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Ambient temperature distribution monitoring is desired in a variety of real-life applications including indoors temperature control and building energy management. Traditional temperature sensors have their limitations in the aspects of single point/item based measurements, slow response time and huge cost for distribution estimation. In this paper, we introduce VECTOR, a temperature-field monitoring system that achieves high temperature sensing accuracy and fast response time using commercial sound playing/recording devices. First, our system uses a distributed ranging algorithm to measure the time-of-flight of multiple sound paths with microsecond resolution. We then propose a dRadon transform algorithm that reconstructs the temperature distribution from the measured speed of sound along different paths. Our experimental results show that we can measure the temperature with an error of 0.25°C from single sound path and reconstruct the temperature distribution at a decimeter-level spatial resolution.

Corneal transplantation is an effective treatment for reconstructing injured corneas but is very limited due to insufficient donors, which has led to a growing demand for development of artificial corneal substitutes (ACSs). Collagen is a potential building block for ACS fabrication, whereas technically there are limited capabilities to control the collagen assembly for creating highly transparent collagen ACSs. Here, we report an electro-assembly technique to kinetically control collagen assembly on the nanoscale that allows the yielding collagen ACSs with structure determined superior optics. Structurally, the kinetically electro-assembled collagen (KEA-Col) is composed of partially aligned microfibrils (∼10 nm in diameter) with compacted lamellar organization. Optical analysis reveals that such microstructure is directly responsible for its optimal light transmittance by reducing light scattering. Moreover, this method allows the creation of complex three-dimensional geometries and thus is convenient to customize collagen ACSs with specific curvatures to meet refractive power requirements. Available properties (e.g., optics and mechanics) of cross-linked KEA-Cols were studied to meet the clinical requirement as ACSs, and

Continuous domestic respiration monitoring provides vital information for diagnosing assorted diseases. In this paper, we introduce RespTracker, the first continuous, multiple-person respiration tracking system in domestic settings using acoustic-based COTS devices. RespTracker uses a multi-stage algorithm to separate and recombine respiration signals from multiple paths so that it can track the respiration rate of multiple moving subjects. And it leverages features from multiple dimensions to separate different users in the same area. Our experimental results show that our two-stage algorithm can distinguish the respiration of at least four subjects and cover a distance of three meters.

Silent speech recognition (SSR) allows users to speak to the device without making a sound, avoiding being overheard or disturbing others. Compared to the video-based approach, wireless signal-based SSR can work when the user is wearing a mask and has fewer privacy concerns. However, previous wireless-based systems are still far from well-studied, e.g. they are only evaluated in corpus with highly limited size, making them only feasible for interaction with dozens of deterministic commands. In this paper, we present mSilent, a millimeter-wave (mmWave) based SSR system that can work in the general corpus containing thousands of daily conversation sentences. With the strong recognition capability, mSilent not only supports the more complex interaction with assistants, but also enables more general applications in daily life such as communication and input. To extract fine-grained articulatory features, we build a signal processing pipeline that uses a clustering-selection algorithm to separate articulatory gestures and generates a multi-scale detrended spectrogram (MSDS). To handle the complexity of the general corpus, we design an end-to-end deep neural network that consists of a multi-branch convolutional front-end and a Transformer-based sequence-to-sequence back-end. We collect a general corpus dataset of 1,000 daily conversation sentences that contains 21K samples of bi-modality data (mmWave and video). Our evaluation shows that mSilent achieves a 9.5% average word error rate (WER) at a distance of 1.5m, which is comparable to the performance of the state-of-the-art video-based approach. We also explore deploying mSilent in two typical scenarios of text entry and in-car assistant, and the less than 6% average WER demonstrates the potential of mSilent in general daily applications.

Laser additive manufacturing (LAM) of complex-shaped metallic components offers great potential for fabricating customized endovascular stents. In this study, anti-tetrachiral auxetic stents with negative Poisson ratios (NPR) were designed and fabricated via LAM. Poisson’s ratios of models with different diameters of circular node (DCN) were calculated using finite element analysis (FEA). The experimental method was conducted with the LAM-fabricated anti-tetrachiral stents to validate their NPR effect and the simulation results. The results show that, with the increase in DCN from 0.6 to 1.5 mm, the Poisson ratios of anti-tetrachiral stents varied from −1.03 to −1.12, which is in line with the simulation results. The interrelationship between structural parameters of anti-tetrachiral stents, their mechanical properties and biocompatibility was demonstrated. The anti-tetrachiral stents with a DCN of 0.9 mm showed the highest absolute value of negative Poisson’s ratio, combined with good cytocompatibility. The cytocompatibility tests indicate the envisaged cell viability and adhesion of the vascular endothelial cell on the LAM-fabricated anti-tetrachiral auxetic stents. The manufactured stents exhibit great superiority in the application of endovascular stent implantation due to their high flexibility for easy maneuverability during deployment and enough strength for arterial support.

Collagen is a biological building block that is hierarchically assembled into diverse morphological structures that, in some cases, is dynamically adaptive in response to external cues and in other cases forms static terminal structures. Technically, there is limited capabilities to guide the emergence of collagen’s hierarchical organization to recapitulate the richness of biological structure and function. Here, we report an electro-assembly pathway to create a dynamically adaptive intermediate molten fibril state for collagen. Structurally, this intermediate state is composed of partially aligned and reversibly associating fibrils with limited hierarchical structure. These molten fibrils can be reversibly reconfigured to offer dynamic properties such as stimuli-stiffening, stimuli-contracting, self-healing, and self-shaping. Also, molten fibrils can be guided to further assemble to recapitulate the characteristic hierarchical structural features of native collagen (e.g., aligned fibers with D-banding). We envision that the electro-assembly of collagen fibrils will provide previously unidentified opportunities for tailored collagen-based biomedical materials.

Transition metal dichalcogenides (TMDs), as one of the most promising two-dimensional (2D) materials, have attracted considerable attention for use in photodetection applications over the past few years due to their distinct properties, such as atomic-scale thickness, tunable direct bandgaps, and decent carrier mobilities at room temperature. Compared with pure 2D TMDs, the construction of hybrids consisting of TMDs and other low-dimensional materials can further improve the performance of photodetectors including their spectral range, responsivity and detectivity, which significantly boosts interest in the development of TMDs-based photodetectors. On the other hand, solution-phase synthesis methods provide a facile strategy for the scalable production of TMD hybrids, opening an exciting avenue to develop low-cost devices. In this review, we summarize the material synthesis, characterizations, and photodetection applications of the solution processable TMDs-based hybrids, as well as provide insights into their prospects.

Continuous domestic respiration monitoring provides vital information for diagnosing assorted diseases. In this paper, we introduce RESPTRACKER, the first continuous, multiple-person respiration tracking system in domestic settings using acoustic-based COTS devices. RESPTRACKER uses a two-stage algorithm to separate and recombine respiration signals from multiple paths in a short period so that it can track the respiration rate of multiple moving subjects. Our experimental results show that our two-stage algorithm can distinguish the respiration of at least four subjects at a distance of three meters.