bluuebunny/crossref_metadata_2025 huggingface dataset:
Image Fusion and Stylization Processing Based on Multiscale Transformation and Convolutional Neural Network
Authors: Xu Qingzeng
Published: April 2022

With the continuous development of imaging sensors, images contain more and more information, the images presented by different types of sensors are different, and the images obtained by the same type of sensors under different parameters or conditions are also different. Multisource image fusion technology combines images acquired by different types of sensors or the same type of sensors with different parameter settings, which makes the image information more complete, compensates for the limitations of images of the same type, and also allows you to save information about the characteristics of the original image. Multimodal image mosaic and multifocal image mosaic have been studied in detail in two directions. On the one hand, a method based on frequency domain transformation is used for multiscale image decomposition. On the other hand, image extraction with neural network-based methods is proposed. The technology of convolutional neural networks (CNNs) allows to extract richer texture features. However, when using this method for fusion, it is difficult to obtain an accurate decision map, and there are artifacts in the fusion boundary. Based on this, a multifocal fusion method based on a two-stage CNN is proposed. Train the advanced intensive network to classify input image blocks as focus, and then use the appropriate merge rules to get the ideal decision tree. In addition, several versions of the fuzzy learning set have been developed to improve network performance. Experimental results show that the frames of the first stage proposed by the algorithm make it possible to obtain an accurate decision scheme and that the frames of the second stage make it possible to eliminate the pseudo-shadow of the integration boundary.
Effect of Carbon on the Emission Performance of Tungsten Electrode Electron in Gas Discharge Lamps
Authors: Wang Luyan , Yu Yueguang , Dong Jianxin , Zhang Yuqing , Liu Shanyu , Li Caobing
Published: April 2022

Tungsten electrodes are widely used as electric light sources because of their excellent performance. Impurity elements, such as carbon, can be easily introduced during the preparation of lamp tubes; therefore, it is necessary to analyze the influence of carbon impurities on the performance of gas discharge lamps and propose reasonable solutions. In this study, we investigated the manner in which carbon enters a gas discharge lamp and compared the electron emission properties of carbon and noncarbon electrodes through extensive experiments. The results showed that the current density was reduced by more than 50% at 1450°C, and the most obvious change was 75.00%. Furthermore, we propose a detailed solution for the introduction of carbon, which provides technical support for the quality control of gas discharge lamps.
A Research on the Realization Algorithm of Internet of Things Function for Smart Education
Authors: Fu Kuiliang
Published: April 2022

The traditional teaching mode is to use a point-to-point mode or a computer-aided system for teaching, but this limits students’ enthusiasm and interest in learning. The Internet of Things (IoT) technology is a technology that integrates sensors, the Internet, and terminals to transmit information in real time. The smart education based on the Internet of Things can realize remote teaching and actual scene teaching, and students can freely choose the learning location and time, which can greatly improve students learning interest and learning efficiency, which is a development trend of a new teaching method. Smart IoT teaching is a teaching method that combines IoT technology and artificial intelligence technology. This paper mainly studies the research and analysis of the smart education model based on the IoT in remote teaching. In this paper, sensor technologies such as cameras will be used to collect students’ expressions, speech, and other actions in class from different regions. These data features will be processed by the terminal’s intelligent algorithm, and the desired knowledge will be obtained according to the students’ behavior information. The information processed by the intelligent algorithm will be transmitted to the terminal system where the teacher is located, such as computer and mobile phone. This paper focuses on analyzing the reliability and accuracy of the intelligent algorithm of the IoT smart education terminal. The results show that the prediction error of the student behavior information is within 3% and the correlation coefficient reaches 0.99.
In Vivo Bioactivities of Hoya parasitica (Wall.) and In Silico Study against Cyclooxygenase Enzymes
Authors: Sarkar Kishore Kumar , Mitra Trina , Rahman Md Asibur , Raja Iqbal Mahmud , Aktaruzzaman Md , Abid Md Ahsan , Zilani Md Nazmul Hasan , Roy Debendra Nath
Published: April 2022

Hoya parasitica (Wall.) is extensively used in traditional medicine for the treatment of various diseases including rheumatism, kidney problems, jaundice, urinary tract disorders, fever, and pain. The present study was designed to explore new lead compound(s) to alleviate pain, pyresis, and diarrhea from methanol, ethyl acetate, and n‐hexane extracts of H. parasitica (Wall.) leaves (MHP, EAHP, and NHP, respectively). Analgesic activity of the extracts was assessed through acetic acid induced writhing, tail immersion, and hot plate tests while brewer’s yeast‐induced pyrexia test was employed for the assessment of antipyretic activity. Besides, castor oil and magnesium sulfate induced diarrheal tests were utilized for the evaluation of antidiarrheal properties. Moreover, in silico study of the isolated compounds was undertaken to seek out best‐fit phytoconstituent(s) against cyclooxygenase enzymes. MHP revealed substantial antioxidant activities in different in vitro assays compared to EAHP and NHP. In the acetic acid‐induced writhing test, among the extracts, MHP (400 mg/kg) revealed maximum 74.15 ± 1% inhibition of writhing comparable to that of standard (85.77 ± 1.39%). Again, in tail immersion and hot plate tests, higher doses of all the test samples exhibited a significant increase of latent period in a time‐dependent manner. In brewer yeast‐induced pyrexia test, at 3rd and 4th hour of treatment, significant (P < 0.05) antipyretic action was found in the test samples. In both castor oil and magnesium induced diarrheal tests, MHP at 400 mg/kg showed the highest percent inhibition of diarrhea (68.62 ± 4.74 and 64.99 ± 2.90, respectively). Moreover, molecular docking analysis corroborated the results of the present study. The findings of the present study supported the traditional uses of this plant for the alleviation of pain and fever. Furthermore, hoyasterone was found to be the most effective lead compound as cyclooxygenase enzyme inhibitor.
Cross-Border E-Commerce Logistics Collaboration Model Based on Supply Chain Theory
Authors: Xie Cuijie , Wang Haijuan , Jiao Jianhong
Published: April 2022

