bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Influence of Different Prophase Stress Levels on the Fatigue Damage Characteristics of Granite
Authors: Wang Tianzuo , Xue Mengya , Sha Peng , Xue Fei , Wang Linxiang
Published: June 2021

In order to reveal the influence of prophase stress levels on the fatigue damage characteristics of granite, uniaxial fatigue tests of granite with different prophase stress levels were carried out on the basis of the MTS 815.04 rock mechanics test system. The results show that, under the same number of cycles, the failure degree increases with the increase of the prophase stress level. Under the low upper limit of cyclic stress, the tangent modulus and dissipated energy increase significantly with the increase of prophase stress level at the early stage of the cycle loading, while the increasing trend is not obvious with the increase of prophase stress level at the late stage. Under the high upper limit of cyclic stress, the tangent modulus and dissipated energy are less affected by the prophase stress level. The development trend of elastic release energy is not obvious with the increase of prophase stress level, which is less affected by the number of cycles. From the damage parameters defined by dissipative energy, under the low upper limit of cyclic stress, the initial damage is less affected by the prophase stress level. With the increase of the number of cycles, the influence of the prophase stress level on the development trend of the damage variable increases gradually. And the development trend of damage variables shows “C‐shaped” damage.
Adaptive‐Weighted Multiview Deep Basis Matrix Factorization for Multimedia Data Analysis
Authors: Li Shicheng , Liu Qinghua , Dai Jiangyan , Wang Wenle , Gui Xiaolin , Yi Yugen
Published: June 2021

Feature representation learning is a key issue in artificial intelligence research. Multiview multimedia data can provide rich information, which makes feature representation become one of the current research hotspots in data analysis. Recently, a large number of multiview data feature representation methods have been proposed, among which matrix factorization shows the excellent performance. Therefore, we propose an adaptive‐weighted multiview deep basis matrix factorization (AMDBMF) method that integrates matrix factorization, deep learning, and view fusion together. Specifically, we first perform deep basis matrix factorization on data of each view. Then, all views are integrated to complete the procedure of multiview feature learning. Finally, we propose an adaptive weighting strategy to fuse the low‐dimensional features of each view so that a unified feature representation can be obtained for multiview multimedia data. We also design an iterative update algorithm to optimize the objective function and justify the convergence of the optimization algorithm through numerical experiments. We conducted clustering experiments on five multiview multimedia datasets and compare the proposed method with several excellent current methods. The experimental results demonstrate that the clustering performance of the proposed method is better than those of the other comparison methods.
Study on the Radial Displacement Law and Permeability Enhancement Effect of Coal Body around Hydraulic Flushing Drilling
Authors: Yang He , Miao Dejun , Liu Zhen , Zhao Dawei , Zhang Mingrui
Published: June 2021

Hydraulic flushing drilling technology can not only improve the efficiency of high-pressure and low-permeability geological reservoir coalbed methane drainage but also effectively reduce the probability of coal and gas outburst disasters through pressure relief. The main mechanism of this technology is to expand the borehole diameter through hydraulic flushing measures, increase the strain of the coal around the borehole, and increase the development of cracked pores, to improve the permeability of the coal seam and realize the dual reduction of ground and gas pressure. However, in the actual application process, the interaction mechanism among the stress field, the structure field, and the seepage field is still not clear, and there is no clear method to accurately determine the pressure relief range based on the pressure relief mechanism in order to carry out reasonable drilling arrangements. Therefore, this article comprehensively uses laboratory experiments, numerical simulations, and field practices to fully explain the hydraulic flushing pressure relief mechanism and proposes a method to accurately determine the pressure relief range based on the radial line strain law. The results based on radial line strain showed that the effective relief radius expands to 0.86 m once adopting the Φ579 mm hydraulic flushing borehole compared to Φ160 mm; the borehole’s equivalent diameter of drilling field #11 is 2 to 3 times than that of #10 and 1.2 times the average CBM extraction amount. Therefore, as the borehole diameter increases, the permeability and radial line strain of the coal around the borehole increase significantly, but the tendency of the increase in permeability decreases with increasing vertical stress. The findings of this study can help for a better understanding of the pressure relief and permeability enhancement mechanism of hydraulic flushing, and the method of determining the pressure relief range based on radial strain can also provide a new way for other mines to practice ideas.
Protease Hydrolysates Ameliorates Inflammation and Intestinal Flora Imbalance in DSS-Induced Colitis Mice
Authors: Zhao Lixia , Tian Weijie , Qu Wenjuan , Li Ting , Zhu Junsong , Ma Haile
Published: June 2021

Wheat germ and fish skin usually has not been completely utilized and sometimes may be discarded, thus causing a lot of waste. Here, we aim at exploring the therapeutic anti-inflammatory effects of protease hydrolysates of wheat germ and fish skin on the ulcerative colitis (UC) mice. In the current study, wheat germ protein hydrolysates (WGPH) and fish skin gelatin hydrolysates (FSGH) treated mice had a longer colon than the DSS-induced mice. Moreover, protease hydrolysates reversed DSS-induced gut dysbiosis. Protease hydrolysates were likely to shift the balance of the intestinal flora on inflammation. In summary, these findings suggested that protease hydrolysates might serve as a latent therapy for UC treatment.
On the
k
-Component Independence Number of a Tree
Authors: Cheng Shuting , Wu Baoyindureng
Published: June 2021

