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Recent studies have shown that reducing the precision of floating‐point calculations in an atmospheric model can improve the model's computational performance without affecting model fidelity, but code changes are needed to accommodate lower precision or to prevent undue round‐off error. For complex...

Clean energy from oceans and rivers is becoming a reality with the development of new technologies like tidal and instream turbines that generate electricity from naturally flowing water. These new technologies are being monitored for effects on fish and other wildlife using underwater video...

We report the construction of a database of infrared spectra aimed at detecting the gases emitted by biomass burning. The project uses many of the methods of the Pacific Northwest National Laboratory (PNNL) infrared database, but the selection of the species and special experimental considerations...

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The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over...

Christine H Chang, William C Nelson, Abby Jerger, Aaron T Wright, Robert G Egbert, Jason E McDermott, Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding, Bioinformatics Advances , Volume 3, Issue 1, 2023, vbad005, https://doi.org/10.1093/bioadv/vbad005...

The Human Islet Research Network (HIRN) is a large consortia with many research projects focused on understanding how beta cells are lost in type 1 diabetics (T1D) with a goal of finding how to protect against or replace the loss of functional beta cells. The consortia has multiple branches of...

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This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities.

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The EyeSea underwater video dataset was assembled for developing algorithms for detecting fish in real world underwater video data. The data were recorded as part of environmental monitoring efforts at three different water power sites.
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This project is an interdisciplinary collaboration supported by US DOE Office of Science's Scientific Discovery through Advanced Computing (SciDAC) program. The project addresses a crucial but largely overlooked source of error in the Energy Exascale Earth System Model (E3SM) and other atmosphere...

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This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities.

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The PNNL-SERDP database was constructed by PNNL to generate the quantitative infrared spectra of gases associated with biomass burning; the reference data are to allow detection and quantification of such gases via infrared absorption spectroscopy. Candidates for the database were selected based on...

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Predictive Phenomics is addressing the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems .

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The Human Islet Research Network (HIRN) is a large consortia with many research projects focused on understanding how beta cells are lost in type 1 diabetics (T1D) with a goal of finding how to protect against or replace the loss of functional beta cells. The consortia has multiple branches of...

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Machine learning is a core technology that is rapidly advancing within type 1 diabetes (T1D) research. Our Human Islet Research Network (HIRN) grant is studying early cellular response initiating β cell stress in T1D through the generation of heterogenous low- and high-throughput molecular...

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The VAST Challenge 2019 presents three mini-challenges and a grand challenge for you to apply your visual analytics research and technologies to help a city grapple with the aftermath of an earthquake that damages their nuclear power plant. These challenges are open to participation by individuals...
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