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At least 1,639 records · Page 91

A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis

Differentiating erythroblasts execute a dynamic alternative splicing program shown here to include extensive and diverse intron retention (IR) events. Cluster analysis revealed hundreds of developmentallydynamic introns that exhibit increased IR in mature erythroblasts, and are enriched in functions related to RNA processing such as SF3B1 spliceosomal factor. Distinct, developmentally-stable IR clusters are enriched in metal-ion binding functions and include mitoferrin genes SLC25A37 and SLC25A28 that are critical for iron homeostasis. Some IR transcripts are abundant, e.g. comprising ~50% of highly-expressed SLC25A37 and SF3B1 transcripts in late erythroblasts, and thereby limiting functional mRNA levels. IR transcripts tested were predominantly nuclearlocalized. Splice site strength correlated with IR among stable but not dynamic intron clusters, indicating distinct regulation of dynamically-increased IR in late erythroblasts. Retained introns were preferentially associated with alternative exons with premature termination codons (PTCs). High IR was observed in disease-causing genes including SF3B1 and the RNA binding protein FUS. Comparative studies demonstrated that the intron retention program in erythroblasts shares features with other tissues but ultimately is unique to erythropoiesis. Finally, we conclude that IR is a multi-dimensional set of processes that post-transcriptionally regulate diverse gene groups during normal erythropoiesis, misregulation of which could be responsible for human disease.

59 BASIC BIOLOGICAL SCIENCES↗

A Coupled Plasma Dynamics and Gas Flow Model for Semiconductor Processing

A continuum modeling approach by self-consistently coupling plasma dynamics and gas flow will be presented for the analysis of high density plasma reactors. Experimental data shows that gas flow distribution affects the etch rate uniformity even at low pressures (6-20 mTorr) and flow rates (20-70 sccm). This study will investigate the effects of gas flow and gas energy on bulk plasma densities and temperatures using a continuum model. The model solves multidimensional equations of mass balance for neutrals and ions, gas momentum, separate energy equations for electrons and neutrals and Maxwell's equations for power coupling. A test case of N2 plasma in a 300mm TCP etch reactor, for which hybrid model and Langmuir probe data are available, is chosen for this analysis. Our preliminary results show that modeling gas flow and energy improves the predictions of electron density and its spatial variation in the reactor when compared with the experimental data. The aim of this study is to identify the operating conditions for the TCP reactor when a self-consistent modeling of gas flow is important.

Bose, Deepak↗

WearGP: A computationally efficient machine learning framework for local erosive wear predictions via nodal Gaussian processes

Computational fluid dynamics (CFD)-based wear predictions are computationally expensive to evaluate, even with a high-performance computing infrastructure. Thus, it is difficult to provide accurate local wear predictions in a timely manner. Data-driven approaches provide a more computationally efficient way to approximate the CFD wear predictions without running the actual CFD wear models. In this paper, a machine learning (ML) approach, termed WearGP, is presented to approximate the 3D local wear predictions, using numerical wear predictions from steady-state CFD simulations as training and testing datasets. The proposed framework is built on Gaussian process (GP) and utilized to predict wear in a much shorter time. The WearGP framework can be segmented into three stages. At the first stage, the training dataset is built by using a number of CFD simulations in the order of O (10 2 ). At the second stage, the data cleansing and data mining process are performed, where the nodal wear solutions are extracted from the solution database to build a training dataset. At the third stage, the wear predictions are made, using trained GP processes. Two CFD case studies including 3D slurry pump impeller and casing are used to demonstrate the WearGP framework, in which 144 training and 40 testing data points are used to train and test the proposed method, respectively. The numerical accuracy, computational effiency and effectiveness between the WearGP framework and CFD wear model for both slurry pump impellers and casings are compared. It is shown that the WearGP framework can achieve highly accurate results that are comparable with the CFD results, with a relatively small size training dataset, with a computational time reduction in an order of 10 5 to 10 6 .

