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Carbon Crops Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network and Resilient Economic Agricultural Practices in Morris, Minnesota The overall goal of the Carbon...
Search relevance: 1.00 | Views last month: 9 | Catalog Last Checked: May 05, 2026 at 11:41 PM -
These environmental DNA data and corresponding water quality data were collected and analyzed by the Fish and Wildlife Service in 2017. The samples were collected from 4 sites in pools 17 and 18...
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These data were compiled for a study that investigated the effects of drought seasonality and plant community composition on two dominant perennial grasses, Achnatherum hymenoides (C3...
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The NIST/SEMATECH e-Handbook of Statistical Methods is a Web-based book written to help scientists and engineers incorporate statistical methods into their work as efficiently as possible....
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These data were compiled to assess the response of vegetation and biological soil crusts to drought in a semi-arid ecosystem on the Colorado Plateau near Moab, Utah. Objective(s) of our study were...
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This repository provides the raw data and analysis code used to demonstrate the implementation of a mathematical framework that uses internal standards to correct for compositionally in MGS...
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These data were compiled to investigate competitive interactions between Pleurphis jamesii and other herbaceous plants in a semiarid grassland community. The objectives of our study were to...
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Included are a report and data from triaxial shear tests on simulated Sierra White fault gouge and a borehole stimulation experiment. This serves as a progress report for the Role of Fluid and...
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Examples of adaptive measurement protocols using optimal Bayesian experiment design. This dataset supports "Simplified algorithms for adaptive experiment design in parameter estimation", arXiv...
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Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model -...
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Python module "optbayesexpt" uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given a parametric model -...
Search relevance: 1.00 | Views last month: 0 | Catalog Last Checked: August 02, 2025 at 02:06 PM -
Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model -...
Search relevance: 1.00 | Views last month: 0 | Catalog Last Checked: August 02, 2025 at 03:06 PM