With the rapid development of cross-border e-commerce, however, logistics has become a bottleneck in the development of cross-border electricity traders. The results of studies on cross-border e-commerce logistics are still less, and the relevant theoretical studies are not yet mature enough. As cross-border e-commerce occupies a share of foreign trade in foreign trade increases, so does their influence. In order to eliminate bottlenecks in the cross-border logistics of an electric enterprise, it is of great importance to systematically study the issues of synergy in the logistics of the supply chain of a cross-border electric enterprise and validate how cross-border traders and cross-border logistics work together using cross-border discussion based on the perspective of cross-border e-commerce ecosystem. At the same time, an analysis of the need for cross-border logistics collaboration electricity traders and cross-border logistics is being carried out, as well as an in-depth study of synergy mechanisms between cross-border electricity traders and cross-border logistics based on a cross-border ecosystem perspective. The empirical results show that cross-border logistics is available function service capability; cross-border logistics information sharing level, cross-border logistics resource optimization and allocation capability, and the opening level of cross-border logistics environment have different contributions to the impact on the efficiency of cross-border e-commerce logistics. Among them, the level of cross-border logistics information exchange has the most significant influence on the logistics efficiency of cross-border traders, followed by cross-border logistics functional services capabilities, again the level of openness of the cross-border logistics environment, and finally, the ability to optimally distribute cross-border logistics resources.
Cholesterol Promotes Colorectal Cancer Growth by Activating the PI3K/AKT Pathway
Authors: Wu Cheng , Wang Ming , Shi Hui
Published: April 2022

Globally, the incidence of colorectal cancer (CRC) increases each year, with an unhealthy diet representing one of the major pathogenic risk factors for CRC. Cholesterol is a vital dietary ingredient required to maintain the normal function of the body; however, disturbances in cholesterol levels have been discovered to exert a significant role in tumorigenesis. The present study is aimed at investigating the role of cholesterol in the occurrence of CRC. Briefly, CRC model mice were established through an intraperitoneal injection of azoxyemethane (AOM) and were subsequently either fed a normal diet (ND), high-fat diet (HFD), or high-fat high-cholesterol diet (HFHC). Furthermore, in vitro experiments were performed following the treatment of SW480 and HCT116 cells with cholesterol, and the cell viability and colony formation rate of CRC cells were analyzed. The findings identified that cholesterol levels were increased in CRC tissues compared with adjacent normal tissues. In contrast, the serum levels of cholesterol were decreased in patients with CRC compared with the healthy controls; however, no significant differences were observed in the cholesterol levels between

stage
 
I
+
II

and

stage
 
III
+
IV

patients with CRC. Notably, CRC model mice fed with an HFD or HFHC recorded a larger body weight compared with those mice fed a ND; however, no significant differences were reported in the number of tumors formed in each group. Furthermore, the tumor size in the HFHC group was discovered to be increased compared with the ND and HFD groups, and HGD and the pathological morphology were the most pronounced in the HFHC group. Moreover, mice in the HFHC group presented the highest ratio of Ki-67-positive staining and the lowest ratio of TUNEL-positive staining compared with those in the two other groups. Cholesterol treatment also increased the cell viability and clonality of SW480 and HCT116 cells. In addition, the protein expression levels of phosphorylated-AKT were upregulated in cholesterol-induced CRC cells and tissues, whereas the treatment with BAY80-6946 attenuated the cholesterol-induced increases in the cell viability, colony formation ability, and tumor size. In conclusion, the findings of the present study suggested that cholesterol may stimulate the progression of CRC by activating the PI3K/AKT signaling pathway; however, cholesterol may not affect the number of tumors formed in CRC. In addition, cholesterol was discovered to mainly affect the advanced stages of CRC rather than the early stages.
Baseline Plasma Gas6 Protein Elevation Predicts Adverse Outcomes in Hospitalized COVID-19 Patients
Authors: Tonello Stelvio , Rizzi Manuela , Matino Erica , Costanzo Martina , Casciaro Giuseppe Francesco , Croce Alessandro , Rizzi Eleonora , Zecca Erika , Pedrinelli Anita , Vassia Veronica , Landi Raffaella , Bellan Mattia , Castello Luigi Mario , Minisini Rosalba , Mallela Venkata Ramana , D’Onghia Davide , Avanzi Gian Carlo , Pirisi Mario , Lilleri Daniele , Sainaghi Pier Paolo
Published: April 2022

