bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Extraction Process of Methyl Eugenol and Asarinin in Asarum with Deep Eutectic Solvent Based on the Response Surface Methodology
Authors: Bao Huiwei , Xu Yang , Wang Yuejie , Zhang Tao , Wang Enpeng , Huang Xin , Chen Changbao , Liu Fangxin
Published: September 2021

To explore a green and efficient extraction technology for the extraction of active ingredients of Asarum, the deep eutectic solvent combined with ultrasonic was applied to compare the extraction efficiency of 10 kinds of deep eutectic solvents, taking the extraction rate of methyl eugenol and asarinin as indices. Single-factor experiments were adopted to investigate the influence of molar ratio, liquid-to-solid ratio, eddy time, ultrasonic time, and temperature of the deep eutectic solvent on the extraction rate of methyl eugenol and asarinin. Based on single-factor experiments, the surface response methodology was used to optimize the extraction process conditions. The results showed that the optimum extracting process conditions of methyl eugenol and asarinin in Asarum consisted of a ratio of choline chloride to glycerol of 1 : 3, a DES volume of 2 mL, an ultrasonic temperature of 60°C, an ultrasonic time of 30 min, and a vortex oscillation of 7 min. Under the optimum extracting process conditions, the contents of methyl eugenol and asarinin were 1.9428 mg/g and 0.9989 mg/g, respectively, and the comprehensive index was 2.3280 (RSD of 1.91%). The results were close to the predicted values of the response surface model, demonstrating the applicability of the model. The extraction rate of methyl eugenol and asarinin in Asarum by this method was higher than that of water extraction and alcohol extraction, which fully indicated the high efficiency of ultrasonic-assisted green deep eutectic solvent extraction technology. The results provide data support for further development and utilization of Asarum.
Deep Learning-Based Image Feature with Arthroscopy-Aided Early Diagnosis and Treatment of Meniscus Injury of Knee Joint
Authors: Li Zijian , Ren Shiyou , Zhang Xintao , Bai Lu , Jiang Changqing , Wu Jiangyi , Zhang Wentao
Published: September 2021

The aim of this study is to explore the clinical effect of deep learning-based MRI-assisted arthroscopy in the early treatment of knee meniscus sports injury. Based on convolutional neural network algorithm, Adam algorithm was introduced to optimize it, and the magnetic resonance imaging (MRI) image super-resolution reconstruction model (SRCNN) was established. Peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) were compared between SRCNN and other algorithms. Sixty patients with meniscus injury of knee joint were studied. Arthroscopic surgery was performed according to the patients’ actual type of injury, and knee scores were evaluated for all patients. Then, postoperative scores and MRI results were analyzed. The results showed that the PSNR and SSIM values of the SRCNN algorithm were (42.19 ± 4.37) dB and 0.9951, respectively, which were significantly higher than those of other algorithms (

P

 < 0.05). Among patients with meniscus injury, 17 cases (28.33%) were treated with meniscus suture, 39 cases (65.00%) underwent secondary resection, 3 cases (5.00%) underwent partial resection, and 1 case (1.67%) underwent full resection. After meniscus suture, secondary resection, partial resection, and total resection, the knee function scores of patients after treatment were (83.17 ± 8.63), (80.06 ± 7.96), (84.34 ± 7.74), and (85.52 ± 5.97), respectively. There was no great difference in knee function scores after different methods of treatment (

P

 > 0.05), and there were considerable differences compared with those before treatment (

P

 < 0.01). Compared with the results of arthroscopy, there was no significant difference in the grading of meniscus injury by MRI (

P

 > 0.05). To sum up, the SRCNN algorithm based on the deep convolutional network algorithm improved the MRI image quality and the diagnosis of knee meniscus injuries. Arthroscopic knee surgery had good results and had great clinical application and promotion value.
An Improved Social Force Model for Bicycle Flow in Groups
Authors: Rui Ying-Xu , Tang Tie-Qiao , Zhang Jian
Published: September 2021

Bicycle flow widely has group behavior (i.e., cyclists have a tendency to ride in groups), which may have some significant effects on the bicycle’s motion. However, the existing studies on bicycle flow rarely consider this factor. Generally, bicycle flow has two kinds of group behaviors, i.e., shoulder group behavior and following group behavior. In this paper, we propose an improved social force (SF) model to describe the two kinds of group behaviors. Then, we use the improved SF model to, respectively, explore the effects of the two kinds of group behaviors on the bicycle’s motion from the simulation perspective. The numerical results show that (i) shoulder group behavior has some negative impacts on the bicycle’s motion, i.e., the critical density (where the through capacity can reach the maximum value), the jam density, and the through capacity will be reduced; (ii) following group behavior has some positive impacts on the bicycle’s motion, i.e., the critical density, the jam density, and the through capacity will be enhanced; (iii) the impacts of coexistence of shoulder and following group behavior are related to the density. Besides, increasing group size and group probability will enlarge the negative impacts of shoulder group behavior and alleviate the positive impacts of following group behavior. These results can guide administrators to better manage bicycle flow (especially reasonably control the negative impacts of group behaviors).
Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis
Authors: Yan Liu , Xin Sun
Published: September 2021

