bluuebunny/crossref_metadata_2025 huggingface dataset:
Fut7 Promotes Adhesion and Invasion of Acute Lymphoblastic Leukemia Cells through the Integrin/Fak/Akt Pathway
Authors: He Fei , Yi Lijun , Lai Changcheng
Published: June 2022

Purpose. To investigate the role and mechanism of N-fucosyltransferase VII (FUT7) in acute lymphoblastic leukemia (ALL). Methods. Bone marrow tissues were collected from patients with ALL and children with immune thrombocytopenic purpura (control) hospitalized in our hospital during the same period. Then, the FUT7 expression in bone marrow tissues was detected by qRT-PCR and western blotting. Human ALL cell strain Jurkat was cultured, and after knockdown or overexpression of FUT7, cell proliferation, apoptosis, adhesion and invasion were examined by MTT assay, flow cytometry, fibronectin adhesion assay and transwell, respectively; the protein expression level of integrin α5, integrin β1, p-FAK, and p-AKT was tested by western blotting. Results. The FUT7 expression was up-regulated in bone marrow cells of ALL patients. After knockdown of FUT7, the proliferation, adhesion and migration ability of ALL cells were significantly reduced, and apoptosis was increased, while the overexpression of FUT7 obtained the opposite results. Moreover, the overexpression of FUT7 also promoted the protein expression of integrin α5, integrin β1, p-FAK, p-AKT. Conclusion. FUT7 can promote the adhesion and invasion of ALL cells by activating the integrin/FAK/AKT pathway.
Deep LSTM Network for Word-of-Mouth Management of Rural Tourism
Authors: Wang Jun
Published: June 2022

With the development of tourism, rural tourism as an industry with great development potential is gradually attracting urban consumers. Considering the differences between different types of rural tourism, I refine it at the visitor level to balance the differences in visitor groups of different types of rural tourism. I propose an improved LSTM framework for rural tourism theme feature extraction. I chose a deep neural network approach to decompose the diverse rural tourism word of mouth into different tourism themes. Then, through tourist feedback data preprocessing, destination theme detection, rural tourism type classification, and word-of-mouth management prediction network, I finally achieve an accurate grasp of rural tourism word-of-mouth features and develop corresponding tourism management strategies. To test the performance of our method, I established different types of rural tourism databases through field surveys for experimental validation. The experimental results show that our method achieves over 90% accuracy in review sentiment detection.
Clinical Efficacy of Sanfeng Tongqiao Diwan in the Treatment of Allergic Rhinitis: A Randomized Controlled Trial
Authors: Ma Jing , Luo Jiaying , Cheng Zhangkai J. , Chen Gui , Liang Zhiman , Sun Baoqing , Wang Feng
Published: June 2022

Objective. To explore the clinical effect of Sanfeng Tongqiao Diwan in the treatment of allergic rhinitis. Methods. Allergic rhinitis patients included in this study were randomly divided into control group and study group for 7 days of treatment. The control group was treated with Tongqiao Biyan Pian, while the study group was treated with Sanfeng Tongqiao Diwan. Results. After 7 days of treatment, the total effective rate of Sanfeng Tongqiao Diwan was 75.76%, which was higher than that of Tongqiao Biyan Pian (65.62%). The scores of visual analogue scale (VAS), symptom relief, Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ), and Epworth sleepiness scale (ESS) in both groups were significantly improved before and after treatment (

P
<
0.05

), and the improvement was most significant 24 hours after treatment. The adverse reactions in both groups were low. Conclusion. Sanfeng Tongqiao Diwan can significantly alleviate the symptoms and improve the quality of life of patients with allergic rhinitis, with less adverse reactions.
5G Traffic Prediction Based on Deep Learning
Authors: Gao Zihang
Published: June 2022

The demand of wireless access users is increasing explosively. The 5G network traffic is increasing exponentially and showing a trend of diversity and heterogeneity, which makes network traffic forecasting face many challenges. By studying the actual performance of the 5G network, this paper makes an accurate prediction of the 5G network and builds a smoothed long short-term memory (SLSTM) traffic prediction model. The model updates the number of layers and hidden units according to the prediction accuracy adaptive mechanism. At the same time, in order to reduce the randomness of the 5G traffic sequence, the output feature sequence of the original time series is stabilized by the seasonal time difference method. In the experiments, the prediction results of the proposed algorithm are compared with those of the traditional algorithms. The results show that the SLSTM algorithm can effectively improve the accuracy of 5G traffic prediction. The model can be used for 5G traffic prediction for decision-making.
Anti-Diabetic Effects of Cucurbitacins from Ibervillea lindheimeri on Induced Mouse Diabetes
Authors: Hernández Navia Sonia E. , Figueroa-Hernández José L. , Rodríguez-Zavala José S. , Rodriguez-Sosa Miriam , Martínez-Vázquez Mariano
Published: June 2022

