| Records |
| Author |
Wu, B.; Wang, Y.; Wu, X.; Liu, D.; Xu, D.; Wang, F. |
| Title |
On-orbit sleep problems of astronauts and countermeasures |
Type |
Journal Article |
| Year |
2018 |
Publication |
Military Medical Research |
Abbreviated Journal |
Mil Med Res |
| Volume |
5 |
Issue |
1 |
Pages |
17 |
| Keywords |
Human Health |
| Abstract |
Sufficient sleep duration and good sleep quality are crucial to ensure normal physical and mental health, cognition and work performance for the common people, as well as astronauts. On-orbit sleep problem is very common among astronauts and has potential detrimental influences on the health of crewmembers and the safety of flight missions. Sleep in space is becoming a new medical research frontier. In this review we summarized on-orbit sleep problems of astronauts and six kinds of causes, and we presented the effects of lack of sleep on performance as well as mental and physical health, then we proposed seven kinds of countermeasures for sleep disturbance in spaceflight, including pharmacologic interventions, light treatment, crew selection and training, Traditional Chinese Medicine and so on. Furthermore, we discussed and oriented the prospect of researches on sleep in space. |
Address  |
State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, No. 26 Beiqing Road, Haidian District, Beijing, 100094, People's Republic of China |
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English |
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2054-9369 |
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PMID:29843821; PMCID:PMC5975626 |
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no |
| Call Number |
GFZ @ kyba @ |
Serial |
1930 |
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| Author |
Zeng, C.; Zhou, Y.; Wang, S.; Yan, F.; Zhao, Q. |
| Title |
Population spatialization in China based on night-time imagery and land use data |
Type |
Journal Article |
| Year |
2011 |
Publication |
International Journal of Remote Sensing |
Abbreviated Journal |
International Journal of Remote Sensing |
| Volume |
32 |
Issue |
24 |
Pages |
9599-9620 |
| Keywords |
DMSP-OLS; remote sensing; light at night; population; modeling |
| Abstract |
Population is a key indicator of socioeconomic development, urban planning and environmental protection, particularly for developing countries like China. But, census data for any given area are neither always available nor adequately reflect the internal differences of population. The authors tried to overcome this problem by spatializing the population across China through utilizing integer night-time imagery (Defense Meteorological Satellite Program/Operational Linescan System, DMSP/OLS) and land-use data. In creating the population linear regression model, night-time light intensity and lit areas, under different types of land use, were employed as predictor variables, and census data as dependent variables. To improve model performance, eight zones were created using night-time imagery clustering and shortest path algorithm. The population model is observed to have a coefficient of determination (R 2) ranging from 0.80 to 0.95 in the research area, which remained the same in different years. A comparison of the results of this study with those of other researchers shows that the spatialized population density map, prepared on the basis of night-time imagery, reflects the population distribution character more explicitly and in greater detail. |
| Address |
State Key Laboratory of Remote Sensing Science , Jointly Sponsored by the Institute of Remote Sensing Applications of the Chinese Academy of Sciences and Beijing Normal University , Beijing, 100101, PR China |
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0143-1161 |
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IDA @ john @ |
Serial |
228 |
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| Author |
Liu, X.Y.; Luo, M.R.; Li, H. |
| Title |
A study of atmosphere perceptions in a living room |
Type |
Journal Article |
| Year |
2014 |
Publication |
Lighting Research and Technology |
Abbreviated Journal |
Lighting Research and Technology |
| Volume |
47 |
Issue |
5 |
Pages |
581-594 |
| Keywords |
lighting; indoor lighting; perception; Chinese; Dutch; aesthetics |
| Abstract |
An experiment has been carried out to investigate the effect of lighting on the perception of atmosphere in a living room, using three types of light sources: halogen, fluorescent and LED lamps. In a psychophysical experiment, 29 native Chinese observers assessed eight lighting conditions having different luminances and correlated colour temperatures. For each condition, 71 scales were employed using the categorical judgment method. Factor analysis identified two underlying dimensions: liveliness and cosiness. This agrees with those found by Vogels who used Dutch observers to assess atmosphere perception. Both observer groups also agreed that an increase of luminance would make the room more lively. However, there were also some disagreements such as a higher CCT source would make the room more lively for Chinese observers but less lively for Dutch observers. |
| Address |
State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou, China |
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SAGE |
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English |
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IDA @ john @ |
Serial |
310 |
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| Author |
Zhang, G.; Li, L.; Jiang, Y.; Shen, X.; Li, D. |
| Title |
On-Orbit Relative Radiometric Calibration of the Night-Time Sensor of the LuoJia1-01 Satellite |
Type |
Journal Article |
