Protein-gold nanoclusters for identification of amino acids by metal ions modulated ratiometric fluorescence

Here we report that the dual fluorescence emissions from protein-gold (Au) nanoclusters can greatly be modulated by metal ions and the resultant fluorescence ratiometric responses provide a novel sensory method for the identification of amino acids. The protein-gold (Au) nanoclusters were simply synthesized by the reduction of chloroauric acid with bovine serum albumin (BSA), which exhibit dual emissions: the blue at 425 nm from the oxides of BSA, and the red at 635 nm from Au nanoclusters. It has been demonstrated that different metal ions react with BSA-Au nanoclusters and thus greatly affect the two emissions in different ways by fluorescence enhancement or quenching. Interestingly, the addition of amino acids leads to fluorescence ratiometric changes through the interactions with the bound metal ions. When BSA-Au nanocluster probes modulated by four different metal ions were used together to construct a sensor array, different amino acids were clearly discriminated by the distinctive patterns of four ratiometric fluorescence responses. Results and methods reported here provide a unique strategy for the determination of amino acids.     

Fusion of visible and infrared images using saliency analysis and detail preserving based image decomposition

Image fusion for visible and infrared images is a significant task in image analysis. The target regions in infrared image and abundant detail information in visible image should be both extracted into the fused result. Thus, one should preserve or even enhance the details from original images in fusion process. In this paper, an algorithm using pixel value based saliency detection and detail preserving based image decomposition is proposed. Firstly, the multi-scale decomposition is constructed using weighted least squares filter for original infrared and visible images. Secondly, the pixel value based saliency map is designed and utilized for image fusion in different decomposition level. Finally, the fusion result is reconstructed by synthesizing different scales with synthetic weights. Since the information of original signals can be well preserved and enhanced with saliency extraction and multi scale decomposition process, the fusion algorithm performs robustly and excellently. The proposed approach is compared with other state-of the-art methods on several image sets to verify the effectiveness and robustness.     

跑道型结构光子晶体波导定向耦合器

鉴于波导定向耦合器在集成光路以及光电集成方面的广泛应用,提出了一种基于光子晶体波导间高效耦合的光子晶体定向耦合器。通过主波导和耦合波导间的耦合,可以实现对波长为1 490 nm和1 550 nm电磁波的高效分光。在将器件长度控制在30 μm左右的同时,其总效率高达93.05%。另外,发现主波导和耦合波导间介质柱结构参数对电磁波的耦合周期有着极大的影响。并通过将介质柱沿z方向拉伸0.1a(a为晶格周期),设计了工作波长为1 530 nm和1 540 nm的光子晶体定向耦合器,器件长度仅为60 μm。通过拉伸介质柱的纵向长度,可以大幅减小耦合周期,这对缩小器件体积以及实现更为密集的波分复用有着重要的意义。     

Copolypeptide-doped polyaniline nanofibers for electrochemical detection of ultratrace trinitrotoluene

This paper demonstrates a new electrochemical method for the detection of ultratrace amount of 2,4,6-trinitrotoluene (TNT) with synthetic copolypeptide-doped polyaniline nanofibers. The copolypeptide, comprising of glutamic acid (Glu) and lysine (Lys) units, is in situ doped into polyaniline through the protonation of the imine nitrogen atoms of polyaniline by the free carboxylic groups of Glu segments, resulting in the formation of polyaniline nanofibers of emeraldine salt. The free amino groups of Lys segments at the surface of nanofibers provide the receptor sites of TNT through the formation of charge-transfer complex between the electron-rich amino groups and the electron-deficient aromatic rings. Adsorptive stripping voltammetry results demonstrate that the poly(Glu-Lys)-doped nanofibers confined onto glassy carbon electrodes exhibit a remarkable enriching effect and thus sensitive electrochemical response to TNT with a linear dynamic range of 0.5-10 μM and a detection limit down to 100 nM. Moreover, other kinds of nitro compounds show different redox behaviors from TNT at the doped nanofibers, and thus do not interfere with the electrochemical detection of TNT. This study essentially offers a new and simple method for electrochemical detection of ultratrace TNT.     

Inverted Opal Fluorescent Film Chemosensor for the Detection of Explosive Nitroaromatic Vapors through Fluorescence Resonance Energy Transfer

This paper reports an inverted opal fluorescence chemosensor for the ultrasensitive detection of explosive nitroaromatic vapors through resonance‐energy‐transfer‐amplified fluorescence quenching. The inverted opal silica film with amino ligands was first fabricated by the acid–base interaction between 3‐aminopropyltriethoxysilane and surface sulfonic groups on polystyrene microsphere templates. The fluorescent dye was then chemically anchored onto the interconnected porous surface to form a hybrid monolayer of amino ligands and dye molecules. The amino ligands can efficiently capture vapor molecules of nitroaromatics such as 2,4,6‐trinitrotoluene (TNT) through the charge‐transfer complexing interaction between electron‐rich amino ligands and electron‐deficient aromatic rings. Meanwhile, the resultant TNT–amine complexes can strongly suppress the fluorescence emission of the chosen dye by the fluorescent resonance energy transfer (FRET) from the dye donor to the irradiative TNT–amino acceptor through intermolecular polar–polar resonance at spatial proximity. The quenching response of the highly ordered porous films with TNT is greatly amplified by at least 10‐fold that of the amorphous silica films, due to the interconnected porous structure and large surface‐to‐volume ratio. The inverted opal film with a stable fluorescence brightness and strong analyte affinity has lead to an ultrasensitive detection of several ppb of TNT vapor in air.     

