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With the continuous development of the sensory experience urban tourism, soundscape perception has become of importance. Taking the Qianmen Avenue, a typical historical block in the Central Axis of Beijing Old City as a case study, this paper presents an analysis of the objective soundscape features just after the first climax of the COVID-19 in January 2021. Based on the model of "acoustical parameters - classifications - extraction of the keynote and signal and soundmark - SPL mapping", the case study shows that although the soundscapes of Qianmen Avenue are complex and changeable with a LAeq from 55dB to 90dB, the noisy keynotes are combined with the sales' broadcasting, loudspeakers, tourists and traffic noise;natural sounds are rarely perceived;the warning bells of passing trams are extremely loud and harsh, causing great disturbance to tourists;no clearly identifiable soundmark has been found;and there is no obvious regularity in the spatial distribution in the SPL mapping. Apart from the architectural features and recently painted murals, the soundscape is far away from the "Culture-enriched Beijing” related content that the public perceives it carries. And due to the COVID-19, an epidemic broadcasting is added as a possible signal or soundmark. © ICA 2022.All rights reserved
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Children of incarcerated parents experience a range of vulnerabilities which have led to them being dubbed the ‘invisible victims' of the criminal justice system. This article discusses the needs of children with incarcerated parents using recent literature describing children's experiences during prison visitation suspensions caused by the COVID-19 pandemic. We then critically examine the human rights-based communications framework, as well as the challenges faced by children of incarcerated parents, in the Australian Capital Territory (ACT). We recommend corrective services around Australia retain alternative contact methods and consider introducing in-cell communication technology. © The Author(s) 2023.
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The nucleic acid detection is an effective way for the prevention and control of COVID-19. PCR amplification is an important process in the nucleic acid detection. At present, PCR amplification has the problem of low heating/cooling rates, and poor temperature uniformity. This paper proposes a microchannel temperature control device for the nucleic acid detection. Five groups of parallel serpentine channels are used to increase the cooling rate of the PCR amplification. A gradual thermal conductivity design is applied to the reaction module to increase the temperature uniformity. The experimental results show that the best temperature uniformity is obtained when the materials of the inner and outer layers of the reaction module are copper and aluminum alloys, respectively. The limit and average heating/cooling rate are 7.2, 6.12, 5.52 and 5.28 °C/s, respectively, when the input power of the thermoelectric cooler is 11.07 W/cm2, the temperature and flow rate of the cooling water are 15℃ and 700 ml/min, and the thermal conductivity of the thermal grease is 6 W/(m·K). Compared with the commercial fan-fin cooling method, the limit and average heating/cooling rates are increased by 38.02%, 80.82%, 86.49% and 208.77%, respectively, with the help of microchannel cooling method. © 2023 Elsevier Ltd
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The pandemic of coronavirus disease 2019 is "not over,"in fact, the "dynamic clearing"policy for SARS-CoV-2 control and prevention in China has been firmly enforced. This study aimed to analyze the clinical symptoms and dynamic viral RNA changes in 2021 at Guangzhou Eighth People's Hospital. This study showed that 31.4% of the patients (695/2212) tested negative for viral RNA from admission to the final release from quarantine. Of all negative cases, 86.5% (601/695) remained in the hospital for no more than 5 days and were asymptomatic or mild. Among the remaining 402 patients who stayed for no more than 5 days, 76.4% (307/402) were viral RNA retest positive during the isolation stage. However, 96.4% of the peak viral RNA (296/307) was over Ct = 33 cycles during the isolation stage. © Wolters Kluwer Health, Inc. All rights reserved.
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Background: The COVID-19 has a huge negative impact on people's health. Traditional Chinese Medicine (TCM) has a good effect on viral pneumonia. It is of great practical significance to study its pharmacology. Methods: The ingredients and targets of each herb in Maxing Shigan Decoction which obtained from Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and the related targets of COVID-19 were screened by GeneCards database based on the network pharmacology. Venn was used to analyze the intersection target between active ingredients and diseases. Cytoscape software was used to construct an active ingredient-disease target network. The protein-protein interaction network was constructed by STRING database and Cytohubba was used to screen out the key targets. Gene Ontology (GO) functional enrichment analysis and KEGG pathway analysis were performed by DAVID database. Results: In this study, a total of 134 active ingredients and 229 related targets, 198 targets of COVID-19 and 48 common targets of drug-disease were chosen. Enrichment items and pathways were obtained through GO and KEGG pathway analysis. The predicted active ingredients were quercetin, kaempferol, luteolin, naringenin, glycyrol, and the key targets involved IL6, MAPK3, MAPK8, CASP3, IL10, etc. The results showed that the active ingredients of Maxing Shigan Decoction acted on multiple targets which played roles in the treatment of COVID-19 by regulating inflammation, immune system and other pathways. Conclusions: The main contribution of this paper is to use data to mine the principles of the treatment of COVID-19 from the pharmacology of these prescriptions, and the results can be provided theoretical reference for medical workers. © The Author (s) 2023. Published by Higher Education Press.