42 ENGINEERING↗

Quantum process identification: a method for characterizing non-markovian quantum dynamics

Established methods for characterizing quantum information processes do not capture non-Markovian (history-dependent) behaviors that occur in real systems. These methods model a quantum process as a fixed map on the state space of a predefined system of interest. Such a map averages over the system's environment, which may retain some effect of its past interactions with the system and thus have a history-dependent influence on the system. Although the theory of non-Markovian quantum dynamics is currently an active area of research, a systematic characterization method based on a general representation of non-Markovian dynamics has been lacking. In this article we present a systematic method for experimentally characterizing the dynamics of open quantum systems. Our method, which we call quantum process identification (QPI), is based on a general theoretical framework which relates the (non-Markovian) evolution of a system over an extended period of time to a time-local (Markovian) process involving the system and an effective environment. In practical terms, QPI uses time-resolved tomographic measurements of a quantum system to construct a dynamical model with as many dynamical variables as are necessary to reproduce the evolution of the system. Through numerical simulations, we demonstrate that QPI can be used to characterize qubit operations with non-Markovian errors arising from realistic dynamics including control drift, coherent leakage, and coherent interaction with material impurities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Suppression of Void Nucleation in High-Purity Aluminum via Dynamic Recrystallization

The process of ductile fracture in metals often begins with void nucleation at second-phase particles and inclusions. Previous studies of rupture in high-purity face-centered-cubic metals, primarily aluminum (Al), concluded that second-phase particles are necessary for cavitation. A recent study of tantalum (Ta), a body-centered-cubic metal, demonstrated that voids nucleate readily at deformation-induced dislocation boundaries. These same features form in Al during plastic deformation. This study investigates why void nucleation was not previously observed at dislocation boundaries in Al. Here, we demonstrate that void nucleation is impeded in Al by room-temperature dynamic recrystallization (DRX), which erases these boundaries before voids can nucleate at them. If dislocation cells reform after DRX and before specimen separation by necking, voids nucleation is observed. These results indicate that dislocation substructures likely plays an important role in ductile rupture.

36 MATERIALS SCIENCE↗

The symmetrical quasi-classical approach to electronically nonadiabatic dynamics applied to ultrafast exciton migration processes in semiconducting polymers

In the last several years, a symmetrical quasi-classical (SQC) windowing model applied to the classical Meyer-Miller (MM) vibronic Hamiltonian has been shown to be a simple, efficient, general, and quite-accurate method for treating electronically nonadiabatic processes at the totally classical level. Here, the SQC/MM methodology is applied to ultrafast exciton dynamics in a Frenkel/site-exciton model of oligothiophene (OT) as a model of organic semiconductor polymers. In order to keep the electronic representation as compact and efficient as possible, the adiabatic version of the MM Hamiltonian was employed, with dynamical calculations carried out in the recently developed “kinematic momentum” representation, from which site/monomer-specific (diabatic) excitation probabilities were extracted using a new procedure developed in this work. The SQC/MM simulation results are seen to describe coherent exciton transport driven by planarization of a central torsion defect in the OT oligomer as well as to capture exciton self-trapping effects in good agreement with benchmark quantum calculations using the multi-layer multiconfiguration time-dependent Hartree approach. The SQC/MM calculations are also seen to significantly outperform the standard Ehrenfest approach, which shows serious discrepancies. Furthermore, these results are encouraging, not only because they illustrate a significant further application of the SQC/MM approach and its utility, but because they strongly suggest that classical mechanical simulations (with the potential for linear scaling efficiency) can be used to capture, quantitatively, important dynamical features of electronic excitation energy transfer in semiconducting polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-informed machine-learning model of temperature evolution under solid phase processes

We model temperature dynamics during Shear Assisted Proccess Extrusion (ShAPE), a solid phase process that plasticizes feedstock with a rotating tool and subsequently extrudes it into a consolidated tube, rod, or wire. Control of temperature is critical during ShAPE processing to avoid liquefaction, ensure smooth extrusion, and develop desired material properties in the extruded products. Accurate modeling of the complicated thermo-mechanical feedbacks between process inputs, material temperature, and heat generation presents a significant barrier to predictive modeling and process design. In particular, connecting micro-structural scale mechanisms of heat generation to macro-scale predictions of temperature can become computationally intractable. In this work we use a neural network (NN) model of heat generation to bridge this gap, by combining it with a simplified model of the temperature dynamics due to conduction and convection to capture the macro scale evolution of temperature. We inform the construction of the NN heat generation model using crystal plasticity simulations at the micro-structural scale to model the effects of process inputs on generation of heat. We achieved close fits of the temperature dynamics model to a diverse experimental data-set. Further, the relationships learned by the NN model between process inputs and heat generation showed qualitative agreement with those predicted by crystal plasticity simulations.

