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At least 595 records · Page 33

The Genetic Architecture of Shoot and Root Trait Divergence Between Mesic and Xeric Ecotypes of a Perennial Grass

Environmental heterogeneity can drive patterns of functional trait variation and lead to the formation of locally adapted ecotypes. Plant ecotypes are often differentiated by suites of correlated root and shoot traits that share common genetic, developmental, and physiological relationships. For instance, although plant water loss is largely governed by shoot systems, root systems determine water access and constrain shoot water status. To evaluate the genetic basis of root and shoot trait divergence, we developed a recombinant inbred population derived from mesic and xeric ecotypes of the perennial grass Panicum hallii. Our study sheds light on the genetic architecture underlying the relationships between root and shoot traits. We identified several genomic “hotspots” which control suites of correlated root and shoot traits, thus indicating genetic coordination between plant organ systems in the process of ecotypic divergence. Genomic regions of colocalized quantitative trait locus (QTL) for the majority of shoot and root growth related traits were independent of colocalized QTL for shoot and root resource acquisition traits. The allelic effects of individual QTL underscore ecological specialization for drought adaptation between ecotypes and reveal possible hybrid breakdown through epistatic interactions. These results have implications for understanding the factors constraining or facilitating local adaptation in plants.

epistasis↗

Natural Language Processing for Extracting Rich Disease Data Aligned To Satellite Meteorological Data

Global climate change is redefining our understanding of how diseases spread. In Sri Lanka, vector-borne diseases such as dengue fever, encephalitis, and leptospirosis historically surged during the monsoon seasons when temperatures were high enough for mosquito eggs to hatch. Unfortunately, due to rising temperatures and more erratic rainfall patterns, mosquito eggs can now hatch year-round and are increasingly unpredictable, leading to an alarmingly increasing number of hospitalizations and deaths. More data is needed to adapt our response to these diseases in an increasingly warmer world. In the contemporary landscape, a wealth of disease information is available, yet accessibility remains limited due to unstructured data formats such as PDFs. Therefore, converting unstructured disease reports into structured formats is necessary for effectively leveraging data. This paper introduces a comprehensive framework for collecting unstructured disease reports and transforming them into analyzable formats. By creating separate models tailored to each data format, we can ensure accuracy compared to general models. These straightforward models enhance accessibility and empower other researchers to use our tools. The returned structured data can then be harnessed for analysis, statistical purposes, and informing evidence-based public health interventions, thus facilitating more informed decision-making in healthcare. We deploy this framework to produce geospatial data for Sri Lanka and Brazil for many different conditions and align these data with satellite environmental data, providing for the first time a structured, aligned powerful dataset for disease modeling.

Open Source Open Science↗

Parameter-free determination of the exchange constant in thin films using magnonic patterning

An all-electrical method is presented to determine the exchange constant of magnetic thin films using ferromagnetic resonance. For films of 20 nm thickness and below, the determination of the exchange constant A, a fundamental magnetic quantity, is anything but straightforward. Among others, the most common methods are based on the characterization of perpendicular standing spin-waves. These approaches are however challenging, due to (i) very high energies and (ii) rather small intensities in this thickness regime. In the presented approach, surface patterning is applied to a permalloy (Ni{sub 80}Fe{sub 20}) film and a Co{sub 2}Fe{sub 0.4}Mn{sub 0.6}Si Heusler compound. Acting as a magnonic crystal, such structures enable the coupling of backward volume spin-waves to the uniform mode. Subsequent ferromagnetic resonance measurements give access to the spin-wave spectra free of unquantifiable parameters and, thus, to the exchange constant A with high accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Techno-Economic Analysis of BEVs with Fast Charging Infrastructure: Preprint

Battery electric vehicles (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but high upfront costs, battery-limited vehicle range, and concern over high battery replacement costs may discourage many potential purchasers. One proposed solution is to employ a subscription model under which a service provider assumes ownership of the battery while providing access to vast fast charging infrastructure. Thus, high upfront and subsequent battery replacement costs are replaced by a predictable monthly fee, and battery-limited range is replaced by a larger infrastructure-limited range. Assessing the costs and benefits of such a proposal are complicated by many factors, including customer drive patterns, the amount of required infrastructure, and battery life. Herein the National Renewable Energy Laboratory applies its Battery Ownership Model to address these challenges and compare the economics and utility of a BEV fast charging service plan to a traditional direct ownership option. In single vehicle households, where such a service is most valuable, we find that operating a BEV under a fast charge service plan can be more cost-effective than direct ownership of a BEV, but it is rarely more cost-effective than direct ownership of a conventional vehicle.

