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Mobile Augmented Reality (AR) demands realistic rendering of virtual content that seamlessly blends into the physical environment. For this reason, AR headsets and recent smartphones are increasingly equipped with Time-of-Flight (ToF) cameras to acquire depth maps of a scene in real-time. ToF cameras are cheap and fast, however, they suffer from several issues that affect the quality of depth data, ultimately hampering their use for mobile AR. Among them, scale errors of virtual objects - appearing much bigger or smaller than what they should be - are particularly noticeable and unpleasant. This article specifically addresses these challenges by proposing InDepth,more »Free, publicly-accessible full text available March 1, 2023
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Abstract 316L stainless steel (316L SS) is a flagship material for structural applications in corrosive environments, having been extensively studied for decades for its favorable balance between mechanical and corrosion properties. More recently, 316L SS has also proven to have excellent printability when parts are produced with additive manufacturing techniques, notably laser powder bed fusion (LPBF). Because of the harsh thermo-mechanical cycles experienced during rapid solidification and cooling, LPBF processing tends to generate unique microstructures. Strong heterogeneities can be found inside grains, including trapped elements, nano-inclusions, and a high density of dislocations that form the so-called cellular structure. Interestingly, LPBFmore »Free, publicly-accessible full text available April 1, 2023
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Mobile Augmented Reality (AR), which overlays digital content on the real-world scenes surrounding a user, is bringing immersive interactive experiences where the real and virtual worlds are tightly coupled. To enable seamless and precise AR experiences, an image recognition system that can accurately recognize the object in the camera view with low system latency is required. However, due to the pervasiveness and severity of image distortions, an effective and robust image recognition solution for “in the wild” mobile AR is still elusive. In this article, we present CollabAR, an edge-assisted system that provides distortion-tolerant image recognition for mobile AR withmore »Free, publicly-accessible full text available February 1, 2023
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Abstract Background Genes that belong to the same network are frequently co-expressed, but collectively, how the coordination of the whole transcriptome is perturbed during aging remains unclear. To explore this, we calculated the correlation of each gene in the transcriptome with every other, in the brain of young and older outbred deer mice (P. leucopus and P. maniculatus). Results In about 25 % of the genes, coordination was inversed during aging. Gene Ontology analysis in both species, for the genes that exhibited inverse transcriptomic coordination during aging pointed to alterations in the perception of smell, a known impairment occurring during aging.more »Free, publicly-accessible full text available December 1, 2022
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We explore how different elements of student persistence on computer programming problems may be related to learning outcomes and inform us about which elements may distinguish between productive and unproductive persistence. We collected data from an introductory computer science course at a large midwestern university in the U.S. hosted on an open-source, problem-driven learning system. We defined a set of features quantifying various aspect of persistence during problem solving and used a predictive modeling approach to predict student scores on subsequent and related quiz questions. We focused on careful feature engineering and model interpretation to shed light on the intricaciesmore »Free, publicly-accessible full text available November 19, 2022
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Free, publicly-accessible full text available August 24, 2022
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Free, publicly-accessible full text available December 1, 2022
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Free, publicly-accessible full text available December 16, 2022
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Predicting temperature-dependent ultimate strengths of body-centered-cubic (BCC) high-entropy alloys
Abstract This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature,
T break, introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay belowT break. We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and showmore » -
Protein transfer into nanoscale compartments is critical for many cellular/life processes, yet there are few reports on how compartment properties impact the protein orientation during a transfer. Such a knowledge gap limits a deeper understanding of the protein transfer mechanism, which could be bridged using nanoporous materials. Here, we use a mesoporous silica, a covalent organic framework, and a metal-organic framework with charged, hydrophobic, and neutral surfaces, respectively, to elucidate the impact of channel properties on the transfer of a model protein, lysozyme. Using site-directed spin labeling and time-resolved electron paramagnetic resonance spectroscopy, we reveal that the transfer can bemore »Free, publicly-accessible full text available September 22, 2022