Creating Localized Amyloid Nucleation of Silk-Elastin-Like Peptide Polymer Using Atomic Force Microscopy

Research into amyloids was initially motivated by pathogenic amyloids involved in disease states such as Alzheimer's; however, new research implicates small oliogmeric species and not the mature fibers. This lack of toxicity has allowed for the development of amyloid-based biomaterials for use as nanowires, biosensors, and tissue regeneration. The directed self-assembly of peptides into amyloid-like fibers for use as biomaterials requires the ability to control both the nucleation location and growth direction of the fiber. We have used Atomic Force Microscopy to repeatedly stretch Silk-Elastin-Like Peptide Polymer (SELP) in the normal direction using continuous pulling in a force acquisition mode which has the ability to create nanodots of SELP at a specified location which are capable of nucleating SELP nanofibers. This work, if generalized to other amyloidogenic systems, may aid in the mechanistic understanding of the assembly process of both pathogenic and functional amyloids

Procedure for improving wildfire simulations using observations

This report suggests a variational update method for improving wildfire simulations using observations as feedback to update information. We first assume a onedimensional fire model for simplicity and present numerical simulations obtained in this case. As possible alternative approaches, we also discuss two other update methods: a particle filter method and an optimal control method

A Simple Model to Predict Scalar Dispersion within a Successively Thinned Loblolly Pine Canopy

Bark beetles kill millions of acres of trees in the United States annually by using chemical signaling to attack host trees en masse. As an attempt to control infestations, forest managers use synthetic semiochemical sources to attract beetles to traps and/or repel beetles from high-value resources such as trees and stands. The purpose of this study was to develop a simple numerical technique that may be used by forest managers as a guide in the placement of synthetic semiochemicals. The authors used a one-dimensional, one-equation turbulence model (k–lm) to drive a three-dimensional transport and dispersion model. Predictions were compared with observations from a unique tracer gas experiment conducted in a successively thinned loblolly pine canopy. Predictions of wind speed and turbulent kinetic energy compared well with observations. Scalar concentration was predicted well and trends of maximum observed concentration versus leaf area index were captured within 30 m of the release location. A hypothetical application of the numerical technique was conducted for a 12-day period to demonstrate the model’s usefulness to forest managers

A Simple Model to Predict Scalar Dispersion within a Successively Thinned Loblolly Pine Canopy

Bark beetles kill millions of acres of trees in the United States annually by using chemical signaling to attack host trees en masse. As an attempt to control infestations, forest managers use synthetic semiochemical sources to attract beetles to traps and/or repel beetles from high-value resources such as trees and stands. The purpose of this study was to develop a simple numerical technique that may be used by forest managers as a guide in the placement of synthetic semiochemicals. The authors used a one-dimensional, one-equation turbulence model (k–lm) to drive a three-dimensional transport and dispersion model. Predictions were compared with observations from a unique tracer gas experiment conducted in a successively thinned loblolly pine canopy. Predictions of wind speed and turbulent kinetic energy compared well with observations. Scalar concentration was predicted well and trends of maximum observed concentration versus leaf area index were captured within 30 m of the release location. A hypothetical application of the numerical technique was conducted for a 12-day period to demonstrate the model’s usefulness to forest managers

Ocean model-based covariates improve a marine fish stock assessment when observations are limited

The productivity of many fish populations is influenced by the environment, but developing environment-linked stock assessments remain challenging and current management of most commercial species assumes that stock productivity is time-invariant. In the Northeast United States, previous studies suggest that the recruitment of Southern New England-Mid Atlantic yellowtail flounder is closely related to the strength of the Cold Pool, a seasonally formed cold water mass on the continental shelf. Here, we developed three new indices that enhance the characterization of Cold Pool interannual variations using bottom temperature from a regional hindcast ocean model and a global ocean data assimilated hindcast. We associated these new indices to yellowtail flounder recruitment in a state–space, age-structured stock assessment framework using the Woods Hole Assessment Model. We demonstrate that incorporating Cold Pool effects on yellowtail flounder recruitment reduces the retrospective patterns and may improve the predictive skill of recruitment and, to a lesser extent, spawning stock biomass. We also show that the performance of the assessment models that incorporated ocean model-based indices is improved compared to the model using only the observation-based index. Instead of relying on limited subsurface observations, using validated ocean model products as environmental covariates in stock assessments may both improve predictions and facilitate operationalization.publishedVersio

Effects of impurities and vortices on the low-energy spin excitations in high-Tc materials

We review a theoretical scenario for the origin of the spin-glass phase of underdoped cuprate materials. In particular it is shown how disorder in a correlated d-wave superconductor generates a magnetic phase by inducing local droplets of antiferromagnetic order which eventually merge and form a quasi-long range ordered state. When correlations are sufficiently strong, disorder is unimportant for the generation of static magnetism but plays an additional role of pinning disordered stripe configurations. We calculate the spin excitations in a disordered spin-density wave phase, and show how disorder and/or applied magnetic fields lead to a slowing down of the dynamical spin fluctuations in agreement with neutron scattering and muon spin rotation (muSR) experiments.Comment: 4 pages, 3 figures, submitted for SNS2010 conference proceeding

Migratory behavior of aggregating male Tiger Grouper (Mycteroperca tigris) in Little Cayman, Cayman Islands