In view of the intelligent demand of tennis line examination, this paper performs a systematic analysis on the intelligent recognition of tennis line examination. Then, a tennis line recognition method based on machine vision is proposed. In this paper, the color region of the image recognition region is divided based on the region growth, and the rough estimation of the court boundary is realized. In order to achieve the effect of camera calibration, a fast camera calibration method which can be used for a variety of court types is proposed. On the basis of camera calibration, a tennis line examination and segmentation system based on machine vision analysis is constructed, and the experimental results are verified by design experiments. The results show that the machine vision analysis‐based intelligent segmentation system of tennis line examination has high recognition accuracy and can meet the actual needs of tennis line examination.
Anisakis pegreffii Extract Induces Airway Inflammation with Airway Remodeling in a Murine Model System
Authors: Choi Jun Ho , Kim Ju Yeong , Yi Myung-hee , Kim Myungjun , Yong Tai-Soon
Published: September 2021

Exposure of the respiratory system to the Anisakis pegreffii L3 crude extract (AE) induces airway inflammation; however, the mechanism underlying this inflammatory response remains unknown. AE contains allergens that promote allergic inflammation; exposure to AE may potentially lead to asthma. In this study, we aimed to establish a murine model to assess the effects of AE on characteristic features of chronic asthma, including airway hypersensitivity (AHR), airway inflammation, and airway remodeling. Mice were sensitized for five consecutive days each week for 4 weeks. AHR, lung inflammation, and airway remodeling were evaluated 24 h after the last exposure. Lung inflammation and airway remodeling were assessed from the bronchoalveolar lavage fluid (BALF). To confirm the immune response in the lungs, changes in gene expression in the lung tissue were assessed with reverse transcription‐quantitative PCR. The levels of IgE, IgG1, and IgG2a in blood and cytokine levels in the BALF, splenocyte, and lung lymph node (LLN) culture supernatant were measured with ELISA. An increase in AHR was prominently observed in AE‐exposed mice. Epithelial proliferation and infiltration of inflammatory cells were observed in the BALF and lung tissue sections. Collagen deposition was detected in lung tissues. AE exposure increased IL-4, IL-5, and IL-13 expression in the lung, as well as the levels of antibodies specific to AE. IL‐4, IL‐5, and IL‐13 were upregulated only in LLN. These findings indicate that an increase in IL‐4+ CD4+ T cells in the LLN and splenocyte resulted in increased Th2 response to AE exposure. Exposure of the respiratory system to AE resulted in an increased allergen‐induced Th2 inflammatory response and AHR through accumulation of inflammatory and IL‐4+ CD4+ T cells and collagen deposition. It was confirmed that A. pegreffii plays an essential role in causing asthma in mouse models and has the potential to cause similar effects in humans.
Study of Scraping with Copper Stone Based on Theory of Midnight-Noon Ebb-Flow in Angina Pectoris with Coronary Heart Disease of Qi Stagnation and Blood Stasis
Authors: Tang Xianwen , Yang Jinguo , Feng Zhong , Piao Jingyu , Yan Quanhao , Gao Chao
Published: September 2021

Angina pectoris (AP) with coronary heart disease (CHD) is one of the common cardiovascular diseases in clinical practice, which can be classified as “chest paralysis” in Chinese medicine according to its symptoms, and it is described in many ancient documents. Ancient Chinese medicine believes that the main pathogenesis of the disease is poor blood flow leading to paralysis of the heart and veins, so it is often treated by activating blood and removing blood stasis. In this study, 120 patients with AP of CHD of Qi stagnation and blood stasis type were randomly divided into the observation (n = 60) and the control group (n = 60). In the control group, basic care, conventional treatment, and unselected copper acupuncture scraping were used, while in the observation group, copper acupuncture scraping was performed at the right time of the heart meridian (11 : 00–13 : 00) on the basis of the control group, and all patients received the treatment for a total duration of 4 weeks. We collected data on the traditional Chinese medical (TCM) syndrome score, frequency and duration of angina attacks, nitroglycerin dosage, inflammatory factor levels, and hematological indices pretreatment and posttreatment in both groups. Patients’ adverse effects during treatment were recorded, and the clinical efficacy and ECG efficacy in both groups were evaluated after 4 weeks. We used SPSS.20 statistical software to statistically analyze the above data, and the results showed that the clinical efficacy and ECG efficacy of the observation group were significantly higher than the control group posttreatment. After treatment, the TCM symptom score, angina attack frequency, attack duration and nitroglycerin dosage, serum interleukin-8 (IL-8), hypersensitive C-reactive protein (hs-CRP), and tumor necrosis factor-α (TNF-α) levels, whole blood viscosity (WBV), plasma viscosity (PV), fibrinogen (FIB), and hematocrit (Hct) were significantly lower in both groups compared with those posttreatment. And the observation group showed a greater decrease when compared with the control group. The results also showed that the overall incidence of adverse reactions was lower in both groups during the treatment period. The above results indicate that while ensuring high safety, the copper stone based on theory of midnight-noon ebb-flow can more effectively improve the symptoms and inflammatory response of the body and reduce the viscosity of the blood in AP with CHD of Qi stagnation and blood stasis, and it has better therapeutic effects.
Comparison of the Initiation Time of Enteral Nutrition for Critically Ill Patients: At Admission vs. 24 to 48 Hours after Admission
Authors: Yu Anshan , Xie Yanmei , Zhong Meixin , Wang Fen , Huang Huachun , Nie Liang , Liu Xiaofeng , Xiao Mingfang , Zhu Hongquan
Published: September 2021

