bluuebunny/crossref_metadata_2025 huggingface dataset:
Mother’s Characteristics and Socioeconomic Status as Possible Risk Factors for Children’s Caries in Jordan
Authors: Al-Rashdan Omar , AlZoubi Zaid , Ibrahimi Mahmoud , Al-khraisha Amal , Almajali Nabeel
Published: March 2022

Background. Clinical oral health status of children affects their health-related quality of life. A major determinant of oral health is early childhood caries, which possesses a negative effect. Objective. The primary objective of the study was to examine the association between socioeconomic status and different mother’s characteristics and the risk of dental caries in children using the decay missing filled (DMF) score as an indicator. Methods. This was a cross-sectional descriptive study that was in the pediatric dental clinic in Hashem Ibn Al-Hussein medical military hospital in Jordan. Pearson correlation was used to examine associations between two continuous variables. Linear regression was used to detect variables that might predict the decayed missing filled teeth (dmft) score of the child. Results. A total of 264 children were enrolled in the study. Average age of children was 4.80 ± 1.99 years, and average mothers’ age was 32.74 ± 5.68. Mothers had an average DMFT score of 8.84 ± 5.39, while children had an average dmft score of 6.17 ± 4.82. There was no association between the mother’s age and the dmft score of the child (Pearson correlation = 0.08, andPvalue = 0.215). However, a moderate, statistically significant correlation was found between the mother’s and the child’s DMFT scores (Pearson correlation = 0.418, andPvalue = 0.001). Children who belonged to low and middle-income families had a higher dmft score compared to those that belonged to families with high income. Conclusion. Socioeconomic status of the family, mother’s habits, dental hygiene, and education level are important factors that influence the child’s oral health. Strategies that focus on children with these characteristics can help them achieve better oral health.
Overconsolidation Characteristics of Silt Layer in the Guangdong-Hong Kong-Macao Greater Bay Area
Authors: Guan Dashu , Zhang Wei , Zhou Guoqing , Zhu QiYin , Zou Jiaqiang , Zheng Jiaxi , Huang Wenhao
Published: March 2022

In practical engineering projects, overconsolidation plays an irreplaceable role in the calculation of silt consolidation settlement. Based on a series of systematic consolidation tests conducted on reconstituted soft clay in different cities of the Guangdong-Hong Kong-Macao Greater Bay Area, the overconsolidation behavior of soft clay under different depths was studied. According to these tests, the shape of the curves of the overconsolidation ratio with depth was similar to that of the compression curves. Moreover, the deeper the silt depth is, the smaller the overconsolidation ratio is. Hence, the overconsolidation state eventually changes to the underconsolidation state. On this basis, the depths of normal consolidation were calculated through the fitting curves of the overconsolidation ratio with depth by CurveExpert1.4, which is strongly dependent on both the average thickness of the overfill and the range of water level. Based on the results, a polynomial relationship between overconsolidation ratio (OCR) and sampling depth (h) is established. This study can serve as a basis for predicting the consolidation settlement of the silt layer more accurately in practical engineering applications.
Posterior Tibial Nerve Stimulation for Overactive Bladder: Mechanism, Classification, and Management Outlines
Authors: Al-Danakh Abdullah , Safi Mohammed , Alradhi Mohammed , Almoiliqy Marwan , Chen Qiwei , Al-Nusaif Murad , Yang Xuehan , Al-Dherasi Aisha , Zhu Xinqing , Yang Deyong
Published: March 2022

Purpose of the Review. Posterior tibial nerve stimulation (PTNS) techniques have dramatically grown after approval to manage overactive bladder (OAB). The present review will focus on the most current data on PTNS types (percutaneous, transcutaneous, and implant) and their mechanism of action, safety, efficacy, advantages, drawbacks, limitation, and clinical applications. Recent Findings. The present review described the recent studies that addressed the tibial nerve stimulation role in OAB management. BlueWind RENOVA system, Bioness StimRouter, and eCoin are examples of emerging technologies that have evolved from interval sessions (percutaneous PTNS and transcutaneous PTNS) to continuous stimulation (implants). These can be efficiently managed at home by patients with minimum burden on the health system and fewer visits, especially in the COVID-19 pandemic. Summary. Our review shows that the tibial nerve stimulation advancements in OAB treatment have been rapidly increasing over the recent years. It is minimally invasive and effective, similar to sacral nerve stimulation (SNM), but less aggressive. Implantable PTNS has been promised in terms of efficacy, safety, and high acceptance rate. However, evidence is still limited to short-term trials, and tolerability, method, and drawbacks remain challenges.
Application Value of Spectral CT Imaging in Quantitative Analysis of Early Lung Adenocarcinoma
Authors: Du Wang , Yu Mingji , Luo Xiaojie , Chen Min
Published: March 2022

