Monitoring of the central blood pressure waveform via a conformal ultrasonic device.

Continuous monitoring of the central-blood-pressure waveform from deeply embedded vessels, such as the carotid artery and jugular vein, has clinical value for the prediction of all-cause cardiovascular mortality. However, existing non-invasive approaches, including photoplethysmography and tonometry, only enable access to the superficial peripheral vasculature. Although current ultrasonic technologies allow non-invasive deep-tissue observation, unstable coupling with the tissue surface resulting from the bulkiness and rigidity of conventional ultrasound probes introduces usability constraints. Here, we describe the design and operation of an ultrasonic device that is conformal to the skin and capable of capturing blood-pressure waveforms at deeply embedded arterial and venous sites. The wearable device is ultrathin (240 μm) and stretchable (with strains up to 60%), and enables the non-invasive, continuous and accurate monitoring of cardiovascular events from multiple body locations, which should facilitate its use in a variety of clinical environments

Controllable Epitaxial Growth of Metal Halide Perovskites for Single-crystal Devices

As an emerging class of semiconductors, metal halide perovskites have demonstrated tremendous potential in various applications, including photovoltaic solar cells, light-emitting diodes, photodetection, and many other electronic devices. While most of these perovskite electronic devices have adopted polycrystalline perovskite thin films, problems of polycrystalline thin films like the high density of grain boundaries and defects, low stability can hinder the further performance enhancement of perovskite electronic devices. Comparing with their polycrystalline counterpart, single-crystal perovskites provide opportunities in solving such problems. Not only can they provide enhanced crystalline quality and excellent material stability, but also the possibility to alter the electronic properties of perovskites by lattice-mismatch-induced strain. Yet the development of single-crystal perovskite electronic devices is still in its infancy due to the low controllability over the growth of single-crystal perovskite nano/micro-structures and the incompatibility with the conventional semiconductor fabrication protocol. This research aims to develop a platform for growing high-quality single-crystal metal halide perovskite nano/micro-structures using controllable chemical homo/heteroepitaxial growth and fabricating high-performance single-crystal-perovskite-based electronic devices with the conventional semiconductor fabrication protocols. In Chapter One, the basic properties of metal halide perovskites and the current problems presented in the polycrystalline perovskite thin films will be introduced and discussed. In Chapter Two, controllable homoepitaxial growth of metal halide perovskite micro-arrays will be introduced. Our work presents the first controllable growth of large-area single-crystal perovskite microarrays with different sizes, morphologies, crystalline orientations, and patterned structures. In Chapter Three, controllable strain engineering of single-crystal metal halide perovskite thin films by heteroepitaxial-growth-induced lattice mismatch will be introduced. Our work presents the first controllable strain engineering in metal halide perovskite family. In Chapter Four, epitaxial stabilization induced by the chemically epitaxial strain growth will be introduced. Our strategy provides insights into structurally stabilizing the metastable metal halide perovskite family. Our understanding of the controllable epitaxial growth of metal halide perovskites paves the way for next-generation single-crystal metal halide perovskites electronic devices

Controllable Epitaxial Growth of Metal Halide Perovskites for Single-crystal Devices

As an emerging class of semiconductors, metal halide perovskites have demonstrated tremendous potential in various applications, including photovoltaic solar cells, light-emitting diodes, photodetection, and many other electronic devices. While most of these perovskite electronic devices have adopted polycrystalline perovskite thin films, problems of polycrystalline thin films like the high density of grain boundaries and defects, low stability can hinder the further performance enhancement of perovskite electronic devices. Comparing with their polycrystalline counterpart, single-crystal perovskites provide opportunities in solving such problems. Not only can they provide enhanced crystalline quality and excellent material stability, but also the possibility to alter the electronic properties of perovskites by lattice-mismatch-induced strain. Yet the development of single-crystal perovskite electronic devices is still in its infancy due to the low controllability over the growth of single-crystal perovskite nano/micro-structures and the incompatibility with the conventional semiconductor fabrication protocol. This research aims to develop a platform for growing high-quality single-crystal metal halide perovskite nano/micro-structures using controllable chemical homo/heteroepitaxial growth and fabricating high-performance single-crystal-perovskite-based electronic devices with the conventional semiconductor fabrication protocols. In Chapter One, the basic properties of metal halide perovskites and the current problems presented in the polycrystalline perovskite thin films will be introduced and discussed. In Chapter Two, controllable homoepitaxial growth of metal halide perovskite micro-arrays will be introduced. Our work presents the first controllable growth of large-area single-crystal perovskite microarrays with different sizes, morphologies, crystalline orientations, and patterned structures. In Chapter Three, controllable strain engineering of single-crystal metal halide perovskite thin films by heteroepitaxial-growth-induced lattice mismatch will be introduced. Our work presents the first controllable strain engineering in metal halide perovskite family. In Chapter Four, epitaxial stabilization induced by the chemically epitaxial strain growth will be introduced. Our strategy provides insights into structurally stabilizing the metastable metal halide perovskite family. Our understanding of the controllable epitaxial growth of metal halide perovskites paves the way for next-generation single-crystal metal halide perovskites electronic devices

Controlled synthesis of core/shell magnetic iron oxide/carbon systems via a self-template method

