Ai Qun Liu

Bio: Ai Qun Liu is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Resonator & Optical switch. The author has an hindex of 54, co-authored 594 publications receiving 11127 citations. Previous affiliations of Ai Qun Liu include Chinese Ministry of Education & ESIEE Paris.

High-Efficiency Broadband Meta-Hologram with Polarization-Controlled Dual Images

Abstract: Holograms, the optical devices to reconstruct predesigned images, show many applications in our daily life. However, applications of hologram are still limited by the constituent materials and therefore their working range is trapped at a particular electromagnetic region. In recent years, the metasurfaces, an array of subwavelength antenna with varying sizes, show the abilities to manipulate the phase of incident electromagnetic wave from visible to microwave frequencies. Here, we present a reflective-type and high-efficiency meta- hologram fabricated by metasurface for visible wavelength. Using gold cross nanoantennas as building blocks to construct our meta-hologram devices with thickness ∼ λ/4, the reconstructed images of meta-hologram show polarization- controlled dual images with high contrast, functioning for both coherent and incoherent light sources within a broad spectral range and under a wide range of incidence angles. The flexibility demonstrated here for our meta-hologram paves the road to a wide range of applications related to holographic images at arbitrary electromagnetic wave region.

Mechanism of multisoliton formation and soliton energy quantization in passively mode-locked fiber lasers

Abstract: We report results of numerical simulations on multiple-soliton generation and soliton energy quantization in a soliton fiber ring laser passively mode locked by using the nonlinear polarization rotation technique. We found numerically that the formation of multiple solitons in the laser is caused by a peak-power-limiting effect of the laser cavity. It is also the same effect that suppresses the soliton pulse collapse, an intrinsic feature of solitons propagating in gain media, and makes the solitons stable in the laser. Furthermore, we show that the soliton energy quantization observed in the lasers is a natural consequence of the gain competition between the multiple solitons. Enlightened by the numerical result we speculate that multisoliton formation and soliton energy quantization observed in other types of soliton fiber lasers could have a similar mechanism.

Context Contrasted Feature and Gated Multi-scale Aggregation for Scene Segmentation

Abstract: Scene segmentation is a challenging task as it need label every pixel in the image. It is crucial to exploit discriminative context and aggregate multi-scale features to achieve better segmentation. In this paper, we first propose a novel context contrasted local feature that not only leverages the informative context but also spotlights the local information in contrast to the context. The proposed context contrasted local feature greatly improves the parsing performance, especially for inconspicuous objects and background stuff. Furthermore, we propose a scheme of gated sum to selectively aggregate multi-scale features for each spatial position. The gates in this scheme control the information flow of different scale features. Their values are generated from the testing image by the proposed network learnt from the training data so that they are adaptive not only to the training data, but also to the specific testing image. Without bells and whistles, the proposed approach achieves the state-of-the-arts consistently on the three popular scene segmentation datasets, Pascal Context, SUN-RGBD and COCO Stuff.

The Poisson distribution and beyond: methods for microfluidic droplet production and single cell encapsulation

Abstract: There is a recognized and growing need for rapid and efficient cell assays, where the size of microfluidic devices lend themselves to the manipulation of cellular populations down to the single cell level. An exceptional way to analyze cells independently is to encapsulate them within aqueous droplets surrounded by an immiscible fluid, so that reagents and reaction products are contained within a controlled microenvironment. Most cell encapsulation work has focused on the development and use of passive methods, where droplets are produced continuously at high rates by pumping fluids from external pressure-driven reservoirs through defined microfluidic geometries. With limited exceptions, the number of cells encapsulated per droplet in these systems is dictated by Poisson statistics, reducing the proportion of droplets that contain the desired number of cells and thus the effective rate at which single cells can be encapsulated. Nevertheless, a number of recently developed actively-controlled droplet production methods present an alternative route to the production of droplets at similar rates and with the potential to improve the efficiency of single-cell encapsulation. In this critical review, we examine both passive and active methods for droplet production and explore how these can be used to deterministically and non-deterministically encapsulate cells.