Reliable biomarkers allowing early patients’ stratification for the risk of adverse outcomes in COVID-19 are lacking. Gas6, together with its tyrosine kinase receptors named TAM, is involved in the regulation of immune homeostasis, fibrosis, and thrombosis. Our aim was to evaluate whether Gas6, sAxl, and sMerTK could represent early predictors of disease evolution either towards a negative (death or need of ICU admission) or a positive (discharge and/or clinical resolution within the first 14 days of hospitalization) outcome. To this purpose, between January and May 2021 (corresponding to third pandemic wave in Italy), 139 consecutive SARS-CoV-2 positive patients were enrolled in a prospective observational study. Plasma levels of these molecules were measured by ELISA at the time of hospitalization and after 7 and 14 days. We observed that higher plasma Gas6 concentrations at hospital admission were associated with a worsening in clinical conditions while lower sMerTK concentrations at baseline and after 7 days of hospitalization were associated with a more favorable outcome. At multivariate analysis, after correction for demographic and COVID-19 severity variables (NEWS2 and PiO2/FiO2), only Gas6 measured at baseline predicted an adverse prognosis with an odds ratio of 1.03 (C.I. 1.01-10.5). At ROC curve analysis, baseline Gas6 levels higher than 58.0 ng/ml predicted a severe disease evolution with 53.3% sensitivity and 77.6% specificity (area under the curve 0.653,

p
=
0.01

, likelihood ratio of 2.38, IQR: 1.46-3.87). Taken together, these results support the hypothesis that a dysregulation in the Gas6/TAM axis could play a relevant role in modulating the course of COVID-19 and suggest that plasma Gas6 may represent a promising prognostic laboratory parameter for this condition.
Andrographolide Suppresses Pyroptosis in Mycobacterium tuberculosis-Infected Macrophages via the microRNA-155/Nrf2 Axis
Authors: Fu Yan , Shen Jingjing , Liu Fanglin , Zhang Hemin , Zheng Yuejuan , Jiang Xin
Published: April 2022

Tuberculosis (TB) remains a leading threat to public health worldwide with Mycobacterium tuberculosis (Mtb) infections causing long-term abnormal and excessive inflammatory responses, which in turn lead to lung damage and fibrosis, and ultimately death. Host-directed therapy (HDT) has been shown to be an effective anti-TB strategy in the absence of effective anti-TB drugs. Here, we used an in vitro macrophage model of Mtb infection to evaluate the effects of andrographolide (Andro), extracted from Andrographis paniculata, on pyroptosis in Mtb-infected macrophages. We evaluated the molecular mechanisms underlying these outcomes. These evaluations revealed that Andro downregulated the expression of proinflammatory miR-155-5p, which then promoted the expression of Nrf2 to suppress pyroptosis in Mtb-infected macrophages. Further study also demonstrated that siNrf2 could attenuate the inhibitory effect of Andro on TXNIP, validating our mechanistic studies. Thus, our data suggest that Andro may be a potential candidate adjuvant drug for anti-TB therapy as it inhibits pyroptosis in Mtb-infected macrophages, potentially improving clinical outcomes.
A New Generalized-
X
Family for Analyzing the COVID-19 Data Set: a Case Study
Authors: Xin Yue , Zhou Yinghui , Mekiso Getachew Tekle
Published: April 2022

Nowadays, researchers in applied sectors are highly motivated to propose and study new generalizations of the existing distributions to provide the best fit to data. To provide a close fit to data in numerous sectors, a series of new distributions have been proposed. In this study, we propose a new family called the new generalized-

X

(for short, “NG-

X

”) family of distributions. Based on the NG-

X

method, a novel modification of the Weibull model called the new generalized-Weibull (for short, “NG-Weibull”) distribution is studied. The heavy-tailed characteristics of the NG-

X

distributions are derived. The maximum likelihood estimators of the NG-

X

distributions are also obtained. Based on the special case (i.e., NG-Weibull) of the NG-

X

family, a simulation study is provided. The practical performance of the new NG-Weibull model is assessed by analyzing the COVID-19 data set. The fitting results of the NG-Weibull model are compared with three other competing models. Based on certain statistical measures, it is observed that the NG-Weibull model is the best competitive model.
Employment Recommendation for Education Talents Based on Big Data Precision Technology
Authors: Jiang Xiuqin , Maia Darchia
Published: April 2022

The cornerstone of future social education is the development of skills. This work enhances the big data algorithm and presents an effective association algorithm that may boost relevance in order to improve the accuracy of educational talent employment. Furthermore, this paper employs data mining association analysis technology to identify educational talent attributes that are disproportionately important in determining the problem of student employment, as well as to eliminate attributes that are unrelated to the problem, in order to achieve the goal of screening educational talent attributes. In addition, this paper combines an improved algorithm to build an education talent employment recommendation system, builds a system function structure based on the actual situation, and combines experimental research to verify the effect of the model built in this paper. From the experimental research, it can be seen that the education talent employment recommendation system based on big data precision technology constructed in this paper can play an important auxiliary role in the education talent employment recommendation.
Genetic Characteristics of Resectable Colorectal Cancer with Pulmonary Metastasis
Authors: Qiu Yan-Yu , Peng Dong , Wei Zheng-Qiang , Li Jin-Dou , Huang Yong-Jia , Yang Jian-Guo , Song Zhi-Yang , Cheng Yong
Published: April 2022

