bluuebunny/crossref_metadata_2025 huggingface dataset:
Explainable Deep Attention Active Learning for Sentimental Analytics of Mental Disorder
Authors: Ahmed Usman , Jhaveri Rutvij H. , Srivastava Gautam , Lin Jerry Chun-Wei
Published: July 2022

With the increasing use of online mediums, Internet-delivered psychological treatments (IDPs) are becoming an essential tool for improving mental disorders. Online-based health therapies can help a large segment of the population with little resource investment. The task is greatly complicated by the overlapping emotions for specific mental health. Early adoption of a deep learning system presented severe difficulties, including ethical and legal considerations that contributed to a lack of trust. Modern models required highly interpretable, intuitive explanations that humans could understand. To achieve this, we present a deep attention model based on fuzzy classification that uses the linguistic features of patient texts to build emotional lexicons. In medical applications, a diversified dataset generates work. Active learning techniques are used to extend fuzzy rules and the learned dataset gradually. From this, the model can gain a reduction in labeling efforts in mental health applications. In this way, difficulties such as the amount of vocabulary per class, method of generation, the source of data, and the baseline for human performance level can be solved. Moreover, this work illustrates fuzzy explainability by using weighted terms. The proposed method incorporates a subset of unstructured data into the set for training and uses a similarity-based approach. The approach then updates the model training using the new training points in the subsequent cycle of the active learning mechanism. The cycle is repeated until the optimal solution is found. At this point, all unlabeled text is converted into the set for training. The experimental results show that the emotion-based enhancement improves test accuracy and helps develop quality criteria. In the blind test, the bidirectional LSTM architecture with an attention mechanism and fuzzy classification achieved an F1 score of 0.89.
High Throughput Screening for Bioactive Components of Berberis baluchistanica Ahrendt Root and Their Functional Potential Assessment
Authors: Gul Zareen , Akbar Ali , Ali Imran , Muhammad Javed , Rehman Zia Ur , Bano Amna , Samad Abdul , Khan Amjad , Samiullah  , Leghari Saadullah Khan , Chein Su Hlaing , Rabaan Ali A.
Published: July 2022

Berberis baluchistanica Ahrendt is a medicinal plant potentially known for the treatment of different diseases. The bioactive, antioxidant, nutritional components, and antimicrobial properties of crude ethanolic root extract of Berberis baluchistanica were evaluated in this study. The extract was analyzed for total phenolic, flavonoid, DPPH (2, 2‐diphenyl‐1‐picryl‐hydrazyl) scavenging ability, FRAP (ferric reducing antioxidant power), nutritional, and antimicrobial potentials. The alkaloids, tannins, cardiac glycosides, anthraquinones, coumarin, saponins, phenolics, flavonoids, steroids, and terpenoids were confirmed. The extract possessed DPPH radical inhibition with the IC50 of 1.125 mg/mL and FRAP % reduction activity with IC50 (0.912 mg/mL). Total phenolic 19.897 ± 4.8141 mg GAE/g and flavonoid 12.9876 ± 0.8388 mg QE/g contents were confirmed in the root. The extracts exhibit good antibacterial activity against a broad spectrum of food borne pathogens Pseudomonas aeruginosa, Salmonella typhi, Klebsiella pneumoniae, Escherichia coli, and Staphylococcus aureus. The highest inhibitory activity was against Escherichia coli 23.30 ± 1.16 mm and lowest against Klebsiella pneumoniae 7 ± 0.01 mm. Furthermore, the presence of various phytochemical constituents (plant secondary metabolites) was also confirmed with gas chromatography and mass spectroscopy analysis. Results disclosed the occurrence of more than 70 compounds possessing various medicinal properties supporting the traditional uses of root of Berberis baluchistanica in various medical complications indigenously.
Evaluation of Macrophage Activation Syndrome in Patients with Systemic Juvenile Idiopathic Arthritis: A Single Center Experience
Authors: Høeg Pia Elkjær , Glerup Mia , Mahler Birgitte , Høst Christian , Herlin Troels
Published: July 2022

Objectives. Macrophage activation syndrome (MAS) is a severe complication of systemic juvenile arthritis (sJIA), and early diagnosis is critical for survival. The objective of this study was to evaluate the 2016 MAS classification criteria in a Danish sJIA cohort and to compare different sets of criteria for the early identification of MAS including the HLH-2004 diagnostic guidelines, MS score, and the ferritin/ESR ratio. Methods. Data was extracted from medical charts of 32 patients with sJIA from a single Danish paediatric rheumatology center diagnosed between January 2014 and June 2021. Patients who met the 2016 MAS classification criteria were classified as having MAS. From a receiver operating characteristic (ROC) plot, the area under the curve (AUC) was calculated for the prediction of patients with MAS according to the 2016 MAS classification criteria using either MS score or the ferritin/ESR ratio. Results. Of the cohort, eight (25%) patients were classified as having MAS according to the 2016 MAS classification criteria compared to only three (9.4%) patients fulfilling the HLH-2004 diagnostic guidelines, all of which had recurrent MAS. The ferritin/ESR ratio showed the highest sensitivity (100%) but the lowest specificity (72.2%). In comparison, the MS score had a higher specificity (90.9%) for the identification of MAS according to the 2016 classification criteria. In our cohort, the most optimal cut-off point for the ferritin/ESR ratio was ≥19.4 (sensitivity: 100%, specificity: 72.2%) and ≥ -1.5 for the MS score (sensitivity: 71.4%, specificity: 91.7%), respectively. Conclusion. The 2016 MAS classification criteria were a valuable tool in the discrimination of sJIA with and without MAS. The HLH-2004 diagnostic guidelines showed the lowest sensitivity, ferritin/ESR ratio, and the lowest specificity compared to the MS score where an acceptable high sensitivity and specificity was found.
Detection of Power Data Outliers Using Density Peaks Clustering Algorithm Based on
K
-Nearest Neighbors
Authors: Li Qingpeng , Chen Lei , Wang Yuhan
Published: July 2022

