Dynamics of quantum dissipation systems interacting with fermion and boson grand canonical bath ensembles: Hierarchical equations of motion approach

A hierarchical equations of motion formalism for a quantum dissipation system in a grand canonical bath ensemble surrounding is constructed on the basis of the calculus-on-path-integral algorithm, together with the parametrization of arbitrary non-Markovian bath that satisfies fluctuation-dissipation theorem. The influence functionals for both the fermion or boson bath interaction are found to be of the same path integral expression as the canonical bath, assuming they all satisfy the Gaussian statistics. However, the equation of motion formalism is different due to the fluctuation-dissipation theories that are distinct and used explicitly. The implications of the present work to quantum transport through molecular wires and electron transfer in complex molecular systems are discussed. (c) 2007 American Institute of Physics.

Nanoelectrode ensembles based on semi-interpenetrating network of carbon nanotubes

A method for preparing nanoelectrode ensembles based on semi-interpenetrating network (SIN) of multi-walled carbon nanotubes (MWNTs) on gold electrode through phase-separation method is initially proposed. Individual nanoelectrode owns irregular three-dimensional MWNTs networks, which is denoted as SIN-MWNTs. On the as-prepared SIN-MWNTs nanoelectrode ensembles, the assembled MWNTs clusters in nanoscale serve as individual nanoelectrode and the electroinactive lipid networks located on the top of alkanethiol monolayer are used as a shielding layer. Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), tapping-mode atomic force microscopy (TM-AFM) and scanning electron microscopy (SEM) were used to characterize the as-prepared SIN-MWNT nanoelectrode ensembles. Experimental results indicate that the well-defined nanoelectrode ensembles were prepared through self-assembly technology. Meantime, sigmoid curves in a wide scanning range can be obtained in CV experiments. This study may pave the way for the construction of truly nanoscopic nanoelectrode arrays by bottom-up strategy.

Investigation of electrochemical charging behaviors of "naked" gold nanoparticles ensembles in aqueous media

Gold nanopartides were Immobilized onto the electrode surface by simple self-assembly technique. Interestingly, the ensembles of these nanopartides exhibit quantized charging behaviors in aqueous solution. Possible mechanism for such behaviors was proposed.

Fabrication of Au(111) single-crystal nanoisland-arrayed electrode ensembles by template-directed seeding growth

A new and simple approach for preparation of Au(111) single-crystal nanoisland - arrayed electrode ensembles, based on fine colloidal Au monolayer-directed seeding growth, is reported.

Colloid chemical approach to nanoelectrode ensembles with highly controllable active area fraction

A novel "bottom-up" approach to highly controllable nanoelectrode ensembles (NEEs) has been developed using colloidal nanoparticle self-assembly techniques. Ibis solution-based strategy allows flexible control over nanoelectrode size, shape, and interspacing of the as-prepared NEEs. Atomic force microscopy (AFM) was proved to be a powerful tool to monitor the NEE topography, which yields parameters that can be used to calculate the fractional nanoelectrode area of the NEEs. AFM, ac impedance, and cyclic voltammetry studies demonstrate that most of nanoelectrodes on the NEEs (at least by 9-min self-assembly) are not diffusionally isolated under conventional ac frequency range and scan rates. As a result, the NEEs behave as "nanoelectrode-patch" assemblies. Besides, the as-prepared NEEs by different self-assembling times show an adjustable sensitivity to heterogeneous electron-transfer kinetics, which may be helpful to sensor applications. Like these NEEs constructed by other techniques, the present NEEs prepared by chemical self-assembly also exhibit the enhancement of electroanalytical detection limit consistent with NEE theory prediction.

Studies of electrochemical quantized capacitance charging of surface ensembles of silver nanoparticles

CTAB-stabilized silver nanoparticles were synthesized by NaBH4 reduction. The as-prepared nanoparticles can be self-assembled on 3-mercaptopropionic acid (MPA) modified gold electrode, which was supported strongly by XPS measurements. Exceptional long-term stability of the as-prepared colloidal silver aqueous solution and the desorption of silver nanoparticle ensemble on MPA after alcohol rinsing proved that these CTAB molecules adsorbed on silver core formed interdigitated bilayer structure. DPV and differential capacitance measurements were performed to characterize the as-prepared silver nanoparticle ensemble. and the interesting quantized capacitance charging behaviors were observed.

