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At least 721 records · Page 40

Solution structure for an Encephalitozoon cuniculi adrenodoxin-like protein in the oxidized state

Encephalitozoon cuniculi is a unicellular, obligate intracellular eukaryotic parasite in the Microsporidia family and one of the agents responsible for microsporidosis infections in humans. Like most Microsporidia, the genome of E. cuniculi is markedly reduced and the organism contains mitochondria-like organelles called mitosomes instead of mitochondria. Here we report the solution NMR structure for a protein physically associated with mitosome-like organelles in E. cuniculi, the 128-residue, adrenodoxin-like protein Ec-Adx (UniProt ID Q8SV19) in the [2Fe-2S] ferredoxin superfamily. Oxidized Ec-Adx contains a mixed four-strand β-sheet, β2-β1-β4-β3 (↓↑↑↓), loosely encircled by three α-helices and two 310-helices. This fold is similar to the structure observed in other adrenodoxin and adrenodoxin-like proteins except for the absence of a fifth anti-parallel β-strand next to β3 and the position of α3. Cross peaks are missing or cannot be unambiguously assigned for 20 amide resonances in the 1 H- 15 N HSQC spectrum of Ec-Adx. These missing residues are clustered primarily in two regions, G48-V61 and L94-L98, containing the four cysteine residues predicted to ligate the paramagnetic [2Fe-2S] cluster. Missing amide resonances in 1 H- 15 N HSQC spectra are detrimental to NMR-based solution structure calculations because 1 H- 1 H NOE restraints are absent (glass half-empty) and this may account for the absent β-strand (β5) and the position of α3 in oxidized Ec-Adx. On the other hand, the missing amide resonances unambiguously identify the presence, and immediate environment, of the paramagnetic [2Fe-2S] cluster in oxidized Ec-Adx (glass half-full).

59 BASIC BIOLOGICAL SCIENCES↗

The Effect of Approximating Some Molecular Integrals in Coupled-Cluster Calculations: Fundamental Frequencies and Rovibrational Spectroscopic Constants of Cyclopropenylidene

The singles and doubles coupled-cluster method that includes a perturbational estimate of connected triple excitations, denoted CCSD(T), has been used, in conjunction with approximate integral techniques, to compute highly accurate rovibrational spectroscopic constants of cyclopropenylidene, C3H2. The approximate integral technique was proposed in 1994 by Rendell and Lee in order to avoid disk storage and input/output bottlenecks, and today it will also significantly aid in the development of algorithms for distributed memory, massively parallel computer architectures. It is shown in this study that use of approximate integrals does not impact the accuracy of CCSD(T) calculations. In addition, the most accurate spectroscopic data yet for C3H2 is presented based on a CCSD(T)/cc-pVQZ quartic force field that is modified to include the effects of core-valence electron correlation. Cyclopropenylidene is of great astronomical and astrobiological interest because it is the smallest aromatic ringed compound to be positively identified in the interstellar medium, and is thus involved in the prebiotic processing of carbon and hydrogen. The singles and doubles coupled-cluster method that includes a perturbational estimate of

