Consequences of incorrect sampling procedures in resonance-based radar target identification

Radar target identification based on complex natural resonances is sometimes achieved by convolving a linear time-domain filter with a received target signature. The filter is constructed from measured or pre-calculated target resonances. The performance of the target identification procedure is degraded if the difference between the sampling rates of the target signature and the filter is ignored. The problem is investigated for the natural extinction pulse technique (E-pulse) for the case of identifying stick models of aircraft.

Cortical activity during rotational and linear transformations

Neuroimaging studies of cortical activation during image transformation tasks have shown that mental rotation may rely on similar brain regions as those underlying visual perceptual mechanisms. The V5 complex, which is specialised for visual motion, is one region that has been implicated. We used functional magnetic resonance imaging (fMRI) to investigate rotational and linear transformation of stimuli. Areas of significant brain activation were identified for each of the primary mental transformation tasks in contrast to its own perceptual reference task which was cognitively matched in all respects except for the variable of interest. Analysis of group data for perception of rotational and linear motion showed activation in areas corresponding to V5 as defined in earlier studies. Both rotational and linear mental transformations activated Brodman Area (BA) 19 but did not activate V5. An area within the inferior temporal gyrus, representing an inferior satellite area of V5, was activated by both the rotational perception and rotational transformation tasks, but showed no activation in response to linear motion perception or transformation. The findings demonstrate the extent to which neural substrates for image transformation and perception overlap and are distinct as well as revealing functional specialisation within perception and transformation processing systems.

Characteristics of motor resonance predict the pattern of flash-lag effects for biological motion

Background - When a moving stimulus and a briefly flashed static stimulus are physically aligned in space the static stimulus is perceived as lagging behind the moving stimulus. This vastly replicated phenomenon is known as the Flash-Lag Effect (FLE). For the first time we employed biological motion as the moving stimulus, which is important for two reasons. Firstly, biological motion is processed by visual as well as somatosensory brain areas, which makes it a prime candidate for elucidating the interplay between the two systems with respect to the FLE. Secondly, discussions about the mechanisms of the FLE tend to recur to evolutionary arguments, while most studies employ highly artificial stimuli with constant velocities. Methodology/Principal Finding - Since biological motion is ecologically valid it follows complex patterns with changing velocity. We therefore compared biological to symbolic motion with the same acceleration profile. Our results with 16 observers revealed a qualitatively different pattern for biological compared to symbolic motion and this pattern was predicted by the characteristics of motor resonance: The amount of anticipatory processing of perceived actions based on the induced perspective and agency modulated the FLE. Conclusions/Significance - Our study provides first evidence for an FLE with non-linear motion in general and with biological motion in particular. Our results suggest that predictive coding within the sensorimotor system alone cannot explain the FLE. Our findings are compatible with visual prediction (Nijhawan, 2008) which assumes that extrapolated motion representations within the visual system generate the FLE. These representations are modulated by sudden visual input (e.g. offset signals) or by input from other systems (e.g. sensorimotor) that can boost or attenuate overshooting representations in accordance with biased neural competition (Desimone & Duncan, 1995).

Transfer characteristics and propagation effects of a multi-resonance ring resonator-based optical device

We describe the linear and nonlinear optical transfer characteristics of a multi-resonance device consisting of two optical ring resonators coupled one to the other and to an optical waveguide. The propagation effects displayed by the device are compared with those of a sequence of fundamental ring resonators coupled to a waveguide.