Mexico has a great tradition of using medicinal plants against diabetes. For example, species from the genus Ibervillea traditionally known as “wereque” in Mexican popular medicine have a long ethnobotanical history as anti-diabetic agents. Previous studies by our group indicated that ethyl acetate extract from Ibervillea lindheimeri (I. lindheimeri) roots reduced glucose in mice with chemically induced diabetes. In this work, the primary metabolites of the ethyl acetate extract of I. lindheimeri; 23,24-dihydrocucurbitacin D (1); 2-O-β glucopyranosyl-23,24-dihydrocucurbitacin D (2), and acetylated compounds (3) and (4) obtained from 1 and 2, respectively, were evaluated as anti-hyperglycemic agents in a murine model of chemically induced diabetes. Our results showed that cucurbitacins 1, 2, and 4 reduced glycemia in diabetic CD1 mice compared to the control diabetic group. In addition, the results suggest that compounds 1, 2, and 4 promote glucose transporter type 4 (Glut4) translocation to the plasma membrane (PM) mainly in epididymal adipose tissue (EAT), AMP-activated protein kinase (AMPK) activation in soleus muscle (SM) or dual activation of AMPK, and protein kinase B (AKT) in EAT in an insulin-independent manner when compared to controls. All results together indicate that the isolated cucurbitacins are responsible for the anti-diabetic properties of I. lindheimeri acting predominantly on adipose tissue and call attention to this species as a new source of anti-diabetic compounds.
Optimal Superpixel Kernel-Based Kernel Low-Rank and Sparsity Representation for Brain Tumour Segmentation
Authors: Ge Ting , Zhan Tianming , Li Qinfeng , Mu Shanxiang
Published: June 2022

Given the need for quantitative measurement and 3D visualisation of brain tumours, more and more attention has been paid to the automatic segmentation of tumour regions from brain tumour magnetic resonance (MR) images. In view of the uneven grey distribution of MR images and the fuzzy boundaries of brain tumours, a representation model based on the joint constraints of kernel low-rank and sparsity (KLRR-SR) is proposed to mine the characteristics and structural prior knowledge of brain tumour image in the spectral kernel space. In addition, the optimal kernel based on superpixel uniform regions and multikernel learning (MKL) is constructed to improve the accuracy of the pairwise similarity measurement of pixels in the kernel space. By introducing the optimal kernel into KLRR-SR, the coefficient matrix can be solved, which allows brain tumour segmentation results to conform with the spatial information of the image. The experimental results demonstrate that the segmentation accuracy of the proposed method is superior to several existing methods under different indicators and that the sparsity constraint for the coefficient matrix in the kernel space, which is integrated into the kernel low-rank model, has certain effects in preserving the local structure and details of brain tumours.
Relational Meir-Keeler Contractions and Common Fixed Point Theorems
Authors: Khan Faizan Ahmad , Sk Faruk , Alshehri Maryam Gharamah , Khan Qamrul Haq , Alam Aftab
Published: June 2022

In this article, we prove some coincidence and common fixed point theorems under the relation-theoretic Meir-Keeler contractions in a metric space endowed with a locally finitely

T

-transitive binary relation. Our newly proved results generalize, extend, and sharpen some existing coincidence point as well as fixed point theorems existing in the literature. Moreover, we give some examples to affirm the efficacy of our results.
Hydroalcoholic Leaf Extract of Isatis tinctoria L. via Antioxidative and Anti-Inflammatory Effects Reduces Stress-Induced Behavioral and Cellular Disorders in Mice
Authors: Nicosia Noemi , Kwiecień Inga , Mazurek Justyna , Mika Kamil , Bednarski Marek , Miceli Natalizia , Ragusa Salvatore , Ekiert Halina , Maes Michael , Kotańska Magdalena
Published: June 2022

Stress that can occur at different levels of a person’s life can cause and exacerbate various diseases. Oxidative stress and inflammation underlie this process at the cellular level. There is an urgent need to identify new and more effective therapeutic targets for the treatment of stress-induced behavioral disorders and specific drugs that affect these targets. Isatis tinctoria L. is a herbaceous species in the Brassicaceae family. Due to its potential antioxidant, nitric oxide- (NO-) inhibiting, anti-inflammatory, and neuroprotective properties, I. tinctoria could be used to treat depression, anxiety, and stress resistance. Hence, the present study is aimed at delineating whether administration of I. tinctoria leaf extract may improve stress-induced disorders in mice. A set of four behavioral tests was selected that together are suitable for phenotyping acute restraint stress-associated behaviors in mice, namely locomotor activity, social integration, dark/light box, and splash tests. The plasma and brains were collected. A brain-derived neurotrophic factor, tumor necrosis factor-alpha, C-reactive protein, corticosterone, NO, reactive oxygen species levels, superoxide dismutase and catalase activity, and ferric-reducing antioxidant power were measured. In mice stressed by immobilization, decreased locomotor activity, anxiety-like behavior, and contact with other individuals were observed, as well as increased oxidative stress and increased levels of nitric oxide in the brain and plasma C-reactive protein. A single administration of I. tinctoria leaf extract was able to reverse the behavioral response to restraint by a mechanism partially dependent on the modulation of oxidative stress, neuroinflammation, and NO reduction. In conclusion, Isatis tinctoria hydroalcoholic leaf extract can reduce stress-induced behavioral disturbances by regulating neurooxidative, neuronitrosative, and neuroimmune pathways. Therefore, it could be recommended for further research on clinical efficacy in depression and anxiety disorder treatment.
GeneMiner: A Classification Approach for Detection of XSS Attacks on Web Services
Authors: Gupta Charu , Singh Rakesh Kumar , Mohapatra Amar Kumar
Published: June 2022

