Wavelet-based dynamic and privacy-preserving similitude data models for edge computing

Wireless Networks - The privacy-preserving data release is an increasingly important problem in today’s computing. As the end devices collect more and more data, reducing the amount of...     

The languages FCP(:) and FCP(:,?)

The language FCP(:,?) is the outcome of attempts to integrate the best of several flat concurrent logic programming languages, including Flat GHC, FCP (↓, |) and Flat Concurrent Prolog, in a single consistent framework. FCP(:) is a subset of FCP(:, ?), which is a variant of FPP(↓, |) and employs concepts of the concurrent constraint framework of cc(↓, |). FCP(:, ?) is a language which is strong enough to accommodate all useful concurrent logic programming techniques, including those which rely on atomic test unification and read-only variables, yet incorporates the weaker languages mentioned as subsets. This allows the programmer to remain within a simple subset of the language such as Flat GHC when the full power of atomic unification or read-only variables is not needed.     

Active tracking and pursuit under different levels of occlusion: a two-layer approach

We present an algorithm for real-time, robust, vision-based active tracking and pursuit. The algorithm was designed to overcome problems arising from active vision-based pursuit, such as target occlusion. Our method employs two layers to deal with occlusions of different lengths. The first layer is for short- or medium-term occlusions: those where a known method—such as mean shift combined with a Kalman filter—fails. For this layer we designed the hybrid filter for active pursuit (HAP). HAP utilizes a Kalman filter modified to respond to two different modes of action: one in which the target is positively identified and one in which the target identification is uncertain. For long-term occlusions we use the second layer. This layer is a decision algorithm that follows a learning procedure and is based on game theory-related reinforcement (Cesa-Bianchi and Lugosi, Prediction Learning and Games, 2006). The learning process is based on trial and error and is designed to perform adequately with a small number of samples. The algorithm produces a data structure that can be shared among agents or sent to a central control of a multi-agent system. The learning process is designed so that agents perform tasks according to their skills: an efficient agent will pursue targets while an inefficient agent will search for entering targets. These capacities make this system well suited for embedding in a multi-agent control system.     

Self-assembly of peptide nanotubes and amyloid-like structures by charged-termini-capped diphenylalanine peptide analogues

We had recently demonstrated that the diphenylalanine peptide, the core recognition motif of the Alzheimer's ß-amyloid polypeptide, self-assembles into a novel class of peptide nanotubes. The formation of well-ordered supramolecular structures at the nanoscale by such a simple peptide was consistent with our suggestion that aromatic interactions may provide order and directionality needed for the formation of fibrillar peptide structures. Yet, we could not rule out a contribution of the charged amine and carboxyl moieties at the termini of the short peptide. In order to explore the potential role of electrostatic interaction in the assembly process we have studied a modified non-charged peptide analogue, Ac-Phe–Phe-NH₂, in which the N-terminal amine was acetylated and the C-terminal carboxyl was amidated. Scanning and transmission electron microscopy analyses demonstrated that this peptide analogue self-assembles into highly-ordered tubular structures, as observed with the NH₂-Phe–Phe-COOH. Also, infrared spectroscopy revealed an amide I absorbance pattern that is very similar to that of the non-modified peptide. Furthermore, an amidated NH₂-Phe–Phe-NH₂ peptide, which has a net positive charge, also self-assembled into ordered tubular structures. On the other hand, the amine-modified analogues Boc-Phe–Phe-COOH, Z-Phe–Phe-COOH, and Fmoc-Phe–Phe-COOH peptides formed amyloid-like structures that had a significantly smaller diameter. Taken together, the current study further supports our hypothesis regarding the role of aromatic interactions in the self-assembly of amyloid fibrils and amyloid-associated nanostructures that can be modulated by simple chemical modifications.     

Influence of the shear flow on electron cyclotron resonance plasma confinement in an axisymmetric magnetic mirror trap of the electron cyclotron resonance ion source

Influence of shear flows of the dense plasma created under conditions of the electron cyclotron resonance (ECR) gas breakdown on the plasma confinement in the axisymmetric mirror trap ("vortex" confinement) was studied experimentally and theoretically. A limiter with bias potential was set inside the mirror trap for plasma rotation. The limiter construction and the optimal value of the potential were chosen according to the results of the preliminary theoretical analysis. This method of "vortex" confinement realization in an axisymmetric mirror trap for non-equilibrium heavy-ion plasmas seems to be promising for creation of ECR multicharged ion sources with high magnetic fields, more than 1 T.     

Front dynamics in catalytic surface reactions

A variety of pattern formation phenomena in catalytic surface reactions can be attributed to the dynamics of interfaces, or fronts, separating distinct uniform states. The states may represent surface coverages by different adsorbates or in the case of forced oscillations, different phases of oscillation. The dynamics of fronts are strongly affected by front instabilities and by diffusion anisotropy. We identify two new pattern formation mechanisms associated with different front behaviors in orthogonal directions: an ordering process by which stationary labyrinths in an isotropic system evolve into ordered stationary stripes, and confinement of isotropic spatiotemporal chaos to one space dimension, a state we term stratified chaos.