Objective. To investigate the clinical value of gemstone energy spectral CT imaging for the quantitative analysis of early lung adenocarcinoma. Methods. 76 cases of pulmonary ground-glass nodules pathologically confirmed as precancerous lesion and early lung cancer (including pure ground-glass nodules in 46 cases and mixed ground-glass nodules in 30 cases) underwent chest CT scan first and then underwent contrast-enhanced gemstone energy spectral CT to get arterial phase images, venous phase images, and delayed phase images. All the lesions were set the region of interest (ROI). Cases of the pure ground-glass nodule (pGGN) were measured at the maximum level of lesions, cases of the mixed ground-glass nodule (mGGN) were measured in two areas of ground-glass and solid components, CT value and iodine concentrations of lesions in three-phase scanning were separately measured, and at the same time, iodine concentrations of the thoracic aorta were also measured. The normalized iodine concentrations (NICs) were calculated, that is, the ratio of iodine concentrations of lesions and the thoracic aorta. CT values of lesions were also measured at each stage of 70 keV. All the quantitative data were expressed by the mean ± standard deviation, and paired t-test was used for pairwise comparison. Results. In 76 cases, in the spectral CT imaging mode, the NIC value of solid components of the GGN was 0.33 ± 0.16 in the arterial phase (AP), 0.52 ± 0.25 in the venous phase (VP), and 0.58 ± 0.34 in the delayed phase (DP). There were significant differences of

P

values of NICs between each two phases in both solid component cases and the ground-glass component cases in AP/VP, VP/DP, and AP/DP (

P
<
0.05

); there were no statistically significant

P

values of CT values between each two phases in three-period enhanced CT in both the solid component cases and the ground-glass component cases in AP/VP, VP/DP, and AP/DP (

P
>
0.05

). Conclusion. Gemstone energy spectral CT with quantitative imaging can dynamically reflect the enhancement features of the pulmonary GGN.
Physicochemical Properties and Biological Activities of Garden Cress (Lepidium sativum L.) Seed and Leaf Oil Extracts
Authors: Adera Fikremariam , Yusuf Zekeria , Desta Mulugeta
Published: March 2022

Garden cress (Lepidium sativum L.) seed is a rich source of proteins, dietary fiber, omega-3 fatty acids, iron, and other essential nutrients and phytochemicals. The aim of the present study was to investigate the physicochemical properties and biological activities of garden cress (L. sativum) seed and leaf oil extracts using solvent extraction methods. The result indicated that oil yield (25.75 ± 2.48%) and specific gravity (0.84 ± 0.08) were significantly (

P
<
0.05

based on least significance difference t-test) higher for seed oil extract. Seed oil also presented significantly (

P
<
0.05

) higher antioxidant activities with respect to ascorbic acid content (24.21 ± 3.04%) and DPPH (2, 2-diphenyl-1-picrylhydrazyl) (26.55 ± 0.21%) values. The leaf oil extract has exhibited stronger antibacterial activity with a maximum zone of inhibition (18.50 mm), a minimum inhibitory concentration (MIC) of 0.05 µg/ml, and a minimum bactericidal concentration (MBC) of 0.05 µg/ml against Staphylococcus aureus. Leaf oil extract has also demonstrated stronger antifungal activity with a maximum zone of inhibition (18.50 mm), MIC (0.25 µg/ml), and a minimum fungicidal concentration (MFC) of 0.50 µg/ml against Aspergillus Niger. The result suggesting that leaf oil presented superior antimicrobial but inferior antioxidant potential than seed oil in garden cress.
Mosapride Citrate Combined with Divine Qu Disinfectant Oral Liquid for Children Function Dyspepsia and the Influence of Serum Factors
Authors: Dou Zhenyun , Xu Zhou , Wang Qizheng , Li Jiangshu , Yu Chunlin , Miao Yequan , Ren Tailiang , Wang Haijun
Published: March 2022

In order to investigate the efficacy of mosapril citrate combined with ShenQu Xiaoshi oral liquid in the treatment of children with functional dyspepsia and the effect on serum cytokines, 136 children with functional dyspepsia admitted from May 2017 to September 2020 were divided into 2 groups randomly, 68 cases in each group. The western medicine group was treated with mosapril citrate tablets, and the combined group was treated with Shenqu xiaoshi oral liquid on the basis of the western medicine group. The efficacy of patients was evaluated 14 days after treatment, and the safety, symptom score, and serum cytokines of the two groups were compared. The results showed that, after 14 days of treatment, the scores of abdominal distension and abdominal pain (ADAP), lack of food (LOF), nausea and vomiting (NAV), irregular stool (IS), and mental fatigue (MF) in the combined group were all lower than those in the western group (

P
<
0.05

). There was no statistical significance in the incidence of diarrhea, abnormal liver and kidney, and allergic rash between the two groups (

p
>
0.05

). In conclusion, mosapride citrate tablets combined with Shenqu Xiaoshi oral liquid can achieve good therapeutic effects in children with functional dyspepsia, reduce symptom scores, improve serum cytokine levels, and have high drug safety, which is worthy of promotion and application.
Enhanced Feature Extraction-based CNN Approach for Epileptic Seizure Detection from EEG Signals
Authors: Dhar Puja , Garg Vijay Kumar , Rahman Mohammad Anisur
Published: March 2022

