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At least 91 records · Page 5

GPS/Optical/Inertial Integration for 3D Navigation Using Multi-Copter Platforms

In concert with the continued advancement of a UAS traffic management system (UTM), the proposed uses of autonomous unmanned aerial systems (UAS) have become more prevalent in both the public and private sectors. To facilitate this anticipated growth, a reliable three-dimensional (3D) positioning, navigation, and mapping (PNM) capability will be required to enable operation of these platforms in challenging environments where global navigation satellite systems (GNSS) may not be available continuously. Especially, when the platform's mission requires maneuvering through different and difficult environments like outdoor opensky, outdoor under foliage, outdoor-urban and indoor, and may include transitions between these environments. There may not be a single method to solve the PNM problem for all environments. The research presented in this paper is a subset of a broader research effort, described in [1]. The research is focused on combining data from dissimilar sensor technologies to create an integrated navigation and mapping method that can enable reliable operation in both an outdoor and structured indoor environment. The integrated navigation and mapping design is utilizes a Global Positioning System (GPS) receiver, an Inertial Measurement Unit (IMU), a monocular digital camera, and three short to medium range laser scanners. This paper describes specifically the techniques necessary to effectively integrate the monocular camera data within the established mechanization. To evaluate the developed algorithms a hexacopter was built, equipped with the discussed sensors, and both hand-carried and flown through representative environments. This paper highlights the effect that the monocular camera has on the aforementioned sensor integration scheme's reliability, accuracy and availability.

Dill, Evan T.↗

Missing data in multi-omics integration: Recent advances through artificial intelligence

Biological systems function through complex interactions between various ‘omics (biomolecules), and a more complete understanding of these systems is only possible through an integrated, multi-omic perspective. This has presented the need for the development of integration approaches that are able to capture the complex, often non-linear, interactions that define these biological systems and are adapted to the challenges of combining the heterogenous data across ‘omic views. A principal challenge to multi-omic integration is missing data because all biomolecules are not measured in all samples. Due to either cost, instrument sensitivity, or other experimental factors, data for a biological sample may be missing for one or more ‘omic techologies. Recent methodological developments in artificial intelligence and statistical learning have greatly facilitated the analyses of multi-omics data, however many of these techniques assume access to completely observed data. A subset of these methods incorporate mechanisms for handling partially observed samples, and these methods are the focus of this review. We describe recently developed approaches, noting their primary use cases and highlighting each method's approach to handling missing data. We additionally provide an overview of the more traditional missing data workflows and their limitations; and we discuss potential avenues for further developments as well as how the missing data issue and its current solutions may generalize beyond the multi-omics context.

97 MATHEMATICS AND COMPUTING↗

Considerations for Distributed Edge Data Centers and Use of Building Loads to Support Large Interconnections

The rapid expansion of artificial intelligence (AI) and machine learning is driving unprecedented electricity demand from data centers. It is predicted that by 2030, 90% of AI workloads will be inference-based, requiring interconnection of multiple low-latency edge data centers (<20 MW) sited closer to end users - often on already constrained distribution feeders. Although individually small, these loads can aggregate to large loads per feeder, straining infrastructure, creating multi-year interconnection delays, and driving up customer costs. This paper proposes a data center-focused grid-integration framework that combines feeder hosting capacity analysis with building energy efficiency, building load flexibility, and waste heat reuse to expand effective feeder and substation headroom. Such approaches can reduce interconnection delays, lower costs for ratepayers, and accelerate AI-ready infrastructure deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Data base systems in electronic design engineering

The concepts of an integrated design data base system (DBMS) as it might apply to an electronic design company are discussed. Data elements of documentation, project specifications, project tracking, firmware, software, electronic and mechanical design can be integrated and managed through a single DBMS. Combining the attributes of a DBMS data handler with specialized systems and functional data can provide users with maximum flexibility, reduced redundancy, and increased overall systems performance. Although some system overhead is lost due to redundancy in transitory data, it is believed the combination of the two data types is advisable rather than trying to do all data handling through a single DBMS.

