The OGA tool: AI/ML enhanced integrated offshore hazard analysis
The Ocean & Geohazard Analysis (OGA) tool: AI/ML enhanced integrated offshore hazard analysis.
Bauer, Jennifer↗
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Facile Labeling of Sieve Element Phloem-Protein Bodies Using the Reciprocal Oligosaccharide Probe OGA488
Sieve elements of many angiosperms contain structural phloem proteins (P-proteins) that can interact to create large P-protein bodies. P-protein bodies can occlude sieve plates upon injury but the range of functional and physiological roles of P-proteins remains uncertain, in part because of challenges in labeling and visualization methods. Here, we show that a reciprocal oligosaccharide probe, OGA 488 , can be used in rapid and sensitive labeling of P-protein bodies in Arabidopsis, poplar, snap bean and cucumber in histological sections. OGA 488 labeling of knockouts of the two Arabidopsis P-protein-encoding genes, AtSEOR1 and AtSEOR2 , indicated that labeling is specific to AtSEOR2. That protein bodies were labeled and visible in Atseor1 knockouts indicates that heterodimerization of AtSEOR1 and AtSEOR2 may not be necessary for P-protein body formation. Double labeling with a previously characterized stain for P-proteins, sulphorhodamine 101, confirmed P-protein labeling and also higher specificity of OGA 488 for P-proteins. OGA 488 is thus robust and easily used to label P-proteins in histological sections of multiple angiosperm species.
59 BASIC BIOLOGICAL SCIENCES↗
Gulf of Mexico Risk Analysis Database (GoMRAD)
The Gulf of Mexico Risk Analysis Database is comprehensive Esri geodatabase of vector layers, raster layers, and tables curated for risk analysis within the offshore Gulf of Mexico. Datasets include bathymetry, seafloor characteristics (channels, anomalies, faults, etc.), MetOcean data (wind speed, wave height, etc.), ocean current data, sediment data, and machine learning training regions used in NETL's Ocean & Geohazard Analysis (OGA) tool. This database serves as a compliment to the OGA tool by providing many of the datasets used in the design of the OGA tool, including regions used for machine learning. This database also serves as a valuable resource for risk analysis studies within the offshore Gulf of Mexico. This work was completed under the Advanced Offshore Research Portfolio, FWP Number: 1022476.
BOEM,Bathymetry,Gulf Of Mexico,Machine Learning,Me↗
Eliminating Signal Bias Caused by Vacuum System Backstreaming in the Diagnostic Residual Gas Analyzer of ITER
In fusion neutral gas analysis, such as with the Diagnostic Residual Gas Analyzer (DRGA) for ITER, the primary measurement range of interest comprises the low-amu species (1 to 6), especially deuterium and helium. The challenge in successfully obtaining accurate measurements is two-fold. First, the sensitivity of the method must be sufficient to resolve trace amounts accurately; typically, one percent or less. Second, the gas signal from the fusion processes must be free of bias caused by the latent presence (from system outgassing and/or vacuum backstreaming) of these gases to enable accurate interpretation of the measured signal. This latter criterion can be problematic for the lightest gases since there is a propensity for some fraction of the pumped gas load to undergo a phenomenon known as backstreaming. This behavior is manifested in pumping systems for gas properties related to relative atomic weight (lightest) and size (smallest). Backstreaming results in a significant amount of the pumped gas undertaking a reverse flow and re-entering the measurement region; thus, contaminating the forward, real-time measurement. To fully eliminate this adverse effect, a conductance-limiting device – or orifice – has been installed in the high-vacuum pumping system of the present ITER DRGA prototype. The system was already equipped with a secondary turbomolecular pump (TMP), but with limited effectiveness against backstreaming in the inter-pump volume (IPV). This orifice is placed within the suction inlet coupling of the secondary TMP, which is downstream of the IPV. Its objective is to eliminate the backstreaming phenomenon by increasing the back pressure in the IPV. However, the orifice sizing must take into consideration other factors, such as the diagnostic measurement objectives. For example, in the ITER DRGA, one of the measurement requirements is a dynamic response time of ~1s. Fortunately, an added benefit of the pumping restriction created by the orifice is that the upstream pressure increase is beneficial for the DRGA’s optical gas analysis (OGA) sensors. These sensors are attached to the IPV in the present design. The glow discharges, when used as an OGA light source, will typically have a brighter light emission with increasing plasma cell pressure. In addition to the fusion machine research sector, there are other potential applications of this pumping technique where the monitoring of lighter gas concentrations is essential, such as the photolithography process for the semiconductor fabrication of integrated circuits. This presentation will describe the vacuum system used to demonstrate a process to eliminate backstreaming as well as show test results to verify the accomplishment of this critical objective.