Let

G

be a graph and

k
≥
1

be an integer. A subset

S

of vertices in a graph

G

is called a

k

-component independent set of

G

if each component of

G

S

has order at most

k

. The

k

-component independence number, denoted by

α
c
k

G

, is the maximum order of a vertex subset that induces a subgraph with maximum component order at most

k

. We prove that if a tree

T

is of order

n

, then

α

k

T

≥

k
/

k
+
1

n

. The bound is sharp. In addition, we give a linear-time algorithm for finding a maximum

k

-component independent set of a tree.
Marker Genes Change of Synovial Fibroblasts in Rheumatoid Arthritis Patients
Authors: Liao Lifen , Liang Ke , Lan Lan , Wang Jinheng , Guo Jun
Published: June 2021

Background. Rheumatoid arthritis (RA) is a chronic condition that manifests as inflammation of synovial joints, leading to joint destruction and deformity. Methods. We identified single‐cell RNA‐seq data of synovial fibroblasts from RA and osteoarthritis (OA) patients in GSE109449 dataset. RA‐ and OA‐specific cellular subpopulations were identified, and enrichment analysis was performed. Further, key genes for RA and OA were obtained by combined analysis with differentially expressed genes (DEGs) between RA and OA in GSE56409 dataset. The diagnostic role of key genes for RA was predicted using receiver operating characteristic (ROC) curve. Finally, we identified differences in immune cell infiltration between RA and OA patients, and utilized flow cytometry, qRT‐PCR, and Western blot were used to examine the immune cell and key genes in RA patients. Results. The cluster 0 matched OA and cluster 3 matched RA and significantly enriched for neutrophil‐mediated immunity and ECM receptor interaction, respectively. We identified 478 DEGs. In the top 20 degrees of connection in the PPI network, the key genes for RA were obtained by comparing with the gene markers of cluster 0 and cluster 3, respectively. ROC curve showed that CCL2 and MMP13 might be diagnostic markers for RA. We found aberrant levels of CD8+T, neutrophil, and B cells in RA fibroblasts, which were validated in clinical samples. Importantly, we also validated the differential expression of key genes between RA and OA. Conclusion. High expression of CCL2 and MMP13 in RA may be a diagnostic and therapeutic target.
k
-Fractional Variants of Hermite-Mercer-Type Inequalities via
s
-Convexity with Applications
Authors: Butt Saad Ihsan , Nasir Jamshed , Qaisar Shahid , Abualnaja Khadijah M.
Published: June 2021

This article is aimed at studying novel generalizations of Hermite-Mercer-type inequalities within the Riemann-Liouville

k

-fractional integral operators by employing

s

-convex functions. Two new auxiliary results are derived to govern the novel fractional variants of Hadamard-Mercer-type inequalities for differentiable mapping

Ψ

whose derivatives in the absolute values are convex. Moreover, the results also indicate new lemmas for

Ψ

′

,

Ψ

′
′

, and

Ψ

′
′
′

and new bounds for the Hadamard-Mercer-type inequalities via the well-known Hölder’s inequality. As an application viewpoint, certain estimates in respect of special functions and special means of real numbers are also illustrated to demonstrate the applicability and effectiveness of the suggested scheme.
Chemical Composition and In Vitro Evaluation of the Mosquito (Anopheles) Repellent Property of Neem (Azadirachta indica) Seed Oil
Authors: Aidoo Olive , Kuntworbe Noble , Owusu Fredrick William Akuffo , Nii Okantey Kuevi Deryl
Published: June 2021

As one of the killer diseases in the world, malaria contributes to child mortality and global death annually. As a result, many reactive mechanisms have evolved to control and repel mosquitoes. The use of synthetic mosquito repellents with N,N-Diethyl-meta-toluamide (DEET) is one of the popular interventions despite its dermatological limitations such as skin irritations. Ethnobotanical reviews have identified that the adoption of natural repellents promises high repellence on mosquitoes with minimal side effects compared with synthetic ones. However, this has received little attention in modern pharmaceutical literature. This research is focused on the formulation of a natural mosquito repellent from the oil extracted from Azadirachta indica (A. Juss). The oil cream was formulated in concentrations of 10%

v
/
w

, 12.5%

v
/
w

, 15%

v
/
w

, 17.5%

v
/
w

, and 20%

v
/
w

using an in vitro evaluation approach. Pharmacopoeia characteristics of the cream such as pH, viscosity, spreadability, and organoleptic properties were carried out to verify acidity, permeation, and flow properties of the formulated cream. The spreadability rate was inversely proportional to the concentration of the cream in terms of oil content falling from 1.24 gm/s to 0.84 gm/s from concentrations 10%

v
/
w

to 20%

v
/
w

correspondingly. Skin irritation tests, however, indicated traces of irritation at 20%

v
/
w

. Repellency properties of the cream revealed a lasting effect on the mosquitoes, although this was dependent on concentration levels. Formulations of 17.5%

v
/
w

and 20%

v
/
w

neem seed oil cream had an equal repellency effect of 87.5%, whereas the synthetic repellent had a repellency of 75% within a justifiable time frame for all the formulations. This work shows that plant-based mosquito repellents promise a healthier approach in controlling mosquito bites, protecting the skin, and preventing malaria.
Testing  Method for  the Range of  Fracture Zone of  Rock  Slope under Blasting Load
Authors: Wang Zhide , Ma Zuyao , Xia Yuanyou , Zhou Xiong , Lin Manqing , Li Jie , Wang Jinyuan
Published: June 2021

