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At least 325 records · Page 18

Modeling the effects of vorinostat in vivo reveals both transient and delayed HIV transcriptional activation and minimal killing of latently infected cells

Recent efforts to cure human immunodeficiency virus type-1 (HIV-1) infection have focused on developing latency reversing agents as a first step to eradicate the latent reservoir. The histone deacetylase inhibitor, vorinostat, has been shown to activate HIV RNA transcription in CD4+ T-cells and alter host cell gene transcription in HIV-infected individuals on antiretroviral therapy. In order to understand how latently infected cells respond dynamically to vorinostat treatment and determine the impact of vorinostat on reservoir size in vivo , we have constructed viral dynamic models of latency that incorporate vorinostat treatment. We fitted these models to data collected from a recent clinical trial in which vorinostat was administered daily for 14 days to HIV-infected individuals on suppressive ART. The results show that HIV transcription is increased transiently during the first few hours or days of treatment and that there is a delay before a sustained increase of HIV transcription, whose duration varies among study participants and may depend on the long term impact of vorinostat on host gene expression. Parameter estimation suggests that in latently infected cells, HIV transcription induced by vorinostat occurs at lower levels than in productively infected cells. Lastly, the estimated loss rate of transcriptionally induced cells remains close to baseline in most study participants, suggesting vorinostat treatment does not induce latently infected cell killing and thus reduce the latent reservoir in vivo .

59 BASIC BIOLOGICAL SCIENCES↗

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗

TRAPEDS: Producing traces for multicomputers via execution-driven simulation

Trace-driven simulation is an important aid in performance analysis of computer systems. Capturing address traces for these simulations is a difficult problem for single processors and particularly for multicomputers. Even when existing trace methods can be used on multicomputers, the amount of collected data typically grows with the number of processors, so I/O and trace storage costs increase. A new technique is presented which modifies the executable code to dynamically collect the address trace from the user code and analyzes this trace during the execution of the program. This method helps resolve the I/O and storage problems and facilitates parallel analysis of the address trace. If a trace stored on disk is desired, the generated trace information can also be written to files during execution, with a resultant drop in program execution speed. An initial implementation on the Intel iPSC/2 hypercube multicomputer is detailed, and sample simulation results are presented. The effect of this trace collection method on execution time is illustrated.

Stunkel, Craig B.↗

TRAPEDS - Producing traces for multicomputers via execution driven simulation

Trace-driven simulation is an important aid in performance analysis of computer systems. Capturing address traces for these simulations is a difficult problem for single processors and particularly for multicomputers. Even when existing trace methods can be used on multicomputers, the amount of collected data typically grows with the number of processors, so I/O and trace storage costs increase. A new technique is presented which modifies the executable code to dynamically collect the address trace from the user code and analyzes this trace during the execution of the program. This method helps resolve the I/O and storage problems and facilitates parallel analysis of the address trace. If a trace stored on disk is desired, the generated trace information can also be written to files during execution, with a resultant drop in program execution speed. An initial implementation on the Intel iPSC/2 hypercube multicomputer is detailed, and sample simulation results are presented. The effect of this trace collection method on execution time is illustrated.

Stunkel, Craig B.↗

A sensor fusion field experiment in forest ecosystem dynamics

The background of the Forest Ecosystem Dynamics field campaign is presented, a progress report on the analysis of the collected data and related modeling activities is provided, and plans for future experiments at different points in the phenological cycle are outlined. The ecological overview of the study site is presented, and attention is focused on forest stands, needles, and atmospheric measurements. Sensor deployment and thermal and microwave observations are discussed, along with two examples of the optical radiation measurements obtained during the experiment in support of radiative transfer modeling. Future activities pertaining to an archival system, synthetic aperture radar, carbon acquisition modeling, and upcoming field experiments are considered.

Smith, James A.↗

BOREAS TE-20 Soils Data Over the NSA-MSA and Tower Sites in Raster Format

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set was gridded from vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were gridded into raster files that cover the NSA-MSA and tower sites. The data are stored in binary, image format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Hall, Forrest G.↗

BOREAS TE-21 SSA Site Characteristics Data

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-20 (Terrestrial Ecology) team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set contains measurements of site characteristics conducted in the Southern Study Area (SSA) from 18 Jul 1994 to 30 Jul 1994. The data are stored in CSV files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Knox, Robert↗

BOREAS TE-20 Soils Data Over the NSA-MSA and Tower Sites in Vector Format

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set contains vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were converted to ARCANFO EXPORT files. These data cover 1-kilometer diameters around each of the NSA tower sites, and another layer covers the NSA-MSA. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Hall, Forrest G.↗

