bluuebunny/crossref_metadata_2025 huggingface dataset:
Oxidative Stress in Fibromyalgia: From Pathology to Treatment
Authors: Assavarittirong Chanika , Samborski Włodzimierz , Grygiel-Górniak Bogna
Published: October 2022

Fibromyalgia (FM) is characterized by chronic widespread musculoskeletal pain associated with sleep problems, fatigue, depression, and anxiety. The persistence of pain, impairment of cognitive function, and negative impact on the psychological state have caused a detrimental effect on the patients’ quality of life. However, to date, the treatment and mechanisms of this disease are yet to be established. Oxidative stress might play a critical role in FM pathophysiology. Increased levels of prooxidative factors such as nitric oxide, lipid peroxidation, and mitophagy can cause pain sensitization in fibromyalgia. Numerous studies have supported the hypothesis of beneficial antioxidative effects in FM. Due to the lack of effective therapy for fibromyalgia, many treatments are sought to reduce pain and fatigue and improve patients’ quality of life. This manuscript discusses the impact of various antioxidative procedures that can diminish fibromyalgia symptoms, such as hyperbaric oxygen therapy, modification of dietary habits, and physical activity.
Characteristics of Maxillary Sinus Septa: A Cone-Beam Computed Tomography Evaluation
Authors: Assari Ahmad , Alotaibi Najwa , Alajaji Maha A. , Alqarni Amal , Ali Alarishi Maha
Published: October 2022

Objective. Our study aimed to determine the prevalence, location, and morphological differences of the septa using CBCT images. Methods. This retrospective study was conducted on CBCT examinations. The sample included both mixed and permanent dentition and edentulous patients. The images were viewed in 3 planes (sagittal, coronal, and axial) and the left and right maxillary sinuses were evaluated for the septa’s prevalence, location, and morphological differences. Results. The measurements were statistically analyzed using SPSS software. Out of 200, 122 patients showed one or more bony septa in the maxillary sinus. The septal location and angulation were not limited to a specific area or a specific range. Significant differences between genders were found. Conclusions. The increased surface area of the septa using plane 2-dimensional radiographs is impossible. CBCT has improved the planning of any sinus procedure and offers adequate information compared to conventional radiographs.
Multicriteria Decision Making for Carbon Dioxide (CO2) Emission Reduction
Authors: Ali Rahman , Iqbal Farkhund , Hassan Zada Muhammad Sadiq
Published: October 2022

The fast industrial revolution all over the world has increased emission of carbon dioxide (CO2), which has badly affected the atmosphere. Main sources of CO2 emission include vehicles and factories, which use oil, gas, and coal. Similarly, due to the increased mobility of automobiles, CO2 emission increases day-by-day. Roughly, 40% of the world’s total CO2 emission is due to the use of personal cars on busy and congested roads, which burn more fuel. In addition to this, the unavailability of parking in all parts of the cities and the use of conventional methods for searching parking areas have added more to this problem. To solve the problem of reducing CO2 emission, a novel cloud-based smart parking methodology is proposed. This methodology enables drivers to automatically search for nearest parking(s) and recommend the most preferred ones that have empty lots. For determining preferences, the methodology uses the analytical hierarchy process (AHP) of multicriteria decision-making methods. For aggregating the decisions, the weighted sum model (WSM) is adopted. The methods of sorting, multilevel multifeatures filtering, exploratory data analysis (EDA), and weighted sum model (WSM) are used for ranking parking areas and recommending top-k parking to the drivers for parking their cars. To implement the methodology, a scenario comprising cars, smart parkings are considered. To use EDA, a freely available dataset “2020testcar-2020-03-03” is used for the estimation of CO2 emitted by cars. For evaluation purpose, the results obtained are compared with the results of traditional approach. The comparison results show that the proposed methodology outperforms the traditional approach.
The Proangiogenic Potential of Rat Adipose-Derived Stromal Cells with and without Cell-Sheet Induction: A Comparative Study
Authors: Xu Xiaoru , Song Shuang , Liu Xiangdong , Zhou Yuchao , Shi Shaojie , Zhao Guoqiang , Wang Xingxing , Chen Xutao , Zhao Wenshuang , Zhang Sijia , Ma Wei , Song Yingliang
Published: October 2022

A functional vasculature for survival remains a challenge for tissue regeneration, which is indispensable for oxygen and nutrient supply. Utilizing mesenchymal stromal cells (MSCs) to alleviate tissue ischemia and repair dysfunctional or damaged endothelium is a promising strategy. Compared to other populations of MSCs, adipose-derived stromal cells (ASCs) possess a more significant proangiogenic potential and are abundantly available. Cell sheet technology has recently been widely utilized in bone engineering. Compared to conventional methods of seeding seed cell suspension onto biological scaffolds, cell sheet technology prevents cell loss and preserves the extracellular matrix (ECM). Nevertheless, the proangiogenic potential of ASC sheets remains unknown. In this study, rat ASC sheets were constructed, and their macro- and microstructures were examined. In addition, we investigated the effects of ASCs and ASC sheets on the biological properties and angiogenic capacity of endothelial cells (ECs). The results demonstrated that the ASC sheets gradually thickened as the number of cells and ECM increased over time and that the cells were in an active state of secretion. Similar to ASC-CM, the conditioned medium (CM) of ASC sheets could significantly enhance the proliferative capacity of ECs. ASC sheet-CM has significant advantages over ASC-CM in promoting the migration and angiogenesis of ECs, where the exosomes secreted by ASC sheets play an essential role. Therefore, using ASC sheets for therapeutic tissue and organ regeneration angiogenesis may be a valuable strategy.
Analysis of Multimedia Combination-Assisted English Teaching Mode Based on Computer Platform
Authors: Zhang Yitian , Li Na
Published: October 2022