Lee, Timothy J.↗

A DEEP, WIDE-FIELD, AND PANCHROMATIC VIEW OF 47 Tuc AND THE SMC WITH HST: OBSERVATIONS AND DATA ANALYSIS METHODS

In Hubble Space Telescope (HST) Cycle 17, we imaged the well-known globular star cluster 47 Tucanae for 121 orbits using the Wide Field Channel of the Advanced Camera for Surveys (ACS) and both the UV/visible (UVIS) and IR channels of the newly installed Wide Field Camera 3 (WFC3) instrument (GO-11677, PI: H. Richer). This unique data set was obtained to address many scientific questions that demand a very deep, panchromatic, and panoramic view of the cluster's stellar populations. In total, the program obtained over 0.75 Ms of imaging exposure time with the three HST cameras, over a time span of 9 months in 2010. The primary ACS field was imaged in the two broadband filters F606W and F814W, at 13 orientations, for all 121 orbits. The parallel WFC3 imaging provides a panchromatic (0.4-1.7 {mu}m) and contiguous imaging swath over a 250 Degree-Sign azimuthal range at impact radii of 6.5-17.9 pc in 47 Tuc. This imaging totals over 60 arcmin{sup 2} in area and utilizes the F390W and F606W broadband filters on WFC3/UVIS and the F110W and F160W broadband filters on WFC3/IR. In this paper, we describe the observational design of the new survey and one of the methods used to analyze all of the imaging data. This analysis combines over 700 full-frame images taken with the three HST cameras into a handful of ultra-deep, well-sampled combined images in each of the six filters. We discuss in detail the methods used to calculate accurate transformations that provide optimal alignment of the input images, the methods used to perform sky background offsets in the input stack and the flagging of deviant pixels, and the balance reached between the input-pixel drop size onto an output supersampled pixel grid. Careful photometric, morphological, and astrometric measurements are performed on the stacks using iterative PSF-fitting techniques, and reveal unprecedented color-magnitude diagrams of the cluster extending to >30th magnitude in the optical, 29th magnitude in the UV, and 27th magnitude in the IR. The data set provides a characterization of the complete stellar populations of 47 Tuc, extending from the faintest hydrogen-burning dwarfs through the main-sequence and giant branches down to very cool white dwarf remnants in the cluster. The imaging also provides the deepest probe of the stellar populations of the background Small Magellanic Cloud galaxy, resolving low-mass main-sequence dwarfs with M {approx}< 0.2 M{sub Sun }.

79 ASTRONOMY AND ASTROPHYSICS↗

First-Principles Grand-Canonical Simulations of Water Adsorption in Proton-Exchanged Zeolites

Water appears by design or as impurities in many important reactive systems. For those catalyzed by porous solid acids, such as widely used zeolites, experimentally quantifying the amount or elucidating the structure of adsorbed water clusters at reaction conditions is challenging, while computational studies (e.g., first-principles molecular dynamics simulations) often need to assume the loading to examine solvation effects. Furthermore, we perform first-principles grand-canonical simulations to predict water adsorption to H-ZSM-5 zeolites under specified experimental conditions. Presampling with inexpensive force fields and a pool-based parallelization algorithm are used to improve simulation efficiency, while molecular dynamics is used to sample configurations involving hydronium species. We observe that H + exchange dramatically increases the hydrophilicity of zeolite MFI and an appreciable amount of water is present at very low relative humidities. At all conditions examined, the zeolitic protons are found to dissociate readily from the surface basic sites and become mobile by participating in the hydrogen-bonded chains of adsorbed water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parallelization of Lower-Upper Symmetric Gauss-Seidel Method for Chemically Reacting Flow

Development of technologies for exploration of the solar system has revived an interest in computational simulation of chemically reacting flows since planetary probe vehicles exhibit non-equilibrium phenomena during the atmospheric entry of a planet or a moon as well as the reentry to the Earth. Stability in combustion is essential for new propulsion systems. Numerical solution of real-gas flows often increases computational work by an order-of-magnitude compared to perfect gas flow partly because of the increased complexity of equations to solve. Recently, as part of Project Columbia, NASA has integrated a cluster of interconnected SGI Altix systems to provide a ten-fold increase in current supercomputing capacity that includes an SGI Origin system. Both the new and existing machines are based on cache coherent non-uniform memory access architecture. Lower-Upper Symmetric Gauss-Seidel (LU-SGS) relaxation method has been implemented into both perfect and real gas flow codes including Real-Gas Aerodynamic Simulator (RGAS). However, the vectorized RGAS code runs inefficiently on cache-based shared-memory machines such as SGI system. Parallelization of a Gauss-Seidel method is nontrivial due to its sequential nature. The LU-SGS method has been vectorized on an oblique plane in INS3D-LU code that has been one of the base codes for NAS Parallel benchmarks. The oblique plane has been called a hyperplane by computer scientists. It is straightforward to parallelize a Gauss-Seidel method by partitioning the hyperplanes once they are formed. Another way of parallelization is to schedule processors like a pipeline using software. Both hyperplane and pipeline methods have been implemented using openMP directives. The present paper reports the performance of the parallelized RGAS code on SGI Origin and Altix systems.

