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DOE OSTI2022

Phylogenetic structure of specialization: A new approach that integrates partner availability and phylogenetic diversity to quantify biotic specialization in ecological networks

Abstract Biotic specialization holds information about the assembly, evolution, and stability of biological communities. Partner availabilities can play an important role in enabling species interactions, where uneven partner availabilities can bias estimates of biotic specialization when using phylogenetic diversity indices. It is therefore important to account for partner availability when characterizing biotic specialization using phylogenies. We developed an index, phylogenetic structure of specialization (PSS), that avoids bias from uneven partner availabilities by uncoupling the null models for interaction frequency and phylogenetic distance. We incorporate the deviation between observed and random interaction frequencies as weights into the calculation of partner phylogenetic α‐diversity. To calculate the PSS index, we then compare observed partner phylogenetic α‐diversity to a null distribution generated by randomizing phylogenetic distances among the same number of partners. PSS quantifies the phylogenetic structure (i.e., clustered, overdispersed, or random) of the partners of a focal species. We show with simulations that the PSS index is not correlated with network properties, which allows comparisons across multiple systems. We also implemented PSS on empirical networks of host–parasite, avian seed‐dispersal, lichenized fungi–cyanobacteria, and hummingbird pollination interactions. Across these systems, a large proportion of taxa interact with phylogenetically random partners according to PSS, sometimes to a larger extent than detected with an existing method that does not account for partner availability. We also found that many taxa interact with phylogenetically clustered partners, while taxa with overdispersed partners were rare. We argue that species with phylogenetically overdispersed partners have often been misinterpreted as generalists when they should be considered specialists. Our results highlight the important role of randomness in shaping interaction networks, even in highly intimate symbioses, and provide a much‐needed quantitative framework to assess the role that evolutionary history and symbiotic specialization play in shaping patterns of biodiversity. PSS is available as an R package at https://github.com/cjpardodelahoz/pss .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)↗

DOE OSTI2023

Relationship between magnetoresistance behavior and magnetic states in intercalated compounds Fe x TiS 2

Here, temperature and field-dependent neutron powder diffraction (NPD) measurements have been performed to reveal the nature of the unusual evolution of the magnetoresistance behavior with increasing Fe content in the intercalated compounds Fe x TiS 2 (with x=0.25,0.33,0.50,0.55) synthesized by solid-phase reaction method with prolonged homogenization heat treatment. As derived from neutron diffraction measurements, both the Fe 0.25 TiS 2 and the Fe 0.50 TiS 2 compound exhibit an antiferromagnetic (AFM) order below their respective Néel temperatures T N ≈52 K and T N ≈140K, which results in the presence of a large magnetoresistance accompanying the field-induced phase transition from AFM to the ferromagnetic (FM) state. At low temperatures, this AFM-FM transition is irreversible, confirmed by the irreversibility of changes in the NPD patterns and the presence of remnant magnetoresistance. In contrast, Fe 0.33 TiS 2 shows short-range magnetic order at T f ≈44 K due to a triangular network of intercalated Fe atoms and frustrations of exchange interactions with a field-induced FM alignment of Fe magnetic moments in an applied magnetic field as revealed by NPD measurements. The field-induced transformations of the cluster glass magnetic state in this compound lead to a significant decrease in electrical resistivity. According to NPD data, a reduced impact of an external magnetic field on the electrical resistivity of the compound Fe 0.55 TiS 2 can be ascribed to the presence of ferromagnetic or ferrimagnetic order in compounds with the Fe concentrations above x=0.50. The results obtained indicate that the distribution of the Fe atoms, along with their concentration in Fe x TiS 2 layered compounds, plays a decisive role in the formation of the magnetic state and the behavior of the magnetoresistance.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Urbanization and malaria have a contextual relationship in endemic areas: A temporal and spatial study in Ghana

