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At least 55 records · Page 3

Fragmentation dynamics of CS 2 dications and trications following S 2p ionization

Here, we present the results from a detailed study of the fragmentation dynamics of CS$_2^{2+}$ and CS$_2^{3+}$, formed in intense femtosecond soft x-ray pulses above the sulfur 2p edge, primarily through single core photoionization from the S 2p site, and subsequent Auger–Meitner decay(s). By combining three-dimensional velocity map imaging with covariance analysis, we determine the relative momenta of the ions produced in each two- and three-body fragmentation channel, at significantly higher ion count rates than conventional coincidence measurements. We shed new light on the wide range of fragmentation channels observed from the CS 2 dication and trication, including channels that involve ionization-induced bond formation and fragmentations producing undetected neutral cofragments. In the latter case, a “native frames” approach is used to isolate contributions from concerted and sequential fragmentations and extract dynamical information about each step of a concerted fragmentation process. While dications often fragment sequentially, the trication is dominated by concerted fragmentation. The main trication fragmentation channel into S + + C + + S + can be well-approximated by classical Coulombic simulations of the ground-state geometry distribution, reflecting both the nature of the trication potential energy surface and the rapid multiple ionization prior to substantial structural dynamics. This study demonstrates ways in which fundamental insights into the fragmentation dynamics of polycations following x-ray ionization may be extracted, which will be beneficial to future studies that employ time-resolved x-ray Coulomb explosion imaging to study ultrafast photochemistry.

Allum, Felix [Deutsches Elektronen-Synchrotron (DE↗

Streaming Data Reorganization at Scale with DeltaFS Indexed Massive Directories

We report complex storage stacks providing data compression, indexing, and analytics help leverage the massive amounts of data generated today to derive insights. It is challenging to perform this computation, however, while fully utilizing the underlying storage media. This is because, while storage servers with large core counts are widely available, single-core performance and memory bandwidth per core grow slower than the core count per die. Computational storage offers a promising solution to this problem by utilizing dedicated compute resources along the storage processing path. We present DeltaFS Indexed Massive Directories (IMDs), a new approach to computational storage. DeltaFS IMDs harvest available (i.e., not dedicated) compute, memory, and network resources on the compute nodes of an application to perform computation on data. We demonstrate the efficiency of DeltaFS IMDs by using them to dynamically reorganize the output of a real-world simulation application across 131,072 CPU cores. DeltaFS IMDs speed up reads by 1,740x while only slightly slowing down the writing of data during simulation I/O for in situ data processing.

97 MATHEMATICS AND COMPUTING↗

Influence of surface relaxation on solute atoms positioning within atom probe tomography reconstructions

Highlights: • APT measurement of Al/Cu alloy is simulated with a combined electrostatics and molecular dynamics (MD) approach. • Results show segregation of dilute Cu at [111] poles in correspondence to experimental measurements. • No temperature is involved. The effect originates in both disparate evaporation field and bond-energies in the alloy. While thermal or field-induced surface migration has been invoked often in past literature to rationalize the experimental observations of solute and impurity atoms segregation to specific poles and zones lines in atom probe tomography (APT) reconstructions, it does not satisfactorily explain all experimental results. Using a combined finite-element and molecular dynamics simulation approach that models the field evaporation process from mechanically relaxed emitter structures, we show that an additional mechanism, athermal relaxation, can also drive significant solute migration. The mechanism is illustrated for Cu in solid solution in Al, which exhibits segregation of Cu to 111 poles and along [110] zone lines in reconstructed APT data. The higher bonding energy of Cu atoms on the surface, confirmed using density-functional theory calculations, causes longer retention on the surface and preferential evaporation of neighboring Al atoms with subsequent athermal relaxation of Cu into higher-neighbor-count sites left vacant by evaporating Al neighbors. This in turn results in barrier-free long-range migration of the Cu atoms by a series of relaxation events that follow the receding terrace ledges towards high-neighbor count poles and zone lines. This mechanism fundamentally limits spatial resolution in the limit of zero temperature.

