基于多孔泡沫状Au/MXene复合纳米材料的无酶葡萄糖传感器

本文研究了一种基于三维Au/MXene复合纳米颗粒的新型无酶电化学传感器.MXene的制备选择采用温和刻蚀方法,多孔泡沫状Au纳米颗粒多通过原位合成法与MXene结合.通过控制合成过程中MXene的量,获得一种具有多孔泡沫状结构的Au纳米颗粒.使用扫描电子显微镜证实了该纳米颗粒的三维泡沫状结构.使用循环伏安法和电化学阻抗谱测试探究了Au/MXene纳米复合材料的电化学性能.Au/MXene纳米复合材料作为无酶葡萄糖的快速氧化还原探针表现出良好的性能,包括22.45μA·(mmol/L)^(-1)·cm^(-1)的高灵敏度和1~12 mmol/L的宽线性检测范围.研究表明,MXene作为催化剂的负载材料,有利于增强电子的导电性,提高催化剂材料的负载率.具有泡沫结构的Au纳米颗粒可以提供更大的表面积,增加催化反应中与葡萄糖分子的接触面积,增强电化学反应信号.研究表明在无酶葡萄糖传感器中,Au/MXene复合纳米颗粒具有应用潜力.

Raman and infrared spectra of complex low energy tetrahedral carbon allotropes from first-principles calculations

Up to now,at least 806 carbon allotropes have been proposed theoretically.Three interesting carbon allotropes(named Pbam-32,P6/mmm,and I43d)were recently uncovered based on a random sampling strategy combined with space group and graph theory.The calculation results show that they are superhard and remarkably stable compared with previously proposed metastable phases.This indicates that they are likely to be synthesized in experiment.We use the factor group analysis method to analyze theirΓ-point vibrational modes.Owing to their large number of atoms in primitive unit cells(32 atoms in Pbam-32,36 atoms in P6/mmm,and 94 atoms in I43d),they have many Raman-and infrared-active modes.There are 48 Raman-active modes and 37 infrared-active modes in Pbam-32,24 Raman-active modes and 14 infrared-active modes in P6/mmm,and 34 Raman-active modes and 35 Raman-and infrared-active modes in I43d.Their calculated Raman spectra can be divided into middle frequency range from 600 cm-1 to 1150 cm-1 and high frequency range above 1150 cm-1.Their largest infrared intensities are 0.82,0.77,and 0.70(D/Å)2/amu for Pbam,P6/mmm,and I43d,respectively.Our calculated results provide an insight into the lattice vibrational spectra of these sp3 carbon allotropes and suggest that the middle frequency Raman shift and infrared spectrum may play a key role in identifying newly proposed carbon allotropes.

The circuit design and optimization of quantum multiplier and divider

A fault-tolerant circuit is required for robust quantum computing in the presence of noise.Clifford+T circuits are widely used in fault-tolerant implementations.As a result,reducing T-depth,T-count,and circuit width has emerged as important optimization goals.A measure-and-fixup approach yields the best T-count for arithmetic operations,but it requires quantum measurements.This paper proposes approximate Toffoli,TR,Peres,and Fredkin gates with optimized T-depth and T-count.Following that,we implement basic arithmetic operations such as quantum modular adder and subtractor using approximate gates that do not require quantum measurements.Then,taking into account the circuit width,T-depth,and T-count,we design and optimize the circuits of two multipliers and a divider.According to the comparative analysis,the proposed multiplier and divider circuits have lower circuit width,T-depth,and T-count than the current works that do not use the measure-and-fixup approach.Significantly,the proposed second multiplier produces approximately 77%T-depth,60%T-count,and 25%width reductions when compared to the existing multipliers without quantum measurements.

A review of object representation based on local features

Object representation based on local features is a topical subject in the domain of image understanding and computer vision. We discuss the defects of global features in present methods and the advantages of local features in object recognition, and briefly explore state-of-the-art recognition methods using local features, especially the main approaches of local feature extraction and object representation. To clearly explain these methods, the problem of local feature extraction is divided into feature region detection, feature region description, and feature space optimization. The main components and merits of these steps are presented. Technologies for object presentation are classified into three types: vector space, sliding window, and structure relationship models. Future development trends are discussed briefly.

Efficient quantum arithmetic operation circuits for quantum image processing

Efficient quantum circuits for arithmetic operations are vital for quantum algorithms.A fault-tolerant circuit is required for a robust quantum computing in the presence of noise.Quantum circuits based on Clifford+T gates are easily rendered faulttolerant.Therefore,reducing the T-depth and T-Count without increasing the qubit number represents vital optimization goals for quantum circuits.In this study,we propose the fault-tolerant implementations for TR and Peres gates with optimized T-depth and T-Count.Next,we design fault-tolerant circuits for quantum arithmetic operations using the TR and Peres gates.Then,we implement cyclic and complete translations of quantum images using quantum arithmetic operations,and the scalar matrix multiplication.Comparative analysis and simulation results reveal that the proposed arithmetic and image operations are efficient.For instance,cyclic translations of a quantum image produce 50%T-depth reduction relative to the previous best-known cyclic translation.

Time-sequential changes of differentially expressed miRNAs during the process of anterior lumbar interbody fusion using equine bone protein extract, rhBMP-2 and autograft

The precise mechanism of bone regeneration in different bone graft substitutes has been well studied in recent researches. However, miRNAs regulation of the bone formation has been always mysterious. We developed the anterior lumbar interbody fusion （ALIF） model in pigs using equine bone protein extract （BPE）, recombinant human bone morphogenetic protein-2 （rhBMP-2） on an absorbable collagen sponge （ACS）, and autograft as bone graft substitute, respectively. The miRNA and gene expression profiles of different bone graft materials were examined using microarray technology and data analysis, including self-organizing maps, KEGG pathway and Biological process GO analyses. We then jointly analyzed miRNA and mRNA profiles of the bone fusion tissue at different time points respectively. Results showed that miRNAs, including let-7, miR-129, m iR-21, miR-133, miR-140, miR-146, miR-184, and miR-224, were involved in the regulation of the immune and inflammation response, which provided suitable inflammatory microenvironment for bone formation. At late stage, several miRNAs directly regulate SMAD4, Estrogen receptor 1 and 5-hydroxytryptamine （serotonin） receptor 2C for bone formation. It can be concluded that miRNAs play important roles in balancing the inflammation and bone formation.

Geometry of Motion for Video Shakiness Detection

This paper presents a novel algorithm for automatically detecting global shakiness in casual videos. Per-frame amplitude is computed by the geometry of motion, based on the kinematic model defined by inter-frame geometric transformations. Inspired by motion perception, we investigate the just-noticeable amplitude of shaky motion perceived by the human visual system. Then, we use the thresholding contrast strategy on the statistics of per-frame amplitudes to determine the occurrence of perceived shakiness. For testing the detection accuracy, a dataset of video clips is constructed with manual shakiness label as the ground truth. The experiments demonstrate that our algorithm can obtain good detection accuracy that is in concordance with subjective judgement on the videos in the dataset.