In engineering blasting, the determination of the range of rock blasting fracture zone has important guiding significance for blasting construction. This paper proposes a method that can accurately and directly obtain the range of rock blasting fracture zone. Based on the theory of elastic wave propagation, test rods which are made of appropriate material are selected and prepared. A certain number of boreholes are drilled for subsequent insertion of the test rods along the direction perpendicular to the free surface of the excavation at a certain distance from the blast hole. Based on the field blasting test results, the deepest fracture position of the test rod is used as the boundary of the blasting fracture zone, and the range of the rock blasting fracture zone is obtained. A numerical analysis model is established according to the Mohr–Coulomb constitutive relationship and the Von Mises yield criterion. Then, the range of the fracture zone and the maximum horizontal radius of the fracture zone are analyzed and obtained. The numerical analysis results are compared with the field measured data. It is demonstrated that the range of the fracture zone obtained by the numerical simulation is in good agreement with the blasting test results of the pre‐embedded test rods. The research results can provide references for the safety control of blasting and excavation of rock slopes.
Xiaoxuming Decoction Regulates Vascular Function by Modulating G Protein‐Coupled Receptors: A Molecular Docking Study
Authors: Shen Yanjia , Yang Ran , Zhou Rui , Lu Wendan , Li Li , Niu Ziran , Chen Miao , Wang Jinhua , Wang Yuehua , Fang Lianhua , Du Guanhua
Published: June 2021

Xiaoxuming decoction (XXMD) is a traditional Chinese herbal medicine (CHM) that is used for the treatment of stroke in China. Stroke injury damages the cerebral vasculature and disrupts the autoregulation of vasoconstriction and vasodilatation, which is crucial for maintaining constant cerebral blood flow (CBF). It has been reported that XXMD exerts a positive effect on cerebral circulation in animal models of stroke. However, the mechanisms underlying the regulatory effect of XXMD on vascular tone, and the interactions among the multiple components of XXMD, remain unclear. In this study, XXMD was found to induce relaxation of the basilar artery rings of rats precontracted by 5‐hydroxytryptamine (5‐HT) in vitro, in a dose‐dependent manner. The modulation of vascular tone and the process of cerebral ischemia are mediated via the interactions between G protein‐coupled receptors (GPCRs) and their ligands, including 5‐HT, angiotensin II (Ang II), and urotensin II (UII). Thus, the potential synergistic effects of the different components of XXMD on the regulation of vasoconstriction and vasodilation were further investigated by molecular docking based on network pharmacology. We constructed and analyzed a database comprising 963 compounds of XXMD and studied the interactions between five vascular GPCRs (5‐HT1A receptor (5‐HT1AR), 5‐HT1B receptor (5‐HT1BR), Ang II type 1 receptor (AT1R), beta 2‐adrenergic receptor (β2‐AR), and UII receptor (UTR)) and the various herbal constituents of XXMD using molecular docking. By constructing and analyzing the compound‐target networks of XXMD, we found that Glycyrrhizae Radix et Rhizoma, Ginseng Radix et Rhizoma, and Paeoniae Radix Alba were the three major herbs that contained a large number of compounds with high docking scores. We additionally observed that several constituents of XXMD, including gallotannin, liquiritin apioside, nariutin, 1,2,3,4,6‐pentagalloylglucose, folic acid, and ginsenoside Rb1, targeted multiple vascular GPCRs. Moreover, the interactions between the components of XXMD and the targets related to vascular tone constituted the comprehensive cerebrovascular regulatory function of XXMD and provided a material basis of the vasoregulatory function of XXMD. The study reports the contributions of various components of XXMD to the regulatory effects on vascular tone and provides scientific evidence for the multicomponent and multitargeting characteristics of XXMD.
Mortality and Excess Mortality: Improving FluMOMO
Authors: Portugal Luís
Published: June 2021

