Domain-specific chatbots for science using embeddings
We demonstrate how large language models (LLMs) can be adapted to domain-specific science topics by connecting them to a corpus of trusted documents.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Evolution of bidirectional costly mutualism from byproduct consumption
Mutualisms are essential for life, yet it is unclear how they arise. A two-stage process has been proposed for the evolution of mutualisms that involve exchanges of two costly resources. First, costly provisioning by one species may be selected for if that species gains a benefit from costless byproducts generated by a second species, and cooperators get disproportionate access to byproducts. Selection could then drive the second species to provide costly resources in return. Previously, a synthetic consortium evolved the first stage of this scenario: Salmonella enterica evolved costly production of methionine in exchange for costless carbon byproducts generated by an auxotrophic Escherichia coli . Growth on agar plates localized the benefits of cooperation around methionine-secreting S. enterica . Here, we report that further evolution of these partners on plates led to hypercooperative E. coli that secrete the sugar galactose. Sugar secretion arose repeatedly across replicate communities and is costly to E. coli producers, but enhances the growth of S. enterica . The tradeoff between individual costs and group benefits led to maintenance of both cooperative and efficient E. coli genotypes in this spatially structured environment. This study provides an experimental example of de novo, bidirectional costly mutualism evolving from byproduct consumption. The results validate the plausibility of costly cooperation emerging from initially costless exchange, a scenario widely used to explain the origin of the mutualistic species interactions that are central to life on Earth.
59 BASIC BIOLOGICAL SCIENCES↗
INJECTION OF PLASMA INTO THE NASCENT SOLAR WIND VIA RECONNECTION DRIVEN BY SUPERGRANULAR ADVECTION
To understand the origin of the solar wind is one of the key research topics in modern solar and heliospheric physics. Previous solar wind models assumed that plasma flows outward along a steady magnetic flux tube that reaches continuously from the photosphere through the chromosphere into the corona. Inspired by more recent comprehensive observations, Tu et al. suggested a new scenario for the origin of the solar wind, in which it flows out in a magnetically open coronal funnel and mass is provided to the funnel by small-scale side loops. Thus mass is supplied by means of magnetic reconnection that is driven by supergranular convection. To validate this scenario and simulate the processes involved, a 2.5 dimensional (2.5D) numerical MHD model is established in the present paper. In our simulation a closed loop moves toward an open funnel, which has opposite polarity and is located at the edge of a supergranulation cell, and magnetic reconnection is triggered and continues while gradually opening up one half of the closed loop. Its other half connects with the root of the open funnel and forms a new closed loop which is submerged by a reconnection plasma stream flowing downward. Thus we find that the outflowing plasma in the newly reconnected funnel originates not only from the upward reconnection flow but also from the high-pressure leg of the originally closed loop. This implies an efficient supply of mass from the dense loop to the dilute funnel. The mass flux of the outflow released from the funnel considered in our study is calculated to be appropriate for providing the mass flux at the coronal base of the solar wind, though additional heating and acceleration mechanisms are necessary to keep the velocity at the higher location. Our numerical model demonstrates that in the funnel the mass for the solar wind may be supplied from adjacent closed loops via magnetic reconnection as well as directly from the footpoints of open funnels.
79 ASTRONOMY AND ASTROPHYSICS↗
BioADAPT-MRC: adversarial learning-based domain adaptation improves biomedical machine reading comprehension task
ABSTRACT Motivation Biomedical machine reading comprehension (biomedical-MRC) aims to comprehend complex biomedical narratives and assist healthcare professionals in retrieving information from them. The high performance of modern neural network-based MRC systems depends on high-quality, large-scale, human-annotated training datasets. In the biomedical domain, a crucial challenge in creating such datasets is the requirement for domain knowledge, inducing the scarcity of labeled data and the need for transfer learning from the labeled general-purpose (source) domain to the biomedical (target) domain. However, there is a discrepancy in marginal distributions between the general-purpose and biomedical domains due to the variances in topics. Therefore, direct-transferring of learned representations from a model trained on a general-purpose domain to the biomedical domain can hurt the model’s performance. Results We present an adversarial learning-based domain adaptation framework for the biomedical machine reading comprehension task (BioADAPT-MRC), a neural network-based method to address the discrepancies in the marginal distributions between the general and biomedical domain datasets. BioADAPT-MRC relaxes the need for generating pseudo labels for training a well-performing biomedical-MRC model. We extensively evaluate the performance of BioADAPT-MRC by comparing it with the best existing methods on three widely used benchmark biomedical-MRC datasets—BioASQ-7b, BioASQ-8b and BioASQ-9b. Our results suggest that without using any synthetic or human-annotated data from the biomedical domain, BioADAPT-MRC can achieve state-of-the-art performance on these datasets. Availability and implementation BioADAPT-MRC is freely available as an open-source project at https://github.com/mmahbub/BioADAPT-MRC. Supplementary information Supplementary data are available at Bioinformatics online.