In West Africa, malaria is one of the leading causes of disease-induced deaths. Existing studies indicate that as urbanization increases, there is corresponding decrease in malaria prevalence. However, in malaria-endemic areas, the prevalence in some rural areas is sometimes lower than in some peri-urban and urban areas. Therefore, the relationship between the degree of urbanization, the impact of living in urban areas, and the prevalence of malaria remains unclear. This study explores this association in Ghana, using epidemiological data at the district level (2015–2018) and data on health, hygiene, and education. We applied a multilevel model and time series decomposition to understand the epidemiological pattern of malaria in Ghana. Then we classified the districts of Ghana into rural, peri-urban, and urban areas using administratively defined urbanization, total built areas, and built intensity. We converted the prevalence time series into cross-sectional data for each district by extracting features from the data. To predict the determinant most impacting according to the degree of urbanization, we used a cluster-specific random forest. We find that prevalence is impacted by seasonality, but the trend of the seasonal signature is not noticeable in urban and peri-urban areas. While urban districts have a slightly lower prevalence, there are still pockets with higher rates within these regions. These areas of high prevalence are linked to proximity to water bodies and waterways, but the rise in these same variables is not associated with the increase of prevalence in peri-urban areas. The increase in nightlight reflectance in rural areas is associated with an increased prevalence. We conclude that urbanization is not the main factor driving the decline in malaria. However, the data indicate that understanding and managing malaria prevalence in urbanization will necessitate a focus on these contextual factors. Finally, we design an interactive tool, ’malDecision’ that allows data-supported decision-making.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1989

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Tescher, Andrew G.↗

DOE OSTI2025

Tailoring Cu-Zr gradient nanoglass structures: Influence of nanoparticle size and cooling rates on glass-glass interfaces

The study of gradient nanoglasses (GNGs) has gained attention due to their unique mechanical properties and potential applications in advanced materials. This study employs molecular dynamics simulations to synthesize a GNG using Cu-Zr metallic glass nanoparticles (NPs) sized from 3 to 15 nm. The NPs were produced by melting and quenching metallic clusters at a relatively slow quench rate of 10 9 K/s. The synthesis of GNG is elucidated along with the characterization of its heterogeneous metallic glass nanostructure. A seamless GNG structure is formed through cold compression of Cu 64 Zr 36 amorphous NPs of varying sizes. The influence of NP size on the GNG structure is investigated, utilizing deeply relaxed NPs, which exhibit a characteristic Cu segregation pattern on their surfaces. The results highlight an increase in structural heterogeneity due to heterogeneous mass transport and the development of local composition and density variations caused by Cu segregation at glass-glass interfaces (GGIs). A reduction in NP size is correlated with decreased Cu atomic displacements and local density at GGIs, suggesting that larger NPs may produce stronger GGIs. This research presents a novel methodology for synthesizing heterogeneous metallic glasses, demonstrating the capacity to control and customize nanostructure heterogeneity through the manipulation of NP sizes and cooling rates. Furthermore, these findings enhance our understanding of structural evolution during nanoglass synthesis and lay the foundation for further exploration in nanomaterial synthesis and characterization.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The Role of Multiscale Interaction in Tropical Cyclogenesis and Its Predictability in Near-Global Aquaplanet Cloud-Resolving Simulations

Tropical cyclogenesis (TCG) is a multiscale process that involves interactions between large-scale circulation and small-scale convection. A near-global aquaplanet cloud-resolving model (NGAqua) with 4-km horizontal grid spacing that produces tropical cyclones (TCs) is used to investigate TCG and its predictability. This study analyzes an ensemble of three 20-day NGAqua simulations, with initial white-noise perturbations of low-level humidity. TCs develop spontaneously from the northern edge of the intertropical convergence zone (ITCZ), where large-scale flows and tropical convection provide necessary conditions for barotropic instability. Zonal bands of positive low-level absolute vorticity organize into cyclonic vortices, some of which develop into TCs. A new algorithm is developed to track the cyclonic vortices. A vortex-following framework analysis of the low-level vorticity budget shows that vertical stretching of absolute vorticity due to convective heating contributes positively to the vorticity spinup of the TCs. A case study and composite analyses suggest that sufficient humidity is key for convective development. TCG in these three NGAqua simulations undergoes the same series of interactions. The locations of cyclonic vortices are broadly predetermined by planetary-scale circulation and humidity patterns associated with ITCZ breakdown, which are predictable up to 10 days. Whether and when the cyclonic vortices become TCs depend on the somewhat more random feedback between convection and vorticity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Atomistic insights into the nucleation and growth of platinum on palladium nanocrystals