Williams, D.↗

Integration of AIRSAR and AVIRIS data for Trail Canyon alluvial fan, Death Valley, California

Combining quantitative geophysical information extracted from the optical and microwave wavelengths provides complementary information about both the surface mineralogy and morphology. This study combines inversion results from two remote sensing instruments, a polarimetric synthetic aperture radar, AIRSAR, and an imaging spectrometer, AVIRIS, for Trail Canyon alluvial fan in Death Valley, California. The NASA/JPL Airborne Synthetic Aperture Radar (AIRSAR) is a quad-polarization, three frequency instrument. AIRSAR collects data at C-band = 5.66 cm, L-band = 23.98 cm, and P-band = 68.13 cm. The data are processed to four-looks and have a spatial resolution of 10 m and a swath width of 12 km. The AIRSAR data used in this study were collected as part of the Geologic Remote Sensing Field Experiment (GRSFE) over Death Valley on 9/14/89. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is a NASA/JPL instrument that flies in an ER-2 aircraft at an altitude of 20 km. AVIRIS uses four spectrometers to collect data in 224 spectral channels from 0.4 micrometer to 2.45 micrometer. The width of each spectral band is approximately 10 nm. AVIRIS collects data with a swath width of 11 km and a pixel size of 20 m. The AVIRIS data used in this study were collected over Death Valley on 5/31/92.

Kierein-Young, Kathryn S.↗

NETMARK: A Schema-less Extension for Relational Databases for Managing Semi-structured Data Dynamically

Object-Relational database management system is an integrated hybrid cooperative approach to combine the best practices of both the relational model utilizing SQL queries and the object-oriented, semantic paradigm for supporting complex data creation. In this paper, a highly scalable, information on demand database framework, called NETMARK, is introduced. NETMARK takes advantages of the Oracle 8i object-relational database using physical addresses data types for very efficient keyword search of records spanning across both context and content. NETMARK was originally developed in early 2000 as a research and development prototype to solve the vast amounts of unstructured and semi-structured documents existing within NASA enterprises. Today, NETMARK is a flexible, high-throughput open database framework for managing, storing, and searching unstructured or semi-structured arbitrary hierarchal models, such as XML and HTML.

Maluf, David A.↗

Search for the Higgs boson decays to a ρ 0 , ϕ, or K ⁎0 meson and a photon in proton-proton collisions at $\sqrt{s} = 13$ TeV

Three rare decay processes of the Higgs boson to a ρ(770) 0 , Φ(1020), or K ⁎ (892) 0 meson and a photon are searched for using $\sqrt{s} = 13$ TeV proton-proton collision data collected by the CMS experiment at the LHC. Events are selected assuming the mesons decay into a pair of charged pions, a pair of charged kaons, or a charged kaon and pion, respectively. Depending on the Higgs boson production mode, different triggering and reconstruction techniques are adopted. The analyzed data sets correspond to integrated luminosities up to 138 fb -1 , depending on the reconstructed final state. After combining various data sets and categories, no significant excess above the background expectations is observed. Upper limits at 95% confidence level on the Higgs boson branching fractions into ρ(770) 0 $γ$, Φ(1020)$γ$, and K ⁎ (892) 0 are determined to be 3.7 x 10 -4 , 3.0 x 10 -4 , and 3.0 x 10 -4 , respectively. In case of the ρ(770) 0 $γ$ and Φ(1020)$γ$ channels, these are the most stringent experimental limits to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modular Autonomous Experimentation for Biological Applications (Full Report)

The Modular Autonomous Research System (MARS) was developed to address the pressing need for faster, more reliable, and more adaptable scientific discovery. Traditional experimentation is limited by manual labor, long cycle times, and fragmented data streams, which constrain the ability to explore complex chemical and materials design spaces. To overcome these limitations, we created an integrated, modular platform that combines laboratory robotics, diverse measurement instruments, and a central data infrastructure with artificial intelligence–driven decision-making. The system links liquid handling robots, robotic arms, and optical plate readers into a closed loop where experiments are executed automatically, data is analyzed in real time, and subsequent experimental conditions are adaptively chosen to maximize information gain. Over the course of the project, MARS was validated on two primary test cases—spectroscopic metal–ligand binding assays and peptide-directed mineralization—which highlighted the system’s ability to handle uncertainty and variability in experimental measurements. To further demonstrate modularity and extensibility, we also established additional testbeds in electrochemistry for catalyst discovery and electrolyte formulation for advanced batteries. The results show that MARS can reliably conduct autonomous campaigns with minimal human intervention, adapt to distinct scientific domains, and provide a scalable model for future self-driving laboratories. This work establishes new capabilities for modular, uncertainty-aware automation and directly supports the need for advanced, data-driven research platforms capable of accelerating discovery across a wide range of scientific and national security missions.