Objective. To investigate the better time of initiation of enteral nutrition for critically ill patients, such as at admission or 24 to 48 hours after admission. Methods. This was a prospective, randomized, parallel-controlled, single-blind, interventional clinical trial. A total of 100 patients admitted to the intensive care unit (ICU) of our hospital between January 2017 and December 2018 were recruited in this study. These patients had been divided into the control group or intervention group by a computer-generated random number table, and each group had 50 patients. For the control group, a gastric tube was inserted to start enteral nutrition at 24 to 48 hours after admission. For the intervention group, a nasojejunal tube was placed to start enteral nutrition at admission. The main endpoints included serum albumin and prealbumin at admission and on days 3, 7, and 14 after admission, length of ICU stay, ventilator time, and complications such as diarrhea, gastric retention, esophageal reflux, and pulmonary infection. Results. The results showed that serum albumin and prealbumin were significantly higher in the intervention group than in the control group (

P

 < 0.05). The length of ICU stay (

P

 < 0.05) and ventilator time (

P

 < 0.05) were both significantly shorter in the intervention group than in the control group. The incidences of gastric retention, esophageal reflux, and pulmonary infection were significantly lower in the intervention group than those in the control group (

P

 < 0.05). Conclusion. In the absence of contraindications, enteral nutrition can be initiated immediately after admission to the ICU (within 6 hours), and feeding nasojejunal tube is recommended. It can improve the nutritional status and prognosis of critical patients, improve the feeding effect, shorten the length of stay in the ICU and the use of the ventilator, and reduce the incidence of complications.
Effects of GLP‐1 Receptor Agonists on Bone Mineral Density in Patients with Type 2 Diabetes Mellitus: A 52‐Week Clinical Study
Authors: Cai Ting-ting , Li Hui-qin , Jiang Lan-lan , Wang Hui-ying , Luo Meng-hui , Su Xiao-fei , Ma Jian-hua
Published: September 2021

Introduction. Hypoglycemic drugs affect the bone quality and the risk of fractures in patients with type 2 diabetes mellitus (T2DM). We aimed to investigate the effects of glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) and insulin on bone mineral density (BMD) in T2DM. Methods. In this single‐blinded study, a total of 65 patients with T2DM were randomly assigned into four groups for 52 weeks: the exenatide group (n = 19), dulaglutide group (n = 19), insulin glargine group (n = 10), and placebo (n = 17). General clinical data were collected, and BMD was measured by dual‐energy X‐ray absorptiometry. Results. Compared with baseline, the glycosylated hemoglobin (HbA1c) decreased significantly in the exenatide (8.11 ± 0.24% vs. 7.40 ± 0.16%, P = 0.007), dulaglutide (8.77 ± 0.37% vs. 7.06 ± 0.28%, P < 0.001), and insulin glargine (8.57 ± 0.24% vs. 7.23 ± 0.25%, P < 0.001) groups after treatment. In the exenatide group, the BMD of the total hip increased. In the dulaglutide group, only the BMD of the femoral neck decreased (P = 0.027), but the magnitude of decrease was less than that in the placebo group; the BMD of L1‐L4, femoral neck, and total hip decreased significantly (P < 0.05) in the placebo group, while in the insulin glargine group, the BMD of L2, L4, and L1‐4 increased (P < 0.05). Compared with the placebo group, the BMD of the femoral neck and total hip in the exenatide group and the insulin glargine group were increased significantly (P < 0.05); compared with the exenatide group, the BMD of L4 in the insulin glargine group was also increased (P = 0.001). Conclusions. Compared with the placebo, GLP‐1RAs demonstrated an increase of BMD at multiple sites of the body after treatment, which may not exacerbate the consequences of bone fragility. Therefore, GLP‐1RAs might be considered for patients with T2DM. This trial is registered with ClinicalTrials.gov NCT01648582.
Analytical versus Metaheuristic Methods to Extract the Photovoltaic Cells and Panel Parameters
Authors: Cotfas Daniel T. , Cotfas Petru A. , Oproiu Mihai P. , Ostafe Paul A.
Published: September 2021