According to OWASP 2021, cross-site scripting (XSS) attacks are increasing through specially crafted XML documents. The attacker injects a malicious payload with a new pattern and combination of scripts, functions, and tags that deceits the existing security mechanisms in web services. This paper proposes an approach, GeneMiner, encompassing GeneMiner-E to extract new features and GeneMiner-C for classification of input payloads as malicious and nonmalicious. The proposed approach evolves itself to the changing patterns of attack payloads and identifies adversarial XSS attacks. The experiments have been conducted by collecting data from open source and generating various combinations of scripts, functions, and tags using an incremental genetic algorithm. The experimental results show that the proposed approach effectively detects newly crafted malicious XSS payloads with an accuracy of 98.5%, which is better than the existing classification techniques. The approach learns variations in the existing attack sample space and identifies the new attack payloads with reduced efforts.
Comparative Analysis of Early Clinical Features and Complications of Different Types of Acute Pancreatitis
Authors: Wu Hongsheng , Ma Keqiang , Liao Biling , Ji Tengfei , Zhang Shengmin , Cao Tiansheng
Published: June 2022

Background. Acute pancreatitis (AP) is a common surgical acute abdomen. Different kinds of pancreatitis may have different pathophysiological characteristics each other. The objective of this research was to investigate the early clinical features and complications of different types of acute pancreatitis. Methods. 787 AP patients admitted in the Huadu District People’s Hospital of Guangzhou during January 2009 and December 2019 were analyzed retrospectively. Among 787 AP patients, 520 (66.1%) were biliary AP (group I), 69 (8.7%) were alcoholic AP (group II), and 198 (25.2%) were hypertriglyceridemic AP (group III). According to the local and systemic complications and mortality in the early stage, we compared and analyzed the clinical characteristics and prognosis of different types of pancreatitis. Results. Mild acute pancreatitis accounted for the highest proportion (79.4%) in group I, while moderately severe acute pancreatitis in group II (36.2%) and severe acute pancreatitis in group III (62.6%). In terms of severity score of the pancreatitis, the average scores of BISAP, Ranson, APACHE-II, and MCTSI of the patients in group III were the highest (

p
<
0.01

). The incidence of acute peripancreatic fluid collection and infectious pancreatic necrosis was the highest in group III. The incidences of acute necrotic collection, pancreatic pseudocyst, and walled-off necrosis in group III were significantly higher than those in the other two groups (

p
<
0.01

). The incidences of systemic inflammatory response syndrome, sepsis, multiple organ failure, intra-abdominal hypertension, and mortality were highest in group III. Conclusions. There is an upward trend of the incidence rate of hypertriglyceridemic AP in recent years; it has been gradually developed into the second type of acute pancreatitis which is second only to the acute biliary pancreatitis. It is worthy to pay more and more attentions to it due to the feature of its younger onset, high incidence of complications, and high mortality.
A Single-Stage SPV-Fed Reduced Switching Inverter-Based Sensorless Speed Control of IM for Water Pumping Applications
Authors: Narendra Ankireddy , Venkataramana Naik N. , Panda Anup Kumar , Tiwary Nishit , Kumar Amit
Published: June 2022

This article elaborates on a reduced switch count-based inverter for a single-stage solar photovoltaic (SPV) fed induction motor (IM) with sensorless speed control for water pumping applications. The traditional SPV-fed IM for water pumping applications requires a six-switch voltage source inverter (SSVSI) for transforming the DC power from the SPV system into AC power. However, the same performance is achieved using a four-switch voltage source inverter (FSVSI). Here, the entire system requires less number of switches and hence reduces switching losses and cost as compared to the traditional solar water pumping system. Moreover, the sensorless speed control is implemented using a speed estimator to reduce the overall cost further and enhance reliability. The reference voltage (

V

d
c
r

) is achieved using an adapted incremental conductance (AINC), and the control of IM is performed using direct vector control (DVC). The control signals for the proposed system are generated using DSPACE DS-1104 for real-time implementation. The proposed SPV-fed FSVSI-based 1-HP IM operation is performed at different irradiation levels in the MATLAB-Simulink environment and validated experimentally.
Deoxyelephantopin Suppresses Pancreatic Cancer Progression In Vitro and In Vivo by Targeting linc00511/miR-370-5p/p21 Promoter Axis
Authors: Ji Daolin , Hou Li , Xie Chunyang , Feng Haonan , Bao Dongdong , Teng Yue , Liu Junhao , Cui Tiangang , Wang Xiuhong , Xu Yi , Tan Gang
Published: June 2022