Tiger Grouper (Mycteroperca tigris) form fish spawning aggregations (FSAs) around the winter full moons (typically January through April) in the Caribbean. Males defend territories to attract mates in a lek-like reproductive strategy. Prior studies have documented rapid declines in populations with FSA-associated fisheries. This study examines the migratory behavior of adult male Tiger Grouper in Little Cayman, Cayman Islands, to better understand the impacts of aggregation fishing. As part of the Grouper Moon Project, we acoustically tagged ten spawning male Tiger Grouper at the western end of Little Cayman in February 2015. Using a hydrophone array surrounding the island, we tracked the movements of the tagged fish for 13 months. We observed 3 migratory strategies: resident fish (n = 2) that live at the FSA site, neighboring fish (n = 5) that live within 4 km of the site, and commuter fish (n = 3) that travel over 4 km for spawning. Fish began aggregating 2 days before the full moon and left 10–12 days after the full moon, from January to May. Regardless of migratory strategy, all tagged fish that aggregated after February 2015 returned to the west end FSA. However, in January 2016, one fish appeared to attend a different FSA closer to its presumed home territory. Tiger Grouper may establish multiple FSAs around Little Cayman, and males appear to attend FSAs near their home territories. Protracted spawning seasons, FSA site infidelity, and putative FSA catchments should all be considered to ensure sustainable fisheries management for this important species.publishedVersio

Protected fish spawning aggregations as self-replenishing reservoirs for regional recovery

Dispersal of eggs and larvae from spawning sites is critical to the population dynamics and conservation of marine fishes. For overfished species like critically endangered Nassau grouper (Epinephelus striatus), recovery depends on the fate of eggs spawned at the few remaining aggregation sites. Biophysical models can predict larval dispersal, yet these rely on assumed values of key parameters, such as diffusion and mortality rates, which have historically been difficult or impossible to estimate. We used in situ imaging to record three-dimensional positions of individual eggs and larvae in proximity to oceanographic drifters released into egg plumes from the largest known Nassau grouper spawning aggregation. We then estimated a diffusion–mortality model and applied it to previous years' drifter tracks to evaluate the possibility of retention versus export to nearby sites within 5 days of spawning. Results indicate that larvae were retained locally in 2011 and 2017, with 2011 recruitment being a substantial driver of population recovery on Little Cayman. Export to a nearby island with a depleted population occurred in 2016. After two decades of protection, the population appears to be self-replenishing but also capable of seeding recruitment in the region, supporting calls to incorporate spawning aggregation protections into fisheries management.publishedVersio

Seasonal prediction of bottom temperature on the Northeast U.S. Continental Shelf

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chen, Z., Kwon, Y.-O., Chen, K., Fratantoni, P., Gawarkiewicz, G., Joyce, T. M., Miller, T. J., Nye, J. A., Saba, V. S., & Stock, B. C. Seasonal prediction of bottom temperature on the Northeast U.S. Continental Shelf. Journal of Geophysical Research: Oceans, 126(5), (2021): e2021JC017187, https://doi.org/10.1029/2021JC017187.The Northeast U.S. shelf (NES) is an oceanographically dynamic marine ecosystem and supports some of the most valuable demersal fisheries in the world. A reliable prediction of NES environmental variables, particularly ocean bottom temperature, could lead to a significant improvement in demersal fisheries management. However, the current generation of climate model-based seasonal-to-interannual predictions exhibits limited prediction skill in this continental shelf environment. Here, we have developed a hierarchy of statistical seasonal predictions for NES bottom temperatures using an eddy-resolving ocean reanalysis data set. A simple, damped local persistence prediction model produces significant skill for lead times up to ∼5 months in the Mid-Atlantic Bight and up to ∼10 months in the Gulf of Maine, although the prediction skill varies notably by season. Considering temperature from a nearby or upstream (i.e., more poleward) region as an additional predictor generally improves prediction skill, presumably as a result of advective processes. Large-scale atmospheric and oceanic indices, such as Gulf Stream path indices (GSIs) and the North Atlantic Oscillation Index, are also tested as predictors for NES bottom temperatures. Only the GSI constructed from temperature observed at 200 m depth significantly improves the prediction skill relative to local persistence. However, the prediction skill from this GSI is not larger than that gained using models incorporating nearby or upstream shelf/slope temperatures. Based on these results, a simplified statistical model has been developed, which can be tailored to fisheries management for the NES.This work was supported by NOAA's Climate Program Office's Modeling, Analysis, Predictions, and Projections (MAPP) Program (NA17OAR4310111, NA19OAR4320074), and Climate Program Office's Climate Variability and Predictability (CVP) Program (NA20OAR4310482). We acknowledge our participation in MAPP's Marine Prediction Task Force

Yellow and Red Supergiants in the Large Magellanic Cloud

Due to their transitionary nature, yellow supergiants provide a critical challenge for evolutionary modeling. Previous studies within M31 and the SMC show that the Geneva evolutionary models do a poor job at predicting the lifetimes of these short-lived stars. Here we extend this study to the LMC while also investigating the galaxy's red supergiant content. This task is complicated by contamination by Galactic foreground stars that color and magnitude criteria alone cannot weed out. Therefore, we use proper motions and the LMC's large systemic radial velocity (\sim278 km/s) to separate out these foreground dwarfs. After observing nearly 2,000 stars, we identified 317 probable yellow supergiants, 6 possible yellow supergiants and 505 probable red supergiants. Foreground contamination of our yellow supergiant sample was \sim80%, while that of the the red supergiant sample was only 3%. By placing the yellow supergiants on the H-R diagram and comparing them against the evolutionary tracks, we find that new Geneva evolutionary models do an exemplary job at predicting both the locations and the lifetimes of these transitory objects.Comment: Accepted for publication in the Ap