FluMOMO is a universal formula to forecast mortality in 27 European countries and was developed on EuroMOMO context, http://www.euromomo.eu. The model has a trigonometric baseline and considers any upwards deviation from that to come from flu or extreme temperatures. To measure it, the model considers two variables: influenza activity and extreme temperatures. With the former, the model gives the number of deaths because of flu and with the latter the number of deaths because of extreme temperatures. In this article, we show that FluMOMO lacks important variables to be an accurate measure of all-cause mortality and flu mortality. Indeed, we found, as expected, that population ageing and exposure to the risk of death cannot be excluded from the linear predictor. We model weekly deaths as an autoregressive process (lag of one together with a lead of one week). This step allowed us to avoid FluMOMO trigonometric baseline and have a fit to weekly deaths through demographic variables. Our model uses data from Portugal between 2009 and 2020, on ISO-week basis. We use negative binomial-generalized linear models to estimate the weekly number of deaths as an alternative to traditional overdispersion Poisson. As explanatory variables were found to be statistically significant, we registered the number of deaths from the previous week, the influenza activity index, the population average age, the heat waves, the flu season, the number of deaths with COVID-19, and the population exposed to the risk of dying. Considering as excess mortality the number of deaths above the best estimate of deaths from our model, we conclude that excess mortality in 2020 (net of COVID-19 deaths, heat wave of July, and ageing) is low or inexistent. The model also allows us to have the number of deaths arising from flu and we conclude that FluMOMO is overestimating deaths from flu by 78%. Averages from the probability of dying are obtained as well as the probability of dying from flu. The latter is shown to be decreasing over time, probably due to the increase of flu vaccination. Higher mortality detected with the start of COVID-19, in March-April 2020, was probably due to COVID-19 deaths not recognized as COVID-19 deaths.
A Multiregion Discrete-Time Epidemic Model of Mycobacterium tuberculosis Infections: An Optimal Control Approach
Authors: Bouajaji Rachid , Laarabi Hassan , Rachik Mostafa , Abta Abdelhadi
Published: June 2021

The main goal of this article is to devise the spatial-temporal spread of TB, in multiple neighboring domains, taking into account the epidemiological diversity of their populations. However, since both the environment and any population are spatially heterogeneous, it is obviously desirable to include spatial structure into an epidemic model. Individuals with tuberculosis can spread the disease by moving from one area to another. In addition, people travel by air between cities, so diseases can be spread quickly between very distant places (as was the case with the COVID-19). In our model, each region’s studied population is divided into five compartments S, L1, I, L2, and R. Further, we introduce in our discrete systems three control variables which represent the effectiveness rates of vaccination, travel-blocking operation, and treatment. We focus in our study to control the outbreaks of an epidemic that affects a hypothetical population belonging to a specific region. Firstly, we analyze the epidemic model when the control strategy is based on the vaccination control only, and secondly, when the travel-blocking control is added, we finish with the introduction of the treatment control. The optimal control theory, based on Pontryagin’s maximum principle, is applied thrice in this paper, for the characterizations of the vaccination, travel-blocking, and treatment controls. The numerical results associated with the multipoint boundary value problems are obtained based on the forward-backward sweep method combined with progressive-regressive Runge–Kutta fourth-order schemes.
Protective Effects of Almond Oil on Streptozotocin-Induced Diabetic Rats via Regulating Nrf2/HO-1 Pathway and Gut Microbiota
Authors: Liu Rui , Shu Ying , Qi Wenhui , Rao Weili , Fu Zihan , Shi Zhenxiao , Zhang Zhisheng
Published: June 2021

Almond oil has been used as a medicine substitution for its numerous health benefits. This study aimed to evaluate the effect of almond oil on streptozotocin- (STZ-) induced diabetic rats for 4 weeks. The results showed that the administration of almond oil could significantly increase body weight, attenuate abnormally elevated blood glucose, promote insulin secretion, and improve glucose tolerance. Almond oil treatment also suppressed oxidative stress, reduced inflammation reaction, improved liver and kidney function, upregulated the expressions of Nrf2, HO-1, and NQO1, while downregulating the expression of Keap1. Furthermore, almond oil reversed the gut microbiota change by STZ and regulated the gut microbiota associated with glucose metabolism. At the phylum level, the relative abundance of Firmicutes was decreased, while Bacteroidetes was increased by almond oil treatment. More importantly, the ratio of Firmicutes/Bacteroidetes was significantly increased. At the genus level, administration of almond oil increased the abundances of Lactobacillus, Bacteroides, and Lachnospiraceae_NK4A136_group, while decreased the abundances of Ruminococcaceae_UCG-014, Clostridium_sensu_stricto_1, and Fusicatenibacter. These results provided evidence for the regulating effect of almond oil on diabetic rats via the Nrf2/HO-1 pathway and gut microbiota.
Portable 3D Gait Analysis Assessment in MTT Treat Chronic Ankle Instability: A Retrospective Study
Authors: Song Yujuan , Xu Sibai , Dai Yanqiu , Jia Jun , Liu Hebin , Li Zhenjing
Published: June 2021

Purpose. Retrospective analysis of the effect of portable 3D gait analysis as an innovative evaluation method in the treatment with MTT on chronic ankle instability patient. Methods. From January 1, 2019, to December 31, 2019, 56 cases of chronic ankle instability (CAI) were extracted from the medical record system of Shenzhen Longhua District Central Hospital. All the patients of 56 cases accepted the medical training therapy (MTT). As outcome parameters, the alterations of the Cumberland ankle instability tool (CAIT), foot and ankle ability measure (FAAM), were used before the treatment and after treatment; meanwhile, the portable apparatus 3D gait analysis was used to measure the gait parameters. Conclusion. The results showed only ankle angle parameters Y‐axis, maximum dorsiflexion during support period (°) had a significant difference, and the p value is 0.039. Meanwhile, the CAIT, FAAM, and most 3D gait analysis data had no significant difference. This particular statistical difference shows that CAI can be measured scientifically and objectively, although most measurement parameters have no change. These results make further reveal that the CAI patients are suffering with dynamic abnormality of ankle motion angle; this also provides us with a measurable and systematic evaluation reference plan for CAI treatment in the future.
Optimization of Sports Good Recycling Management System Based on Internet of Things
Authors: Ren Panhong , Nie Mengjian , Ming Hui
Published: June 2021