Objectives. Deoxyelephantopin (DET) is a kind of natural active ingredient extracted from the Chinese herbal medicine Elephantopus scaber L. Many studies have revealed the potential antitumor effect on multiple malignancies. However, the detailed mechanism of its antitumor effect in pancreatic cancer remains unclear. Recently, studies have confirmed that noncoding RNA (ncRNA) plays an important regulatory role in malignancies. This research was performed to explore the relationship between ncRNA and DET-induced tumor inhibition in pancreatic cancer. Methods. Microarray profiling was applied to identify the candidate ncRNAs associated with DET-induced tumor inhibition. Quantitative real-time PCR was used to evaluate the expression of linc00511 in pancreatic cancer cells and tissues. The influence of DET on the cell proliferation, migration, and invasion was assessed by CCK-8, colony formation, wound healing, and Transwell assays. The relationship between lncRNAs, miRNAs, and p21 promoter region was analyzed by bioinformatics and verified by luciferase reporter gene and western blotting. The effect of linc00511 on nuclear translocation of miR-370-5p was explored by cytoplasmic and nuclear RNA purification. Moreover, the effect of DET on tumor growth and metastasis, and the prophylactic effect were investigated by establishing subcutaneous and lung metastatic tumor models. Results. Microarray assay indicated linc00511 was a potential target gene. The antitumor effect of DET in pancreatic cancer depended on downregulating linc00511 expression, and linc00511 might be an oncogene in pancreatic cancer. Silencing linc00511 enhanced the antitumor function of DET; conversely, linc00511 overexpression antagonized the DET cytotoxic effect. Additionally, miR-370-5p could bind to p21 promoter to exert the RNA activation and then promote p21 expression. P21 was a downstream gene of linc00511 and associated with pancreatic cancer progression. Linc00511 regulated p21 expression by blocking miR-370-5p nuclear translocation. Conclusions. To sum up, the present finding confirmed that DET suppressed the malignant biological behavior of pancreatic cancer via linc00511/miR-370-5p/p21 promoter axis.
Computational Validation of the Best Tuning Method for a Vehicle-Integrated PID Controller
Authors: Manuel Calequela J. T. , Santos Max M. D. , Lenzi Giane G. , Tusset Angelo M.
Published: June 2022

This paper validates and analyzes the robustness of the proportional-integral-derivative (PID) action controller from an open transfer function that integrates a proportional-integral (PI) action controller to obtain the response of a robust action control during the automatic parking maneuver of a vehicle where the simulations are based on 3 adjustment methods: Ziegler-Nichols (ZN), Chien-Hrones-Reswick (CHR), and Cohen-Coon (CC), and as a result of the computer simulations, it is determined the best performance index of the PID controller represented by mathematical and graphic equations with the help of MATLAB/Simulink software.
Evaluation of Traditional Culture Teaching Efficiency by Course Ideological and Political Integration Lightweight Deep Learning
Authors: Zhong Qingqing
Published: June 2022

With the development of society, China pays more and more attention to cultural education. The teaching method of introducing ideological and political content into cultural teaching plays an important role in improving the overall teaching quality. However, the traditional methods used to evaluate the quality of culture teaching, curriculum ideological, and political teaching have some problems, such as strong subjectivity and unrepresentative results. Firstly, this work analyzes the connotation of curriculum thought and politics. Secondly, a teaching quality evaluation model based on an improved lightweight convolutional neural network (CNN) is proposed, which mainly judges the students’ recognition of teachers’ content and teaching methods by identifying the students’ expressions in the classroom. Finally, the students of a senior high school in Shanghai are selected as the survey object, and the current situation of ideological and political education (IPE) in the school curriculum is preliminarily understood by issuing a questionnaire; experiments are designed to test the performance of the model. The results show that most of the students in the school do not understand the connotation of IPE, and the teachers cannot accurately and deeply teach the relevant ideological and political knowledge to the students. About 73% and 82% of students prefer that teachers can mention life experience and social skills in class. More than 50% of the students are more willing to accept the course ideological and political activities in the form of lectures and competitions. This indirectly shows that the school lacks the above contents in the current course ideological and political teaching, the teaching method is relatively single, and cannot fully mobilize the enthusiasm of students. Further improvement is needed for these problems in the follow-up. The accuracy of expression recognition of this model is more than 2.9% higher than other algorithms, and the improvement effect of the model is remarkable. To sum up, this work fully understands the current teaching situation of the surveyed schools through questionnaire survey, and puts forward corresponding improvement suggestions. The effectiveness of this model is verified by designing experiments, which proves that it is suitable for the research of teaching quality evaluation.
Numerical Investigation of Two In‐Line Two‐Dimensional Bubbles Rising in a Two‐Dimensional Quiescent Ambient Liquid by a Conservative Phase‐Field Lattice Boltzmann Method
Authors: Liao Bin , Yang Zaihe , Chen Shanqun
Published: June 2022

The coalescence and interaction of two in‐line two‐dimensional bubbles rising in viscous ambient liquids were studied using two‐dimensional simulations. A mass‐conserving lattice Boltzmann model that was combined by the phase‐field lattice Boltzmann equation (LBE) and the pressure‐evolution lattice Boltzmann method (LBM) with a multiple‐relaxation‐time (MRT) collision operator was used to solve the Navier–Stokes equations for multiphase flow. Starting from the circle shape, the interfaces of bubbles during the rising processes are captured by the calculation of the conservative phase‐field LBE. The influence of liquid viscosity and interface tension on the coalescence and interaction of bubbles was studied by varying the Archimedes numbers (Ar) from 1 to 300 and several Bond numbers (Bo) from 5 to 200. It was found that the bubble–bubble interaction is enhanced with the decrease of the liquid viscosity, and the outcome of the coalescence is promoted by the two vortex rings (liquid circulations) around the two bubbles. A comprehensive map of the coalescence regime was obtained. Four distinct coalescence regimes (namely, Central I, Central II, Edge, and Hug) were identified, and three critical Ar that can distinguish the above four regimes were defined. Moreover, the effects of Ar and Bo on the coalescence time and the relative velocity between the two bubbles were also investigated. The current work enhances the understanding of the coalescence and interaction of bubbles.
Prominin 1 Significantly Correlated with Bone Metastasis of Breast Cancer and Influenced the Patient’s Prognosis
Authors: Yu Cheng-cheng , Wu Yi-nan , Hu Kai-min , Zhang Su-zhan
Published: June 2022

