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1. On Image Quality Metadata, FAIR in ML, AI-Readiness and Reproducibility: Fish-AIR example

   https://doi.org/10.3897/biss.7.112178  

   Bakış, Yasin; Wang, Xiaojun; Altıntaş, Bahadır; Jebbia, Dom; Bart_Jr, Henry (September 2023, Biodiversity Information Science and Standards)

   A new science discipline has emerged within the last decade at the intersection of informatics, computer science and biology:Imageomics. Like most other -omics fields, Imageomics also uses emerging technologies to analyze biological data but from the images. One of the most applied data analysis methods for image datasets is Machine Learning (ML). In 2019, we started working on a United States National Science Foundation (NSF) funded project, known as Biology Guided Neural Networks (BGNN) with the purpose of extracting information about biology by using neural networks and biological guidance such as species descriptions, identifications, phylogenetic trees and morphological annotations (Bart et al. 2021). Even though the variety and abundance of biological data is satisfactory for some ML analysis and the data are openly accessible, researchers still spend up to 80% of their time preparing data into a usable, AI-ready format, leaving only 20% for exploration and modeling (Long and Romanoff 2023). For this reason, we have built a dataset composed of digitized fish specimens, taken either directly from collections or from specialized repositories. The range of digital representations we cover is broad and growing, from photographs and radiographs, to CT scans, and even illustrations. We have added new groups of vocabularies to the dataset management system including image quality metadata, extended image metadata and batch metadata. With the image quality metadata and extended image metadata, we aimed to extract information from the digital objects that can possibly help ML scientists in their research with filtering, image processing and object recognition routines. Image quality metadata provides information about objects contained in the image, features and condition of the specimen, and some basic visual properties of the image, while extended image metadata provides information about technical properties of the digital file and the digital multimedia object (Bakış et al. 2021, Karnani et al. 2022, Leipzig et al. 2021, Pepper et al. 2021, Wang et al. 2021) (see details on Fish-AIR vocabulary web page). Batch metadata is used for separating different datasets and facilitates downloading and uploading data in batches with additional batch information and supplementary files. Additional flexibility, built into the database infrastructure using an RDF framework, will enable the system to host different taxonomic groups, which might require new metadata features (Jebbia et al. 2023). By the combination of these features, along with FAIR (Findable, Accessable, Interoperable, Reusable) principles, and reproducibility, we provide Artificial Intelligence Readiness (AIR; Long and Romanoff 2023) to the dataset. Fish-AIR provides an easy-to-access, filtered, annotated and cleaned biological dataset for researchers from different backgrounds and facilitates the integration of biological knowledge based on digitized preserved specimens into ML pipelines. Because of the flexible database infrastructure and addition of new datasets, researchers will also be able to access additional types of data—such as landmarks, specimen outlines, annotated parts, and quality scores—in the near future. Already, the dataset is the largest and most detailed AI-ready fish image dataset with integrated Image Quality Management System (Jebbia et al. 2023, Wang et al. 2021). 

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2. On doubly symmetric periodic orbits

   https://doi.org/10.1007/s10569-023-10135-6  

   Frauenfelder, Urs; Moreno, Agustin (April 2023, Celestial Mechanics and Dynamical Astronomy)

   Abstract In this article, for Hamiltonian systems with two degrees of freedom, we study doubly symmetric periodic orbits, i.e., those which are symmetric with respect to two (distinct) commuting antisymplectic involutions. These are ubiquitous in several problems of interest in mechanics. We show that, in dimension four, doubly symmetric periodic orbits cannot be negative hyperbolic. This has a number of consequences: (1) All covers of doubly symmetric orbits are good , in the sense of Symplectic Field Theory (Eliashberg et al. Geom Funct Anal Special Volume Part II:560–673, 2000); (2) a non-degenerate doubly symmetric orbit is stable if and only if its CZ-index is odd; (3) a doubly symmetric orbit does not undergo period doubling bifurcation; and (4) there is always a stable orbit in any collection of doubly symmetric periodic orbits with negative SFT-Euler characteristic (as coined in Frauenfelder et al. in Symplectic methods in the numerical search of orbits in real-life planetary systems. Preprint arXiv:2206.00627 ). The above results follow from: (5) A symmetric orbit is negative hyperbolic if and only its two B - signs (introduced in Frauenfelder and Moreno 2021) differ. 

