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1.
41st Chinese Control Conference, CCC 2022 ; 2022-July:7540-7545, 2022.
Article in English | Scopus | ID: covidwho-2100719

ABSTRACT

The outbreak of COVID-19 in 2019, as well as the development of hot big data, cloud computing, artificial intelligence, and other technologies to promote the enterprise into the digital era, accelerated the progress of society, will continue to promote the development of society, vigorously developing digital economy is an important direction of enterprise economic growth. To push the basis of the rapid economic development is to realize the digital transformation, to realize the core of the digital transformation is the realization of digital transformation of enterprises, as the core power of enterprise development, human resource management, digital transformation, not only the need for human resources also need to speed up the pace of digital transformation of human resources, to support the realization of the digital transformation of enterprises. In order to realize the digital transformation of enterprise human resource management and the contactless human resource management of enterprises, this study constructed a DEA-Malmquist personnel efficiency evaluation model and classified enterprise employees in sequence. According to the enterprise contribution degree of different sequences of personnel and the possibility of online service, the paper puts forward the change of employee demand after digital transformation. In this study, the constructed model is applied to the practice of G company's human resource management digital transformation. According to the model, different employee needs of the company after digital transformation are predicted. Through the analysis of relevant data of G Company, the validity of the model is verified. © 2022 Technical Committee on Control Theory, Chinese Association of Automation.

2.
Chinese Journal of Parasitology and Parasitic Diseases ; 40(4):507-510, 2022.
Article in Chinese | Scopus | ID: covidwho-2080954

ABSTRACT

The COVID-19 pandemic has promoted the development of online teaching in various educational institutions. Different online teaching practice has shown advantages and potential problems. The combination of online and offline teaching (mixed teaching) is a new teaching practice that can exert its advantages simultaneously, and has been wildly used during the COVID-19 pandemic, even being extended to the post-pandemic era. Medical parasitology is a foundation course for medicine and a bridging course towards clinical medicine and preventive medicine. The traditional teaching of medical parasitology has presented many limitations, including outdated teaching concepts and practices, and the disconnection between theory teaching and practice teaching. In response to these difficulties, many innovative ideas and measures have been taken o reform the teaching practice of the foundation medical courses, including updating teaching program, adopting innovative teaching practice (such as blended teaching), and promoting the teaching evaluation method. In this paper, we concluded the blended teaching tools, platforms, manners, effects and evaluation methods in medical parasitology in China during the COVID-19 pandemic to provide information for the teaching reform in the post-pandemic era. © 2022, National Institute of Parasitic Diseases. All rights reserved.

3.
6th International Conference on Robotics and Automation Sciences, ICRAS 2022 ; : 47-51, 2022.
Article in English | Scopus | ID: covidwho-2018869

ABSTRACT

In the context of the new coronavirus epidemic, medical systems throughout the world has suffered tremendous pressure, the most intuitive problem is a shortage of human resources. In this regard, the 'intelligent drug delivery vehicle' puts forward a feasible scheme, which can replace manual work in a specific hospital area to complete the delivery of drugs. The system is based on STM32F103ZET6 core processor, controlling the OpenMV visual module to identify the hospital corridor information, and then through the pressure detection module, gray detection tracking module and angle sensing module information, the core processor controls the motor drive module to make the vehicle move. The system modifies the algorithm under the traditional NCC template matching algorithm, and uses the zoom image to reduce the pixels which improve the camera frame rate and recognition accuracy. At the same time, the Bluetooth communication module is installed to enable different vehicles to execute the drug delivery operations at the same time, therefore reducing manual work saving. © 2022 IEEE.

5.
Mathematical Biosciences and Engineering ; 19(12):11854-11867, 2022.
Article in English | Web of Science | ID: covidwho-2006289

ABSTRACT

Infectious diseases generally spread along with the asymmetry of social network propagation because the asymmetry of urban development and the prevention strategies often affect the direction of the movement. But the spreading mechanism of the epidemic remains to explore in the directed network. In this paper, the main effect of the directed network and delay on the dynamic behaviors of the epidemic is investigated. The algebraic expressions of Turing instability are given to show the role of the directed network in the spread of the epidemic, which overcomes the drawback that undirected networks cannot lead to the outbreaks of infectious diseases. Then, Hopf bifurcation is analyzed to illustrate the dynamic mechanism of the periodic outbreak, which is consistent with the transmission of COVID-19. Also, the discrepancy ratio between the imported and the exported is proposed to explain the importance of quarantine policies and the spread mechanism. Finally, the theoretical results are verified by numerical simulation.