Background. This study is aimed at identifying the important biomarkers associated with bone metastasis (BM) in breast cancer (BRCA). Methods. The GSE175692 dataset was used to detect significant differential expressed genes (DEGs) between BRCA samples with or without BM, and DEG‐related pathways were then explored. Further, we constructed the protein‐protein interaction (PPI) network on GEGs and filtered 5 vital nodes. We then performed the Cox regression, Kaplan‐Meier analysis, nomogram, and ROC curve to filter the most significant prognosis genes. The GSE14020 and GSE124647 datasets were used to verify the expression and prognostic value of hub genes, respectively. Finally, the gene set enrichment analysis (GSEA) was performed to reveal the potential mechanism. Results. Totally, 74 DEGs were detected, which mainly correlated with infectious disease, signaling molecules, and interaction. The 5 important DEGs were then filtered, and the Cox regression further showed that 2 genes, including prominin 1 (PROM1) and C‐C motif chemokine ligand 2 (CCL2), were related to the prognosis of BRCA metastasis patients. Especially, PROM1 presented a better prognostic performance on the survival probability of patients than CCL2. Verification analysis further confirmed the abnormal expression and significant prognostic influence of PROM1. Finally, GSEA revealed that PROM1 was negatively related to IGF1 and mTOR pathways in BRCA metastasis. Conclusion. PROM1 was an important biomarker associated with BRCA bone metastasis and affected the prognosis of metastatic BRCA patients. It may play a vital role in metastatic BRCA by negatively regulating IGF1 and mTOR pathways.
Spatial Distribution and Associated Factors of Institutional Delivery among Reproductive-Age Women in Ethiopia: The Case of Ethiopia Demographic and Health Survey
Authors: Sisay Daniel , Ewune Helen Ali , Muche Temesgen , Molla Wondwosen
Published: June 2022

Background. Maternal mortality is unacceptably high. About 295,000 women died during and following pregnancy and childbirth in 2017. The vast majority of these deaths (94%) occurred in low-resource settings, and most could have been prevented. Methods. This research is based on a cross-sectional study using 2016 EDHS data. The analysis included 7,590 women who had given birth in the five years prior to the survey. Clusters with high and low hot spots with institutional delivery were found using SatScan spatial statistical analysis. A multilevel multivariable mixed-effect logistic regression was utilized to discover characteristics associated with institutional delivery. Result. In this study, 33.25% of women who gave birth in the last 5 years preceding the survey delivered their babies at health institutions. The finding also indicated that the spatial distribution of institutional delivery was nonrandom in the country. Variables achieving statically significant association with utilization of institutional delivery were as follows: at the individual level, richness (AOR = 2.18, 95%CI: 1.39–3.41), higher education (AOR = 3.89, 95%CI: 1.51–10.01), a number of antenatal care visits of four and above (AOR = 6.57, 95%CI: 4.83–8.94), and parity of more than two children (AOR = 0.48, 95%CI: 0.34–0.68); at the community level, higher education (AOR = 1.70, 95%CI: 1.22–2.36) and urban residence (AOR = 5.30, 95%CI: 3.10–9.06) were variables that had achieved statically significant association for utilization of institutional delivery. Conclusions. This study identified a spatial cluster of institutional delivery with the Somali and Afar region having low utilization rates and Addis Ababa and Tigray regions having the highest utilization rates. The significant individual factors associated with institution delivery were woman antenatal care visits, household wealth index, maternal education, and parity, and the significant community ones were region, place of residence, and educational status. Therefore, to maximize health facility delivery in Ethiopia, the predictors of institutional delivery identified in this study should be given more attention by governmental and nongovernmental stakeholders.
The Influence of Robot-Assisted Industry Using Deep Learning on the Economic Growth Rate of Manufacturing Industry in the Era of Artificial Intelligence
Authors: Xu Ziyu
Published: June 2022

The arrival of the era of artificial intelligence (AI) impacts a country’s economic growth. This work was aimed at helping a country achieve high-quality economic growth through AI. First, the penetration effect, boundary extension effect, knowledge creation effect, and self-deepening effect of AI in the process of penetration into the economy and society are analyzed. Then, the labor factors, capital factors, and production technology factors affecting economic growth are discussed. Furthermore, three channels through which AI affects economic growth are proposed: the labor channel, capital channel, and productivity channel. Finally, relevant verifications are carried out. The verification results demonstrate that AI will promote an increase in economic growth rate in the long run but have a specific inhibitory effect in a short time. According to the research results, sound policy suggestions are put forward for the positive impact of AI technology on economic growth, the negative effect on labor employment and income distribution, capital accumulation and capital structure, and the effect on production efficiency. This work has certain reference significance for the research on the economic growth rate of the national manufacturing industry in the era of AI.
Estimating the Geological Strength Index (GSI) in Regional Seismic‐Landslide Zonation Using the Empirical Regression Model
Authors: Mirabedini M. E. , Haghshenas E. , Ganjian N.
Published: June 2022

