SOME EXTENDED RESULTS OF“SUBHARMONIC RESONANCE BIFURCATION THEORY OF NONLINEAR MATHIEU EQUATION”

The authors of [1] discussed the subharmonic resonance bifurcation theory of nonlinear Mathieu equation and obtained six bifurcation diagrams in -plane. In this paper, we extended the results of[1] and pointed out that there may exist as many as fourteen bifurcation diagrams which are not topologically equivalent to each other.

Spin resonance transport properties of a single Au atom in S–Au–S junction and Au–Au–Au junction

The spin transport properties of S–Au–S junction and Au–Au–Au junction between Au nanowires are investigated with density functional theory and the non-equilibrium Green＇s function. We mainly focus on the spin resonance transport properties of the center Au atom. The breaking of chemical bonds between anchor atoms and center Au atom significantly influences their spin transmission characteristics. We find the 0.8 eV orbital energy shift between anchor S atoms and the center Au atom can well protect the spin state stored in the S–Au–S junction and efficiently extract its spin state to the current by spin resonance mechanism, while the spin interaction of itinerant electrons and the valence electron of the center Au atom in the Au–Au–Au junction can extract the current spin information into the center Au atom. Fermi energy drift and bias-dependent spin filtering properties of the Au–Au–Au junction may transform information between distance, bias,and electron spin. Those unique properties make them potential candidates for a logical nanocircuit.

Learning Vector Coding Methods of ART1 and Their Applications

As one of the unsupervised learning models, ART1 has been widely used in data mining or other fields, while coding of it’s learning vector is very important. Their input vector coding methods and learning vector coding methods are described in detail. The corresponding applications are given.

An artificial neural network for detecting weld position in arc welding process

A kind of self organizing artificial neural network used for weld detection is presented in this paper, and its concepts and issues are discussed. The network can transform the weld visual information into typical patterns and match with the weld data collected on line, and so realize the accurate detection of the weld position in arc welding process.

Relation between singularity expansion method (SEM) and resonance scattering theory (RST)

In recent years there are two theories for the acoustic scattering, one is the Singularity Expansion Method (SEM) , the other is the Resonance Scattering Theory (RST). In this paper, relation between these two theories was established. For the examples of the acoustic scattering from the solid elastic cylinder and sphere immersed in water, we prove that the RST can be directly derived from the SEM, so that these two theories are equivalent. By use of the Mittag- Leffler theorem we expand the pure elastic scattering wave, which is extracted by isolating the rigid background from the total scattering wave, in an exact resonance expansion. We specially prove that the reradiation efficiency and the resonance width are nearly proportional to the imaginary part of the corresponding pole for most solid objects immersed in water. This shows that the resonance scattering behavious can be entirely determined by the complex frequency poles. For the cases of an aluminum cylinder and a tungsten carbide sphere immersed in water, we calculate the partial-wave form functions by using the new resonance formulae. The results agree with the exact calculation well.

Space and Human Consciousness: The Great Whisper

Human Consciousness is one of most elusive issues in the scientific history. Its nature created major historical debate started thousands of years ago and still ongoing. Despite the explosive developments in the last century to explore its nature, the knowledge about it is still deficient. The important advances in the twentieth and 21st centuries in understanding cerebral cortex dynamics fortified by the dominant materialistic approach of the era dictated its impact on consciousness science, which is perceived as sole human brain function. This original review is a call for holistic perception of human consciousness incorporating the ancient wisdom of the human civilizations with the massive current era advances in different disciplines of applied sciences. The description of René Descartes in the 17th century of the Cartesian dualism is timely to revisit with new holistic perspective, in view of the major advances of our understanding of heart brain communications, astrophysical resonances with human heart ascending afferents to central nervous system, and signaling between humans and the space. Universal vibrations, frequencies and resonances as perceived by Nikola Tesla constitute the core of our new conceptual and experimental perspective on human consciousness. Neural and psychological correlates of human consciousness which dominate the consciousness research nowadays should undergo revolutionary conceptual understanding to perceive consciousness as a massive universal event expanding from human genes to galaxies. In the next discussion, we are going to navigate in the nature and fate of human consciousness with new innovative universal perspective based on heart rate variability of human heart and its cosmic resonances as represented by Schumann Resonances, Solar Wind Indices and Galactic Cosmic Rays. The interpretation of our existential secrets and biology without the space around us is a major gap in our scientific perception of life. The delicate orchestration between human heart and the space frequencies create the great whisper which in our perspective, encodes the secrets of human consciousness.