LAD-C: A large area debris collector on the ISS

The Large Area Debris Collector (LAD-C) is a 10 sq m aerogel and acoustic sensor system under development by the U.S. Naval Research Laboratory (NRL) with main collaboration from the NASA Orbital Debris Program Office at Johnson Space Center, JAXA Institute of Space and Astronautical Science (ISAS), Chiba University (Japan), ESA Space Debris Office, University of California at Berkeley, and University of Kent at Canterbury (UK). The U.S. Department of Defense (DoD) Space Test Program (STP) has assumed the responsibility for having the system manifested and deployed on the International Space Station (ISS), and then having it retrieved and returned to Earth after one to two years. LAD-C will attempt to utilize the ISS as a scientific platform to characterize the near-Earth meteoroid and orbital debris environment in the size regime where little data exist. In addition to meteoroid and orbital debris sample return, the acoustic sensors will record impact time, location, signal strength, and acoustic waveform data of the largest collected samples. A good time-dependent meteoroid and orbital debris flux estimate can be derived. Analysis of the data will also enable potential source identification of some of the collected samples. This dynamical link can be combined with laboratory composition analysis of impact residuals extracted from aerogel to further our understanding of orbital debris population, and the sources of meteoroids, asteroids and comets.

Liou, J.-C.↗

Results from One Year of Ka-Band Beacon Measurements at Svalbard

Since April 1, 2016, a Ka-band (20.198 GHz) propagation terminal has been installed and operating at the Svalsat facility in Longyearbyen, Norway. This campaign is a joint effort between the European Space Agency (ESA), Kongsberg Satellite Services (KSAT), the French Aerospace Laboratory (ONERA), the Centre National d'Etudes Spatiales (CNES), and NASA Glenn Research Center (GRC) to characterize atmospheric attenuation, scintillation, and depolarization in the Ka-band in high latitude regions at low elevation angles. The propagation terminal observes the Thor 7 20.198 GHz RHCP beacon at nominally 2.6 deg elevation angle. Simultaneous 10 Hz and 1 Hz sampling is performed and a total dynamic range of 35 dB is achieved. One year of propagation data has been collected and the preliminary results are presented in this paper. From the first year of measurements, it is observed that at these low elevation angles, strong scintillation/multi-path conditions, as well as significant depolarization events can occur which may impose difficulties in meeting mission link acquisition requirements at 5 deg elevation angle, such as those desired by the Joint Polar Satellite System (JPSS) mission. The design of the dual-polarized terminal with integrated digital radiometer, as well as the data processing techniques are described, along with the first year results and preliminary conclusions.

Nessel, James↗

Small Gas Bubble Experiment for Mitigation of Cavitation Damage and Pressure Waves in Short-pulse Mercury Spallation Targets

Populations of small helium gas bubbles were introduced into a flowing mercury experiment test loop to evaluate mitigation of beam-pulse induced cavitation damage and pressure waves. The test loop was developed and thoroughly tested at the Spallation Neutron Source (SNS) prior to irradiations at the Los Alamos Neutron Science Center - Weapons Neutron Research Center (LANSCE-WNR) facility. Twelve candidate bubblers were evaluated over a range of mercury flow and gas injection rates by use of a novel optical measurement technique that accurately assessed the generated bubble size distributions. Final selection for irradiation testing included two variations of a swirl bubbler provided by Japan Proton Accelerator Research Complex (J-PARC) collaborators and one orifice bubbler developed at SNS. Bubble populations of interest consisted of sizes up to 150 m in radius with achieved gas void fractions in the 10^-5 to 10^-4 range. The nominal WNR beam pulse used for the experiment created energy deposition in the mercury comparable to SNS pulses operating at 2.5 MW. Nineteen test conditions were completed each with 100 pulses, including variations on mercury flow, gas injection and protons per pulse. The principal measure of cavitation damage mitigation was surface damage assessment on test specimens that were manually replaced for each test condition. Damage assessment was done after radiation decay and decontamination by optical and laser profiling microscopy with damaged area fraction and maximum pit depth being the more valued results. Damage was reduced by flow alone; the best mitigation from bubble injection was between half and a quarter that of flow alone. Other data collected included surface motion tracking by three laser Doppler vibrometers (LDV), loop wall dynamic strain, beam diagnostics for charge and beam profile assessment, embedded hydrophones and pressure sensors, and sound measurement by a suite of conventional and contact microphones.