English is an important international language. Whether it is international economic or international political communication, it is inseparable from English. English teaching is mainly to impart the basic knowledge of English as well as the knowledge of audiovisual knowledge. However, the traditional English teaching mode often ignores the expression of English emotion and the background of English. The traditional English teaching mode often uses textbooks and other forms to impart knowledge, which can no longer meet the English teaching in today’s era. Computer-aided systems have become an important technology in the field of teaching today. Multimedia technology can also show English knowledge to students in the form of video or audio. This will increase students’ interest in learning English. This research will use computer platform and multimedia technology to build a new English teaching platform. It also uses the ConvLSTM algorithm and the CF algorithm to implement the active recommendation function of English knowledge. The research results show that multimedia technology can achieve the purpose of collecting video and audio information in the process of English teaching. The CF algorithm has a specific high similarity index in recommending English knowledge. The ConvLSTM method can also better predict the characteristics of English grammar and English emotion in the English teaching process. This can also show that the multimedia-assisted English teaching mode has a certain use value for different English teaching scenarios.
Design of the UAV Trajectory Tracking System Based on the Adaptive Neural Network - ADRC Method
Authors: Cai Xin , Zhu Xiaozhou , Yao Wen
Published: October 2022

In order to solve the problems of internal uncertainty and external disturbance of an unmanned aerial vehicle (UAV), this paper proposes the active disturbance rejection controller (ADRC) based on the adaptive radial basis function (RBF) neural network. Firstly, the dynamic model of a quadrotor with disturbance is analyzed and the controller is designed based on the ADRC method. Secondly, the RBF network is used to estimate the unknown parameter

b

of the system and the Lyapunov function is constructed to prove the stability of the closed-loop system. Finally, simulation results of a spiral ascent and a climbing maneuver flight illustrate that the controller proposed in this paper has high tracking accuracy and strong robustness under different flight scenarios; the average tracking error of the outdoor flight experiment is about 0.22 m, which further verifies the effectiveness of the proposed controller.
Analysis of the Renal Protection and Antioxidative Stress Effects of Panax notoginseng Saponins in Diabetic Nephropathy Mice
Authors: Mi Wei , Yu Min , Yin Shuying , Ji Yuhan , Shi Tala , Li Ning
Published: October 2022

Objective. Diabetic nephropathy (DN), a diabetes-induced chronic complication, is the major trigger of end-stage renal disease. As the main active ingredient of Panax notoginseng (PNG), Panax notoginseng saponins (PNS) are crucial in treating renal diseases. This study is aimed at investigating the role played by PNS in renal protection and antioxidative stress (OS) in DN mice. Methods. A DN mouse model was constructed, and then low, medium, and high doses of PNS were used to intervene the model group mice. Eight weeks after intervention, the 24 h urine protein (UPro) and urinary albumin (UAlb) were quantitatively examined, and the related blood biochemical indices were measured. HE and PAS staining were performed for pathological changes of renal tissue. ELISA and western blotting were carried out to quantify the levels of OS indexes and inflammatory factors (IFs) in mouse kidney tissues and the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1), respectively. Results. The weight of DN mice decreased first compared with control animals and then gradually increased after different doses of PNS treatment. Besides, DN mice presented elevated urine volume, UPro, and UAlb, all of which were reversed by PNS intervention. SOD activity and GSH content in renal tissues of the model group mice decreased markedly versus the control group, and MDA, CRP, IL-6, and TGF-β1 contents elevated statistically, while different doses of PNS effectively reduced the OS injury and IFs in mice. Compared with the model group, PNS dose-dependently increased Nrf2 and HO-1 levels in DN mice. Conclusions. PNS is protective of HFF + STZ-induced DN mice against kidney tissue damage and can reduce the excretion of UPro and relieve the OS state of mice, possibly by activating Nrf2/HO-1 axis to play an antioxidant and anti-inflammatory role.
Improve the Assessment Model of Personnel Develop Level in Higher Education Based on Machine Learning
Authors: Zhu Rui , Li Yong
Published: October 2022