One of the most common neurological disorders is epilepsy, which disturbs the nerve cell activity in the brain, causing seizures. Electroencephalography (EEG) signals are used to detect epilepsy and are considered standard techniques to diagnose epilepsy conditions. EEG monitors and records the brain activity of epilepsy patients, and these recordings are used in the diagnosis of epilepsy. However, extracting the information from the EEG recordings manually for detecting epileptic seizures is a difficult cumbersome, error-prone, and labor-intensive task. These negative attributes of the manual process increase the demand for implementing an automated model for the seizure detection process, which can classify seizure and nonseizures from EEG signals to help in the timely identification of epilepsy. Recently, deep learning (DL) and machine learning (ML) techniques have been used in the automatic detection of epileptic seizures because of their superior classification abilities. ML and DL algorithms can accurately classify different seizure conditions from large-scale EEG data and provide appropriate results for neurologists. This work presents a feature extraction-based convolutional neural network (CNN) to sense and classify different types of epileptic seizures from EEG signals. Different features are analyzed to classify seizures via EEG signals. Simulation analysis was managed to investigate the classification performance of the hybrid CNN-RNN model in terms of different achievement metrics such as accuracy, precision, recall, f1 score, and false-positive rate. The results validate the efficacy of the CNN-RNN model for seizure detection.
Experimental Research for CHF Sensitivity of Heat Flux Distribution under IVR Conditions
Authors: Han Shilei , Liu Pengfei , Kuang Bo , Yang Yanhua
Published: March 2022

In-vessel retention (IVR) through external reactor vessel cooling (ERVC) is one of the most effective severe accident mitigation measures in the nuclear power plants. The most influential issues on the IVR strategy are in-vessel core melt evolution, the heat fluxes imposed on the lower head, and the external cooling of reactor pressurized vessel (RPV). In the molten pool research, there are mainly two different molten pool configurations: two layers and three layers. Based on the different distributions of heat flux in molten pool configurations, a new problem was raised: whether the in-vessel heat flux distribution will affect the CHF on the outer wall of RPV and further affect the effectiveness of IVR measures? A full-height external reactor vessel cooling and natural circulating facility was conducted to study the CHF sensitivity of different heat flux distributions. The experimental results show that the characteristics of natural circulation are similar and the CHF of the RPV lower head external surface is not obviously affected under the different heat flux distributions. The varying heat flux distribution during severe accident process will not threaten significantly the success of IVR strategy.
Medicinal Plants Utilized for the Treatment of Gastrointestinal Parasitosis in Ethiopia
Authors: Aschale Yibeltal , Reta Haimanot , Minwuyelet Awoke , Ayehu Animen , Wubetu Muluken
Published: March 2022

Background. Nonhygienic living conditions give rise to parasitic infections. Intestinal parasitosis is a serious public health problem in Ethiopia. It is more common in the poor part of the population with low-income, poor personal, and environmental sanitation and limited clean water supply. This review is aimed at providing an overview of the medicinal plants used for the treatment of gastrointestinal parasitosis in Ethiopia. Methods. International databases (PubMed, Google Scholar, Scopus, and Web of Science) were systematically searched to access published original articles on medicinal plants used to treat gastrointestinal parasitosis without restriction on the year of publication and methodology. The validity of articles was checked before inclusion in the review by undertaking critical appraisal using tools adapted from JBI Critical Appraisal Checklist. The details of medicinal plants were extracted from the included studies using a standardized data extraction format in excel spreadsheet and analyzed using descriptive statistics to calculate frequency and percentage. Results. A search for published articles produced a total of 205 papers, of which 23 met the inclusion criteria. Of the 85 medicinal plants identified, the majority (40.2%) were shrubs, and the common plant part used was leaf (28.2%). Family Asteraceae has the highest number of plant species. The majority of the plant remedies were given orally (96.9%). Taeniasis comprises the highest percentage of intestinal parasitosis treated followed by ascariasis. Conclusion. Numerous plants have been utilized to treat gastrointestinal parasitosis. Information obtained from this review could serve as a guide to discover novel antiparasitic agents. Therefore, it is advisable for researchers to properly identify, document, conserve, and conduct safety and efficacy studies on such claimed medicinal plants.
LSTM-Based Attentional Embedding for English Machine Translation
Authors: Jian Lihua , Xiang Huiqun , Le Guobin
Published: March 2022

In order to reduce the workload of manual grading and improve the efficiency of grading, a computerized intelligent grading system for English translation based on natural language processing is designed. An attention-embedded LSTM English machine translation model is proposed. Firstly, according to the characteristics of the standard LSTM network model that uses fixed dimensional vectors to represent words in the encoding stage, an English machine translation model based on LSTM attention embedding is established; the structure level of the English translation scoring system is constructed. A linguistic model of the English translation scoring system is established, and the probability distribution of a particular sentence sequence or word sequence of the translated text is statistically calculated using the model. The results show that the English machine translation model based on LSTM attention embedding proposed in this study can enhance the representation of the source language contextual information and improve the performance of the English machine translation model and the quality of the translation compared with the English machine translation models constructed by existing neural network structures, such as standard LSTM models, RNN models, and GRU-Attention translation models.
A Corpus‐Based Study of Public Attitudes towards Coronavirus Vaccines
Authors: Xia Ganlin , Chen Yiting , Lu Lijing
Published: March 2022

