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1.
International Transactions in Operational Research ; 2022.
Article in English | Scopus | ID: covidwho-1874435

ABSTRACT

The spread of COVID-19 outbreak has promoted truck-drone delivery from trials to commercial applications in end-to-end contactless solutions. To fully integrate truck-drone delivery in contactless solutions, we introduce the robust traveling salesman problem with a drone, in which a drone makes deliveries and returns to the truck that is moving on its route under uncertainty. The challenge is to find, for each customer location in truck-drone routing, an assignment to minimize the expected makespan. Apart from the complexity of this problem, the risk of synchronization failure associated with uncertain travel time should be also considered. The problem is first formulated as a robust model, and a novel efficient frontier heuristic is proposed to solve this model. By coupling the implicit adaptive weighting with epsilon-constraint methods, the heuristic generates a series of scalarized single-objective problems, where the goal is to minimize expected makespan under the constraint of synchronization risk. The experiment results show that the robust (near-)optimal solutions offer a considerable reduction in risk, yet only hint at a small increase in makespan. The heuristic in the present study is effective to construct approximations of Pareto frontier and allows for assignment decisions in a priori or a posteriori manner. © 2022 The Authors. International Transactions in Operational Research © 2022 International Federation of Operational Research Societies.

2.
International Review of Research in Open and Distributed Learning ; 23(2):25-43, 2022.
Article in English | Web of Science | ID: covidwho-1865957

ABSTRACT

Within the COVID-19 pandemic and the new normal period, online learning has become one of the main options for learning. Previous studies on self-regulated learning have shown that it was a better predictor of online learning effectiveness. However, this discussion has not been extended to the situation of the COVID-19 pandemic. To address this gap, this study aims to explore the relationship between the three stages of self-regulated learning (SRL) and learning ineffectiveness (LI). Data of 370 high school students were collected during the period of COVID-19. Structural equation modeling was used to perform confirmatory factor analysis on the data. Findings show that the preparatory stage was positively related to the stages of performance and appraisal, and the performance stage was positively related to the appraisal stage;on the other hand, the stages of performance and appraisal were negatively related to learning ineffectiveness. In addition, the preparatory stage had no direct relation to learning ineffectiveness, but the preparatory stage was correlated with learning ineffectiveness, mediated by the stages of performance and appraisal. These results suggest that better performance in the three stages of self-regulated learning decrease learners' perceived online learning ineffectiveness. This understanding can have implications for global education.

3.
Asia Pacific Journal of Marketing and Logistics ; : 30, 2022.
Article in English | Web of Science | ID: covidwho-1853320

ABSTRACT

Purpose This study investigated whether there are differences in the effects of green traditional media communication (GTMC) and green social media communication on consumers' intention to cocreate green value (ICGV) in post-COVID-19 China. The authors further tested the chain mediating role of cocreation efficacy and cocreation outcome expectation and the moderating role of perceived CSR image. Design/methodology/approach Using a survey, we collected a dataset of 683 consumers through stratified random sampling in main shopping malls in four Chinese cities. Structural equation modeling (SEM) was used to test the conceptual framework and hypotheses, and bootstrapping was used to estimate the mediated standardized regression coefficients. Multiple linear regression analysis was used to test the moderating effect. Findings GTMC, firm-created content (FCC), and user-generated content (UGC) all had positive effects on ICGV. Cocreation efficacy and cocreation outcome expectation had a chain mediation effect in GTMC and ICGV, UGC, and ICGV. Perceived CSR image positively moderated the effects of both GTMC and FCC on ICGV. However, perceived CSR image did not significantly moderate the relationship between UGC and ICGV. Originality/value This study contributes to our understanding of the effect of green media communication on consumers' ICGV in post-COVID-19 China. It also develops the concepts of cocreation efficacy and cocreation outcome expectation. Moreover, analyzing the chain mediating role of cocreation efficacy and cocreation outcome expectation in green media communication and ICGV extends social cognitive theory to the context of green value cocreation. Finally, examining the moderating role of perceived CSR image provides a basis for understanding the boundary conditions of green media communication's effect on ICGV.