Prediction of inter-residue contacts map based on genetic algorithm optimized radial basis function neural network and binary input encoding scheme

Summary Inter-residue contacts map prediction is one of the most important intermediate steps to the protein folding problem. In this paper, we focus on the problem of protein inter-residue contacts map prediction based on neural network technique. Firstly, we use a genetic algorithm (GA) to optimize the radial basis function widths and hidden centers of a radial basis function neural network (RBFNN), then a novel binary encoding scheme is employed to train the network for the purpose of learning and predicting the inter-residue contacts patterns of protein sequences got from the protein data bank (PDB). The experimental evidence indicates the utility of our proposed encoding strategy and GA optimized RBFNN. Moreover, the simulation results demonstrate that the network got a better performance for these proteins, whose residue length falls into the area of (100, 300), and the predicted accuracy with a contact threshold of 7 Å scores higher than the other 3 values with 5, 6, and 8 Å .     

A Versatile Anisometric Metallic Supercrystal with Controllable Orientation on a Chip as a Stable and Reliable Label‐Free Biosensor

Based on anisometric noble‐metal nanocrystals, a universal fabrication protocol for preparing 3D supercrystals with controlled orientation on a chip has been developed. A comparison of the surface‐enhanced Raman scattering (SERS) behavior of 3D nanorod supercrystals aligned vertically and parallel to the chip indicates that the SERS‐enhancing ability and reproducibility of the former is superior to the latter. The 3D nanorod supercrystals aligned vertically to the chip have been utilized as highly sensitive SERS substrates for the label‐free discrimination of Gram‐positive and ‐negative bacteria. Furthermore, to strengthen the stability of the supercrystal substrate for assays of bacteria in biosamples, a coating of the antibiotic vancomycin can dramatically increase adhesion of bacteria on a nanointerface and simultaneously improve the SERS response of bacteria to achieve a layer‐by‐layer assembled, stable, and reliable biosensor for bacteria.     

Green process of fuel production under porous γ-Al2O3 catalyst: Study of activation and deactivation kinetic for MTD process

One of the methods of industrial dimethyl ether production is the catalytic dehydration of methanol. In this research work, methanol dehydration reactor has been modeled using continuous model and its results have been compared with experimental works and Voronoi pore network model. A 1D heterogeneous dispersed plug flow model was utilized to model an adiabatic fixed-bed reactor for the catalytic dehydration of methanol to dimethyl ether. The mass and heat transfer equations are numerically solved for the reactor. The concentration of the reactant and products and also the temperature varies along the reactor, therefore the effectiveness factor would also change in the reactor. We used the the effectiveness factor that was simulated according to the diffusion and reaction in the catalyst pellet as a Voronoi pore network model. Sensitivity analysis was performed to determine the influence of T, P and weight hourly space velocity on performance of the chemical reactor. Acceptable agreement was reached between the measured and the model data. The results showed that the maximum reaction conversion was obtained about 90 % at WHSV = 10 h^?1 and T = 560 K, while the inlet temperature (T_inlet) had a greater effect on methanol conversion. In addition, the effect of water in the feed on methanol conversion was quantitatively studied. Also, the deactivation kinetics of γ-Al₂O₃ heterogeneous-acidic catalyst in methanol to dimethyl ether dehydration process was studied using integral analysis method. Based on independent deactivation kinetics, a second order was found that accurately fitted the experimental conversion time data. The main reaction activation energies and catalyst deactivation energies were 143.1 and ?102.1 kJ/mol, respectively.     

化学毒剂探测技术发展现状

化学毒剂(CWAs)作为一种大规模杀伤性武器,具有杀伤力强、影响范围广、防护困难、易于制作施放等特征,从诞生之初即常被用于战争冲突,在现代非对称战争、恐怖袭击中也造成了巨大威胁。因此如何及时地探测化学毒剂成为世界各国国土安全的重点研究方向。该文聚焦于化学毒剂现有主流及具有潜力的各类探测技术,对各种检测技术的基本原理及其军事、商用的具体应用情况以及最新的研究进展进行了分析,对世界各国的主要相关计划进行了介绍,并对化学毒剂探测技术所面临的困难和未来的发展进行了展望。     

声光双稳态系统混沌的周期扰动控制

声光双稳混沌系统的参量受到进行周期扰动,在一定扰动强度下,可实现对混沌的控制.通过数值模拟,证明该方法的有效性,并计算了系统随扰动强度的状态演化和李雅普诺夫指数演化,揭示了扰动强度与系统状态的关系.在此基础上的实验研究,实验证实了对声光双稳混沌系统进行参量扰动可以有效控制混沌.