As an important research branch in data mining, outlier detection has been widely used in equipment operation monitoring and system operation control. Power data outlier detection is playing an increasingly vital role in power systems. Density peak clustering (DPC) is a simple and efficient density-based clustering algorithm with a good application prospect. Nevertheless, the clustering results by the DPC algorithm can be greatly influenced by the cutoff distance, indicating that the results are highly sensitive to this parameter. To address the shortcomings of the DPC algorithm and take the characteristics of power data into consideration, we propose a DPC algorithm based on

K

-nearest neighbors for the detection of power data outliers. The proposed DPC algorithm introduces the idea of

K

-nearest neighbors and uses a unified definition of local density. In the DPC algorithm, only one parameter (

K

) needs to be determined, thus eliminating the influence of cutoff distance on the clustering result of the algorithm. The experimental results showed that the proposed algorithm can achieve accurate detection of power data outliers and has broad application prospects.
[Retracted] Antihypertensive Activity in High Salt‐Induced Hypertensive Rats and LC‐MS/MS‐Based Phytochemical Profiling of Melia azedarach L. (Meliaceae) Leaves
Authors: Saeed Anam , Bashir Kashif , Shah Abdul Jabbar , Qayyum Rahila , Khan Taous
Published: July 2022

Melia azedarach L. leaves have been traditionally used but not scientifically evaluated for antihypertensive activity. The focus of the present work was to carry out the detailed phytochemical profiling and antihypertensive potential of methanolic extract and subsequent fractions of this plant. The tandem mass spectrometry‐based phytochemical profiling of M. azedarach extract (Ma.Cr) and fractions was determined in negative ionization mode while molecular networking was executed using the Global Natural Product Social (GNPS) molecular networking platform. This study resulted in the identification of 29 compounds including flavonoid O‐glycosides, simple flavonoids, triterpenoidal saponins, and cardenolides as the major constituents. Ma.Cr at the concentration of 300 mg/kg resulted in a fall in blood pressure (BP), i.e., 81.44 ± 2.1 mmHg in high salt‐induced hypertensive rats in vivo, in comparison to normotensive group, i.e., 65.36 ± 1.8 mmHg at the same dose. A decrease in blood pressure was observed in anaesthetized normotensive and hypertensive rats treated with extract and various fractions of M. azedarach. A reasonable activity was observed for all fractions except the aqueous fraction. The highest efficacy was shown by the ethyl acetate fraction, i.e., 77.06 ± 3.77 mmHg in normotensive and 88.96 ± 1.3 mmHg in hypertensive anaesthetized rats. Ma.Cr and fractions showed comparatively better efficacy towards hypertensive rats as compared to rats with normal blood pressure. Blood pressure‐lowering effects did not change upon prior incubation with atropine. In vitro testing of Ma.Cr and polarity‐based fractions resulted in L‐NAME sensitive, endothelium‐dependent vasodilator effects on aortic tissues. Pretreatment of aorta preparations with Ma.Cr and its fractions also blocked K+‐induced precontractions indicating Ca2+ channel blocking activity comparable to verapamil. The extract and polarity‐based fractions did not reveal a vasoconstrictor response in spontaneously beating isolated rat aorta. Ma.Cr and fractions when used in atrial preparations resulted in negative inotropic and chronotropic effects. These effects in atrial preparations did not change in the presence of atropine. These effects of extract and fractions explained the antihypertensive potential of M. azedarach and thus provided a scientific basis for its ethnopharmacological use in the treatment of hypertension. Among the constituents observed, flavonoids and flavonoid O‐glycosides were previously reported for antihypertensive potential.
The Effects of Self-Efficacy and Physical Activity Improving Methods on the Quality of Life in Patients with Diabetes: A Systematic Review
Authors: Hamidi Sajjad , Gholamnezhad Zahra , Kasraie Narges , Sahebkar Amirhossein
Published: July 2022

