industry and poses new challenges to the operation and financing of companies. From the perspective of preventive motivation of corporate cash holding, we creatively use the industry working capital shortfall as the explanatory variable to construct an Extended Cash Holding Model and a Cash Holding Value Regression Model. Taking the panel data of A‐share listed companies in Shanghai and Shenzhen as samples, this paper uses the Classical Linear Regression Model and Fixed Effects Regression Model to study the relationship between industry working capital shortfall and cash holdings in the same industry, as well as the relationship between industry working capital shortfall and cash holding value. The empirical results show that industry working capital shortfall has an important impact on the cash holding level within the same industry, and the cash holding level is significantly and positively correlated with industry working capital shortfall. Moreover, this study also reveals that the industry working capital shortfall has a dual impact on cash holdings. Specifically, the higher the risk of industry working capital shortfall, the lower the value of company cash holdings. The conclusions of this paper not only extend the research on cash holding but also provide support and reference for companies to optimize the cash holding value.
Computational Study on the Microscopic Adsorption Characteristics of Linear Alkylbenzene Sulfonates with Different Chain Lengths on Anthracite Surface
Authors: Chen Xuanlai , Yan Guochao , Xu Guang , Yang Xianglin , Dong Jinfa , Liang Zidong , Wei Shuai
Published: February 2022

In order to explore the influence of different lengths of hydrophobic carbon chains on the diffusion characteristics of surfactants on the surface of anthracite, six linear alkyl benzene sulfonates with different hydrophobic carbon chain lengths were selected (mC, m = 8, 10, 12, 14, 16, 18; m represents the numbers of carbon atoms in the hydrophobic carbon chain), and molecular dynamics (MD) simulations were adopted. Models of surfactant-anthracite, surfactant-graphite layer, and water-surfactant-anthracite were constructed. After analyzing a series of properties such as adsorption energy, diffusion coefficient, radial distribution function (RDF), and hydrophobic tail order parameters, it was found that 12C had the highest adsorption strength on the surface of anthracite; the reason was that 12C had the highest degree of aggregation near the oxygen-containing functional groups on the surface of anthracite. Further studies had found that the hydrophobic tail chain of 12C had the strongest isotropy. The study fills the gap in the systematic study of the diffusion characteristics of linear alkylbenzene sulfonates (LAS) with different chain lengths on the surface of anthracite, enriches and develops the basic theory of coal wettability, and also provides technical ideas for the design of new surfactants and new dust suppression agents.
Advances in Nanostructured Polyamide‐Based Chemical Sensors
Authors: Khanyile Nokuthula
Published: February 2022

Nanofibers have shown great potential to contribute to the growing demand for point of care sensors and other kinds of sensors where they are utilized as supporting materials or used to interact with other materials through their functional groups. The choice of a polymer material to be used depends on whether it has the potential to give the properties of the desired sensor. Polyamide nanofibers have properties such as good chemical resistance, very good strength and hardness, high wear resistance, and high surface area to volume ratio, and they are porous, just to name a few. Furthermore, the amide groups in polyamide enable it to interact with other molecules via hydrogen bonding. These characteristics make polyamide nanofibers good candidates for sensor development. Polyamide nanofibers are used nowadays to make various types of sensors. This paper provides a review of some of the reports on the development of nanostructured polyamide‐based chemical sensors in the last two decades (2000‐2020).
Comprehensive Analysis of HOX Family Members as Novel Diagnostic and Prognostic Markers for Hepatocellular Carcinoma
Authors: Jin Zhipeng , Sun Dongxu , Song Mengying , Zhu Wenjing , Liu Huayuan , Wang Jianping , Shi Guangjun
Published: February 2022

Background. The homeobox (HOX) gene family has been found to be involved in human cancers. However, its involvement in hepatocellular carcinoma (HCC) has not been well documented. Here, we comprehensively evaluated the role of HOXs in HCC. Methods. RNA sequencing profile of TCGA-LIHC and LIRI-JP were obtained from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), respectively. Data of TCGA-LIHC methylation were downloaded from UCSC Xena. Genetic alteration data for the TCGA samples was obtained from cBioPortal and GSCA. The diagnostic efficiency was assessed using ROC curves. The prognostic significance was evaluated by the Kaplan–Meier method and Cox regression analysis. Subsequent functional analysis was performed through the clusterProfiler package. ssGSEA, ESTIMATE, and TIDE algorithms were employed to explore the relationship between HOXs and the HCC microenvironment. Finally, pRRophetic package and NCI-60 cancerous cell lines were applied to estimate anticancer drug sensitivity. Results. The mRNA levels of HOXs in HCC tissues were higher than those of noncancerous tissues and were correlated with poor overall survival (OS). HOXA6, C6, D9, D10, and D13 could serve as independent risk factors for OS. Further functional analysis revealed that these five HOXs regulate the cell proliferation, cell cycle, immune response, and microenvironment composition of HCC. In addition, the aberrant expression and methylation of HOXs is of great value in the diagnosis of HCC. Conclusion. HOXs play crucial roles in HCC and could serve as potential markers for HCC diagnosis and prognosis.
Application of Unsupervised Migration Method Based on Deep Learning Model in Basketball Training
Authors: Sun Hui , Wang Yu , Wang Yujue
Published: February 2022