4.
Kuei Suan Jen Hsueh Pao/Journal of the Chinese Ceramic Society ; 50(4):1143-1159, 2022.
Article in Chinese | Scopus | ID: covidwho-1835964

ABSTRACT

Scintillators as the core materials of radiation detection play an important role in industrial nondestructive testing, medical imaging, high energy physics and safety inspection, etc.. Theexisting scintillator research faces both opportunities and challenges, especially in the context of COVID-19 pandemic period. It is of great practical significance to develop cost-effective scintillators and optimize their overall performance. The nano-glass composites (i.e., glass ceramics) have some advantages like high emission efficiency of scintillator crystals, simple preparation and low cost as an effective star scintillator. Based on the different luminescence centers, such scintillators can be broadly divided into rare-earth element ions doped or rare-earth-free luminescent nanocrystals embedded materials. This review represented recent development on the preparation of these materials, the relationship between the types of nanocrystals and their luminescence properties, and the potential applications of these materials in high-energy X-ray and gamma-ray detection. In addition, the existing problems in the research were discussed and the future development direction of nano-glass composite scintillators was also prospected. © 2022, Editorial Department of Journal of the Chinese Ceramic Society. All right reserved.

5.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334805

ABSTRACT

Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2's immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals' plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents' plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants.

6.
Chinese Journal of Pharmacology and Toxicology ; 35(1):1-13, 2021.
Article in Chinese | EMBASE | ID: covidwho-1820653

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has led to the urgent need to develop therapeutic drugs to respond to disease progression and treatment of patients. Drug repur- posing is one of the potential ways to rapidly find treatments for emerging viral infection. Favipiravir is a novel broad-spectrum antiviral drug that has been approved for new and re-emerging pandemic influenza. As a potential drug against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, favipiravir is currently under clinical trials in several countries and has shown promising results in clinical studies. This paper reviews the clinical studies on the treatment of COVID-19 with favipiravir or combination with other drugs by focusing on the data about dose, trial design, efficacy and safety in China, Japan, Russia and India. Favipiravir with proven safety profiles has proved to be effective in improving viral RNA clearance or clinical recovery in patients with mild and moderate symptoms. This review will help gain insights into the evidence based role of favipiravir in antiviral therapy of COVID-19.

7.
Indoor and Built Environment ; : 19, 2022.
Article in English | Web of Science | ID: covidwho-1819962

ABSTRACT

The novel corona respiratory viruses usually leave the host via droplets and float in the air or settle down. Medically, the decay characteristics of aerosolized viruses have been simulated and measured by atomizing suspensions into air, but there has been no systematic study on the effect of ambient temperature and humidity. In this study, we collected experimental data from existing medical studies, then introduced and calculated the initial decay constant (k(1)) and the secondary decay constant (k(2)) based on these data as a unified standard to quantify the decay process of the aerosolized viruses. Additionally, the influence of various factors on the decay constant of respiratory viruses in the air was statistically analyzed. The results showed that the phase decay of aerosolized viruses was very evident, and k(1) (0.1 similar to 50) was usually one order of magnitude higher than k(2) (0.005 similar to 3.2). Furthermore, the relationship between the decay constant and the survival rate of viruses, representing the risk of virus transmission, and the decay time constants, reflecting the effective period of prevention and control, was discussed. According to the decay law, the main contradiction between virus transmission and epidemic prevention and control at different time nodes was pointed out, and scientific measures to reduce the transmission risk in the built environment were recommended.

8.
Journal of Chinese Economic and Business Studies ; : 10, 2022.
Article in English | Web of Science | ID: covidwho-1815851

ABSTRACT

Public health diplomacy is a diplomatic practice that focuses on addressing public health crises, such as infectious diseases. It is mainly implemented by sovereign states and relies on the joint efforts of health and foreign affairs departments, under the leadership and coordination of international organizations such as the WHO. The purpose is to safeguard national interests and promote global health governance through international medical cooperation. Public health diplomacy has presented new characteristics in the 21st century: health and diplomacy are more and more deeply integrated, involving an increasing number of players;Competition, which co-exists with cooperation on public health, is intensifying in this century;Countries endow this diplomacy with their own characteristics by leveraging their advantages. Compared with that of European countries and America, China's public health diplomacy started late, but has shown its unique characteristics.