6.
Smart Biomedical and Physiological Sensor Technology Xix ; 12123, 2022.
Article in English | Web of Science | ID: covidwho-2005290

ABSTRACT

Rapid, simple, inexpensive, and sensitive self-testing for SARS-CoV-2 is expected to be an important element of controlling the ongoing COVID pandemic. We report a novel approach in which saliva is mixed at room temperature with a Designer DNA Nanostructure (DDN) engineered to create a net-like structure that positions an array of highly specific nucleic acid aptamer-quencher locks at the locations of the trimeric spike proteins. When the spike proteins selectively unlock aptamers on the DDN, fluorescent reporter molecules are unquenched, generating an intense and easily measured optical signal. The fluorescence intensity, proportional to the virus concentration, is detected by a battery-powered palmsized fluorimeter, whose functions are managed wirelessly with a Bluetooth-linked smartphone. Because the single-step, room temperature, test is performed in a conventional 0.2 mL PCR tube that is inserted into the fluorimeter, which resembles an Apple AirPodsT headphone case, we call the technology (DDN+fluorimeter+App) a "V-Pod." We show that DDNs are highly specific only for detection of SARS-CoV-2 in both its initial form as well as common variants. The approach achieves a detection limit of 10,000 genome copies/mL, consistent with laboratory-based PCR, while requiring only one reagent and a 5-10 minute incubation time with saliva. Because DDNs are inexpensively synthesized, structurally stable nucleic acid constructs, and the V-Pod instrument is comprised of inexpensive electronic and photonic components, the approach offers potential for rapid self-monitoring of viral infection with integrated capability for contact tracing and interaction with health services.

7.
Acs Applied Polymer Materials ; 2022.
Article in English | Web of Science | ID: covidwho-2004744

ABSTRACT

The COVID-19 outbreak has seen the widespread use of personal protective equipment, especially antibacterial fibers. In this work, ionic liquid (IL) is used as a solvent to fabricate antibacterial fibers combining plant essential oils (PEOs) with cellulose. PEOs are buried in microcapsules first or mixed directly with IL-cellulose spinning dopes to prepare a series of composite fibers. The internal structures, surface and cross morphologies, thermal stability, mechanical properties, antibacterial activity, washing stability, and biocompatibility of these fibers are investigated and analyzed in-depth further. Artemisia microcapsule fiber (AMCRCF) with a break strength of 30.07 MPa is obtained. Besides, the antibacterial activity rates of AMC-RCF against Escherichia coli and Staphylococcus aureus are 89.8 and 97.8%, and the fibers still have a long-lasting antibacterial effect after 30 standard washes. Furthermore, the antibacterial fibers exhibit excellent biocompatibility. This research provides a green approach for the fabrication of the antibacterial fibers with long-lasting antibacterial activity and good biocompatibility.