25 ENERGY STORAGE↗

Using Formal Grammars to Predict I/O Behaviors in HPC: The Omnisc'IO Approach

The increasing gap between the computation performance of post-petascale machines and the performance of their I/O subsystem has motivated many I/O optimizations including prefetching, caching, and scheduling. In order to further improve these techniques, modeling and predicting spatial and temporal I/O patterns of HPC applications as they run has become crucial. In this paper we present Omnisc'IO, an approach that builds a grammar-based model of the I/O behavior of HPC applications and uses it to predict when future I/O operations will occur, and where and how much data will be accessed. To infer grammars, Omnisc'IO is based on StarSequitur, a novel algorithm extending Nevill-Manning's Sequitur algorithm. Omnisc'IO is transparently integrated into the POSIX and MPI I/O stacks and does not require any modification in applications or higher-level I/O libraries. It works without any prior knowledge of the application and converges to accurate predictions of any N future I/O operations within a couple of iterations. Its implementation is efficient in both computation time and memory footprint.

97 MATHEMATICS AND COMPUTING↗

Warm and Saline Events Embedded in the Meridional Circulation of the Northern North Atlantic

Ocean state estimates from 1958 to 2005 from the Simple Ocean Assimilation System (SODA) system are analyzed to understand circulation between subtropical and subpolar Atlantic and their connection with atmospheric forcing. This analysis shows three periods (1960s, around 1980, and 2000s) with enhanced warm, saline waters reaching high latitudes, alternating with freshwater events originating at high latitudes. It complements surface drifter and altimetry data showing the subtropical -subpolar exchange leading to a significant temperature and salinity increase in the northeast Atlantic after 2001. The warm water limb of the Atlantic meridional overturning cell represented by SODA expanded in density/salinity space during these warm events. Tracer simulations using SODA velocities also show decadal variation of the Gulf Stream waters reaching the subpolar gyre and Nordic seas. The negative phase of the North Atlantic Oscillation index, usually invoked in such variability, fails to predict the warming and salinization in the early 2000s, with salinities not seen since the 1960s. Wind stress curl variability provided a linkage to this subtropical/subpolar gyre exchange as illustrated using an idealized two ]layer circulation model. The ocean response to the modulation of the climatological wind stress curl pattern was found to be such that the northward penetration of subtropical tracers is enhanced when amplitude of the wind stress curl is weaker than normal. In this case both the subtropical and subpolar gyres weaken and the subpolar density surfaces relax; hence, the polar front moves westward, opening an enhanced northward access of the subtropical waters in the eastern boundary current.

Hakkinen, Sirpa↗

MBSE-Driven Visualization of Requirements Allocation and Traceability

In a Model Based Systems Engineering (MBSE) infusion effort, there is a usually a concerted effort to define the information architecture, ontologies, and patterns that drive the construction and architecture of MBSE models, but less attention is given to the logical follow-on of that effort: how to practically leverage the resulting semantic richness of a well-formed populated model to enable systems engineers to work more effectively, as MBSE promises. While ontologies and patterns are absolutely necessary, an MBSE effort must also design and provide practical demonstration of value (through human-understandable representations of model data that address stakeholder concerns) or it will not succeed. This paper will discuss opportunities that exist for visualization in making the richness of a well-formed model accessible to stakeholders, specifically stakeholders who rely on the model for their day-to-day work. This paper will discuss the value added by MBSE-driven visualizations in the context of a small case study of interactive visualizations created and used on NASA's proposed Europa Mission. The case study visualizations were created for the purpose of understanding and exploring targeted aspects of requirements flow, allocation, and comparing the structure of that flow-down to a conceptual project decomposition. The work presented in this paper is an example of a product that leverages the richness and formalisms of our knowledge representation while also responding to the quality attributes SEs care about.