9.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333792

ABSTRACT

Patients with COVID-19 present with a wide variety of clinical manifestations. Thromboembolic events constitute a significant cause of morbidity and mortality in patients infected with SARS-CoV-2. Severe COVID-19 has been associated with hyperinflammation and pre-existing cardiovascular disease. Platelets are important mediators and sensors of inflammation and are directly affected by cardiovascular stressors. In this report, we found that platelets from severely ill, hospitalized COVID-19 patients exhibit higher basal levels of activation measured by P-selectin surface expression, and have a poor functional reserve upon in vitro stimulation. Correlating clinical features to the ability of plasma from COVID-19 patients to stimulate control platelets identified ferritin as a pivotal clinical marker associated with platelet hyperactivation. The COVID-19 plasma-mediated effect on control platelets was highest for patients that subsequently developed inpatient thrombotic events. Proteomic analysis of plasma from COVID-19 patients identified key mediators of inflammation and cardiovascular disease that positively correlated with in vitro platelet activation. Mechanistically, blocking the signaling of the FcgammaRIIa-Syk and C5a-C5aR pathways on platelets, using antibody-mediated neutralization, IgG depletion or the Syk inhibitor fostamatinib, reversed this hyperactivity driven by COVID-19 plasma and prevented platelet aggregation in endothelial microfluidic chamber conditions, thus identifying these potentially actionable pathways as central for platelet activation and/or vascular complications in COVID-19 patients. In conclusion, we reveal a key role of platelet-mediated immunothrombosis in COVID-19 and identify distinct, clinically relevant, targetable signaling pathways that mediate this effect. These studies have implications for the role of platelet hyperactivation in complications associated with SARS-CoV-2 infection. Cover illustration: ONE-SENTENCE SUMMARY: The FcgammaRIIA and C5a-C5aR pathways mediate platelet hyperactivation in COVID-19.

10.
Web of Science; 2021.
Preprint in English | Web of Science | ID: ppcovidwho-331129

ABSTRACT

Background The worldwide surge in coronavirus cases has led to the COVID-19 testing demand surge. Rapid, accurate, and cost-effective COVID-19 screening tests working at a population level are in imperative demand globally. Methods Based on the eye symptoms of COVID-19, we developed and tested a COVID-19 rapid prescreening model using the eye-region images captured in China and Spain with cellphone cameras. The convolutional neural networks (CNNs)-based model was trained on these eye images to complete binary classification task of identifying the COVID-19 cases. The performance was measured using area under receiver-operating-characteristic curve (AUC), sensitivity, specificity, accuracy, and F1. The application programming interface was open access. Findings The multicenter study included 2436 pictures corresponding to 657 subjects (155 COVID-19 infection, 23·6%) in development dataset (train and validation) and 2138 pictures corresponding to 478 subjects (64 COVID-19 infections, 13·4%) in test dataset. The image-level performance of COVID-19 prescreening model in the China-Spain multicenter study achieved an AUC of 0·913 (95% CI, 0·898-0·927), with a sensitivity of 0·695 (95% CI, 0·643-0·748), a specificity of 0·904 (95% CI, 0·891 -0·919), an accuracy of 0·875(0·861-0·889), and a F1 of 0·611(0·568-0·655). Interpretation The CNN-based model for COVID-19 rapid prescreening has reliable specificity and sensitivity. This system provides a low-cost, fully self-performed, non-invasive, real-time feedback solution for continuous surveillance and large-scale rapid prescreening for COVID-19.