36 MATERIALS SCIENCE↗

SCIP: a single-cell image processor toolbox

Abstract Summary Each cell is a phenotypically unique individual that is influenced by internal and external processes, operating in parallel. To characterize the dynamics of cellular processes one needs to observe many individual cells from multiple points of view and over time, so as to identify commonalities and variability. With this aim, we engineered a software, ‘SCIP’, to analyze multi-modal, multi-process, time-lapse microscopy morphological and functional images. SCIP is capable of automatic and/or manually corrected segmentation of cells and lineages, automatic alignment of different microscopy channels, as well as detect, count and characterize fluorescent spots (such as RNA tagged by MS2-GFP), nucleoids, Z rings, Min system, inclusion bodies, undefined structures, etc. The results can be exported into *mat files and all results can be jointly analyzed, to allow studying not only each feature and process individually, but also find potential relationships. While we exemplify its use on Escherichia coli, many of its functionalities are expected to be of use in analyzing other prokaryotes and eukaryotic cells as well. We expect SCIP to facilitate the finding of relationships between cellular processes, from small-scale (e.g. gene expression) to large-scale (e.g. cell division), in single cells and cell lineages. Availability and implementation http://www.ca3-uninova.org/project_scip Supplementary information Supplementary data are available at Bioinformatics online.

Martins, Leonardo (ORCID:0000000333512910)↗

Observation of biexciton emission from single semiconductor nanoplatelets

Quasi-two-dimensional semiconductor nanoplatelets (NPLs) are intriguing systems for studying the influence of Auger recombination processes on the multiexciton emission efficiencies in the weak in-plane confinement regime. We investigate CdSe/CdS core/shell NPLs using cryogenic temperature single particle spectroscopy and observe bright biexciton emission at high excitation powers. The average binding energy of the biexcitons is determined to be 16.5 meV. The observed switching between the biexciton and trion states indicates charging-decharging dynamics of the NPLs mediated by the Auger ionization process. These findings are highly relevant for harvesting efficient biexciton emission for energy, lighting, and quantum applications.

36 MATERIALS SCIENCE↗

Counting generations in birth and death processes with competing Erlang and exponential waiting times

Lymphocyte populations, stimulated in vitro or in vivo, grow as cells divide. Stochastic models are appropriate because some cells undergo multiple rounds of division, some die, and others of the same type in the same conditions do not divide at all. If individual cells behave independently, then each cell can be imagined as sampling from a probability density of times to division and death. The exponential density is the most mathematically and computationally convenient choice. It has the advantage of satisfying the memoryless property, consistent with a Markov process, but it overestimates the probability of short division times. With the aim of preserving the advantages of a Markovian framework while improving the representation of experimentally-observed division times, we consider a multi-stage model of cellular division and death. We use Erlang-distributed (or, more generally, phase-type distributed) times to division, and exponentially distributed times to death. We classify cells into generations, using the rule that the daughters of cells in generation n are in generation n + 1. In some circumstances, our representation is equivalent to established models of lymphocyte dynamics. We find the growth rate of the cell population by calculating the proportions of cells by stage and generation. The exponent describing the late-time cell population growth, and the criterion for extinction of the population, differs from what would be expected if N steps with rate λ were equivalent to a single step of rate λ/N. We link with a published experimental dataset, where cell counts were reported after T cells were transferred to lymphopenic mice, using Approximate Bayesian Computation. In the comparison, the death rate is assumed to be proportional to the generation and the Erlang time to division for generation 0 is allowed to differ from that of subsequent generations. The multi-stage representation is preferred to a simple exponential in posterior distributions, and the mean time to first division is estimated to be longer than the mean time to subsequent divisions.

59 BASIC BIOLOGICAL SCIENCES↗

A valence balanced rule for discovery of 18-electron half-Heuslers with defects

Using first-principles DFT we systematically investigate the thermodynamic stability and off-stoichiometry in 108 nominal 19-electron half-Heusler (hH) compounds. We demonstrate unambiguously that considering a cation deficiency towards the off-stoichiometric valence balanced, VEC = 18 composition is necessary for explaining the stability of all previously reported nominal VEC = 19 compounds. This is understandable in terms of an energy benefit from valence balance considering the valence of each atom using Zintl chemistry that offsets the energy penalty of forming defects in nearly all cases. Thus, we propose a valence balanced rule to understand the ground state stability of half-Heuslers irrespective of stoichiometry and nominal electron count (8, 18 or 19). Using this generalized rule we (a) predict 16 previously unreported nominal 19-electron XYZ half-Heuslers and (b) rationalize the reports of giant off-stoichiometries in compounds such as Ti (1–x) NiSb which has been known for over 50 years. Of the 16 new compounds predicted here, Ti (1–x) PtSb was synthesized and the half-Heusler phase confirmed through X-ray studies. Here, the flexibility in stoichiometry of the half-Heusler systems to attain a stable valence balanced composition by accommodating large defect concentrations opens up multiple dimensions for discovery of multi-component defective half-Heuslers based on intrinsic and extrinsic defects which compensate for the nominally non-18-electron count of the structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Conservation laws and effective hadronization models