The assessment of the strength parameters of geological formations in regional scale which encounters thousands of slopes is a complicated approach and time consuming and needs huge field work. This issue is an important research topic concerning the regional seismic‐landslide susceptibility analysis or hazard zonation. An empirical regression model was presented to estimate the Geological Strength Index (GSI) with an implication on geological quadrangle of Gorgan region at Alborz mountains range (north of Iran). Two main sets of data were applied in this study: (1) geomorphological data including the slope height, aspect, and distance from faults and distance from thrusts and (2) the physical and mechanical properties of rocks including the unit weight, uniaxial compressive strength (σci), and the petrographic constant (mί) of intact rock. The first group was extracted from a 1 : 100,000 digital geologic map and 10 m digital elevation model (DEM) and the second group was obtained from the Hoek–Brown failure criterion recommended tables. Linear regression equations were generated applying data collected from 294 studied stations using SPSS software. The regression equation predicted GSI in terms of (1) the distance from faults, (2) the distance from thrusts, and (3) the uniaxial compressive strength (σci). The equation had an R2 value of 0.739 and thus fit well to the data. The new method in its present state was recommended for the estimation of the GSI values in regional scale conditions for the assessment of landslide susceptibility and hazard mapping or post events landslide occurrence prediction in the case of probable big earthquakes in Alborz area that is required for emergency responses. The results indicated that the estimation error was about ±30 while the average error was within +5 and −5 and average error percentage was about 3%.
Long-Term Metabolic Outcomes after Gestational Diabetes Mellitus (GDM): Results from the Odense GDM Follow-Up Study (OGFUS)
Authors: Jacobsen Kristine Hovde , Aalders Jori , Sølling Katrine , Andersen Marianne Skovsager , Snogdal Lena Sønder , Christensen Maria Hornstrup , Vinter Christina Anne , Højlund Kurt , Jensen Dorte Møller
Published: June 2022

Aims. To compare metabolic profiles and the long-term risk of metabolic dysfunction between women with previous gestational diabetes mellitus (pGDM) and women without pGDM (non-GDM) matched on age, prepregnancy body mass index (BMI), and parity. Methods. In total, 128 women with pGDM (median follow-up: 7.8 years) and 70 non-GDM controls (median follow-up: 10.0 years) completed a 2 h oral glucose tolerance test (OGTT) with assessment of glucose, C-peptide, insulin, and other metabolic measures. Additionally, anthropometrics, fat mass, and blood pressure were assessed and indices of insulin sensitivity and beta cell function were calculated. Results. The prevalence of type 2 diabetes mellitus (T2DM) was significantly higher in the pGDM group compared to the non-GDM group (26% vs. 0%). For women with pGDM, the prevalence of prediabetes (38%) and the metabolic syndrome (MetS) (59%) were approximately 3-fold higher than in non-GDM women (

p
’
s
<
0.001

). Both insulin sensitivity and beta cell function were significantly reduced in pGDM women compared to non-GDM women. Conclusion. Despite similar BMI, women with pGDM had a substantially higher risk of developing T2DM, prediabetes, and the MetS compared to controls. Both beta cell dysfunction and reduced insulin sensitivity seem to contribute to this increased risk.
[Retracted] The Mathematical Analysis of the New Fractional Order Ebola Model
Authors: Khan Faiz Muhammad , Ali Amjad , Bonyah Ebenezer , Khan Zia Ullah
Published: June 2022

This research study focuses on the analytical behavior and numerical computation of the fractional order Ebola model. In this study we have calculated the conditions for the existence, uniqueness, and stability of the solution with the help of the fixed point results. In addition to this, we calculated the numerical solution of the fractional order smoke model with the help two‐step fractional Adam’s Bashforth method using the Caputo’s fractional derivative of order μ. Furthermore, the results obtained for different orders of the fractional derivative μ have been shown graphically with the help of Matlab.
Application of Cloud Service-Oriented Heterogeneous Execution Scheduling and VR Technology in Dance Video Teaching
Authors: Min Liu
Published: June 2022

Cloud computing is the result of the revolution in information technology and a massively complex computing system. As a model for business computing, cloud computing aims to facilitate resource sharing and collaborative work, meet the service needs of users, and generate revenue for cloud service providers. How to reasonably allocate cloud resources, efficiently manage and schedule massive application tasks in real time, reduce the cost of users, and increase the income of cloud service providers on the basis of ensuring the load balance of the cloud computing system and enhancing the utilization of cloud resources is, therefore, one of the research hotspots in the current cloud computing environment. Simultaneously, with the rapid development of human motion simulation and virtual reality technologies, the natural cooperation between humans and computers has become the primary focus of computer science research. The motion capture system is able to track, detect, capture, and record real-time human motion. By analyzing the captured three-dimensional data, we can determine the various characteristics of human motion posture at various times. Due to the potential research and practical value of motion capture technology, it is predominantly used in cutting-edge fields such as animation video production, rehabilitation medicine, sports training, and game software development, thereby effectively realizing the connection between the three-dimensional world and the real world. However, the combination of motion capture technology and educational activities is not universally applicable. This research proposes an approach to dance posture analysis based on matching feature vectors, which can be applied to dance teaching and significantly improves the quality of education and teaching activities. For the purpose of this study, it will be determined whether the combination of dance instruction-based motion capture technology and education is effective and feasible.
Optimisation of Malting Parameters for Quinoa and Barley: Application of Response Surface Methodology
Authors: Chawanda Esther Tatenda , Manhokwe Shepherd , Jombo Talknice Z. , Mugadza Desmond T. , Njini Michael , Manjeru Pepukai
Published: June 2022