8.
Journal of General Internal Medicine ; 37:S169, 2022.
Article in English | EMBASE | ID: covidwho-1995589

ABSTRACT

BACKGROUND: Timely follow-up of abnormal cancer screening test results (“abnormal screens”) is critical but often not achieved. As part of an NCI funded intervention trial (mFOCUS: multilevel Follow-up of Cancer Screening, ClinicalTrials.gov NCT03979495), we report on abnormal screens that were identified and tracked to identify eligible patients overdue for study inclusion. While not anticipated when this study was conceived, the COVID-19 pandemic resulted in a larger than anticipated backlog of patients in need of follow-up of abnormal screens. METHODS: Patients in two primary care practice networks affiliated with Mass General Brigham who had an abnormal screen for breast, cervical or lung cancer were identified using computerized algorithms and then tracked for completion of appropriate follow-up based upon the cancer type and the severity of the abnormal result. Since the intervention was designed as a “fail safe” system, additional time (2-6 months depending on the severity of the abnormal screen) was added after the recommended follow-up interval. We report the number of abnormal screens by cancer type and severity of the abnormality and the number of patients who completed follow-up based upon guideline and expert recommendations. RESULTS: Patient tracking and enrollment started with abnormal screens for breast and lung on 8/24/2020 and cervical cancer on 10/16/2020. Enrollment ended for all abnormal screens on December 15, 2021. Over the study period, 4003 abnormal breast, 5214 abnormal cervical, and 478 abnormal lung screens were identified. High risk abnormalities were most common for cervical (51.7%, recommended colposcopy or endometrial biopsy), lung (22.6%, LRADS 4B, 4X or 5), and lowest for breast (0.4%, BIRADS 5). Rates of completing recommended follow-up of abnormal screens by cancer type and severity of the result are shown in the table. CONCLUSIONS: Maximizing the benefits of cancer screening requires the timely follow-up of abnormal screening results. Though likely exacerbated by the COVID-19 pandemic, we identified that timely completion of abnormal screens is often not achieved. Rates of completion varied by cancer type and the severity of the abnormal result but highlight the need for systems based, multi-level interventions to identify, report and track abnormal results.

9.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925091

ABSTRACT

Objective: The development and persistence of neurological symptoms following SARS-CoV-2 infection is referred to as “long-haul” syndrome. Here, we aim to study the role of small fiber neuropathy (SFN) underlying neuropathic symptoms associated with COVID-19 infection. Background: Post COVID-19 “long-haul” syndrome include chronic fatigue, brain fog, sleep disturbance and paraesthesias. These symptoms can overlap with those seen in SFN, which have not been investigated given the recent wave of pandemic and patients who developed new onset of symptoms following infection. Design/Methods: Using retrospective study between May 2020 - May 2021, we screened the skin biopsy database of patients who were referred from the Center of Post-COVID Care at the Mount Sinai Hospital. Thirteen patients were identified and undergone routine nerve conduction studies and electromyography which ruled out evidence of a large fiber neuropathy. Patients were then clinically evaluated and consented for skin punch biopsy. All specimens were processed using PGP9.5 immunostaining for evaluating intraepidermal nerve fiber density (IENFD) to confirm SFN. Results: We identified 13 patients, 8 women and 5 men (age 38-67 years) with follow-up duration between 8-12 months. All had negative neuropathy blood profile including HbA1c, ANA, B12, TSH, free T4, and serum immunofixation. Three patients had pre-existing but controlled neuropathy risk factors. None had neurological symptoms prior to the SARS-CoV-2 infection. All patients developed new-onset paresthesias within 2 months following infection, with an acute onset in 7 and co-existing autonomic symptoms in 7. Six patients had biopsyconfirmed SFN, all of whom showed both neuropathy symptoms and signs, with 2 showing autonomic dysfunction. Of the remaining 7 patients with negative skin biopsies, 6 showed no clinical neuropathy signs, and 1 exhibited signs with abnormal autonomic function testing. Conclusions: Our findings support that symptoms of SFN may develop during or shortly after COVID-19 illness. SFN may underlie the paresthesias associated with long-haul post-COVID-19 symptoms.

10.
DISCRETE DYNAMICS IN NATURE AND SOCIETY ; 2022, 2022.
Article in English | Web of Science | ID: covidwho-1909895

ABSTRACT

With the rapid development of modern society, there are many problems concerning the physical and mental health of students. This paper develops a feature analysis method of the mental health data of students in different colleges and regions and of different ages based on a convolutional neural network and TOPSIS evaluation model and studies the college students' mental health analysis model based on convolutional neural network. First, through the data cluster summary and internal characteristics analysis of college students' psychological questionnaire survey data in different regions and grades, we established a college students' mental health grade system and evaluation index system. Then, the TOPSIS analysis method is used to analyze the characteristics of the data results, and the feasibility of the accuracy of the evaluation index standard is analyzed. Finally, the experimental results show that the college students' mental health analysis model based on convolutional neural network can effectively classify and summarize various mental health data, quickly locate the mental health problems of different students and analyze the optimal solutions, and can effectively promote the process of analysis and research on the mental health problems in modern college students.