Hadronization models based on local string-breaking dynamics are typically Markovian by construction, yet the physical ensemble of final states is shaped by global constraints that couple the entire fragmentation trajectory. Recasting hadronization as a conditioned stochastic diffusion process provides a precise mathematical resolution to this tension. In particular, this language reveals explicitly that constraints stemming from conservation laws induce non-Markovian correlations between otherwise independent fragmentation steps, and that these correlations can be absorbed exactly into a renormalization of the local dynamics through a Doob $h$-transform. We develop this formalism for a $q\bar{q}$ string in the chiral limit, where the longitudinal-transverse factorization of the Lund kernel becomes exact, enabling systematic power counting and clean ultraviolet (UV)/infrared (IR) separation. The dynamics organize naturally into a tower of effective theories distinguished by the remaining string mass, spanning a UV fixed point with scale-invariant transport coefficients, an intermediate regime where transverse phase space induces controlled running, and an IR boundary layer where non-local effects enter at leading order. The tower exhibits genuine Wilsonian structure, including $β$-functions, anomalous dimensions, and systematic matching conditions. The resulting framework achieves a clean factorization of universal microscopic fragmentation dynamics from infrared constraint effects, and opens new directions for both the theoretical analysis and practical simulation of hadronization.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

Multichannel response analysis on 2D projection views for detection of clustered microcalcifications in digital breast tomosynthesis

Purpose: To investigate the feasibility of a new two-dimensional (2D) multichannel response (MCR) analysis approach for the detection of clustered microcalcifications (MCs) in digital breast tomosynthesis (DBT). Methods: With IRB approval and informed consent, a data set of two-view DBTs from 42 breasts containing biopsy-proven MC clusters was collected in this study. The authors developed a 2D approach for MC detection using projection view (PV) images rather than the reconstructed three-dimensional (3D) DBT volume. Signal-to-noise ratio (SNR) enhancement processing was first applied to each PV to enhance the potential MCs. The locations of MC candidates were then identified with iterative thresholding. The individual MCs were decomposed with Hermite–Gaussian (HG) and Laguerre–Gaussian (LG) basis functions and the channelized Hotelling model was trained to produce the MCRs for each MC on the 2D images. The MCRs from the PVs were fused in 3D by a coincidence counting method that backprojects the MC candidates on the PVs and traces the coincidence of their ray paths in 3D. The 3D MCR was used to differentiate the true MCs from false positives (FPs). Finally a dynamic clustering method was used to identify the potential MC clusters in the DBT volume based on the fact that true MCs of clinical significance appear in clusters. Using two-fold cross validation, the performance of the 3D MCR for classification of true and false MCs was estimated by the area under the receiver operating characteristic (ROC) curve and the overall performance of the MCR approach for detection of clustered MCs was assessed by free response receiver operating characteristic (FROC) analysis. Results: When the HG basis function was used for MCR analysis, the detection of MC cluster achieved case-based test sensitivities of 80% and 90% at the average FP rates of 0.65 and 1.55 FPs per DBT volume, respectively. With LG basis function, the average FP rates were 0.62 and 1.57 per DBT volume at the same sensitivity levels. The difference in the two sets of basis functions for detection of MCs did not show statistical significance. Conclusions: The authors' experimental results indicate that the MCR approach is promising for the detection of MCs on PV images. The HG or LG basis functions are both effective in characterizing the signal response of MCs using the channelized Hotelling model. The coincidence counting method for fusion of the 2D MCR in 3D is an important step for FP reduction. Further study is underway to improve the MCR approach for microcalcification detection in DBT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Wide Dynamic Range, 10 kHz Framing Detector for 4D-STEM