Quinoa (Chenopodium quinoa Willd) is a nutritious pseudocereal that is more stress-tolerant compared with traditional cereals. It is an excellent example of a climate-smart crop that is more resilient to climate change compared with barley. The purpose of the study was to investigate the optimum malting conditions required to produce quinoa malt using barley as a control. Response surface methodology (RSM) was used to investigate the influence of the two malting parameters steeping time and germination time on Brix (wort extract), diastatic power (DP), and free amino nitrogen (FAN) of the malt. The temperature was set at 15°C during the steeping process. Steeping time ranging from 12 to 48 hours and germination time ranging from 24 to 96 hours were designed using a central composite design (CCD). The kilning temperature for all malts was 65°C. For quinoa malt, there was a notable weak positive correlation between germination time and Brix (r = +0.119). However, there was a strong positive correlation between steeping time and diastatic power (r = +0.893). A similar trend was noted for barley with a weak positive correlation between germination time and Brix (r = +0.142). A strong positive correlation was also recorded between steeping time and diastatic power (r = +0.897) during the malting of barley. There was a relatively stronger correlation between steeping time and FAN (r = +0.895) than germination time and FAN (r = +0.275) in quinoa malt. The optimum values for the malting of barley were 47.68 hrs steeping time and 82.55 hrs germination time with a desirability value of 1.00. The responses for the optimised barley malt were 8.25°Bx, 162.28 mg/L, and 271.69°L for Brix, FAN, and diastatic power, respectively. To produce quinoa malt with Brix, FAN, and diastatic power of 8.37°Bx, 165.60 mg/L, and 275.86°L, respectively, malting conditions of 47.69 hrs steeping time and 95.81 hrs germination time are required. It was noted that quinoa is a very good candidate for producing high-quality malt for the brewing process.
Diagnostic Efficacy of CT Radiomic Features in Pulmonary Invasive Mucinous Adenocarcinoma
Authors: Sheng Aizhu , Zhou Pengfei , Ye Yizhai , Sun Keda , Yang Zhenhua
Published: June 2022

In order to solve the problem of the effect of CT images on the diagnosis of lungs, the authors proposed a method for the diagnosis of invasive mucinous adenocarcinoma of the lungs based on CT radiomic features, and the modified method is found by reviewing past cases: among the 34 cases of primary pulmonary lymphoma, 12 cases were nodular mass type, 19 cases were nonnodular mass type, and 3 cases were mixed type; 13 cases involved bilateral lung lobes, 7 cases involved right lung, and 4 cases involved left lung example. There were 17 cases of tumor consolidation density shadow, 17 cases of mixed density shadow, the average CT value was about 32HU, 15 cases of cavitation sign, 6 cases of cavity, 9 cases of angiography sign, 30 cases of air bronchus sign, 22 cases of bronchiectasis, bronchial stenosis or amputation in 8 cases, pleural effusion in 12 cases, lymph node enlargement in 15 cases, and pleural metastasis in 2 cases. The final pathological results included 24 cases of membrane-associated lymphoid tissue (MALT) lymphoma, 9 cases of diffuse large B-cell lymphoma (DLBCL), and 1 case of T-cell lymphoma. The CT manifestations of primary pulmonary lymphoma (PPL) are diverse and do not have obvious specificity, the imaging manifestations are correlated with pathological types, and air bronchial signs, bronchiectasis, angiography signs, and other signs are used for the diagnosis of PPL. This is of great significance for the diagnosis of PPL.
Step-by-Step Multi-Ship Collision Avoidance Navigation Path Planning Based on Particle Swarm Optimization
Authors: Zhao Canglong
Published: June 2022

In order to solve the problem that it is difficult to combine path planning with navigation rules in the process of multi-ship collision avoidance in wide waters, a step-by-step multi-ship collision avoidance path planning algorithm is proposed in this paper. Firstly, the obstacle ship is regarded as a static obstacle, and the static path planning is carried out by using the particle swarm optimization path planning algorithm in polar coordinate space combined with the field of ship safety to obtain the turning point of ship collision avoidance. Then, the steering angle of the steering point is dynamically corrected by using the navigation rules. The experimental results show that the particle swarm optimization algorithm finds an optimal path in about 35 iterations, and the shortest path is 38.4 n miles. Conclusion. The algorithm can solve the problem of multi-ship collision avoidance path planning and provide a new idea for solving the problem of multi-ship collision avoidance.
Stress-Strength Reliability and Randomly Censored Model of Two-Parameter Power Function Distribution
Authors: Liu Yang , Khan Majid , Anwar Syed Masroor , Rasheed Zahid , Feroze Navid
Published: June 2022