Nowadays, China’s sports industry has attained effective development, but the athlete’s efficiency in the training process is too complex to have a scientific guarantee. Machine learning technology’s help in guiding the sports training process has become a hot spot. In this work, we investigate the use of deep learning in real-time analysis of basketball sports data, utilizing research approaches such as scientific reporting, audio/video analysis, experimental research, and mathematical statistics. The suggested basketball stance action recognition and analysis system are made up of two pieces that are sequentially connected. The bottom-up stance estimate approach is utilized to locate the joint locations in the first segment, which is then used to extract the target’s posture sequence from the video. The analyses are needed for a Support Vector Machine (SVM) algorithm based on the deep learning method of the space-time graph. The basketball activity of the set classification is recognized and extracted from the segmented stance sequence. The study used an auxiliary method, which is contrasted to standard training, in order to get higher accuracy and also correct player errors in a timely manner. The approach can help players rectify technical errors, develop muscle memory, and increase their abilities. The results revealed that the algorithm generated 97.7% accuracy in evaluating data from basketball training.
Implementation of Financial Audited Robot Question and Answer Technology of Feature Processing and Improved Bi-LSTM
Authors: Liu Bingru , Zhao Qing
Published: February 2022

In order to improve the accuracy of financial robot audit question answering, we propose, on the premise of processing corpus features, combining Bi-LSTM network and CRF to identify the domain entities, so as to solve the problem of low recognition rate of financial knowledge domain entities, and introducing the mechanism based on attention and CNN network to construct the multigranularity feature question-answering matching model. Finally, the above methods are verified by experiments. The results show that the AUC, MAP, and MRR increase by 0.74%, 0.85%, and 0.81%, respectively, indicating the feasibility of the improved method.
Sphingosine 1-Phosphate-Upregulated COX-2/PGE2 System Contributes to Human Cardiac Fibroblast Apoptosis: Involvement of MMP-9-Dependent Transactivation of EGFR Cascade
Authors: Yang Chien-Chung , Hsiao Li-Der , Shih Ya-Fang , Su Mei-Hsiu , Yang Chuen-Mao
Published: February 2022

Human cardiac fibroblasts (HCFs) play key roles in normal physiological functions and pathological processes in the heart. Our recent study has found that, in HCFs, sphingosine 1-phosphate (S1P) can upregulate the expression of cyclooxygenase-2 (COX-2) leading to prostaglandin E2 (PGE2) generation mediated by S1P receptors/PKCα/MAPKs cascade-dependent activation of NF-κB. Alternatively, G protein-coupled receptor- (GPCR-) mediated transactivation of receptor tyrosine kinases (RTKs) has been proved to induce inflammatory responses. However, whether GPCR-mediated transactivation of RTKs participated in the COX-2/PGE2 system induced by S1P is still unclear in HCFs. We hypothesize that GPCR-mediated transactivation of RTKs-dependent signaling cascade is involved in S1P-induced responses. This study is aimed at exploring the comprehensive mechanisms of S1P-promoted COX-2/PGE2 expression and apoptotic effects on HCFs. Here, we used pharmacological inhibitors and transfection with siRNA to evaluate whether matrix metalloprotease (MMP)2/9, heparin-binding- (HB-) epidermal growth factor (EGF), EGF receptor (EGFR), PI3K/Akt, MAPKs, and transcription factor AP-1 participated in the S1P-induced COX-2/PGE2 system determined by Western blotting, real-time polymerase chain reaction (RT-PCR), chromatin immunoprecipitation (ChIP), and promoter-reporter assays in HCFs. Our results showed that S1PR1/3 activated by S1P coupled to Gq- and Gi-mediated MMP9 activity to stimulate EGFR/PI3K/Akt/MAPKs/AP-1-dependent activity of transcription to upregulate COX-2 accompanied with PGE2 production, leading to stimulation of caspase-3 activity and apoptosis. Moreover, S1P-enhanced c-Jun bound to COX-2 promoters on its corresponding binding sites, which was attenuated by these inhibitors of protein kinases, determined by a ChIP assay. These results concluded that transactivation of MMP9/EGFR-mediated PI3K/Akt/MAPKs-dependent AP-1 activity was involved in the upregulation of the COX-2/PGE2 system induced by S1P, in turn leading to apoptosis in HCFs.
Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence
Authors: Guo Ming , Jia Weichen
Published: February 2022