The parameters of the photovoltaic cells and panels are very important to forecast the power generated. There are a lot of methods to extract the parameters using analytical, metaheuristic, and hybrid algorithms. The comparison between the widely used analytical method and some of the best metaheuristic algorithms from the algorithm families is made for datasets from the specialized literature, using the following statistical tests: absolute error, root mean square error, and the coefficient of determination. The equivalent circuit and mathematical model considered is the single diode model. The result comparison shows that the metaheuristic algorithms have the best performance in almost all cases, and only for the genetic algorithm, there are poorer results for one chosen photovoltaic cell. The parameters of the photovoltaic cells and panels and also the current-voltage characteristic for real outdoor weather conditions are forecasted using the parameters calculated with the best method: one for analytical—the five-parameter analytical method—and one for the metaheuristic algorithms—hybrid successive discretization algorithm. Additionally, the genetic algorithm is used. The forecast current-voltage characteristic is compared with the one measured in real sunlight conditions, and the best results are obtained in the case of a hybrid successive discretization algorithm. The maximum power forecast using the calculated parameters with the five-parameter method is the best, and the error in comparison with the measured ones is 0.48%.
Identification of Psychological Crisis Signals of College Students Based on the Dufferin Equation
Authors: Zhao Jianping , Song Haitao
Published: September 2021

This paper presents an in-depth analysis and research on the identification of psychological crisis signals of college students using the optimized Dufferin equation. The early warning index system of college students’ psychological crisis was established and tested on 300 junior college students, and the early warning system of college students’ psychological crisis was established by using structural equation model, focusing on the mediating effect of coping mode between stress source and stress response and the mediating effect of stress source between social support and stress response. At the same time, the characteristics of psychological crises among college students of different genders and grades were compared and analyzed. To address the shortcomings of the classical Dufferin equation with limited noise immunity, the use of a higher-order double-coupled Dufferin system was further improved. A detection model based on the higher-order double-coupled system was established, and its feasibility was verified by the psychological crisis signal. The geometric features of the phase trajectory are adopted as the basis for judging the system state, which greatly reduces the computational effort. Based on defining the conceptual connotation of college students’ psychological crisis behavior system, the vulnerability of college students’ psychological crisis behavior system is interpreted from the perspective of system self-organization theory, and the vulnerability of college students’ psychological crisis behavior is mainly expressed in latent and manifest states, and its vulnerability transformation is a self-organization process. A questionnaire survey was conducted for ordinary college students to examine the performance of college students’ vulnerability state of the subject who endured college students’ psychological crisis behavior, and it was concluded that most college students appear to be normal and healthy on the surface, but college students’ vulnerability is in an uncertain state of intermediate transition.
[Retracted] Automatic Parking System Based on Improved Neural Network Algorithm and Intelligent Image Analysis
Authors: Guo Yucheng , Shi Hongtao
Published: September 2021

This research designs an intelligent parking system including service application layer, perception layer, data analysis layer, and management layer. The network system adopts opm15 system, and the parking space recognition adopts improved convolution neural networks (CNNs) algorithm and image recognition technology. Firstly, the parking space is occupied and located, and the shortest path (Dynamic Programming, DP) is selected. In order to describe the path algorithm, the parking system model is established. Aiming at the problems of DP low power and adjacent path interference in the path detection system, a method of combining interference elimination technology with enhanced detector technology is proposed to effectively eliminate the interference path signal and improve the performance of the intelligent parking system. In order to verify whether the CNNs system designed in this study has advantages, the simulation experiments of CNNs, ZigBee, and manual parking are carried out. The results show that the parking system designed in this study can control the parking error, has smaller parking error than ZigBee, and has more than 25.64% less parking time than ZigBee, and more than 34.83% less time than manual parking. In terms of parking energy consumption, when there are less free parking spaces, CNNs have lower energy consumption.
A Weakly Supervised Academic Search Model Based on Knowledge‐Enhanced Feature Representation
Authors: Xu Mingying , Du Junping , Kou Feifei , Liang Meiyu , Xu Xin , Yang Jiaxin
Published: September 2021

Internet of Things search has great potential applications with the rapid development of Internet of Things technology. Combining Internet of Things technology and academic search to build academic search framework based on Internet of Things is an effective solution to realize massive academic resource search. Recently, the academic big data has been characterized by a large number of types and spanning many fields. The traditional web search technology is no longer suitable for the search environment of academic big data. Thus, this paper designs academic search framework based on Internet of Things Technology. In order to alleviate the pressure of the cloud server processing massive academic big data, the edge server is introduced to clean and remove the redundancy of the data to form a clean data for further analysis and processing by the cloud server. Edge computing network effectively makes up for the deficiency of cloud computing in the conditions of distributed and high concurrent access, reduces long‐distance data transmission, and improves the quality of network user experience. For Academic Search, this paper proposes a novel weakly supervised academic search model based on knowledge‐enhanced feature representation. The proposed model can relieve high cost of acquisition of manually labeled data by obtaining a lot of pseudolabeled data and consider word‐level interactive matching and sentence‐level semantic matching for more accurate matching in the process of academic search. The experimental result on academic datasets demonstrate that the performance of the proposed model is much better than that of the existing methods.
A Scoping Review of Text-Matching Software Used for Student Academic Integrity in Higher Education
Authors: Hayden K. Alix , Eaton Sarah Elaine , Pethrick Helen , Crossman Katherine , Lenart Bartlomiej A. , Penaluna Lee-Ann
Published: September 2021