11.
2021 International Conference on Statistics, Applied Mathematics, and Computing Science, CSAMCS 2021 ; 12163, 2022.
Article in English | Scopus | ID: covidwho-1901894

ABSTRACT

Based on Baidu index data and the development timeline of COVID-19 in China, this study analyzes the spatial and temporal distribution pattern of network attention in Xi'an under epidemic prevention and control. The results show that: 1) In 2020, the network attention of Xi ' an affected by the epidemic is low. The trend of monthly network attention in the year is consistent with the time axis of domestic epidemic development, showing a ' double peak and double valley ' mode, and it is high in summer and autumn, and low in winter and spring. On the holidays, the attention increased before the festival, and the ' May 1 ' reached the peak one day before the festival, and the ' Eleventh ' reached the peak on the third day of the festival, showing a clear ' blowout ' trend. 2) The spatial distribution of Xi'an network attention is scattered, and shows the characteristics of high network attention in Henan, Sichuan and other surrounding provinces and Guangdong, Jiangsu, Zhejiang and other coastal economic developed areas. © COPYRIGHT SPIE.

12.
Environmental Science: Atmospheres ; 1(5):208-213, 2021.
Article in English | Scopus | ID: covidwho-1900673

ABSTRACT

The immense reduction in aerosol levels during the COVID-19 pandemic provides an opportunity to reveal how atmospheric chemistry is regulating our climate, among which the effect of aerosols on climate is a phenomenon of great interest but still in hot debate. The Intergovernmental Panel on Climate Change (IPCC) has continually identified the effect of aerosols on climate to have the largest uncertainty among the factors contributing to global climate change. Several studies indicate an inverse relationship between aerosol presence in the atmosphere and the diurnal surface air temperature range (DTR). Herein, we test this relationship by analyzing the DTR values from in situ weather station records for periods before and during the COVID-19 epidemic in Chinawhere aerosol levels have substantially reduced, compared with the climatological mean levels for a 19 year period.Our analyses find that DTRs fromFebruary to June during the COVID-19 pandemic are greater than 3 standard deviations above the climatological mean DTR. This anomaly has never occurred before in the 21st century and is at least in part associated with the observed reduction in aerosols. © 2021 The Author(s).

13.
Nature Machine Intelligence ; 4(5):494-+, 2022.
Article in English | English Web of Science | ID: covidwho-1882770

ABSTRACT

Tremendous efforts have been made to improve diagnosis and treatment of COVID-19, but knowledge on long-term complications is limited. In particular, a large portion of survivors has respiratory complications, but currently, experienced radiologists and state-of-the-art artificial intelligence systems are not able to detect many abnormalities from follow-up computerized tomography (CT) scans of COVID-19 survivors. Here we propose Deep-LungParenchyma-Enhancing (DLPE), a computer-aided detection (CAD) method for detecting and quantifying pulmonary parenchyma lesions on chest CT. Through proposing a number of deep-learning-based segmentation models and assembling them in an interpretable manner, DLPE removes irrelevant tissues from the perspective of pulmonary parenchyma, and calculates the scan-level optimal window, which considerably enhances parenchyma lesions relative to the lung window. Aided by DLPE, radiologists discovered novel and interpretable lesions from COVID-19 inpatients and survivors, which were previously invisible under the lung window. Based on DLPE, we removed the scan-level bias of CT scans, and then extracted precise radiomics from such novel lesions. We further demonstrated that these radiomics have strong predictive power for key COVID-19 clinical metrics on an inpatient cohort of 1,193 CT scans and for sequelae on a survivor cohort of 219 CT scans. Our work sheds light on the development of interpretable medical artificial intelligence and showcases how artificial intelligence can discover medical findings that are beyond sight. Respiratory complications after a COVID infection are a growing concern, but follow-up chest CT scans of COVID-19 survivors hardly present any recognizable lesions. A deep learning-based method was developed that calculates a scan-specific optimal window and removes irrelevant tissues such as airways and blood vessels from images with segmentation models, so that subvisual abnormalities in lung scans become visible.