Based on the technology of Internet of Things, this paper proposes a sports good recycling management system and realizes the system optimization. Based on the management of returned good flow based on the Internet of Things, we can comprehensively apply system integration technology, system architecture, cloud computing technology, etc., based on the current situation of surrounding return flow management, combined with the reality of the sports product recycling business process. From two aspects of process information and operation information, based on the information system of each link of the Internet of Things recycling, a recycling logistics information management system platform is constructed. This can solve the problem of the integrated management of the recycling logistics process and the operation control of the recycling logistics management system. In the stage of sports information management, combined with the Internet of Things technology, we should do a good job of sports artificial intelligence management and information knowledge exploration. In the development of sports under the framework of the Internet of Things, we should combine the needs of sports information management and the technology mode of the Internet of Things, so as to realize the scientific and standardized management of sports good recycling under the Internet of Things technology.
Predicting Customer Turnover Using Recursive Neural Networks
Authors: Chashmi Abdullah Jafari , Rahmati Vahid , Rezasoroush Behrouz , Alamoti Masumeh Motevalli , Askari Mohsen , Khalili Faezeh Heydari
Published: June 2021

The most valuable asset for a company is its customers’ base. As a result, customer relationship management (CRM) is an important task that drives companies. By identifying and understanding the valuable customer segments, appropriate marketing strategies can be used to enhance customer satisfaction and maintain loyalty, as well as increase company retention. Predicting customer turnover is an important tool for companies to stay competitive in a fast‐growing market. In this paper, we use the recurrent nerve sketch to predict rejection based on the time series of the lifetime of the customer. In anticipation, a key aspect of identifying key triggers is to turn off. To overcome the weakness of recurrent neural networks, the research model of the combination of LRFMP with the neural network has been used. In this paper, it was found that clustering by LRFMP can be used to perform a more comprehensive analysis of customers’ turnover. In this solution, LRFMP is used to execute customer segregation. The objective is to provide a new framework for LRFMP for macrodata and macrodata analysis in order to increase the problem of business problem solving and customer depreciation. The results of the research show that the neural networks are capable of predicting the LRFMP precursors of the customers in an effective way. This model can be used in advocacy systems for advertising and loyalty programs management. In the previous research, the LRFM and RFM algorithms along with the neural network and the machine learning algorithm, etc., have been used, and in the proposed solution, the use of the LRFMP algorithm increases the accuracy of the desired.
A Systemic Review and Meta‐analysis of the Leading Pathogens Causing Neonatal Sepsis in Developing Countries
Authors: Zelellw Desalegne Amare , Dessie Getenet , Worku Mengesha Endalkachew , Balew Shiferaw Melashu , Mela Merhaba Masresha , Emishaw Solomon
Published: June 2021

Background. Neonatal sepsis is one of the major public health problems globally, particularly, in developing countries. Klebsiella, Staphylococcus aureus, Coagulase-negative Staphylococcus, and Escherichia coli are the common pathogens for neonatal sepsis in developing countries. However, the pooled estimate of common pathogens causing neonatal sepsis in developing countries is still unknown. Therefore, this study is aimed at computing the pooled proportion of the leading cause of pathogens for neonatal sepsis in developing countries. Methods. We strictly followed the Preferred Reporting Items for Systemic Reviews and Meta‐analysis guidelines to report this systematic review and meta‐analysis. PubMed, Cochrane Library, Web of Science, CINAHL, Science Direct, and other search engines such as Google Scholar, Africa Journals Online, and Hinari were used to obtain studies related to the leading cause of pathogens for neonatal sepsis in developing countries. The search was done from October 1 to December 30, 2018, by considering both published and gray literature. Studies were evaluated based on the PRISMA guideline checklist by using their titles, abstracts, and full texts. Studies were extracted using Microsoft Excel spreadsheets, and STATA software version 14 was used to analyze data. Heterogeneity between studies was checked based on Cochran’s Q‐test and the corresponding I2 statistic test. Results. The pooled prevalence of the leading cause of pathogens of neonatal sepsis in developing countries were Klebsiella (26.36%), Staphylococcus aureus (23.22%), Coagulase-negative Staphylococcus (23.22%), and Escherichia coli (15.30%). Common pathogens were varied across regions; for instance, pooled isolated Coagulase-negative Staphylococcus was 25.98% in Africa, 16.62% in Asia, and 36.71% in Latin America, and Klebsiella was 29.80% in Africa, 23.21% in Asia, and 22.00% in Latin America. Also, Staphylococcus aureus was 27.87% in Africa and 18.28% in Asia, and Escherichia coli was 22.97% in Asia and 9.43% in Africa. Conclusions. This study highlights that the more prevalent common isolated pathogens in developing countries were Klebsiella, Staphylococcus aureus, Coagulase-negative Staphylococcus, and Escherichia coli, Klebsiella, and Staphylococcus aureus pathogens were predominantly high in Africa as compared to other Asian and Latin American countries. At the same time, Coagulase-negative Staphylococcus was more prevalent in Latin America compared to other regions. Escherichia coli is more dominant in Asia as compared to Africa and Latin America.
Effect of International Technology Transfer on the Technical Efficiency of High‐Tech Manufacturing in China: A RAGA‐PP‐SFA Analysis
Authors: Zhou Shuzhen , Deng Qunzhao , Peng Feng
Published: June 2021