Yoon, Seokkwan↗

Spatially Resolved Mapping of Three-Dimensional Molecular Orientations with ~2 nm Spatial Resolution through Tip-Enhanced Raman Scattering

We record local optical field images of silver nanocubes (75 nm) using tip-enhanced Raman (TER) spectral imaging. The images that we observe are consistent with several recent reports from our group, but here, we demonstrate sub-2 nm spatial resolution in local optical field nanoimaging under ambient laboratory conditions. This is achieved by scanning the substrate (nanocube on Si) relative to a 4-thiobenzonitrile (TBN)-functionalized Ag-coated TER probe. The spatial resolution that we obtain necessitates that only a few molecules govern the recorded optical response; molecular orientation becomes an important consideration in such measurements. We model the orientation through geometry optimization of a TBN molecule chemisorbed onto an Ag79 cluster (sphere with a ~1 nm diameter). Using the computed orientation of the cluster-bound molecule, we then model the optical response using formalism that accounts for the orientation of the molecule relative to vector components of the local optical fields. We find optimal agreement between experiment and theory. In effect, this work reveals the parallels between single-molecule Raman scattering and high-spatial-resolution TER spectroscopy, even when the images themselves cannot be used to visualize a single molecule in real space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Episodic Earthquake Swarms in the Mineral Mountains, Utah Driven by the Roosevelt Hydrothermal System

Over 1,000 earthquakes (-2.0 < M < 2.0), identified using a matched-filter method, occurred in the Mineral Mountains, Utah between 2016 and 2019. The enhanced catalog is complete down to M -0.9 and contains roughly 15 times more events than originally cataloged. Earthquake relocation of ~800 earthquakes shows that activity is concentrated in a <2 km long E-W striking narrow zone, ~4 km east of the Roosevelt hydrothermal system. Two fault orientations, both N-S and E-W parallel to the Opal Mound and Mag Lee faults, respectively, are observed after computing composite focal mechanisms of highly similar earthquakes. Looking solely at the temporal distribution of the seismicity, we identify 15 periods of swarm-like activity, with two major clusters occurring in December 2016, recorded by three stations, and in October 2019 recorded by eight stations. The October 2019 swarm, the best recorded sequence in the area, provides evidence for the underlying triggering mechanism. We show that a complex mechanism of fluid diffusion and aseismic slip is responsible for the swarm evolution with migration velocities reaching 10 km/day. We hypothesize that these episodic swarms in the Mineral Mountains are primarily driven by migrating fluids that originate within the Roosevelt hydrothermal system.

58 GEOSCIENCES↗

The benzene⋯naphthalene complex: A more challenging system than the benzene dimer for newly developed computational methods

High-level coupled cluster singles, doubles, and perturbative triples [CCSD(T)] computations with up to the aug-cc-pVQZ basis set (1924 basis functions) and various extrapolations toward the complete basis set (CBS) limit are presented for the sandwich, T-shaped, and parallel-displaced benzene⋯naphthalene complex. Using the CCSD(T)/CBS interaction energies as a benchmark, the performance of some newly developed wave function and density functional theory methods has been evaluated. The best performing methods were found to be the dispersion-corrected PBE0 functional (PBE0-D3) and spin-component scaled zeroth-order symmetry-adapted perturbation theory (SCS-SAPT0). The success of SCS-SAPT0 is very encouraging because it provides one method for energy component analysis of π-stacked complexes with 200 atoms or more. Most newly developed methods do, however, overestimate the interaction energies. The results of energy component analysis show that interaction energies are overestimated mainly due to the overestimation of dispersion energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Abundance inhomogeneities and atmospheric structure in CN-bimodal globular cluster giants

