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1. Neogene echinoids of Florida

   Osborn, A. S. ; Portell, R. W. ; Mooi, R. ( July 2020 , Bulletin of the Florida Museum of Natural History)

   Forty-three species, and five indeterminate taxa of Florida Neogene echinoids are discussed and their geographic and stratigraphic distributions provided. These include 16 species documented from the Pleistocene, 20 from the Pliocene, and 12 from the Miocene. Eight new species are described: Rhyncholampas meansi n. sp. from the Pleistocene; Fernandezaster whisleri n. sp., Genocidaris oyeni n. sp., and Lovenia kerneri n. sp. from the Pliocene; and Clypeaster petersonorum n. sp., Gagaria hunterae n. sp., Brissopsis hoffmani n. sp., and Abertella carlsoni n. sp. from the Miocene. Additionally, we herein recognize Abertella floridana, from the Sopchoppy Limestone, as a species distinct from Abertella aberti, and provide the first documentation of Echinolampas lycopersicus, Rhyncholampas sabistonensis, and Arbia aldrichi from the fossil record of Florida. We update the taxonomy for all referred species and their known distributions. This document is intended to be a compilation of the entire Neogene echinoid record from Florida, which is now understood to have the most speciose and diverse assemblage of Neogene echinoids in the eastern United States. 

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2. Inferring the size of a collective of self-propelled Vicsek particles from the random motion of a single unit

   https://doi.org/10.1038/s42005-022-00864-9  

   De Lellis, Pietro ; Porfiri, Maurizio ( April 2022 , Communications Physics)

   Inferring the size of a collective from the motion of a few accessible units is a fundamental problem in network science and interdisciplinary physics. Here, we recognize stochasticity as the commodity traded in the units’ interactions. Drawing inspiration from the work of Einstein-Perrin-Smoluchowski on the discontinuous structure of matter, we use the random motion of one unit to identify the footprint of every other unit. Just as the Avogadro’s number can be determined from the Brownian motion of a suspended particle in a liquid, the size of the collective can be inferred from the random motion of any unit. For self-propelled Vicsek particles, we demonstrate an inverse proportionality between the diffusion coefficient of the heading of any particle and the size of the collective. We provide a rigorous method to infer the size of a collective from measurements of a few units, strengthening the link between physics and collective behavior.

    

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3. Validation of Deep Learning Segmentation of CT Images of Fiber-Reinforced Composites

   https://doi.org/10.3390/jcs6020060  

   Badran, Aly ; Parkinson, Dula ; Ushizima, Daniela ; Marshall, David ; Maillet, Emmanuel ( February 2022 , Journal of Composites Science)

   Micro-computed tomography (µCT) is a valuable tool for visualizing microstructures and damage in fiber-reinforced composites. However, the large sets of data generated by µCT present a barrier to extracting quantitative information. Deep learning models have shown promise for overcoming this barrier by enabling automated segmentation of features of interest from the images. However, robust validation methods have not yet been used to quantify the success rate of the models and the ability to extract accurate measurements from the segmented image. In this paper, we evaluate the detection rate for segmenting fibers in low-contrast CT images using a deep learning model with three different approaches for defining the reference (ground-truth) image. The feasibility of measuring sub-pixel feature dimensions from the µCT image, in certain cases where the µCT image intensity is dependent on the feature dimensions, is assessed and calibrated using a higher-resolution image from a polished cross-section of the test specimen in the same location as the µCT image. 

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4. Comparison of metagenomes from fermentation of various agroindustrial residues suggests a common model of community organization

   https://doi.org/10.3389/fbioe.2023.1197175  

   Myers, Kevin S. ; Ingle, Abel T. ; Walters, Kevin A. ; Fortney, Nathaniel W. ; Scarborough, Matthew J. ; Donohue, Timothy J. ; Noguera, Daniel R. ( May 2023 , Frontiers in Bioengineering and Biotechnology)

   Strik, David (Ed.)

   The liquid residue resulting from various agroindustrial processes is both rich in organic material and an attractive source to produce a variety of chemicals. Using microbial communities to produce chemicals from these liquid residues is an active area of research, but it is unclear how to deploy microbial communities to produce specific products from the different agroindustrial residues. To address this, we fed anaerobic bioreactors one of several agroindustrial residues (carbohydrate-rich lignocellulosic fermentation conversion residue, xylose, dairy manure hydrolysate, ultra-filtered milk permeate, and thin stillage from a starch bioethanol plant) and inoculated them with a microbial community from an acid-phase digester operated at the wastewater treatment plant in Madison, WI, United States. The bioreactors were monitored over a period of months and sampled to assess microbial community composition and extracellular fermentation products. We obtained metagenome assembled genomes (MAGs) from the microbial communities in each bioreactor and performed comparative genomic analyses to identify common microorganisms, as well as any community members that were unique to each reactor. Collectively, we obtained a dataset of 217 non-redundant MAGs from these bioreactors. This metagenome assembled genome dataset was used to evaluate whether a specific microbial ecology model in which medium chain fatty acids (MCFAs) are simultaneously produced from intermediate products (e.g., lactic acid) and carbohydrates could be applicable to all fermentation systems, regardless of the feedstock. MAGs were classified using a multiclass classification machine learning algorithm into three groups, organisms fermenting the carbohydrates to intermediate products, organisms utilizing the intermediate products to produce MCFAs, and organisms producing MCFAs directly from carbohydrates. This analysis revealed common biological functions among the microbial communities in different bioreactors, and although different microorganisms were enriched depending on the agroindustrial residue tested, the results supported the conclusion that the microbial ecology model tested was appropriate to explain the MCFA production potential from all agricultural residues.

    

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5. Nonparametric Reconstruction of Vector Fields From Noisy Observations of Their Flow Curves

   https://doi.org/10.23919/ACC50511.2021.9482622  

   Sneed, Terry-Ann ; Komaee, Arash ( January 2021 , 2021 American Control Conference (ACC 2021))

   null (Ed.)

   In an ordinary differential equation represented by a set of state-space equations, the differential of the state vector is given by the values of a vector field evaluated at the values of the state vector. This paper focuses on the reconstruction of this vector field from noisy measurements of the state trajectories generated empirically from a physical process. For this estimation problem, a nonparametric least squares formulation is presented, which is then expressed as a linear quadratic tracking problem with a well known solution from the optimal control theory. This approach is demonstrated for experimental reconstruction of the magnetic force field around a permanent magnet from the motion trajectories of a magnetic particle attracted toward the magnet. 

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