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Semiconducting single-walled carbon nanotubes (SWCNTs) with tailored corona phases (CPs), or surface-adsorbed molecules, have emerged as a promising interface for sensing applications. The adsorption of an analyte can be specifically transduced as a modulation of their band-gap near-infrared (nIR) photoluminescence (PL). One such CP ideal for this purpose is single-stranded DNA (ssDNA), where subsequent sequence-dependent hybridization can result in PL emission wavelength shifts. Due to ssDNA adsorption to the SWCNT surface, the resultant noncanonical hybridization and its effect on SWCNT photophysical properties are not well understood. In this work, we study 20- and 21-mer DNA and RNA hybridization on the complementary ssDNA-SWCNT CP in the context of nucleic acid sensing for SARS-CoV-2 sequences as model analytes. We found that the van't Hoff transition enthalpy of hybridization on SWCNT CP was −11.9 kJ mol-1, much lower than that of hybridization in solution (−707 kJ mol-1). We used SWCNT solvatochromism to calculate the solvent-exposed surface area to indicate successful hybridization. We found that having a 30-mer anchor region in addition to the complementary region significantly improved PL response sensitivity and selectivity, with a (GT)15 anchor preferred for RNA targets. Coincubation of ssDNA-SWCNTs with an analyte at 37 °C resulted in faster hybridization kinetics without sacrificing specificity. Other methods aimed to improve CP rearrangement kinetics such as bath sonication and surfactant additions were ineffective. We also determined that the target sequence choice is important as secondary structure formation in the target is negatively correlated with hybridization. Best-performing CPs showed detection limits of 11 and 13 nM for DNA and RNA targets, respectively. Finally, we simulated sensing conditions using the saliva environment, showing sensor compatibility in biofluids. In total, this work elucidates key design features and processing to enable sequence-specific hybridization on ssDNA-SWCNT CPs. © 2022 American Chemical Society.
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Personal greenhouse gas (PGHG) emissions were crucial for achieving carbon peak and neutrality targets. The accounting methodology and driving forces identification of PGHG emissions were helpful for the quantification and the reduction of the PGHG emissions. In this study, the methodology of PGHG emissions was developed from resource obtaining to waste disposal, and the variations of Shanghainese PGHG emissions from 2010 to 2020 were evaluated, with the driving forces analysis based on Logarithmic Mean Divisia Index (LMDI) model. It showed that the emissions decreased from 3796.05 (2010) to 3046.87 kg carbon dioxides (CO2) (2014) and then increased to 3411.35 kg CO2 (2018). The emissions from consumptions accounted for around 62.1% of the total emissions, and that from waste disposal were around 3.1%, which were neglected in most previous studies. The PGHG emissions decreased by around 0.53 kg CO2 (2019) and 405.86 kg CO2 (2020) compared to 2018 and 2019, respectively, which were mainly affected by the waste forced source separation policy and the COVID-19 pandemic. The income level and consumption GHG intensity were two key factors influencing the contractively of GHG emissions from consumption, with the contributing rate of 169.3% and − 188.1%, respectively. Energy consumption was the main factor contributing to the growth of the direct GHG emissions (296.4%), and the energy GHG emission factor was the main factor in suppressing it (− 92.2%). Green consumption, low carbon lifestyles, green levy programs, and energy structure optimization were suggested to reduce the PGHG emissions. © 2023, The Author(s).
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In the era of global transmission of COVID-19, it is a challenge for physicians to efficiently and accurately use chest Xray images to diagnose whether a patient is positive or not. The application of deep learning and computer vision in medical image processing solves this problem, but a highly accurate method is still needed. In this research, we proposed an innovative CNN structure used for chest X-ray classification. Based on deep learning and CNN, this new architecture has an efficient training process and the performance of accuracy is better than other classic nets. The best accuracy on the test dataset is 97.68%. It has competitive advantages over AlexNet, LeNet-5, and Vgg-16. Dropout, Data augmentation, and Grad-CAM technique are added to improve performance. © 2022 IEEE.