Hybrid pixel array detectors (PADs) have expanded the fidelity, frame rate and dynamic range for diffractive imaging in electron microscopes. With their high detective quantum efficiencies (DQE), the noise performance limited is by counting statistics. Consequently, improving the precision and quality of high-speed images requires increasing the linear dynamic range and the maximum usable beam current. Here we describe a new prototype hybrid PAD, our next-generation electron microscope pixel array detector (NG-EMPAD) that expands both the framing speed and dynamic range of our earlier EMPAD design. Like the EMPAD, electrons are detected directly in a 500 μm thick silicon sensor bonded pixel-by-pixel to a custom signal processing integrated circuit (IC). Each pixel in the IC integrates charge carriers produced by the high-energy incident electrons. Here, in-pixel circuitry uses a combination of techniques to extend the dynamic range, including adaptive gain switching and the quantitative excess charge dumping similar to the EMPAD. In-pixel buffering of signals during readout allows acquiring a new image while reading out the previously collected image, yielding an image collection duty cycle of nearly 100%.

36 MATERIALS SCIENCE↗

Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions

Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/ EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D–, or microbial-negative) groups: D+ and D– data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D– data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.

59 BASIC BIOLOGICAL SCIENCES↗

Building a machine learning surrogate model for wildfire activities within a global Earth system model

Abstract. Wildfire is an important ecosystem process, influencing land biogeophysical and biogeochemical dynamics and atmospheric composition. Fire-driven loss of vegetation cover, for example, directly modifies the surface energy budget as a consequence of changing albedo, surface roughness, and partitioning of sensible and latent heat fluxes. Carbon dioxide and methane emitted by fires contribute to a positive atmospheric forcing, whereas emissions of carbonaceous aerosols may contribute to surface cooling. Process-based modeling of wildfires in Earth system land models is challenging due to limited understanding of human, climate, and ecosystem controls on fire counts, fire size, and burned area. Integration of mechanistic wildfire models within Earth system models requires careful parameter calibration, which is computationally expensive and subject to equifinality. To explore alternative approaches, we present a deep neural network (DNN) scheme that surrogates the process-based wildfire model with the Energy Exascale Earth System Model (E3SM) interface. The DNN wildfire model accurately simulates observed burned area with over 90 % higher accuracy with a large reduction in parameterization time compared with the current process-based wildfire model. The surrogate wildfire model successfully captured the observed monthly regional burned area during validation period 2011 to 2015 (coefficient of determination, R2=0.93). Since the DNN wildfire model has the same input and output requirements as the E3SM process-based wildfire model, our results demonstrate the applicability of machine learning for high accuracy and efficient large-scale land model development and predictions.

58 GEOSCIENCES↗

Efficient GPU Implementation of Automatic Differentiation for Computational Fluid Dynamics

Many scientific and engineering applications require repeated calculations of derivatives of output functions with respect to input parameters. Automatic Differentiation (AD) is a method that automates derivative calculations and can significantly speed up code development. In Computational Fluid Dynamics (CFD), derivatives of flux functions with respect to state variables (Jacobian) are needed for efficient solutions of the nonlinear governing equations. AD of flux functions on graphics processing units (GPUs) is challenging as flux computations involve many intermediate variables that create high register pressure and require significant memory traffic because of the need to store the derivatives. This paper presents a forward-mode AD method based on multivariate dual numbers that addresses these challenges and simultaneously reduces the floating-point operation count. The dimension of the multivariate dual numbers is optimized for performance. The flux computations are restructured to minimize the number of temporary variables and reduce register pressure. For effective utilization of memory bandwidth, shared memory is used to store the local flux Jacobian. This AD implementation is compared with several other Jacobian implementations on an NVIDIA V100 GPU (V100). For three-dimensional perfect-gas compressible-flow equations implemented in a practical CFD code, the AD implementation of a flux Jacobian based on multivariate dual numbers of dimension 5 outperforms all other GPU AD implementations on V100. Its performance is comparable with the optimized hand-differentiated version. Finally, the implementation achieves 75% of the peak floating-point throughput and 61 % of the peak global device memory bandwidth usage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Anomaly Detection in Dynamic Networks

Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. A second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the communication counts. In a sequential analysis, anomalous behavior is then identified from outlying behavior with respect to the fitted predictive probability models. Seasonality is again incorporated into the model and is treated as a changepoint model on the transition probabilities of a discrete time Markov process. Second stage analytics are then developed which combine anomalous edges to identify anomalous substructures in the network.

