ABSTRACT
Simulating the behavior of a human heart, predicting tomorrow's weather, optimizing the aerodynamics of a sailboat, finding the ideal cooking time for a hamburger: to solve these problems, cardiologists, meteorologists, sportsmen, and engineers can count on math help. This book will lead you to the discovery of a magical world, made up of equations, in which a huge variety of important problems for our life can find useful answers. © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022. All rights reserved.
ABSTRACT
Background/Aims We report the features of chronic chilblain-like digital lesions newly presenting since the start of the covid-19 pandemic. Comparison with primary perniosis and acrocyanosis, reveals a unique phenotype which appears to be a long-covid phenomenon. Methods The case records of 26 patients with new onset persistent chilblain-like lesions presenting to the Rheumatology service of St George's University Hospital, London between Autumn 2020 and Spring 2022 were reviewed. Demographic and clinical features, serology, imaging, treatment response and outcome up to Summer 2022 were collated retrospectively. Results Chilblain-like lesions first occurred between September and March;2019/ 2020 6 cases, 2020/2021 18 cases and 2021/2022 2 cases. Mean age 35.4 (17-60) years, 88% female, 85% white, all non-smokers. Median body mass index (BMI) 20.2, range 17.0 - 33.2. BMI underweight (<18.5) in 27%. All cases reported new red-purple-blue colour changes of the fingers, some with pain, swelling and pruritis, affecting both hands in 12, one hand in 6, and both hands and feet in 8 cases. There was a past history of cold sensitivity or primary Raynaud's in 54%. Covid was confirmed in 3 cases, 2 - 8 months prior to onset of chilblain-like symptoms. Possible covid, unconfirmed, was suspected in 5 cases, 1 - 11 months earlier. Affected digits appeared diffusely erythro-cyanotic in 81%, with blotchy discrete maculo-papular erythematous lesions in 42%, some with both features. Involvement was asymmetric in 54%, thumbs spared in 69%. Complement was low in 50% (8/16), ANA positive in 26% (6/23). MRI of hands showed phalangeal bone marrow oedema in keeping with osteitis in 4 of 7 cases. More severe signs and symptoms were associated with low BMI, low C3/4 and a past history of cold sensitivity or Raynauds. Cold avoidance strategies were sufficient for 58%. Pain prompted a trial of NSAIDs, aspirin, nitrates, calcium channel blockers, hydroxychloroquine, oral or topical corticosteroid or topical tacrolimus in 42%. In general, these were minimally effective or not tolerated. 4 severe cases received sildenafil or tadalafil, effective in 2. In 27% complete remission occurred during the first summer season after symptoms commenced, median duration 6 (range 2 - 10) months. In the remaining 19 cases, chilblain-like symptoms returned or worsened in the subsequent second winter period, with 6 of 19 entering remission the following summer. For the remaining 13 persistent cases the total duration of symptoms spans more than a year, and in four cases more than 2 years. Conclusion This series illustrates a distinct chronic chilblain-like condition. Features similar to primary perniosis include female predominance, middle age, pruritic painful blotchy lesions, asymmetry and low BMI. Features in keeping with acrocyanosis include chronicity, extensive diffuse erythro-cyanotic discoloration, relative improvement in warm weather and lack of association with smoking.