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Introduction: Black and Latinx patients bear a disproportionate burden of asthma-related morbidity partly due to inadequate healthcare access. Telehealth could improve access, but its impact on asthma outcomes compared to in-person visits in these populations is unknown. Method(s): Black and Latinx adults with moderate-severe asthma were recruited from US clinics, including Puerto Rico for the PREPARE trial. For this ancillary study, 7/19 sites had available EMR data on asthma care appointment setting (telehealth vs. in-person). Participants whose asthma care included telehealth (TH) vs. those with exclusively in-person visits (IP) starting at COVID-19 pandemic onset (3/2020, greater telehealth prevalence) through 4/2021 (last PREPARE exit) were included if 2+ monthly PREPARE surveys were available for the post-index visit period. Asthma control (ACT) and asthma-related quality of life (ASUI) were compared between TH vs. IP. Result(s): Data were available for n=62 TH and n=36 IP participants, with comparable duration of follow-up (6.36 vs. 6.42 months, respectively). TH were more likely Latinx, from the Northeast, employed, only use inhaled corticosteroids as controller therapy, lower BMI, and lower self-reported asthma therapy adherence compared to IP. Before and after adjustment for these baseline differences and for PREPARE treatment assignment and baseline ACT and ASUI scores, TH and IP had comparable follow-up asthma control (ACT 18.43 vs. 18.93, respectively, p=0.519) and asthma-related quality of life (ASUI 0.79 vs. 0.84, respectively, p=0.163). Conclusion(s): Asthma control and asthma-related quality of life were comparable between TH and IP after adjustment. TH may represent a valuable asthma care option for Black and Latinx patients. Copyright © 2022
ABSTRACT
Semiconducting single-walled carbon nanotubes (SWCNTs) with tailored corona phases (CPs), or surface adsorbed molecules, have emerged as a promising interface for sensing applications. The adsorption of an analyte can be specifically transduced as a modulation of their band-gap near infrared (nIR) photoluminescence (PL). One such CP ideal for this purpose is single-stranded DNA (ssDNA), where subsequent sequence-dependent hybridization can result in PL emission wavelength shifts. Due to ssDNA adsorption to the SWCNT surface, the resultant noncanonical hybridization and its effect on SWCNT photophysical properties are not well understood. In this work, we study 20-and 21-mer DNA and RNA hybridization on the complementary ssDNA-SWCNT CP in the context of nucleic acid sensing for SARS-CoV-2 sequences as model analytes. We found that the van't Hoff transition enthalpy of hybridization on SWCNT CP was -11.9 kJ mol-1, much lower than that of hybridization in solution (-707 kJ mol-1). We used SWCNT solvatochromism to calculate the solvent-exposed surface area to indicate successful hybridization. We found that having a 30-mer anchor region in addition to the complementary region significantly improved PL response sensitivity and selectivity, with a (GT)15 anchor preferred for RNA targets. Coincubation of ssDNA-SWCNTs with an analyte at 37 degrees C resulted in faster hybridization kinetics without sacrificing specificity. Other methods aimed to improve CP rearrangement kinetics such as bath sonication and surfactant additions were ineffective. We also determined that the target sequence choice is important as secondary structure formation in the target is negatively correlated with hybridization. Best performing CPs showed detection limits of 11 and 13 nM for DNA and RNA targets, respectively. Finally, we simulated sensing conditions using the saliva environment, showing sensor compatibility in biofluids. In total, this work elucidates key design features and processing to enable sequence-specific hybridization on ssDNA-SWCNT CPs.
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During the coronavirus disease 2019 (COVID-19) epidemics, universities take responsibility for the health of their students and epidemic control. Our urgent recommendation focuses on four key questions of emergency management in universities following rigorous evidence-based approaches and provides timely suggestions to university managers, academic faculties and student affairs managers. We recommend universities during the COVID-19 epidemics should: 1) suspend offline lectures;2) provide proper health education on the disease;3) encourage face masks, however oppose using N95 masks on the campus;4) encourage hand hygiene and provide sanitizing products on the campus. Copyright © 2020 West China University of Medical Science. All rights reserved.