With a large number of images provided by TV and other media flowing into the Internet and the reduction of technical barriers, images have not only become a daily practice for people to record their lives and communicate their behaviors but also become an important means for the public to express their discourse in the cyberspace. Therefore, it is of great significance to analyze the image propagation algorithm using artificial intelligence. This paper mainly studies the algorithm analysis and governance of local media image propagation in the era of artificial intelligence. In this paper, the media is the research object, with its daily dissemination of video works as the research text, in order to discover the ethical problems in its dissemination activities as the purpose, integrating disciplinary knowledge to analyze the ethical problems in this art form, and trying to find out the fundamental measures to solve the problem. The advantages and disadvantages of the video recommendation intelligent algorithm based on the BP neural network are analyzed. By comparing different algorithms, it can be seen that the video recommendation accuracy of the BP neural network algorithm based on swarm optimization (FEBP) is 15.8% higher than that of the traditional BP neural network algorithm. These intelligent algorithms are added into the image transmission system, in order to achieve the goal of improving the image transmission and recommendation effect.
[Retracted] The New Approach Research on Singing Voice Detection Algorithm Based on Enhanced Reconstruction Residual Network
Authors: Liu Lilin
Published: February 2022

With the development of Internet technology, multimedia information resources are increasing rapidly. Faced with the massive resources in the multimedia music library, it is extremely difficult for people to find the target music that meets their needs. How to realize computer analysis and perceive users’ needs for music resources has become the goal of the future development of human‐computer interaction capabilities. Content‐based music information retrieval applications are mainly embodied in the automatic classification and recognition of music. Traditional feedforward neural networks are prone to lose local information when extracting singing voice features. For this reason, on the basis of fully considering the impact of information persistence in the network propagation process, this paper proposes an enhanced two‐stage super‐resolution reconstruction residual network which can effectively integrate the learned features of each layer while increasing the depth of the network. The first stage of reconstruction is to complete the hierarchical learning of singing voice features through dense residual units to improve the integration of information. The second stage of reconstruction is mainly to perform residual relearning on the high‐frequency information of the singing voice learned in the first stage to reduce the reconstruction error. In the middle of these two stages, the model introduces feature scaling and expansion convolution to achieve the dual purpose of reducing information redundancy and increasing the receptive field of the convolution kernel. A monophonic singing voice separation based on the high‐resolution neural network is proposed. Because the high‐resolution network has parallel subnetworks with different resolutions, it also has original resolution representations and multiple low‐resolution representations, avoiding information loss caused by serial network downsampling effects and repeating multiple feature fusions to generate new semantic representations, allowing for the learning of comprehensive, high‐precision, and highly abstract features. In this article, a high‐resolution neural network is utilized to model the time spectrogram in order to correctly estimate the real value of the anticipated time‐amplitude spectrograms. Experiments on the dataset MIR‐1K show that compared with the current leading SH‐4Stack model, the method in this paper has improved SDR, SIR, and SAR indicators for measuring the separation performance, confirming the effectiveness of the algorithm in this paper.
New Inexact Parallel Splitting Algorithm for a Class of Separable Convex Programming
Authors: Chen Xiaobiao , Zhang Meiyu , Lian Gaoshe , Chai Lichen
Published: February 2022

In this paper, a new inexact parallel splitting algorithm based on the shrinkage algorithm is proposed. We bring in inexact terms, and new iteration points are obtained by the parallel splitting method. A new descent direction and a proper step length are derived. Under reasonable assumptions, the convergence of the algorithm is demonstrated. Some matrix correction problem experiments show that the algorithm is efficient and easy to implement.
Application of Cellular Automata with Improved Dynamic Analysis in Evacuation Management of Sports Events
Authors: Xie Jingyi , Zhang Li
Published: February 2022

