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Understanding the structure and composition of aluminate complexes in extremely alkaline systems such as Bayer liquors has received enormous attention due to their fundamental and industrial importance. However, obtaining direct molecular information of the underlying ion–ion interactions using...

The molecular speciation of aluminum (Al3+) in alkaline solutions is fundamental to its precipitation chemistry within a number of industrial applications that include ore refinement and industrial processing of Al wastes. Under these conditions, Al3+ is predominantly Al(OH)4–, while at high [Al3+]...

X-ray, energetic photon, and electron irradiation can ionize and electronically excite target atoms and molecules. These excitations undergo complicated relaxation and energy-transfer processes that ultimately determine the manifold system responses to the deposited excess energy. In weakly bound...

In highly alkaline “water-in-salt” Na2O/Al2O3/H2O solutions where the monomeric Al(OH)4– anion dominates, isolation of transitional species that seed crystallization of sodium aluminate salt hydrates has been challenging. For example, discrimination of dimeric [for example, Al2O(OH)62–] species via...

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 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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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. This data was generated by PNNL. Activities can be phone calls, transactions, or any other type of communications. Most 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 Environmental Determinants of Diabetes in the Young (TEDDY) study is searching for factors influencing the development of type 1 diabetes (T1D) in children. Research has shown that there are certain genes that correlate to higher risk of developing T1D, but not all children with these genes...

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The Diabetes Autoimmunity Study in the Young (DAISY) seeks to find environmental factors that can trigger the development of type 1 diabetes (T1D) in children. DAISY follows children with high-risk of developing T1D based on family history or genetic markers. Genes, diets, infections, and...

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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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