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Xiaolong, G.; Mo, Z.; Xian, L.; Ce, S.; Changbin, S.; Ying, L. |
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Title |
Effects of LED light quality on the growth, metabolism, and energy budgets of Haliotis discus discus |
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Journal Article |
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Year |
2016 |
Publication |
Aquaculture |
Abbreviated Journal  |
Aquaculture |
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Volume |
453 |
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Pages |
31-39 |
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Keywords |
Animals; Abalone; LED; Metabolism; Energy budgets; Haliotis discus; Haliotis discus discus; Photobiology |
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Abstract |
In this study, a bioenergetics approach was used to examine the effects of different LED light qualities (red, orange, blue, green light, natural light and a dark setting) on the growth and survival of the abalone Haliotis discus discus, and its physiological response mechanism under different light qualities. The results suggest that under blue or green light, the survival rate, specific growth rate, food intake, and food conversion efficiency of H. d. discus were significantly lower than in those groups under red or orange light (P < 0.05). Under red or orange light, pepsin, amylase and cellulose activity was significantly higher than those in any other light quality group (P < 0.05), whereas lipase activity exhibited no significant difference among the light quality groups (P > 0.05). Under blue or green light, lactate dehydrogenase activity and lactic acid content were higher (P < 0.05), suggesting enhanced anaerobic metabolism. Under blue or green light, H. d. discus lost more energy via excretion, feces and respiration than was acquired from its food. Under red or orange light, H. d. discus acquired more energy from its food and lost less energy via excretion and feces; as a result, its assimilation efficiency (K1) and net growth efficiency (K2) were significantly higher than those of any other group (P < 0.05). Therefore, we suggest that red or orange light should be used as a light source for the aquaculture of H. d. discus. |
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Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China |
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Elsevier |
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English |
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English |
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0044-8486 |
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IDA @ john @ |
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1311 |
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Author |
Rybnikova, N.A.; Haim, A.; Portnova, B.A. |
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Title |
Is Prostate Cancer Incidence Worldwide Linked to Artificial Light at Night Exposures? Earlier Findings' Revisit and Current Trends' Analysis |
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Journal Article |
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Year |
2016 |
Publication |
Archives of Environmental & Occupational Health |
Abbreviated Journal |
Arch Environ Occup Health |
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Volume |
72 |
Issue |
2 |
Pages |
111-122 |
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Keywords |
Human Health; Remote Sensing |
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Abstract |
Widespread use of artificial light at night (ALAN) might contribute to the global burden of hormone-dependent cancers. However, previous attempts to verify this association in population-level studies have been sparse. Using the GLOBOCAN, US-DMSP and World Bank's 2010-2012 databases, we studied the association between ALAN and prostate cancer (PC) incidence in 180 countries worldwide, controlling for several country-level confounders. As our analysis indicates, the PC-ALAN association emerged marginally significant when year-2012 PC age-standardized rate data were compared with ALAN levels (t = 1.886, P<0.1); while this association emerged as more significant (t>2.7; P<0.01) when only 110 countries with well-maintained cancer registries were analyzed. Along with other variables, ALAN explains up to 79% of PC ASRs variability. PC-ALAN association appears to vary regionally, with the greatest deviations in Central Africa, Small Island Developing States, South East Asia and Gulf States. |
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a Department of Natural Resources and Environmental Management, Faculty of Management, University of Haifa, 31805, Carmel, Mt, Israel |
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1933-8244 |
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PMID:27029744 |
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LoNNe @ kyba @ |
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1412 |
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Kim, Y.J.; Park, M.S.; Lee, E.; Choi, J.W. |
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Title |
High Incidence of Breast Cancer in Light-Polluted Areas with Spatial Effects in Korea |
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Journal Article |
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Year |
2016 |
Publication |
Asian Pacific Journal for Cancer Prevention |
Abbreviated Journal |
Asian Pac J Cancer Prev |
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Volume |
17 |
Issue |
1 |
Pages |
361-367 |
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Keywords |
Human Health; Light pollution; breast cancer; spatial analysis; intrinsic conditional autoregressive model |
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We have reported a high prevalence of breast cancer in light-polluted areas in Korea. However, it is necessary to analyze the spatial effects of light polluted areas on breast cancer because light pollution levels are correlated with region proximity to central urbanized areas in studied cities. In this study, we applied a spatial regression method (an intrinsic conditional autoregressive [iCAR] model) to analyze the relationship between the incidence of breast cancer and artificial light at night (ALAN) levels in 25 regions including central city, urbanized, and rural areas. By Poisson regression analysis, there was a significant correlation between ALAN, alcohol consumption rates, and the incidence of breast cancer. We also found significant spatial effects between ALAN and the incidence of breast cancer, with an increase in the deviance information criterion (DIC) from 374.3 to 348.6 and an increase in R² from 0.574 to 0.667. Therefore, spatial analysis (an iCAR model) is more appropriate for assessing ALAN effects on breast cancer. To our knowledge, this study is the first to show spatial effects of light pollution on breast cancer, despite the limitations of an ecological study. We suggest that a decrease in ALAN could reduce breast cancer more than expected because of spatial effects. |
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Department of Preventive Medicine, College of Medicine, Korea University, Seoul, Korea; eunil(at)korea.ac.kr. |
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Asian Pacific Organization for Cancer Prevention |
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Korea |
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English |
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English |
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Call Number |
IDA @ john @ |
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1362 |
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Author |
Zhao, X.; Shi, H.; Yu, H.; Yang, P. |
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Title |
Inversion of Nighttime PM2.5 Mass Concentration in Beijing Based on the VIIRS Day-Night Band |
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Journal Article |
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Year |
2016 |
Publication |
Atmosphere |
Abbreviated Journal |
Atmosphere |
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Volume |
7 |
Issue |
10 |
Pages |
136 |
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Keywords |
Remote Sensing |
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Abstract |
In order to monitor nighttime particular matter (PM) air quality in urban area, a back propagation neural network (BP neural network) inversion model is established, using low-light radiation data from the day/night band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The study focuses on the moonless and cloudless nights in Beijing during March–May 2015. A test is carried out by selecting surface PM2.5 data from 12 PM2.5 automatic monitoring stations and the corresponding night city light intensity from DNB. As indicated by the results, the linear correlation coefficient (R) between the results and the corresponding measured surface PM2.5 concentration is 0.91, and the root-mean-square error (RMSE) is 14.02 μg/m3 with the average of 59.39 μg/m3. Furthermore, the BP neural network model shows better accuracy when air relative humility ranges from 40% to 80% and surface PM2.5 concentration exceeds 40 μg/m3. The study provides a superiority approach for monitoring PM2.5 air quality from space with visible light remote sensing data at night. |
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2073-4433 |
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no |
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LoNNe @ kyba @ |
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1546 |
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Author |
Li, C.; Hsu, N.C.; Sayer, A.M.; Krotkov, N.A.; Fu, J.S.; Lamsal, L.N.; Lee, J.; Tsay, S.-C. |
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Title |
Satellite observation of pollutant emissions from gas flaring activities near the Arctic |
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Journal Article |
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Year |
2016 |
Publication |
Atmospheric Environment |
Abbreviated Journal |
Atmospheric Environment |
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Volume |
133 |
Issue |
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Pages |
1-11 |
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Keywords |
Remote Sensing |
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1352-2310 |
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LoNNe @ kyba @ |
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1373 |
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