Text-matching software has been used widely in higher education to reduce student plagiarism and support the development of students’ writing skills. This scoping review provides insights into the extant literature relating to commercial text-matching software (TMS) (e.g., Turnitin) use in postsecondary institutions. Our primary research question was “How is text-matching software used in postsecondary contexts?” Using a scoping review method, we searched 14 databases to find peer-reviewed literature about the use of TMS among postsecondary students. In total, 129 articles were included in the final synthesis, which comprised of data extraction, quality appraisal, and the identification of exemplar articles. We highlight evidence about how TMS is used for teaching and learning purposes to support student success at the undergraduate and graduate levels.
Alignment Method of Combined Perception for Peg‐in‐Hole Assembly with Deep Reinforcement Learning
Authors: Wang Yongzhi , Zhao Lei , Zhang Qian , Zhou Ran , Wu Liping , Ma Junqiao , Zhang Bo , Zhang Yu
Published: September 2021

The method of tactile perception can accurately reflect the contact state by collecting force and torque information, but it is not sensitive to the changes in position and posture between assembly objects. The method of visual perception is very sensitive to changes in pose and posture between assembled objects, but they cannot accurately reflect the contact state, especially since the objects are occluded from each other. The robot will perceive the environment more accurately if visual and tactile perception can be combined. Therefore, this paper proposes the alignment method of combined perception for the peg‐in‐hole assembly with self‐supervised deep reinforcement learning. The agent first observes the environment through visual sensors and then predicts the action of the alignment adjustment based on the visual feature of the contact state. Subsequently, the agent judges the contact state based on the force and torque information collected by the force/torque sensor. And the action of the alignment adjustment is selected according to the contact state and used as a visual prediction label. Whereafter, the network of visual perception performs backpropagation to correct the network weights according to the visual prediction label. Finally, the agent will have learned the alignment skill of combined perception with the increase of iterative training. The robot system is built based on CoppeliaSim for simulation training and testing. The simulation results show that the method of combined perception has higher assembly efficiency than single perception.
Analysis for Flow of an Incompressible Brinkman-Type Fluid in Thin Medium with Friction
Authors: Manaa Soumia , Boulaaras Salah , Benseridi Hamid , Dilmi Mourad , Alodhaibi Sultan
Published: September 2021

In this paper, we consider the Brinkman equation in the three-dimensional thin domain

ℚ

ε

⊂

ℝ

3

. The purpose of this paper is to evaluate the asymptotic convergence of a fluid flow in a stationary regime. Firstly, we expose the variational formulation of the posed problem. Then, we presented the problem in transpose form and prove different inequalities for the solution

u

ε

,

p

ε

independently of the parameter

ε

. Finally, these estimates allow us to have the limit problem and the Reynolds equation and establish the uniqueness of the solution.
Prevalence and Risk Factors Associated with Intestinal Parasitic Infection among Primary School Children in Dera District, Northwest Ethiopia
Authors: Tegen Dires , Damtie Destaw
Published: September 2021

Background. Globally, over 600 million school children are living with intestinal parasites. The prevalence of intestinal parasitic infections (IPIs) among school children in Ethiopia and the Amhara region is 52% and 51%, respectively. The present study aimed to determine the prevalence and associated risk factors of IPIs among primary school children in Dera district, Northwest Ethiopia. Methods. A school-based cross-sectional study was conducted from December 2019 to February 2020. The study used a structured pretested questionnaire and stool tests to obtain epidemiological and disease data. Data were analyzed using appropriate univariate and multivariable logistic regression methods by statistical package for social science (SPSS) version 25.0. Results. Of the 382 students who were examined for IPIs, 238 (62.3%) (61.8% males, 62.8% females) were positive for one or more IPIs. One hundred thirty-six (35.6%), 98 (25.7%), and 4 (1.05%) were single, double, and triple infections, respectively. Out of the nine species of IPIs detected, Entamoeba sp. was the predominant species (29.6%) followed by hookworm (21.7%), Schistosoma mansoni (11.3%), Taenia sp. (9.2%), Giardia lamblia (5.2%), and Ascaris lumbricoides, Hymenolepis nana, and Enterobius vermicularis (4.2%) each, and Trichuris trichiura (0.5%). Family size greater than five (AOR = 1.8; 95% CI: 1.004, 3.13), open field school waste disposal (AOR = 15.88; 95% CI: 1.91, 132.1), and lack of knowledge about intestinal parasitic infection (AOR = 1.8; 95% CI: 1.1, 3.2) were the independent risk factors associated with the overall prevalence of IPIs. Conclusions. The prevalence of intestinal parasitic infection was high in the Dera district. Health education, extending school-based deworming, and mass treatments are recommended.
Intrahemispheric EEG: A New Perspective for Quantitative EEG Assessment in Poststroke Individuals
Authors: Brito Rodrigo , Baltar Adriana , Berenguer-Rocha Marina , Shirahige Lívia , Rocha Sérgio , Fonseca André , Piscitelli Daniele , Monte-Silva Kátia
Published: September 2021