Objective. The purpose of this systematic review is to study the impact of self-efficacy-improving strategies on physical activity-related glycemic control of diabetes. Method. This systematic review was conducted based on the PRISMA statement. (“Diabetes” OR “glycemic control”) AND (“exercise” OR “physical activity”) AND “self-efficacy” were searched as keywords in databases including PubMed, Google Scholar, Science Direct, Embase, Cochrane, Web of Science, and Scopus between 2000 and 2019 for relesvant articles. Results. Two reviewers independently screened articles (

n
=
400

), and those meeting eligibility criteria (

n
=
47

) were selected for data extraction using a predesigned Excel form and critical appraisal using the “Tool for Quantitative Studies.” Different strategies and health promotion programs such as individual or group face-to-face education and multimedia (video conference, video, phone calls, short message service, and Internet-based education) were used in diabetes self-management education programs. The results of different interventions including motivational interviewing (7 studies), exercise (5 studies), multidimensional self-management programs (25 studies), and electronic education (11 studies) had been evaluated. Interventions with more social support, longer duration, combined educative theory-based, and individual education had better outcomes both in postintervention and in follow-up evaluation. Conclusion. A combination of traditional and virtual long-lasting self-care promoting (motivating) programs is needed to improve patients’ self-efficacy for healthy habits like active lifestyle.
The Influence of Multisensor Fusion Machine Learning on the Controllable Fabrication of MOF (UIO-66)/ZrAl Ceramic Composite Membranes
Authors: Xu Xiaobing , Yang Xu , Shao Shiyuan , Zhu Chunling , Xu Xiaoyong
Published: July 2022

This study is aimed at improving the utilization efficiency of resources and enhancing the experiments’ effect of various composite membrane research. Firstly, the meaning and preparation process of Metal-Organic Frameworks (MOFs) are discussed. Then, the theoretical knowledge of fusing machine learning and multisensor technology is outlined. Finally, based on the controllable fabrication concept of MOF [UIO- (Universitetet I Oslo-) 66]/ZrAl ceramic composite membranes, a multisensor model incorporating machine learning is designed. The results show that the designed radial sensor backpropagation (RS-BP) fusion multisensor model has the highest error rate of about 0.87. When the number of training is about 100 times, the model’s error rate tends to be stable, and the minimum error rate is about 0.01. Secondly, the maximum adsorption capacity of the composite membrane under the controllable preparation of the model is 800 cm3/g Spanning Tree Protocol (STP). Additionally, the adsorption capacity decreases slowly, and the overall adsorption energy is higher than that of the traditional preparation method. Finally, the catalytic efficiency of membranes prepared by fusing multiple sensors is 90%-97%. The research achieves innovation in technology and improves the feasibility of rational application of MOF (UIO-66)/ZrAl ceramic composite membranes. This study not only provides technical support for the development of machine learning fusion multisensing technology but also contributes to the comprehensive improvement of the resource utilization effect.
Research and Implementation of Robot Vision Scanning Tracking Algorithm Based on Deep Learning
Authors: Guo Haifeng , Li Wenyi , Zhou Na , Sun He , Han Zhao
Published: July 2022

In order to solve the difficult problem of deep learning-based robot vision tracking algorithm research and implementation, a deep learning-based target tracking algorithm and a classical tracking algorithm were proposed. It mainly uses the combination of traditional TLD algorithm and GOTURN algorithm to benefit from a large number of offline training data and updates the learner online, so that the whole system has better performance in real-time and accuracy. The results show that the performance of the TLD algorithm is poor regardless of the accuracy curve or the accuracy curve, and the performance of GOTURN-LD is significantly improved when the illumination changes. In the face of occlusion problem, the TLD algorithm shows strong robustness. Although GOTURN-LD is not very stable, its performance is better than GOTURN on the whole.
[Retracted] Physical Fitness Recovery of Athletes Based on High‐Intensity Sports Intermittent Training
Authors: He Ruihua , Yang Xiwen , Ma Ligang
Published: July 2022

Baseball itself is a new sport. In the process of training, teachers often use traditional training methods, which leads to unsatisfactory training results. High‐intensity intermittent and intensive interval training can better improve the efficiency of athletes’ oxidation and energy supply and ultimately play a positive role in improving athletes’ performance. This paper takes the influence of high‐intensity and intensive interval training on the special endurance of baseball players as the research object. A series of functional training programs are developed through adaptive training, testing, coordination training, and recovery training. Through the use of experimental means to understand the influence of high‐intensity interval training and intensive interval training on the physical fitness of baseball players, the paper is aimed at providing ways and means to improve the physical fitness level of baseball players in the future. Based on the experimental test data, functional training is different from traditional training methods to make up for the lack of training research. It is to improve the competitive ability of our baseball players and promote the development of our baseball. It plays an active role in improving the specific endurance, speed, and intermittent endurance of baseball players.
XGBoost-Based Travel Time Prediction between Bus Stations and Analysis of Influencing Factors
Authors: Zhu Lingxiang , Shu Sisi , Zou Liang
Published: July 2022

Real-time and accurate travel time information between bus stations is critical for passengers to make suitable travel plans to reduce waiting time at the stops. By mining and analyzing bus operational data, it can be obtained that factors such as the variation of vehicle speed in adjacent sections and the proportion of bus lanes between stations have affected the travel time between bus stations. Therefore, considering the temporal feature, spatial feature, and weather feature as the prediction model’s input, travel time between bus stations prediction model based on eXtreme Gradient Boosting (XGBoost) was trained and established. The 28-day bus operation data of a certain bus line in Guangzhou was used for training and verification, and they were compared with the prediction models based on

