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We explored neural processing differences associated with aging across four cognitive functions. In addition to ERP analysis, we included task-related microstate analyses, which identified stable states of neural activity across the scalp over time, to explore whole-head neural activation differences. Younger and older adults (YA, OA) completed face perception (N170), word-pair judgment (N400), visual oddball (P3), and flanker (ERN) tasks. Age-related effects differed across tasks. Despite age-related delayed latencies, N170 ERP and microstate analyses indicated no age-related differences in amplitudes or microstates. However, age-related condition differences were found for P3 and N00 amplitudes and scalp topographies: smaller condition differences were found for in OAs as well as broader centroparietal scalp distributions. Age group comparisons for the ERN revealed similar focal frontocentral activation loci, but differential activation patterns. Our findings of differential age effects across tasks are most consistent with the STAC-r framework which proposes that age-related effects differ depending on the resources available and the kinds of processing and cognitive load required of various tasks. 

Weak but persistent synoptic-scale ascent may play a role in the initiation or maintenance of nocturnal convection over the central United States. An analytical model is used to explore the nocturnal low-level jets (NLLJ) and ascent that develop in an idealized diurnally varying frictional (Ekman) boundary layer in a neutrally stratified barotropic environment when the flow aloft is a zonally propagating Rossby wave. Steady-periodic solutions are obtained of the linearized Reynolds-averaged Boussinesq-approximated equations of motion on a beta plane with an eddy viscosity that is specified to increase abruptly at sunrise and decrease abruptly at sunset. Rayleigh damping terms are used to parameterize momentum loss due to radiation of inertia–gravity waves. The model-predicted vertical velocity is (approximately) proportional to the wavenumber and wave amplitude. There are two main modes of ascent in midlatitudes, an afternoon mode and a nocturnal mode. The latter arises as a gentle but persistent surge induced by the decrease of turbulence at sunset, the same mechanism that triggers inertial oscillations in the Blackadar theory of NLLJs. If the Rayleigh damping terms are omitted, the boundary layer depth becomes infinite at three critical latitudes, and the vertical velocity becomes infinite far above the ground at two of those latitudes. With the damping terms retained, the solution is well behaved. Peak daytime ascent in the model occurs progressively later in the afternoon at more southern locations (in the Northern Hemisphere) until the first (most northern) critical latitude is reached; south of that latitude the nocturnal mode is dominant.

 

We integrated a mechanistic wildfire simulation system with an agent-based landscape change model to investigate the feedbacks among climate change, population growth, development, landowner decision-making, vegetative succession, and wildfire. Our goal was to develop an adaptable simulation platform for anticipating risk-mitigation tradeoffs in a fire-prone wildland–urban interface (WUI) facing conditions outside the bounds of experience. We describe how five social and ecological system (SES) submodels interact over time and space to generate highly variable alternative futures even within the same scenario as stochastic elements in simulated wildfire, succession, and landowner decisions create large sets of unique, path-dependent futures for analysis. We applied the modeling system to an 815 km2 study area in western Oregon at a sub-taxlot parcel grain and annual timestep, generating hundreds of alternative futures for 2007–2056 (50 years) to explore how WUI communities facing compound risks from increasing wildfire and expanding periurban development can situate and assess alternative risk management approaches in their localized SES context. The ability to link trends and uncertainties across many futures to processes and events that unfold in individual futures is central to the modeling system. By contrasting selected alternative futures, we illustrate how assessing simulated feedbacks between wildfire and other SES processes can identify tradeoffs and leverage points in fire-prone WUI landscapes. Assessments include a detailed “post-mortem” of a rare, extreme wildfire event, and uncovered, unexpected stabilizing feedbacks from treatment costs that reduced the effectiveness of agent responses to signs of increasing risk. 

Pupillary synchrony or contagion is the automatic unconscious mimicry of pupil dilation in dyadic interactions. This experiment explored electrophysiological event‐related potential (ERP) concomitants of pupillary synchrony. Artificial pupils (black dots) were superimposed on either partial faces (eyes, nose, brow) or random textures. Observers were asked to judge dot size (large, medium, or small). There was clear evidence of pupillary synchrony with observer pupil dilation greater to large dots than to small or medium dots. The pupillary synchrony increased in magnitude throughout the trial and was found both with faces and with textures. When the stimuli were partial faces with artificial pupils (dots), there was ERP activity related to target dot size in the period at P250 and P3. A face specific N170 was also found. When the stimuli were random textures with dots, there was ERP activity at P1 and in the interval from 140 to 200 ms post‐stimulus onset. The use of ERP with pupillometry revealed results for faces that were consistent with a social explanation of pupillary synchrony whereas results for textures were consistent with a local luminance explanation.