Abstract Despite the large number of reports on colloidal nanocrystals, very little is known about the mechanistic details in terms of nucleation and growth at the atomistic level. Taking bimetallic core-shell nanocrystals as an example, here we integrate in situ liquid-cell transmission electron microscopy with first-principles calculations to shed light on the atomistic details involved in the nucleation and growth of Pt on Pd cubic seeds. We elucidate the roles played by key synthesis parameters, including capping agent and precursor concentration, in controlling the nucleation site, diffusion path, and growth pattern of the Pt atoms. When the faces of a cubic seed are capped by Br − , Pt atoms preferentially nucleate from corners and then diffuse to edges and faces for the creation of a uniform shell. The diffusion does not occur until the Pt deposited at the corner has reached a threshold thickness. At a high concentration of the precursor, self-nucleation takes place and the Pt clusters then randomly attach to the surface of a seed for the formation of a non-uniform shell. These atomistic insights offer a general guideline for the rational synthesis of nanocrystals with diverse compositions, structures, shapes, and related properties.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Partons as unique ground states of quantum Hall parent Hamiltonians: The case of Fibonacci anyons

We present microscopic, multiple Landau level, (frustration-free and positive semi-definite) parent Hamiltonians whose ground states, realizing different quantum Hall fluids, are parton-like and whose excitations display either Abelian or non-Abelian braiding statistics. We prove ground state energy monotonicity theorems for systems with different particle numbers in multiple Landau levels, demonstrate S-duality in the case of toroidal geometry, and establish complete sets of zero modes of special Hamiltonians stabilizing parton-like states, specifically at filling factor \nu=2/3 ν = 2 / 3 . The emergent Entangled Pauli Principle (EPP), introduced in [Phys. Rev. B 98, 161118(R) (2018)] and which defines the “DNA” of the quantum Hall fluid, is behind the exact determination of the topological characteristics of the fluid, including charge and braiding statistics of excitations, and effective edge theory descriptions. When the closed-shell condition is satisfied, the densest (i.e., the highest density and lowest total angular momentum) zero-energy mode is a unique parton state. We conjecture that parton-like states generally span the subspace of many-body wave functions with the two-body M M -clustering property within any given number of Landau levels, that is, wave functions with M M th-order coincidence plane zeroes and both holomorphic and anti-holomorphic dependence on variables. General arguments are supplemented by rigorous considerations for the M=3 M = 3 case of fermions in four Landau levels. For this case, we establish that the zero mode counting can be done by enumerating certain patterns consistent with an underlying EPP. We apply the coherent state approach of [Phys. Rev. X 1, 021015 (2011)] to show that the elementary (localized) bulk excitations are Fibonacci anyons. This demonstrates that the DNA associated with fractional quantum Hall states encodes all universal properties. Specifically, for parton-like states, we establish a link with tensor network structures of finite bond dimension that emerge via root level entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Mobility, Energy, and Electric Vehicle Typology for New York State