The lung is the most common extra-abdominal metastasis site of colorectal cancer (CRC). This study aimed to investigate the genetic variation of pulmonary metastases (PM) and primary tumors in resectable CRC. The clinical data of 410 patients with PM after CRC surgery and 33 paraffin-embedded tissue samples from January 2012 to July 2019 in our hospital were collected retrospectively. Next, 450-panel gene detection technologies based on next-generation sequencing (NGS) were used to analyze the changes in the gene map and the overall variation in cancer-related genes in PM and primary tumors. After quality control, 19 samples were included in the final gene analysis. The results showed that APC (89.5%), TP53 (89.5%), and KRAS (53%) were the most common mutations in PM and primary tumors, but the gene amplification variation was enriched in primary tumors (4.6% vs. 11.4%). KRAS G12D was the most common site variation of the KRAS gene in both PM and primary tumors of CRC. There was no hotspot mutation in the TP53 locus in CRC, and the TP53 mutation in the PM was consistent with that in the primary lesion. The microsatellite instability (MSI) levels of 10 patients were MSS. The mean tumor mutation burden (TMB) of the primary tumor (5.3 muts·Mb−1) was slightly higher than that of metastasis (5.0 muts·Mb−1). In our institution, the genetic characteristics of resectable PM from CRC may be highly consistent with those of the primary tumor.
Quality Evaluation for Physical Education Teaching in Colleges with Joint Neural Network
Authors: Li Yiliang
Published: April 2022

A new teaching curriculum for physical education in colleges has been proposed as part of the teaching reform. New developments in content, goals, and teaching methods have also occurred, and these have gradually become the focus of current physical education researchers. By developing a model for objectively, truly, comprehensively, and accurately evaluating college physical education teaching, it will be possible not only to improve the quality of physical education instruction and the effectiveness of faculty in achieving their goals but also to improve the quality of programs. This research work proposes a Joint Neural Network (JNN) composed of an Improved Support Vector Machine (ISVM) and improved Back Propagation (BP) network for evaluating physical education quality in colleges. When using a standard SVM to classify feature data, the parameters used have an impact on the SVM’s classification. This study introduces an improved SVM with hybrid optimization of PSO and GA algorithms, combining the properties of genetic algorithms and particle swarm optimization. As the existing BP network is trapped with a local optimum, this work proposes an optimized BP network algorithm using the bat algorithm. The improved SVM and improved BP are then combined to form a joint neural network for evaluating the quality of physical education in colleges. Comprehensive and systematic experiments validate the correctness and effectiveness of the algorithm proposed in this paper.
IL2RB Is a Prognostic Biomarker Associated with Immune Infiltrates in Pan-Cancer
Authors: Li Guangyao , Wang Yandong , Cheng Ya
Published: April 2022

Background. Interleukin-2 receptor β (IL2RB) is a receptor protein of interleukin-2. IL2RB is implicated in regulation of T cell-mediated immune response. However, the role of IL2RB in pan-cancer is unknown. The present premise sought to explore the role of IL2RB in tumorigenesis, tumor metabolism, and tumor immunity in pan-cancer. Methods. Data were retrieved from multiple data resources including GTEx data resource, CCLE data resource, TCGA data resource, UCSC data resource, and TISIDB web server. These data were adopted to assess the expression, prognosis value, relationship between IL2RB and immune microenvironment, microsatellite instability, immune new antigen, gene mutation, immune modulatory factors immune checkpoint and TMB, and immune or molecular subtypes of IL2RB in various tumors. Estimate analysis and GSEA were conducted to assess the role of IL2RB in pan-cancer. Results. Differential analysis illustrated that L2RB was remarkably elevated in pan-cancer, notably in solid tumors compared with normal tissues. Survival analysis indicated that IL2RB was linked to pan-cancer prognosis, and elevated IL2RB contents were remarkably linked to dismal prognosis patients in diverse kinds of cancers. The findings illustrated that IL2RB contents were remarkably linked to tumor immune invasion, tumor microenvironment, TMB, MSI, DNA repair genes, methyl transferases, immune modulatory factors, and immune or molecular subtypes in pan-cancer. IL2RB gene mutation was evident in numerous cancers. The data illustrated that IL2RB contents were remarkably enriched in multiple signaling cascades which modulate tumorigenesis, tumor metabolism along with immunity. Conclusion. The findings of the present premise illustrate that IL2RB plays an indispensible role in tumorigenesis, tumor metabolism, and immunity. Therefore, it is a prospective target gene in tumor-target therapy and tumor immune therapy. IL2RB is also a valuable predictive biomarker in most solid tumors.
Human-Wildlife Conflict in Save Valley Conservancy: Residents’ Attitude Toward Wildlife Conservation
Authors: Makumbe Peter , Mapurazi Stenly , Jaravani Sostina , Matsilele Isaac
Published: April 2022