K

-Nearest Neighbors (KNN), BP neural network, and Light Gradient Boosting Machine (LightGBM). In comparison with other models, the lowest MAPE of 11.96% was found for the XGBoost prediction model, which is 9.30% lower than other models on average. The sensitivity analysis of the proposed prediction model was further conducted: temporally, the accuracy of the prediction model was best during the flat peak hours; spatially, the MAPE of the model gradually decreased as the number of line units increased, and when the number of line units exceeded 18, the accuracy of the prediction model stabilized and was lower than 7%. The results confirm that the XGBoost model outperforms the KNN, BP, and LightGBM in terms of fitting, accuracy, and stability.
Exercise Recommendation Model Based on Cognitive Level and Educational Big Data Mining
Authors: Pu Yongming , Chen Hongming
Published: July 2022

There are differences in the learning ability and cognitive ability of different learners. The unified exercises of traditional teaching ignore the differences of learners and cannot meet the personalized needs of learners. Previous recommendation systems focus on the optimization of recommendation performance, rarely clearly reflect the learning state of learners’ knowledge points, and there are large errors in the recommendation results. This paper combines the comprehensive cognitive analysis module and the classified knowledge point cognitive analysis module to analyze the cognitive degree of learners’ knowledge points. Based on the analysis results, appropriate exercises are selected from the educational resource data to form a list to be recommended. The experimental results show that the exercise recommendation algorithm based on cognitive level and data mining has better recommendation effect and accuracy than the other two recommendation models. The error between the actual difficulty of recommended exercises and the index value is very small. It can recommend an appropriate exercise list according to the actual situation of learners. The teaching comparison results show that the exercise recommendation algorithm can meet the personalized needs of students, recommend targeted exercises, and effectively and greatly improve the learning effect and test scores in a short time. When the motion recommendation algorithm based on cognitive level and data mining has the best recommendation effect, the cognitive module of classifying knowledge points accounts for a large proportion in parameter adjustment. Compared with other recommendation systems, this model has higher accuracy and recommendation effect.
A New Correlation Coefficient for
T
-Spherical Fuzzy Sets and Its Application in Multicriteria Decision-Making and Pattern Recognition
Authors: Ali Wajid , Ali Mehboob , Hussain Israr , Ullah Syed Sajid , Alroobaea Roobaea , Hussain Saddam , Binmahfoudh Ahmed , Umar Fazlullah
Published: July 2022

The goal of this paper is to design a new correlation coefficient for

T

-spherical fuzzy sets (TSFSs), which can accurately measure the nature of correlation (i.e., positive and negative) as well as the degree of relationship between TSFS. In order to formulate our proposed idea, we had taken inspiration from the statistical concept of the correlation coefficient. While doing so, we firstly introduce the variance and covariance of two TSFS and then constructed our scheme using these two newly defined notions. The numerical value of our proposed correlation coefficient lies within the interval

−
1

,

+

1

, as it should be from a statistical point of view, whereas the existing methods cannot measure the negative correlation between TSFS, as their numerical value falls within the interval

0
,
1

, which is not reasonable both statistically and intuitively. This aspect has also been thoroughly demonstrated using some numerical examples. The comparison results witnessed the dominance and upper hand of our proposed method over the existing definitions, with reliable and better results. In order to demonstrate the feasibility, usefulness, and practical application, we applied our proposed scheme to solve technical and scientific problems of multicriteria decision-making and pattern recognition. The numerical results show that our proposed scheme is practically suitable, technically applicable, and intuitively reasonable.
[Retracted] Effect of Evodiamine on Collagen‐Induced Platelet Activation and Thrombosis
Authors: Yang Xiaona , Leng Min , Yang Lihong , Peng Yunzhu , Wang Jing , Wang Qian , Wu Kun , Zou Junhua , Wan Wen , Li Longjun , Ye Yujia , Meng Zhaohui
Published: July 2022

Evodia rutaecarpa has multiple pharmacological effects and is widely used in the prevention and treatment of migraine, diabetes, cardiovascular disease, cancer, and other chronic diseases; however, the pharmacological effects of its active compound evodiamine (Evo) have not been thoroughly investigated. The purpose of this study was to investigate the effects of Evo on antiplatelet activation and thrombosis. We discovered that Evo effectively inhibited collagen‐induced platelet activation but had no effect on platelet aggregation caused by activators such as thrombin, ADP, and U46619. Second, we found that Evo effectively inhibited the release of platelet granules induced by collagen. Finally, evodiamine inhibits the transduction of the SFKs/Syk/Akt/PLCγ2 activation pathway in platelets. According to in vivo studies, Evo significantly prolonged the mesenteric thromboembolism induced by ferric chloride and had no discernible effect on the coagulation function of mice. In conclusion, the antiplatelet and thrombotic effects of Evo discovered in this study provide an experimental basis for the investigation of the pharmacological mechanisms of Evo and the development of antiplatelet drugs.
Silencing TUFM Inhibits Development of Monocrotaline-Induced Pulmonary Hypertension by Regulating Mitochondrial Autophagy via AMPK/mTOR Signal Pathway
Authors: Wei Ruyuan , Lv Xin , Fang Changcun , Liu Chuanzhen , Ma Zengshan , Liu Kai
Published: July 2022