It has been suggested by several authors that the sodium and aluminum abundance variations correlating with CN-band strength, frequently observed in CN-bimodal globular cluster giants, could be spurious manifestations of different temperature structures in the 'CN-strong' and 'CN-weak' stars, caused by different molecular line blanketing related to the C, N, and O trio. For stellar parameters generally appropriate to giants in the intermediate metallicity CN-bimodal cluster M4, we demonstrate through new model atmosphere calculations, employing opacity sampling and spherical geometry, that the observed abundance anomalies cannot be the result of atmospheric temperature structure. Our results using spherical geometry are compared to identical calculations performed with plane-parallel geometry: the effects of atmospheric extension on derived abundances for all lines considered amount to less than 0.1 dex.

Drake, Jeremy J.↗

MMS Examination of FTEs at the Earth's Subsolar Magnetopause

Determining the magnetic field structure, electric currents, and plasma distributions within flux transfer event (FTE)-type flux ropes is critical to the understanding of their origin, evolution, and dynamics. Here the Magnetospheric Multiscale mission's high-resolution magnetic field and plasma measurements are used to identify FTEs in the vicinity of the subsolar magnetopause. The constant-alpha flux rope model is used to identify quasi-force free flux ropes and to infer the size, the core magnetic field strength, the magnetic flux content, and the spacecraft trajectories through these structures. Our statistical analysis determines a mean diameter of 1,700 ± 400 km (~30 ± 9 d(sub i)) and an average magnetic flux content of 100 ± 30 kWb for the quasi-force free FTEs at the Earth's subsolar magnetopause which are smaller than values reported by Cluster at high latitudes. These observed nonlinear size and magnetic flux content distributions of FTEs appear consistent with the plasmoid instability theory, which relies on the merging of neighboring, small-scale FTEs to generate larger structures. The ratio of the perpendicular to parallel components of current density, R(sub J), indicates that our FTEs are magnetically force-free, defined as R(sub J) < 1, in their core regions (<0.6 R(sub flux rope)). Plasma density is shown to be larger in smaller, newly formed FTEs and dropping with increasing FTE size. It is also shown that parallel ion velocity dominates inside FTEs with largest plasma density. Field-aligned flow facilitates the evacuation of plasma inside newly formed FTEs, while their core magnetic field strengthens with increasing FTE size.

Akhavan-Tafti, M.↗

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Comparison↗

Exotic structure in light neutron-rich nuclei

In this presentation I discussed two subjects. One is the persistence of threefold symmetry in the ground state of {sup 12}C. Recently D{sub 3h} symmetry has been established in {sup 12}C, which reflects the geometric symmetry of the three α particles. Although the spin-orbit interaction plays a significant role and this interaction breaks the α clusters, we show that threefold symmetry of {sup 12}C is still there. We use AQCM approach and discuss that inclusion of spin-orbit interaction, which is absent in the conventional microscopic α cluster models, is possible keeping the threefold symmetry. The second subject is the appearance of rod shape in C isotopes, which has been investigated in the framework of the cranking covariant density functional theory. The relationship between the stability of such states and the spin and isospin degrees of freedom is discussed; adding valence neutrons and rotating the system. These two effects stabilize the rod shape, and in addition, their coherent effect has been found; the σ-orbits (parallel to the symmetry axis) of the valence neutrons, which enhances the rod shape, is lowered by the rotation of the system, and this σ-orbit pulls down the single particle energies of protons with linear configuration owing to the proton-neutron interaction effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Taming parallel I/O complexity with auto-tuning