In this paper, the cellular automaton simulation technology is applied to the evacuation management of sports events, combined with the dynamic analysis method to analyze the collision of people in the evacuation process. At the same time, the cellular automaton model is used to refine the evacuation space to simplify environmental modeling, and the network model is used to determine the individual evacuation path from a macroperspective, simplify modeling, and improve simulation efficiency. In addition, this article simulates the evacuation process of the cellular automaton according to the actual evacuation situation of sports events and constructs the evacuation management system of sports events. Finally, this article evaluates the effect of the model in conjunction with experiments. The experimental results show that the role of the evacuation management system for sports events based on cellular automata proposed in this paper is obvious.
lncRNA RUNDC3A-AS1 Regulates Proliferation and Apoptosis of Thyroid Cancer Cells via the miR-151b/SNRPB Axis
Authors: Deng Yan , Wu Jie , Li Xin
Published: February 2022

The number of thyroid cancer (THCA) cases has increased dramatically worldwide. Many previous reports have confirmed that lncRNA is involved in the pathogenesis of THCA. However, the role and mechanism of lncRNA RUNDC3A-AS1 in THCA have not been studied. We intended to explore the effect of RUNDC3A-AS1 on the proliferation and apoptosis of THCA cells. Relative expression levels of RUNDC3A-AS1, microRNA (miR)-151b, and small nuclear ribonucleoprotein polypeptides B and B1 (SNRPB) were examined by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in THCA cells. The localization of RUNDC3A-AS1 in THCA cells was detected by subcellular fractionation assay. The cell proliferation was tested by 5-ethynyl-2′-deoxyuridine (EdU), cell counting kit-8 (CCK-8), and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays. Flow cytometry was used to examine the cell apoptosis capacity. The relationships between RUNDC3A-AS1 and miR-151b or miR-151b and SNRPB were verified by luciferase reporter assay. The protein level was detected by Western blot analysis. RUNDC3A-AS1 exhibited high expression in THCA cells. RUNDC3A-AS1 knockdown suppressed cell proliferation but induced cell apoptosis. Importantly, RUNDC3A-AS1 targeted miR-151b to regulate the SNRPB expression. In rescue assays, SNRPB overexpression partially reversed the suppressive effect of RUNDC3A-AS1 knockdown on cell proliferation and the promotive effect of RUNDC3A-AS1 knockdown on cell apoptosis. The RUNDC3A-AS1/miR-151b/SNRPB axis regulated THCA cell proliferation and apoptosis, which provides novel insight into THCA investigation at the molecular level.
Effective Stress Factor Analysis of Proppant for Multi-stage Fracturing in Horizontal Wells
Authors: Cai Bo , Gao Rui , He Chunming , Chen Jin , Cheng Ning , Liang Tiancheng , Duan Guifu , Meng Chuanyou , Fu Haifeng , Zhang Haoyu
Published: February 2022

In order to determine the effective stress factor of proppants during the multi-stage hydraulic fracturing operation in horizontal wells and select the appropriate proppant type, the analysis of the effective stress characteristics of proppants is carried out. This analysis considers the geomechanics and long-term production characteristics of multi-stage fractured horizontal wells in reservoirs like Xinjiang Mahu shale oil and Southwest China shale gas. The analysis of influencing factors is also carried out. The results show that, during the multi-stage hydraulic fracturing operation in horizontal wells, the stress on proppants is not only related to geological factors such as reservoir closure stress, but also closely related to total injection volume, cluster spacing, liquid type, injection displacement and post fracture management. First, increasing injection intensity, reducing fracture spacing, using low viscosity fracturing fluid, adopting high injection displacement and utilizing reasonable flowback system can effectively supplement reservoir energy, postpone the effective stress peak of proppants, and increase the effective conductivity of proppants. Second, the production performance analysis results of nearly 300 horizontal wells (from Xinjiang oil field, Erdos tight oil reservoir, Sichuan shale gas reservoir, etc.) shows that: the effective stress of proppants in horizontal wells is only 50–60% of that in vertical wells, which results in a different proppant selection criterion in the volume stimulation of horizontal wells and provides the geomechanics basis of replacing ceramsite proppant with quartz sand to reduce cost and increase efficiency. Based on the above conclusions, the field test of replacing ceramsite proppant with quartz sand was carried out. The proportion of quartz sand increased from less than 30% in 2014 to 69% in 2019. Without any impact on production, the annual investment cost was decreased by more than 1 billion yuan, which set a great example for the promoted low-cost development of unconventional oil and gas reservoirs under low oil price background.
The Relationship between MACC1/c-Met/Cyclin D1 Axis Expression and Prognosis in ESCC
Authors: Shi Yan , Li Meng-Yan , Wang Hui , Li Chao , Liu Wen-Ying , Gao Yong-Mei , Wang Bo , Song Jia-Wei , Ma Yu-Qing
Published: February 2022