Pulmonary arterial hypertension (PAH) is an extremely malignant cardiovascular disease which mainly involves the uncontrollable proliferation of the pulmonary arterial smooth muscular cells (PASMCs). Recent studies have confirmed that mitochondria play an important role in the pathogenesis of pulmonary hypertension through sensing cell hypoxia, energy metabolism conversion, and apoptosis. As a mitochondrial membrane protein, TUFM has been regarded to be related to mitochondrial autophagy (mitophagy), apoptosis, and oxidative stress. Considering these factors are closely associated with the pathogenesis of PAH, we hypothesize that TUFM might play a role in the development of PAH. Our preliminary examination has showed TUFM mainly expressed in the PASMCs, and the subsequent test indicated an increased TUFM expression in the SMCs of pulmonary arteriole in monocrotaline- (MCT-) induced PAH rat model compared with the normal rat. The TUFM knockdown (Sh-TUFM) or overexpressed (OE-TUFM) rats were used to establish PAH by treating with MCT. A notable lower pulmonary arterial systolic pressure together with slightly morphological changes of pulmonary arteriole was observed in the Sh-TUFM group compared with the single MCT-induced PAH group. Increased levels of P62 and Bax and reduced LC3II/I, BECN1, and Bcl2 were detected in the Sh-TUFM group, while the expressions of these proteins in the OE-TUFM group were contrast to the results of the Sh-TUFM group. To elucidate the possible mechanism underlying biological effect of TUFM in PAH, PASMCs were treated with silence or overexpression of TUFM and then exposed to hypoxia condition. An obviously high levels of P62 and Bax along with a decreased LC3 II/I, BECN1, ULK1, Atg12, Atg13, and Bcl2 levels were noticed in cells with silence of TUFM. Moreover, the phosphorylated AMPK and mTOR which was well known in mitophagy modulating vary by the alternation of TUFM. These observations suggested that TUFM silence inhibits the development of MCT-induced PAH via AMPK/mTOR pathway.
Research on the Theory and Value Analysis Algorithm of Marx’s Outlook on the People Based on Deep Learning under the Background of the Internet of Things
Authors: Liu Yanyan , Yan Pan
Published: July 2022

Marxist outlook on the people is an important part of Marxist theory and one of the important contents of historical materialism. Starting from the realistic man, Marx expounded that the premise of the development of human history is the existence of a living individual. On the basis of practice, we can see that the people are the creators of history. Taking the realization of everyone’s free and all-round development as the value goal, it points out the direction of the development of human society. The Communist Party of China has always adhered to and innovated Marx’s outlook on the people, formed a “people-centered” outlook on the people, and realized the new development of Marx’s outlook on the people in the new era of China. In the new era, adhering to the Marxist concept of the people has important values of the times. It provides theoretical weapons for maintaining ideological security, points out the right direction for party building, gathers strength for realizing the great dream, and provides dynamic support for coping with the great changes.
Phytochemical Analysis and Antioxidant, Antibacterial, and Antifungal Effects of Essential Oil of Black Caraway (Nigella sativa L.) Seeds against Drug‐Resistant Clinically Pathogenic Microorganisms
Authors: Zouirech Otmane , Alyousef Abdullah A. , El Barnossi Azeddin , El Moussaoui Abdelfattah , Bourhia Mohammed , Salamatullah Ahmad M. , Ouahmane Lahcen , Giesy John P. , Aboul-soud Mourad A. M. , Lyoussi Badiaa , Derwich Elhoussine
Published: July 2022

Nigella sativa (NS) is a plant that has long been utilized in traditional medicine as a treatment for certain diseases. The aim of this work was to valorize the essential oil (EO) of this species by phytochemical analysis and antimicrobial and antioxidant evaluation. EO was extracted by hydrodistillation from the seeds of Nigella sativa (EO‐NS). Phytochemical content of EO‐NS was evaluated by use of gas chromatography coupled to mass spectrometry (GC‐MS/MS). Antioxidant ability was in vitro determined by use of three assays: 2.2‐diphenyl‐1‐picrylhydrazyl (DPPH), ferric reducing power (FRAP), and total antioxidant capacity (TAC) relative to two synthetic antioxidants: BHT and quercetin. Antimicrobial effect was evaluated against four clinically important bacterial strains (Staphylococcus aureus, ATCC 6633; Escherichia coli, K12; Bacillus subtilis, DSM 6333; and Proteus mirabilis, ATCC 29906) and against four fungal strains (Candida albicans, ATCC 10231; Aspergillus niger, MTCC 282; Aspergillus flavus, MTCC 9606; and Fusarium oxysporum, MTCC 9913). Fifteen constituents that accounted for the majority of the mass of the EO‐NS were identified and quantified by use of GC‐MSMS. The main component was O‐cymene (37.82%), followed by carvacrol (17.68%), α‐pinene (10.09%), trans‐sabinene hydrate (9.90%), and 4‐terpineol (7.15%). EO‐NS exhibited significant antioxidant activity with IC50, EC50, and total antioxidant capacity (TAC) of 0.017 ± 0.0002, 0.1196 ± 0.012, and 114.059 ± 0.97 mg EAA/g, respectively. Additionally, EO‐NS exhibited promising antibacterial activity on all strains under investigation, especially on E. coli K12 resulting in inhibition diameter of 38.67 ± 0.58 mm and a minimum inhibitory concentration (MIC) of 1.34 ± 0.00 μg/mL. Also, EO‐NS had significant antifungal efficacy, with a percentage of inhibition of 67.45 ± 2.31% and MIC of 2.69 ± 0.00 μg/mL against F. oxysporum, MTCC 9913 and with a diameter of inhibition 42 ± 0.00 mm and MIC of 0.67 ± 0.00 μg/mL against C. albicans. To minimize development of antibiotic‐resistant bacteria, EO‐NS can be utilized as a natural, alternative to synthetic antibiotics and antioxidants to treat free radicals implicated in microbial infection‐related inflammatory reactions.
The Application of Multimedia Information Technology in the Moral Education Teaching System of Colleges and Universities
Authors: Yu Weichun
Published: July 2022