The power function distribution is a flexible waiting time model that may provide better fit for some failure data. This paper presents the Bayes estimates of two-parameter power function distribution under progressive censoring. Different progressive censoring schemes have been used for the analysis. The Bayes estimates are obtained, using conjugate priors, under five loss functions including square error, precautionary, weighted, LINEX, and DeGroot loss function. The Gibbs sampling algorithm and Tierney and Kadane’s Approximation are used for the Bayes estimates of model parameters, reliability function, and stress-strength reliability. The comparison of the Bayes estimates is considered through the root mean squared errors. One real-life dataset is analyzed to illustrate the applications of proposed estimates. The results from the simulation study and real data analysis suggest that the Bayes estimation was more efficient for the progressive censoring schemes with all the withdrawals at the time of first failure.
Construction of College English Teaching Information Resource Integration Model Based on Fuzzy Clustering Algorithm
Authors: Deng Hua
Published: June 2022

The existing college English teaching information resource integration methods have problems of low recall rate, low accuracy rate, and long integration time. Therefore, this paper constructs a college English teaching information resource integration model based on fuzzy clustering algorithm. The ant colony algorithm is used to optimize the topic crawler, the optimized topic crawler is used to collect the college English teaching information resources in the mixed teaching mode, and the weight and naive Bayes algorithm are combined to classify the collected resources. According to the results of resource classification, fuzzy clustering algorithm is used to construct the integration model of college English teaching information resources. The experimental results show that the recall rate of the proposed model is more than 95%, the accuracy rate is more than 94%, and the average resource integration time is only 0.71 s, indicating that the model has relatively reliable performance.
Integrated Learning-Based Algorithm for Predicting Graduates’ Employment Mental Health
Authors: Dongrui Chen , Shengjie Wang , Kate Wen
Published: June 2022

Adaboost is a mental health prediction method that utilizes an integrated learning algorithm to address the current state of mental health issues among graduates in the workforce. The method first extracts the features of mental health test data, and after data cleaning and normalization, the data are mined and analyzed using a decision tree classifier. The Adaboost algorithm is then used to train the decision tree classifier for multiple iterations in order to improve its classification efficiency, and a mental health prognosis model is constructed. Using the model, 2780 students in the class of 2022 at a university were analyzed. The trial results demonstrated that the strategy was capable of identifying sensitive psychological disorders in a timely manner, providing a basis for making decisions and developing plans for mental health graduate students.
Intelligent Storage Data Classification System Based on the BP Neural Network
Authors: Li Minghui
Published: June 2022

In order to solve the problem of multifeature recognition and classification of many kinds of pests, this study puts forward a method of pest feature classification using the BP neural network. Through the preprocessing of stored grain pest images, five characteristic parameters are obtained and optimized and input into the BP network for training. The experimental results show that sample 3 of flat grain thief and sample 4 of bark beetle are not well recognized. Because these two kinds of pests have small bodies and thin legs, some detailed features are eliminated after image processing, resulting in a low recognition rate. But the overall recognition rate can reach 95%. Conclusion. The experiment has obtained good recognition results. This method is accurate and effective for the classification and recognition of stored grain pests and provides a scientific basis for the scientific decision-making of controlling stored grain pests.
Mechanical Properties of the Shear Failure of Rock Masses with Prefabricated Sinusoidal Fractures
Authors: Tian Limei , Zhang Hongzhou , Hong Wei , Zhang Yunxia , Zhang Jinghua , Tan Wenhui
Published: June 2022

A large number of sinusoidal fractures exist in the open‐pit slopes of mines, and the mechanical properties of shear failure are of great significance to the stability of the open‐pit slope. Sandstone specimens containing sinusoidal fractures with different undulated heights were prefabricated by the CNC sand‐wire‐electrode cutting technology to explore the effect of sinusoidal fractures on the mechanical properties of shear failure of rock masses. The TFD‐20H/50J rock shear testing machine was used for shear tests on sinusoidal‐fracture sandstone with different undulated heights. In the shear loading process, the prefabricated‐fracture sandstone specimens with different undulated heights have the fracture‐compacting stage, linear‐elastic changing stage, bottom‐up stage, and residual strength stage. Before peak strength, the sinusoidal prefabricated‐fracture rock masses with different undulated heights have the precursory characteristics of decreased stress, which can provide an early warning for the instability and failure of rock masses. The undulated height of sinusoidal fractures significantly affects the fracture initiation and propagation of specimens. Fractures occur and develop from the prefabricated fractures at low undulated height (≤10 mm) to multiple ways under the high undulated height (>10 mm); that is, fractures occur at the prefabricated fractures and the end of specimens simultaneously. With the increased undulated height, the fractures expand from parallel to the slope of the prefabricated fractures to perpendicular to the prefabricated fractures. The fracture propagation direction of sinusoidal‐fracture rock masses with different undulated heights is mainly from the middle of the slope surface of prefabricated fractures to the end. It is the main direction of the shear failure of sinusoidal prefabricated fractures, and the monitoring of weak planes should be strengthened in the actual slope engineering.