Control of the orientational order and nonlinear optical response of the "push-pull" chromophore RuPZn via specific incorporation into densely packed monolayer ensembles of an amphiphilic four-helix bundle peptide: characterization of the peptide-chromophore complexes.

"Push-pull" chromophores based on extended pi-electron systems have been designed to exhibit exceptionally large molecular hyperpolarizabilities. We have engineered an amphiphilic four-helix bundle peptide to vectorially incorporate such hyperpolarizable chromophores having a metalloporphyrin moiety, with high specificity into the interior core of the bundle. The amphiphilic exterior of the bundle facilitates the formation of densely packed monolayer ensembles of the vectorially oriented peptide-chromophore complexes at the liquid-gas interface. Chemical specificity designed into the ends of the bundle facilitates the subsequent covalent attachment of these monolayer ensembles onto the surface of an inorganic substrate. In this article, we describe the structural characterization of these monolayer ensembles at each stage of their fabrication for one such peptide-chromophore complex designated as AP0-RuPZn. In the accompanying article, we describe the characterization of their macroscopic nonlinear optical properties.

Addressing Selective Polypharmacology of Antipsychotic Drugs Targeting the Bioaminergic Receptors through the Receptor Dynamic Conformational Ensembles

Selective polypharmacology, where a drug acts on multiple rather than single molecular targets involved in a disease, emerges to develop a structure-based system biology approach to design drugs selectively targeting a disease-active protein network. We focus on the bioaminergic receptors that belong to the group of integral membrane signalling proteins coupled to the G protein and represent targets for therapeutic agents against schizophrenia and depression. Among them, it has been shown that the serotonin (5-HT2A and 5-HT6), dopamine (D2 and D3) receptors induce a cognition-enhancing effect (group 1), while the histamine (H1) and serotonin (5-HT2C) receptors lead to metabolic side effects and the 5-HT2B serotonin receptor causes pulmonary hypertension (group 2). Thus, the problem arises to develop an approach that allows identifying drugs targeting only the disease-active receptors, i.e. group 1. The recent release of several crystal structures of the bioaminergic receptors, involving the D3 and H1 receptors provides the possibility to model the structures of all receptors and initiate a study of the structural and dynamic context of selective polypharmacology. In this work, we use molecular dynamics simulations to generate a conformational space of the receptors and subsequently characterize its binding properties applying molecular probe mapping. All-against-all comparison of the generated probe maps of the selected diverse conformations of all receptors with the Tanimoto similarity coefficient (Tc) enable to separate the receptors of group 1 from group 2. The pharmacophore built based on the Tc-selected receptor conformations, using the multiple probe maps discovers structural features that can be used to design molecules selective towards the receptors of group 1. The importance of several predicted residues to ligand selectivity is supported by the available mutagenesis and ligand structure-activity relationships studies. In addition, the Tc-selected conformations of the receptors for group 1 show good performance in isolation of known ligands from a random decoy. Our computational structure-based protocol to tackle selective polypharmacology of antipsychotic drugs could be applied for other diseases involving multiple drug targets, such as oncologic and infectious disorders.

Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

Fuzzy Ensembles for Embedding Adaptive Behaviours in Semi-Autonomous Avatars in 3D Virtual Worlds

Semi-autonomous avatars should be both realistic and believable. The goal is to learn from and reproduce the behaviours of the user-controlled input to enable semi-autonomous avatars to plausibly interact with their human-controlled counterparts. A powerful tool for embedding autonomous behaviour is learning by imitation. Hence, in this paper an ensemble of fuzzy inference systems cluster the user input data to identify natural groupings within the data to describe the users movement and actions in a more abstract way. Multiple clustering algorithms are investigated along with a neuro-fuzzy classifier; and an ensemble of fuzzy systems are evaluated.

U.W. Percussion and Steel Drum Ensembles, June 2, 2005

Concert Program for U.W. Percussion and Steel Drum Ensembles