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Continent‐scale observations of seismic phenomena have provided multi‐scale constraints of the Earth's interior. Of those analyzed, array‐based observations of slowness vector properties (backazimuth and horizontal slowness) and multipathing have yet to be made on a continental scale. Slowness vector measurements give inferences on mantle heterogeneity properties such as velocity perturbation and velocity gradient strength and quantify their effect on the wavefield. Multipathing is a consequence of waves interacting with strong velocity gradients resulting in two arrivals with different slowness vector properties and times. The mantle structure beneath the contiguous Unites States has been thoroughly analyzed by previous seismic studies and is data‐rich, making it an excellent testing ground to both analyze mantle structure with our approach and compare with other imaging techniques. We apply an automated array‐analysis technique to an SKS data set to create the first continent‐scale data set of multipathing and slowness vector measurements. We analyze the divergence of the slowness vector deviation field to highlight seismically slow and fast regions. Our results resolve several slow mantle anomalies beneath Yellowstone, the Appalachian mountains and fast anomalies throughout the mantle. Many of the anomalies cause multipathing in frequency bands 0.15–0.30 and 0.20–0.40 Hz which suggests velocity transitions over at most 500 km exist. Comparing our observations to synthetics created from tomography models, we find model NA13 (Bedle et al., 2021,https://doi.org/10.1029/2021GC009674) fits our data best but differences still remain. We therefore suggest slowness vector measurements should be used as an additional constraint in tomographic inversions and will lead to better resolved models of the mantle.

 

The blue mussel (Mytilus edulis) is a suspension feeder which has been used in gut‐microbiome surveys. Although raw 16S sequence data are often publicly available, unifying secondary analyses are lacking. The present work analysed raw data from seven projects conducted by one group over 7 years. Although each project had different motivations, experimental designs and conclusions, all selected samples were from the guts ofM. eduliscollected from a single location in Long Island Sound. The goal of this analysis was to determine which independent factors (e.g., collection date, depuration status) were responsible for governing composition and diversity in the gut microbiomes. Results indicated that whether mussels had undergone depuration, defined here as voidance of faeces in a controlled, no‐food period, was the primary factor that governed gut microbiome composition. Gut microbiomes from non‐depurated mussels were mixtures of resident and transient communities and were influenced by temporal factors. Resident communities from depurated mussels were influenced by the final food source and length of time host mussels were held under laboratory conditions. These findings reinforce the paradigm that gut microbiota are divided into resident and transient components and suggest that depuration status should be taken into consideration when designing and interpreting future experiments.

 

SUMMARY Horizontal slowness vector measurements using array techniques have been used to analyse many Earth phenomena from lower mantle heterogeneity to meteorological event location. While providing observations essential for studying much of the Earth, slowness vector analysis is limited by the necessary and subjective visual inspection of observations. Furthermore, it is challenging to determine the uncertainties caused by limitations of array processing such as array geometry, local structure, noise and their effect on slowness vector measurements. To address these issues, we present a method to automatically identify seismic arrivals and measure their slowness vector properties with uncertainty bounds. We do this by bootstrap sampling waveforms, therefore also creating random sub arrays, then use linear beamforming to measure the coherent power at a range of slowness vectors. For each bootstrap sample, we take the top N peaks from each power distribution as the slowness vectors of possible arrivals. The slowness vectors of all bootstrap samples are gathered and the clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is used to identify arrivals as clusters of slowness vectors. The mean of slowness vectors in each cluster gives the slowness vector measurement for that arrival and the distribution of slowness vectors in each cluster gives the uncertainty estimate. We tuned the parameters of DBSCAN using a data set of 2489 SKS and SKKS observations at a range of frequency bands from 0.1 to 1 Hz. We then present examples at higher frequencies (0.5–2.0 Hz) than the tuning data set, identifying PKP precursors, and lower frequency by identifying multipathing in surface waves (0.04–0.06 Hz). While we use a linear beamforming process, this method can be implemented with any beamforming process such as cross correlation beamforming or phase weighted stacking. This method allows for much larger data sets to be analysed without visual inspection of data. Phenomena such as multipathing, reflections or scattering can be identified automatically in body or surface waves and their properties analysed with uncertainties. 