36 MATERIALS SCIENCE↗

Probabilistic Discrete‐Time Models for Spreading Processes in Complex Networks: A Review

Abstract Research into network dynamics of spreading processes typically employs both discrete and continuous time methodologies. Although each approach offers distinct insights, integrating them can be challenging, particularly when maintaining coherence across different time scales. This review focuses on the Microscopic Markov Chain Approach (MMCA), a probabilistic f ramework originally designed for epidemic modeling. MMCA uses discrete dynamics to compute the probabilities of individuals transitioning between epidemiological states. By treating each time step—usually a day—as a discrete event, the approach captures multiple concurrent changes within this time frame. The approach allows to estimate the likelihood of individuals or populations being in specific states, which correspond to distinct epidemiological compartments. This review synthesizes key findings from the application of this approach, providing a comprehensive overview of its utility in understanding epidemic spread.

Granell, Clara↗

Atomistic details of protein dynamics and the role of hydration water

The importance of protein dynamics for their biological activity is nowwell recognized. Different experimental and computational techniques have been employed to study protein dynamics, hierarchy of different processes and the coupling between protein and hydration water dynamics. But, understanding the atomistic details of protein dynamics and the role of hydration water remains rather limited. Based on overview of neutron scattering, molecular dynamic simulations, NMR and dielectric spectroscopy results we present a general picture of protein dynamics covering time scales from faster than ps to microseconds and the influence of hydration water on different relaxation processes. Internal protein dynamics spread over a wide time range fromfaster than picosecond to longer than microseconds. We suggest that the structural relaxation in hydrated proteins appears on the microsecond time scale, while faster processes present mostly motion of side groups and some domains. Hydration water plays a crucial role in protein dynamics on all time scales. It controls the coupled protein-hydration water relaxation on 10 100 ps time scale. Our process defines the friction for slower protein dynamics. Analysis suggests that changes in amount of hydration water affect not only general friction, but also influence significantly the protein's energy landscape.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-Zone Liquid Thrust Chamber Performance Code with Domain Decomposition for Parallel Processing

Computational Fluid Dynamics (CFD) has considerably evolved in the last decade. There are many computer programs that can perform computations on viscous internal or external flows with chemical reactions. CFD has become a commonly used tool in the design and analysis of gas turbines, ramjet combustors, turbo-machinery, inlet ducts, rocket engines, jet interaction, missile, and ramjet nozzles. One of the problems of interest to NASA has always been the performance prediction for rocket and air-breathing engines. Due to the complexity of flow in these engines it is necessary to resolve the flowfield into a fine mesh to capture quantities like turbulence and heat transfer. However, calculation on a high-resolution grid is associated with a prohibitively increasing computational time that can downgrade the value of the CFD for practical engineering calculations. The Liquid Thrust Chamber Performance (LTCP) code was developed for NASA/MSFC (Marshall Space Flight Center) to perform liquid rocket engine performance calculations. This code is a 2D/axisymmetric full Navier-Stokes (NS) solver with fully coupled finite rate chemistry and Eulerian treatment of liquid fuel and/or oxidizer droplets. One of the advantages of this code has been the resemblance of its input file to the JANNAF (Joint Army Navy NASA Air Force Interagency Propulsion Committee) standard TDK code, and its automatic grid generation for JANNAF defined combustion chamber wall geometry. These options minimize the learning effort for TDK users, and make the code a good candidate for performing engineering calculations. Although the LTCP code was developed for liquid rocket engines, it is a general-purpose code and has been used for solving many engineering problems. However, the single zone formulation of the LTCP has limited the code to be applicable to problems with complex geometry. Furthermore, the computational time becomes prohibitively large for high-resolution problems with chemistry, two-equation turbulence model, and two-phase flow. To overcome these limitations, the LTCP code is rewritten to include the multi-zone capability with domain decomposition that makes it suitable for parallel processing, i.e., enabling the code to run every zone or sub-domain on a separate processor. This can reduce the run time by a factor of 6 to 8, depending on the problem.

Homayun K. Navaz↗

Collisional damping rates for plasma waves

The distinction between the plasma dynamics dominated by collisional transport versus collective processes has never been rigorously addressed until recently. A recent paper [P. H. Yoon et al., Phys. Rev. E 93, 033203 (2016)] formulates for the first time, a unified kinetic theory in which collective processes and collisional dynamics are systematically incorporated from first principles. One of the outcomes of such a formalism is the rigorous derivation of collisional damping rates for Langmuir and ion-acoustic waves, which can be contrasted to the heuristic customary approach. However, the results are given only in formal mathematical expressions. The present brief communication numerically evaluates the rigorous collisional damping rates by considering the case of plasma particles with Maxwellian velocity distribution function so as to assess the consequence of the rigorous formalism in a quantitative manner. Comparison with the heuristic (“Spitzer”) formula shows that the accurate damping rates are much lower in magnitude than the conventional expression, which implies that the traditional approach over-estimates the importance of attenuation of plasma waves by collisional relaxation process. Such a finding may have a wide applicability ranging from laboratory to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-Speed Synchrotron X-ray Imaging Studies of the Ultrasound Shockwave and Enhanced Flow during Metal Solidification Processes

