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451 to 460 of 485 Results
PolyP-JC-D7 fluorescence_calibration.tab
May 6, 2024 - Polyphosphate extraction and quantification in environmental planktonic samples using a fluorescence dye JC-D7, method assessment
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...
PolyP_MethodComparison.tab
May 6, 2024 - Polyphosphate extraction and quantification in environmental planktonic samples using a fluorescence dye JC-D7, method assessment
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.
Polyphosphate in aquatic environments
May 6, 2024
This is a collection of polyphosphate data in aquatic environments.
Policy Country Actor Short List 20240330-1.pdf
Apr 2, 2024 - Policy Interventions and Actors
Adobe PDF - 383.3 KB - MD5: 3504c9cbfb5ab464784572fccd4845b0
List of policy actors by country and sector, with name of the policy/program specified
Innovation for Sustainable Development Policy Actors and Policy Mixes
Mar 25, 2024
A database of innovation policies between 2008 and 2020 that support sustainable development. Includes OECD countries between 4-6million people, plus Central European and Nordic countries, Singapore (for energy sector) and Hong Kong.
Codes for machine learning and Shapley value analysis
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...
_beeswarm.py
Mar 18, 2024 - Codes for machine learning and Shapley value analysis
Python Source Code - 44.3 KB - MD5: 95f77842584d6e194edc3fd54225121e
Ensemble_global_shap_analysis.py
Mar 18, 2024 - Codes for machine learning and Shapley value analysis
Python Source Code - 7.1 KB - MD5: de87681988f9e11cf6a67e3710a1d5df
_scatter.py
Mar 18, 2024 - Codes for machine learning and Shapley value analysis
Python Source Code - 34.9 KB - MD5: ecf526403dc904c321a6c15e52426b6a
Factor_dominance_shap_analysis.py
Mar 15, 2024 - Codes for machine learning and Shapley value analysis
Python Source Code - 2.6 KB - MD5: 48a19eb170ddcbf0b891aa64dc06358b
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