The ratio between slower and faster frequencies of brain activity may change after stroke. However, few studies have used quantitative electroencephalography (qEEG) index of ratios between slower and faster frequencies such as the delta/alpha ratio (DAR) and the power ratio index (PRI;

delta
+
theta
/
alpha
+
beta

) for investigating the difference between the affected and unaffected hemisphere poststroke. Here, we proposed a new perspective for analyzing DAR and PRI within each hemisphere and investigated the motor impairment-related interhemispheric frequency oscillations. Forty-seven poststroke subjects and twelve healthy controls were included in the study. Severity of upper limb motor impairment was classified according to the Fugl–Meyer assessment in mild/moderate (

n
=
25

) and severe (

n
=
22

). The qEEG indexes (PRI and DAR) were computed for each hemisphere (intrahemispheric index) and for both hemispheres (cerebral index). Considering the cerebral index (DAR and PRI), our results showed a slowing in brain activity in poststroke patients when compared to healthy controls. Only the intrahemispheric PRI index was able to find significant interhemispheric differences of frequency oscillations. Despite being unable to detect interhemispheric differences, the DAR index seems to be more sensitive to detect motor impairment-related frequency oscillations. The intrahemispheric PRI index may provide insights into therapeutic approaches for interhemispheric asymmetry after stroke.
Data Analysis of Athletes’ Physiological Indexes in Training and Competition Based on Wireless Sensor Network
Authors: Liu Hairen , Zhang Wei
Published: September 2021

The application of physiological and biochemical indicators in athlete training and competition has become a hot research topic in related fields at home and abroad. Both coaches and scientific researchers hope to use quantitative physiological and biochemical indicators to study the load, fatigue, and recovery of athletes in training competitions and use them to scientifically guide athletes in training competitions, improve sports performance, and reduce injuries. This article introduces in detail the development status of wireless sensor network technology, energy consumption detection system, and ZigBee technology. On this basis, the focus is on the design of the detection terminal (coordinator and router node), the routing protocol of the ZigBee network, and the algorithm for the detection of human energy consumption. This subject proposes a design plan for the human exercise energy consumption detection system and researches and designs the wireless sensor network coordinator, router node, and host computer monitoring system. The microprocessors of the two types of network nodes use the single‐chip microcomputer. Among them, the router node is composed of sensor modules, data transmission modules, and power modules; the software part is transplanted to ZigBee protocol Z‐Stack, combined with the routing algorithm, and we add the corresponding node function code to achieve them. Based on the introduction of the development status and development points of the single‐chip‐based motion wireless sensor, this article focuses on the analysis of the single‐chip‐based motion wireless sensor network products. The common features of the single‐chip microcomputer are wireless, huge low power consumption, and simple development. Engineering practice shows that the designed system is relatively good in terms of reliability and stability of data transmission; even in the case of severe noise interference and electromagnetic interference, the probability of network nodes malfunctioning is still very small. The router node processes and analyzes the collected motion data, calculates the energy consumption and motion state of human motion based on the acceleration value of each axis and extracts data characteristics, and transmits the obtained results to the coordinator for real‐time display.
Application of Adaptive Virtual Reality with AI-Enabled Techniques in Modern Sports Training
Authors: Zhang Yajun , Tsai Sang-Bing
Published: September 2021

Virtual reality technology has many characteristics, such as high immersion, dynamic interactive response, and multidimensional information digitization. These characteristics are needed by the combination of modern sports development and scientific and technological progress. The introduction of virtual reality technology into the field of sports will be conducive to the scientific training of sports competition and the digital research of technical theory and to the rapid development of modern sports. This paper constructs the framework of sports training based on virtual reality technology and designs a motion capture data algorithm based on behavior string, which successfully improves the advantages of virtual reality technology. In addition, the training experiment method is used to verify the effectiveness and superiority of the system, focusing on the high-school students learning tennis for the first time as the experimental object to study the differences in training effects between the traditional training method and the training method using virtual reality technology. The training effect of tennis is better than the traditional training method, and the difference is significant; the internal motivation of training psychology is better than the traditional training method, and the difference is significant. Compared with the traditional training method, this training method can stimulate students’ interest in training, improve students’ training effect, and promote students’ psychological internal motivation to continue training. This study provides useful enlightenment for the further application of virtual reality technology and in the modern sports training for various sports events.
Deep Learning Approach in DOA Estimation: A Systematic Literature Review
Authors: Ge Shengguo , Li Kuo , Rum Siti Nurulain Binti Mohd
Published: September 2021

In array signal processing, the direction of arrival (DOA) of the signal source has drawn broad research interests with its wide applications in fields such as sonar, radar, communications, medical detection, and electronic countermeasures. In recent years, the application of deep learning (DL) to DOA estimation has achieved great success. This study provides a systematic review of research on DOA estimation using deep neural network methods. We manually selected twenty-five papers related to this research from five prominent databases (SpringerLink, IEEE Xplore, ScienceDirect, Scopus, and Google Scholar) for exploration. Six questions describing the overall trend of DOA estimation using deep learning are put forward. Then, we answered these questions by reviewing the literature. This review is helpful for researchers in this field because it provides more specific and comprehensive information needed for future research. Specifically, we first analyzed the background of the selected papers, including the type of publication, the number of citations, and the country of origin. Then, the DL technology used in DOA estimation is systematically analyzed, including the purpose of using DL in DOA estimation, various DL models (convolutional neural network, deep neural network, and combination network), and various DOA estimation schemes. Finally, various evaluation criteria (root-mean-squared error, accuracy, and mean absolute error) are used to evaluate the DL technology in DOA estimation, and various factors (signal-to-noise ratio, number of snapshots, number of antennas, and number of signal sources) affecting DOA estimation are analyzed. Based on our findings, we believe that deep learning can perform DOA estimation well, and there is still room for improvement in deep learning technology. In this study, the factors affecting DOA estimation can be used as the direction for researchers to conduct in-depth research.
Single-Valued Neutro Hyper BCK-Subalgebras
Authors: Hamidi M. , Smarandache F.
Published: September 2021