Since the beginning of 2020, COVID‐19 has been sweeping the world on an unprecedented scale. As an important means of fighting the virus, vaccines have provoked heated discussions. Motivated by this practical concern, the present study aims at contributing to the understanding of public opinions about vaccines, which may provide implications for the government in their making and implementation of related policies. This research adopts a corpus‐based approach in conjunction with a Critical Discourse Analysis (CDA). Data for this study drawn from the Coronavirus corpus show what people are actually saying in online newspapers and magazines in 20 different English‐speaking countries. The collocation and frequency of the word “vaccine” are arranged in concordance contextually. Overall, this study reveals that the collocation of vaccine can be divided into several categories, and people’s major concerns about COVID‐19 vaccination include global progress, equality, and the latest development.
Innovative Research on Urban Community Governance Decision-Making Relying on Distributed High-Performance Computing Blockchain Key Algorithms
Authors: Wen Jun , Xie Peihong
Published: March 2022

Since the country began to go global, the country’s economy has developed rapidly, cultural exchanges between countries have become more and more frequent, and foreign cultures have begun to gradually spread to the country. At the same time, through the absorption of foreign community governance experience, domestic research on community governance has also begun to be put on the agenda. This paper aims to study the innovative exploration of urban community governance mechanisms through key high-performance computing algorithms. To this end, this paper proposes a combination of the Bayesian algorithm and distributed high-performance computing to analyze and explore the governance and management methods of the community through its efficient and stable computing power, and derive the most suitable community governance mechanism. An experiment was also set up for comparative analysis. The experimental results show that the community governance mechanism derived from the key distributed high-performance computing algorithm improves the community governance capability by 19.4%, effectively improving the community governance and management issues.
Association of Antibiotic Resistance Traits in Uropathogenic Escherichia coli (UPEC) Isolates
Authors: Rahman Md. Mostafizer , Hossain Mridha Md. Kamal , Rubaya Rubaya , Halder Joyanta , Karim Md. Ekramul , Bhuiya Anjuman Ara , Khatun Anwara , Alam Jahangir
Published: March 2022

Background. Antimicrobial resistance (AMR) is a global health problem which is constantly evolving and varies spatially and temporally. Resistance to a particular antibiotic may serve as a selection and coselection marker for the same or different antibiotic classes. Therefore, this cross-sectional study was conducted to predict the association of phenotypic and genotypic resistance traits in uropathogenic Escherichia coli (UPEC). Method. A total of 42 UPEC from 83 urine samples were investigated for the prevalence and association of phenotypic and genotypic AMR traits. Antibiogram profiling was carried out by Kirby–Bauer’s disc diffusion method and AMR genes (ARGs) were detected by PCR. Result. UPECs were isolated from 50.60% (42/83) of the samples examined. Of these, 80.95% of cases were derived from females, and 38.10% of cases were found in the age group of 21–30 years. The isolates were shown to have a high frequency of resistance to tetracycline (92.86%), followed by sulfonamide (71.43%), ampicillin (52.38%), trimethoprim-sulfamethoxazole (47.62%), and 28.57% each to streptomycin, chloramphenicol, and erythromycin. The most prevalent antimicrobial resistance genes (ARGs) in these isolates were tet(A) (78.57%), tet(B) (76.19%), sul1 (61.91%), dfrA1 (35.71%), blaSHV (26.19%), cmlA (19.05%), and CITM, qnrA, and catA1 each at 11.91%. According to statistical analysis, ampicillin, sulfonamide, trimethoprim-sulfamethoxazole, and ciprofloxacin resistance were strongly correlated with the presence of blaSHV, sul1, dfrA1, and qnrA, respectively. Nonsignificant associations were observed between ciprofloxacin-tetracycline, sulfonamide-erythromycin pairs as well as between tet(A) and tet(B) genes. Besides, coselection was also assumed in the case of chloramphenicol resistance genes, namely, catA1 and cmlA. Conclusion. Both the phenotypic and genetic resistance traits were found in the UPEC isolates. Statistical association and coselection phenomena among AMR phenotypes and genotypes were also observed but required to be validated in a broad-scale study. However, these findings might have important implications for the development of an AMR prediction model to tackle future AMR outbreaks.
Sustainability Measurement of Transportation Systems in China: A System-Based Bayesian Network Approach
Authors: Jiang Wu , Huan Zhou
Published: March 2022

Sustainability has been a challenging issue in the transportation industry, which necessitates obtaining a better measurement of transport sustainability performance. To appropriately measure performance, this paper presents a hybrid approach based on the hierarchical Bayesian network model (BNM) and Principal Component Analysis (PCA). The proposed BNM encompasses social, economic, environmental, and technological dimensions, where each dimension consists of various subdivisions. The Conditional Probability Table of the model is determined by PCA. Twenty-three sustainable transportation indicators involved in the different stages of traffic management are used to kick off the calculation and probability propagation. The results show that the overall transport sustainability of the selected cities is generally at a medium level, indicating that there is much room for further improvement. The sustainability-economic coupling analysis exhibits the nonlinear relationship between sustainability and economic level, revealing that economic growth does not necessarily lead to the enhancement of the transport sustainability. Additionally, the sensitivity analysis reveals that “Accessibility,” “Serviceability,” “Reliability,” and “Innovation” demonstrate an upward trend, indicating their great effect on transportation sustainability. Last, the policy implications of this study can not only offer a solution for the current needs of transportation systems but also serve as more transparent decision-making to develop a sustainable transportation system in the future.
Identification of Novel Noninvasive Diagnostics Biomarkers in the Parkinson’s Diseases and Improving the Disease Classification Using Support Vector Machine
Authors: Moradi Shadi , Tapak Leili , Afshar Saeid
Published: March 2022

