Single-bonded cubic form of nitrogen

Nitrogen usually consists of molecules where two atoms are strongly triple-bonded. Here, we report on an allotropic form of nitrogen where all atoms are connected with single covalent bonds, similar to carbon atoms in diamond. The compound was synthesized directly from molecular nitrogen at temperatures above 2,000 K and pressures above 110 GPa using a laser-heated diamond cell. From X-ray and Raman scattering we have identified this as the long-sought-after polymeric nitrogen with the theoretically predicted cubic gauche structure (cg-N). This cubic phase has not been observed previously in any element. The phase is a stiff substance with bulk modulus >or=300 GPa, characteristic of strong covalent solids. The polymeric nitrogen is metastable, and contrasts with previously reported amorphous non-molecular nitrogen, which is most likely a mixture of small clusters of non-molecular phases. The cg-N represents a new class of single-bonded nitrogen materials with unique properties such as energy capacity: more than five times that of the most powerfully energetic materials.     

Ascertaining the importance of neurons to develop better brain-machine interfaces

In the design of brain-machine interface (BMI) algorithms, the activity of hundreds of chronically recorded neurons is used to reconstruct a variety of kinematic variables. A significant problem introduced with the use of neural ensemble inputs for model building is the explosion in the number of free parameters. Large models not only affect model generalization but also put a computational burden on computing an optimal solution especially when the goal is to implement the BMI in low-power, portable hardware. In this paper, three methods are presented to quantitatively rate the importance of neurons in neural to motor mapping, using single neuron correlation analysis, sensitivity analysis through a vector linear model, and a model-independent cellular directional tuning analysis for comparisons purpose. Although, the rankings are not identical, up to sixty percent of the top 10 ranking cells were in common. This set can then be used to determine a reduced-order model whose performance is similar to that of the ensemble. It is further shown that by pruning the initial ensemble neural input with the ranked importance of cells, a reduced sets of cells (between 40 and 80, depending upon the methods) can be found that exceed the BMI performance levels of the full ensemble.     

V2O5 nanofibre sheet actuators

Vanadium oxides, such as V2O5, are promising for lithium-ion batteries, catalysis, electrochromic devices and sensors. Vanadium oxides were proposed more than a decade ago for another redox-dependent application: the direct conversion of electrical energy to mechanical energy in actuators (artificial muscles). Although related conducting polymer and carbon nanotube actuators have been demonstrated, electromechanical actuators based on vanadium oxides have not be realized. V2O5 nanofibres and nanotubes provide the potential advantages of low-cost synthesis by sol-gel routes and high charging capacity and long cycle life. Here, we demonstrate electromechanical actuation for obtained high modulus V2O5 sheets comprising entangled V2O5 nanofibres. The high surface area of these V2O5 sheets facilitates electrochemical charge injection and intercalation that causes the electromechanical actuation. We show that the V2O5 sheets provide high Young's modulus, high actuator-generated stress, and high actuator stroke at low applied voltage.     

Accurate spatio-temporal reconstruction of missing data in dynamic scenes

In this paper, the accurate method for texture reconstruction with non-desirable moving objects into dynamic scenes is proposed. This task is concerned to editor off-line functions, and the main criteria are the accuracy and visibility of the reconstructed results. The method is based on a spatio-temporal analysis and includes two stages. The first stage uses a feature points tracking to locate the rigid objects accurately under the assumption of their affine motion model. The second stage involves the accurate reconstruction of video sequence based on texture maps of smoothness, structural properties, and isotropy. These parameters are estimated by three separate neural networks of a back propagation. The background reconstruction is realized by a tile method using a single texton, a line, or a field of textons. The proposed technique was tested into reconstructed regions with a frame area up to 8–20%. The experimental results demonstrate more accurate inpainting owing to the improved motion estimations and the modified texture parameters.     