bubbles↗

Experiments and Simulations of Hypervelocity Impact Plasmas: Final Report

The space environment is fraught with complex plasmas spanning a wide range of densities and temperatures. Much of space plasma research has focused on large-scale changes in the ambient plasma and fields from the Sun to the Earth’s atmosphere, driven primarily by the solar wind. Yet one particular type of space plasma, which forms from a hypervelocity impact, remains poorly understood. Hypervelocity impactors include both meteoroids and space debris. Meteoroids are naturally occurring objects in space that travel between 11 and 72.8 km/s and originate primarily from comets and asteroids. In contrast, space debris are human-made objects with speeds typically < 11 km/s. Hypervelocity impactors routinely hit spacecraft, yet the physics behind the formation of the plasma and the dynamics of its expansion remain largely unknown. The complexity of this phenomenon necessitates a research approach that includes both experimental studies and numerical simulation in order to understand the underlying physical processes that occur upon formation and expansion of the impact plasma. Our research has focused on providing the first comprehensive understanding of plasma generated by hypervelocity impacts by meteoroids and space debris on spacecraft in order to characterize the behavior of the expanding plasma and its interactions with the ambient environment. We conducted experimental campaigns at a dust accelerator facility that can accelerate particles up to 60 km/s, which is representative of meteoroid speeds, and at a light gas gun facility that can accelerate larger projectiles up to 7 km/s, which is representative of orbital debris. The experiments included plasma, optical and radio frequency (RF) sensors in order to understand the dynamics and associated RF emission resulting from hypervelocity plasmas. Furthermore, we combined the collected data with results from numerical simulations using particle-in-cell (PIC) and smoothed particle hydrodynamics (SPH) techniques. Using results from both experimental measurements and simulations, we addressed the following outstanding science questions: 1) What are the properties of hypervelocity impact plasmas? 2) What conditions cause impact plasmas to create RF emission and what is the power dependence on frequency? 3) How does the ambient environment around the spacecraft, including the background magnetic and electric fields and plasma density, influence the hypervelocity impact plasmas?

42 ENGINEERING↗

Attosecond Transient Grating Spectroscopy with Near-Infrared Grating Pulses and an Extreme Ultraviolet Diffracted Probe

Transient grating spectroscopy has become a mainstay among metal and semiconductor characterization techniques. Here, we extend the technique toward the shortest achievable time scales by using tabletop high-harmonic generation of attosecond extreme ultraviolet (XUV) pulses that diffract from transient gratings generated with sub-5 fs near-infrared (NIR) pulses. We demonstrate the power of attosecond transient grating spectroscopy (ATGS) by investigating the ultrafast photoexcited dynamics in an Sb semimetal thin film. ATGS provides an element-specific, background-free signal unfettered by spectral congestion, in contrast to transient absorption spectroscopy. With ATGS measurements in Sb polycrystalline thin films, we observe the generation of coherent phonons and investigate the lattice and carrier dynamics. Among the latter processes, we extract carrier thermalization, hot carrier cooling, and electron-hole recombination, which are on the order of 20 fs, 50 fs, and 2 ps time scales, respectively. Furthermore, the simultaneous collection of transient absorption and transient grating data allows us to extract the total complex dielectric constant in the sample dynamics with a single measurement, including the real-valued refractive index, from which we are also able to investigate carrier-phonon interactions and longer-lived phonon dynamics. The outlined experimental technique expands the capabilities of transient grating spectroscopy and attosecond spectroscopies by providing a wealth of information concerning carrier and lattice dynamics with an element-selective technique at the shortest achievable time scales.

Quintero-Bermudez, Rafael↗

Use of continuous sample translation to reduce radiation damage for XPCS studies of protein diffusion

An experimental setup to measure X-ray photon correlation spectroscopy during continuous sample translation is presented and its effectiveness as a means to avoid sample damage in dynamics studies of protein diffusion is evaluated. X-ray damage from focused coherent synchrotron radiation remains below tolerable levels as long as the sample is translated through the beam sufficiently quickly. Here it is shown that it is possible to separate sample dynamics from the effects associated with the transit of the sample through the beam. By varying the sample translation rate, the damage threshold level, D thresh = 1.8 kGy, for when beam damage begins to modify the dynamics under the conditions used, is also determined. Signal-to-noise ratios, R sn ≥ 20, are obtained down to the shortest delay times of 20 µs. The applicability of this method of data collection to the next generation of multi-bend achromat synchrotron sources is discussed and it is shown that sub-microsecond dynamics should be obtainable on protein samples.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Space-Based Sensor Web for Earth Science Applications: An Integrated Architecture for Providing Societal Benefits

