Super-Resolution Reconstruction in Frequency-Domain Optical-Coherence Tomography Using the Finite-Rate-of-Innovation Principle

The standard approach to signal reconstruction in frequency-domain optical-coherence tomography (FDOCT) is to apply the inverse Fourier transform to the measurements. This technique offers limited resolution (due to Heisenberg's uncertainty principle). We propose a new super-resolution reconstruction method based on a parametric representation. We consider multilayer specimens, wherein each layer has a constant refractive index and show that the backscattered signal from such a specimen fits accurately in to the framework of finite-rate-of-innovation (FRI) signal model and is represented by a finite number of free parameters. We deploy the high-resolution Prony method and show that high-quality, super-resolved reconstruction is possible with fewer measurements (about one-fourth of the number required for the standard Fourier technique). To further improve robustness to noise in practical scenarios, we take advantage of an iterated singular-value decomposition algorithm (Cadzow denoiser). We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramer-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach.

Formation Flying with Nonlinear Partial Integrated Guidance and Control

Using the dynamic inversion philosophy, a nonlinear partial integrated guidance and control approach is presented in this paper for formation flying. It is based on the evolving philosophy of integrated guidance and control. However, it also retains the advantages of the conventional guidance then control philosophy by retaining the timescale separation between translational and rotational dynamics explicitly. Simulation studies demonstrate that the proposed technique is effective in bringing the vehicles into formation quickly and maintaining the formation.

Analogous stress and electric field driven structural transformation and decrease in polarization coherence on poling around the morphotropic phase boundary in BiScO3-PbTiO3

The nature of the stress and electric field driven structural and microstructural transformations in the morphotropic phase boundary (MPB) compositions of the high Curie point piezoelectric system BiScO3-PbTiO3 has been examined by ex situ based techniques. Using a powder poling technique, which is based on the concept of exploiting the irreversible structural change that occurs after the application of a strong electric field and stress independently, it was possible to ascertain that both moderate stress and electric field induce identical structural transformation-a fraction of the monoclinic phase transforms irreversibly to the tetragonal phase. Moreover, analysis of the dielectric response before and after poling revealed a counterintuitive phenomenon of poling induced decrease in the spatial coherence of polarization for compositions around the MPB and not so for compositions far away from the MPB range. Exploiting the greater sensitivity of this technique, we demonstrate that the criticality associated with the interferroelectric transition spans a wider composition range than what is conventionally reported in the literature based on bulk x-ray/neutron powder diffraction techniques.

Statistical significance of episodes with general partial orders

Frequent episode discovery is one of the methods used for temporal pattern discovery in sequential data. An episode is a partially ordered set of nodes with each node associated with an event type. For more than a decade, algorithms existed for episode discovery only when the associated partial order is total (serial episode) or trivial (parallel episode). Recently, the literature has seen algorithms for discovering episodes with general partial orders. In frequent pattern mining, the threshold beyond which a pattern is inferred to be interesting is typically user-defined and arbitrary. One way of addressing this issue in the pattern mining literature has been based on the framework of statistical hypothesis testing. This paper presents a method of assessing statistical significance of episode patterns with general partial orders. A method is proposed to calculate thresholds, on the non-overlapped frequency, beyond which an episode pattern would be inferred to be statistically significant. The method is first explained for the case of injective episodes with general partial orders. An injective episode is one where event-types are not allowed to repeat. Later it is pointed out how the method can be extended to the class of all episodes. The significance threshold calculations for general partial order episodes proposed here also generalize the existing significance results for serial episodes. Through simulations studies, the usefulness of these statistical thresholds in pruning uninteresting patterns is illustrated. (C) 2014 Elsevier Inc. All rights reserved.