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Heparin is a kind of glycosaminoglycan drug with a complex structure, which is a mixture of polysaccharides with different chain lengths composed of hexuronic acid, aminohexose and its derivatives.Hexuronic acids are L-aduronic acid and D-glucuronic acid, aminohexose is α -D-glucosamine, and the modification of derivatives includes sulfation and acetylation.As a natural biomacromolecule, heparin has a variety of biological activities.It has been discovered for more than a hundred years and has good anticoagulant effect, which is clinically the first choice for anticoagulant and prevention and treatment of thromboembolic diseases.It has been discovered that there are more than one hundred functional proteins that interact with heparin.Heparin can bind to a variety of proteins and exert a variety of biological activities such as anticoagulant, anti-inflammatory, antiviral, and anti-tumor. The anticoagulant mechanism of heparin has been explained in detail, but its anti-inflammatory, antiviral, anti-tumor and other non-anticoagulant biolo-gical activities are still under extensive research, and these activities also have the potential to be developed into new drugs and new materials.Derivatives which with low anticoagulant activity and high antiangiogenic activity have been developed.In addition, sepsis-induced coagulopathy was common in patients with severe pneumonia caused by COVID-19 during the global outbreak of novel coronavirus epidemic.Heparin is effective in improving coagulation disorders and is likely to provide a better prognosis in patients with severe pneumonia.Due to its better biological activity, it also has potential applications in the field of new materials, such as being a cross-linking agent in the formation of hydrogels, and as a surface modifier of nanoparticles. This article consists of five parts, through which the author will first review the pharmacological activities of heparin in anticoagulation, anti-inflammatory and anti-tumor activities, then introduce the application of heparin in the new coronavirus, and finally give an overview of the application of heparin in new materials.
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COVID-19 is pandemic worldwide, and different countries have adopted different measures to stop the spread of the epidemic. In order to study the impact of quarantining close contacts on the spread of coronavirus disease 2019 (COVID-19), based on data published by Beijing Municipal Health Commission, World Health Organization (WHO) and Korea Central Disaster Control Headquarters (KCDC), SEIR dynamic models of virus transmission in Beijing and South Korea were set up respectively;the Genetic algorithm was used to fit the important parameters such as transmission rate, recovery rate and quarantine rate;calculated the control reproduction number;we discuss the impact of quarantining close contacts on daily new cases in South Korea, the daily new cases decrease after a week, and drop to 16.93 after 30 days. When close contacts were quarantined, the maximum value of daily new cases Imax = 57.4 obtained by simulation is only 13% of the actual maximum value actual Imax = 441;the influences of different quarantine rates and the number of the susceptible on the number of daily new cases are also discussed, the quarantine of close contacts has significant effect on reducing the number of daily new cases compared with less stringent control measures. Vigorous control measures reduce the number of daily new cases to single digits in just 17 days in Beijing, effectively curbing the transmission of COVID-19. It has vital significance for the prevention and control of the epidemic in other countries and regions. © 2022, Wilmington Scientific Publisher. All rights reserved.
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The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the biggest challenge in public health worldwide. Similarities among viral receptors predict that there are several animal species that could function as reservoirs for the virus. Recent studies have reported that felid animals, including wild and domestic cats, are highly susceptible to SARS-CoV-2 infection. These findings cause great concerns on the potential for human-to-animal and animal-to-human transmission, along with the virus mutations that appear as the virus goes back and forth between species. It is urgently needed to develop novel reagents for control of viral infection and preventing interspecies transmission. In this chapter, we described protocols for generation of a mouse-feline chimeric neutralizing antibody against SARS-CoV-2. This chimeric antibody has potential to be developed as a diagnostic tool and therapeutic agent against SARS-CoV-2 infections in cats.
ABSTRACT
The novel coronavirus epidemic, appearing at the end of December 2019, spread rapidly due to the large-scale population movement in the Spring Festival travel rush in 2020. Since January 23, 2020, China has taken various measures to effectively control the epidemic. For example, the closure of Wuhan, the tracking and isolation of close contacts of confirmed cases, and the home isolation of Hubei people, etc. Based on the actual transmission of novel coronavirus (COVID-19) in Shanxi province, a dynamic model was established for tracking and isolation of close contacts with imported and confirmed cases. Without regard to the imported cases, the dynamic behavior of the model was analyzed. By means of the case data of novel coronavirus in Shanxi province, the real-time reproduction number was calculated. It is found that the closure of villages and streets in Shanxi province on January 25, 2020 effectively controls the spread of COVID-19 epidemic, that is, the real-time reproduction number is less than 1, which verifies the effectiveness of prevention and control measures from a macro perspective. Further, through the numerical simulation of the model, it is concluded that the prevention and control strategy for early infected patients isolated for 14 days is reasonable and effective;the earlier the closure of Wuhan is, the smaller the scale of infected people will be;the larger number of tracked and isolated contacts of confirmed cases is, the smaller the size of the patients will be. © Editorial Office of Applied Mathematics and Mechanics.
