In recent years, machine learning (ML) methods have become increasingly popular in computational chemistry. After being trained on appropriate ab initio reference data, these methods allow for ...accurately predicting the properties of chemical systems, circumventing the need for explicitly solving the electronic Schrödinger equation. Because of their computational efficiency and scalability to large data sets, deep neural networks (DNNs) are a particularly promising ML algorithm for chemical applications. This work introduces PhysNet, a DNN architecture designed for predicting energies, forces, and dipole moments of chemical systems. PhysNet achieves state-of-the-art performance on the QM9, MD17, and ISO17 benchmarks. Further, two new data sets are generated in order to probe the performance of ML models for describing chemical reactions, long-range interactions, and condensed phase systems. It is shown that explicitly including electrostatics in energy predictions is crucial for a qualitatively correct description of the asymptotic regions of a potential energy surface (PES). PhysNet models trained on a systematically constructed set of small peptide fragments (at most eight heavy atoms) are able to generalize to considerably larger proteins like deca-alanine (Ala10): The optimized geometry of helical Ala10 predicted by PhysNet is virtually identical to ab initio results (RMSD = 0.21 Å). By running unbiased molecular dynamics (MD) simulations of Ala10 on the PhysNet-PES in gas phase, it is found that instead of a helical structure, Ala10 folds into a “wreath-shaped” configuration, which is more stable than the helical form by 0.46 kcal mol–1 according to the reference ab initio calculations.
We consider the frequency domain form of proper orthogonal decomposition (POD), called spectral proper orthogonal decomposition (SPOD). Spectral POD is derived from a space–time POD problem for ...statistically stationary flows and leads to modes that each oscillate at a single frequency. This form of POD goes back to the original work of Lumley (Stochastic Tools in Turbulence, Academic Press, 1970), but has been overshadowed by a space-only form of POD since the 1990s. We clarify the relationship between these two forms of POD and show that SPOD modes represent structures that evolve coherently in space and time, while space-only POD modes in general do not. We also establish a relationship between SPOD and dynamic mode decomposition (DMD); we show that SPOD modes are in fact optimally averaged DMD modes obtained from an ensemble DMD problem for stationary flows. Accordingly, SPOD modes represent structures that are dynamic in the same sense as DMD modes but also optimally account for the statistical variability of turbulent flows. Finally, we establish a connection between SPOD and resolvent analysis. The key observation is that the resolvent-mode expansion coefficients must be regarded as statistical quantities to ensure convergent approximations of the flow statistics. When the expansion coefficients are uncorrelated, we show that SPOD and resolvent modes are identical. Our theoretical results and the overall utility of SPOD are demonstrated using two example problems: the complex Ginzburg–Landau equation and a turbulent jet.
CD4＋ T lymphocytes represent the main target cell population of human immunodeficiency virus （HIV）. In an activated state, CD4＋ T cells residing in lymphoid organs are a major reservoir of ongoing ...HIV-1 replication in in- fected individuals. In contrast, resting CD4＋ T cells are highly resistant to productive HIV-1 infection, yet are mas- sively depleted during disease progression and represent a substantial latent reservoir for the virus in vivo. Barriers preventing replication of HIV-1 in resting CD4＋ T cells include a rigid layer of cortical actin and, early after HIV-1 entry, a block that limits reverse transcription of incoming viral RNA genomes. Defining the molecular bases of these restrictions has remained one of the central open questions in HIV research. Recent advances unraveled mechanisms by which HIV-1 bypasses the entry block and established the host cell restriction factor SAMHDI, a deoxynucleoside tripbosphate triphosphohydrolase, as a central determinant of the cellular restriction to HIV-1 reverse transcription in resting CD4＋ T cells. This review summarizes our current molecular and pathophysiological understanding of the mnlti-faceted interactions of HIV-1 with resting CD4＋ T lymphocytes.
Four different applications of spectral proper orthogonal decomposition (SPOD) are demonstrated on large-eddy simulation data of a turbulent jet. These are: low-rank reconstruction, denoising, ...frequency–time analysis and prewhitening. We demonstrate SPOD-based flow-field reconstruction using direct inversion of the SPOD algorithm (frequency-domain approach) and propose an alternative approach based on projection of the time series data onto the modes (time-domain approach). We further present a SPOD-based denoising strategy that is based on hard thresholding of the SPOD eigenvalues. The proposed strategy achieves significant noise reduction while facilitating drastic data compression. In contrast to standard methods of frequency–time analysis such as wavelet transform, a proposed SPOD-based approach yields a spectrogram that characterises the temporal evolution of spatially coherent flow structures. A convolution-based strategy is proposed to compute the time-continuous expansion coefficients. When applied to the turbulent jet data, SPOD-based frequency–time analysis reveals that the intermittent occurrence of large-scale coherent structures is directly associated with high-energy events. This work suggests that the time-domain approach is preferable for low-rank reconstruction of individual snapshots, and the frequency-domain approach for denoising and frequency–time analysis.
