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Author Romeo, S. et al.
Title Bright light exposure reduces TH-positive dopamine neurons: implications of light pollution in Parkinson's disease epidemiology Type Journal Article
Year 2013 Publication (down) Scientific Reports Abbreviated Journal
Volume 3 Issue Pages
Keywords Animals; Parkinson's disease; Cell death in the nervous system; Neural ageing; Risk factors
Abstract This study explores the effect of continuous exposure to bright light on neuromelanin formation and dopamine neuron survival in the substantia nigra. Twenty-one days after birth, Sprague–Dawley albino rats were divided into groups and raised under different conditions of light exposure. At the end of the irradiation period, rats were sacrificed and assayed for neuromelanin formation and number of tyrosine hydroxylase (TH)-positive neurons in the substantia nigra. The rats exposed to bright light for 20 days or 90 days showed a relatively greater number of neuromelanin-positive neurons. Surprisingly, TH-positive neurons decreased progressively in the substantia nigra reaching a significant 29% reduction after 90 days of continuous bright light exposure. This decrease was paralleled by a diminution of dopamine and its metabolite in the striatum. Remarkably, in preliminary analysis that accounted for population density, the age and race adjusted Parkinson's disease prevalence significantly correlated with average satellite-observed sky light pollution.
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Call Number LoNNe @ christopher.kyba @ Serial 382
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Author Knutsson, A.; Alfredsson, L.; Karlsson, B.; Akerstedt, T.; Fransson, E.I.; Westerholm, P.; Westerlund, H.
Title Breast cancer among shift workers: results of the WOLF longitudinal cohort study Type Journal Article
Year 2013 Publication (down) Scandinavian Journal of Work, Environment & Health Abbreviated Journal Scand J Work Environ Health
Volume 39 Issue 2 Pages 170-177
Keywords Adult; Aged; Breast Neoplasms/*epidemiology/etiology; Circadian Rhythm; Female; Humans; Incidence; Longitudinal Studies; Middle Aged; Proportional Hazards Models; Risk Assessment; Sweden/epidemiology; *Work Schedule Tolerance; oncogenesis
Abstract OBJECTIVE: The aim of this study was to investigate whether shift work (with or without night work) is associated with increased risk of breast cancer. METHODS: The population consisted of 4036 women. Data were obtained from WOLF (Work, Lipids, and Fibrinogen), a longitudinal cohort study. Information about baseline characteristics was based on questionnaire responses and medical examination. Cancer incidence from baseline to follow-up was obtained from the national cancer registry. Two exposure groups were identified: shift work with and without night work. The group with day work only was used as the reference group in the analysis. Cox regression analysis was used to calculate relative risk. RESULTS: In total, 94 women developed breast cancer during follow-up. The average follow-up time was 12.4 years. The hazard ratio for breast cancer was 1.23 [95% confidence interval (95% CI) 0.70-2.17] for shifts without night work and 2.02 (95% CI 1.03-3.95) for shifts with night work. When including only women <60 years of age, the risk estimates were 1.18 (95% CI 0.67-2.07) for shifts without night work, and 2.15 (95% CI 1.10-4.21) for shifts with night work. CONCLUSIONS: Our results indicate an increased risk for breast cancer among women who work shifts that includes night work.
Address Department of Health Sciences, Mid Sweden University, Sundsvall. Sweden. Anders.Knutsson@miun.se
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ISSN 0355-3140 ISBN Medium
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Notes PMID:23007867 Approved no
Call Number IDA @ john @ Serial 154
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Author Li, X.; Chen, X.; Zhao, Y.; Xu, J.; Chen, F.; Li, H.
Title Automatic intercalibration of night-time light imagery using robust regression Type Journal Article
Year 2013 Publication (down) Remote Sensing Letters Abbreviated Journal Remote Sensing Letters
Volume 4 Issue 1 Pages 45-54
Keywords remote sensing; light at night
Abstract In remote-sensing community, radiometric calibration of night-time light images has long been a problem, hindering change detection of images in different dates. Currently, an intercalibration model is regarded as the unique solution for the problem, but prior knowledge is needed to extract reference pixels with stable lights, which are hard to obtain in most of the applications. This study proposed an automatic algorithm to extract the reference pixels for convenient use of the intercalibration model, with an assumption that there are sufficient pixels with stable night-time lights in the multi-temporal images. To automatically extract the stable pixels from images in two dates, all pixels in the two dates were entered into a linear regression model, and the outliers viewed as suspected changed pixels were discarded iteratively. Consequently, some stable pixels were extracted and the intercalibration model was implemented. Annual night-time light composites in Beijing, China, from 1992 to 2010 were taken as the study material, and the results show that the multi-temporal calibrated night-time light data have higher correlation with gross domestic production (GDP) (R 2&#8201;=&#8201;0.8734) and urban population (UP) (R 2&#8201;=&#8201;0.9269) than those of the uncalibrated images (with the R 2 values 0.7963 and 0.8575, respectively). Furthermore, the data inconsistency from different night-time light satellites in the same year was reduced with the proposed algorithm. The results demonstrate that the proposed algorithm is effective in intercalibrating the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) images automatically.