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The ongoing coronavirus disease 2019 (COVID-19) is a pandemic causing millions of deaths, devastating social and economic disruptions. Testing individuals for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of COVID-19, is critical for mitigating and containing COVID-19. Many countries are implementing group testing strategies against COVID-19 to improve testing capacity and efficiency while saving required workloads and consumables. A group of individuals' nasopharyngeal/oropharyngeal (NP/OP) swab samples is mixed to conduct one test. However, existing group testing methods neglect the fact that mixing samples usually leads to substantial dilution of viral ribonucleic acid (RNA) of SARS-CoV-2, which seriously impacts the sensitivity of tests. In this paper, we aim to screen individuals infected with COVID-19 with as few tests as possible, under the premise that the sensitivity of tests is high enough. To achieve this goal, we propose an Adaptive Group Testing (AdaGT) method. By collecting information on the number of positive and negative samples that have been identified during the screening process, the AdaGT method can estimate the ratio of positive samples in real-time. Based on this ratio, the AdaGT algorithm adjusts its testing strategy adaptively between an individual testing strategy and a group testing strategy. The group size of the group testing strategy is carefully selected to guarantee that the sensitivity of each test is higher than a predetermined threshold and that this group contains at most one positive sample on average. Theoretical performance analysis on the AdaGT algorithm is provided and then validated in experiments. Experimental results also show that the AdaGT algorithm outperforms existing methods in terms of efficiency and sensitivity.
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The pandemic of emerging coronavirus disease 2019 (COVID-19) has been a serious threat to public health. Specifically, the asymptomatic patients are not easily identified but contribute significantly to coronavirus transmission. We used a previously developed SCIRA model with asymptomatic populations, fitted the model to the epidemic data and performed stochastic simulations. The results showed that complete recovery of asymptomatic patients usually showed remarkable delays compared to that of diagnosed cases. The mutual contacts among populations can be significantly lowered under strictly controlled measures to impede COVID-19 transmission. If strict interventions are only maintained for short durations after curation of all diagnosed patients, there might be potentially a second outbreak owing to asymptomatic patients. Therefore, strict interventions should be continuously implemented to impede potential COVID-19 transmission even after diagnosed patients are all cured. © 2021, Editorial Department of Journal, Sun Yat-sen(Zhongshan) University. All right reserved.
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Coronavirus disease 2019 (COVID-19), the pandemic that is spreading fast globally, has caused over 181 million confirmed cases. Apart from the reverse transcription polymerase chain reaction (RT-PCR), the chest computed tomography (CT) is viewed as a standard and effective tool for disease diagnosis and progression monitoring. We propose a diagnosis and prognosis model based on graph convolutional networks (GCNs). The chest CT scan of a patient, typically involving hundreds of sectional images in a sequential order, is formulated as a densely connected weighted graph. A novel distance aware pooling is proposed to abstract the node information hierarchically, which is robust and efficient for such densely connected graphs. Our method, combining GCNs and distance aware pooling, can integrate the information from all slices in the chest CT scans for optimal decision making, which leads to the state-of-the-art accuracy in the COVID-19 diagnosis and prognosis. With less than 1% of the total number of parameters in the baseline 3D ResNet model, our method achieves 94.8% accuracy for diagnosis, which represents a 2.4% improvement over the baseline on the same dataset. In addition, we can localize the most informative slices with disease lesions for COVID-19 within a large sequence of chest CT images. The proposed model can produce visual explanations for the diagnosis and prognosis, making the decision more transparent and explainable, while RT-PCR only leads to the test result with no prognosis information. The prognosis analysis can help hospitals or clinical centers designate medical resources more efficiently and better support clinicians to determine the proper clinical treatment. © 2021, Springer Nature Switzerland AG.
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The novel coronavirus COVID-19 can be transmitted, for example, by contacting with oral and nasal's secretions, and traditional mask detection algorithms often fail to distinguish whether masks are worn regularly. In this article, we improve the algorithm network structure based on the improved YOLOV3-tiny algorithm and use the combination of nose detection and mask detection for feature fusion based on the training of massive data sets, which perfectly solves the problem of detecting whether the mask is worn in a normative way. The experiment shows that this system can detect the target of wearing face masks in different scenes with an accuracy rate of over 99%, laying a solid foundation for the detection of wearing face masks normatively. © 2021 IEEE.