Model Based Systems Engineering↗

MBSE-Driven Visualization of Requirements Allocation and Traceability

In a Model Based Systems Engineering (MBSE) infusion effort, there is a usually a concerted effort to define the information architecture, ontologies, and patterns that drive the construction and architecture of MBSE models, but less attention is given to the logical follow-on of that effort: how to practically leverage the resulting semantic richness of a well formed populated model to enable systems engineers to work more effectively, as MBSE promises. While ontologies and patterns are absolutely necessary, an MBSE effort must also design and provide practical demonstration of value (through human-understandable representations of model data that address stakeholder concerns) or it will not succeed. This paper will discuss opportunities that exist for visualization in making the richness of a well-formed model accessible to stakeholders, specifically stakeholders who rely on the model for their day-to-day work. This paper will discuss the value added by MBSE-driven visualizations in the context of a small case study of interactive visualizations created and used on NASA’s proposed Europa Mission. The case study visualizations were created for the purpose of understanding and exploring targeted aspects of requirements flow, allocation, and comparing the structure of that flow-down to a conceptual project decomposition. The work presented in this paper is an example of a product that leverages the richness and formalisms of our knowledge representation while also responding to the quality attributes SEs care about.

Model Based Systems Engineering↗

Northern Arabian Sea Circulation-Autonomous Research (NASCar): A Research Initiative Based on Autonomous Sensors

The Arabian Sea circulation is forced by strong monsoonal winds and is characterized by vigorous seasonally reversing currents, extreme differences in sea surface salinity, localized substantial upwelling, and widespread submesoscale thermohaline structures. Its complicated sea surface temperature patterns are important for the onset and evolution of the Asian monsoon. This article describes a program that aims to elucidate the role of upper-ocean processes and atmospheric feedbacks in setting the sea surface temperature properties of the region. The wide range of spatial and temporal scales and the difficulty of accessing much of the region with ships due to piracy motivated a novel approach based on state-of-the-art autonomous ocean sensors and platforms. The extensive data set that is being collected, combined with numerical models and remote sensing data, confirms the role of planetary waves in the reversal of the Somali Current system. These data also document the fast response of the upper equatorial ocean to monsoon winds through changes in temperature and salinity and the connectivity of the surface currents across the northern Indian Ocean. New observations of thermohaline interleaving structures and mixing in setting the surface temperature properties of the northern Arabian Sea are also discussed.

54 ENVIRONMENTAL SCIENCES↗

Direct photopatterning of robust and diverse materials

The present invention relates to methods of metathesizing olefins using catalysts previously considered to be practically inactive. The present invention further relates to novel photosensitive compositions, their use as photoresists, and methods related to patterning polymer layers on substrates. Further, modifications to the compositions and method provide for an unprecedented functionalization of the compositions, useful for example in the preparation of sensors, drug delivery systems, and tissue scaffolds. The novel compositions and associated methods also provide for the opportunity to prepare 3-dimensional objects which provide new access to critically dimensioned devices, including for example photonic devices.

36 MATERIALS SCIENCE↗

Data Release Report for the Source Physics Experiment Phase II: Dry Alluvium Geology Experiments (DAG-1 through DAG-4), Nevada National Security Site

The Dry Alluvium Geology (DAG) project was Phase II of the Source Physics Experiment and consisted of a series of four chemical explosive tests conducted in the same source hole on the Nevada National Security Site. This hole is located at 37.1146°N and -116.0693°W, with a surface elevation of 1,285.2 meters (m) (4,216.5 feet [ft]) above sea level. The first test (DAG-1) was conducted on July 20, 2018, at 16:51:52.67838 Coordinated Universal Time (UTC). The explosive source for DAG-1 was nitromethane initiated by a small plastic-bonded explosive (PBX) charge, detonated at the depth of 385.0 m (1,263.2 ft) below ground surface. DAG-1 had a trinitrotoluene (TNT) equivalent yield of 0.908 metric tons (2,002 pounds [lbs]). DAG-2 was conducted on December 19, 2018, at 18:45:56.92115 UTC. This test was the largest in the series, with a TNT equivalent yield of 50.997 metric tons (112,429 lbs). The explosive source for DAG-2 was nitromethane initiated by a small PBX charge, detonated at the depth of 299.8 m (983.6 ft) below ground surface. DAG-3 was conducted on April 27, 2019, at 15:49:01.84183 UTC. The explosive source for this test was nitromethane initiated by a small PBX charge, detonated at the depth of 149.9 m (492.0 ft) below ground surface. DAG-3 had a TNT equivalent yield of 0.908 metric tons (2,002 lbs). The final DAG test (DAG-4) was conducted on June 22, 2019, at 21:06:19.87632 UTC. The explosive source for DAG-4 was nitromethane initiated by a small PBX charge, detonated at the depth of 51.6 m (169.3 ft) below ground surface. DAG-4 had a TNT equivalent yield of 10.357 metric tons (22,833 lbs). The four tests were recorded by an extensive set of instrumentation that included sensors both at near-field (less than 200 m) and far-field (200 m or greater) distances. The near-field instruments consisted of three-component (3C) accelerometers installed at various depths ranging from 51.6 to 385 m (169.3 to 1,263.1 ft) below ground surface in boreholes positioned around the source hole, and arrays of single-component and 3C accelerometers on the surface. The far-field network comprised a variety of seismic and acoustic sensors, including short-period geophones, broadband seismometers, and 3C accelerometers at distances of 200 m to 400 kilometers. In addition, the DAG-2, DAG-3, and DAG-4 explosions were recorded by a temporary array of 496 geophones arranged in a densely spaced grid pattern known as “Large N.” This report coincides with the release of these data for analysts and organizations that are not participants in this program. This report describes the four DAG tests and the various types of near-field, far-field, and other data that are available. Assembled data sets are accessible through: Incorporated Research Institutions for Seismology, Data Management Center 1408 NE 45th Street, Suite 201, Seattle, Washington 98105 USA. www.iris.washington.edu