Analysis of Binding Interaction between Captopril and Human Serum Albumin

The interaction between captopril, an inhibitor of angiotensin converting enzyme and human serum albumin, a principal plasma protein in the liver has been investigated in vitro under a simulated physiological condition by UV-vis spectrophotometry and fluorescence spectrometry. The intrinsic fluorescence intensity of human serum albumin was strongly quenched by captopril. The binding constants and the number of binding sites can be calculated from the data obtained from fluorescence quenching experiments. The negative value of ΔG0 reveals that the binding process is a spontaneous process. According to the van’t Hoff equation, the standard enthalpy change (ΔH0) and standard entropy change (ΔS0) for the reaction were calculated to be 35.98 KJ●mol-1 and 221.25 J●mol-1 K. It indicated that the hydrophobic interactions play a main role in the binding of captopril to human serum albumin. In addition, the distance between captopril (acceptor) and tryptophan residues of human serum albumin (donor) was estimated to be 1.05 nm according to the F?rster’s resonance energy transfer theory. The results obtained herein will be of biological significance in pharmacology and clinical medicine.

SOLVABILITY FOR FRACTIONAL FUNCTIONAL DIFFERENTIAL EQUATION BOUNDARY VALUE PROBLEMS AT RESONANCE

The paper deals a fractional functional boundary value problems with integral boundary conditions. Besed on the coincidence degree theory, some existence criteria of solutions at resonance are established.

Neural network based method for background modeling and detecting moving objects

This paper proposes a novel method, primarily based on the fuzzy adaptive resonance theory （ART） neural network with forgetting procedure, for moving object detection and background modeling in natural scenes. With the ability, inheriting from the ART neural network, of extracting patterns from arbitrary sequences, the background model based on the proposed method can learn new scenes quickly and accurately. To guarantee that a long-life model can derived from the proposed mothed, a forgetting procedure is employed to find the neuron that needs to be discarded and reconstructed, and the finding procedure is based on a neural network which can find the extreme value quickly. The results of a suite of quantitative and qualitative experiments conducted verify that for processes of modeling background and detecting moving objects our method is more effective than five other proven methods with which it is compared.

All-dielectric metamaterial frequency selective surface

Frequency selective surface(FSS)has been extensively studied due to its potential applications in radomes,antenna reflectors,high-impedance surfaces and absorbers.Recently,a new principle of designing FSS has been proposed and mainly studied in two levels.In the level of materials,dielectric materials instead of metallic patterns are capable of achieving more functional performance in FSS design.Moreover,FSSs made of dielectric materials can be used in different extreme environments,depending on their electrical,thermal or mechanical properties.In the level of design principle,the theory of metamaterial can be used to design FSS in a convenient and concise way.In this review paper,we provide a brief summary about the recent progress in all-dielectric metamaterial frequency selective surface(ADM-FSS).The basic principle of designing ADM-FSS is summarized.As significant tools,Mie theory and dielectric resonator(DR)theory are given which illustrate clearly how they are used in the FSS design.Then,several design cases including dielectric particle-based ADM-FSS and dielectric network-based ADM-FSS are introduced and reviewed.After a discussion of these two types of ADM-FSSs,we reviewed the existing fabrication techniques that are used in building the experiment samples.Finally,issues and challenges regarding the rapid fabrication techniques and further development aspects are discussed.