The highly dynamic behavior of ultrasonic bubble implosion in liquid metal, the multiphase liquid metal flow containing bubbles and particles, and the interaction between ultrasonic waves and semisolid phases during solidification of metal were studied in situ using the complementary ultrafast and high-speed synchrotron X-ray imaging facilities housed, respectively, at the Advanced Photon Source, Argonne National Laboratory, US, and Diamond Light Source, UK. Real-time ultrafast X-ray imaging of 135,780 frames per second revealed that ultrasonic bubble implosion in a liquid Bi-8 wt pctZn alloy can occur in a single wave period (30 kHz), and the effective region affected by the shockwave at implosion was 3.5 times the original bubble diameter. Furthermore, ultrasound bubbles in liquid metal move faster than the primary particles, and the velocity of bubbles is 70 similar to 100 pct higher than that of the primary particles present in the same locations close to the sonotrode. Ultrasound waves can very effectively create a strong swirling flow in a semisolid melt in less than one second. The energetic flow can detach solid particles from the liquid-solid interface and redistribute them back into the bulk liquid very effectively.

Tan, Dongyue↗

Dopant effects on 2-ethyl-1-hexanol: A dual-channel impedance spectroscopy and neutron scattering study

A two-channel impedance technique has been used to study the relaxation behavior of 2-ethyl-1-hexanol with polar and non-polar dopants at the few percent concentration level over a wide temperature and frequency range. The non-polar dopants shift both the Debye and the primary structural relaxation time in the same direction, to shorter times for 3-methylpentane and to longer times for squalane, consistent with the relative glass transition temperatures (T{sub g}) of the components. By contrast, polar dopants such as water or methanol modify the α-process towards slower dynamics and increased amplitude, while the Debye process is accelerated and with a decreased amplitude. This effect of adding water to alcohol is explained by water promoting more compact structures with reduced Kirkwood correlation factors. This picture is consistent with a shift in the neutron scattering pre-peak to lower scattering vectors and with simulation work on alcohol-water systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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)↗

The opportunities offered by SCADM for the study of surface phenomena related to interior structure and dynamics

The physical processes to be probed by experiments may be grouped as large scale flows, oscillations, and chromospheric/coronal diagnostics. While the fundamental concerns and observational equipments are similar within each class, different investigations may tell different things about the Sun. Observational requirements are listed for experiments to study (1) plasma-magnetic field interactions; (2) interior structure via oscillations; (3) chromospheric and coronal tracers; (4) rotation, meridional flows, and giant cells; (5) the depth dependence of rotation; (6) EUV luminosity; (7) intensity fluctuations and tracers; and (8) diameter oscillations, the effects of noise and timestring on experiment results are assessed.

Brown, T. M.↗

Computer simulation of surface and film processes

A molecular dynamics technique based upon Lennard-Jones type pair interactions is used to investigate time-dependent as well as equilibrium properties. The case study deals with systems containing Si and O atoms. In this case a more involved potential energy function (PEF) is employed and the system is simulated via a Monte-Carlo procedure. This furnishes the equilibrium properties of the system at its interfaces and surfaces as well as in the bulk.

Tiller, W. A.↗

Coastal Observations of Weather Features in Senegal during the AMMA SOP-3 Period

During 15 August through 30 September 2006, ground and aircraft measurements were obtained from a multi-national group of students and scientists in Senegal. Key measurements were aimed at investigating and understanding precipitation processes, thermodynamic and dynamic environmental conditions, cloud, aerosol and microphysical processes and spaceborne sensors (TRMM, CloudSat/Calipso) validation. Ground and aircraft instruments include: ground based polarimetric radar, disdrometer measurements, a course and a high-density rain gauge network, surface chemical measurements, a 10 m flux tower, broadband IR, solar and microwave measurements, rawinsonde and radiosonde measurements, FA-20 dropsonde, in situ microphysics and cloud radar measurements. Highlights during SOP3 include ground and aircraft measurements of squall lines, African Easterly Waves (AEWs), Saharan Air Layer advances into Senegal, and aircraft measurements of AEWs -- including the perturbation that became Hurricane Isaac.

Jenkins, G.↗