Background. Parkinson’s disease (PD) is a neurological disorder that is marked by the deficit of neurons in the midbrain that changes motor and cognitive function. In the substantia nigra, the selective demise of dopamine‐producing neurons was the main cause of this disease. The purpose of this research was to discover genes involved in PD development. Methods. In this study, the microarray dataset (GSE22491) provided by GEO was used for further analysis. The Limma package under R software was used to examine and assess gene expression and identify DEGs. The DAVID online tool was used to accomplish GO enrichment analysis and KEGG pathway for DEGs. Furthermore, the PPI network of these DEGs was depicted using the STRING database and analyzed through the Cytoscape to identify hub genes. Support vector machine (SVM) classifier was subsequently employed to predict the accuracy of genes. Result. PPI network consisted of 264 nodes as well as 502 edges was generated using the DEGs recognized from the Limma package under the R software. Moreover, three genes were identified as hubs: GNB5, GNG11, and ELANE. By using 3‐gene combination, SVM found that prediction accuracy of 88% can be achieved. Conclusion. According to the findings of the study, the 3 hub genes GNB5, GNG11, and ELANE may be used as PD detection biomarkers. Moreover, the results obtained from SVM with high accuracy can be considered as PD biomarkers in further investigations.
Experimental Analysis of Heat Transfer by Using Nanofluid and Impact of Thermophysical Properties
Authors: Karikalan L. , Baskar S. , Poyyamozhi N. , Negash Kassu
Published: March 2022

The scope of the project is to analyse the heat transfer behaviours by using shell and tube heat exchangers and measurements of various thermophysical properties of carbon nanotube nanofluid. The nanofluid is created using different volume fractions at different operation temperatures. The research focuses on theoretical and experimental research on CNT nanofluids, with the goal of improving thermophysical parameters such as thermal conductivity, specific heat, and viscosity. The thermophysical characteristics of CNTs were investigated using this theoretical method. Various tests were carried out to investigate the thermophysical qualities, and they were found to have an impact. The improved characteristics of carbon nanotubes (CNTs) have the potential to save energy and reduce CO2, NO2, and SO2 emissions in industrial settings. Improving heat exchange performance in the thermal sector would result in a high heat‐to‐power conversion efficiency. Nanofluids can considerably enhance critical heat flux (CHF) in heat transfer systems.
Application of Neural Network Based on Multisource Information Fusion in Production Cost Prediction
Authors: Wei Biaowen
Published: March 2022

Production cost forecasting is an important basis for cost accounting, cost decision-making, and cost planning. It is the scale necessary to reduce product costs and an important way to enhance enterprise competitiveness and improve system benefits. A neural network based on multisource information fusion is a manifestation of integrated internal knowledge. By learning to integrate multiple sources of information, it is easier to understand cognitive thinking and integrate the complex relationships of uncertain regions into regular signals. Fusion prediction does not need to understand the specific mechanism of the process but can fully approximate various nonlinear functional relationships determined by input and output with the continuous update of its internal weights. This paper mainly studies the application of neural network based on multisource information fusion in production cost prediction, analyzes the technology of multisource information fusion, and proposes a method of applying multisource information fusion theory to BP neural network and RBF network. Experiments have proved that through the comparison of the results of the BP neural network and the RBF network, for the six cost categories, compared with the BP neural network, the prediction results of the RBF network are closer to the true value, and they all show higher prediction capabilities. Among them, the error of the RBF network in predicting the total salary of the current month is 0.01004. The performance of the RBF network model is better than that of the BP neural network model.
Residue Classification-Based Robust Phase Unwrapping in High-Noise Region
Authors: Chen Xiaomao , Wen Zhongyuan , Wu Qi
Published: March 2022

Synthetic aperture radar interferometry can obtain information on the surface of the earth. In fact, the accuracy of phase unwrapping directly affects the accuracy of the digital elevation model, but the problem that has been puzzling people is the low accuracy of unwrapping in high-noise regions. To solve this problem, we propose a new approach based on an improved branch-cut method, which classifies the branch cut. First, connect the short branch cuts and then use the network-flow method to connect the long branch cuts. By categorized branch cuts, each type of branch cut processes part of the residues and divides the region with high residue density into two regions with low residue density for unwrapped, which solves the problem of low phase unwrapping accuracy in high-noise regions. The experimental results of simulation and measured data show that RCBC method shows high unwrapping accuracy in high-noise regions, very short total length of connected branch cuts, and strong robustness.
A Route Choice Model for Road Network Users in Mountainous Cities considering Vulnerability
Authors: Wu Lei , Lu Baichuan
Published: March 2022