The sustainable development of China’s high‐tech manufacturing (HTM) sector is restricted by dependence on technology introduction and foreign direct investment (FDI), low input‐output efficiency, and environmental pollution. This study aimed to examine the roles of technology introduction and FDI in improving the technical efficiency of Chinese HTM from an environmental perspective. By integrating stochastic frontier analysis (SFA) and projection pursuit (PP) based on the real‐coded accelerated genetic algorithm (RAGA), this study constructed a RAGA‐PP‐SFA model that considers undesirable outputs. This model includes various outputs, including environmental pollution, in the production function to improve estimation accuracy. Moreover, to verify the robustness of the estimation results, the results were provided when environmental pollutants were taken as input factors. The results showed that technology introduction could significantly promote HTM’s technical efficiency, while FDI had no significant positive effect. By comparing the estimated results with those that did not consider environmental pollution, this study not only reveals different roles of technology introduction and FDI in improving HTM’s technical efficiency but also confirms that ignoring environmental pollution will overestimate their roles (especially the role of FDI) in such improvement.
Influence of Sliding Time Window Size Selection Based on Heart Rate Variability Signal Analysis on Intelligent Monitoring of Noxious Stimulation under Anesthesia
Authors: Yin Qiang , Shen Dai , Ding Qian
Published: June 2021

In recent decades, little progress of objective evaluation of pain and noxious stimulation has been achieved under anesthesia. Some researches based on medical signals have failed to provide a general understanding of this problem. This paper presents a feature extraction method for heart rate variability signals, aiming at further improving the evaluation of noxious stimulation. In the process of data processing, the empirical mode decomposition is used to decompose and recombine heart rate variability signals, and the sliding time window approach is used to extract the signal features of noxious stimulation, respectively. The influence of window size on feature extraction is studied by changing the window size. By comparing the results, the feature extraction in the process of data processing is valuable, and the selection of window size has a significant impact. With the increase of selected window sizes, we can get better detection results. But for the best choice of window size, to ensure the accuracy of the results and to make it easy to use, then, we need to get just a suitable window size.
miR‐125a‐5p Regulates Osteogenic Differentiation of Human Adipose‐Derived Mesenchymal Stem Cells under Oxidative Stress
Authors: Ye Yongheng , Liu Quan , Li Changzhao , He Peiheng
Published: June 2021

Adipose‐derived mesenchymal stem cells (ADSCs) are a well‐recognized multilineage stem cell with vital clinical feasibility for tissue regeneration. Extensive evidence indicates that oxidative stress and microRNAs (miRNAs/miRs) play an important role in the osteoinduction of adipose‐derived mesenchymal stem cells. In this study, we investigated the mechanism of miR‐125a‐5p in regulating the osteogenesis of human adipose‐derived mesenchymal stem cells (hADSCs) under oxidative stress. The expression of miR‐125a‐5p lessened gradually during the osteogenic differentiation of hADSCs. Relative to the negative group, the expression levels of runt‐related transcription factor 2 (RUNX2), alkaline phosphatase (ALP), osteocalcin (OCN), and osterix in the miR‐125a‐5p group were marked lower than those in the miR‐125a‐5p inhibitor group. The levels of p16, p21, p53, miR‐125a‐5p, and ROS during osteoinduction of hADSCs were assessed in vitro under oxidative stress and were observed to be upregulated. Further experiments showed that oxidative stress and miR‐125a‐5p together suppressed the expression of VEGF during osteogenic differentiation of hADSCs and that the inhibition of miR‐125a‐5p reversed the effect of oxidative stress. In short, our study indicated that miR‐125a‐5p is induced under oxidative stress and inhibits the expression of VEGF, leading to the reduction of osteogenic differentiation of hADSCs. Our outcomes showed that miR‐125a‐5p could be a potential clinical target for bone repairing.
Downregulation of snoRNA SNORA52 and Its Clinical Significance in Hepatocellular Carcinoma
Authors: Ding Yuan , Sun Zhongquan , Zhang Sitong , Li Yanjie , Han Xin , Xu Qianhui , Zhou Liuzhi , Xu Hao , Bai Yang , Xu Chang , Ding Hao , Ge Yao , Wang Weilin
Published: June 2021