14.
American Journal of Respiratory and Critical Care Medicine ; 205:2, 2022.
Article in English | English Web of Science | ID: covidwho-1880224
15.
Journal of Economic Dynamics and Control ; 139, 2022.
Article in English | Scopus | ID: covidwho-1838042

ABSTRACT

This study evaluates the dynamic impact of various policies adopted by U.S. states, including social distancing, financial assistance, and vaccination policies. We propose a time-varying parameter multilevel dynamic factor model (TVP-MDFM) to improve the model's accuracy for evaluating the dynamic policy effect. The estimation is based on the Bayesian shrinkage method jointly with the Markov chain Monte Carlo (MCMC) algorithm that combines model selection and parameter estimation into the same iterative sampling process. The advantages and reliability of the TVP-MDFM are explored using simulation studies and robustness tests. The main empirical results highlight that the direct causal effect of the social distancing policy is more significant than the indirect effect mediated through human behavior. We also find income heterogeneity in financial assistance policies. Moreover, we provide evidence that banning vaccination certification by legislation is a stronger driver of the new case rate than executive orders during the Omicron dominance. © 2022 Elsevier B.V.

16.
Chinese Journal of Evidence-Based Medicine ; 22(4):438-443, 2022.
Article in Chinese | EMBASE | ID: covidwho-1818644

ABSTRACT

Objective To systematically review the impact of ACEI/ARB (angiotensin converting enzyme inhibitor/angiotensin receptor antagonist) treatment on the clinical outcomes of Chinese patients with COVID-19 infections. Methods PubMed, EMbase, Web of Science, The Cochrane Library, CNKI, WanFang Data, and VIP databases were electronically searched to collect cohort studies on the impact of the treatment with ACEI/ARB on the clinical outcomes of Chinese patients with COVID-19 infections from January 2020 to January 2022. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of the included studies. Then, meta-analysis was performed using RevMan 5.3 software. Results A total of 17 cohort studies involving 4 912 subjects were included. The results of meta-analysis showed that patients who were prescribed ACEI/ARB had shorter hospital stays (SMD=-0.28, 95%CI -0.46 to -0.11, P=0.002) and a lower mortality rate (OR=0.47, 95%CI 0.36 to 0.62, P<0.000 01) than patients who did not take ACEI/ARB. Conclusion Current evidence shows that the use of ACEI/ARB drugs can improve the clinical prognosis of Chinese patients with COVID-19 infections. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.

17.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333517

ABSTRACT

PURPOSE: Conjunctival signs and symptoms are observed in a subset of patients with COVID-19, and SARS-CoV-2 has been detected in tears, raising concerns regarding the eye both as a portal of entry and carrier of the virus. The purpose of this study was to determine whether ocular surface cells possess the key factors required for cellular susceptibility to SARS-CoV-2 entry/infection. METHODS: We analyzed human post-mortem eyes as well as surgical specimens for the expression of ACE2 (the receptor for SARS-CoV-2) and TMPRSS2, a cell surface-associated protease that facilitates viral entry following binding of the viral spike protein to ACE2. RESULTS: Across all eye specimens, immunohistochemical analysis revealed expression of ACE2 in the conjunctiva, limbus, and cornea, with especially prominent staining in the superficial conjunctival and corneal epithelial surface. Surgical conjunctival specimens also showed expression of ACE2 in the conjunctival epithelium, especially prominent in the superficial epithelium, as well as the substantia propria. All eye and conjunctival specimens also expressed TMPRSS2. Finally, western blot analysis of protein lysates from human corneal epithelium obtained during refractive surgery confirmed expression of ACE2 and TMPRSS2. CONCLUSIONS: Together, these results indicate that ocular surface cells including conjunctiva are susceptible to infection by SARS-CoV-2, and could therefore serve as a portal of entry as well as a reservoir for person-to-person transmission of this virus. This highlights the importance of safety practices including face masks and ocular contact precautions in preventing the spread of COVID-19 disease.