Micromachined tunable metamaterials: a review

Abstract: This paper reviews micromachined tunable metamaterials, whereby the tuning capabilities are based on the mechanical reconfiguration of the lattice and/or the metamaterial element geometry. The primary focus of this review is the feasibility of the realization of micromachined tunable metamaterials via structure reconfiguration and the current state of the art in the fabrication technologies of structurally reconfigurable metamaterial elements. The micromachined reconfigurable microstructures not only offer a new tuning method for metamaterials without being limited by the nonlinearity of constituent materials, but also enable a new paradigm of reconfigurable metamaterial-based devices with mechanical actuations. With recent development in nanomachining technology, it is possible to develop structurally reconfigurable metamaterials with faster tuning speed, higher density of integration and more flexible choice of the working frequencies.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Dual Attention Network for Scene Segmentation

Abstract: In this paper, we address the scene segmentation task by capturing rich contextual dependencies based on the self-attention mechanism. Unlike previous works that capture contexts by multi-scale features fusion, we propose a Dual Attention Networks (DANet) to adaptively integrate local features with their global dependencies. Specifically, we append two types of attention modules on top of traditional dilated FCN, which model the semantic interdependencies in spatial and channel dimensions respectively. The position attention module selectively aggregates the features at each position by a weighted sum of the features at all positions. Similar features would be related to each other regardless of their distances. Meanwhile, the channel attention module selectively emphasizes interdependent channel maps by integrating associated features among all channel maps. We sum the outputs of the two attention modules to further improve feature representation which contributes to more precise segmentation results. We achieve new state-of-the-art segmentation performance on three challenging scene segmentation datasets, i.e., Cityscapes, PASCAL Context and COCO Stuff dataset. In particular, a Mean IoU score of 81.5% on Cityscapes test set is achieved without using coarse data.

Gold nanoparticles in chemical and biological sensing.

Abstract: Detection of chemical and biological agents plays a fundamental role in biomedical, forensic and environmental sciences1–4 as well as in anti bioterrorism applications.5–7 The development of highly sensitive, cost effective, miniature sensors is therefore in high demand which requires advanced technology coupled with fundamental knowledge in chemistry, biology and material sciences.8–13 In general, sensors feature two functional components: a recognition element to provide selective/specific binding with the target analytes and a transducer component for signaling the binding event. An efficient sensor relies heavily on these two essential components for the recognition process in terms of response time, signal to noise (S/N) ratio, selectivity and limits of detection (LOD).14,15 Therefore, designing sensors with higher efficacy depends on the development of novel materials to improve both the recognition and transduction processes. Nanomaterials feature unique physicochemical properties that can be of great utility in creating new recognition and transduction processes for chemical and biological sensors15–27 as well as improving the S/N ratio by miniaturization of the sensor elements.28 Gold nanoparticles (AuNPs) possess distinct physical and chemical attributes that make them excellent scaffolds for the fabrication of novel chemical and biological sensors (Figure 1).29–36 First, AuNPs can be synthesized in a straightforward manner and can be made highly stable. Second, they possess unique optoelectronic properties. Third, they provide high surface-to-volume ratio with excellent biocompatibility using appropriate ligands.30 Fourth, these properties of AuNPs can be readily tuned varying their size, shape and the surrounding chemical environment. For example, the binding event between recognition element and the analyte can alter physicochemical properties of transducer AuNPs, such as plasmon resonance absorption, conductivity, redox behavior, etc. that in turn can generate a detectable response signal. Finally, AuNPs offer a suitable platform for multi-functionalization with a wide range of organic or biological ligands for the selective binding and detection of small molecules and biological targets.30–32,36 Each of these attributes of AuNPs has allowed researchers to develop novel sensing strategies with improved sensitivity, stability and selectivity. In the last decade of research, the advent of AuNP as a sensory element provided us a broad spectrum of innovative approaches for the detection of metal ions, small molecules, proteins, nucleic acids, malignant cells, etc. in a rapid and efficient manner.37 Figure 1 Physical properties of AuNPs and schematic illustration of an AuNP-based detection system. In this current review, we have highlighted the several synthetic routes and properties of AuNPs that make them excellent probes for different sensing strategies. Furthermore, we will discuss various sensing strategies and major advances in the last two decades of research utilizing AuNPs in the detection of variety of target analytes including metal ions, organic molecules, proteins, nucleic acids, and microorganisms.