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Traffic flowprediction has always been the focus of research in the field of Intelligent Transportation Systems, which is conducive to the more reasonable allocation of basic transportation resources and formulation of transportation policies. The spread of COVID-19 has seriously affected the normal order in the transportation sector. With the increase in the number of infected people and the government's anti-epidemic policy, human outgoing activities have gradually decreased, resulting in increasingly obvious discreteness and irregularities in traffic flow data. This article proposes a deep-space time traffic flow prediction model based on discrete wavelet transform (DSTM-DWT) to overcome the highly discrete and irregular nature of the new crown epidemic. First, DSTM-DWT decomposes traffic flow into discrete attributes, such as flow trend, discrete amplitude, and discrete baseline. Second, we design the spatial relationship of the transportation network as a graph and integrate the new crown pneumonia epidemic data into the characteristics of each transportation node. Then, we use the graph convolutional network to calculate the spatial correlation of each node, and the temporal convolutional network to calculate the temporal correlation of the data. In order to solve the problem of high discreteness of traffic flow data during the epidemic, this article proposes a graph memory network (GMN), which is used to convert discrete magnitudes separated by discrete wavelet transform into highdimensional discrete features. Finally, use DWT to segment the predicted traffic data, and then perform the inverse discrete wavelet transform between the newly segmented traffic trend and discrete baseline and the discrete model predicted by GMN to obtain the final traffic flow prediction result. In simulation experiments, this work was compared with the existing advanced baselines to verify the superiority of DSTM-DWT.
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The recent COVID-19 pandemic has led to a nearly world-wide shelter-in-place strategy. This raises several natural concerns about the safe relaxing of current restrictions. This article focuses on the design and operation of heating ventilation and air conditioning (HVAC) systems in the context of transportation. Do HVAC systems have a role in limiting viral spread? During shelter-in-place, can the HVAC system in a dwelling or a vehicle help limit spread of the virus? After the shelter-in-place strategy ends, can typical workplace and transportation HVAC systems limit spread of the virus? This article directly addresses these and other questions. In addition, it also summarizes simplifying assumptions needed to make meaningful predictions. This article derives new results using transform methods first given in Ginsberg and Bui. These new results describe viral spread through an HVAC system and estimate the aggregate dose of virus inhaled by an uninfected building or vehicle occupant when an infected occupant is present within the same building or vehicle. Central to these results is the derivation of a quantity called the "protection factor"-a term-of-art borrowed from the design of gas masks. Older results that rely on numerical approximations to these differential equations have long been lab validated. This article gives the exact solutions in fixed infrastructure for the first time. These solutions, therefore, retain the same lab validation of the older methods of approximation. Further, these exact solutions yield valuable insights into HVAC systems used in transportation.
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Background: COVID-19 has significantly impacted humans worldwide in recent times. Weather variables have a remarkable effect on COVID-19 spread all over the universe. Objectives: The aim of this study was to find the correlation between weather variables with COVID-19 cases and COVID-19 deaths. Methods: Five electronic databases such as PubMed, Science Direct, Scopus, Ovid (Medline), and Ovid (Embase) were searched to conduct the literature survey from January 01, 2020, to February 03, 2022. Both fixed-effects and random-effects models were used to calculate pooled correlation and 95% confidence interval (CI) for both effect measures. Included studies heterogeneity was measured by Cochrane chi-square test statistic Q, I 2 and τ 2 . Funnel plot was used to measure publication bias. A Sensitivity analysis was also carried out. Results: Total 38 studies were analyzed in this study. The result of this analysis showed a significantly negative impact on COVID-19 fixed effect incidence and weather variables such as temperature (r = -0.113∗∗∗), relative humidity (r = -0.019∗∗∗), precipitation (r = -0.143∗∗∗), air pressure (r = -0.073∗), and sunlight (r = -0.277∗∗∗) and also found positive impact on wind speed (r = 0.076∗∗∗) and dew point (r = 0.115∗∗∗). From this analysis, significant negative impact was also found for COVID-19 fixed effect death and weather variables such as temperature (r = -0.094∗∗∗), wind speed (r = -0.048∗∗), rainfall (r = -0.158∗∗∗), sunlight (r = -0.271∗∗∗) and positive impact for relative humidity (r = 0.059∗∗∗). Conclusion: This meta-analysis disclosed significant correlations between weather and COVID-19 cases and deaths. The findings of this analysis would help policymakers and the health professionals to reduce the cases and fatality rate depending on weather forecast techniques and fight this pandemic using restricted assets.