Dr. Gao obtained her Ph.D degree in Chemistry from institute of chemistry, Chinese Academy of Science. His Ph.D research focused on multiscale modeling of morphology and properties of polymeric materials, polymer processing and unveiling the process–properties relationships. (atomic to coarse...

HDF5 file containing 10,000 hydraulic transmissivity inputs and the corresponding hydraulic pressure field outputs for a two-dimensional saturated flow model of the Hanford Site. The inputs are generated by sampling a 1,000-dimensional Kosambi-Karhunen-Loève (KKL) model of the transmissivity field...

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...

This dataset was collected from PNNL operated buildings utilizing the PNNL developed open source platform, VOLTTRON in conjunction with PNNL Facilities and Operations staff. VOLTTRON provides an environment for buildings researchers to deploy applications interacting with building management systems...

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...

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...

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...

PNNL’s Vision Statement for Equity in the Power Grid Drawing from a wealth of interdisciplinary research in grid modernization, PNNL is spearheading an effort to advance equity and energy justice through the role of scientific research with the goal of building an advanced national power grid...

Earth Scientist Emily Graham is an quantitative ecosystem ecologist in the Biological Sciences Group at PNNL and is part of the Ecosystem Science Team. She is co-principal investigator of the Subsurface Biogeochemical Research Science Focus Area (SFA) and a key member of PNNL’s soil microbiome SFA...

The IONTOF TOF.SIMS 5 data source is a time-of-flight secondary ion mass spectrometer and powerful surface analysis tool used to investigate scientific questions in biological, environmental, and energy research. Among the most sensitive of surface analysis tools, it uses a high-vacuum technique...

This dataset contains time series data collected from devices and sensors in the PNNL Systems Engineering Building collected using the VOLTTRON platform. The data includes readings from HVAC, power, and lighting systems and was collected between March and July of 2018. This work was funded by the...

This dataset includes one baseline and three cybersecurity based scenarios utilizing the IEEE 9 Bus Model. This instantiation of the IEEE 9 model was built utilizing the OpalRT Simulator ePhasorsim module, with Bus 7 represented by hardware in the loop (HiL). The HiL was represented by two SEL351s...

This dataset includes the results of high-fidelity, hardware in the loop experimentation on simulated models of representative electric and natural gas distribution systems with real cyber attack test cases. Such datasets are extremely important not only in understanding the system behavior during...

ProxyTSPRD profiles are collected using NVIDIA Nsight Systems version 2020.3.2.6-87e152c and capture computational patterns from training deep learning-based time-series proxy-applications on four different levels: models (Long short-term Memory and Convolutional Neural Network), DL frameworks...

Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. Metatranscriptomic data from MSC-2. [Data Set] PNNL DataHub. https://data.pnnl.gov/group/nodes/dataset/33232 Metatranscriptomic data from MSC-2 12 fastq files (6 forward read, 6 reverse...