Background. Esophageal cancer is one of the most common malignant tumors of the digestive system, with high incidence and mortality. Methods. Immunohistochemical method was used to detect the expression of MACC1, c-Met, and cyclin D1 in ESCC and its adjacent tissues. Statistical analysis was done by SPSS 23.0. Results. The high expression of MACC1 and cyclin D1 was significantly correlated with tumor size. High c-Met expression was associated with patient ethnicity. MACC1 expression was positively correlated with both c-Met and cyclin D1. c-Met expression was also positively correlated with cyclin D1. Patients with high expression of MACC1 and c-Met had worse OS; patients with high c-Met expression also had worse PFS. Conclusion. MACC1, c-Met, and cyclin D1 proteins are closely related to the occurrence and development of esophageal squamous cell carcinoma. MACC1 may affect the prognosis of ESCC by regulating the expression of the c-Met/cyclin D1 axis.
Physicochemical, Rheological, Structural, Antioxidant, and Antimicrobial Properties of Polysaccharides Extracted from Tamarind Seeds
Authors: Ren Likun , Yang Yang , Bian Xin , Li Xiaomei , Wang Bing , Wang Dangfeng , Su Dan , Liu Linlin , Yu Dehui , Guo Xiaoxue , Zhang Xiumin , Zhang Na
Published: February 2022

In this study, the polysaccharides were firstly extracted from the tamarind seeds in which the crude polysaccharides have been extracted once by hot water extraction. The structure was characterized by FTIR, SEM, and X-ray diffraction after removing protein and small molecule impurities. Furthermore, the rheological and bioactivity of tamarind seed polysaccharides (TSP) were also investigated. The results indicated that the yield of the obtained polysaccharide was 3.42%. TSP was mainly composed of glucose (45.09%), galactose (22.80%), and xylose (28.89%), while it contained characteristic structure of polysaccharides, such as –OH, pyranose, and uronic acid at 3,418, 1,150, and 1,040 cm−1 respectively, which demonstrated that it was a uronic acid heteropolysaccharide. Moreover, the XRD pattern revealed the amorphous behavior of TSP, and it was found to consist of films or “sheets” reflected by SEM. The flow behavior testing confirmed its pseudoplastic character, and the flow behavior index (n) was between 0.4539 and 0.9201. The DPPH radical scavenging activity of TSP was 40.34% at 10 mg/mL. Furthermore, TSP displayed moderate hydroxyl radical scavenging and anti-bacterial activities, owing to its special structure and composition. Overall, our results suggested that TSP could be used as a food ingredient with anti-oxidative and antibacterial activities, which provides useful information on the potential utilization of TSP in the food industry.
Monitoring Opioids in Europe: The Need for Shared Definitions and Measuring Drivers of Opioid Use and Related Harms
Authors: Kalkman Gerard A. , van den Brink Wim , Pierce Mimi , Atsma Femke , Vissers Kris C. P. , Schers Henk J. , van Dongen Robert T. M. , Kramers Cornelis , Schellekens Arnt F. A.
Published: February 2022

The past 20 years, the USA is facing a serious opioid crisis initiated by an increase in prescription opioid use. Europe has also seen an increase in prescription opioid use, but the extent of related harm is still largely unknown. Given the impact of the US opioid epidemic, it is important to closely monitor signs of emerging opioid-related problems to guarantee early warnings and timely actions. Shared and meaningful definitions for opioid use and related harms, and relevant information about specific drivers for opioid use and related problems are needed for an adequate policy response. In this commentary, we discuss these definitions, the need to know more about the specific drivers for increased opioid use, its related harm, and proposals for strategies to move forward. Policy recommendations include making a distinction between licit and illicit opioids when monitoring and reporting on opioid-related harm, and using oral morphine equivalents to quantify prescription opioid use in a clinically relevant and comparable manner. A major topic of further research is exploring unique and universal drivers of prescription opioid (mis)use across Europe, in particular the role of opioid diversion.
Indigenous Foods: Resilience against Emerging Diseases
Authors: Tandon Achla Pritam , Ghorai Soma Mondal
Published: February 2022

The harmful effects of processed food have seen a worldwide increase in the number of people falling prey to lifestyle-related diseases. The latest in the row of diseases striking humans has been the deadly COVID-19, which also we would like to critique as a consequence of reduced immunities besides compromised health and sanitation restrictions being exercised. Ironically, Indigenous people, despite their greater challenges with the natural elements, lower levels of infrastructural and medicinal access, we're able to garner their coping mechanisms to curb death counts in their communities. It was observed that support groups at the village level emerged along with traditional food choices as well as them choosing holistic ways of healing. This paper is an attempt to the forefront the idea of ‘going back to basics along with our modern-day lifestyles, dietary preferences, and food consumption patterns.