The rapid development of multimedia technology provides technical support for higher education and makes higher education move towards automation and informatization. Multimedia technology has been widely used in the teaching of colleges and universities in China, and the traditional teaching mode will be gradually replaced. Multimedia education is the product of the combination of multimedia technology and modern educational technology. It can create a broader space for the future of education and help education achieve diversified development. This technology can not only improve the teaching efficiency but also further complete the comprehensive training of students’ quality. The popularization of multimedia information technology in the classroom is also a main direction of today’s education reform. The application of multimedia technology in moral education teaching system is highly valued by teachers. Students have a strong autonomy to understand and accept the network education mode. Therefore, network multimedia information technology can be widely used. In particular, for moral education, network education is more feasible and scientific. It can widely cover every student through the construction of network platform and integrate moral education teaching into campus culture for gradual development. This paper discusses multimedia information technology. This paper discusses the design of moral education teaching system under the environment of multimedia information technology, including the design of various functions, in order to improve the integrity of moral education teaching in colleges and universities.
Multiobjective Optimization of Process Parameters of Silicon Single Crystal Growth
Authors: Huang Weichao , Zhang Ganggang , Wang Jing
Published: July 2022

In order to obtain higher quality silicon single crystal, a hybrid strategy for modeling of Czochralski silicon crystal growth and optimizing of process parameters is presented in the paper. The hybrid strategy includes the computational fluid dynamics (CFD) method, neural network of group method of data handing (GMDH), and improved nondominated sorting genetic algorithm II (NSGA-II). The shape variable of solid-liquid interface

h

and the defect evaluation criteria

V
/
G

are set to objective functions according to engineering experience and process requirement. The polynomial of the objective functions is produced by GMDH and CFD. Ultimately, an improved elitist strategy and crowding distance NSGA-II is proposed in the paper to obtain the Pareto optimum solution by the objective functions identified by the GMDH. Compared with other optimization algorithms, the improved NSGA-II can increase the lateral diversity and the uniform distribution of the nondominated solutions. Engineering validation proved that the proposed hybrid strategy can effectively solve the complex uncertain multiobjective optimization problem of system and provides a new method for obtaining high-quality crystal growth process parameters.
ESM1 Is a Promising Therapeutic Target and Prognostic Indicator for Esophageal Carcinogenesis/Esophageal Squamous Cell Carcinoma
Authors: Li Juan , Yang Dong , Zhang Cong , Wei Sisi , Zhao Ruinian , Dai Suli , Shan Baoen
Published: July 2022

Objective. Endothelial cell‐specific molecule 1 (ESM1) has been implicated as an oncogene in several types of cancer. However, the potential role of ESM1 in esophageal carcinogenesis (ESCA)/esophageal squamous cell carcinoma (ESCC) is still unclear. Methods. The expression, function, and survival data of ESM1 were observed using a bioinformatics approach. Subsequently, the expression level of ESM1 in surgical esophageal tumors and adjacent normal tissues was detected by qRT–PCR and immunofluorescence. We further revealed protein expression by immunohistochemistry (IHC), which is related to the prognosis of patients with ESCC using survival analysis. In vitro, knockdown of ESM1 in KYSE150 and KYSE510 cell lines, colony formation assays, wound healing assays, and Transwell assays were performed. Results. ESM1 is significantly elevated in 12 of 20 types of human cancer. ESM1 is highly expressed in tumor tissue compared with adjacent normal tissue and was identified as a hub gene in ESCA. Clinical outcome endpoints of overall survival (OS), progression‐free interval (PFI), and disease‐specific survival (DSS) curves showed that patients whose ESM1 expression was high had a lower clinical survival rate. The ESM1 high‐expression group has a certain correlation with clinical stage and grade. The IHC of ESM1 further demonstrated that the higher the expression was, the worse the N classification and pTNM stage in patients with ESCC, which had a distinctly poorer overall 5‐year survival rate. Univariate analysis showed that age, N classification, pTNM stage, and ESM1 expression were all prognostic factors, although multivariate Cox regression analysis showed that only pTNM stage was an independent prognostic factor. In vitro, silencing ESM1 suppressed the proliferation, migration, and invasion of KYSE150 and KYSE510 cells. Conclusions. ESM1 is a hub gene in the initiation and progression of ESCA/ESCC that promotes the proliferation, migration, and invasion of esophageal cancer cells and may be a promising therapeutic target and prognostic indicator.
Identification of Novel and Safe Fungicidal Molecules against Fusarium oxysporum from Plant Essential Oils: In Vitro and Computational Approaches
Authors: Yousafi Qudsia , Bibi Shabana , Saleem Shahzad , Hussain Abrar , Hasan Mohammad Mehedi , Tufail Maria , Qandeel Amina , Khan Muhammad Saad , Mazhar Sania , Yousaf Maha , Moustafa Mahmoud , Al-Shehri Mohammed , Khalid Mohammad , Kabra Atul
Published: July 2022