Mobility patterns, technology adoption and associated energy outcomes vary tremendously across settlement types. This paper explores how a highly geographically resolved exploration of the social, economic, techno-infrastructural and environmental domains of New York State is key to understanding observed variations in transportation technology adoption and associated mobility and energy outcomes. Current socioeconomic and mobility data sets at the census block group level are integrated in a hierarchical clustering approach to show how variations in mobility and energy outcomes are shaped by these domains - which may enhance progress on investments, or effectively inform planning and other decisions for state-wide goals. The clustering produces four settlement types to predict dependent variables of electric vehicle (EV) adoption rates, commute mode, vehicle fuel economy, and vehicles per household. This typology shows EV adoption rates among the core urban population, which is wealthy and highly-educated, are high - 3 EVs/1000 vehicles versus 1 EV/1000 vehicles among the urban working class. Commuting mode is closely linked with population and employment density - more than 90% of core urbanites use transit or active modes, compared with only 22% of suburbanites and 17% of rural residents. Household vehicle ownership also varies, with 2 vehicles per household in rural areas and only 0.5 in core urban settings. Important findings on differences among the rural, suburban, urban, and urban core settlement types suggest a need to explore how best to manage and anticipate very different types of services that may be supportive in achieving energy-efficient and affordable mobility systems state-wide.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Large-scale genomic analyses with machine learning uncover predictive patterns associated with fungal phytopathogenic lifestyles and traits

Abstract Invasive plant pathogenic fungi have a global impact, with devastating economic and environmental effects on crops and forests. Biosurveillance, a critical component of threat mitigation, requires risk prediction based on fungal lifestyles and traits. Recent studies have revealed distinct genomic patterns associated with specific groups of plant pathogenic fungi. We sought to establish whether these phytopathogenic genomic patterns hold across diverse taxonomic and ecological groups from the Ascomycota and Basidiomycota, and furthermore, if those patterns can be used in a predictive capacity for biosurveillance. Using a supervised machine learning approach that integrates phylogenetic and genomic data, we analyzed 387 fungal genomes to test a proof-of-concept for the use of genomic signatures in predicting fungal phytopathogenic lifestyles and traits during biosurveillance activities. Our machine learning feature sets were derived from genome annotation data of carbohydrate-active enzymes (CAZymes), peptidases, secondary metabolite clusters (SMCs), transporters, and transcription factors. We found that machine learning could successfully predict fungal lifestyles and traits across taxonomic groups, with the best predictive performance coming from feature sets comprising CAZyme, peptidase, and SMC data. While phylogeny was an important component in most predictions, the inclusion of genomic data improved prediction performance for every lifestyle and trait tested. Plant pathogenicity was one of the best-predicted traits, showing the promise of predictive genomics for biosurveillance applications. Furthermore, our machine learning approach revealed expansions in the number of genes from specific CAZyme and peptidase families in the genomes of plant pathogens compared to non-phytopathogenic genomes (saprotrophs, endo- and ectomycorrhizal fungi). Such genomic feature profiles give insight into the evolution of fungal phytopathogenicity and could be useful to predict the risks of unknown fungi in future biosurveillance activities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138 fb −1 of proton-proton collision data at $\sqrt{𝑠}$ = 13 TeV, collected in 2016–2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large ’t Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics. With no observed excess of events over the standard model expectation, limits are set on the cross section for production via gluon fusion of a scalar mediator with SUEP-like decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Insights of Molecular Mechanism of Xylem Development in Five Black Poplar Cultivars

Black poplar (Populus deltoides, P. nigra, and their hybrids) is the main poplar cultivars in China. It offers interesting options of large-scale biomass production for bioenergy due to its rapid growth and high yield. Poplar wood properties were associated with chemical components and physical structures during wood formation. In this study, five poplar cultivars, P. euramericana ‘Zhonglin46’ (Pe1), P. euramericana ‘Guariento’ (Pe2), P. nigra ‘N179’ (Pn1), P. deltoides ‘Danhong’ (Pd1), and P. deltoides ‘Nanyang’ (Pd2), were used to explore the molecular mechanism of xylem development. We analyzed the structural differences of developing xylem in the five cultivars and profiled the transcriptome-wide gene expression patterns through RNA sequencing. The cross sections of the developing xylem showed that the cell wall thickness of developed fiber in Pd1 was thickest and the number of xylem vessels of Pn1 was the least. A total of 10,331 differentially expressed genes were identified among 10 pairwise comparisons of the five cultivars, most of them were related to programmed cell death and secondary cell wall thickening. K-means cluster analysis and Gene Ontology enrichment analysis showed that the genes highly expressed in Pd1 were related to nucleotide decomposition, metabolic process, transferase, and microtubule cytoskeleton; whereas the genes highly expressed in Pn1 were involved in cell wall macromolecule decomposition and polysaccharide binding processes. Based on a weighted gene co-expression network analysis, a large number of candidate regulators for xylem development were identified. And their potential regulatory roles to cell wall biosynthesis genes were validated by a transient overexpression system. This study provides a set of promising candidate regulators for genetic engineering to improve feedstock and enhance biofuel conversion in the bioenergy crop Populus.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1995