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ISSN 2150-704X ISBN Medium
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Notes Approved no
Call Number IDA @ john @ Serial 211
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Author Elvidge, C.; Zhizhin, M.; Hsu, F.-C.; Baugh, K.
Title VIIRS Nightfire: Satellite Pyrometry at Night Type Journal Article
Year 2013 Publication (down) Remote Sensing Abbreviated Journal Remote Sensing
Volume 5 Issue 9 Pages 4423-4449
Keywords SNPP; VIIRS; fire detection; gas flaring; biomass burning; fossil fuel carbon emissions
Abstract The Nightfire algorithm detects and characterizes sub-pixel hot sources using multispectral data collected globally, each night, by the Suomi National Polar Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS). The spectral bands utilized span visible, near-infrared (NIR), short-wave infrared (SWIR), and mid-wave infrared (MWIR). The primary detection band is in the SWIR, centered at 1.6 &#956;m. Without solar input, the SWIR spectral band records sensor noise, punctuated by high radiant emissions associated with gas flares, biomass burning, volcanoes, and industrial sites such as steel mills. Planck curve fitting of the hot source radiances yields temperature (K) and emission scaling factor (ESF). Additional calculations are done to estimate source size (m2), radiant heat intensity (W/m2), and radiant heat (MW). Use of the sensor noise limited M7, M8, and M10 spectral bands at night reduce scene background effects, which are widely reported for fire algorithms based on MWIR and long-wave infrared. High atmospheric transmissivity in the M10 spectral band reduces atmospheric effects on temperature and radiant heat retrievals. Nightfire retrieved temperature estimates for sub-pixel hot sources ranging from 600 to 6,000 K. An intercomparison study of biomass burning in Sumatra from June 2013 found Nightfire radiant heat (MW) to be highly correlated to Moderate Resolution Imaging Spectrometer (MODIS) Fire Radiative Power (MW).
Address Earth Observation Group, NOAA National Geophysical Data Center, Boulder, CO 80305, USA
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ISSN 2072-4292 ISBN Medium
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Call Number IDA @ john @ Serial 199
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Author Li, X.; Xu, H.; Chen, X.; Li, C.
Title Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China Type Journal Article
Year 2013 Publication (down) Remote Sensing Abbreviated Journal Remote Sensing
Volume 5 Issue 6 Pages 3057-3081
Keywords nighttime light; gross regional product; Visible Infrared Imaging Radiometer Suite; linear regression
Abstract Historically, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) was the unique satellite sensor used to collect the nighttime light, which is an efficient means to map the global economic activities. Since it was launched in October 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite has become a new satellite used to monitor nighttime light. This study performed the first evaluation on the NPP-VIIRS nighttime light imagery in modeling economy, analyzing 31 provincial regions and 393 county regions in China. For each region, the total nighttime light (TNL) and gross regional product (GRP) around the year of 2010 were derived, and a linear regression model was applied on the data. Through the regression, the TNL from NPP-VIIRS were found to exhibit R2 values of 0.8699 and 0.8544 with the provincial GRP and county GRP, respectively, which are significantly stronger than the relationship between the TNL from DMSP-OLS (F16 and F18 satellites) and GRP. Using the regression models, the GRP was predicted from the TNL for each region, and we found that the NPP-VIIRS data is more predictable for the GRP than those of the DMSP-OLS data. This study demonstrates that the recently released NPP-VIIRS nighttime light imagery has a stronger capacity in modeling regional economy than those of the DMSP-OLS data. These findings provide a foundation to model the global and regional economy with the recently availability of the NPP-VIIRS data, especially in the regions where economic census data is difficult to access.
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ISSN 2072-4292 ISBN Medium
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Notes Approved no
Call Number IDA @ john @ Serial 201
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