HCN channels enhance spike phase coherence and regulate the phase of spikes and LFPs in the theta-frequency range

What are the implications for the existence of subthreshold ion channels, their localization profiles, and plasticity on local field potentials (LFPs)? Here, we assessed the role of hyperpolarization-activated cyclic-nucleotide-gated (HCN) channels in altering hippocampal theta-frequency LFPs and the associated spike phase. We presented spatiotemporally randomized, balanced theta-modulated excitatory and inhibitory inputs to somatically aligned, morphologically realistic pyramidal neuron models spread across a cylindrical neuropil. We computed LFPs from seven electrode sites and found that the insertion of an experimentally constrained HCN-conductance gradient into these neurons introduced a location- dependent lead in the LFP phase without significantly altering its amplitude. Further, neurons fired action potentials at a specific theta phase of the LFP, and the insertion of HCN channels introduced large lags in this spike phase and a striking enhancement in neuronal spike-phase coherence. Importantly, graded changes in either HCN conductance or its half-maximal activation voltage resulted in graded changes in LFP and spike phases. Our conclusions on the impact of HCN channels on LFPs and spike phase were invariant to changes in neuropil size, to morphological heterogeneity, to excitatory or inhibitory synaptic scaling, and to shifts in the onset phase of inhibitory inputs. Finally, we selectively abolished the inductive lead in the impedance phase introduced by HCN channels without altering neuronal excitability and found that this inductive phase lead contributed significantly to changes in LFP and spike phase. Our results uncover specific roles for HCN channels and their plasticity in phase-coding schemas and in the formation and dynamic reconfiguration of neuronal cell assemblies.

Wireless scheduling with partial channel state information: large deviations and optimality

We consider a server serving a time-slotted queued system of multiple packet-based flows, where not more than one flow can be serviced in a single time slot. The flows have exogenous packet arrivals and time-varying service rates. At each time, the server can observe instantaneous service rates for only a subset of flows ( selected from a fixed collection of observable subsets) before scheduling a flow in the subset for service. We are interested in queue length aware scheduling to keep the queues short. The limited availability of instantaneous service rate information requires the scheduler to make a careful choice of which subset of service rates to sample. We develop scheduling algorithms that use only partial service rate information from subsets of channels, and that minimize the likelihood of queue overflow in the system. Specifically, we present a new joint subset-sampling and scheduling algorithm called Max-Exp that uses only the current queue lengths to pick a subset of flows, and subsequently schedules a flow using the Exponential rule. When the collection of observable subsets is disjoint, we show that Max-Exp achieves the best exponential decay rate, among all scheduling algorithms that base their decision on the current ( or any finite past history of) system state, of the tail of the longest queue. To accomplish this, we employ novel analytical techniques for studying the performance of scheduling algorithms using partial state, which may be of independent interest. These include new sample-path large deviations results for processes obtained by non-random, predictable sampling of sequences of independent and identically distributed random variables. A consequence of these results is that scheduling with partial state information yields a rate function significantly different from scheduling with full channel information. In the special case when the observable subsets are singleton flows, i.e., when there is effectively no a priori channel state information, Max-Exp reduces to simply serving the flow with the longest queue; thus, our results show that to always serve the longest queue in the absence of any channel state information is large deviations optimal.

Optimum Parameter Selection in Sparse Reconstruction of Frequency-Domain Optical-Coherence Tomography Signals

For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

Generalized Partial Response Equalization and Data-Dependent Noise Predictive Signal Detection Over Media Models for TDMR

Two-dimensional magnetic recording (2-D TDMR) is an emerging technology that aims to achieve areal densities as high as 10 Tb/in(2) using sophisticated 2-D signal-processing algorithms. High areal densities are achieved by reducing the size of a bit to the order of the size of magnetic grains, resulting in severe 2-D intersymbol interference (ISI). Jitter noise due to irregular grain positions on the magnetic medium is more pronounced at these areal densities. Therefore, a viable read-channel architecture for TDMR requires 2-D signal-detection algorithms that can mitigate 2-D ISI and combat noise comprising jitter and electronic components. Partial response maximum likelihood (PRML) detection scheme allows controlled ISI as seen by the detector. With the controlled and reduced span of 2-D ISI, the PRML scheme overcomes practical difficulties such as Nyquist rate signaling required for full response 2-D equalization. As in the case of 1-D magnetic recording, jitter noise can be handled using a data-dependent noise-prediction (DDNP) filter bank within a 2-D signal-detection engine. The contributions of this paper are threefold: 1) we empirically study the jitter noise characteristics in TDMR as a function of grain density using a Voronoi-based granular media model; 2) we develop a 2-D DDNP algorithm to handle the media noise seen in TDMR; and 3) we also develop techniques to design 2-D separable and nonseparable targets for generalized partial response equalization for TDMR. This can be used along with a 2-D signal-detection algorithm. The DDNP algorithm is observed to give a 2.5 dB gain in SNR over uncoded data compared with the noise predictive maximum likelihood detection for the same choice of channel model parameters to achieve a channel bit density of 1.3 Tb/in(2) with media grain center-to-center distance of 10 nm. The DDNP algorithm is observed to give similar to 10% gain in areal density near 5 grains/bit. The proposed signal-processing framework can broadly scale to various TDMR realizations and areal density points.