In order to improve the ability to manage the quality constraint index parameters of higher education talent training, an evaluation model of higher education talent training quality based on improved machine learning is proposed. Combined with the characteristic analysis method of higher education talent training quality constraint index parameters, an autocorrelation feature matching model of higher education talent training quality constraint index parameters is established, and fuzzy association rule scheduling is used to realize the feature extraction and fuzzy clustering of higher education talent training quality constraint index parameters. The mutual information coupling parameter analysis of the quality constraint index parameters of higher education talent training, combined with the generalized association rules and periodic association rules, realizes the feature clustering and global candidate item set analysis of the quality constraint index parameters of higher education talent training and realizes the dynamic evaluation of the quality of higher education talent training according to the machine learning analysis results. The test results show that this method has good clustering of data characteristics, good reliability of the evaluation process, and good convergence of machine learning process, which improves the dynamic and quantitative management ability of talent training quality in higher education.
[Retracted] Correlation Decomposition between TCM Syndrome Types and Calcium and Phosphorus Metabolism in 50 Maintenance Hemodialysis Sufferers
Authors: Li Yuanyuan
Published: October 2022

Aiming to reveal the relationship between TCM syndrome types and calcium and phosphorus metabolism in maintenance hemodialysis (MHD) sufferers, 50 sufferers diagnosed with MHD who were admitted to Suixi County Hospital in Anhui Province are selected for retrospective decomposition. The data of TCM classification and laboratory indicators of the sufferers are collected. The experimental results indicate that calcium and phosphorus metabolism disorder is common in maintenance hemodialysis patients, especially calcium and phosphorus product and blood phosphorus elevation. The increase of the calcium‐phosphorus product is closely related to the mortality and calcification rate of the subcutaneous soft tissue. It can provide a reference for the diagnosis and therapy of abnormal calcium and phosphorus metabolism in sufferers, which is worthy of clinical application.
Synchronous Optimization for Demand-Driven Train Operation Plan in Rail Transit Network Using Nondominated Sorting Coevolutionary Memetic Algorithm
Authors: Han Zhenyu , Li Dewei , Han Baoming , Gao Han
Published: October 2022

In many cities and regions, decision makers independently develop Train Operation Plan (TOP) for each line in the rail transit network, resulting in a lack of TOP Synchronization (TOPS). Considering the entire network as a whole, researchers have realized that synchronous optimization is of great significance. In this paper, we formulate two Mixed-Integer Linear Programming (MILP) models to optimize demand-driven TOP in the network. The former is an Asynchronous TOP Optimization (ATOPO) model, while the latter is a Synchronous TOP Optimization (STOPO) model. The bi-objective models simultaneously determine train frequency, train timetable, and rolling stock circulation under small-granularity passenger demand to minimize trains’ total cost and passengers’ total time. Then, we propose the Nondominated Sorting Coevolutionary Memetic Algorithm (NSCMA) to solve the combinatorial optimization problems. The hybrid heuristic algorithm incorporates Coevolutionary Memetic Algorithm (CMA) into Advanced and Adaptive Nondominated Sorting Genetic Algorithm II (AANSGA-II) to ameliorate the evolution process for elite individuals. On this basis, we study the case of Shenyang Metro to verify the models and the algorithm. The results demonstrate that the STOPO model is better than the ATOPO model in reducing trains’ total cost and passengers’ total time. In addition, NSCMA is better than AANSGA-II in obtaining elite individuals.
Switched Capacitor Based High Step-Up Multilevel Inverter with Self-Balancing Ability and Low Switching Stress
Authors: Venkatesan M. , Gouse Basha S. , Ramkumar A. , Manikandan R. , Easwaran M. , Khan Baseem
Published: October 2022

In this article, the switched capacitor (SC) based high step-up multilevel inverter is proposed with self-balancing capability. The proposed SC inverter topology is to step up the high output voltage from the very low input voltage without any bulky transformer. This proposed inverter generates single-phase AC voltage with a frequency of 50 Hz from a very low DC input voltage of 50 V with any intermediate DC-DC conversion stage. Hence, the proposed SC inverter is highly suitable for fuel cell, photovoltaic (PV) applications, and shunt active power filter (SAPF). To control the SC inverter, a multicarrier pulse width modulation (PWM) technique is engaged in the inverter. The high step-up voltage level can be achieved by the charging and discharging process of the SC. Furthermore, the stress voltage of the switches does not exceed the applied voltage and the total standing voltage of the inverter is greatly reduced without H-bridges. The comparative analysis of the proposed SC inverter is made for the components, peak inverse voltage (PIV), total standing voltage (TSV), boosting ability, and voltage balancing of capacitors. The main theme of the paper is producing a thirteen-level sinusoidal current with acceptable total harmonic distortion (THD) at different loads, low PIV, TSV, high boosting ability, and self-balancing of capacitors with fewer passive components. The whole system is examined by using MATLAB/Simulink.
Aortosternal Venous Compression: A Review of Two Cases
Authors: Giglio Victoria , Badar Zain , Bhogadi Yasovineeth , Van Adel Brian , Yip Gordon
Published: October 2022