Urban resilience has become one of the core arguments of sustainable urban development. The urban road system should also respond effectively to various changes or impacts and reduce the uncertainty and vulnerability of road network caused by emergencies. A route choice model considering the vulnerability was proposed. The model analyzed the traveler’ behavior in complex road network. The model is validated by the road network in Chongqing city. First, the vulnerability of road network in mountainous cities is defined, and the failure situation and state classification of road network considering vulnerability are analyzed. The results show that travelers with different sensitive states have obvious different route choice behavior in vulnerable networks. Since nonsensitive users do not reserve travel time in the early days, they are more inclined to respond to emergencies quickly and then choose fast detour paths. However, sensitive users have set off earlier than normal time and have psychological expectations of emergencies. They have more time to maintain the existing path. Finally, a calculation example is used to test that a certain section of the road network fails randomly, and network users can effectively choose the individual optimal route under different failure states.
A Mathematical Model for the Growth Dynamics of Demand in the Fashion Industry within the Era of the COVID-19 Pandemic
Authors: Addor John Awuah , Turkson Anthony Joe , Kparib Douglas Yenwon
Published: March 2022

The outbreak of COVID-19 infection and its effects have not spared any economy on the globe. The fourth variant has just announced its appearance with its high death toll and impact on economic activities. The basic reproductive number

R

0

, which measures the transmission potential of an infectious disease, is extremely important in the study of epidemiology. The main purpose of this study was to derive

R

0

and assess the stability of the model around its equilibrium points. The motivation was to simulate the effect of COVID-19 on the demand for fashion products and how its application has impacted the COVID-19 pandemic. A five-compartment susceptible-infection-recovery-susceptible-based model was formulated in an integrated environment with application of fashion-based personal protective equipment (FPPEs) and government policy regulation, using ordinary differential equations. Solution techniques included a mix of qualitative analysis and simulations with data from various publications on COVID-19. The study revealed that the disease-free equilibrium was both locally and globally asymptotically stable (LAS and GAS) for

R

0

≤
1

, while the disease-endemic equilibrium was both LAS and GAS for

R

0

≥
1

. As the demand for FPPEs increases,

R

0

decreases, and vice versa. The sensitivity analysis indicated that

R

0

was very sensitive to the rate of application of FPPEs. This confirms the significance of high demand for FPPEs in reducing the transmission of COVID-19 infection. Again, the pandemic has had both positive and negative impacts on the demand for fashion products; however, the negative impact outweighed the positive impact. Another discovery was that government policy stringency was significant in increasing demand for FPPEs. The sensitivity analyses suggested prioritization of FPPEs application together with all recommended PPEs. We recommend inter alia that FPPEs be used together with other nonpharmaceutical interventions. Operators in the fashion industry must be dynamic in adjusting to the new trends of taste for fashion products. Finally, governments should maintain high policy stringency.
A Study for Plausible Third Wave of COVID-19 in India through Fuzzy Time Series Modelling Based on Particle Swarm Optimization and Fuzzy c-Means
Authors: Kumar Niteesh , Kumar Harendra , Kumar Kamal
Published: March 2022

The outbreak of COVID-19 has become a global pandemic as announced by World Health Organisation. As India has already met the two waves, named first and second wave, it is assumed that COVID-19 will again strike in India in the form of third wave. The peak during the upcoming third wave and determination of the approximated maximum number of COVID-19 infected cases and deaths at a particular day becomes crucial for India. To determine the peak of infectious curve, this article proposed a hybrid fuzzy time series forecasting model based on particle swarm optimization and fuzzy c-mean technique, named as fuzzy time series particle swarm optimization extended fuzzy c-mean technique. The proposed model works in two phases. In phase-I, particle swarm optimization extended fuzzy c-mean method is used to form initial intervals with the help of centroids, while in phase-II, these intervals are updated to form subintervals. In the present article, a fitness function is developed for particle swarm optimization to increase its convergence speed and basic fuzzy c-mean is extended by using an exponential function to tolerate the effect of outliers, named as extended fuzzy c-mean technique. The effectiveness of the proposed model has been tested based on mean square error and root mean square error on first and second wave COVID-19 data, and the obtained results are very close to the existing data of COVID-19 with less error rate. Thus, the proposed model is suitable to forecast a better approximation value of COVID-19 infected cases and deaths in India during the upcoming third wave. This study demonstrates that third wave of COVID-19 could occur in India, while also illustrating that it is unlikely for any such resurgence to be as large as the second wave. The proposed model predicts that the peak of third wave will occur approximately after 40–70 days from the mid of December. Furthermore, the impact of vaccination on infected cases and deaths during the upcoming third wave in India is also studied. With the implementation of the vaccine on the Indian people, the peak of COVID-19 infected during third wave will be shifted in forward direction. On the basis of the proposed model, government authorities will be enabling to know expected required resources such as hospital patient beds, ICU beds, and oxygen concentrators during the upcoming outspread of COVID-19 like disease in future.
A Study on the Application of Computer-Aided Dual-Coding Theory in English Vocabulary Teaching
Authors: Luo Li
Published: March 2022

