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Cisse, Y. M., Russart, K., & Nelson, R. J. (2020). Exposure to dim light at night prior to conception attenuates offspring innate immune responses. PLoS One, 15(4), e0231140.
Abstract: Functional circadian timekeeping is necessary for homeostatic control of the immune system and appropriate immune responsiveness. Disruption of natural light-dark cycles, through light at night (LAN), impairs innate and adaptive immune responses in nocturnal rodents. These altered immune responses are associated with disrupted endogenous gene transcriptional and endocrine cycles. However, few studies have addressed the multigenerational consequences of systemic circadian rhythm disruption. We hypothesized that parental exposure to dim LAN (dLAN) would alter innate immune and sickness responses to an endotoxin challenge in adult offspring gestated and reared in dark nights. Adult male and female Siberian hamsters were exposed to either dark nights (DARK) or dLAN (~5 lux) for 8 weeks, then paired, mated, and thereafter housed under dark nights. Maternal exposure to dLAN prior to conception impaired febrile responses and increased splenic il-1 production in response to LPS in male offspring. Paternal pre-conception dLAN dampened offspring tnf-alpha expression in the hypothalamus, reduced serum bactericidal capacity, and dark phase locomotor activity. These changes occurred despite offspring being conceived, gestated, and reared under standard dark night conditions. Overall, these data suggest that dLAN has intergenerational effects on innate immunity and sickness responses.
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Roman, M. O., Stokes, E. C., Shrestha, R., Wang, Z., Schultz, L., Carlo, E. A. S., et al. (2019). Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14(6), e0218883.
Abstract: A real-time understanding of the distribution and duration of power outages after a major disaster is a precursor to minimizing their harmful consequences. Here, we develop an approach for using daily satellite nighttime lights data to create spatially disaggregated power outage estimates, tracking electricity restoration efforts after disasters strike. In contrast to existing utility data, these estimates are independent, open, and publicly-available, consistently measured across regions that may be serviced by several different power companies, and inclusive of distributed power supply (off-grid systems). We apply the methodology in Puerto Rico following Hurricane Maria, which caused the longest blackout in US history. Within all of the island's settlements, we track outages and recovery times, and link these measures to census-based demographic characteristics of residents. Our results show an 80% decrease in lights, in total, immediately after Hurricane Maria. During the recovery, a disproportionate share of long-duration power failures (> 120 days) occurred in rural municipalities (41% of rural municipalities vs. 29% of urban municipalities), and in the northern and eastern districts. Unexpectedly, we also identify large disparities in electricity recovery between neighborhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, the most vulnerable to increased mortality and morbidity risks from power losses, shouldered the longest outages because they lived in less dense, detached housing where electricity restoration lagged. The approach developed in this study demonstrates the potential of satellite-based estimates of power recovery to improve the real-time monitoring of disaster impacts, globally, at a spatial resolution that is actionable for the disaster response community.
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Andrade-Pacheco, R., Savory, D. J., Midekisa, A., Gething, P. W., Sturrock, H. J. W., & Bennett, A. (2019). Household electricity access in Africa (2000-2013): Closing information gaps with model-based geostatistics. PLoS One, 14(5), e0214635.
Abstract: Household electricity access data in Africa are scarce, particularly at the subnational level. We followed a model-based Geostatistics approach to produce maps of electricity access between 2000 and 2013 at a 5 km resolution. We collated data from 69 nationally representative household surveys conducted in Africa and incorporated nighttime lights imagery as well as land use and land cover data to produce maps of electricity access between 2000 and 2013. The information produced here can be an aid for understanding of how electricity access has changed in the region during this 14 year period. The resolution and the continental scale makes it possible to combine these data with other sources in applications in the socio-economic field, both at a local or regional level.
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Lu, Y., & Coops, N. C. (2018). Bright lights, big city: Causal effects of population and GDP on urban brightness. PLoS One, 13(7), e0199545.
Abstract: Cities are arguably both the cause, and answer, to societies' current sustainability issues. Urbanization is the interplay between a city's physical growth and its socio-economic development, both of which consume a substantial amount of energy and resources. Knowledge of the underlying driver(s) of urban expansion facilitates not only academic research but, more importantly, bridges the gap between science, policy drafting, and practical urban management. An increasing number of researchers are recognizing the benefits of innovative remotely sensed datasets, such as nighttime lights data (NTL), as a proxy to map urbanization and subsequently examine the driving socio-economic variables in cities. We further these approaches, by taking a trans-pacific view, and examine how an array of socio-economic ind0icators of 25 culturally and economically important urban hubs relate to long term patterns in NTL for the past 21 years. We undertake a classic econometric approach-panel causality tests which allow analysis of the causal relationships between NTL and socio-economic development across the region. The panel causality test results show a contrasting effect of population and gross domestic product (GDP) on NTL in fast, and slowly, changing cities. Information derived from this study quantitatively chronicles urban activities in the pan-Pacific region and potentially offers data for studies that spatially track local progress of sustainable urban development goals.
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Yao, Y., Chen, D., Chen, L., Wang, H., & Guan, Q. (2018). A time series of urban extent in China using DSMP/OLS nighttime light data. PLoS One, 13(5), e0198189.
Abstract: Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning.
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