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Creators/Authors contains: "Williams, Robert"

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  1. Abstract

    We construct Bayesian and frequentist finite-sample goodness-of-fit tests for three different variants of the stochastic blockmodel for network data. Since all of the stochastic blockmodel variants are log-linear in form when block assignments are known, the tests for the latent block model versions combine a block membership estimator with the algebraic statistics machinery for testing goodness-of-fit in log-linear models. We describe Markov bases and marginal polytopes of the variants of the stochastic blockmodel and discuss how both facilitate the development of goodness-of-fit tests and understanding of model behaviour. The general testing methodology developed here extends to any finite mixture of log-linear models on discrete data, and as such is the first application of the algebraic statistics machinery for latent-variable models.

     
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  2. Abstract

    We present the final results of an imaging and spectroscopic search for stars in the Large Magellanic Cloud (LMC) with Ciiλλ7231, 7236 emission lines. The goal is to identify and study [WC11] stars, the coolest of the low-mass Wolf–Rayet sequence, and a subset of central stars of planetary nebulae where the Ciilines are known to be especially prominent. A recent serendipitous discovery of an LMC [WC11] raised the possibility that these objects, although difficult to identify, might in fact be more common than previously believed. Several new members of this rare class have been found in this survey. It now seems clear, however, that a significant number of these stars are not hiding among the general [WC] population. We point out that the Ciidoublet intensity ratio observed in our spectra proves to neatly divide the objects into two distinct groups, with the Ciiemission likely originating from either the stellar wind or a surrounding nebula. The physics of the Ciiemission mechanism correctly explains this bifurcation. Spectral subtypes are suggested for most of the objects. The numerous spectroscopic clues now available for these objects should facilitate future detailed modeling.

     
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  3. Free, publicly-accessible full text available March 1, 2025
  4. Abstract

    Pangenome graphs can represent all variation between multiple genomes, but existing methods for constructing them are biased due to reference-guided approaches. In response, we have developed PanGenome Graph Builder (PGGB), a reference-free pipeline for constructing unbi-ased pangenome graphs. PGGB uses all-to-all whole-genome alignments and learned graph embeddings to build and iteratively refine a model in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.

     
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    Abstract

    Cooperative 3D printing (C3DP) is a novel approach to additive manufacturing, where multiple mobile 3D printing robots work together cooperatively to print the desired part. At the core of C3DP lies the chunk-based printing strategy. This strategy splits the desired part into smaller chunks, and then the chunks are assigned and scheduled to be printed by individual printing robots. In our previous work, we presented various hardware and software components of C3DP, such as mobile 3D printers, chunk-based slicing, scheduling, and simulation. In this study, we present a fully integrated and functional C3DP platform with all necessary components, including chunker, slicer, scheduler, printing robots, build floor, and outline how they work in unison from a system-level perspective. To realize C3DP, new developments of both hardware and software are presented, including new chunking approaches, scalable scheduler for multiple robots, SCARA-based printing robots, a mobile platform for transporting printing robots, modular floor tiles, and a charging station for the mobile platform. Finally, we demonstrate the capability of the system using two case studies. In these demonstrations, a CAD model of a part is fed to the chunker, divided into smaller chunks, passed to the scheduler, and assigned and scheduled to be printed by the scheduler with a given number of robots. The slicer generates G-code for each of the chunks and combines G-code into one file for each robot. The simulator then uses the G-code generated by the slicer to generate animations for visualization purposes.

     
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