Flight Schedule and the Circadian Clock Influence on Sleep Loss During Overnight Cargo Operations

Thirty-four flight crew members were monitored before, during, and after two 8-day overnight cargo duty patterns which involved multiple flights at night crossing no more than one time zone per 24 h. Rectal temperature, heart rate, and wrist activity were recorded every 2 min. Sleep quantity and quality, and nap timing, were noted in a logbook. To reduce the masking effects of physical activity on temperature, 0.28 C was added to each subject's raw temperature data whenever he reported being asleep. For both masked and unmasked data, daily temperature minima were estimated from the multiple complex demodulated waveform. The temperature minima did not show a progressive adaptation to night duty, which was interrupted by a night off after 5 nights on one trip pattern and after 3 nights on the other. On duty days, the average temperature minimum delayed by about 3 h, occurring near the end of the duty period. Daytime sleep episodes averaged 2.9 h shorter than nighttime sleep episodes, and were rated as lighter, less restorative, and poorer overall. Fifty-three percent of subjects slept more than once per 24 h while they were on night duty, compared to 17% when able to sleep at night. The total sleep per 24 h on duty days averaged 1.2 h less than pretrip. Twenty-nine percent of subjects lost more than 2 h of sleep per 24 h across the 8-day duty patterns. After night duty, subjects awoke around 1400 local time, even when they had slept 2-3 h less than a normal nocturnal sleep episode. Consequently, the duration of morning sleep episodes was correlated with the off-duty time (multiple r(sup 2)=0.44, F=37.23, p less than 0.0001). Anecdotally, crew members complained of being unable to sleep longer and not feeling well-rested. These wakeups were clustered 6 h after the temperature minimum, which suggests that they may have been a response to the circadian wakeup signal. Daytime layovers in which crew members were able to sleep again in the evening ended later (0200-0300) and were longer (average 19.2 h versus 14.8 h) than those in which they slept only once in the morning. Overnight cargo crew members are working around the time of the circadian nadir with an accumulating sleep debt. Two scheduling factors affect sleep loss during these operations: how long before the circadian wakeup signal crew members come off duty, and whether the layover lasts long enough to permit a second sleep episode in the early evening.