Long-range transport of biogenic emissions from the coast of Antarctica, precipitation scavenging, and cloud processing are the main processes that influence the observed variability in Southern Ocean (SO) marine boundary layer (MBL) condensation nuclei (CN) and cloud condensation nuclei (CCN) concentrations during the austral summer. Airborne particle measurements on the HIAPER GV from north-south transects between Hobart, Tasmania and 62°S during the Southern Ocean Clouds, Radiation Aerosol Transport Experimental Study (SOCRATES) were separated into four regimes comprising combinations of high and low concentrations of CCN and CN. In 5-day HYSPLIT back trajectories, air parcels with elevated CCN concentrations were almost always shown to have crossed the Antarctic coast, a location with elevated phytoplankton emissions relative to the rest of the SO in the region south of Australia. The presence of high CCN concentrations was also consistent with high cloud fractions over their trajectory, suggesting there was substantial growth of biogenically formed particles through cloud processing. Cases with low cloud fraction, due to the presence of cumulus clouds, had high CN concentrations, consistent with previously reported new particle formation in cumulus outflow regions. Measurements associated with elevated precipitation during the previous 1.5-days of their trajectory had low CCN concentrations indicating CCN were effectively scavenged by precipitation. A coarse-mode fitting algorithm was used to determine the primary marine aerosol (PMA) contribution which accounted for < 20% of CCN (at 0.3% supersaturation) and cloud droplet number concentrations. Vertical profiles of CN and large particle concentrations (Dp > 0.07µm) indicated that particle formation occurs more frequently above the MBL; however, the growth of recently formed particles typically occurs in the MBL, consistent with cloud processing and the condensation of volatile compound oxidation products. 

Stratocumulus clouds over the Southern Ocean have fewer droplets and are more likely to exist in the predominately supercooled phase than clouds at similar temperatures over northern oceans. One likely reason is that this region has few continental and anthropogenic sources of cloud-nucleating particles that can form droplets and ice. In this work, we present an overview of aerosol particle types over the Southern Ocean, including new measurements made below, in and above clouds in this region. These measurements and others indicate that biogenic sulfur-based particles >0.1 μm diameter contribute the majority of cloud condensation nuclei number concentrations in summer. Ice nucleating particles tend to have more organic components, likely from sea-spray. Both types of cloud nucleating particles may increase in a warming climate likely to have less sea ice, more phytoplankton activity, and stronger winds over the Southern Ocean near Antarctica. Taken together, clouds over the Southern Ocean may become more reflective and partially counter the region’s expected albedo decrease due to diminishing sea ice. However, detailed modeling studies are needed to test this hypothesis due to the complexity of ocean-cloud-climate feedbacks in the region. 

Suspension‐feeding bivalves are critical members of aquatic ecosystems worldwide, which is why research into their host‐associated microbiota is growing. Experiments that artificially diminish the native microbial communities of bivalvesin vivowill be increasingly necessary to evaluate the functional role of microbes within their hosts. Previous methods to manipulate the microbiome of bivalves lack standardization and, often, verification of successful disturbance. The goal of this study was to evaluate antibiotic administration as a method for perturbing the gut microbiome of bivalves in two separate, but related, experiments. In the first, a mixture of antibiotics was delivered to eastern oysters for 4 days to probe effects on gut microbial carbon usage, diversity, and taxonomic composition. In the second, the same antibiotic mixture was administered to blue mussels for 21 days to probe effects on microbial abundance, diversity, and taxonomic composition. In both experiments, animals were administered antibiotics in isolation, and stringent sterilization methods were employed, which included sterilized seawater and microalgal food. The results of the oyster experiment revealed that antibiotics substantially reduced microbial carbon usage and perturbed community composition. In the mussel experiment, antibiotics lowered microbial abundance and species richness and significantly altered community composition. Taken together, results from the two experiments demonstrate that antibiotics can be used to effectively alter the function and composition of the gut microbial community of bivalves. Future research that aims to perturb the microbiomes of suspension‐feeding animals should incorporate aspects similar to the protocols described herein. Additionally, future studies must include verification, ideally high‐throughput DNA sequencing coupled with microbial quantification, that the antibiotic perturbation was successful.

 

Memristive devices are promising candidates to emulate biological computing. However, the typical switching voltages (0.2-2 V) in previously described devices are much higher than the amplitude in biological counterparts. Here we demonstrate a type of diffusive memristor, fabricated from the protein nanowires harvested from the bacterium Geobacter sulfurreducens, that functions at the biological voltages of 40-100 mV. Memristive function at biological voltages is possible because the protein nanowires catalyze metallization. Artificial neurons built from these memristors not only function at biological action potentials (e.g., 100 mV, 1 ms) but also exhibit temporal integration close to that in biological neurons. The potential of using the memristor to directly process biosensing signals is also demonstrated. 

This paper describes the creation of a virtual, interactive professional development course to build the capacity of community college faculty to recruit and retain women and underrepresented minorities in computing programs. The project was designed in response to community college faculty reporting need for practical methods to broaden participation in their programs and their feelings of isolation from like-minded faculty. The 12-session prototype has been piloted with eight community college faculty. The finalized PD will be available as free, standalone web-based modules. The course includes instruction on research-based practices for recruiting and retaining women and underrepresented minorities in computing. Evaluation mechanisms are developed to assess the impacts of the PD on faculty attitudes and teaching practices, and the effect of changed practices on introductory computing students’ engagement and persistence. Here we report preliminary findings from interviews. The project outputs will include polished online content modules, validated student survey instruments, a classroom observation protocol, and student and faculty interview instruments.