58 GEOSCIENCES↗

SU-E-T-419: Fabricating Cerrobend Grids with 3D Printing for Spatially Modulated Radiation Therapy: A Feasibility Study

Purpose: Grid therapy has promising applications in the radiation treatment of bulky and large tumors. However, research and applications of grid therapy is limited by the accessibility of the specialized blocks that produce the grid of pencil-like radiation beams. In this study, a Cerrobend grid block was fabricated using a 3D printing technique. Methods: A grid block mold was designed with divergent tubes following beam central rays. The mold was printed using a resin with the working temperature below 230 °C. The melted Cerrobend liquid at 120°oC was cast into the resin mold to yield a block with a thickness of 7.4 cm. The grid had a hexagonal pattern, with each pencil beam diameter of 1.4 cm at the iso-center plane; the distance between the beam centers was 2 cm. The dosimetric properties of the grid block were studied using radiographic film and small field dosimeters. Results: the grid block was fabricated to be mounted at the third accessory mount of a Siemens Oncor linear accelerator. Fabricating a grid block using 3D printing is similar to making cutouts for traditional radiotherapy photon blocks, with the difference being that the mold was created by a 3D printer rather than foam. In this study, the valley-to-peak ratio for a 6MV photon grid beam was 20% at dmax, and 30% at 10 cm depth, respectively. Conclusion: We have demonstrated a novel process for implementing grid radiotherapy using 3D printing techniques. Compared to existing approaches, our technique combines reduced cost, accessibility, and flexibility in customization with efficient delivery. This lays the groundwork for future studies to improve our understanding of the efficacy of grid therapy and apply it to improve cancer treatment.

60 APPLIED LIFE SCIENCES↗

A Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. In order to evaluate and quantify outcomes, we use the Mobility Energy Productivity (MEP) metric, a holistic tool to analyze, quantify, and compare the mobility and accessibility of various transportation modes in a specific area. In this paper, we apply the MEP tool to the ODT system in Arlington, Texas, and compare the results among four existing transportation modes (drive, transportation network company, transit, and bike) and five additional ODT scenarios. We focus our analysis on the opportunities that an ODT system presents such as serving disadvantages communities. While the results in Arlington show the typical U.S. pattern of driving receiving the highest MEP score, the ODT system best serves those in disadvantaged communities, helping with an equity design goal. ODT improved the average MEP score across the service area by 100% when considering only non-private vehicle modes (bike, transit, and ODT). For the ODT scenarios, decreasing the wait time 50% compared to the baseline scenario led to a nearly 160% increase in MEP score, while increasing the ODT travel speed by 21% led to an 80% improvement in MEP score. The decreased wait time scenario had the highest MEP score out of the six ODT scenarios. This paper demonstrates how ODT can enhance mobility, particularly for disadvantaged communities. The results of a MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems in subareas across a service area.

accessibility↗

Structured wafer for device processing

A structured wafer that includes through passages is used for device processing. Each of the through passages extends from or along one surface of the structured wafer and forms a pattern on a top surface area of the structured wafer. The top surface of the structured wafer is bonded to a device layer via a release layer. Devices are processed on the device layer, and are released from the structured wafer using etchant. The through passages within the structured wafer allow the etchant to access the release layer to thereby remove the release layer.