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3. Pocillopora tuahiniensis: a new species of scleractinian coral (Scleractinia, Pocilloporidae) from French Polynesia

   https://doi.org/10.11646/zootaxa.5369.1.5  

   JOHNSTON, ERIKA C; BURGESS, SCOTT C (November 2023, Zootaxa)

   Pocillopora tuahiniensis sp. nov. is described based on mitochondrial and nuclear genomic data, algal symbiont genetic data, geographic isolation, and its distribution pattern within reefs that is distinct from other sympatric Pocillopora species (Johnston et al. 2022a, b). Mitochondrial and nuclear genomic data reveal that P. tuahiniensis sp. nov. is a unique species, sister to P. verrucosa, and in a clade different from that of P. meandrina (Johnston et al. 2022a). However, the gross in situ colony appearance of P. tuahiniensis sp. nov. cannot easily be differentiated from that of P. verrucosa or P. meandrina at Mo’orea. By sequencing the mtORF region, P. tuahiniensis sp. nov. can be easily distinguished from other Pocillopora species. Pocillopora tuahiniensis sp. nov. has so far been sampled in French Polynesia, Ducie Island, and Rapa Nui (Armstrong et al. 2023; Edmunds et al. 2016; Forsman et al. 2013; Gélin et al. 2017; Mayfield et al. 2015; Oury et al. 2021; Voolstra et al. 2023). On the fore reefs of Mo’orea, P. tuahiniensis sp. nov. is very abundant ≥10 m and is one of the most common Pocillopora species at these depths (Johnston et al. 2022b). It can also be found at a much lower abundance at shallow depths on the fore reef and back reef lagoon. The holotype is deposited at the Smithsonian Institution as USNM-SI 1522390 and the mtORF Genbank accession number is OP418359.  

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4. Mountaintop Gamma Ray Observations of Three Terrestrial Gamma‐Ray Flashes at the Säntis Tower, Switzerland With Coincident Radio Waveforms

   https://doi.org/10.1029/2023JD039761  

   Chaffin, Jeffrey M.; Smith, David M.; Lapierre, Jeff; Cummer, Steve; Ortberg, John; Sunjerga, Antonio; Mostajabi, Amirhossein; Rubinstein, Marcos; Rachidi, Farhad (January 2024, Journal of Geophysical Research: Atmospheres)

   Abstract We report on the mountain top observation of three terrestrial gamma‐ray flashes (TGFs) that occurred during the summer storm season of 2021. To our knowledge, these are the first TGFs observed in a mountaintop environment and the first published European TGFs observed from the ground. A gamma‐ray sensitive detector was located at the base of the Säntis Tower in Switzerland and observed three unique TGF events with coincident radio sferic data characteristic of TGFs seen from space. We will show an example of a “slow pulse” radio signature (Cummer et al., 2011,https://doi.org/10.1029/2011GL048099; Lu et al., 2011,https://doi.org/10.1029/2010JA016141; Pu et al., 2019,https://doi.org/10.1029/2019GL082743; Pu et al., 2020,https://doi.org/10.1029/2020GL089427), a −EIP (Lyu et al., 2016,https://doi.org/10.1002/2016GL070154; Lyu et al., 2021,https://doi.org/10.1029/2021GL093627; Wada et al., 2020,https://doi.org/10.1029/2019JD031730), and a double peak TGF associated with an extraordinarily powerful and complicated positive‐polarity sferic, where each TGF peak is possibly preceded by a short burst of stepped leader emission. 

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5. THE BELIEFS AND PRACTICES OF GRADUATE STUDENT TUTORS ENGAGED IN ONLINE TUTORING DURING THE PANDEMIC

   Mule’, T; Houston, S.; Piontek, J.; Webb, J.; Harrell-Williams, L. (November 2022, Proceedings of the forty-fourth annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education)

   Lischka, A. E.; Dyer, E. B.; Jones, R. S.; Lovett, J. N.; Strayer, J.; & Drown, S. (Ed.)

   Many higher education institutions in the United States provide mathematics tutoring services for undergraduate students. These informal learning experiences generally result in increased final course grades (Byerly & Rickard, 2018; Rickard & Mills, 2018; Xu et al., 2014) and improved student attitudes toward mathematics (Bressoud et al., 2015). In recent years, research has explored the beliefs and practices of undergraduate and, sometimes graduate, peer tutors, both prior to (Bjorkman, 2018; Johns, 2019; Pilgrim et al., 2020) and during the COVID19 pandemic (Gyampoh et al., 2020; Mullen et al., 2021; Van Maaren et al., 2021). Additionally, Burks and James (2019) proposed a framework for Mathematical Knowledge for Tutoring Undergraduate Mathematics adapted from Ball et al. (2008) Mathematical Knowledge for Teaching, highlighting the distinction between tutor and teacher. The current study builds on this body of work on tutors’ beliefs by focusing on mathematical sciences graduate teaching assistants (GTAs) who tutored in an online setting during the 2020-2021 academic year due to the COVID-19 pandemic. Specifically, this study addresses the following research question: What were the mathematical teaching beliefs and practices of graduate student tutors participating in online tutoring sessions through the mathematics learning center (MLC) during the COVID-19 pandemic? 

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