97 MATHEMATICS AND COMPUTING↗

StreamGen: Connecting Populations of Streams and Shells to Their Host Galaxies

In this work, we study how the abundance and dynamics of populations of disrupting satellite galaxies change systematically as a function of host galaxy properties. We apply a theoretical model of the phase-mixing process to classify intact satellite galaxies and stellar streamlike and shell-like debris in ∼1500 Milky Way–mass systems generated by a semi-analytic galaxy formation code, SatGen. In particular, we test the effect of host galaxy halo mass, disk mass, ratio of disk scale height to length, and stellar feedback model on disrupting satellite populations. We find that the counts of tidal debris are consistent across all host galaxy models, within a given host mass range, and that all models can have streamlike debris on low-energy orbits, consistent with that observed around the Milky Way. However, we find a preference for streamlike debris on lower-energy orbits in models with a thicker (lower-density) host disk or on higher-energy orbits in models with a more massive host disk. Importantly, we observe significant halo-to-halo variance across all models. These results highlight the importance of simulating and observing large samples of Milky Way–mass galaxies and accounting for variations in host properties when using disrupting satellites in studies of near-field cosmology.

dark matter↗

Ab Initio Prediction of the 4 $\mathrm{H}$e($d, γ$) 6 $\mathrm{L}$i Big Bang Radiative Capture

We report the rate at which helium ( 4 He ) and deuterium (d) fuse together to produce lithium-6 ( 6 Li) and a γ ray, 4 $\mathrm{H}$e($d, γ$) 6 $\mathrm{L}$i, is a critical puzzle piece in resolving the discrepancy between big bang predictions and astronomical observations for the primordial abundance of 6 Li . The accurate determination of this radiative capture rate requires the quantitative and predictive description of the fusion probability across the big bang energy window (30 keV ≲ E ≲ 400 keV), where measurements are hindered by low counting rates. We present first-principle (or, ab initio) predictions of the 4 $\mathrm{H}$e($d, γ$) 6 $\mathrm{L}$i astrophysical S factor using validated nucleon-nucleon and three-nucleon interactions derived within the framework of chiral effective field theory. By employing the ab initio no-core shell model with continuum to describe 4 He-d scattering dynamics and bound 6 Li product on an equal footing, we accurately and consistently determine the contributions of the main electromagnetic transitions driving the radiative capture process. Our results reveal an enhancement of the capture probability below 100 keV owing to previously neglected magnetic dipole (M1) transitions and reduce by an average factor of 7 the uncertainty of the thermonuclear capture rate between 0.002 and 2 GK.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Unprecedented Fluorophore Photostability Enabled by Low‐Loss Organic Hyperbolic Materials

Abstract The dynamics of photons in fluorescent molecules plays a key role in fluorescence imaging, optical sensing, organic photovoltaics, and displays. Photobleaching is an irreversible photodegradation process of fluorophores, representing a fundamental limitation in relevant optical applications. Chemical reagents are used to suppress the photobleaching rate but with exceptionally high specificity for each type of fluorophore. Here, using organic hyperbolic materials (OHMs), an optical platform to achieve unprecedented fluorophore photostability without any chemical specificity is demonstrated. A more than 500‐fold lengthening of the photobleaching lifetime and a 230‐fold increase in the total emitted photon counts are observed simultaneously. These exceptional improvements solely come from the low‐loss hyperbolic dispersion of OHM films and the large resultant Purcell effect in the visible spectral range. The demonstrated OHM platform may open up a new paradigm in nanophotonics and organic plasmonics for super‐resolution imaging and the engineering of light–matter interactions at the nanoscale.

Lee, Yeon Ui↗

Designing Size Consistent Statistics for Accurate Anomaly Detection in Dynamic Networks

An important task in network analysis is the detection of anomalous events in a network time series. These events could merely be times of interest in the network timeline or they could be examples of malicious activity or network malfunction. Hypothesis testing using network statistics to summarize the behavior of the network provides a robust framework for the anomaly detection decision process. Unfortunately, choosing network statistics that are dependent on confounding factors like the total number of nodes or edges can lead to incorrect conclusions (e.g., false positives and false negatives). In this article, we describe the challenges that face anomaly detection in dynamic network streams regarding confounding factors. We also provide two solutions to avoiding error due to confounding factors: the first is a randomization testing method that controls for confounding factors, and the second is a set of size-consistent network statistics that avoid confounding due to the most common factors, edge count and node count.

97 MATHEMATICS AND COMPUTING↗