Automated Classification of Pectinodon Bakkeri Teeth Images Using Machine Learning

Microfossil dinosaur teeth are studied by paleontologists in order to better under- stand dinosaurs. Currently, tooth classification is a long, manual, error-ridden process. Deep learning offers a solution that allows for an automated way of classifying images of these microfossil teeth. In this thesis, we aimed to use deep learning in order to develop an automated approach for classifying images of Pectinodon bakkeri teeth. The proposed model was trained using a custom topology and it classified the images based on clusters created via K-Means. The model had an accuracy of 71%, a precision of 71%, a recall of 70.5%, and an F1-score of 70.5%

Analysis of testbed airborne multispectral scanner data from Superflux II

A test bed aircraft multispectral scanner (TBAMS) was flown during the James Shelf, Plume Scan, and Chesapeake Bay missions as part of the Superflux 2 experiment. Excellent correlations were obtained between water sample measurements of chlorophyll and sediment and TBAMS radiance data. The three-band algorithms used were insensitive to aircraft altitude and varying atmospheric conditions. This was particularly fortunate due to the hazy conditions during most of the experiments. A contour map of sediment, and also chlorophyll, was derived for the Chesapeake Bay plume along the southern Virginia-Carolina coastline. A sediment maximum occurs about 5 nautical miles off the Virginia Beach coast with a chlorophyll maximum slightly shoreward of this. During the James Shelf mission, a thermal anomaly (or front) was encountered about 50 miles from the coast. There was a minor variation in chlorophyll and sediment across the boundary. During the Chesapeake Bay mission, the Sun elevation increased from 50 degrees to over 70 degrees, interfering with the generation of data products

Introducing Normal Forms to Students: A Comparison of Theory-First vs. Project-First Educational Approaches

One of the primary challenges instructors face when educating scientists and engineers is the introduction of important theory, both to show its essential nature in research as well as its practicality. This paper analyzes two pedagogical methods for the instruction of database normal forms. The first of these methods is a theory-based approach that relies on written works and practices to introduce the concept. The second of these focuses on a project-based approach which aligns with normal form standards as students implement a database schema. This paper compares these in a small study and advises an appropriate method for educators

Branch water uptake and redistribution in two conifers at the alpine treeline

During winter, conifers at the alpine treeline suffer dramatic losses of hydraulic conductivity, which are successfully recovered during late winter. Previous studies indicated branch water uptake to support hydraulic recovery. We analyzed water absorption and redistribution in Picea abies and Larix decidua growing at the treeline by in situ exposure of branches to δ2H-labelled water. Both species suffered high winter embolism rates (> 40–60% loss of conductivity) and recovered in late winter (< 20%). Isotopic analysis showed water to be absorbed over branches and redistributed within the crown during late winter. Labelled water was redistributed over 425 ± 5 cm within the axes system and shifted to the trunk, lower and higher branches (tree height 330 ± 40 cm). This demonstrated relevant branch water uptake and re-distribution in treeline conifers. The extent of water absorption and re-distribution was species-specific, with L. decidua showing higher rates. In natura, melting snow might be the prime source for absorbed and redistributed water, enabling embolism repair and restoration of water reservoirs prior to the vegetation period. Pronounced water uptake in the deciduous L. decidua indicated bark to participate in the process of water absorption

Global analyses of endonucleolytic cleavage in mammals reveal expanded repertoires of cleavage-inducing small RNAs and their targets.

In mammals, small RNAs are important players in post-transcriptional gene regulation. While their roles in mRNA destabilization and translational repression are well appreciated, their involvement in endonucleolytic cleavage of target RNAs is poorly understood. Very few microRNAs are known to guide RNA cleavage. Endogenous small interfering RNAs are expected to induce target cleavage, but their target genes remain largely unknown. We report a systematic study of small RNA-mediated endonucleolytic cleavage in mouse through integrative analysis of small RNA and degradome sequencing data without imposing any bias toward known small RNAs. Hundreds of small cleavage-inducing RNAs and their cognate target genes were identified, significantly expanding the repertoire of known small RNA-guided cleavage events. Strikingly, both small RNAs and their target sites demonstrated significant overlap with retrotransposons, providing evidence for the long-standing speculation that retrotransposable elements in mRNAs are leveraged as signals for gene targeting. Furthermore, our analysis showed that the RNA cleavage pathway is also present in human cells but affecting a different repertoire of retrotransposons. These results show that small RNA-guided cleavage is more widespread than previously appreciated. Their impact on retrotransposons in non-coding regions shed light on important aspects of mammalian gene regulation