11.
Blood ; 138:4239, 2021.
Article in English | EMBASE | ID: covidwho-1736303

ABSTRACT

Objective: To analyze the relationship between D-dimer, inflammatory markers, cytokines and disease severity, and the possibility of early identification of COVID-19 critical type patients. Methods: PubMed, EMBASE and CNKI databases were searched by computer, and references of related reviews and systematic reviews were manually searched as supplements. The retrieval deadline is February 9, 2021. According to the inclusion and exclusion criteria, the literatures were screened and the quality was evaluated, and then the data were extracted for meta-analysis. The fixed/random effects model was used to calculate the weighted mean difference (WMD) and 95% CI to evaluate whether the levels of D-dimer, hsCRP, IL-6, IL-8, IL-10 and TNF-α in critical type patients were statistically different from those in severe type patients. If there were statistical differences, logistic regression analysis was used, and establish the receiver operating characteristic curve (ROC) and area under the curve (AUC) of each index for the diagnosis of critical type patients. The best diagnostic value of COVID-19 critical type patients was calculated by Youden index. Results: A total of 3519 literatures entered the screening process. According to the inclusion and exclusion criteria, 40 articles were finally included in this study, and all of them were high-quality studies after evaluation. The results of meta-analysis showed that the levels of D-dimer, hsCRP, IL-6, IL-8 and IL-10 in critical type group were significantly higher than those in severe type group (P<0.05). Based on ROC curve, the AUC of D-dimer was 0.785 (95% CI: 0.671-0.899), AUC of hsCRP was 0.884 (95% CI: 0.632-1.000), AUC of IL-6 was 0.819 (95% CI: 0.700-0.939), which had diagnostic significance for critical type patients (P<0.05). The optimal diagnostic threshold of D-dimer was ≥2.00 mg/L (sensitivity 89.3%, specificity 64.0%);the optimal diagnostic threshold of hsCRP was ≥64.22 mg/L (sensitivity 75.0%, specificity 100%);the optimal diagnostic threshold of IL-6 was ≥33.01 ng/L (sensitivity 68.0%, specificity 92.0%). Conclusion: The levels of D-dimer, hsCRP, IL-6, IL-8 and IL-10 in COVID-19 critical type patients were significantly higher than those in severe type patients. Our results might be helpful in identify and risk reduction of mortality in critical types patients infected with COVID-19. Disclosures: No relevant conflicts of interest to declare.

12.
Educational Technology and Society ; 25(1):142-154, 2022.
Article in English | Scopus | ID: covidwho-1728221

ABSTRACT

With the outbreak of COVID-19, more online learning has been adopted for distance learning. However, the effectiveness of online learning for those students engaged in it for the first time has not been discussed. This study aims to investigate perceived ineffectiveness of online learning and its antecedents related to cognitive and affective factors. Internet self-efficacy (ISE) and Self-efficacy of interacting with learning content (SEILC) were hypothesized to have a correlation with perceived ineffectiveness of online learning (PIOL) mediated by participants’ Internet cognitive fatigue (ICF) and mind-unwandered, while ICF was hypothesized to have a correlation with mind-unwandered. Data of 251 students collected from high schools in China during the lockdown period of COVID-19 were subjected to confirmatory factor analysis via AMOS. Results indicated that participants’ ISE and SEILC were positively related to mind-unwandered, but negatively related to ICF during online learning, while ICF was positively associated with PIOL. On the other hand, mind-unwandered was negatively associated with PIOL. Furthermore, students’ ISE and SEILC indirectly affected their PIOL mediated by ICF. Findings suggest that an enhancement of learners’ ISE and SEILC could have reduced the level of PIOL the first time that online learners experienced under the COVID-19 lockdown to promote their learning effectiveness. This understanding will be useful in case of another pandemic outbreak. © 2022, Educational Technology and Society. All rights reserved.

13.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-329492

ABSTRACT

Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p-value=9.37*10 -4 , 1.0*10 -15 , 4.76*10 -7 and 1.56*10 -4 , respectively), and five additional polymutants in non-spike genes (D343G in nucleocapsid phosphoprotein, V1069I in nsp3, V94A in nsp4, F694Y in the RNA-dependent RNA polymerase and L106L/F of ORF3a) that exhibit significant increasing trajectories (all p-values < 1.0*10 -15 ). In the absence of relevant clinical data for these newly emerging mutations, it is important to monitor them closely. Two emerging mutations may be of particular concern: the N1192S mutation in spike protein locates in an extremely highly conserved region of all human coronaviruses that is integral to the viral fusion process, and the F694Y mutation in the RNA polymerase may induce conformational changes that could impact Remdesivir binding.

14.
Climate Change Economics ; 2022.
Article in English | Scopus | ID: covidwho-1699181

ABSTRACT

This study is intended to test the role of renewable energy financing on climate change and to present the implications for the key stakeholders towards the acquisition of post-covid-recovery in the Asian and ASEAN economies. For this, data envelopment analysis (DEA) technique is applied to draw an inference between the constructs. Study finding resulted that higher energy consumption and rise in environmental pollution has brought a great change in the ASEAN and Asian economies' climate, for which, modern and renewable energy sources are suggested to use for the climate change mitigation. A sufficient amount of funds and the supply of energy finance to mitigate the climate change are eminently needed for the post-covid-recovery. Different financial institutions, banks and finance ministries of countries belonging from the both regions are suggested to play the best role. This is solely possible by pooling the funds in renewable energy sectors to enhance energy efficiency and control the climate change. This must be executed for the long-run period to get the desired outcomes. All the countries of both regions are further suggested to expedite the practices to apply strategic development goals (SDGs) for affordable and clean energy (SDG-7), climate change action (SDG-13) to achieve the national and global strategic objectives. © 2022 World Scientific Publishing Company.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315413

