A photoluminescence-based quantum semiconductor biosensor for rapid in situ detection of Escherichia coli

This work describes a novel method of detecting Escherichia coli using photoluminescence (PL) emission from III–V quantum semiconductor (QS) devices functionalized with two different antibody-based architectures. The first approach employed self-assembled monolayers of biotinylated polyethylene glycol thiols to immobilize biotinylated antibody via neutravidin. In the second approach, we used QS microstructures coated with a thin layer of Si₃N₄ allowing direct functionalization with E. coli antibodies through hydrofluoric acid etching and glutaraldehyde-based reticulation. Atomic force, optical and fluorescence microscopy measurements were used to assess the immobilization process. Depending on the biosensing architecture, density of the immobilized bacteria was observed in the range of 0.5–0.7 bacteria/100 μm². The detection of E. coli at 10⁴ CFU/ml was achieved within less than 120 min of the bacteria exposure. It is expected that an even better sensitivity threshold could be achieved following further optimization of the method.     

Synthesis of quantum size ZnO crystals and their gas sensing properties for NO2

Quantum size ZnO crystals have been synthesized successfully by a room temperature sol-gel process. Oleic acid (OA) has been used as capping agent to control the particle size of ZnO. The crystal structure and size of the ZnO are characterized by the X-ray diffraction (XRD) and transmission electron microscope (TEM). The XRD results show the as-synthesized ZnO has hexagonal wurtzite structure and the average crystallite size is 5.7 nm which is little less than TEM result. It is testified by photoluminescence (PL) and Raman spectra that the quantum size ZnO keeps the crystal structure of the bulk ZnO and possesses more surface defects. The quantum size ZnO has the highest response of 280 to NO₂ and the highest selectivity of 31 and 49 corresponding to CO and CH₄ at operating temperature of 290 °C. The effect of calcination temperatures on sensing property and transient response of the ZnO sensor are also investigated.     

On a class of languages recognizable by probabilistic reversible decide-and-halt automata

We analyze the properties of probabilistic reversible decide-and-halt automata (DH-PRA) and show that there is a strong relationship between DH-PRA and 1-way quantum automata. We show that a general class of regular languages is not recognizable by DH-PRA by proving that two “forbidden” constructions in minimal deterministic automata correspond to languages not recognizable by DH-PRA. The shown class is identical to a class known to be not recognizable by 1-way quantum automata. We also prove that the class of languages recognizable by DH-PRA is not closed under union and other non-trivial Boolean operations.     

Analysis and synthesis of attractive quantum Markovian dynamics

We propose a general framework for investigating a large class of stabilization problems in Markovian quantum systems. Building on the notions of invariant and attractive quantum subsystem, we characterize attractive subspaces by exploring the structure of the invariant sets for the dynamics. Our general analysis results are exploited to assess the ability of open-loop Hamiltonian and output-feedback control strategies to synthesize Markovian generators which stabilize a target subsystem, subspace, or pure state. In particular, we provide an algebraic characterization of the manifold of stabilizable pure states in arbitrary finite-dimensional Markovian systems, that leads to a constructive strategy for designing the relevant controllers. Implications for stabilization of entangled pure states are addressed by example.     

The quantum query complexity of the determinant

In this paper we give tight quantum query complexity bounds of some important linear algebra problems. We prove Θ(n²) quantum query bounds for verify the determinant, rank, matrix inverse and the matrix power problem.     

Convergence performance comparison of quantum-inspired multi-objective evolutionary algorithms

In recent research, we proposed a general framework of quantum-inspired multi-objective evolutionary algorithms (QMOEA) and gave one of its sufficient convergence conditions to the Pareto optimal set. In this paper, two Q-gate operators, H gate and R&N gate, are experimentally validated as two Q-gate paradigms meeting the convergence condition. The former is a modified rotation gate, and the latter is a combination of rotation gate and NOT gate with the specified probability. To investigate their effectiveness and applicability, several experiments on the multi-objective 0/1 knapsack problems are carried out. Compared to two typical evolutionary algorithms and the QMOEA only with rotation gate, the QMOEA with H gate and R&N gate have more powerful convergence ability in high complex instances. Moreover, the QMOEA with R&N gate has the best convergence in almost all of the experimental problems. Furthermore, the appropriate ε value regions for two Q-gates are verified.     

一种基于量子密码的卫星网络窃听攻击检测方法

鉴于窃听攻击是对卫星网络实施各类高级攻击行为的基础,结合量子密码在未来卫星网络的应用趋势,提出了一种基于量子密码的卫星网络窃听攻击检测方法。首先,基于卫星网络节点在空间分布上的分层特点,构建了层簇式的卫星网络窃听攻击检测模型。实际检测过程中,相邻卫星节点检测到窃听攻击威胁时,将相关预警信息经簇首节点融合后通过安全信道传送到地面控制中心,随后再根据地面控制中心反馈的安全链路构建方案构建节点间的安全通信链路。最后,对方案的安全性及有效性进行了分析。相关成果可为进一步深入开展卫星网络安全防护技术研究打下一定的基础。     

Modelling microtubules in the brain as n-qudit quantum Hopfield network and beyond

The scientific approach to understand the nature of consciousness revolves around the study of the human brain. Neurobiological studies that compare the nervous system of different species have accorded the highest place to humans on account of various factors that include a highly developed cortical area comprising of approximately 100 billion neurons, that are intrinsically connected to form a highly complex network. Quantum theories of consciousness are based on mathematical abstraction and the Penrose–Hameroff Orch-OR theory is one of the most promising ones. Inspired by the Penrose–Hameroff Orch-OR theory, Behrman et al. have simulated a quantum Hopfield neural network with the structure of a microtubule. They have used an extremely simplified model of the tubulin dimers with each dimer represented simply as a qubit, a single quantum two-state system. The extension of this model to n-dimensional quantum states or n-qudits presented in this work holds considerable promise for even higher mathematical abstraction in modelling consciousness systems.     

小麦产量实时测报系统

针对当前河南地区小麦产量估测信息滞后问题,集成传感技术、GPS和无线通信技术,对接农机收获装备,构建基于多传感器技术的小麦产量测报信息服务系统,实现小麦收割与产量测报同步进行.系统的应用实验于2015年6月在许昌市长葛县800亩试验田进行,实验结果表明,系统的产量测报误差小于5%,可以满足小麦产量测报的实际需求.系统的推广应用为河南及全国的小麦产量测报提供数据参考,为获知农田信息的时空差异性提供数据支撑,为实施“精细农作”提供决策依据.     

基于量子遗传算法的水下图像增强

随着海洋工程以及海洋科学研究的发展,水下图像增强越来越受到大家的关注。针对水下图像噪声大、对比度低、且边缘和纹理模糊等特点,采用了一种量子遗传算法,在小波域对图像进行非线性增强。实验表明,该算法能较好的实现水下图像增强。