Phytopathogenic fungi are serious threats in the agriculture sector especially in fruit and vegetable production. The use of plant essential oil as antifungal agents has been in practice from many years. Plant essential oils (PEOs) of Cuminum cyminum, Trachyspermum ammi, Azadirachta indica, Syzygium aromaticum, Moringa oleifera, Mentha spicata, Eucalyptus grandis, Allium sativum, and Citrus sinensis were tested against Fusarium oxysporum. Three phase trials consist of lab testing (MIC and MFC), field testing (seed treatment and foliar spray), and computer‐aided fungicide design (CAFD). Two concentrations (25 and 50 μl/ml) have been used to asses MIC while MFC was assessed at four concentrations (25, 50, 75, and 100 μl/ml). C. sinensis showed the largest inhibition zone (47.5 and 46.3 m2) for both concentrations. The lowest disease incidence and disease severity were recorded in treatments with C. sinensis PEO. Citrus sinensis that qualified in laboratory and field trials was selected for CAFD. The chemical compounds of C. sinensis PEO were docked with polyketide synthase beta‐ketoacyl synthase domain of F. oxysporum by AutoDock Vina. The best docked complex was formed by nootkatone with ‐6.0 kcal/mol binding affinity. Pharmacophore of the top seven C. sinensis PEO compounds was used for merged pharmacophore generation. The best pharmacophore model with 0.8492 score was screened against the CMNP database. Top hit compounds from screening were selected and docked with polyketide synthase beta‐ketoacyl synthase domain. Four compounds with the highest binding affinity and hydrogen bonding were selected for confirmation of lead molecule by doing MD simulation. The polyketide synthase‐CMNPD24498 showed the highest stability throughout 80 ns run of MD simulation. CMNPD24498 (FW054‐1) from Verrucosispora was selected as the lead compound against F. oxysporum.
Prescribed Thermal Activity in the Radiative Bidirectional Flow of Magnetized Hybrid Nanofluid: Keller‐Box Approach
Authors: Ahmad Iftikhar , Zan-Ul-Abadin Qazi , Faisal Muhammad , Loganathan K. , Javed Tariq , Chaudhary Dinesh Kumar
Published: July 2022

In this exploration, we decided to investigate the significance of prescribed thermal conditions on unsteady 3D dynamics of water‐based radiative hybrid nanofluid with the impact of cylindrical‐shaped nanosized particles (alumina (Al2O3) and titania (TiO2)). For physical relevancy, the impact of the Lorentz force is also included. The combination of suitable variables has been used to transform the transport equations into the system of ordinary differential equations and then numerically solved via the Keller‐Box approach. Graphical illustrations have been used to predict the impact of the involved parameters on the thermal setup. Convergence analysis is presented via the grid independence approach. Skin frictions and local Nusselt numbers against various choices of involved parameters are plotted and arranged in tabular forms. It is observed through the present investigation that temperature distribution is increased with the higher choices of radiation parameter 0.0 ≤ Rd ≤ 2.0 and decreased with the improvement in the choices of temperature maintaining indices (i.e., −2.0 ≤ r, s ≤ 2.0). Moreover, the thermophysical properties except specific heat for hybrid nanofluid are improved with the involvement of cylindrical‐shaped nanoparticles. The temperature of the hybrid nanofluid is observed to be higher for variable thermal conditions as compared to uniform thermal conditions. Outfalls for a limited version of the report have been compared with a previous published paper.
Bi‐Modified Bi2WO6/BiOI Heterojunction with Enhanced Visible‐Light‐Driven Photoactivity for Antibiotic Degradation
Authors: Zou Xia , Wang Sisi , Wu Chunbei , Peng Zhigang , Yang Jun
Published: July 2022

A flower‐like metallic Bi‐modified Bi2WO6/BiOI heterojunction was fabricated by a two‐step approach of hydrothermal method and in situ ethylene glycol reduction method. The ternary system was confirmed by structural analysis and surface and morphological studies. Compared with Bi2WO6, BiOI, and their binary nanomaterials, the catalyst exhibits excellent photocatalytic performance for the degradation of ciprofloxacin (CIP) and levofloxacin (LEV) under visible light irradiation. The improvement of photocatalytic performance was ascribed to the synergistic effect between metal Bi nanoparticles and Bi2WO6/BiOI p‐n heterojunction, which enhanced the light absorption capacity and the separation efficiency of photogenerated carriers. By studying the effect of solution pH on CIP degradation, it was found that when pH = 10, the degradation efficiency of the catalyst on ciprofloxacin reached 100% within 40 min. It provides a new idea for the design and synthesis of ternary photocatalysts for purification of alkaline domestic sewage.
Enterprise Complementarity Based on Patent Information
Authors: Sun Lin , Xu Wenzheng
Published: July 2022

