Complex system properties in the spreading of COVID-19 pandemic

The objective of the present study was to show that the spread of the COVID-19 pandemic around the world shows complex system properties such as lognormal laws, temporal fluctuation scaling, and time correlation. First, the daily cumulative number of confirmed cases and deaths is distributed among countries as lognormals such that the time series exhibit a temporal fluctuation scaling. Second, the daily return time series of cases and deaths per day have associated Levy stable distributions and they have time correlation. The idea was to draw attention to the fact that the spread of the COVID-19 pandemic can be seen as a complex system, and, thus, contribute to the identification of the structural properties of this system, which is relevant as it is expected that future stochastic models describing the spread of the COVID-19 pandemic from a microscopic dynamics perspective should be able to explain the emergence of the structural properties identified here.

Cancer-Cell Deep-Learning Classification by Integrating Quantitative-Phase Spatial and Temporal Fluctuations

We present a new classification approach for live cells, integrating together the spatial and temporal fluctuation maps and the quantitative optical thickness map of the cell, as acquired by common-path quantitative-phase dynamic imaging and processed with a deep-learning framework. We demonstrate this approach by classifying between two types of cancer cell lines of different metastatic potential originating from the same patient. It is based on the fact that both the cancer-cell morphology and its mechanical properties, as indicated by the cell temporal and spatial fluctuations, change over the disease progression. We tested different fusion methods for inputting both the morphological optical thickness maps and the coinciding spatio-temporal fluctuation maps of the cells to the classifying network framework. We show that the proposed integrated triple-path deep-learning architecture improves over deep-learning classification that is based only on the cell morphological evaluation via its quantitative optical thickness map, demonstrating the benefit in the acquisition of the cells over time and in extracting their spatio-temporal fluctuation maps, to be used as an input to the classifying deep neural network.

Application of loudness level to temporally varying sounds

Most of the environmental noises are temporally varying and include various frequency components. Various methods for evaluating the environmental noises have been proposed. Among them, the method for calculating loudness level was first standardized in 1975 as ISO 532, including Stevens' and Zwicker's methods. Unfortunately, these methods can only be applied to steady state sounds. On the other hand, Aeq (Equivalent Continuous A-weight Sound Pressure Level) is standardized for the evaluation of level fluctuating environmental sounds as ISO 1996. In , the energy mean and A-weighting are used for averaging temporal fluctuation and frequency weighting, respectively. The present authors with their colleagues have conducted many psychological experiments using artificial sounds and actual sounds since 1970's and have being introduced that p (Loudness-based Method), which is a combination of ISO 532 for frequency weighting and ISO 1996 for temporal level fluctuation, is a good method for evaluating various kinds of environmental sounds. ISO 532-1 (Zwicker's method) has been revised including the temporal fluctuation into consideration in 2017, in which p has been adopted as a note. The merit of p will be introduced in this paper presenting many examples.

Influence of COVID-19 Lockdown on Aerosol Optical Depth over Pokhara and Kyanjin Gompa in Nepal

The outbreak of the COVID-19 pandemic and the subsequent global economic shutdown provided an opportunity to conduct a real-time experiment assessing the influence of global emission reductions in the Aerosol Optical Depth (AOD) level, an indicator of air pollution over Nepal. Nepal's government imposed a lockdown on the country for approximately three months (from 24 March onwards) in 2020. The purpose of this study is to examine the temporal fluctuation in Aerosol Optical Depth (AOD) caused by the COVID-19 shutdown by comparing its value during the same time period of the past year over two sites: Pokhara and Kyanjin Gompa. We comparatively analyzed the variation of diurnal mean and monthly average AOD of two selected sites, from the month of January to May 2020 and January to May 2018. By examining the time-series graph of daily average AOD prior to and during the lockdown period, our study showed an apparent fluctuation in AOD throughout the studied areas. The major findings of the research revealed that after the lockdown, a significant variation in monthly averaged AOD was observed, ranging from 20–60% deviation over Pokhara and 25–50% deviation in Kyanjin Gompa at different wavelengths. This confirms previous studies on aerosols and other particulate matter during COVID-19 lockdown, as well as theoretical assumptions. In addition, we performed the heatmap correlation analysis among AOD, Total precipitable water (Tpw), Angstrom exponent (α), Turbidity coefficient (β), and Visibility (V) during the studied period with possible explanations. We believe this research work serves as a crucial reference for our government to implement appropriate policies for pollution control over the studied areas in the future.

The temporal fluctuation of the inverse participation ratio for localized field modes in three-dimensional percolation system

We investigate the structure of the optical field radiated by the disordered optical nano-emitters randomly incorporated in three-dimensional cluster of a percolation material. Our numerical studies shown that the temporal variations of the inverse participation ratio (IPR) allow analyzing the extended and localized field structures over a long time range. The properties of IPR and the dynamics of the lasing emitters allow to find the characteristic time scales when the localization of the field in a general three-dimensional disordered system occurs. The studied effect opens new perspectives to control the optical fields localization in modern optical nano-technologies.