Learning English needs a huge amount of vocabulary recalls as well as multiple grammatical structures and practices. With the development and improvement of the humanization and quality of English teaching, the multidimensional teaching of English has formed a powerful learning model and teaching method. The teaching of dual-coding theory assisted by computer teaching software mainly focuses on the dual activation representation of language combined with nonverbal graphic recognition to complete the recognition of information. According to the dual-coding hypothesis, in Gilford’s intelligence theory, the capacity of spatial and information recognition and reading is highly significant. With the large amount of visual recognition and information acquisition, images involve spatial domain information reading, which is a learning method based on the principle of information feature recognition. Based on the principle of dual-coding theory, it is a very effective way to present information and recall specific information in the form of vision and language. In this study, the application research for the purpose of English vocabulary teaching is adopted that has strong innovative and practical characteristics. According to the steps and contents of English vocabulary learning, the study is carried out step by step from the context in detail, so it continuously improves the learning quality and efficiency of English vocabulary teaching. Vocabulary teaching can help the students better improve their cognitive level of vocabulary and meet the vocabulary test requirements of the new institution entrance examination. Further, how to improve the effect of senior high school English vocabulary teaching is a major topic in the field of senior high school English teaching. In order to sort out this issue, I proposed a computer-aided dual-coding theory to help quickly understand vocabulary usage in order to increase learning efficiency. The Paivio–Desrochers model is used in this study. In addition, this study also attempts to explore the application of dual-coding theory in senior high school English vocabulary teaching.
Clinical Efficacy and Safety of Percutaneous Spinal Endoscopy versus Traditional Open Surgery for Lumbar Disc Herniation: Systematic Review and Meta-Analysis
Authors: Xu Xingping , Chen Changwei , Tang Yong , Wang Fusheng , Wang Yangsheng
Published: March 2022

Objective. Systematic analysis of the incidence of percutaneous spinal endoscopic technique and traditional open surgery for lumbar disc herniation. Methods. A randomized controlled trial (RCT) and cohort study on complications related to traditional open surgery was searched on the MEDLINE, Cochrane Library, PubMed, Web of Science, Chinese journal full-text database (CNKI), Wanfang, and Embase database. Language is not limited. The quality of each study was evaluated, various complications were compiled into electronic baseline tables, and the data from these studies were available. Meta-analysis and synthesis were performed with the RevMan 5.3 software to evaluate the statistical significance of both surgical techniques in terms of various complications. Results. 12 studies were eventually included, and a total of 2,797 patients were included in the analysis. Meta-analysis results showed that there was no statistical difference in postoperative paresthesia between percutaneous spinal endoscopy and traditional open surgery (OR = 1.17, 95% CI (0.82, 1.66),

P

 = 0.38, I2 = 0%, Z = 0.88), direct nerve root damage (OR = 0.79, 95% CI (0.58, 1.07),

P

 = 0.13, I2 = 73%, Z = 1.52), and intraoperative hemorrhage and hematoma formation (OR = 1.00, 95% CI (0.67, 1.48),

P

 = 0.99, I2 = 0%, Z = 0.02), but there was a statistical difference in disc recurrence (OR = 2.24, 95% CI (1.56, 3.21),

P

 < 0.0001, I2 = 81%, Z = 4.39). Conclusion. Compared with the traditional open surgical treatment of lumbar disc herniation, percutaneous spinal endoscopic technology has obvious advantages in reducing nerve root injury, dural injury, and surgical area wound complications, but it is limited to preventing the technical characteristics of the surgical site, which is worse than that of open surgery.
Research on the Construction Model of 5G Special Town Based on Edge Computing
Authors: Da Qi , Pengchao Xing
Published: March 2022

This study conducts a study on edge computing technology, focusing on the advantages of edge computing technology and its applications, and delves into the edge computing architecture, which leads to an in-depth study on the construction of a 5G special town model. Based on the existing 5G characteristic town construction model, this study proposes a new model of edge computing and proposes an application partitioning algorithm based on this model by analyzing the edge computing scheduling scenarios to minimize the total time cost of the system. By analyzing the edge computing scheduling scenarios, an application partitioning algorithm based on this model is proposed, so that the total time cost of the system is minimized. This study analyzes and studies the current situation of infrastructure construction, and investment in the special town analyzes the significance and purpose of its construction and develops the research method and technical route of this study as a result. Then, the connotation of characteristic town and infrastructure is elaborated, and the value, characteristics, and role of infrastructure construction of characteristic town are analyzed; the influencing factors of infrastructure investment in characteristic town are analyzed; the development of the characteristic town has endless potential, and the development of characteristic town must meet the demand of social economy as well as town population for infrastructure support. However, there are more risk factors for infrastructure investment in characteristic towns, and the investment risk is larger than general projects, so it is necessary to strengthen risk management and do a good job of investment protection.
Acupuncture and Moxibustion for Peripheral Neuropathic Pain: A Frequentist Network Meta-Analysis and Cost-Effectiveness Evaluation
Authors: Zhao Weixuan , Huang Haoming , Liu Kun , Wang Shuxin , Lin Shiyu , Long Wenjie , Li Lixia , Zeng Jingchun , Lin Guohua
Published: March 2022