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) has rapidly spread to more than 200 countries. Thus far, reports regarding multi-center data from throughout gestation in women with COVID-19 and newborn outcomes are scarce. Methods: : We retrospectively reviewed data from 92 pregnant women with COVID-19 (PW-COVID-19) and their 78 newborns from 27 hospitals in 12 regions of Hubei, China. The demographic, epidemiological, clinical, laboratory, and therapeutic data and pregnancy, perinatal, and neonatal outcomes were analyzed. Follow-up was censored until April 7, 2020. Findings: Median maternal age was 31.0 years (IQR 28·0-33·0), with nine patients in the first trimester, five in the second trimester, and 78 in the third trimester. None of the patients died, and most (92·4%) recovered and were discharged. Seventy-five deliveries (including three sets of twins) comprised 66 cesarean sections and nine vaginal deliveries, with 21 preterm and 57 full-term infants. Seventeen live births had radiological findings of pulmonary infection. One newborn tested positive for SARS-CoV-2 nucleic acid, and three newborns were viral antibody-positive: two IgG (+) and IgM (-), and one IgG (+) and IgM (+). The median suspected duration of virus exposure was 7 days (IQR 0 to 27). Interpretation: Compared to the pregnant women with other viral infections, such as SARS, MERS, and Zika virus infection, PW-COVID-19 had similar manifestations and relatively better outcomes. The termination time and delivery mode in PW-COVID-19 should be evaluated based on both the maternal and fetal situations. The possibility of maternal-to-fetal transmission of SARS-CoV-2 requires further investigation.Authors Shujie Liao and Renjie Wang contributed equally to this work.

16.
3rd IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021 ; : 576-579, 2021.
Article in English | Scopus | ID: covidwho-1672710

ABSTRACT

Under the background of comprehensively deepening reform and opening up, Xiamen,China's special economic zone, One of the earliest cities in China to carry out reform and opening up,faces a new era of economic development. However, due to the impact of covid-19,the economic situation at home and abroad is terrible, thus predicting Xiamen's GDP is necessary for the better economic development of Xiamen, as it can help Xiamen to carry on macro-control to economy earlier.In this article, the quarterly GDP of Xiamen City from 2009 to 2020 was selected to analyze the economic situation of Xiamen City, and the ARIMA (Autoregressive Integrated Moving Average mode) (4,1,1) (0,1,0) 4 model is established through time series analysis to predict the GDP of Xiamen City in four quarters in 2021,And the results show that the GDP2021 will be 111.56% of GD2020.Based on the analysis of the forecast results, the paper also gives policy suggestions on the economy for Xiamen Government. © 2021 IEEE

17.
3rd International Conference on Intelligent Medicine and Health, ICIMH 2021 ; : 115-124, 2021.
Article in English | Scopus | ID: covidwho-1648379

ABSTRACT

Objective: The purpose of this study was to understand the status of smartphone addiction and mental health of Undergraduates in Inner Mongolia Medical University during the period of the prevalence of COVID-19, and to explore the relationship between the mental health status and smartphone addiction of Undergraduates in Inner Mongolia Medical University. Methodology: Five colleges were randomly selected from Inner Mongolia Medical University, and 100 undergraduate students were randomly selected from each college. A total of 500 students were investigated by questionnaire, including demographic characteristics, smartphone use behaviors, smartphone addition scale: Short Version (SAS-SV) (10 questions), life experience during COVID-19, Depression Anxiety Stress Scales (DASS-21) 21 questions. Univariate logistic regression analysis used binary logistical regression to explore the nature and significance of the relationship between dependent and independent variables. After putting the significant factors into multivariable logistic regression models to control any possible confounding factors, the factors significantly related to smartphone addiction and depression, anxiety, stress were proposed. Results: In the questionnaire survey (33.6% of males and 66.4% of females), the age range was 18 to 28 years old. Almost 277(55.4%) participants can be considered as smartphone addiction,233(44.6%) participants cannot be considered smartphone addiction.105 (21.0%) considered having depression, 153 (30.6%) had anxiety and 69 (13.8%) had stress. Smartphone addiction (OR=4.53), compared with non-addiction, addiction has a positive correlation with the depression the depression risk of smartphone addicts is 4.53 times that of non-smartphone addicts. smartphone addiction (OR=6.47), compared with non-addiction, addiction has a positive correlation with the anxiety the anxiety risk of smartphone addicts is 6.47 times that of non-smartphone addicts. Smartphone addiction (OR=4.05), compared with non-addiction, addiction has a positive correlation with the stress the stress risk of smartphone addicts is 4.05 times that of non-smartphone addicts. Conclusion: Smartphone addiction is very common among the undergraduates of Inner Mongolia Medical University. This study also determined the association between smartphone addiction and mental health of the undergraduates of Inner Mongolia Medical University. These results indicate that intervention measures need to be taken to reduce the smartphone addiction of Undergraduates of Inner Mongolia Medical University to improve their mental health. © 2021 ACM.