Aortosternal venous compression (AVC) is a rare venous compression syndrome that involves brachiocephalic venous compression due to its positioning between the sternum and the aorta. One of the features of AVC involves compression of the left innominate vein with variability in luminal caliber on inspiration and expiration. Imaging modalities such as computed tomography (CT) examination can aid in initial diagnosis; however, venography can be utilized for confirmatory diagnosis due to its higher specificity during the inspiratory and expiratory phases. Through findings demonstrated during venography, we herein present two cases of confirmed AVC secondary to an aberrant right subclavian artery. Characteristic imaging features in the diagnosis of AVC and its etiology are discussed.
Giant Paratubal Cyst Mimicking Mesenteric Cyst
Authors: Almahmeed Ebrahim , Alshaibani Abdulaziz , Alhamad Hamad , Abualsel Abdulmenem
Published: October 2022

Paratubal cysts are adnexal masses located in the broad ligament; whenever the size of the cyst is >20 cm, it is considered a giant cyst and can present with complications including ovarian torsion and perforation. Diagnosis can be made clinically with the help of radiological investigations, although the gold standard diagnostic tool is diagnostic laparoscopy. Managing this condition relies mainly on surgical intervention (open or laparoscopic). Giant paratubal cysts carry challenges in their surgical excision as they carry a higher risk of spillage. We present a case of giant paratubal cyst in a 26-year-old Bahraini female who presented with abdominal distension and pain for 3 years.
Linking Psychological Ownership to Innovative Behaviour in the Workplace: Empirical Evidence from Complex Management Systems in Pakistan
Authors: Mahsud Minhas , Jinxing Hao , Mahsud Zafar , Chen Zhiqiang , Napari Hanifatu Mumuni
Published: October 2022

This research work investigates the association between psychological ownership and innovative behaviour with knowledge hiding and knowledge sharing as mediators. The latter variables are presented as focal antecedents of preventive and promotive psychological ownership. To conduct the study, a theoretical framework was proposed, and data was collected from professionals working in complex management systems in Pakistan. The analysis revealed that knowledge hiding and knowledge sharing can exist simultaneously, and psychological ownership can evoke both positive and negative feelings in employees, which poses a challenge for the management. The results illustrate that psychological ownership has significant associations with knowledge hiding, knowledge sharing, and innovative behaviour. Consequent theoretical contributions and important managerial implications are discussed at the end.
Removal of Cr(III) from Aqueous Solution Using Labeo rohita Chitosan-Based Composite
Authors: Bukhari Attaullah , Hassan Zeeshan , Atta Madiha , Nazir Arif , Aslam Farheen , Naouar Amani , Al-Fawzan Foziah F. , Alissa Siham A. , Iqbal Munawar , Ahmad Naveed
Published: October 2022

This study focusses on the synthesis of chitosan-cellulose composite membrane derived from Labeo rohita fish scales (FS) for the removal of Cr(III) from aqueous solution, while chromium is a serious threat to groundwater. Waste FS are valorized to chitosan by demineralization, deproteination, and deacetylation successively. Cellulose was extracted from sugarcane bagasse using acidic hydrolysis. Chitosan-based cellulose composite porous membrane was fabricated by evaporating solvent from polymer solution in petri dish. The impact of pH, contact time, and absorbent dosage on the removal of Cr(III) from an aqueous solution was investigated. Atomic absorption spectrophotometer was used to check the Cr(III). Results showed that chitosan comprising 85% degree of deacetylation was achieved by alkali treatment, while yield was 22%. FTIR analysis confirmed the chitosan and chitosan-cellulose-based composite membrane. Morphology studies showed that the cellulose was strongly staggered and due to the chitosan, the surface of cellulose became rougher, which is good to enhance the adsorption capacity. The maximum removal 57% of Cr(III) from aqueous solution was observed at pH 6 at 60 min and 50 mg dosage of adsorbent. The minimum removal (47%) of Cr (III) was found at pH 2. These results confer that Labeo rohita-based chitosan-cellulose composite membrane has great potential for the removal of metals from industrial effluents.
Carbetocin Controls Intraoperative Blood Loss and Thickness of Myometrium in Scar Uterus Cases
Authors: Sun Dongjing
Published: October 2022

Objective. To study the effect of carbetocin on intraoperative blood loss and thickness of myometrium during cesarean section with the scarred uterus at term pregnancy. Methods. Pregnant women with full-term gestational scar uterus who underwent cesarean section from March 1, 2021, to April 30, 2022, were retrospectively collected and divided into a reference group (using oxytocin) or a study group (using carbetocin). The clinical data of the two groups were retrospectively analyzed, and the operation time, intraoperative blood loss, hospital stay, uterine contraction effect, changes in the myometrium, and complications were compared between the two groups. Results. A total of 103 pregnant women were retrieved. There were 44 cases in the reference group and 59 cases in the study group. There were significant differences in operation time, intraoperative bleeding, hospital stay, postoperative adverse events, uterine fundus wall thickness, anterior wall thickness, posterior wall thickness, and uterine contraction effect between the two groups (

p
=
0.0001

, 0.005, 0.006, 0.001, 0.0004, 0.003, 0.001, and 0.005, respectively). There were no significant differences in estradiol (E2), luteinizing hormone (LH), or follicle-stimulating hormone (FSH) between the two groups before the surgery (

p
=
0.596

, 0.840, and 0.940, respectively), but there were significant differences after the surgery (

p
=
0.011

, 0.001, and 0.005, respectively). Conclusion. The use of carbetocin in the cesarean section of a full-term scar uterus is significantly effective in shortening the operation time, reducing the amount of intraoperative blood loss, and promoting the recovery of the uterus.
Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer
Authors: Wang Wenxuan , Wu Qinghui , Mohyeddin Ali , Liu Yousheng , Liu Zhitao , Ge Jianqiang , Zhang Bao , Shi Gan , Wang Weifu , Wu Dinglan , Wang Fei
Published: October 2022