Triadic interactions are the fundamental mechanism of energy transfer in fluid flows. This work introduces bispectral mode decomposition as a direct means of educing flow structures that are ...associated with triadic interactions from experimental or numerical data. Triadic interactions are characterized by quadratic phase coupling which can be detected by the bispectrum. The proposed method maximizes an integral measure of this third-order statistic to compute modes associated with frequency triads, as well as a mode bispectrum that identifies resonant three-wave interactions. Unlike the classical bispectrum, the decomposition establishes a causal relationship between the three frequency components of a triad. This permits the distinction of sum- and difference-interactions, and the computation of interaction maps that indicate regions of nonlinear coupling. Three examples highlight different aspects of the method. Cascading triads and their regions of interaction are educed from direct numerical simulation data of laminar cylinder flow. It is further demonstrated that linear instability mechanisms that attain an appreciable amplitude are revealed indirectly by their difference-self-interactions. Applicability to turbulent flows and noise-rejection is demonstrated on particle image velocimetry data of a massively separated wake. The generation of sub- and ultra-harmonics in large eddy simulation data of a transitional jet is explained by extending the method to cross-bispectral information.
Spectral analysis of jet turbulence Schmidt, Oliver T.; Towne, Aaron; Rigas, Georgios ...
Journal of fluid mechanics,
11/2018, Letnik:
855
Journal Article
Recenzirano
Odprti dostop
Informed by large-eddy simulation (LES) data and resolvent analysis of the mean flow, we examine the structure of turbulence in jets in the subsonic, transonic and supersonic regimes. Spectral ...(frequency-space) proper orthogonal decomposition is used to extract energy spectra and decompose the flow into energy-ranked coherent structures. The educed structures are generally well predicted by the resolvent analysis. Over a range of low frequencies and the first few azimuthal mode numbers, these jets exhibit a low-rank response characterized by Kelvin–Helmholtz (KH) type wavepackets associated with the annular shear layer up to the end of the potential core and that are excited by forcing in the very-near-nozzle shear layer. These modes too have been experimentally observed before and predicted by quasi-parallel stability theory and other approximations – they comprise a considerable portion of the total turbulent energy. At still lower frequencies, particularly for the axisymmetric mode, and again at high frequencies for all azimuthal wavenumbers, the response is not low-rank, but consists of a family of similarly amplified modes. These modes, which are primarily active downstream of the potential core, are associated with the Orr mechanism. They occur also as subdominant modes in the range of frequencies dominated by the KH response. Our global analysis helps tie together previous observations based on local spatial stability theory, and explains why quasi-parallel predictions were successful at some frequencies and azimuthal wavenumbers, but failed at others.
Although it has been known for decades that stress influences memory performance, it was only recently shown that stress may alter the contribution of multiple, anatomically and functionally distinct ...memory systems to behavior. Here, we review recent animal and human studies demonstrating that stress promotes a shift from flexible ‘cognitive’ to rather rigid ‘habit’ memory systems and discuss, based on recent neuroimaging data in humans, the underlying brain mechanisms. We argue that, despite being generally adaptive, this stress-induced shift towards ‘habit’ memory may, in vulnerable individuals, be a risk factor for psychopathology.
Instrumental behavior can be controlled by goal-directed action-outcome and habitual stimulus-response processes that are supported by anatomically distinct brain systems. Based on previous findings ...showing that stress modulates the interaction of "cognitive" and "habit" memory systems, we asked in the presented study whether stress may coordinate goal-directed and habit processes in instrumental learning. For this purpose, participants were exposed to stress (socially evaluated cold pressor test) or a control condition before they were trained to perform two instrumental actions that were associated with two distinct food outcomes. After training, one of these food outcomes was selectively devalued as subjects were saturated with that food. Next, subjects were presented the two instrumental actions in extinction. Stress before training in the instrumental task rendered participants' behavior insensitive to the change in the value of the food outcomes, that is stress led to habit performance. Moreover, stress reduced subjects' explicit knowledge of the action-outcome contingencies. These results demonstrate for the first time that stress promotes habits at the expense of goal-directed performance in humans.
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