The study examines the impact of climate indicators on COVID-19 epidemic in New York City. • Average temperature, minimum temperature and air quality have significant correlation with COVID-19 epidemic. • Currently there is no scientific evidence that warm weather would suppress COVID-19 epidemic.

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To overcome the defect of conventional nonlinear piezoelectric cantilever vibration energy harvesters, in this paper we conceive an elastic-support model to study the performance of energy converters under two types of variable-intensity excitation conditions: filtered Gaussian noises and pink noises. When excitation intensity is insufficient, thanks to the system's variable potential function, frequent bistable transition oscillations between two wells occur in elastic-support systems, while only weak oscillations in either well could be observed in rigid-support systems. In practical applications, the structural parameters of energy harvesters are not allowed to make real-time changes. If considered remaining the magnet interval and the spring's elastic stiffness unchanged while receiving stable maximum output voltage, elastic-support systems can be made full use toward variable-intensity filtered Gaussian noises. It has been proven that elastic-support systems are capable of adapting to random excitations with variable intensity, through which maximum power output and sufficient electromechanical energy conversion of the system can be accomplished.

The impact of environmental pollutants and climate indicators on the outbreak of COVID-19 has gained considerable attention in the recent literature. However, specific investigation of industrial economies like Germany is not available. This provides us motivation to examine the association between environmental pollutants, climate indicators and the COVID-19 cases, recoveries, and deaths in Germany using daily data from February 24, 2020, to July 02, 2020. The correlation analysis and wavelet transform coherence (WTC) approach are the analytical tools, which are used to explore the association between variables included in the study. Our findings indicate that PM2.5, O 3 , and NO 2 have a significant relationship with the outbreak of COVID-19. In addition, temperature is the only significant climate indicator which has significant correlation with the spread of COVID-19. Finally, PM10, humidity, and environmental quality index have a significant relationship only with the active cases from COVID-19 pandemic. Our findings conclude that Germany's successful response to COVID-19 is attributed to environmental legislation and the medical care system, which oversaw significant overhaul after the SARS and MERS outbreaks. The current study implicates that other industrial economies, especially European economies, that are still facing COVID-19 outbreak can follow the German model for pandemic response.

Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre-including this research content-immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

In the current context of the COVID-19 pandemic, researchers are working with health professionals to inform governments on how to formulate health strategies. In this study, we examine the correlation between environmental and climate indicators and COVID-19 outbreak in the top 10 most affected states of the USA. In doing so, PM 2.5 , temperature, humidity, environmental quality index, and rainfall are included as crucial meteorological and environmental factors. Kendall and Spearman rank correlation coefficients, quantile regression, and log-linear negative binominal analysis are employed as an estimation strategy. The empirical estimates conclude that temperature, humidity, environmental quality index, PM 2.5 , and rainfall are significant factors related to the COVID-19 pandemic in the top 10 most affected states of the USA. The empirical findings of the current study would serve as key policy input to mitigate the rapid spread of COVID-19 across the USA.

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