| Year |
2018 |
Publication |
Sensors (Basel, Switzerland) |
Abbreviated Journal |
Sensors (Basel) |
| Volume |
18 |
Issue |
12 |
Pages |
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| Keywords |
Instrumentation; Remote Sensing |
| Abstract |
The LuoJia1-01 satellite can acquire high-resolution, high-sensitivity nighttime light data for night remote sensing applications. LuoJia1-01 is equipped with a 4-megapixel CMOS sensor composed of 2048 x 2048 unique detectors that record weak nighttime light on Earth. Owing to minute variations in manufacturing and temporal degradation, each detector's behavior varies when exposed to uniform radiance, resulting in noticeable detector-level errors in the acquired imagery. Radiometric calibration helps to eliminate these detector-level errors. For the nighttime sensor of LuoJia1-01, it is difficult to directly use the nighttime light data to calibrate the detector-level errors, because at night there is no large-area uniform light source. This paper reports an on-orbit radiometric calibration method that uses daytime data to estimate the relative calibration coefficients for each detector in the LuoJia1-01 nighttime sensor, and uses the calibrated data to correct nighttime data. The image sensor has a high dynamic range (HDR) mode, which is optimized for day/night imaging applications. An HDR image can be constructed using low- and high-gain HDR images captured in HDR mode. Hence, a day-to-night radiometric reference transfer model, which uses daytime uniform calibration to calibrate the detector non-uniformity of the nighttime sensor, is herein built for LuoJia1-01. Owing to the lack of calibration equipment on-board LuoJia1-01, the dark current of the nighttime sensor is calibrated by collecting no-light desert images at new moon. The results show that in HDR mode (1) the root mean square of mean for each detector in low-gain (high-gain) images is better than 0.04 (0.07) in digital number (DN) after dark current correction; (2) the DN relationship between low- and high-gain images conforms to the quadratic polynomial mode; (3) streaking metrics are better than 0.2% after relative calibration; and (4) the nighttime sensor has the same relative correction parameters at different exposure times for the same gain parameters. |
| Address |
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. drli@whu.edu.cn |
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English |
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1424-8220 |
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| Notes |
PMID:30513817 |
Approved |
no |
| Call Number |
GFZ @ kyba @ |
Serial |
2125 |
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| Author |
Zhen, J.; Pei, T.; Xie, S. |
| Title |
Kriging methods with auxiliary nighttime lights data to detect potentially toxic metals concentrations in soil |
Type |
Journal Article |
| Year |
2019 |
Publication |
The Science of the Total Environment |
Abbreviated Journal |
Sci Total Environ |
| Volume |
659 |
Issue |
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Pages |
363-371 |
| Keywords |
Remote Sensing |
| Abstract |
The spatial distribution of potentially toxic metals (PTMs) has been shown to be related to anthropogenic activities. Several auxiliary variables, such as those related to remote sensing data (e.g. digital elevation models, land use, and enhanced vegetation index) and soil properties (e.g. pH, soil type and cation exchange capacity), have been used to predict the spatial distribution of soil PTMs. However, these variables are mostly focused on natural processes or a single aspect of anthropogenic activities and cannot reflect the effects of integrated anthropogenic activities. Nighttime lights (NTL) images, a representative variable of integrated anthropogenic activities, may have the potential to reflect PTMs distribution. To uncover this relationship and determine the effects on evaluation precision, the NTL was employed as an auxiliary variable to map the distribution of PTMs in the United Kingdom. In this study, areas with a digital number (DN)>/=50 and an area>30km(2) were extracted from NTL images to represent regions of high-frequency anthropogenic activities. Subsequently, the distance between the sampling points and the nearest extracted area was calculated. Barium, lead, zinc, copper, and nickel concentrations exhibited the highest correlation with this distance. Their concentrations were mapped using distance as an auxiliary variable through three different kriging methods, i.e., ordinary kriging (OK), cokriging (CK), and regression kriging (RK). The accuracy of the predictions was evaluated using the leave-one-out cross validation method. Regardless of the elements, CK and RK always exhibited lower mean absolute error and root mean square error, in contrast to OK. This indicates that using the NTL as the auxiliary variable indeed enhanced the prediction accuracy for the relevant PTMs. Additionally, RK showed superior results in most cases. Hence, we recommend RK for prediction of PTMs when using the NTL as the auxiliary variable. |
| Address |
State Key Laboratory of Geological Processes and Mineral Resources(GPMR), Faculty of Earth Sciences, China University of Geosciences, Wuhan, 430074, China |
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English |
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0048-9697 |
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| Notes |
PMID:30599355 |
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no |
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GFZ @ kyba @ |
Serial |
2494 |
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