18.
Advances in Pattern-Based Ontology Engineering ; 51:1-395, 2021.
Article in English | Scopus | ID: covidwho-1753334

ABSTRACT

Ontologies are the corner stone of data modeling and knowledge representation, and engineering an ontology is a complex task in which domain knowledge, ontological accuracy and computational properties need to be carefully balanced. As with any engineering task, the identification and documentation of common patterns is important, and Ontology Design Patterns (ODPs) provide ontology designers with a strong connection to requirements and a better communication of their semantic content and intent. This book, Advances in Pattern-Based Ontology Engineering, contains 23 extended versions of selected papers presented at the annual Workshop on Ontology Design and Patterns (WOP) between 2017 and 2020. This yearly event, which attracts a large number of researchers and professionals in the field of ontology engineering and ontology design patterns, covers issues related to quality aspects of ontology engineering and ODPs for data and knowledge representation, and is usually co-located with the International Semantic Web Conference (ISWC), apart from WOP 2020, which was held virtually due to the COVID-19 pandemic. Topics covered by the papers collected here focus on recent advances in ontology design and patterns, and range from a method to instantiate content patterns, through a proposal on how to document a content pattern, to a number of patterns emerging in ontology modeling in various situations and applications. The book provides an overview of important advances in ontology engineering and ontology design patterns, and will be of interest to all those working in the field. © 2021 Akademische Verlagsgesellschaft AKA GmbH, Berlin. All rights reserved.

19.
9th International Conference On Secure Knowledge Management In Artificial Intelligence Era, SKM 2021 ; 1549 CCIS:186-199, 2022.
Article in English | Scopus | ID: covidwho-1750601

ABSTRACT

Social media fuels fake news’ spread across the world. English news has dominated existing fake news research, and how fake news in different languages compares remains severely under studied. To address this scarcity of literature, this research examines the content and linguistic behaviors of fake news in relation to COVID-19. The comparisons reveal both differences and similarities between English and Spanish fake news. The findings have implications for global collaboration in combating fake news. © 2022, Springer Nature Switzerland AG.

20.
Analytical and Quantitative Cytopathology and Histopathology ; 43(5):383-392, 2021.
Article in English | Web of Science | ID: covidwho-1749483

ABSTRACT

OBJECTIVE: To investigate the effect of study and life patterns on the visual acuity of primary and secondary school students in Wuhan, China, during the COVID-19 pandemic. STUDY DESIGN: We investigated factors influencing the development of myopia using questionnaires presented to students in primary and secondary schools in Wuhan. After school resumed in September 2020, we obtained 15,596 valid questionnaires. Students who submitted valid questionnaires were examined for visual acuity and computerized optometry, from which 15,428 valid examination results were obtained. Then we cornpared these results with the screening data collected during the same period the previous year (September 2019). RESULTS: The overall prevalence of myopia among primary and secondary school students in Wuhan in 2020 was 59.95%, representing a 6.02% increase as compared with levels in 2019. For primary, junior, and senior high school students, this increase was 9.76%, 5.30%, and 2.79%, respectively. Primary school students primarily exhibited an increase in mild myopia (7.49%), while junior and senior high school students presented with increased rates of moderate (4.51%;5.74%) and high (1.17%;2.95%) myopia. Compared with 2019, senior high school students exhibited the most pronounced deepening of spherical equivalent, which deepened by -0.639 D, -0.774 D, and -0.775 D from Grade 1-3. In 2020 the students in Wuhan spent <1 hour on outdoor activities, but primary, junior, and senior high school students were engaged with online courses for 3.184 hours, 5.828 hours, and 6.239 hours and electronic products outside of online learning for 1.502 hours, 1.788 hours, and 2.146 hours, respectively. Multivariate logistic regression analysis showed that being female, high grade, long time of near-work, long time of using electronic product, the students' age of using electronic products for the first time was <= 3 years old, parents' myopia, and high education level were risk factors for myopia, while outdoor activity was a protective factor for myopia. CONCLUSION: During COVID-19, home-based online learning mode significantly increased the prevalence of myopia among students in Wuhan. The occurrence of myopia is related to heredity and eye use behavior. Increasing outdoor activities and reducing near-work time are important measures to prevent and control myopia occurrence.

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