Fabrics are an indispensable part of our everyday life. They provide us with protection, offer privacy and form an intimate expression of ourselves through their esthetics. Imparting functionality at the fiber level represents an intriguing path toward innovative fabrics with a hitherto unparalleled functionality and value. The fiber technology based on thermal drawing of a preform, which is identical in its materials and geometry to the final fiber, has emerged as a powerful platform for the production of exquisite fibers with prerequisite composition, geometric complexity and control over feature size. A ‘Moore's law’ for fibers is emerging, delivering higher forms of function that are important for a broad spectrum of practical applications in healthcare, sports, robotics, space exploration, etc. In this review, we survey progress in thermally drawn fibers and devices, and discuss their relevance to ‘smart’ fabrics. A new generation of fabrics that can see, hear and speak, sense, communicate, harvest and store energy, as well as store and process data is anticipated. We conclude with a critical analysis of existing challenges and opportunities currently faced by thermally drawn fibers and fabrics that are expected to become sophisticated platforms delivering value-added services for our society.
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ABSTRACT -
Free, publicly-accessible full text available August 20, 2023
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There is a close relation between spatial thinking and mathematical problem-solving. This paper presents a newly developed educational Augmented Reality (AR) mobile application, BRICKxAR/T, to help students intuitively learn spatial transformations and the related mathematics through play. A pilot study with 7 undergraduate students evaluates students learning gain through a mental rotation and a math test on transformation matrices. The results show most students performed better with a higher score after learning with the app. Students found the app interesting to play and useful for learning geometric transformations and matrices.
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Abstract Phase Egg and δ-AlOOH are two typical hydrous phases that might exist in the wet sedimentary layer of subducted slabs under mantle conditions. They are thus regarded as potential water carriers to Earth’s deep mantle. In this report, we report the full elastic constants of both phases determined by Brillouin scattering and X-ray diffraction measurements under ambient conditions. Our results indicate that the hydrogen-bond configurations in the crystal structures of the two phases have a profound effect on their principal elastic constants. The adiabatic bulk modulus (KS) and shear modulus (G) calculated from the obtained elastic constants using the Voigt-Reuss-Hill averaging scheme are 158.3(201) GPa and 123.0(60) GPa for phase Egg and 162.9(31) GPa and 145.2(13) GPa for δ-AlOOH, respectively. These results allow us to evaluate elastic moduli and sound velocities of hydrous minerals in the Al2O3-H2O-SiO2 ternary system (simplified composition of subducted wet sedimentary layer) at ambient conditions, including the contrast of the acoustic velocities VP and VS for the reaction AlSi3OH = δ-AlOOH + SiO2 (stishovite) and the evolution in the elastic moduli and sound velocities of hydrous minerals as a function of density.
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Abstract Digital devices are the essential building blocks of any modern electronic system. Fibres containing digital devices could enable fabrics with digital system capabilities for applications in physiological monitoring, human-computer interfaces, and on-body machine-learning. Here, a scalable preform-to-fibre approach is used to produce tens of metres of flexible fibre containing hundreds of interspersed, digital temperature sensors and memory devices with a memory density of ~7.6 × 105bits per metre. The entire ensemble of devices are individually addressable and independently operated through a single connection at the fibre edge, overcoming the perennial single-fibre single-device limitation and increasing system reliability. The digital fibre, when incorporated within a shirt, collects and stores body temperature data over multiple days, and enables real-time inference of wearer activity with an accuracy of 96% through a trained neural network with 1650 neuronal connections stored within the fibre. The ability to realise digital devices within a fibre strand which can not only measure and store physiological parameters, but also harbour the neural networks required to infer sensory data, presents intriguing opportunities for worn fabrics that sense, memorise, learn, and infer situational context.
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For K-8 computer science (CS) education to continue to expand, it is essential that we understand how students develop and demonstrate computational thinking (CT). One approach to gaining this insight is by having students articulate their understanding of CT through cognitive interviews. This study presents findings of a cognitive interview study with 13 fourth-grade students (who had previously engaged in integrated CT and mathematics instruction) working on CT assessment items. The items assessed four CT concepts: sequence, repetition, conditionals, and decomposition. This study analyzed students' articulated understanding of the four CT concepts and the correspondence between that understanding and hypothesized learning trajectories (LTs). We found that 1) all students articulated an understanding of sequence that matched the intermediate level of the Sequence LT; 2) a majority of students' responses demonstrated the level of understanding that the repetition and decomposition items were designed to solicit (8 of 9 responses were correct for repetition and 4 of 6 were correct for decomposition); and 3) less than half of students' responses articulated an understanding of conditionals that was intended by the items (4 of 9 responses were correct). The results also suggested questioning the directional relationships of two statements in the existing Conditionalsmore »