59 BASIC BIOLOGICAL SCIENCES↗

JPL's Foundry Furnace: Web-Based Concurrent Engineering for Formulation

The Jet Propulsion Laboratory’s Innovation Foundry is an enterprise tasked with shepherding space mission concepts through the formulation lifecycle. It oversees a number of “virtual teams” for the various stages of formulation. Among these is Team X, which has had considerable success over its more than 20-year history. In a Team X study, domain experts (including engineers devoted to the various spacecraft subsystems) work concurrently and collaboratively over several days to arrive at a feasible point design with a reasonable cost estimate. They use a set of linked Excel workbooks, each developed and approved by a responsible “line organization” within JPL. This toolset has served Team X well over the years, and has evolved since its inception. At the same time, the Innovation Foundry’s portfolio of formulation teams has expanded, and so has the scope of the design challenges they face. The A-Team runs workshop-like architecture studies to focus science investigations, generate mission concepts, assess feasibility, and explore trade spaces. Team Xc performs rapid point design in the style of Team X, but for CubeSats and small spacecraft, using a different toolset. Proposal teams further mature concepts to the point where they can be proposed. Recognizing the importance of trade space modeling combined with new IT services for providing and integrating data, JPL is developing the Foundry Furnace web-based software infrastructure. It will support A-Team, Team Xc, and Team X, providing study management, a catalog of hardware components, a library of re-usable analyses, and a design environment. It is a modernization of JPL’s concurrent engineering infrastructure, embracing the core concepts of Model-Based Systems Engineering, and built with modern software design philosophies.

Murphy, Jonathan↗

Knowledge Network Embedding of Transcriptomic Data From Spaceflown Mice Uncovers Signs and Symptoms Associated With Terrestrial Diseases

There has long been an interest in understanding how the hazards from spaceflight may trigger or exacerbate human diseases. With the goal of advancing our knowledge on physiological changes during space travel, NASA GeneLab provides an open-source repository of multi-omics data from real and simulated spaceflight studies. Alone, this data enables identification of biological changes during spaceflight, but cannot infer how that may impact an astronaut at the phenotypic level. To bridge this gap, SPOKE, a heterogeneous knowledge graph connecting biological and clinical data from over 30 databases, was used in combination with GeneLab transcriptomic data from six studies. This integration identified critical symptoms and physiological changes incurred during spaceflight.

spaceflight↗

Molecular architecture and functional dynamics of the pre-incision complex in nucleotide excision repair

Nucleotide excision repair (NER) is vital for genome integrity. Yet, our understanding of the complex NER protein machinery remains incomplete. Combining cryo-EM and XL-MS data with AlphaFold2 predictions, we build an integrative model of the NER pre-incision complex(PInC). Here TFIIH serves as a molecular ruler, defining the DNA bubble size and precisely positioning the XPG and XPF nucleases for incision. Using simulations and graph theoretical analyses, we unveil PInC’s assembly, global motions, and partitioning into dynamic communities. Remarkably, XPG caps XPD’s DNA-binding groove and bridges both junctions of the DNA bubble, suggesting a novel coordination mechanism of PInC’s dual incision. XPA rigging interlaces XPF/ERCC1 with RPA, XPD, XPB, and 5' ssDNA, exposing XPA’s crucial role in licensing the XPF/ERCC1 incision. Mapping disease mutations onto our models reveals clustering into distinct mechanistic classes, elucidating xeroderma pigmentosum and Cockayne syndrome disease etiology.

60 APPLIED LIFE SCIENCES↗

The case for data science in experimental chemistry: examples and recommendations

The physical sciences community is increasingly taking advantage of the possibilities offered by modern data science to solve problems in experimental chemistry and potentially to change the way we design, conduct and understand results from experiments. Successfully exploiting these opportunities involves considerable challenges. In this Expert Recommendation, we focus on experimental co-design and its importance to experimental chemistry. We provide examples of how data science is changing the way we conduct experiments, and we outline opportunities for further integration of data science and experimental chemistry to advance these fields. Our recommendations include establishing stronger links between chemists and data scientists; developing chemistry-specific data science methods; integrating algorithms, software and hardware to ‘co-design’ chemistry experiments from inception; and combining diverse and disparate data sources into a data network for chemistry research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the impact of nuclear-data covariances on various integral responses using adjustment

The EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project created a library of sensitivities for nine different integral responses with respect to nuclear data. These integral responses were obtained from measurements at LLNL (Lawrence Livermore National Laboratory) pulsed spheres, critical and sub-critical assemblies. At the same time, covariances for ENDF/B-VIII.0 were processed at LANL (Los Alamos National Laboratory). The combination of these data allow us to study the impact of nuclear-data covariances on various integral responses, either by forward-propagating covariances via sensitivities, or by using nuclear data, integral responses, and sensitivities for adjustment. Here, we will present: the impact of 1 H, 9 Be, 12 C, 27 Al, 56 Fe, 235,238 U, and 239,240 Pu ENDF/B-VIII.0 covariances on simulated bounds of the following integral responses: LLNL pulsed-spheres neutron-leakage spectra, the effective neutron multiplication factor, reaction rates, and reactivity coefficients of ICSBEP critical assemblies. Also, adjustment results with the same nuclear-data covariances and responses will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Land cover/use classification of Cairns, Queensland, Australia: A remote sensing study involving the conjunctive use of the airborne imaging spectrometer, the large format camera and the thematic mapper simulator