60 APPLIED LIFE SCIENCES↗
Methods for Determining Likelihood of Tweet Deletion
Few works exist that attempt to build predictive models for tweet deletion. Zhou et al. (2015) focus on a subset of deleted tweets – regrettable tweets. These are tweets that the authors believe to contain inappropriate content. Inappropriate can range from vulgar language to sharing private content such as a personal email address. The presence of inappropriate content doesn’t guarantee that a tweet will be deleted, however intuition dictates it can be in an important factor in the tweet being deleted. In their work, the authors create a predictive model for identifying regrettable tweets. It is important to note the authors focus on predicting regrettable tweets that are distinctly not spam and only written in English. Through manual investigation, the authors identify ten major topics including negative sentiment, cursing, and relationships that are prevalent in regrettable tweets. The authors then exploit WordNet and UrbanDictionary to create keyword lists related to the ten topics. Finally, using a combination of existing lexica and the topic keywords as features, the authors build classifiers to test the accuracy of their model. The authors complement 700 manually labeled regrettable tweets with 700 normal tweets to create their evaluation dataset. The authors’ best performance from 10-fold cross-validation was an f1 score of 0.85 using a J48 classifier on a balanced dataset of deleted and non-deleted tweets.
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Latent Dirichlet Allocation modeling of environmental microbiomes
Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given sample, which makes untangling the interaction between an organism and its microbial environment a challenge. Here we apply Latent Dirichlet Allocation (LDA), a technique for language modeling, which decomposes the microbial communities into a set of topics (non-mutually-exclusive sub-communities) that compactly represent the distribution of full communities. LDA provides a lens into the microbiome at broad and fine-grained taxonomic levels, which we show on two datasets. In the first dataset, from the literature, we show how LDA topics succinctly recapitulate many results from a previous study on diseased coral species. We then apply LDA to a new dataset of maize soil microbiomes under drought, and find a large number of significant associations between the microbiome topics and plant traits as well as associations between the microbiome and the experimental factors, e.g. watering level. This yields new information on the plant-microbial interactions in maize and shows that LDA technique is useful for studying the coupling between microbiomes and stressed organisms.
59 BASIC BIOLOGICAL SCIENCES↗
Diffusion of Innovations: Interplay of Social, Economic, Technological, and Policy Drivers in the Solar Industry. Summary of UT Austin Student Capstone Research Projects
The University of Texas at Austin’s Policy Research Project (PRP), a nine-month (two semesters) capstone, is a keystone of the core curriculum at the LBJ School of Public Affairs. In PRPs, small groups of students, under the mentorship of a faculty director, take on real-world problems that require special knowledge and skill sets. PRPs expose students to challenges in formulating and executing research, and in communicating academic research and related complex data to broader stakeholder communities and decision makers. The PRP structure is an innovative and effective approach for integrating research within the teaching and training of graduate students who are preparing themselves to address important real-world problems at the intersection of society, economics, technology, and policy. The project summaries below describe seven papers developed during September 2017 – May 2018 as part of a PRP on “Diffusion of Innovations: Interplay of Social, Economic, Technological, and Policy Drivers in the Solar Industry.” Twenty graduate students, drawn from the LBJ School’s Masters in Public Affairs and Masters in Global Policy Studies programs and the Jackson School Geoscience’s Energy and Earth Resources program, participated in this PRP. Dr. Varun Rai, Associate Professor and Associate Dean for Research at the LBJ School, directed the PRP, with support from his research team including: Dr. Ariane Beck, Dr. Ashok Sekar, D. Cale Reeves, and Erik Funkhouser. Clients for the project included the U.S. Department of Energy (Casey Canfield), Lawrence Berkeley National Laboratory (Ben Hoen, Galen Barbose Joachim Seel, Naïm Darghouth, Ryan Wiser), and National Renewable Energy Laboratory (Benjamin Sigrin, Eric O’Shaughnessy). The seven projects separately addressed one of the following topics: (1) low- and middle-income PV adoption, (2) modeling economic and information intervention design, (3) evaluation of DOE’s Solar in Your Community Challenge, (4) property value impacts near large-scale solar facilities, (5) solar market maturity and evolution of business models, (6) social media data for predicting PV adoption, and (7) individual-level variation in adoption of innovations. Many of the papers relied on data collected and curated by Lawrence Berkeley National Laboratory, including data embedded within the annual Tracking the Sun and Utility-Scale Solar reports. Each of the seven teams in the PRP prepared a research paper. The PRP culminated with a full-day conference at UT Austin in May 2018 to present findings from the seven projects in this PRP to a broad audience of about 75 experts from academia, national labs, industry, and government from across the country.