Human settlement in protected areas (PAs) is a major conservation concern in developing nations as it fuels human-wildlife conflicts (HWCs). The objectives of this study were to (i) determine the key wildlife species causing conflict, (ii) assess the perceptions of residents toward the major causes of conflict with wildlife, and (iii) evaluate the attitudes of residents toward problem animals. We conducted face-to-face semistructured interviews and two reconnaissance field surveys with 290 respondents residing in Save Valley Conservancy (SVC), in Southeast Lowveld Zimbabwe from January 2014 to June 2014. Results showed that lions (Panthera leo), spotted hyenas (Crocuta crocuta), elephants (Loxodonta africana), and Nile crocodiles (Crocodylus niloticus) were the major animals involved in the conflict. Our results also showed that the land-use change from wildlife ranching to farming and contested land ownership were perceived as the major causes of HWCs. Respondents who had lived in the area longer were more likely to agree that change in land use (Ordinal logistic regression: B = 1.32, Odds Ratio (OR) = 3.74) and contested land ownership (B = .67, OR = 1.95) were major sources of conflict. In addition, increased encounters between people and wildlife triggered mixed attitudes toward problem animals. For example, males were less likely to have a negative attitude toward problem animals compared to females (Multinomial logistic regression: B = −1.39; OR = .25). Residents who had stayed for less than five years were more likely to have a negative attitude toward problem animals than those who had stayed longer (B = 3.6; OR = 36.71). These results suggest that there is a need to relook at the resettlement pattern because coordinating HWCs and implementing sustainable conservation objectives are easy in a well-planned settlement. Stakeholders need to come together and create awareness of the use of HWCs mitigations measures.
Protective Effects of Curcumin-Regulated Intestinal Epithelial Autophagy on Inflammatory Bowel Disease in Mice
Authors: Hong Jianhua
Published: April 2022

Objective. This study was aimed at exploring the ameliorating effect of curcumin (Cur) on inflammatory bowel disease (IBD) in mice induced by 3% dextran sodium sulfate (DSS) by regulating intestinal epithelial cell autophagy. Methods. 45 BALB/c mice were randomly divided into three groups: control group, DSS group, and Cur group, with 15 mice in each group. Expect for the control group, 3% DSS was freely drunk by the mice for 7 days to induce acute IBD, and the Cur group was given Cur gavage treatment. Hematoxylin-Eosin (HE) staining was performed to observe the pathological changes of mice colon tissue. The formation of autophagosomes in intestinal epithelial cells was detected by transmission electron microscopy (TEM). The protein expressions of LC3-II/LC3-I, p62, and Beclin1 were detected by Western blot. Results. Compared with that of the control group, body weight of mice in DSS group was significantly reduced, stool was not formed or presented with loose stools, there was occult blood or blood in the stool, hair color lost luster, disease activity index (DAI) score was significantly increased, and colonic mucosal epithelial cells showed colitis; LC3-II/LC3-I and Beclin1 expression were significantly decreased (

P
<
0.05

), p62 was significantly increased, and autophagy was not obvious. In addition, compared with that of the DSS group, the diet of mice in the Cur group was improved, the decline of body weight was slowed down, the hair glossiness was restored, the blood in the stool gradually decreased or occulted, the DAI score was decreased, the colon tissue was significantly improved, the expressions of LC3-II/LC3-I and Beclin1 were significantly increased (

P
<
0.05

), and the p62 was significantly decreased. Conclusions. The effect of Cur on IBD mice was related to the regulation of the expression of autophagy pathway proteins LC3-II/LC3-I, Beclin1, and p62 in intestinal epithelial cells.
Temporal Trend and Regional Disparity of Agricultural Green Total Factor Productivity in China: Data Envelopment Analysis with Biennial Environmental Technology
Authors: Huang Xiuquan , Wang Xi , Chen Baoxin , Li Fanbo , Su Shaodan , Zhang Tao
Published: April 2022

This paper investigates the temporal trend and regional disparity of China’s agricultural green total factor productivity (AGTFP) during 1997‐2016. Combined with the green Luenberger productivity indicator, two different data envelopment analysis models with the biennial environmental technology are constructed for robust checks. Compared with the existing literature, more agricultural carbon emissions are used as the undesirable outputs in the models. It is found that AGTFP in the whole of China and all of its sub‐regions (the east, the middle, and the west) showed an overall increase, with the drive of high technical progress. The east had the largest AGTFP, and the middle experienced the largest AGTFP growth. More specifically, with respect to AGTFP, the total difference and the gross difference among the three regions as well as the specific difference within regions widened during these periods. There was an absolute convergence trend of AGTFP in the whole of China as well as the middle and the west. The speed of convergence was highest in the west.
Efficient Hyperchaotic Image Encryption Algorithm Based on a Fast Key Generation Method and Simultaneous Permutation-Diffusion Structure
Authors: Ge Bin , Chen Gang , Chen Xu , Shen Zhihua
Published: April 2022