In an attempt to improve the land cover/use classification accuracy obtainable from remotely sensed multispectral imagery, Airborne Imaging Spectrometer-1 (AIS-1) images were analyzed in conjunction with Thematic Mapper Simulator (NS001) Large Format Camera color infrared photography and black and white aerial photography. Specific portions of the combined data set were registered and used for classification. Following this procedure, the resulting derived data was tested using an overall accuracy assessment method. Precise photogrammetric 2D-3D-2D geometric modeling techniques is not the basis for this study. Instead, the discussion exposes resultant spectral findings from the image-to-image registrations. Problems associated with the AIS-1 TMS integration are considered, and useful applications of the imagery combination are presented. More advanced methodologies for imagery integration are needed if multisystem data sets are to be utilized fully. Nevertheless, research, described herein, provides a formulation for future Earth Observation Station related multisensor studies.

Heric, Matthew↗

Global Assimilation of EOS-Aura Data as a Means of Mapping Ozone Distribution in the Lower Stratosphere and Troposphere

Ozone in the lower stratosphere and the troposphere plays an important role in forcing the climate. However, the global ozone distribution in this region is not well known because of the sparse distribution of in-situ data and the poor sensitivity of satellite based observations to the lowermost of the atmosphere. The Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) instruments on EOS-Aura provide information on the total ozone column and the stratospheric ozone profile. This data has been assimilated into NASA s Global Earth Observing System, Version 5 (GEOS-5) data assimilation system (DAS). We will discuss the results of assimilating three years of OMI and MLS data into GEOS-5. This data was assimilated alongside meteorological observations from both conventional sources and satellite instruments. Previous studies have shown that combining observations from these instruments through the Trajectory Tropospheric Ozone Residual methodology (TTOR) or using data assimilation can yield useful, yet low biased, estimates of the tropospheric ozone budget. We show that the assimilated ozone fields in this updated version of GEOS-5 exhibit an excellent agreement with ozone sonde and High Resolution Dynamics Limb Sounder (HIRDLS) data in the lower stratosphere in terms of spatial and temporal variability as well as integrated ozone abundances. Good representation of small-scale vertical features follows from combining the MLS data with the assimilated meteorological fields. We then demonstrate how this information can be used to calculate the Stratosphere - Troposphere Exchange of ozone and its contribution to the tropospheric ozone column in GEOS-5. Evaluations of tropospheric ozone distributions from the assimilation will be made by comparisons with sonde and other in-situ observations.

Wargan, Krzysztof↗

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

Quattrochi, Dale A.↗

Combined Weekly Coordinate Solutions from SLR and DORIS

In International Terrestrial Reference Frame (ITRF) 2005 and ITRF2008, the approach for the construction of solutions by the IERS has been for individual analysis centers of each technique to process geodetic tracking data, and for each technique to develop a solution (or contribution) that is integrated into the final ITRF solution by careful combination of the technique solutions. The connections between the geodetic networks are realized by the application of local ties. In an alternate approach, we may assure processing homogeneity by creating normal equations for different techniques with the same orbit determination software, using identically derived algorithms. Another derivative of this approach is to realize the ties between the techniques using satellites tracked with multiple techniques; in effect tieing the networks together using satellite dynamics. In this solution, we develop a time series and a set of cumulative solutions from Satellite Laser Ranging (SLR) & Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) based on homogeneous processing with the NASA GEODYN precise orbit determination suite of programs, where we jointly combine weekly the SLR data to Lageos1, Lageos2, Starlette, and Stella with the DORIS data from SPOT2-SPOT5, as well as satellites that utilize both techniques (TOPEX/Poseidon, Envisat, Jason-2). We discuss the modeling that is applied including upgrades implemented since the submission of the GSC ITRF2008 contributions for IDS. Firstly, we compare the SLR-only solutions comprising four geodetic satellites with the standard approach of utilizing only Lageos1 & Lageos2. Secondly, we evaluate the impact on the DORIS coordinates of the joint analysis with the SLR data.

Lemoine, F.↗