14 SOLAR ENERGY↗
Wind Turbine Optimization with WISDEM
This presentation for the Fourth Wind Energy Systems Engineering Workshop explains the NREL wind energy systems engineering initiative-developed analysis platform and research capability to capture important system interactions to achieve a better understanding of how to improve system-level performance and achieve system-level cost reductions. Topics include Wind-Plant Integrated System Design and Engineering Model (WISDEM) and multidisciplinary design analysis and optimization.
17 WIND ENERGY↗
Low-Temperature Oxidation of Methanol to Formaldehyde on a Model Single-Atom Catalyst: Pd Atoms on Fe 3 O 4 (001)
Single atom catalysis has been a topic of increasing interest due to the potential for improved selectivity, reactivity, and catalyst cost. However, single atom catalysts are still difficult to characterize under realistic reaction conditions, leading to controversy regarding the capabilities of single atoms and a need for model studies. Herein, we examine the reaction of methanol on single Pd atoms supported on Fe 3 O 4 (001) under ultra-high vacuum conditions. On clean Fe 3 O 4 (001) a small fraction of methanol is converted to formaldehyde through a methoxy intermediate at 516 K. The addition of single Pd atoms lowers the barrier to C-H bond cleavage by a factor of two, resulting in formaldehyde desorption by 290 K. Furthermore, Pd atoms sinter by 300 K in the presence of methanol, and Pd clusters do not exhibit the same chemistry. Single atom sites significantly lower the barrier to the oxidation of methanol, although their stability remains an issue.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Health impact assessment – A survey on quantifying tools
Integrating human health into prospective impact assessments is known to be challenging. This is true for both approaches: dedicated health impact assessments (HIA) as well as inclusion of health into more general impact assessments. Acknowledging the full range of participatory, qualitative, and quantitative approaches, this study focuses on the latter, especially on computational tools for quantitative health modelling. We conducted a survey among tool developers concerning the status quo of development and availability of such tools; experiences made with model usage in real-life situations; and priorities for further development. Responding toolmaker groups described 17 such tools, most of them being maintained and reported as ready for use and covering a wide range of topics, including risk & protective factors, exposures, policies, and health outcomes. In recent years, existing models have been improved and were applied in new ways, and completely new models emerged. There was high agreement among respondents on the need to further develop methods for assessment of inequalities and uncertainty. The contribution of quantitative modeling to health foresight would benefit from building joint strategies of further tool development, improving the visibility of quantitative tools and methods, and engaging continuously with actual and potential users. - Highlights: • A survey investigated computational tools for health impact quantification. • Formal evaluation of such tools has been rare. • Handling inequalities and uncertainties are priority areas for further development. • Health foresight would benefit from tool developers and users forming a community. • Joint development strategies across computational tools are needed.
54 ENVIRONMENTAL SCIENCES↗
cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures
Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.
20 FOSSIL-FUELED POWER PLANTS↗
Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks
The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Challenges and opportunities of machine learning control in building operations
Machine learning control (MLC) is a highly flexible and adaptable method that enables the design, modeling, tuning, and maintenance of building controllers to be more accurate, automated, flexible, and adaptable. The research topic of MLC in building energy systems is developing rapidly, but to our knowledge, no review has been published that specifically and systematically focuses on MLC for building energy systems. Here this paper provides a systematic review of MLC in building energy systems. We review technical papers in two major categories of applications of machine learning in building control: (1) building system and component modeling for control, and (2) control process learning. We identify MLC topics that have been well-studied and those that need further research in the field of building operation control. We also identify the gaps between the present and future application of MLC and predict future trends and opportunities.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Solar System Modeling at NREL
This workshop walked through a description and demonstration of solar modeling data and tools available from the US National Renewable Energy Laboratory (NREL). The topics included: The National Solar Radiation Database (NSRDB) - updates and ways to access this sub-hourly gridded resource data; PVWatts - recent updates to include the NSRDB - opening up much of North and South America for analysis; System Advisor Model (SAM) - SAM is now open source, includes PV + batteries, bifacial panels, and much more; REOpt Lite - an online tool for quick PV and battery sizing for commercial buildings; PV Component LCOE Calculator - Allows for module costing based on components; A detailed demonstration of the SAM model for modeling a PV system with a battery and some of the questions that can be answered.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Natural Systems Data Package for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington
This document summarizes the available information regarding the natural system (vadose zone and saturated zone) at the active trenches of the 200 West Area and 200 East Area Low-Level Burial Grounds (LLBGs). This information is relevant for developing the natural system fate and transport model for the update of the active trenches performance assessment. This document presents a description of the major features, events, and processes of the natural system at the active trenches of the 200 West Area and 200 East Area LLBGs that involves the geologic features or framework, and the vadose zone and groundwater flow and transport system. The description of the geologic features includes the following items: geologic setting, major structural features, major hydrostratigraphic units, and geologic framework. The discussion concerning vadose zone flow and transport at the active trenches of the 200 West Area and 200 East Area LLBGs includes the following topics: vadose zone features, events, and processes relevant to the development of the vadose zone conceptual model; hydrogeologic units and conditions; factors affecting moisture movement; and flow and transport properties of major units. The discussion concerning the groundwater flow and transport system in the vicinity of the active trenches of the 200 West Area and 200 East Area LLBGs includes the following topics: saturated zone features, events, and processes relevant to the saturated zone conceptual model; hydrogeologic units; groundwater flow conditions; and flow and transport properties.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Partial Support for the Federal Committee for Meteorological Services and Supporting Research (Final Report)
The OFCM sponsored a session within the 16th annual George Mason University Atmospheric Transport and Diffusion Modeling Conference. The theme of the session was Identifying the Research Needs and Current/Planned Research Projects within the Operational and Research Planetary Boundary Layer Interagency Community. Subject matter experts (SME) from the NWS, U.S. Department of Energy, and the National Center for Atmospheric Research participated in the session’s panel discussion. The OFCM-sponsored special session SMEs identified the following areas as operational and research priorities/requirements: Transitioning from planetary boundary layer (PBL) schemes to large-scale eddy simulation; Separating out waves from turbulence and understanding when and how to simulate internal waves degenerating into turbulence; Treating stable boundary layers and unstable boundary layers as separate entities; Increasing the capacity to observe heterogenous boundary layers and to use these observations to improve data assimilation; Dealing with terrain (in all its variations) in a more appropriate way; Conducting a coordinated, joint field program to address the priorities/requirements listed above. The Federal Coordinator brought the results of the successful forum to the attention of the broader interagency PBL community with the goal of eliciting from that community how best to proceed in meeting the operational and research requirements articulated at the special session. On December 16, 2011, the Federal Coordinator also convened a meeting of the Interdepartmental Committee for Meteorological Services and Supporting Research (ICMSSR), a committee with members from 12 federal agencies, including DOE. One of the topics addressed at the meeting was the status of coupling ATD models and the impact across the federal meteorological community. A status report was provided to all ICMSSR members.
54 ENVIRONMENTAL SCIENCES↗
Enabling Land-Use in E3SM Land Model (Final Report)
Human activity has significantly altered basic element cycles (e.g. of carbon and nitrogen), the water cycle, and the land surface (e.g. vegetation cover, albedo) at regional, continental, and planetary scales, and these alterations are influencing the regional and global environment, including the Earth’s climate system. The overall goal of this contribution to ACME/E3SM was to improve the coupling between models of land-use/land cover change. In particular, our effort was focused to enable ACME/E3SM v1 to use of the newest historical land use forcing data available, LUH2. The second-generation historical land-use harmonization dataset (LUH2, a separate but synergistic activity also lead by G. Hurtt, and supported by a DOE-SciDAC award) is now an entry card for participating in WCRP/CMIP6. Progress was made on all three of the proposed activities i.e. algorithm development, code development and testing, and model experiments to quantify improvements. Results have been disseminated via science team workgroups, telecons, meetings, Jira/Confluence, scientific meetings, and more broadly in related publications. This award has enabled novel science advancing the frontier on the topic of land-use change and climate. The innovative and synergistic scientific advances on modeling (this project) and data (DOE- SciDAC) is one of a kind and world leading.
54 ENVIRONMENTAL SCIENCES↗
Science Drivers and Proposed Modeling Approaches for Future LASSO Scenarios
The United States Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility held a workshop on May 2, 2019 to gather information on different weather scenarios that could be pursued for expanding the range of atmospheric processes that could be studied by the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) data product. To date, LASSO has focused on the use of LES modeling to supplement ARM’s suite of observations at the Southern Great Plains (SGP) atmospheric observatory for days that have shallow convective clouds. Input for the workshop was obtained from the community in the form of white papers that outlined additional meteorological phenomena that LASSO could pursue. Four white papers were submitted covering a wide range of phenomena of scientific interest to the DOE atmospheric modeling community and across the ARM spectrum of observation sites: maritime clouds, deep convection, clear-air turbulence, and arctic clouds. Topic experts were invited to the workshop to discuss each scenario in terms of the science drivers, feasibility of implementation (e.g., model configuration and needed observations), timing considerations, and any open issues related to the scenario that would need further investigation.
54 ENVIRONMENTAL SCIENCES↗