Hepatocellular carcinoma (HCC) is one of the most common and aggressive tumors in the world while the accuracy of the present tests for detecting HCC is poor. A novel diagnostic and prognostic biomarker for HCC is urgently needed. Overwhelming evidence has demonstrated the regulatory roles of small nucleolar RNA (snoRNA) in carcinogenesis. This study is aimed at analyzing the expression of a snoRNA, SNORA52, in HCC and exploring the correlation between its expression and various clinical characteristics of HCC patients. By using quantitative real‐time PCR, we found that SNORA52 was downregulated in HCC cell lines (P < 0.05) and HCC tissues (P < 0.001). Correlation analysis showed that the expression of SNORA52 was obviously associated with tumor size (P = 0.011), lesion number (P = 0.007), capsular invasion (P = 0.011), tumor differentiation degree (P = 0.046), and TNM stage (P = 0.004). The disease‐free survival (DFS) and overall survival (OS) analysis showed that patients with lower SNORA52 expression had a worse prognosis (P < 0.001). Univariate and multivariate Cox regression analysis showed that SNORA52 expression was a completely independent prognostic factor to predict DFS (P = 0.009) and OS (P = 0.012) of HCC patients. Overall, our findings showed SNORA52 expression levels were downregulated in HCC tissues and correlated with multiple clinical variables, and SNORA52 was an independent prognostic factor for HCC patients, which suggested that SNORA52 could function as a potential diagnostic and prognostic biomarker for HCC patients.
Role of Intestinal Microbiota on Gut Homeostasis and Rheumatoid Arthritis
Authors: Li Mingxin , Wang Fang
Published: June 2021

Rheumatoid arthritis (RA) is a chronic inflammatory disease that is immune mediated. Patients typically present with synovial inflammation, which gradually deteriorates to investigate severe cartilage and bone damage, affecting an individual’s ability to perform basic tasks and impairing the quality of life. When evaluated against healthy controls, patients with RA have notable variations within the constituents of the gut microbiota. The human gastrointestinal tract mucosa is colonized by trillions of commensal microbacteria, which are key actors in the initiation, upkeep, and operation of the host immune system. Gut microbiota dysbiosis can adversely influence the immune system both locally and throughout the host, thus predisposing the host to a number of pathologies, including RA. Proximal intestinal immunomodulatory cells, situated in specific locales within the intestine, are a promising intermediary through which the gastrointestinal microbiota can influence the pathogenesis and progression of RA. In the early stages of the disease, the microbiota appear to differ from those present in healthy controls. This difference may reflect potential autoimmune mechanisms. Research studies evaluating intestinal microbiota have demonstrated that RA is associated with a bacterial population growth or with a decline when judged against control groups. The aim of this review is to examine the studies that connect intestinal dysbiosis with the autoimmune pathways implicated in the pathogenesis of RA.
Prediction and Evaluation of Rockburst Based on Depth Neural Network
Authors: Zhang Jin , Wang Mengxue , Xi Chuanhao
Published: June 2021

The formation mechanism of rockburst is complex, and its prediction has always been a difficult problem in engineering. According to the tunnel engineering data, a three‐dimensional discrete element numerical model is established to analyze the initial stress characteristics of the tunnel. A neural network model for rockburst prediction is established. Uniaxial compressive strength, uniaxial tensile strength, maximum principal stress, and rock elastic energy are selected as input parameters for rockburst prediction. Training through existing data. The neural network model shows that the rockburst risk is closely related to the maximum principal stress. Based on the division of rockburst risk areas, according to different rockburst levels, the corresponding treatment methods are put forward to avoid the occurrence of rockburst disaster. Based on the field measured data and test data, combined with the existing rockburst situation, numerical simulation and neural network method are used to predict the rock burst classification, which is of great significance for the early and late construction safety of the tunnel.
Role of Chest Computed Tomography versus Real Time Reverse Transcription Polymerase Chain Reaction for Diagnosis of COVID-19: A Systematic Review and Meta-Analysis
Authors: Ali Dina M. , Zake Lamiaa G. , El Kady Nevine K.
Published: June 2021

Background. The current global pandemic of COVID-19 is considered a public health emergency. The diagnosis of COVID-19 depends on detection of the viral nucleic acid by real time reverse transcription polymerase chain reaction (RT-PCR). However, false-negative RT-PCR tests are reported and could hinder the control of the pandemic. Chest computed tomography could achieve a more reliable diagnosis and represent a complementary diagnostic tool. Aim. To perform a meta-analysis and systematic review to find out the role of chest computed tomography versus RT-PCR for precise diagnosis of COVID-19 infection. Methods. We searched three electronic databases (PubMed, ScienceDirect, and Scopus) from April 1 to April 20, 2020, to find out articles including the accuracy of chest computed tomography scan versus RT-PCR for diagnosis of SARS-CoV-2 infection. Observational studies, case series, and case reports were included. Results. A total of 238 articles were retrieved from the search strategy. Following screening, 39 articles were chosen for full text assessment and finally 35 articles were included for qualitative and quantitative analysis. Chest computed tomography showed a wide range of sensitivity varied from 12%–100%. Conclusion. Chest computed tomography is playing a key role for diagnosis and detection of COVID-19 infection. Computed tomography image findings may precede the initially positive RT-PCR assay.
Cell-Seeded Acellular Artery for Reconstruction of Long Urethral Defects in a Canine Model
Authors: Zhong Hao , Shen Yamei , Zhao Danhui , Yan Guoqiang , Wu Chengai , Huang Guanglin , Liu Zhizhong , Zhai Jianpo , Han Qin
Published: June 2021