18.
10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021 ; 1015:39-49, 2022.
Article in English | Scopus | ID: covidwho-1626567

ABSTRACT

In real world data classification tasks, we always face the situations where the data samples of the normal cases present a well defined pattern and the features of abnormal data samples vary from one to another, i.e., do not show a regular pattern. Up to now, the general data classification hypothesis requires the data features within each class to present a certain level of similarity. Therefore, such real situations violate the classic classification condition and make it a hard task. In this paper, we present a novel solution for this kind of problems through a network approach. Specifically, we construct a core-periphery network from the training data set in such way that core node set is formed by the normal data samples and peripheral node set contains the abnormal samples of the training data set. The classification is made by checking the coreness of the testing data samples. The proposed method is applied to classify radiographic image for COVID-19 diagnosis. Computer simulations show promising results of the method. The main contribution is to introduce a general scheme to characterize pattern formation of the data “without pattern”. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

19.
10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021 ; 1015:16-26, 2022.
Article in English | Scopus | ID: covidwho-1626517

ABSTRACT

An important task in combating COVID-19 involves the quick and correct diagnosis of patients, which is not only critical to the patient’s prognosis, but can also help to optimize the configuration of hospital resources. This work aims to classify chest radiographic images to help the diagnosis and prognosis of patients with COVID-19. In comparison to images of healthy lungs, chest images infected by COVID-19 present geometrical deformations, like the formation of filaments. Therefore, fractal dimension is applied here to characterize the levels of complexity of COVID-19 images. Moreover, real data often contains complex patterns beyond physical features. Complex networks are suitable tools for characterizing data patterns due to their ability to capture the spatial, topological and functional relationship between the data. Therefore, a complex network-based high-level data classification technique, capable of capturing data patterns, is modified and applied to chest radiographic image classification. Experimental results show that the proposed method can obtain high classification precision on X-ray images. Still in this work, a comparative study between the proposed method and the state-of-the-art classification techniques is also carried out. The results show that the performance of the proposed method is competitive. We hope that the present work generates relevant contributions to combat COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

20.
10th Brazilian Conference on Intelligent Systems, BRACIS 2021 ; 13074 LNAI:42-57, 2021.
Article in English | Scopus | ID: covidwho-1592475

ABSTRACT

One important task in the COVID-19 clinical protocol involves the constant monitoring of patients to detect possible signs of insufficiency, which may eventually rapidly progress to hepatic, renal or respiratory failures. Hence, a prompt and correct clinical decision not only is critical for patients prognosis, but also can help when making collective decisions regarding hospital resource management. In this work, we present a network-based high-level classification technique to help healthcare professionals on this activity, by detecting early signs of insufficiency based on Complete Blood Count (CBC) test results. We start by building a training dataset, comprising both CBC and specific tests from a total of 2,982 COVID-19 patients, provided by a Brazilian hospital, to identify which CBC results are more effective to be used as biomarkers for detecting early signs of insufficiency. Basically, the trained classifier measures the compliance of the test instance to the pattern formation of the network constructed from the training data. To facilitate the application of the technique on larger datasets, a network reduction option is also introduced and tested. Numerical results show encouraging performance of our approach when compared to traditional techniques, both on benchmark datasets and on the built COVID-19 dataset, thus indicating that the proposed technique has potential to help medical workers in the severity assessment of patients. Especially those who work in regions with scarce material resources. © 2021, Springer Nature Switzerland AG.

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