We present an auto-tuning system for optimizing I/O performance of HDF5 applications and demonstrate its value across platforms, applications, and at scale. The system uses a genetic algorithm to search a large space of tunable parameters and to identify effective settings at all layers of the parallel I/O stack. The parameter settings are applied transparently by the auto-tuning system via dynamically intercepted HDF5 calls. To validate our auto-tuning system, we applied it to three I/O benchmarks (VPIC, VORPAL, and GCRM) that replicate the I/O activity of their respective applications. We tested the system with different weak-scaling configurations (128, 2048, and 4096 CPU cores) that generate 30 GB to 1 TB of data, and executed these configurations on diverse HPC platforms (Cray XE6, IBM BG/P, and Dell Cluster). In all cases, the auto-tuning framework identified tunable parameters that substantially improved write performance over default system settings. In conclusion, we consistently demonstrate I/O write speedups between 2x and 100x for test configurations.

97 MATHEMATICS AND COMPUTING↗

Transforming microseismic clouds into near real-time visualization of the growing hydraulic fracture

SUMMARY Microseismic observations during unconventional reservoir stimulation are typically seen as a proxy for clusters of hydraulic fractures and the extent of the stimulated reservoir. Such straightforward interpretation is often misleading and fails to provide a physically reasonable image of the fracturing process. This paper demonstrates the application of a physics-based machine learning algorithm which enables a rapid and accurate fracture mapping from the microseismic data. Our training and validation data set relies on a history-matched geomechanical modelling workflow implemented in GEOS software for the Hydraulic Fracturing Test Site 1 (HFTS-1) project. For this study we augmented the simulated fracture growth through geostatistical modelling of induced seismicity, so that the synthetic microseismic catalogue matches the main statistical properties of the field observations. We formulated the problem of mapping the actual fracture in the clutter of events to parallel common video segmentation workflows: several past video frames (microseismic density snapshots) are passed through a deep convolutional network to classify whether a given voxel is associated with a fracture or intact rock. We found that for accurate fracture mapping, the network’s input and architecture must be augmented to incorporate the fluid injection parameters (pressure, rate, concentration of proppant, and location of the perforation within the cluster). The error rate for the network reached as little as 10 per cent of the fracture area, while a conventional microseismic interpretation approach yielded ∼300 per cent. Our approach also yields must faster predictions than conventional methods (minutes instead of weeks), and could enable engineers to make rapid decisions regarding engineering parameters (pumping rate, viscosity) in real time during stimulation.

58 GEOSCIENCES↗

MapReduce Implementation of a Hybrid Spectral Library-Database Search Method for Large-Scale Peptide Identification

A MapReduce-based implementation called MR- MSPolygraph for parallelizing peptide identification from mass spectrometry data is presented. The underlying serial method, MSPolygraph, uses a novel hybrid approach to match an experimental spectrum against a combination of a protein sequence database and a spectral library. Our MapReduce implementation can run on any Hadoop cluster environment. Experimental results demonstrate that, relative to the serial version, MR-MSPolygraph reduces the time to solution from weeks to hours, for processing tens of thousands of experimental spectra. Speedup and other related performance studies are also reported on a 400-core Hadoop cluster using spectral datasets from environmental microbial communities as inputs.

59 BASIC BIOLOGICAL SCIENCES↗

Generic and robust method for automatic segmentation of PET images using an active contour model