The management of urethral stricture remains a major therapeutic challenge in clinics. Herein, we explored the feasibility of reconstructing a relatively long segment of the urethra by the cell-seeded acellular artery in a canine model. The acellular arterial matrix was obtained from the excised carotid artery of donor dogs. Autologous adipose-derived stem cells (ADSCs) from 6 male dogs were grown and seeded onto the premade acellular arterial matrix. A 3 cm long segment of the urethra was resected in 12 male dogs. Urethroplasty was performed with the acellular arterial matrix seeded with ADSCs in 6 animals and without cells in 6. Serial urethrography was performed at 1 and 3 months postoperatively. Wide urethral calibers without any signs of strictures were confirmed in all 6 animals in the experimental group. In contrast, urethral stricture was demonstrated in 3 animals in the control group. The graft was highly epithelialized and smooth in the experimental group, while graft contracture and scar formation were showed in the control group. Histologic analysis of the cell-seeded arterial matrix at 1 month confirmed the presence of multilayered urothelium and muscle. The levels of tissue formation developed over time with a progressive increase in muscle content. In contrast, extensive fibrosis and sparse smooth muscle were seen in animals treated with matrix without ADSCs. This study provides preclinical evidence that the ADSC-seeded arterial matrix can be used as a tubularized scaffold in the reconstruction of 3 cm long urethral defect in a male canine model. The ADSC-seeded arterial matrix remodels and regenerates normal-appearing urethral tissue layers over time.
Serous Borderline Tumor in Transgender Female-to-Male Individuals: A Case Report of Androgen Receptor-Positive Ovarian Cancer
Authors: Ferreira Cristina , Fraga João , Antunes Célia , Gonçalo Manuela , Donato Paulo
Published: June 2021

Ovarian cancer is the most fatal gynecologic malignancy. The incidence of ovarian cancer among female-to-male transsexuals receiving treatment with testosterone is unknown, and few cases have been reported in the literature. We report a recent case in our institution, a 23-year-old female-to-male transsexual patient who received testosterone supplementation. The patient underwent a pelvic magnetic resonance imaging to study an ovarian complex cyst that revealed the presence of a bilateral ovarian tumor with imaging features of borderline serous tumor. These masses were surgically removed and the pathology report confirmed the diagnosis associated with noninvasive peritoneal implants and the presence of numerous androgen receptors in the tumor cells. Although there is still insufficient data to validate a direct correlation between hormonotherapy and ovarian cancer in these patients, this case may reinforce previous reports on this association and highlights the relevance of radiological follow-up and bilateral salpingo-oophorectomy as part of gender reassignment surgery.
A New Fractional Model for Cancer Therapy with M1 Oncolytic Virus
Authors: El Younoussi Majda , Hajhouji Zakaria , Hattaf Khalid , Yousfi Noura
Published: June 2021

The aim of this work is to propose and analyze a new mathematical model formulated by fractional differential equations (FDEs) that describes the dynamics of oncolytic M1 virotherapy. The well‐posedness of the proposed model is proved through existence, uniqueness, nonnegativity, and boundedness of solutions. Furthermore, we study all equilibrium points and conditions needed for their existence. We also analyze the global stability of these equilibrium points and investigate their instability conditions. Finally, we state some numerical simulations in order to exemplify our theoretical results.
Elimination of Aspergillus flavus from Pistachio Nuts with Dielectric Barrier Discharge (DBD) Cold Plasma and Its Impacts on Biochemical Indices
Authors: Makari Mina , Hojjati Mohammad , Shahbazi Samira , Askari Hamed
Published: June 2021

In the present research, the effects of different durations (0, 15, 30, 60, 90, 120, 150, and 180 sec) of dielectric barrier discharge (DBD) cold plasma on decontaminating Aspergillus flavus, detoxifying pure aflatoxin B1 (AFB1), and the quality attributes of pistachio nuts (total phenolic content, antioxidant activity, chlorophylls, total carotenoids, instrumental color, total soluble protein, and malondialdehyde determination) were studied. The results showed that the viable spore population reduced with the increase of plasma treatment duration, so that after 180 s of the treatment, a decrease by 4 logs was observed in the spore population. Chlorophyll a and b, as well as total carotenoid levels and color parameters, decreased, which led to darker pistachio samples and intensity reduction in soluble protein content and protein bands. Plasma treatment did not alter the total phenolic content but slightly increased the antioxidant activity of pistachio nuts samples. The malondialdehyde values significantly increased all the plasma treatment durations. The maximum reduction of AFB1 was observed after 180 s of the treatment, which was 64.63% and 52.42% for glass slides and pistachio nut samples, respectively. The present findings demonstrated that cold plasma could be used as an efficient decontamination method of food products without inducing undesirable quality changes in nuts.