Gander, Philippa H.↗

NASA NTRS2014

Large Meteoroid Impact on the Moon on 17 March 2013

Since early 2006, NASA's Marshall Space Flight Center has observed over 300 impact flashes on the Moon, produced by meteoroids striking the lunar surface. On 17 March 2013 at 03:50:54.312 UTC, the brightest flash of an 8-year routine observing campaign was observed in two 0.35 m telescopes outfitted with Watec 902H2 Ultimate monochrome CCD cameras recording interleaved 30 fps video. Standard CCD photometric techniques, described in [1], were applied to the video after saturation correction, yielding a peak R magnitude of 3.0 +/- 0.4 in a 1/30 second video exposure. This corresponds to a luminous energy of 7.1 × 10(exp 6) J. Geographic Information System (GIS) tools were used to georeference the lunar impact imagery and yielded a crater location at 20.60 +/- 0.17deg N, 23.92 +/- 0.30deg W. The camera onboard the Lunar Reconnaissance Orbiter (LRO), a NASA spacecraft mapping the Moon from lunar orbit, discovered the fresh crater associated with this impact by comparing post-impact images from 28 July 2013 to pre-impact images on 12 Feb 2012. The images show fresh, bright ejecta around an 18 m diameter circular crater, with a 15 m inner diameter measured from the level of pre-existing terrain, at 20.7135deg N, 24.3302deg W. An asymmetrical ray pattern with both high and low reflectance ejecta zones extends 1-2 km beyond the crater, and a series of mostly low reflectance splotches can be seen within 30 km of the crater - likely due to secondary impacts [2]. The meteoroid impactor responsible for this event may have been part of a stream of large particles encountered by the Earth/Moon associated with the Virginid Meteor Complex, as evidenced by a cluster of 5 fireballs seen in Earth's atmosphere on the same night by the NASA All Sky Fireball Network [3] and the Southern Ontario Meteor Network [4]. Assuming a velocity-dependent luminous efficiency (ratio of luminous energy to kinetic energy) from [5] and an impact velocity of 25.6 km/s derived from fireball measurements, the impactor kinetic energy was 5.4 × 10(exp 9) J and the impactor mass was 16 kg. Assuming an impact angle of 56deg from horizontal (based on fireball orbit measurements), a regolith density of 1500 kg/m(exp 3), and impactor density between 1800 and 3000 kg/m(exp 3), the impact crater diameter was estimated to be 8-18 m at the pre-impact surface and 10-23 m rim-to-rim using the Holsapple [6] and Gault [7] models, a result consistent with the observed crater.

Moser, Danielle E.↗

NASA NTRS2003

The expression and function of the achaete-scute genes in Tribolium castaneum reveals conservation and variation in neural pattern formation and cell fate specification

The study of achaete-scute (ac/sc) genes has recently become a paradigm to understand the evolution and development of the arthropod nervous system. We describe the identification and characterization of the ac/sc genes in the coleopteran insect species Tribolium castaneum. We have identified two Tribolium ac/sc genes - achaete-scute homolog (Tc-ASH) a proneural gene and asense (Tc-ase) a neural precursor gene that reside in a gene complex. Focusing on the embryonic central nervous system we find that Tc-ASH is expressed in all neural precursors and the proneural clusters from which they segregate. Through RNAi and misexpression studies we show that Tc-ASH is necessary for neural precursor formation in Tribolium and sufficient for neural precursor formation in Drosophila. Comparison of the function of the Drosophila and Tribolium proneural ac/sc genes suggests that in the Drosophila lineage these genes have maintained their ancestral function in neural precursor formation and have acquired a new role in the fate specification of individual neural precursors. Furthermore, we find that Tc-ase is expressed in all neural precursors suggesting an important and conserved role for asense genes in insect nervous system development. Our analysis of the Tribolium ac/sc genes indicates significant plasticity in gene number, expression and function, and implicates these modifications in the evolution of arthropod neural development.

Non-NASA Center↗

DOE OSTI2021

Spin Reorientation in Antiferromagnetic Layered FePt 5 P

FePt 5 P, a substitutional variant of the anti-CeCoIn 5 structure type in the space group P4/mmm, was synthesized by a high-temperature solid-state method and structurally characterized by X-ray diffraction. FePt 5 P contains layers of FePt 12 clusters formed by magnetically active Fe and heavy Pt with strong spin-orbit coupling (SOC); the layers are separated by P atoms. The various Fe–Pt distances in FePt 12 clusters generate complex magnetic orders in FePt 5 P. According to temperature-dependent magnetic and specific heat measurements, FePt 5 P shows a stripe-type antiferromagnetic order at T N ≈ 90 K, which is also confirmed by resistivity measurements. Furthermore, a spin reorientation occurs at ~74 and ~68 K in and out of the ab plane based on the specific heat measurements. The temperature-dependent neutron powder diffraction patterns demonstrate the antiferromagnetic order in FePt 5 P, and the spins orientate up to 58.4° with respect to the c axis at 10 K. First-principles calculations of FePt 5 P show the band splitting at the Fermi level by strong SOC and the s–d hybridization between P and Fe/Pt electrons enhances the structural stability and affects the magnetic ordering.

36 MATERIALS SCIENCE↗

NASA NTRS2000

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Steyaert, Lou↗