The purpose of this paper is to introduce the notation of single-valued neutrosophic hyper BCK-subalgebras and a novel concept of neutro hyper BCK-algebras as a generalization and alternative of hyper BCK-algebras, that have a larger applicable field. In order to realize the article’s goals, we construct single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras on a given nonempty set. The result of the research is the generalization of single-valued neutrosophic BCK-subalgebras and neutro BCK-algebras to single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras, respectively. Also, some results are obtained between extended (extendable) single-valued neutrosophic BCK-subalgebras and single-valued neutrosophic hyper BCK-subalgebras via fundamental relation. The paper includes implications for the development of single-valued neutrosophic BCK-subalgebras and neutro BCK-algebras and for modelling the uncertainty problems by single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras. The new conception of single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras was given for the first time in this paper. We find a method that can apply these concepts in some complex networks.
Osteogenic Activity of Lupeol Isolated from Clinacanthus nutans Lindau: Activity and Mode of Action
Authors: Nguyen Minh T. H. , Ngo Quang V. , Nguyen Huyen T. T. , Pham Quan M. , Dinh Trang H. , Nguyen Huong T. T. , V. Tinh Nguyen , Nguyen Phuong T. M.
Published: September 2021

Clinacanthus nutans Lindau has been traditionally used for healing of bone fragility, but the mechanism of actions has not been clarified yet. In this study, the bone regeneration activity of lupeol derived from C. nutans was assessed using an in vitro model of osteoblast cells MC3T3-E1. The finding revealed that the compound was not significantly toxic to osteoblast cells at concentration of ≤40 μg/mL. Lupeol demonstrated the osteogenic activity through enhancement of alkaline phosphatase (ALP) of osteoblast cells up to 31.2%, 21%, and 12% at concentrations of 5, 10, and 20 µg/mL, respectively (

p

 < 0.05). Besides, the mineralization activity was increased up to 170, 230, 185, and 117% at concentration of 5, 10, 20, and 40 μg/mL, respectively (

p

 < 0.05). The marker genes related to osteoblast differentiation evaluated on the expression level in the presence of lupeol, including collagen I (col 1), osteopontin (opn), osterix (osx), and runx2, showed upregulated expression in all the test genes (

p

 < 0.05). The Western blot analysis demonstrated a clear effect of lupeol on expression of p38/p-p38, and ERK/p-ERK proteins involved in the MAPK signaling pathway. Thus, lupeol isolated from C. nutans exhibited the osteogenic activity by enhancing expression of important markers of osteogenesis, as well as affected the MAPK signaling pathway relating to osteoblast differentiation. This is the first report on the detailed mechanism of action of lupeol on bone regeneration and also explains for the traditional use of this medicinal plant for bone healing.
The Effect of Pulmonary Rehabilitation on Respiratory Functions, and the Quality of Life, following Coronary Artery Bypass Grafting: A Randomised Controlled Study
Authors: Girgin Zümrüt , Ciğerci Yeliz , Yaman Fatıma
Published: September 2021

Objective. Examining the effects of a pulmonary rehabilitation (PR) program applied to patients undergoing coronary artery bypass grafting (CABG) surgery with open heart technique on respiratory functions, functional capacity, and quality of life (QoL). Design. This randomised controlled study applied the Consolidated Standards of Reporting Trials statement. Methods. The study was conducted with two groups: the intervention group (n = 25) and the control group (n = 25). The control group received standard care after coronary artery bypass grafting. On the contrary, the experimental group participated in a PR program created by the researchers in addition to standard care. After coronary artery bypass grafting, the respiratory functions (on the 4th day of clinical care) and QoL (at the 6th week) of both groups were evaluated. The primary outcome measure was the respiratory function (forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC). The secondary outcome measure of this study was the QoL. Results. When the average pulmonary function test values of the patients were examined, the mean FVC and FEV1 values of the patients in the intervention group on the 4th day of clinical care were significantly higher with a medium level size effect than the control group (p = 0.027; effect size (d) = 0.643; p < 0.024; effect size (d) = 0.658, respectively). At the postoperative 6th week measurement of QoL, a decrease was observed in all subdimensions of the scale, albeit less in the intervention group (p < 0.05). There was a decrease in both the mental and physical component summary of QoL (p < 0.05). Conclusion. The results of this study revealed that pulmonary rehabilitation applied to patients who have undergone coronary artery bypass graft recover their functional capacity faster.
Influence of Soybean Oil on Binder and Warm Mixture Asphalt Properties
Authors: Babagoli Rezvan , Ameli Alireza
Published: September 2021