A sol-gel assembly process was developed for the synthesis of magnetic core/carbon shell materials with porous networks. Fe(CO)5 was assembled into the pore channels of mesoporous silica via a sol-gel method at 18 °C, by using the block copolymer F127 as the template and Fe(CO)5 as an additional precursor. At this temperature, the magnetic precursor Fe(CO)5 was pre-organized into hydrophobic cores of micelles by self-assembly of F127. In the subsequent carbonization of the assembly under an Ar atmosphere, Fe(CO)5 transformed into magnetic nanoparticles and surfactant F127 transferred into carbon shells enveloping the magnetic nanoparticles, forming magnetic iron oxide core/carbon shell structures. The removal of the silica with 5% HF acid resulted in the core/shell nanoporous composite. The obtained system demonstrates a saturation magnetic value of 3 emu g−1 as well as a high surface area (98 cm2 g−1) and pore volume (0.21 m3 g−1), which would benefit its potential applications as adsorbents and catalysts, or applications in targeted drug delivery systems. This facile strategy would provide an efficient approach for tailoring core/shell porous materials with desired functionalities and structures by adjusting precursors and structure-directing agents

Optimized trajectory unraveling for classical simulation of noisy quantum dynamics

The dynamics of open quantum systems can be simulated by unraveling it into an ensemble of pure state trajectories undergoing non-unitary monitored evolution, which has recently been shown to undergo measurement-induced entanglement phase transition. Here, we show that, for an arbitrary decoherence channel, one can optimize the unraveling scheme to lower the threshold for entanglement phase transition, thereby enabling efficient classical simulation of the open dynamics for a broader range of decoherence rates. Taking noisy random unitary circuits as a paradigmatic example, we analytically derive the optimum unraveling basis that on average minimizes the threshold. Moreover, we present a heuristic algorithm that adaptively optimizes the unraveling basis for given noise channels, also significantly extending the simulatable regime. When applied to noisy Hamiltonian dynamics, the heuristic approach indeed extends the regime of efficient classical simulation based on matrix product states beyond conventional quantum trajectory methods. Finally, we assess the possibility of using a quasi-local unraveling, which involves multiple qubits and time steps, to efficiently simulate open systems with an arbitrarily small but finite decoherence rate.Comment: 5+9 pages, 4+6 figures, 0+3 table

A knowledge graph-based method for epidemic contact tracing in public transportation

Contact tracing is an effective measure by which to prevent further infections in public transportation systems. Considering the large number of people infected during the COVID-19 pandemic, digital contact tracing is expected to be quicker and more effective than traditional manual contact tracing, which is slow and labor-intensive. In this study, we introduce a knowledge graph-based framework for fusing multi-source data from public transportation systems to construct contact networks, design algorithms to model epidemic spread, and verify the validity of an effective digital contact tracing method. In particular, we take advantage of the trip chaining model to integrate multi-source public transportation data to construct a knowledge graph. A contact network is then extracted from the constructed knowledge graph, and a breadth-first search algorithm is developed to efficiently trace infected passengers in the contact network. The proposed framework and algorithms are validated by a case study using smart card transaction data from transit systems in Xiamen, China. We show that the knowledge graph provides an efficient framework for contact tracing with the reconstructed contact network, and the average positive tracing rate is over 96%

Large-Scale Video Retrieval via Deep Local Convolutional Features

In this paper, we study the challenge of image-to-video retrieval, which uses the query image to search relevant frames from a large collection of videos. A novel framework based on convolutional neural networks (CNNs) is proposed to perform large-scale video retrieval with low storage cost and high search efficiency. Our framework consists of the key-frame extraction algorithm and the feature aggregation strategy. Specifically, the key-frame extraction algorithm takes advantage of the clustering idea so that redundant information is removed in video data and storage cost is greatly reduced. The feature aggregation strategy adopts average pooling to encode deep local convolutional features followed by coarse-to-fine retrieval, which allows rapid retrieval in the large-scale video database. The results from extensive experiments on two publicly available datasets demonstrate that the proposed method achieves superior efficiency as well as accuracy over other state-of-the-art visual search methods

In vivo nano contrast-enhanced photoacoustic imaging for dynamically lightening the molecular changes of rheumatoid arthritis

Rheumatoid arthritis (RA) is one of the most prevalent inflammatory joint disorders. Early diagnosis, accurate staging, and imaging guided treatment response of RA remain crucial clinical significances for improving treatment outcomes. In this study, we introduced endogenous melanin nanoparticles (MNPs) conjugated with Cyclic Arg-Gly-Asp (RGD) peptide (MNP-PEG-RGD) as a contrast agent for accurate photoacoustic imaging (PAI) of RA diagnosis. It was observed that the prepared nanoprobes had favorable PA sensitivity, photostability and biocompatibility. In vivo studies using RA mouse model revealed that this nanoprobe could target αvβ3 actively at 1 h post-injection, while the signal was remarkably increased in the arthritic joint which could earlier diagnose RA than conventional imaging system. It was of crucial importance to staging RA by PAI with significant difference in nanoprobes accumulation. Furthermore, we tracked the therapeutic efficacy of etanercept in RA treatment by PAI. The observed advancement of arthritis on the PAI was confirmed by histological and immunohistochemical analysis. In conclusion, this study shed light on the development of innovative multifunctional theranostic nanoplatform for both RA monitoring and treatment with a promising future in clinical translation