There is a significant interest in the Earth Science research and user remote sensing community to substantially increase the number of useful observations relative to the current frequency of collection. The obvious reason for such a push is to improve the temporal, spectral, and spatial coverage of the area(s) under investigation. However, there is little analysis available in terms of the benefits, costs and the optimal set of sensors needed to make the necessary observations. Classic observing system solutions may no longer be applicable because of their point design philosophy. Instead, a new intelligent data collection system paradigm employing both reactive and proactive measurement strategies with adaptability to the dynamics of the phenomena should be developed. This is a complex problem that should be carefully studied and balanced across various boundaries including: science, modeling, applications, and technology. Modeling plays a crucial role in making useful predictions about naturally occurring or human-induced phenomena In particular, modeling can serve to mitigate the potentially deleterious impacts a phenomenon may have on human life, property, and the economy. This is especially significant when one is interested in learning about the dynamics of, for example, the spread of forest fires, regional to large-scale air quality issues, the spread of the harmful invasive species, or the atmospheric transport of volcanic plumes and ash. This paper identifies and examines these challenging issues and presents architectural alternatives for an integrated sensor web to provide observing scenarios driving the requisite dynamic spatial, spectral, and temporal characteristics to address these key application areas. A special emphasis is placed on the observing systems and its operational aspects in serving the multiple users and stakeholders in providing societal benefits. We also address how such systems will take advantage of technological advancement in small spacecraft and emerging information technologies, and how sensor web options may be realized and made affordable. Specialized detector subsystems and precision flying techniques may still require substantial innovation, development time and cost: we have presented the considerations for these issues. Finally, data and information gathering and compression techniques are also briefly described.

Habib, Shahid↗

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Training data selection for event classification in a highly variable environment

A problem of interest for nuclear nonproliferation is monitoring activities at nuclear facilities, where proliferation events may only take place a few times and often under variable conditions. Machine learning has revolutionized data analytics by enabling the use of measurable signatures to generate predictive models of facility operations. However, traditional methods for training these models require large, reliable data sets with labeled observations, a challenge for nonproliferation. Highly variable conditions further complicate this as events from training data may have occurred in conditions quite different from the event of interest. Our hypothesis is that when events occur in a highly variable environment, careful training data selection for each test event could outperform the standard approach of using all available training data. We developed a method to optimize training data selection for the given test event and applied it to predicting the power level of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. In this study, the reactor startup exhibits variability between occurrences due to natural variability in environmental conditions and operational procedures. Using a combination of analysis techniques, a similitude assessment was performed on data collected from HFIR to isolate clusters that were optimal for training a predictive model. Concepts such as dynamic time warping and Jaccard similarity were used in conjunction with clustering analysis. In order to validate this approach, the model was trained on every combination of unique training events and the predictive performance was compared to the performance using a subset of the training data selected by isolated clusters found through the similitude assessment.

Iyer, A↗

Persistence and memory timescales in root‐zone soil moisture dynamics

Abstract The memory timescale that characterizes root‐zone soil moisture remains the dominant measure in seasonal forecasts of land‐climate interactions. This memory is a quasi‐deterministic timescale associated with the losses (e.g., evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however, represents a distribution of time periods where soil moisture resides above or below some prescribed threshold and is therefore inherently probabilistic. Using multiple soil moisture data sets collected at high resolution (subhourly) across different biomes and climates, this paper explores the differences, underlying dynamics, and relative importance of memory and persistence timescales in root‐zone soil moisture. A first‐order Markov process, commonly used to interpret soil moisture fluctuations derived from climate simulations, is also used as a reference model. Persistence durations of soil moisture below the plant water‐stress level (chosen as the threshold), and the temporal spectrum of upcrossings and downcrossings of this threshold, are compared to the memory timescale and spectrum of the full time series, respectively. The results indicate that despite the differences between meteorological drivers, the spectrum of threshold‐crossings is similar across sites, and follows a unique relation with that of the full soil moisture series. The distribution of persistence times exhibits an approximate stretched exponential type and reflects a likelihood of exceeding the memory at all sites. However, the rainfall counterpart of these distributions shows that persistence of dry atmospheric periods is less likely at sites with long soil moisture memory. The cluster exponent, a measure of the density of threshold‐crossings in a time frame, reveals that the clustering tendency in rainfall events (on‐off switches) does not translate directly to clustering in soil moisture. This is particularly the case in climates where rainfall and evapotranspiration are out of phase, resulting in less ordered (more independent) persistence in soil moisture than in rainfall.

Ghannam, Khaled↗