To produce a usual hot mix asphalt, significant amount of energy is used, which causes air pollution. As a result, warm mix asphalt (WMA) is introduced to reduce the mixing and compaction temperature of the mixture. On the one hand, accumulation of waste oil in the ground occupies a large space in the Earth. After the process of frying the oil, if the by‐product is not controlled properly, it leads to the pollution of the environment. Hence, utilization of this waste oil can be considered as a sustainable path to dealing with the risk. The main goal of the current research is to evaluate the possibility of exploiting soybean oil to reduce the mixing and compaction temperature of mixtures and produce warm mix asphalt (WMA). Moreover, the rheological and performance properties of mixtures containing soybean are evaluated in this study. The AC‐60/70 and 85/100 binders are modified by soybean oil (0%, 1.5%, 2.5%, and 3.5% by weight of binder). Several binder tests are used to measure the physical and rheological behaviors of binders, such as penetration grade, softening point, temperature susceptibility, rotational viscosity (RV), Multiple Stress Creep Recovery (MSCR), and Linear Amplitude Sweep (LAS) tests. Besides, several mixture tests are used to evaluate the performance of the mixture, including four‐point bending beam fatigue (FPB), resilient modulus (Mr), indirect tensile strength (ITS), dynamic creep, and wheel track tests. Through MSCR test results, at two stress levels, the Jnr parameter increases as the soybean oil is added to the binder. The results of the LAS test revealed that the fatigue life of binders increases by addition of soybean oil. There is no significant difference between the results of new and waste oil. This in turn makes possible reducing soybean oil production and consumption, and instead frying oil (waste) is reused, which displays no significant difference in terms of chemical and physical properties. Also, the performance test of mixtures indicated that as the soybean oil is added to the mixture, the rutting performance decreases and fatigue performance increases. Based on the results, it is recommended to use 1.5% soybean oil in asphalt mixtures without compromising the performance of the mixture. ANOVA results showed that the warm additive had meaningful effects on MR, ITS, and FE; the same was true for the effects of the warm additive‐binder type interaction.
Long Noncoding RNA NR2F1-AS1 Enhances the Migration and Invasion of Hepatocellular Carcinoma via Modulating miR-642a/DEK Pathway
Authors: Xu Yingxia , Han Chunrong , Sun Jing , Zhao Jingjing , Liu Qing , An Ping
Published: September 2021

Purpose. Hepatocellular carcinoma (HCC), a malignant tumor that exists worldwide, has a high morbidity and mortality rate. Previous studies have reported that lncRNA NR2F1-AS1 plays a critical role in several cancers. Here, we aimed to investigate the biological function of NR2F1-AS1 and its molecular mechanism in the migration and invasion of HCC. Methods. Quantitative real-time PCR (qRT-PCR) was performed to analyze NR2F1-AS1 expression in HCC. The biological function was investigated by transwell invasion and migration assays. The protein level was identified by Western blot. In addition, the downstream targets of NR2F1-AS1 and miR-642a were confirmed by luciferase reporter assays. Results. NR2F1-AS1 was significantly upregulated in HCC and associated with the poor prognosis of HCC patients. Biological function experiments revealed that the silence of NR2F1-AS1 suppressed cell invasion and migration in HCC. More importantly, NR2F1-AS1 directly interacted with miR-642a and negatively regulated miR-642a. DEK was the target of miR-642a, and NR2F1-AS1 positively regulated DEK expression by suppressing miR-642a. Conclusion. Taken together, it is the first time we discovered the interaction of NR2F1-AS1 with miR-642a in modulating HCC cell invasion and migration.
Design and Optimization of the Circulatory Cell-Driven Drug Delivery Platform
Authors: Gao Pengyu , Zou Dan , Zhao Ansha , Yang Ping
Published: September 2021

Achievement of high targeting efficiency for a drug delivery system remains a challenge of tumor diagnoses and nonsurgery therapies. Although nanoparticle-based drug delivery systems have made great progress in extending circulation time, improving durability, and controlling drug release, the targeting efficiency remains low. And the development is limited to reducing side effects since overall survival rates are mostly unchanged. Therefore, great efforts have been made to explore cell-driven drug delivery systems in the tumor area. Cells, particularly those in the blood circulatory system, meet most of the demands that the nanoparticle-based delivery systems do not. These cells possess extended circulation times and innate chemomigration ability and can activate an immune response that exerts therapeutic effects. However, new challenges have emerged, such as payloads, cell function change, cargo leakage, and in situ release. Generally, employing cells from the blood circulatory system as cargo carriers has achieved great benefits and paved the way for tumor diagnosis and therapy. This review specifically covers (a) the properties of red blood cells, monocytes, macrophages, neutrophils, natural killer cells, T lymphocytes, and mesenchymal stem cells; (b) the loading strategies to balance cargo amounts and cell function balance; (c) the cascade strategies to improve cell-driven targeting delivery efficiency; and (d) the features and applications of cell membranes, artificial cells, and extracellular vesicles in cancer treatment.