Background. Prostate cancer (PCa) is a malignant tumor in males, with a majority of the cases advancing to metastatic castration resistance. Metastasis is the leading cause of mortality in PCa. The traditional early detection and prediction approaches cannot differentiate between the different stages of PCa. Therefore, new biomarkers are necessary for early detection and clear differentiation of PCa stages to provide precise therapeutic intervention. Methods. The objective of the study was to find significant differences in genes and combine the three GEO datasets with TCGA-PRAD datasets (DEG). Weighted gene coexpression network analysis (WGCNA) determined the gene set and PCa clinical feature correlation module utilizing the TGGA-PRAD clinical feature data. The correlation module genes were rescreened using the biological information analysis tools, with the three hub genes (TOP2A, NCAPG, and BUB1B) for proper verification. Finally, internal (TCGA) and external (GSE32571, GSE70770) validation datasets were used to validate and predict the value of last hub genes. Results. The hub gene was abnormally upregulated in PCa samples during verification. The expression of each gene was favorably connected with the Gleason score and TN tumor grade in clinical samples but negatively correlated with the overall survival rate. The expression of these genes was linked to CD8 naive cells and macrophages, among other cells. Antitumor immune cells like NK and NKT were favorably and adversely correlated with infiltrating cells, respectively. Simultaneously, the GSCV and GSEA indicated that the hub gene is connected with cell proliferation, death, and androgen receptor, among other signaling pathways. Therefore, these genes could influence the incidence and progression of PCa by participating in or modulating various signaling pathways. Furthermore, using the online tool of CMap, we examined the individual medications for Hughes and determined that tipifarnib could be useful for the clinical therapy of PCa. Conclusion. TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis. Moreover, these genes can provide a theoretical basis for precision differentiation and treatment of PCa.
[Retracted] The Expression of hnRNP A2/B1 in Benign and Malignant Lung Lesions and Its Early Diagnosis Value in NSCLC
Authors: Gu Wenchao , Gao Xiwen , Wang Linxun , Deng Guoping , Huang Jiaru , Yang Junxia , Liu Yuan , Liu Qun , Sang Hongyang
Published: October 2022

Lung cancer in its occurrence and development of different stages exist different biological behavior changes. This paper studies the expression of heterogeneous nuclear ribonucleoprotein (hnRNP) A2/B1 in benign and malignant lung lesions and its early diagnosis value of nonsmall‐cell lung cancer (NSCLC), aiming to provide reference for the early diagnosis and therapy of NSCLC. Some lung surgery specimens are selected from January 2021 to March 2022. All cases received no radiotherapy and chemotherapy before surgery, including 90 sufferers with benign lung lesions as the contrast set. hnRNP A2/B1 expressions are measured for comparison. The experimental results show that for lung cancer sufferers, the positive expression of hnRNP A2/B1 in their malignant lesion tissue is notoriously higher than that in their benign lesion tissue, and hnRNP A2/B1 is differently expressed in different differentiation and in different stages.
Machine Learning Approach: Prediction of Surface Roughness in Dry Turning Inconel 625
Authors: Rajesh A. S. , Prabhuswamy M. S. , Rudra Naik M.
Published: October 2022

Roughness is a prime parameter in any process/operation as it aids in confirming the quality status of the product. The insert and workpiece would develop a lot of friction and as a result, it generates heat in the cutting zone, which affects the machined surface. The speed, feed, and depth of cut were chosen as processing factors. L27 Orthogonal array is used based on the Taguchi technique. The regression analysis is used to develop an equation to predict the roughness. The impact of the processing factors on the machined surface is studied with help of ANOVA (Analysis of Variance). Furthermore, the estimation of surface roughness is carried out using a machine learning-based model-feed forward (nonlinear autoregressive network) NARX network, and the evaluated surface roughness is compared with the values predicted by the regression model and experimental results. The average percentage error observed with the predicted values by NARX is observed as 3.01%, which is lower than the average percentage error observed by the regression model 5.131%. Thus, this work provides the best machine learning approach to the prognosis of the roughness in dry turning of Inconel 625, which would save a lot of time and unnecessary wastage of the work material.
Semantic Sentiment Classification for COVID-19 Tweets Using Universal Sentence Encoder
Authors: Fattoh Ibrahim Eldesouky , Kamal Alsheref Fahad , Ead Waleed M. , Youssef Ahmed Mohamed
Published: October 2022