To provide faster encryption speed for protecting image data privacy, a highly efficient hyperchaotic image encryption algorithm using a fast key generation method and simultaneous permutation-diffusion structure is proposed in this paper. Firstly, we design a novel fast key generation method to obtain four key matrixes with the size of W × H (W and H are the width and height of an image) with the hyperchaotic Lorenz system only iterating 2W times. And within the key generation process, the piecewise linear chaotic map serves as a random selector to further enhance the randomness and unpredictability. Secondly, we introduce vectorization technique to parallelize the cipher blockchain-based encryption process. Hence, an image can be fast and sufficiently encrypted row by row and column by column through a four-round and interlinked diffusion process. Furthermore, during the diffusion process, the pixels are simultaneously scrambled by the Chebyshev map to enhance the antiattack capability of the proposed algorithm. Thirdly, we utilize a secure hash function to generate a plaintext-related secret key. Finally, cipher images can successfully pass common security tests with the correlation coefficients on the verge of 0, the entropies are greater than 7.99, and NPCR and UACI values are close to the expected values. Combined with other experimental results and analysis, we can safely conclude that the proposed algorithm has strong robustness against statistical, brute-force, differential, and some other common attacks. Moreover, only 0.009 s of encrypting a 256 × 256 image indicates that our algorithm has extensive application prosperity for real-time communications of massive digital images.
Research and Application of 3D Clothing Design Based on Deep Learning
Authors: Cao Chunnan
Published: April 2022

In order to fully explore the multi-scale features of 3D clothing design, at the same time, so as to realize the extraction of the clothing itself and the overall characteristics of the clothing, a research and application of 3D clothing design based on deep learning is proposed. Deep learning neural network model is applied to recognize 3D human shape features, the characteristic line is obtained by the threshold judgment, feature points are obtained based on the identified feature lines, the body circumference curve is fitted, and the measurement of human body size is realized. Simulation results show that for the training of convolutional neural networks in the research of feature recognition algorithms the final feature recognition accuracy is made to reach 92.56%. The training network based on the front projection has a good recognition effect for the neck, armpit, and waist, while the side projection has a good recognition effect for the back neck, shoulder, chest, waist, and buttocks. In general, the characteristic lines of the key parts of the human body have been effectively identified. The author uses convolutional neural networks in deep learning, carrying out 3D scanning human body feature recognition, a large number of experiments have verified the effectiveness and feasibility of the algorithm.
Quadruple Theories Based Determinants and their Causal Relationships Affecting the Adoption of Community Cloud in Saudi HEI
Authors: Aldahwan Nouf S. , Ramzan Muhammed S.
Published: April 2022

The higher education institutions (HEIs) are adopting the new modern cloud computing technique rapidly due to its cost effectiveness, efficient and productive feature. Though cloud computing technology is beneficial to educational sector, it is important to assess their economic benefits, technical, organizational, environmental appropriateness and potential obstacles before adopting the new technology. There are four evaluating theory for adopting the cloud computing technology which are the Technology Organization Environment (TOE), the Technology Acceptance Model (TAM), the Diffusion of Innovation (DOI), and the Institutional (INT). This study has developed a new adoption framework for accepting cloud computing technology for HEIs of Saudi by integrating the above mentioned theories. This framework is unique from others because no research has been conducted yet on the adoption of community cloud at the organizational level considering the four theory simultaneously. This research has developed 25 hypotheses on the adoption of community cloud computing in HEIs and analyzed those hypotheses using SPSS statistical analysis software. The reliability of the data was tested by utilizing composite reliability and Cronbach’s alpha method. This study have introduced an innovative approach and framework to understand the adoption of the community cloud which will help the decision‐makers to build strategies in their organizations for effective adoption of community cloud services.
GSK3β Exacerbates Myocardial Ischemia/Reperfusion Injury by Inhibiting Myc
Authors: Wen Cong , Lan Meide , Tan Xin , Wang Xiaobo , Zheng Zaiyong , Lv Mingming , Zhao Xuemei , Luo Hao , Liu Yanxu , Wei Ping , Yue Rongchuan , Hu Houxiang , Guo Li
Published: April 2022

Myocardial ischemia/reperfusion (MI/R) injury is a life-threatening disease with high morbidity and mortality. Herein, the present study is conducted to explore the regulatory mechanism of GSK3β in MI/R injury regarding cardiomyocyte apoptosis and oxidative stress. The MI/R injury mouse model and hypoxic reoxygenation (H/R) cell model were established. The expression pattern of GSK3β, FTO, KLF5, and Myc was determined followed by their relation validation. Next, loss-of-function experiments were implemented to verify the effect of GSK3β/FTO/KLF5/Myc on cardiomyocyte apoptosis and oxidative stress in the MI/R injury mouse model and H/R cell model. High expression of GSK3β and low expression of FTO, KLF5, and Myc were observed in the MI/R injury mouse model and H/R cell model. GSK3β promoted phosphorylation of FTO and KLF5, thus increasing the ubiquitination degradation of FTO and KLF5. A decrease of FTO and KLF5 was able to downregulate Myc expression, resulting in enhanced cardiomyocyte apoptosis and oxidative stress. These data together supported the crucial role that GSK3β played in facilitating cardiomyocyte apoptosis and oxidative stress so as to accelerate MI/R injury, which highlights a promising therapeutic strategy against MI/R injury.
Toward English-Chinese Translation Based on Neural Networks
Authors: Xiao Fan
Published: April 2022