Leg muscles motion during whole body linear frequency sweep vibration

Whole body vibration (WBV) aims to mechanically activate muscles by eliciting stretch reflexes. Mechanical vibrations are usually transmitted to the patient body standing on a oscillating plate. WBV is now more and more utilized not only for fitness but also in physical therapy, rehabilitation and in sport medicine. Effects depend on intensity, direction and frequency of vibration; however, the training frequency is one of the most important factors involved. A preliminary vibratory session can be dedicated to find the best vibration frequency for each subject by varying, stepwise, the stimulation frequency and analyzing the resulting EMG activity. This study concentrates on the analysis of muscle motion in response to a vibration frequency sweep, while subjects held two different postures. The frequency of a vibrating platform was increased linearly from 10 to 60 Hz in 26 s, while platform and single muscles (Rectus Femoris, Biceps Femoris - long head and Gastrocnemius Lateralis) motions were monitored using tiny, lightweight three-axial MEMS accelerometers. Displacements were estimated integrating twice the acceleration data after gravity contribution removal. Mechanical frequency response (amplitude and phase) of the mechanical chains ending at the single muscles was characterized. Results revealed a mechanical resonant-like behavior at some muscles, very similar to a second-order system in the frequency interval explored; resonance frequencies and dumping factors depended on subject and its positioning onto the vibrating platform. Stimulation at the resonant frequency maximizes muscle lengthening, and in turn muscle spindle solicitation, which produce muscle activation. © 2009 Springer-Verlag.

Resonance properties of domain boundaries in quasi-two dimensional antiferromagnets

The so-called "internal modes" localized near the domain boundaries in quasi-two dimensional antiferromagnets are investigated. The possible localized states are classified and their frequency dependences on the system discreteness parameter λ=J/β, which describes the ratio of the magnitudes of the exchange interplane interaction and the magnetic anisotropy, are found. A sudden change in the spectrum of the local internal modes is observed at a critical value of this parameter, λ=λb=3/4, where the domain wall shifts from a collinear to a canted shape. When λ<λb there are one symmetric and two antisymmetric local modes, and when λ>λb the modes are two symmetric, one antisymmetric, and one shear. For discreteness parameters close to the critical value, the frequencies of some of the local modes lie deep inside the gap for the linear AFM magnon spectrum and can be observed experimentally. © 2010 American Institute of Physics.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Tensor Completion for Multidimensional Inverse Problems with Applications to Magnetic Resonance Relaxometry

This thesis deals with tensor completion for the solution of multidimensional inverse problems. We study the problem of reconstructing an approximately low rank tensor from a small number of noisy linear measurements. New recovery guarantees, numerical algorithms, non-uniform sampling strategies, and parameter selection algorithms are developed. We derive a fixed point continuation algorithm for tensor completion and prove its convergence. A restricted isometry property (RIP) based tensor recovery guarantee is proved. Probabilistic recovery guarantees are obtained for sub-Gaussian measurement operators and for measurements obtained by non-uniform sampling from a Parseval tight frame. We show how tensor completion can be used to solve multidimensional inverse problems arising in NMR relaxometry. Algorithms are developed for regularization parameter selection, including accelerated k-fold cross-validation and generalized cross-validation. These methods are validated on experimental and simulated data. We also derive condition number estimates for nonnegative least squares problems. Tensor recovery promises to significantly accelerate N-dimensional NMR relaxometry and related experiments, enabling previously impractical experiments. Our methods could also be applied to other inverse problems arising in machine learning, image processing, signal processing, computer vision, and other fields.

A surface plasmon resonance system for the underwater detection of domoic acid

Over the past decade Surface Plasmon Resonance (SPR) techniques have been applied to the measurement of numerous analytes. In this article, an SPR biosensor system deployed from an oceanographic vessel was used to measure dissolved domoic acid (DA), a common and harmful phycotoxin produced by certain microalgae species belonging to the genus Pseudo-nitzschia. During the biosensor deployment, concentrations of Pseudo-nitzschia cells were very low over the study area and measured DA concentrations were below detection. However, the in situ operational detection limit of the system was established using calibrated seawater solutions spiked with DA. The system could detect the toxin at concentrations as low as 0.1 ng mL−1 and presented a linear dynamic range from 0.1 ng mL−1 to 2.0 ng mL−1. This sensor showed promise for in situ detection of DA.