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Wildfires are increasing in size, frequency, and intensity, releasing increased amounts of contaminants, including magnetic particles, into the surrounding environment. The aim of this paper is to develop a sensing method for the detection and quantification of magnetic particles (MPs) in fire ash and fire runoff using a compact Time-Domain Nuclear Magnetic Resonance (TD-NMR) system. The system is made up of custom NMR electronics with a compact and rugged permanent magnet array designed to enable future deployment as an in situ sensor. A signal-to-noise ratio of 25 dB was measured for a single scan, and sufficient data can be acquired in one minute. A linear relationship with an R 2 value of 0.9699 was established between transverse relaxation rates and MP concentrations in ash samples. This was validated by testing known dilutions of pure magnetite particles and showing that they fit within the same linear curve. The developed approach was then applied to detect MPs in surface water, where changes in the relaxation rates as high as 400% were observed before and after a wildfire event. MPs were removed from the surface water using a magnetic particle separator to confirm that observed changes were solely due to the presence ofmore »MPs. The compact NMR system can be used as a simple and rapid approach to track and quantify the concentrations of magnetic particles released from fire ashes and also from other sources such as discharges from coal ash and other combustion ashes.« less

The first aromatic Claisen rearrangement of a 1,2-azaborine is described along with a quantitative kinetic comparison of the reaction of the azaborine with its direct all-carbon analogue. The azaborine A rearranged in a clean, regioselective fashion and reacted faster than the all-carbon substrate B at all temperatures from 140–180 °C. Activation free energies were extracted from observed first-order rate constants (A: Δ G ‡298K = 32.7 kcal mol −1 ; B: Δ G ‡298K = 34.8 kcal mol −1 ) corresponding to a twenty fold faster rate for A at observed reaction temperatures. DFT calculations show that the rearrangement proceeds via a concerted six-membered transition state and that the electronic structure of the BN and CC rings is mostly responsible for the observed regioselectivity and relative reactivity.

We present a study of the molecular gas of seven early-type galaxies with high angular resolution data obtained as part of the mm-Wave Interferometric Survey of Dark Object Masses (WISDOM) project with the Atacama Large Millimeter/submillimeter Array. Using a fixed spatial-scale approach, we study the mass surface density (Σ) and velocity dispersion (σ) of the molecular gas on spatial scales ranging from 60 to 120 pc. Given the spatial resolution of our data (20–70 pc), we characterize these properties across many thousands of individual sightlines (≈50 000 at our highest physical resolution). The molecular gas along these sightlines has a large range (≈2 dex) of mass surface densities and velocity dispersions $\approx 40~{{\ \rm per\ cent}}$ higher than those of star-forming spiral galaxies. It has virial parameters αvir that depend weakly on the physical scale observed, likely due to beam smearing of the bulk galactic rotation, and is generally supervirial. Comparing the internal turbulent pressure (Pturb) to the pressure required for dynamic equilibrium (PDE), the ratio Pturb/PDE is significantly less than unity in all galaxies, indicating that the gas is not in dynamic equilibrium and is strongly compressed, in apparent contradiction to the virial parameters. This may be due to ourmore »neglect of shear and tidal forces, and/or the combination of three-dimensional and vertical diagnostics. Both αvir and Pturb anticorrelate with the global star-formation rate of our galaxies. We therefore conclude that the molecular gas in early-type galaxies is likely unbound, and that large-scale dynamics likely plays a critical role in its regulation. This contrasts to the giant molecular clouds in the discs of late-type galaxies, that are much closer to dynamical equilibrium.

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ABSTRACT Organisms such as jumping froghopper insects and punching mantis shrimp use spring-based propulsion to achieve fast motion. Studies of elastic mechanisms have primarily focused on fully developed and functional mechanisms in adult organisms. However, the ontogeny and development of these mechanisms can provide important insights into the lower size limits of spring-based propulsion, the ecological or behavioral relevance of ultrafast movement, and the scaling of ultrafast movement. Here, we examined the development of the spring-latch mechanism in the bigclaw snapping shrimp, Alpheus heterochaelis (Alpheidae). Adult snapping shrimp use an enlarged claw to produce high-speed strikes that generate cavitation bubbles. However, until now, it was unclear when the elastic mechanism emerges during development and whether juvenile snapping shrimp can generate cavitation at this size. We reared A. heterochaelis from eggs, through their larval and postlarval stages. Starting 1 month after hatching, the snapping shrimp snapping claw gradually developed a spring-actuated mechanism and began snapping. We used high-speed videography (300,000 frames s−1) to measure juvenile snaps. We discovered that juvenile snapping shrimp generate the highest recorded accelerations (5.8×105±3.3×105 m s−2) for repeated-use, underwater motion and are capable of producing cavitation at the millimeter scale. The angular velocity of snaps did not change as juveniles grew; however,more »juvenile snapping shrimp with larger claws produced faster linear speeds and generated larger, longer-lasting cavitation bubbles. These findings establish the development of the elastic mechanism and cavitation in snapping shrimp and provide insights into early life-history transitions in spring-actuated mechanisms.« less

Advances in artificial intelligence have inspired a paradigm shift in human neuroscience, yielding large-scale functional magnetic resonance imaging (fMRI) datasets that provide high-resolution brain responses to thousands of naturalistic visual stimuli. Because such experiments necessarily involve brief stimulus durations and few repetitions of each stimulus, achieving sufficient signal-to-noise ratio can be a major challenge. We address this challenge by introducing GLMsingle , a scalable, user-friendly toolbox available in MATLAB and Python that enables accurate estimation of single-trial fMRI responses ( glmsingle.org ). Requiring only fMRI time-series data and a design matrix as inputs, GLMsingle integrates three techniques for improving the accuracy of trial-wise general linear model (GLM) beta estimates. First, for each voxel, a custom hemodynamic response function (HRF) is identified from a library of candidate functions. Second, cross-validation is used to derive a set of noise regressors from voxels unrelated to the experiment. Third, to improve the stability of beta estimates for closely spaced trials, betas are regularized on a voxel-wise basis using ridge regression. Applying GLMsingle to the Natural Scenes Dataset and BOLD5000, we find that GLMsingle substantially improves the reliability of beta estimates across visually-responsive cortex in all subjects. Comparable improvements in reliability are also observed inmore »a smaller-scale auditory dataset from the StudyForrest experiment. These improvements translate into tangible benefits for higher-level analyses relevant to systems and cognitive neuroscience. We demonstrate that GLMsingle: (i) helps decorrelate response estimates between trials nearby in time; (ii) enhances representational similarity between subjects within and across datasets; and (iii) boosts one-versus-many decoding of visual stimuli. GLMsingle is a publicly available tool that can significantly improve the quality of past, present, and future neuroimaging datasets sampling brain activity across many experimental conditions.« less