The combination of complementary patents can better promote the advancement of technology, and complementary companies can help companies bring better benefits. This topic has carried out patent complementarity research and proposed a patent complementarity algorithm based on patent technology tree. By calculating the complementarity calculation method of a given patent, the company with the strongest complementarity with known patents is obtained. First, the patent text is represented sentence vectors by LSTM model. Second, the generated sentence vectors are clustered, and the patent information is marked with different categories. Then, the patent word vector is obtained by the CNN text classification model to obtain the confidence that the patent belongs to the corresponding category. Finally, the confidence of the patent and the complementarity coefficient based on the patent classification number are combined to obtain the interpatent complementarity. Calculate the average of the complementarity between all patents and a given patent under the same company, and the company with the greatest complementarity is the complementary company sought. The method combines the patent text and the patent classification number, obtains the similarity of the text semantics through the deep learning model, and quantifies the complementarity of the patents, and the discriminating basis is more accurate and reliable.
[Retracted] Expression Profile of MAGE‐B1 Gene and Its Hypomethylation Activation in Colon Cancer
Authors: Almutairi Mikhlid H. , Alotaibi Mona M. , Alonaizan Rasha , Almutairi Bader O.
Published: July 2022

Cancer‐testis (CT) genes are typically expressed in the testes; however, they have been linked to aberrant expression in a variety of malignancies. MAGE-B family genes are an example of CT genes. Therefore, the overarching objective of this study was to examine the expressions of MAGE-B family genes in several patients with colon cancer (CC) to see if they might be employed as cancer biomarkers in the early phases of cancer detection and to improve treatment. In this investigation, RT‐PCR was used to analyze MAGE-B family genes in neighboring normal colon (NC) tissue from 10 CC patients. In addition, the effect of DNA demethylation on the expression status of the MAGE-B1 gene was evaluated by RT‐PCR in HCT116 and Caco‐2 cells and by qRT‐PCR for HCT116 only after treating both CC cell lines with varying concentrations of 5‐aza‐2 ’‐deoxycytidine (1.0, 5.0, and 10.0 μM) for 48 or 72 hours. All MAGE-B family genes except for MAGE-B1 showed weak bands in several samples of NC tissues: MAGE-B2, MAGE-B3, MAGE-B4, MAGE-B5, and MAGE-B6 genes were observed in 40%, 50%, 40%, 30%, and 60% of the NC samples, respectively. Nonetheless, they had strong bands in multiple samples of CC tissues, with 70%, 90%, 60%, 50%, and 90% of the CC samples, respectively. Interestingly, MAGE-B1 was detected in 60% of CC tissues but not in NC tissues, suggesting that it is a potential biomarker for early CC detection. MAGE-B1 expression was not observed in either untreated or DMSO‐treated HCT116 cells after 48 or 72 hours of treatment. However, according to the RT‐PCR and qRT‐PCR results, the MAGE-B1 gene was overexpressed in the HCT116 cells treated with three different concentrations of 5‐aza‐2 ’‐deoxycytidine. This shows that demethylation plays a crucial role in MAGE-B1 expression activation.
Comparison of Modified Broström Procedure with or without Suture Tape Augmentation Technique for the Chronic Lateral Ankle Instability
Authors: Li Ji , Qi Wei , Yun Xing , Wei Yu , Liu Yang , Wei Min
Published: July 2022

Purpose. To compare the clinical outcomes of the modified Broström repair (MBR) with or without suture tape augmentation (STA) for managing the chronic lateral ankle instability. Methods. 72 patients with chronic lateral ankle instability treated at our hospital from January 2018 to July 2019 were included, with 37 patients receiving the MBR and 35 treated by the MBR with STA. The clinical efficacy of the two techniques was assessed in terms of VAS, AOFAS, and Karlsson scores and by physical examination in follow‐ups. Results. In all 72 patients, operations were successful, and the patients were followed up for 29.3 months on average (range, 24‐43 months). There were no significant differences in preoperative pain, AOFAS, and Karlsson scores between the two groups. Compared with preoperative findings, all the functional scores were significantly improved in both groups 3 months after the operation and at the last follow‐up. Three months after the operation, the STA group had significantly lower VAS and higher AOFAS scores than the isolated MBR group, suggesting that patients in the STA group suffered less pain and achieved better functional improvement. However, the VAS and functional scores at the last follow‐up and the Karlsson score at 3 months postoperatively showed no intragroup difference in both groups. Conclusion. MBR with or without STA could achieve good results for the treatment of chronic lateral ankle instability. Compared with the widely used MBR, combining with STA may be more effective in promoting rehabilitation in early term.
Relative Entropy-Based Similarity for Patterns in Graph Data
Authors: Liu Shihu , Deng Li , Gao Haiyan , Ma Xueyu
Published: July 2022

How to make a correct similarity between patterns is a groundwork in data mining, especially for graph data. Despite these methods that can obtain great results, there may be still some limitations, for instance, the similarity of patterns in directed weighted graph data. Here, we introduce a new approach by taking the so-called the second-order neighbors into consideration. The proposed new similarity approach is named as relative entropy-based similarity for patterns in graph data, wherein the relative entropy provides a brand new aspect to make the difference between patterns in directed weighted graph data. The proposed similarity measure can be partitioned under three phases. First of all, strength set is given by degree and weight of patterns; in this phase, four variables holding the strength about out-degree, in-degree, out-weight, and in-weight are constructed. Then, with the help of Euclidean metric, pattern’s probability set is constructed, which contains influence of similarity between pattern and its all one-order neighbors. Finally, relative entropy is used to measure the difference between patterns. In order to examine the validity of our approach as well as its advantage comparing with the state-of-art approach, two sorts of experiments are suggested for real-world and synthetic graph data. The outcomes of experiment indicate that the recommended method get handy execution done measuring similarity and gain accurate results.