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491 to 500 of 1,413 Results
Jun 13, 2024 - Library
Hong Kong University of Science and Technology Library, 2015, "Wi-Fi Connection in HKUST Library", https://doi.org/10.14711/dataset/RQXRQB, DataSpace@HKUST, V9, UNF:6:B31JdKI74W9jFUjjErlyyA== [fileUNF]
Quantitative data of Wi-Fi connection in the Library building of the Hong Kong University of Science and Technology collected between February 2014 and May 2022. This dataset provides usage estimation and trends relating to the number of users in the Library, by floors, user type...
May 6, 2024 - Polyphosphate in aquatic environments
LI, Jiying, 2024, "Polyphosphate extraction and quantification in environmental planktonic samples using a fluorescence dye JC-D7, method assessment", https://doi.org/10.14711/dataset/A1BO6O, DataSpace@HKUST, V1, UNF:6:vZExePw2W4wTUE6K2UiVaw== [fileUNF]
We develop and evaluate a method for quantifying polyP in environmental planktonic samples. This dataset includes two data files. The first file (table) includes the responses of polyP-JC-D7 fluorescence signal (excitation 405 nm, emission 535 nm) under a range of polyP concentra...
MS Word - 78.0 KB - MD5: a2e78d9f1c9099301069df3f11c56254
This is the metadata file of the dataset.
Tabular Data - 18.1 KB - 12 Variables, 233 Observations - UNF:6:bOi5+P7kh26dfsVgd2/88Q==
The file includes data for the responses of polyP-JC-D7 fluorescence signal (excitation 405 nm, emission 535 nm) under a range of polyP concentrations, tested for a number of experimental variabilities, including the compositions of the cell lysing buffer, the concentration of th...
Tabular Data - 29.5 KB - 8 Variables, 244 Observations - UNF:6:HHbiWh50oVyctSumXK9QUA==
The file includes data for comparisons of polyP estimated using different extraction and quantification methods, from algae, bacteria, and environmental samples.
Adobe PDF - 383.3 KB - MD5: 3504c9cbfb5ab464784572fccd4845b0
List of policy actors by country and sector, with name of the policy/program specified
Mar 18, 2024 - Evaluating two wildfire indices and projecting future risks based on CMIP6 multi-model projections
HE, Yan; ZHOU, Zixuan; IM, Eun-Soon, 2024, "Codes for machine learning and Shapley value analysis", https://doi.org/10.14711/dataset/9ZOATO, DataSpace@HKUST, V2
This dataset contains the codes for machine learning and Shapley value analysis over global land and two single spots (Amazona and Southern New South Wales). We have customized the Shapley Value visualization tools based on the original package, so please update the _beeswarm.py...
Python Source Code - 44.3 KB - MD5: 95f77842584d6e194edc3fd54225121e
Python Source Code - 7.1 KB - MD5: de87681988f9e11cf6a67e3710a1d5df
Python Source Code - 34.9 KB - MD5: ecf526403dc904c321a6c15e52426b6a
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