The spread of data on the web has increased in the last twenty years. One of the reasons is the appearance of social media. The data on social sites describe many real-life events in our daily lives. In the period of the COVID-19 pandemic, a lot of people and media organizations were writing and documenting their health status and the latest news about the coronavirus on social media. Using these tweets (sentiments) about the coronavirus and analyzing them in a computational model can help decision makers in measuring public opinion and yielding remarkable findings. In this research article, we introduce a deep learning sentiment analysis model based on Universal Sentence Encoder. The dataset used in this research was collected from Twitter, and it was classified as positive, neutral, and negative. The sentence embedding model determines the meaning of word sequences instead of individual words. The model divides the dataset into training and testing and depends on the sentence similarity in detecting sentiment class. The obtained accuracy results reached 78.062%, and this result outperforms many traditional ML classifiers based on TF-IDF applied on the same dataset and another model based on the CNN classifier.
Identification of the Novel Gene Markers Based on the Gene Profile among Different Severity of Obstructive Sleep Apnea
Authors: Ren Yi , Li Yanyan , Sui Xuemei , Yuan Jinhe , Lan Jun , Li Xiayu , Deng Yue , Xu Zhiping , Cheng Xiu , Zhao Changjing , Lu Junyu
Published: October 2022

Obstructive sleep apnea (OSA) is caused by repeated blockage of the upper respiratory airways during sleep. The traditional evaluation methods for OSA severity are yet limited. This study aimed to screen gene signatures to effectively evaluate OSA severity. Expression profiles of peripheral blood mononuclear cells in the different severities of OSA patients were accessed from Gene Expression Omnibus (GEO) database. A total of 446 differentially expressed genes (DEGs) were screened among the varying severities of OSA samples by analysis of variance (ANOVA) test. A total of 1,152 DEGs were screened between the pre- and post-treatment OSA samples by using

t
 

test. Overlap of the two groups of DEGs was selected (88 DEGs) for Metascape enrichment analysis. Afterwards, Mfuzz package was used to perform soft clustering analysis on these 88 genes, by which 6 clusters were obtained. It was observed that the gene expression condition of the cluster 3 was positively associated with OSA severity degree; also, the gene expression condition in cluster 4 was negatively correlated with OSA severity. A total of 10 gene markers related to OSA progression were selected from cluster 3 and cluster 4. Their expression levels and correlation were analyzed. The marker genes in cluster 3 and cluster 4 were examined, finding that most genes were significantly correlated with apnea hypopnea index (AHI). An accurate and objective assessment of the severity of OSA is of great significance for formulating follow-up treatment strategies for patients with OSA. In this paper, a set of marker genes that can detect the severity of OSA were screened by bioinformatics methods, which could be jointly used with the traditional OSA diagnostic index to achieve a more reliable OSA severity evaluation.
The Application of Interactive Effect Evaluation Model in the Teaching of College Mathematics Courses
Authors: Chen Jungang
Published: October 2022

Mathematics courses in higher education (advanced mathematics, linear algebra, etc.) are characterized by abstract concepts, many easily confused concepts, many nature theorems, and large amount of calculation of many difficulties. In most cases, due to the knowledge level, knowledge structure, and requirements of the teaching process, the traditional mathematics teaching adopts the straight-to-point approach to the introduction of mathematical concepts, and the explanation of property theorems mostly adopts the method of giving the theorems first and then analyzing and proving them for the calculation problems are mostly manual calculation. Educators are mainly concerned with how to organize teaching so that the trainees can acquire more knowledge, while ignoring the subject status of the trainees, and it is often related to the talents of higher education. The training goals are consistent. The traditional mathematics teaching only reflects a function of knowledge inheritance, but lacks the function of knowledge innovation. The lack of concept generation process in teaching makes the abstraction stronger; the lack of case analysis process makes the applicability weaken; and the serious separation of engineering problem solving and computer operation makes it lack of practicability. The current mathematics knowledge and curriculum make students in a passive position in the process of mastering basic knowledge. From the study about the present condition of the math education and the real requirement, the thesis will talk about content, characteristics, and the relationships for the practical education along with interactive teaching process. What is more, the ways of education and online education is able to be presented. At the same time, this paper also obtains the maximum weight value of each teaching quality evaluation index through analytic hierarchy process, introduces the quadratic fuzzy comprehensive calculation method of fuzzy operator, and determines the maximum component of the evaluation level as the final evaluation level according to the most subordinate degree criterion of fuzzy comprehensive evaluation. Especially in the formulation of teaching quality evaluation model in China, the qualitative description is processed quantitatively by the method of fuzzy mathematics and statistics, so that the qualitative index and the quantitative index are organically combined.
Plasma Methylated RNF180 for Noninvasive Diagnosis of Gastric Cancer
Authors: Zhao Luyao , Liu Yandi , Zhang Shiwu , Li Muran
Published: October 2022