42 ENGINEERING↗

Structured wafer for device processing

A structured wafer that includes through passages is used for device processing. Each of the through passages extends from or along one surface of the structured wafer and forms a pattern on a top surface area of the structured wafer. The top surface of the structured wafer is bonded to a device layer via a release layer. Devices are processed on the device layer, and are released from the structured wafer using etchant. The through passages within the structured wafer allow the etchant to access the release layer to thereby remove the release layer.

36 MATERIALS SCIENCE↗

Glove-based sensors for multimodal monitoring of natural sweat

Sweat sensors targeting exercise or chemically induced sweat have shown promise for noninvasive health monitoring. Natural thermoregulatory sweat is an attractive alternative as it can be accessed during routine and sedentary activity without impeding user lifestyles and potentially preserves correlations between sweat and blood biomarkers. We present simple glove-based sensors to accumulate natural sweat with minimal evaporation, capitalizing on high sweat gland densities to collect hundreds of microliters in just 30 min without active sweat stimulation. Sensing electrodes are patterned on nitrile gloves and finger cots for in situ detection of diverse biomarkers, including electrolytes and xenobiotics, and multiple gloves or cots are worn in sequence to track overarching analyte dynamics. Direct integration of sensors into gloves represents a simple and low-overhead scheme for natural sweat analysis, enabling sweat-based physiological monitoring to become practical and routine without requiring highly complex or miniaturized components for analyte collection and signal transduction.

42 ENGINEERING↗

Investigations of a Combustor Using a 9-Point Swirl-Venturi Fuel Injector: Recent Experimental Results

This paper explores recent results obtained during testing in an optically-accessible, JP8-fueled, flame tube combustor using baseline Lean Direct Injection (LDI) research hardware. The baseline LDI geometry has nine fuel/air mixers arranged in a 3 x 3 array. Results from this nine-element array include images of fuel and OH speciation via Planar Laser-Induced Fluorescence (PLIF), which describe fuel spray pattern and reaction zones. Preliminary combustion temperatures derived from Stokes/Anti-Stokes Spontaneous Raman Spectroscopy are also presented. Other results using chemiluminescence from major combustion radicals such as CH* and C2* serve to identify the primary reaction zone, while OH PLIF shows the extent of reaction further downstream. Air and fuel velocities and fuel drop size results are also reported.

Hicks, Yolanda R.↗

Towards A Flexible Data Fusion Tool Incorporating Model, Satellite, Regulatory Monitor and Low-Cost Sensor Data for Air Quality Estimation and Forecasting

Air quality managers, researchers, and concerned community scientists around the world have a variety of sources for air quality information, ranging from traditional regulatory monitoring networks and atmospheric chemistry models to remote sensing data products and low-cost sensor networks. However, the ability to incorporate data from these disparate sources and synthesize a comprehensive overview of the local air quality situation remains a considerable barrier for many end-users. This presentation will outline a tool, currently in development, which will address this need using a flexible data fusion approach. The tool will make use of air quality forecast model outputs (primarily from the NASA GEOS-CF composition forecast modeling system), satellite remote sensing data (from instruments including MODIS, VIIRS, TROPOMI, plus TEMPO for the US when available), and in-situ data from official regulatory and/or low-cost networks where these are available. The ability to incorporate data from low-cost sensor networks will be a key feature of the tool; it will make use of other available data sources to calibrate the low-cost sensor data on a regional scale, then use these calibrated low-cost sensor data for localized updating to resolve finer-scale air quality patterns. Development of this tool is taking place with the help of national and international partners and end-user groups, coordinated through the US EPA and the United Nations Environment Programme (UNEP). The tool is being developed on the Google Earth Engine cloud computing platform to facilitate integration of diverse data sources and free access by a broad community of end-users. Stewardship of the tool will be passed to US EPA and UNEP to support future activities with end-users in the US and around the world, and the tool itself will remain freely accessible. We hope that this tool will lower the barrier to entry for various user groups worldwide, including community scientists, who struggle to integrate disparate data sources to gain insight into their local air quality situations. This presentation will cover the early stages of the development of the tool, including the underlying methods and some pilot case studies in integrating low-cost sensor data.

global models↗