In traditional interactive English translation systems, English semantic context is not obvious in the process of the English translation, and the selection of optimal feature semantics does not reach the optimal translation solution, which leads to low translation accuracy. Toward this solation, a neural network (NN) based translation approach is proposed to predict word order differences in language translation and improve translation accuracy in long sentences. In this study, a multilayer NN model has been established to victories the unlabeled text words, realize the combination of word representation, vector features, and extract effective information of various sentences and semantics. In linear ranking frameworks, the NN is used to rank and score words, obtain semantic information of sample data, and predict the difference of word order. Experimental results show that the NN preorder model can significantly improve translation accuracy and system performance. The application of NN-based translation model in the practical translation process can reduce the effort of translation work, improve the efficiency of translation, and has a good practical significance.
Is Resilient Transportation Infrastructure Low-Carbon? Evidence from High-Speed Railway Projects in China
Authors: He Zheng , Wang Genda , Chen Huihua , Yan Hongyan
Published: April 2022

Establishing resilient transport infrastructure is an effective way for cities to deal with external disturbances and uncertainties during rapid urbanization. However, human society is presently facing a series of sustainable development obstacles, where the energy shortage and environmental pollution are catching significant concerns. Hence, it is imperative to investigate the carbon emission of the growing number of resilient transportation infrastructure (RTI) projects. Through extracting the carbon emission factor (CEF), this study built the carbon emission measurement model (CEMM) to evaluate the carbon emission of 26 resilient high-speed railway construction projects in China. The results indicated that the carbon emissions of the entire high-speed railway infrastructure projects in China show regional and social environmental differences. Meanwhile, there are potential correlations and positive relationships between the resilience of the high-speed railway infrastructure projects and their carbon emission. Suggestions and recommendations for governments and construction enterprises are put forward to further improve the resilient and low-carbon development of transportation infrastructure in China.
Location Optimization Model of a Greenhouse Sensor Based on Multisource Data Fusion
Authors: Qiao DianJu , Zhang ZhenWei , Liu FangHao , Sun Bo
Published: April 2022

In the traditional case, the uncertainty of the ambient temperature measured by the experiential distributed sensor is considered. In this paper, a model based on the moving least square method in the fusion algorithm is proposed to study the optimal monitoring point of the sensor in the greenhouse and determine the most suitable installation position of the sensor in the greenhouse to improve the control effect of the temperature control device of the system. MATLAB simulation software is used to simulate each working condition of the greenhouse. Temperature data measured at 15 locations in the greenhouse were used to evaluate all possible combinations of monitoring locations and to estimate the optimal location for indoor temperature sensors. Compared with the traditional method, the error is reduced to 0.373, and the data are more accurate.
Construction of Water Conservancy and Energy Engineering Structure Platform Based on Cloud Computing
Authors: Yu Xiaoqi , Zhai Jing , Ye Jingui
Published: April 2022

In view of the current water conservancy engineering system in solving the problem of water conservancy spatial information sharing and repeated investment in the construction of GIS systems by various water conservancy business departments, the research on the construction of water conservancy engineering structure platform based on cloud computing is proposed. We discussed the key technologies to realize the platform: pooled services, elastic cloud services, and spatial information services. The aggregation pooling service mainly uses the pooling mechanism and improves the responsiveness of platform services by creating object instances in advance. Based on the Cloud API provided by the cloud computing platform (such as creating a virtual machine, starting a virtual machine at runtime, and obtaining the real-time status of a virtual machine) and the REST Admin API provided by the water conservancy basic service module, using cloud computing technology ideas, we designed and implemented elastic cloud service technology. Enable the water conservancy spatial information service platform to be deployed in the cloud computing environment, support cloud architecture, and provide flexible computing capabilities, because the three types of services have different requirements for CPU and network utilization, the weight coefficient can be assigned to them. The CPU slice map service is 0.1, the spatial query service is 0.3, and the spatial analysis processing service is 0.6. The network bandwidth slice map service is 0.5, the spatial query service is 0.3, and the spatial analysis processing service is 0.2. Reduce the waste of infrastructure resources; meet the concurrent access needs of a large number of users. Spatial information service aggregation is one of the core service capabilities of the platform; it can effectively aggregate multisource spatial information, generate new services, and provide new information.
Impact of Platelets to Lymphocytes Ratio and Lymphocytes during Radical Concurrent Radiotherapy and Chemotherapy on Patients with Nonmetastatic Esophageal Squamous Cell Carcinoma
Authors: Zhang Yaotian , Han Ning , Zeng Xue , Sun Chaonan , Sun Shichen , Ma Xinchi , Zhang Yanyu , Liu Zhuang , Qin Zilan , Guo Hong , Li Yubing , Zhang Na
Published: April 2022

Purpose. This study examined the importance of hematological parameters as prognostic markers for people with esophageal cancer receiving radical concurrent chemoradiation. Methods. 106 patients with esophageal cancer are included in this study. Cox regression analysis, Kaplan-Meier method, and chi-square test were used to analyze our data. Results. The median follow-up time for patients was 15.5 months (3-55). Univariate and multivariate analyses showed that age, the change of platelet-to-lymphocyte ratio (ΔPLR), and the change rate of circulating lymphocyte count (ΔCLC%) were independent influencing factors of OS and DFS. The patients were grouped according to the median of ΔPLR and ΔCLC%, and analysis showed that a higher ΔPLR and a higher ΔCLC% was related to poor OS and DFS (

P
<
0.001

,

P
<
0.001

and

P
<
0.001

,

P
<
0.001

). By subgroup analysis, the OS of T1-4N1-2 were better in the low ΔPLR group than the high one (