Background. RNF180 is a tumor suppressor gene involved in cell development, proliferation, and apoptosis. Methylation of RNF180 (mRNF180) leads to low expression of RNF180, which is closely related to the occurrence and development of gastric cancer (GC). This study was designed to evaluate the potential performance of plasma mRNF180 as noninvasive biomarker for the diagnosis of GC. Methods. A total of 156 participants, including 60 patients with GC, 39 with chronic superficial gastritis (CSG), 27 with chronic atrophic gastritis (CAG), and 30 with gastric ulcer (GU) were recruited for this study. Plasma mRNF180 level was measured using real‐time polymerase chain reaction. Results. As a diagnostic target, mRNF180 had a sensitivity of 71.67% (95% CI: 58.36%–82.18%) and specificity of 59.38% (95% CI: 48.85%–69.14%). The area under the ROC curve value of mRNF180 was 0.731 (95% CI: 0.648%–0.813%) for differentiation of GC from benign gastric diseases (BGD). The effectiveness of mRNF180 was superior to that of CEA, CA199, and CA724. mRNF180 was positively correlated with age, tumor size, T stage, N stage, M stage, and clinical stage of patients with GC. Conclusions. Plasma mRNF180 might serve as a useful and noninvasive biomarker for the diagnosis of GC and can be used to evaluate its prognosis.
Technological Innovation, Emerging Industrial Agglomeration, and High-Quality Green Development
Authors: Cao Jialei , Liu Zhi , Xu Jun , Li Min
Published: October 2022

Exploring the transformation of the mode of economic growth has been widely concerned by researchers around the world, especially in the context of “dual carbon” goals. China’s economy is in a transition stage to high-quality green development (HGD), with technological innovation (TI) and emerging industrial agglomeration (EIA) as important drivers. However, existing studies lack a systematic empirical analysis on different dimensions of TI and its influence mechanism. In order to examine the mechanism of TI affecting HGD through EIA, this study uses the panel data in the western Yangtze River Delta of China from 2009 to 2019 to first comprehensively calculate the TI index, EIA index, and the HGD index as proxy variables for regional TI, EIA, and HGD, respectively, and then empirically examines the impact of TI on HGD and the heterogeneous impacts on HGD. Finally, we test the mediation effect of EIA between TI and HGD. The results show that TI effectively promotes regional HGD, and with the increase in the HGD index, the driving role of TI also increases. Technological innovation has heterogeneous impacts on HGD at different dimensions of innovation, time periods, and regions. Innovation output and diffusion have significant impacts on HGD, whereas innovation input and environment have insignificant impacts. The effects of TI promoting HGD are different before and after 2013. Additionally, the nexus between TI and HGD also differs across spatial distributions. The mediation effect indicates that EIA is an important mechanism for TI to release the dividends of HGD, and it explains approximately 29% of the conduction effect.
A Hybrid Deep Learning‐Based Network for Photovoltaic Power Forecasting
Authors: Hussain Altaf , Khan Zulfiqar Ahmad , Hussain Tanveer , Ullah Fath U Min , Rho Seungmin , Baik Sung Wook
Published: October 2022

For efficient energy distribution, microgrids (MG) provide significant assistance to main grids and act as a bridge between the power generation and consumption. Renewable energy generation resources, particularly photovoltaics (PVs), are considered as a clean source of energy but are highly complex, volatile, and intermittent in nature making their forecasting challenging. Thus, a reliable, optimized, and a robust forecasting method deployed at MG objectifies these challenges by providing accurate renewable energy production forecasting and establishing a precise power generation and consumption matching at MG. Furthermore, it ensures effective planning, operation, and acquisition from the main grid in the case of superior or inferior amounts of energy, respectively. Therefore, in this work, we develop an end‐to‐end hybrid network for automatic PV power forecasting, comprising three basic steps. Firstly, data preprocessing is performed to normalize, remove the outliers, and deal with the missing values prominently. Next, the temporal features are extracted using deep sequential modelling schemes, followed by the extraction of spatial features via convolutional neural networks. These features are then fed to fully connected layers for optimal PV power forecasting. In the third step, the proposed model is evaluated on publicly available PV power generation datasets, where its performance reveals lower error rates when compared to state‐of‐the‐art methods.
Strategies of Using Multimedia Technology to Optimize Music Classroom Teaching in Primary and Secondary Schools
Authors: Deng Yu
Published: October 2022

Information technology has entered every aspect of life. The music classroom is no exception for training music talents. The development of information technology has become an inevitable trend of social development. Not only the call of the era of computer multimedia teaching but also the music curriculum standard under the background of quality education has put forward high requirements for today’s computers. From this, we can realize that it is crucial to transform teaching concepts, actively practice and explore, and seek new teaching models. As the main auxiliary teaching method, multimedia technology is known and used by most primary and secondary schools, and is widely used in music classroom teaching. This paper deeply analyzes the role and position of multimedia in music teaching in junior high school music classroom teaching, compares multimedia technology with other educational technology means, and explains the advantages and limitations of the implementation of music classroom teaching assisted by multimedia educational technology means. At the same time, this paper turns the cognitive problem of selective attention into the problem of measuring the auditory attractiveness of objectively existing music parts. The specific process is as follows: first, on the CQT spectrum of real music audio, this paper uses the auditory cognitive model based on auditory saliency, and uses the Bayesian inference mechanism of time series to propose the calculation method of quantitative features of auditory saliency. Then, TANN network is used to identify multiple auditory significant subbands as candidate semitones, and a priori knowledge obtained from the generalized chord structure is introduced to standardize the chord like structure at each time in the candidate melody stream, which improves the accuracy of the melody stream’s description of the original music. Finally, according to the data analysis of teaching practice, the teaching objectives of “order” and “circulation” in social and natural life have been well realized through “rhythm” insight in this teaching practice unit.
[Retracted] Higher Education Environment Monitoring and Quality Assessment Model Using Big Data Analysis and Deep Learning
Authors: Wu Hanfei
Published: October 2022