Purpose. Acupuncture and moxibustion techniques have been increasingly used to treat peripheral neuropathic pain (PNP). However, there is a paucity of comparative information and cost-effectiveness assessment for techniques on PNP management. Patients and Methods. Randomized controlled trials studying the acupuncture or moxibustion treatments on PNP were identified from electronic databases. The quality of the included studies and the potential risk of bias was evaluated using the ROB 2.0 assessment tool. The primary outcome was at least 20% pain relief. The treatment effects were pooled through a frequentist-based network meta approach. Subsequently, the cost-effectiveness measured by incremental cost per additional responder (ICPR) was calculated. Results. One three-arm trial and 15 two-arm trials comprising 1308 participants that satisfy the eligibility criteria were identified. Among the included studies, 12.5% were at low risk of bias, 68.75% had some concerns about the risk of bias, and 18.75% were at high risk of bias. The major sources of bias originated from the randomization processes of the studies. The patients were assigned to seven different acupuncture or moxibustion interventions and two pharmaceutical treatments. Except for acupoint injection, all the included acupuncture and moxibustion techniques showed superior improvements in PNP and were more cost-effective as compared to pharmaceutical treatments. Warm needling, fire needling, and moxibustion were the most effective treatments. Fire needling showed the lowest ICPR relative to the nonsteroidal anti-inflammatory drugs in the cost-effectiveness analysis of direct and indirect costs. Conclusion. Acupuncture and moxibustion techniques are beneficial and cost-effective approaches for easing PNP and hence can be considered for PNP management.
Long Noncoding RNA MMP2-AS1 Contributes to Progression of Renal Cell Carcinoma by Modulating miR-34c-5p/MMP2 Axis
Authors: Fan Bo , Niu Yunfeng , Ren Zongtao , Wei Shufei , Ma Yongliang , Su Jianzhi , Zhang Aili
Published: March 2022

Renal cell carcinoma (RCC) serves as a prevalent malignancy of urinary system and presents severe mortality and increasing incidence. Long noncoding RNAs (lncRNAs) have demonstrated critical roles in RCC development. Here, we were interested in the function of MMP2-AS1 during RCC progression. We observed that MP2-AS1 localized in both nucleus and cytoplasm of RCC cells using fluorescent in situ hybridization (FISH). The cell viability, proliferation, invasion, and migration of RCC cells were reduced by the depletion of MMP2-AS1. The MMP2-AS1 depletion-inhibited viability, proliferation, migration, and invasion of RCC cells were rescued by the overexpression of MMP2 in vitro. Consistently, the tumor growth of RCC cells was repressed by the depletion of MMP2-AS1 in the nude mice, while the overexpression of MMP2 could reverse this effect in vivo. Mechanically, we predicted the potential interaction of miR-34c-5p with both MMP2-AS1 and MMP2. The treatment of miR-34c-5p mimic reduced the luciferase activity of MMP2-AS1 and MMP2 3

′

UTR. The depletion of MMP2-AS1 enhanced miR-34c-5p expression and the expression of MMP2 was inhibited by miR-34c-5p in RCC cells. The protein levels of MMP2 were downregulated by MMP2-AS1 knockdown, while the inhibitor of miR-34c-5p rescued the expression of MMP2 in the cells. The treatment of miR-34c-5p mimic attenuated the cell viability, proliferation, invasion, and migration of RCC cells, in which MMP2 overexpression restored the phenotypes. MMP2-AS1 depletion-attenuated viability, proliferation, migration, and invasion of RCC cells were reversed by miR-34c-5p inhibitor. We concluded that MMP2-AS1 contributed to progression of renal cell carcinoma by modulating miR-34c-5p/MMP2 axis.
Crosslinked Decellularized Porcine Pericardium as a Substrate for Conjunctival Reconstruction
Authors: Chen Fangyuan , Deng Jingyue , Luo Lishi , Zhu Ying , Dong Yuying , Yang Yuanting , Zhang Rijia , Chen Jian , Zhou Qing
Published: March 2022

Seeking for suitable conjunctival reconstruction substitutes to overcome the limitations of current substitutes, such as amniotic membrane, is urgent. Decellularized tissues have become a promising strategy for tissue engineering. In this study, we prepared decellularized porcine pericardium (DPP) scaffolds by the phospholipase A2 method and crosslinked them with aspartic acid (Asp) and human endothelial growth factor (hEGF) to enhance biological performance on the DPP, obtaining DPP-Asp-hEGF scaffolds. In vitro DPP showed lower apoptosis, highly desirable, well preservation of extracellular matrix components, and favorable macro-microstructure, which was confirmed by histology, immunofluorescence, electron microscopy, collagen and DNA quantification, and cytotoxicity assay, compared to the native porcine pericardium (NPP). The crosslinked efficacy of the DPP-Asp-hEGF was furtherer verified by in vitro experiments with Fourier transform infrared (FTIR) and X-ray diffraction (XRD). Through animal models of conjunctiva defect model, the DPP-Asp-hEGF revealed a closed, multilayer epithelium with an equal amount of goblet cells and no indication for conjunctival scarring after 28 days, compared to amniotic membrane (AM) groups and sham groups. These results suggested that DPP-Asp-hEGF can offer a good conjunctival reconstructive substitute both in structure and in function.