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  • 2015-2019  (410)
  • 1985-1989  (1)
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  • 1
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Clinical and experimental pharmacology and physiology 15 (1988), S. 0 
    ISSN: 1440-1681
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: b1. The effects of central administration of met-enkephalin, leu-enkephalin, the enkephalin analogue FK-33824 and the opiate antagonist naloxone on plasma concentration of adrenocorticotrophic hormone (ACTH) were examined in conscious sheep.2. Intracerebroventricular infusion of met-enkephalin and FK-33824 significantly decreased the basal plasma concentration of ACTH.3. Intracerebroventricular infusion of FK-33824 inhibited the haemorrhage-induced increase in plasma concentration of ACTH.4. Intracerebroventricular infusion of naloxone attenuated the central inhibition of plasma concentration of ACTH induced by FK-33824, but intravenous infusion of naloxone had no effect on the reduction in plasma concentration of ACTH induced by FK-33824.5. These studies suggest that in sheep met-enkephalin may play a central inhibitory role in the control of ACTH secretion.
    Type of Medium: Electronic Resource
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  • 2
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    PANGAEA
    In:  RMIT University, Melbourne | Supplement to: Wang, Xiaoming; Zhang, Kefei; Wu, Suqin; Fan, Shijie; Cheng, Yingyan (2016): Water vapor-weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend. Journal of Geophysical Research: Atmospheres, 121(2), 833-852, https://doi.org/10.1002/2015JD024181
    Publication Date: 2023-01-13
    Description: Water vapor-weighted mean temperature, Tm, is a vital parameter for retrieving precipitable water vapor (PWV) from the zenith wet delay (ZWD) of Global Navigation Satellite Systems (GNSS) signal propagation. In this study, the Tm at 368 GNSS stations for 2000-2012 were calculated using three methods: (1) temperature and humidity profiles from ERA-Interim, (2) the Bevis Tm-Ts relationship, and (3) the Global Pressure and Temperature 2 wet model. Tm derived from the first method was used as a reference to assess the errors of the other two methods. Comparisons show that the relative errors of the Tm derived from these two methods are in the range of 1-3% across more than 95% of all the stations. The PWVs were calculated using the aforementioned three types of Tm and the GNSS-derived ZWD at 107 stations. Again, the PWVs calculated using Tm from the first method were used as the reference of the other two PWVs. The root-mean-square errors of these two PWVs are both in the range of 0.1-0.7 mm. The second method is recommended in real-time applications, since its performance is slightly better than the third method. In addition, the linear trends of the PWV time series from the first method were also used as the reference to evaluate the trends from the other two methods. Results show that 13% and 23% of the PWV trends from the respective second and third methods have a relative error of larger than 10%. For climate change studies, the first method, if available, is always recommended.
    Type: Dataset
    Format: application/zip, 372 datasets
    Location Call Number Limitation Availability
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  • 3
    Publication Date: 2023-01-13
    Keywords: ADE1; Analysis of precipitable water vapor from GPS measurements; Australia; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 32680 data points
    Location Call Number Limitation Availability
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  • 4
    Publication Date: 2023-01-13
    Keywords: ADIS; Analysis of precipitable water vapor from GPS measurements; DATE/TIME; Day of the year; Ethiopia; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 13458 data points
    Location Call Number Limitation Availability
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  • 5
    Publication Date: 2023-01-13
    Keywords: AIRA; Analysis of precipitable water vapor from GPS measurements; DATE/TIME; Day of the year; Japan; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 43728 data points
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  • 6
    Publication Date: 2023-01-13
    Keywords: ALGO; Analysis of precipitable water vapor from GPS measurements; Canada; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 57340 data points
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  • 7
    Publication Date: 2023-01-13
    Keywords: ALBH; Analysis of precipitable water vapor from GPS measurements; British Columbia, Canada; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 58180 data points
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  • 8
    Publication Date: 2023-01-13
    Keywords: ALIC; Analysis of precipitable water vapor from GPS measurements; Australia; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 50798 data points
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  • 9
    Publication Date: 2023-01-13
    Keywords: ALRT; Analysis of precipitable water vapor from GPS measurements; Arctic Ocean; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 31766 data points
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  • 10
    Publication Date: 2023-01-13
    Keywords: AMC2; Analysis of precipitable water vapor from GPS measurements; DATE/TIME; Day of the year; Precipitable water vapour; United States of America; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 43752 data points
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