A university exists to help students develop their skills. The goal of university development is to raise the standard of personnel training, and the core component of university development is teaching quality. Whether the level of practical training can as soon meet the requirements of enterprise employment. For responding to the demands of professions and occupations, it is essential. Teaching quality evaluation is a crucial cornerstone for ensuring the quality of instruction. Universities and colleges should therefore concentrate on evaluating instruction. Schools and colleges can more rapidly and thoroughly comprehend how their off‐campus cooperative adult education programmes are running while also enhancing the efficacy and impartiality of their quality assessment by utilising educational data mining and learning analysis technology. Currently, issues with backward evaluation instruments, a single evaluation topic, and easy evaluation methods exist when evaluating the quality of schooling. Big data technology is used to create a higher vocational education environment monitoring and quality evaluation system that offers new and varied approaches to evaluate teaching quality. The technique for evaluating the quality of schooling is expanded upon in this research using various big data mining technologies. The improved collaborative filtering algorithm’s mean absolute difference is approximately 18.23% when the data set is larger. In conclusion, when applied to big data sets, the technique in this work performs with greater accuracy than the conventional collaborative filtering algorithm. The scoring matrix becomes denser as there are more scoring items in the model. In turn, this results in a more accurate similarity calculation at the beginning of the programme, albeit the similarity calculation error increases as the scoring matrix becomes denser.
[Retracted] Effect of Carrying out Continuous Nursing Based on Mobile Platform on the Life of Children with Leukemia after Discharge from Hospital
Authors: Xu Lidan , Han Xueling , Li Ling
Published: October 2022

Objective. To analyze the effect of carrying out continuous nursing based on mobile platform on the life of children with leukemia after discharge. Methods. A total of 104 children diagnosed with leukemia admitted in Pediatric Internal Medicine, Hainan Provincial People’s Hospital, from September 2019 to August 2020 were randomly divided into two groups, observation group and control group, with 52 cases in each group. For the control group, routine follow‐up was used for continuous nursing after discharge from hospital, and the observation group was treated with continuous nursing based on mobile platform on the basis of routine follow‐up nursing after discharge from hospital. Results. When discharged from hospital, there was no significant difference in SDS and SAS scores between the two groups (P > 0.05). After 8 weeks of discharge, SDS and SAS scores in both groups were significantly decreased, and SDS and SAS scores in the observation group were significantly lower than those in the control group, with statistical significance (P < 0.05). After 8 weeks of discharge, the cancer‐related fatigue score of the observation group was significantly lower than that of the control group, and the difference was statistically significant (P < 0.05). When discharged from hospital, there was no significant difference in quality of life between two groups (P > 0.05). Eight weeks after discharge, the quality of life in both groups was significantly improved, and the quality of life in the observation group was significantly better than that in the control group; the difference was statistically significant (P < 0.05). The occurrence of adverse reactions in the observation group was significantly lower than that in the control group, and the difference was statistically significant (P < 0.05). Conclusion. After children with leukemia were discharged from hospital, medical staff used mobile platform to carry out continuous nursing for them, which could relieve the negative emotions of children, reduce the incidence of adverse reactions, and improve the quality of life. This kind of intervention had promotion value.
Modelling and Analysis of Surface Roughness Using the Cascade Forward Neural Network (CFNN) in Turning of Inconel 625
Authors: A. S. Rajesh , Prabhuswamy M. S. , Komalnu Raghavan Ishwarya
Published: October 2022

In this paper, the influence of process components on surface roughness in turning of Inconel 625 using cubic boron nitride (CBN) is studied. A predictive model is developed to forecast the surface roughness using the cascade forward neural network (CFNN). The experiments are designed based on Taguchi. L27 orthogonal array (OA) is used to perform the experimental trails by considering speed, feed, and depth of cut as input factors. Out of 27 experimental trails, 18 experiments are used for training and 9 experimental trails are used for testing. The developed predictive model by the CFNN is compared with regression model values. The average prediction error for surface roughness is 2.94% with R2 = 99.99% by the CFNN. The CFNN is known to be superior to predict the response with minimum of percentage error. The minimum and maximum roughness observed at trail 8 and trail 20 is noted, respectively, and the increases in roughness at experimental trail 8 is equal to 3.384 times higher than the roughness observed at experimental trail.20. The feed rate dominates effectively on the roughness rather than other factors. The consequences of process factors on surface roughness are studied with the help of ANOVA. This experimental study and developed model would be used for aero parts manufacturing to forecast the roughness accurately before to the actual experiment so that actual machining and material cost could be avoided.