PROTECTION AGAINST SYSTEM RESEARCH

In our study we analyze information restrictions determined by researchers when creating ideal objects of the real world and we classify types of researchers and describe methods of protection against system research.     

Lot-sizing on a single imperfect machine: ILP models and FPTAS extensions

A single-machine multi-product lot-sizing and sequencing problem is studied. In this problem, items of n different products are manufactured in lots. Demands for products as well as per item processing times are known. There are losses of productivity because of non perfect production. There is also a sequence dependent set-up time between lots of different products. Machine yields and product lead times are assumed to be known deterministic functions. The objective is to minimize the cost of the demand dissatisfaction provided that the total processing time does not exceed a given time limit. We propose two integer linear programming (ILP) models for the NP-hard “fraction defective” case of this problem and compare effectiveness of their ILOG CPLEX realizations with a dynamic programming algorithm in a computer experiment. We also show how an earlier developed fully polynomial time approximation scheme (FPTAS) and one of the ILP models can be extended for a more complex case.     

Characterizations of detectability notions in terms of discontinuous dissipation functions

We consider a new Lyapunov-type characterization of detectability for non-linear systems without controls, in terms of lower-semicontinuous (not necessarily smooth, or even continuous) dissipation functions, and prove its equivalence to the GASMO (global asymptotic stability modulo outputs) and UOSS (uniform output-to-state stability) properties studied in previous work. The result is then extended to provide a construction of a discontinuous dissipation function characterization of the IOSS (input-to-state stability) property for systems with controls. This paper complements a recent result on smooth Lyapunov characterizations of IOSS. The utility of non-smooth Lyapunov characterizations is illustrated by application to a well-known transistor network example.     

Relaxation Properties of Pressure-sensitive Adhesives upon Withdrawal of Bonding Pressure

Relaxation properties of pressure-sensitive adhesives (PSA) have been studied with the squeeze-recoil tester used in the regime of parallel-plate dilatometer under conditions imitating the removal of compressive force in the course of adhesive bond formation. The relaxation properties of PSAs are compared with their adhesive behavior measured using the 180-Deg Peel Test. Two classes of PSAs are considered: 1) conventional rubbery adhesives based on the mixtures of styrene-isoprene-styrene (SIS) block copolymer with a tackifier resin and a plasticizer, and butyl rubber plasticized with low-molecular-weight polyisobutylene, and 2) hydrophilic PSAs composed of the blends of high-molecular-weight poly(N-vinyl pyrrolidone) (PVP) with oligomeric polyethylene glycol (PEG). By comparing the adhesive and relaxation behaviors of different PSAs, the relaxation criteria for pressure-sensitive adhesion have been stated. Relaxation behavior of the examined PSAs demonstrates two values of retardation time: the shorter retardation time of 10–70?sec and the longer time of 300–660?sec. These times can be associated, respectively, with small- and large-scale mechanisms of strain recovery. By comparing the relaxation and adhesive properties of PVP-PEG blend (which involves the formation of a hydrogen-bonded network through both terminal hydroxyl groups in PEG short chains) with the properties of covalently crosslinked copolymers of vinyl pyrrolidone (VP) with PEG-diacrylate and comb-like VP copolymers with PEG-monomethacrylate, the contributions of covalent crosslinking and H-bonding network have been characterized.     

Efficient Output Mode Converter for 30 GHz Gyroklystron at IAP

An output mode converter for Ka-band multi-MW gyroklystron in the Institute of Applied Physics (IAP) operating in the TE₅₃ mode is suggested. Two variants of the converter, aimed for different applications, are presented: the TE₅₃ to TE₀₁ mode converter with power output along the device axis and the TE₅₃ mode to Gaussian wavebeam quasi-optical converter with a visor. The suggested designs include the built-in electron beam collector. The converters were designed using a new synthesis algorithm, which implies iterative improvement of the waveguide wall shape in order to achieve high efficiency. The calculation results were proven by HFSS simulation and low-power tests of one version of the converter.