Marcus, Chris↗
Ocean & Geohazard Analysis Tool
The Ocean & Geohazard Analysis (OGA) software tool is designed to summarize insights into key offshore hazards drawing from a diverse set of approaches, including artificial intelligence, machine learning, probabilistic and statistical, and offshore data sources. The offshore hazards that can be analyzed include submarine landslides, extreme wind/wave/current event probabilities, earthquakes, and metocean pathways (CIAM Climatological Isolation and Attraction Model–Climatological Lagrangian Coherent Structures - Submissions - EDX (doe.gov)). Currently, the tool is developed for use in the Gulf of Mexico. The data underlying the offshore hazard analyses can be found here: https://edx.netl.doe.gov/dataset/gulf-of-mexico-risk-analysis-database-gomrad This work was conducted under the Advanced Offshore Research Portfolio, FWP Number 1022409 at National Energy Technology Laboratory, U.S. Dept. of Energy. Disclaimer This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
AIML↗
A semidominant point mutation of Mediator tail subunit MED5b in Arabidopsis leads to altered enrichment of H3K27me3 and reduced expression of targets of MYC2
Abstract The Mediator complex coordinates regulatory input for transcription driven by RNA polymerase II in eukaryotes. reduced epidermal fluorescence4-3 (ref4-3) is a semidominant mutation that results in a single amino acid substitution in the Mediator tail subunit Med5b. Previous characterization of ref4-3 revealed altered expression of a variety of loci in Arabidopsis, including those contributing to phenylpropanoid biosynthesis. Examination of existing RNA-seq data indicated that loci enriched for the transcriptionally repressive chromatin modification H3K27me3 are overrepresented among genes that are misregulated in ref4-3. We used ChIP-seq and RNA-seq to examine the possibility that perturbation of H3K27me3 homeostasis in ref4-3 plants contributed to altered transcript levels. We observed that ref4-3 results in a modest global reduction of H3K27me3 at enriched loci and that this reduction is not dependent on gene expression; however, altered H3K27me3 was not strongly predictive of altered expression in ref4-3 plants. Instead, our analyses revealed a substantial enrichment of targets of the MYC2 transcriptional regulator among genes that exhibit decreased expression in ref4-3. Consistent with previous characterization of ref4-3, we observed that ref4-3-dependent decreased expression of MYC2 targets can be suppressed by loss of another Mediator tail subunit, MED25. This observation is consistent with previous biochemical characterization of MYC2. Our data highlight the diverse and distinct impacts that a single amino acid change in the tail subunit of Mediator can have on transcriptional circuits and raise the prospect that Mediator directly contributes to H3K27me3 homeostasis in plants.
Long, Jiaxin (ORCID:0000000335150706)↗
Potential for Combined Heat and Power with Carbon Capture and Storage at U.S. Ethanol Facilities
Conference paper presented at 17th International Conference on Greenhouse Gas Control Technologies (GHGT-17), Calgary, Alberta, Canada, October 20–24, 2024. Economic conditions in the United States have positioned ethanol producers as early adopters of industrial CO 2 capture and storage (CCS) from fermentation processes, creating an opportunity to further reduce emissions. Replacing fossil fired energy with biogenic combined heat and power (CHP) coupled with CCS could enable ethanol production to achieve net negative CO 2 emissions, with gasification based CHP better matching ethanol facilities’ heat and power needs than combustion based systems. Pilot scale testing showed that while 100% biomass gasification increased tar formation, cofeeding corn stover with coal and optimizing gasifier configurations offered promising pathways to reduce tar and improve operational performance.
09 BIOMASS FUELS↗
Charliecloud 101
This workshop will provide participants with background and hands-on experience to use basic containers for HPC applications. We will discuss what containers are, why they matter for HPC, and how they work. We’ll give an overview of Charliecloud, the unprivileged container solution from HPC Division, and walk participants through installing it on their own compute resource. Participants will build toy containers and a real HPC application, and then run them in parallel on an HPC Division cluster. This will be a highly interactive workshop with lots of Q&A.
97 MATHEMATICS AND COMPUTING↗
cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine
The domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases. In this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets. We test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas. The results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease.
60 APPLIED LIFE SCIENCES↗
Acceptance Testing the Chicoma HPE-Cray EX Supercomputer
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Computer Science↗