P
=
0.03

,

P
<
0.001

,

P
=
0.001

,

P
<
0.001

, and

P
=
0.008

). DFS of T3-4N1-2 in the low ΔPLR group were better than the high one (

P
<
0.001

,

P
=
0.016

and

P
<
0.001

,

P
=
0.022

). For patients with T1-4N0-2, the OS in the low ΔCLC% group were better than in the high ΔCLC% group (

P
=
0.01

,

P
<
0.001

,

P
<
0.002

,

P
=
0.012

,

P
<
0.001

, and

P
=
0.024

). For T1-4N1-2, the DFS were better in the low ΔCLC% group than others (

P
=
0.042

,

P
<
0.001

,

P
<
0.001

,

P
<
0.001

, and

P
=
0.006

). Conclusion. ΔPLR and ΔCLC% are independent factors of OS and DFS, and a lower ΔPLR and ΔCLC% are associated with a better OS and DFS. And T3-4N1-2 patients in the low ΔPLR group and low ΔCLC% group have greater survival benefit.
SNHG3 Affects Gastric Cancer Development by Regulating SEPT9 Methylation
Authors: Li Wei , Ma Xudong , Wang Feng , Chen Shi , Guo Qingxiong , Sun Feng , Duan Yongqing
Published: April 2022

Background. Gastric cancer (GC) is a common malignancy that can be formed by methylation-induced deactivation of tumor silencer genes, which is one of the key mechanisms of tumorigenesis. SEPT9 methylation, a symptomatic marker for tumors, can downregulate gene expression. Long noncoding RNA small nucleolar host gene 3 (lncRNA SNHG3) is a new type of lncRNA related to cancer. Our study investigated the mechanism of SNHG3 regulation of SEPT9 methylation and its effects on the growth, metastasis, and spread of gastric cancer cells. Methods. Quantitative real-time PCR (qRT–PCR) was used to detect SNHG3 and miR-448 in gastric cancer, and a dual-luciferase experiment verified the effects of SNHG3, miR-448, and DNMT1. After abnormally expressing SNHG3, miR-448, and DNMT1 alone or together, methylation-specific PCR was performed to determine the methylation of SEPT9, Western blotting was performed to detect the expression of DNA methyltransferase 1 (DNMT1) and SEPT9, and Transwell, scratch, and CCK-8 assays were performed to reveal the invasion, migration, and cell growth of gastric cancer cells. Results. We found that SNHG3 was upregulated in gastric cancer and that SNHG3 knockdown or miR-448 overexpression inhibited SEP9 methylation and therefore increased its expression, thereby inhibiting the growth, metastasis, and spread of gastric cancer cells. Conclusion. Our study indicates that SNHG3 regulates SEPT9 methylation by targeting miR-448/DNMT1 and subsequently affecting the occurrence and development of gastric cancer.
Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm
Authors: Zhang Dengfeng , Li Yupeng
Published: April 2022

Fuzzy clustering algorithms have received widespread attention in various fields. Point tracking technology has significant application importance in sports image data analysis. In order to solve the problem of limited tracking performance caused by the fuzzy and rough division of moving image edges, this paper proposes a point tracking technology based on a fuzzy clustering algorithm, which is used for the point tracking of moving image sequence signs. This article analyzes the development status of sports image sequence analysis and processing technology and introduces some basic theories about fuzzy clustering algorithms. On the basis of the fuzzy clustering algorithm, the positioning and tracking of the marker points of the moving image sequence are studied. A series of experiments have proved that the fuzzy clustering algorithm can improve the recognition rate of the landmark points of the moving image. For the detection and tracking of moving targets, the fuzzy clustering algorithm can reach the limit faster under the same number of iterations, and the image noise can be reduced to 60% of the original by 5 iterations. This has excellent development value in application.
Synchronization and Antisynchronization of Identical 4D Hyperchaotic Financial System with External Perturbation via Sliding Mode Control Technique
Authors: Rehman Fazal ur , Mufti Muhammad Rafiq , Farooq Muhammad Umar , Din Sami ud , Ali Jawad , Mehmood Nadir
Published: April 2022

In this article, complete synchronization and antisynchronization in the identical financial chaotic system are presented. The proposed control strategies depend on first‐order sliding mode and adaptive integral sliding mode for complete synchronization and antisynchronization of the identical financial chaotic system. In the primary case, the system parameters should be known, and first‐order sliding mode control is utilized for synchronization and antisynchronization while in the second case, the system parameters are considered unknown. An adaptive integral sliding mode control strategy is utilized for synchronization and antisynchronization of the system considering the parameters unknown. The error system is changed into a particular structure containing a nominal part and several unknown terms to utilize the adaptive integral sliding mode control. Then, this error system is stabilized using integral sliding mode control. The stabilizing controller is usually developed based on the nominal part plus the compensator control part. To suppress the high‐frequency oscillation (chattering) phenomenon, smooth continuous compensator control can be used rather than conventional discontinuous control. The compensator controller along with the adapted law is derived such that the time derivative of the Lyapunov function becomes strictly negative. The effectiveness of the proposed method was tested through computer simulations. The proposed control strategies are verified for that Identical 4D hyperchaotic financial system to attain complete synchronization and antisynchronization along with the improved performance.