Purpose: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies. Methods: MASAC, a method for automatic segmentation using an active contour model, incorporates the histogram fuzzy C-means clustering, and localized and textural information to constrain the active contour to detect boundaries in an accurate and robust manner. Moreover, the lattice Boltzmann method is used as an alternative approach for solving the level set equation to make it faster and suitable for parallel programming. Twenty simulated phantom studies and 16 clinical studies, including six cases of pharyngolaryngeal squamous cell carcinoma and ten cases of nonsmall cell lung cancer, were included to evaluate its performance. Besides, the proposed method was also compared with the contourlet-based active contour algorithm (CAC) and Schaefer’s thresholding method (ST). The relative volume error (RE), Dice similarity coefficient (DSC), and classification error (CE) metrics were used to analyze the results quantitatively. Results: For the simulated phantom studies (PSs), MASAC and CAC provide similar segmentations of the different lesions, while ST fails to achieve reliable results. For the clinical datasets (2 cases with connected high-uptake regions excluded) (CSs), CAC provides for the lowest mean RE (−8.38% ± 27.49%), while MASAC achieves the best mean DSC (0.71 ± 0.09) and mean CE (53.92% ± 12.65%), respectively. MASAC could reliably quantify different types of lesions assessed in this work with good accuracy, resulting in a mean RE of −13.35% ± 11.87% and −11.15% ± 23.66%, a mean DSC of 0.89 ± 0.05 and 0.71 ± 0.09, and a mean CE of 19.19% ± 7.89% and 53.92% ± 12.65%, for PSs and CSs, respectively. Conclusions: The authors’ results demonstrate that the developed novel PET segmentation algorithm is applicable to various types of lesions in the authors’ study and is capable of producing accurate and consistent target volume delineations, potentially resulting in reduced intraobserver and interobserver variabilities observed when using manual delineation and improved accuracy in treatment planning and outcome evaluation.

60 APPLIED LIFE SCIENCES↗

Scale-up Unlearnable Examples Learning with High-performance Computing

Recent advancements in AI models, like ChatGPT, are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when radiologists use AI-driven diagnostic tools hosted on online platforms, there is a risk that medical imaging data may be repurposed for future AI training without explicit consent, spotlighting critical privacy and intellectual property concerns around healthcare data usage. Addressing these privacy challenges, a novel approach known as Unlearnable Examples (UEs) has been introduced, aiming to make data unlearnable to deep learning models. A prominent method within this area, called Unlearnable Clustering (UC), has shown improved UE performance with larger batch sizes but was previously limited by computational resources (e.g., a single workstation). To push the boundaries of UE performance with theoretically unlimited resources, we scaled up UC learning across various datasets using Distributed Data Parallel (DDP) training on the Summit supercomputer. Our goal was to examine UE efficacy at high-performance computing (HPC) levels to prevent unauthorized learning and enhance data security, particularly exploring the impact of batch size on UE’s unlearnability. Utilizing the robust computational capabilities of the Summit, extensive experiments were conducted on diverse datasets such as Pets, MedMNist, Flowers, and Flowers102. Our findings reveal that both overly large and overly small batch sizes can lead to performance instability and affect accuracy. However, the relationship between batch size and unlearnability varied across datasets, highlighting the necessity for tailored batch size strategies to achieve optimal data protection. The use of Summit’s high-performance GPUs, along with the efficiency of the DDP framework, facilitated rapid updates of model parameters and consistent training across nodes. Our results underscore the critical role of selecting appropriate batch sizes based on the specific characteristics of each dataset to prevent learning and ensure data security in deep learning applications. The source code is publicly available at https: // github. com/ hrlblab/ UE_ HPC .

Zhu, Yanfan [Vanderbilt University, Nashville, TN,↗

Whistler Waves Driven by Anisotropic Strahl Velocity Distributions: Cluster Observations

Observed properties of the strahl using high resolution 3D electron velocity distribution data obtained from the Cluster/PEACE experiment are used to investigate its linear stability. An automated method to isolate the strahl is used to allow its moments to be computed independent of the solar wind core+halo. Results show that the strahl can have a high temperature anisotropy (T(perpindicular)/T(parallell) approximately > 2). This anisotropy is shown to be an important free energy source for the excitation of high frequency whistler waves. The analysis suggests that the resultant whistler waves are strong enough to regulate the electron velocity distributions in the solar wind through pitch-angle scattering

Vinas, A.F.↗