 

Methanobactins (MBs) are ribosomally produced and post-translationally modified peptides (RiPPs) that are used by methanotrophs for copper acquisition. The signature post-translational modification of MBs is the formation of two heterocyclic groups, either an oxazolone, pyrazinedione or imidazolone group, with an associated thioamide from an X -Cys dipeptide. The precursor peptide (MbnA) for MB formation is found in a gene cluster of MB-associated genes. The exact biosynthetic pathway of MB formation is not yet fully understood, and there are still uncharacterized proteins in some MB gene clusters, particularly those that produce pyrazinedione or imidazolone rings. One such protein is MbnF, which is proposed to be a flavin monooxygenase (FMO) based on homology. To help to elucidate its possible function, MbnF from Methylocystis sp. strain SB2 was recombinantly produced in Escherichia coli and its X-ray crystal structure was resolved to 2.6 Å resolution. Based on its structural features, MbnF appears to be a type A FMO, most of which catalyze hydroxylation reactions. Preliminary functional characterization shows that MbnF preferentially oxidizes NADPH over NADH, supporting NAD(P)H-mediated flavin reduction, which is the initial step in the reaction cycle of several type A FMO enzymes. It is also shown that MbnF binds the precursor peptide for MB, with subsequent loss of the leader peptide sequence as well as the last three C-terminal amino acids, suggesting that MbnF might be needed for this process to occur. Finally, molecular-dynamics simulations revealed a channel in MbnF that is capable of accommodating the core MbnA fragment minus the three C-terminal amino acids. 

Many scientific problems can be formulated as sparse regression, i.e., regression onto a set of parameters when there is a desire or expectation that some of the parameters are exactly zero or do not substantially contribute. This includes many problems in signal and image processing, system identification, optimization, and parameter estimation methods such as Gaussian process regression. Sparsity facilitates exploring high-dimensional spaces while finding parsimonious and interpretable solutions. In the present work, we illustrate some of the important ways in which sparse regression appears in plasma physics and point out recent contributions and remaining challenges to solving these problems in this field. A brief review is provided for the optimization problem and the state-of-the-art solvers, especially for constrained and high-dimensional sparse regression.

 

Highly time-resolved mechanical measurements, modeling, and simulations show that large shear bands in bulk metallic glasses nucleate in a manner similar to cracks. When small slips reach a nucleation size, the dynamics changes and the shear band rapidly grows to span the entire sample. Smaller nucleation sizes imply lower ductility. Ductility can be increased by increasing the nucleation size relative to the maximum (“cutoff”) shear band size at the upper edge of the power law scaling range of their size distribution. This can be achieved in three ways: (1) by increasing the nucleation size beyond this cutoff size of the shear bands, (2) by keeping all shear bands smaller than the nucleation size, or (3) by choosing a sample size smaller than the nucleation size. The discussed methods can also be used to rapidly order metallic glasses according to ductility.

 

The ability to create stimuli-responsive DNA nanostructures has played a prominent role in dynamic DNA nanotechnology. Primary among these is the process of toehold-based strand displacement, where a nucleic acid molecule can act as a trigger to cause conformational changes in custom-designed DNA nanostructures. Here, we add another layer of control to strand displacement reactions through a 'toehold clipping' process. By designing DNA complexes with a photocleavable linker-containing toehold or an RNA toehold, we show that we can use light (UV) or enzyme (ribonuclease) to eliminate the toehold, thus preventing strand displacement reactions. We use molecular dynamics simulations to analyze the structural effects of incorporating a photocleavable linker in DNA complexes. Beyond simple DNA duplexes, we also demonstrate the toehold clipping process in a model DNA nanostructure, by designing a toehold containing double-bundle DNA tetrahedron that disassembles when an invading strand is added, but stays intact after the toehold clipping process even in the presence of the invading strand. This work is an example of combining multiple physical or molecular stimuli to provide additional remote control over DNA nanostructure reconfiguration, advances that hold potential use in biosensing, drug delivery or molecular computation.

 

Abstract Alfvén eigenmodes (AEs) are an important and complex class of plasma dynamics commonly observed in tokamaks and other plasma devices. In this work, we manually labeled a small database of 26 discharges from the DIII-D tokamak in order to train simple neural-network-based models for classifying AEs. The models provide spatiotemporally local identification of four types of AEs by using an array of 40 electron cyclotron emission (ECE) signals as inputs. Despite the minimal dataset, this strategy performs well at spatiotemporally localized classification of AEs, indicating future opportunities for more sophisticated models and incorporation into real-time control strategies. The trained model is then used to generate spatiotemporally-resolved labels for each of the 40 ECE measurements on a much larger database of 1112 DIII-D discharges. This large set of precision labels can be used in future studies for advanced deep predictors and new physical insights.