Mono layer to Interdigitated Partial Bilayer Smectic C Transition in Thiophene-Based Spacer Mesogens: X-ray Diffraction and C-13 Nuclear Magnetic Resonance Studies

Mesophase organization of molecules built with thiophene at the center and linked via flexible spacers to rigid side arm core units and terminal alkoxy chains has been investigated. Thirty homologues realized by varying the span of the spacers as well as the length of the terminal chains have been studied. In addition to the enantiotropic nematic phase observed for all the mesogens, the increase of the spacer as well as the terminal chain lengths resulted in the smectic C phase. The molecular organization in the smectic phase as investigated by temperature dependent X-ray diffraction measurements revealed an interesting behavior that depended on the length of the spacer vis-a-vis the length of the terminal chain. Thus, a tilted interdigitated partial bilayer organization was observed for molecules with a shorter spacer length, while a tilted monolayer arrangement was observed for those with a longer spacer length. High-resolution solid state C-13 NMR studies carried out for representative mesogens indicated a U-shape for all the molecules, indicating that intermolecular interactions and molecular dynamics rather than molecular shape are responsible for the observed behavior. Models for the mesophase organization have been considered and the results understood in terms of segregation of incompatible parts of the mesogens combined with steric frustration leading to the observed lamellar order.

Partial rotation of the isopropyl group in the solid state: single-crystal-to-single-crystal phase transformation in a carvacrol derivative

A hitherto unseen rotation of the isopropyl group in the solid state, predicted to be forbidden based on theoretical investigations, is reported. This C-C rotation observed during the temperature dependent single-crystal-to-single-crystal transformation is attributed to the concomitant changes in molecular structure and intermolecular packing.

Partial-Dislocation-Mediated Processes in Nanocrystalline Ni with Nonequilibrium Grain Boundaries

The partial-dislocation-mediated processes have so far eluded high-resolution transmission electron microscopy studies in nanocrystalline nc Ni with nonequilibrium grain boundaries. It is revealed that the nc Ni deformed largely by twinning instead of extended partials. The underlying mechanisms including dissociated dislocations, high residual stresses, and stress concentrations near stacking faults are demonstrated and discussed.

Surface Tension and Its Temperature Coefficient of Molten Tin Determined with the Sessile Drop Method at Different Oxygen Partial Pressures

The surface tension of molten tin has been determined by the sessile drop method at The surface tension of molten tin has been determined by the sessile drop method at temperatures ranging from 523 to 1033 K and in the oxygen partial pressure (P-O2) range from 2.85 x 10(-19) to 8.56 x 10(-6) MPa, and its dependence on temperature and oxygen partial pressure has been analyzed. At P-O2 = 2.85 x 10(-19) and 1.06 x 10(-15) MPa, the surface tension decreases linearly with the increase of temperature and its temperature coefficients are -0.151 and -0.094 mNm(-1) K-1, respectively. However, at high P-O2 (3.17 x 10(-10), 8.56 x 10(-6) MPa), the surface tension increases with the temperature near the melting point (505 K) and decreases above 723 K. The surface tension decrease with increasing P-O2 is much larger near the melting point than at temperatures above 823 K. The contact angle between the molten tin and the alumina substrate is 158-173degrees, and the wettability is poor.

Predictions for Partial-Dislocation-Mediated Processes in Nanocrystalline Ni by Generalized Planar Fault Energy Curves: An Experimental Evaluation

Generalized planar fault energy (GPFE) curves have been used to predict partial-dislocation-mediated processes in nanocrystalline materials, but their validity has not been evaluated experimentally. We report experimental observations of a large quantity of both stacking faults and twins in nc Ni deformed at relatively low stresses in a tensile test. The experimental findings indicate that the GPFE curves can reasonably explain the formation of stacking faults, but they alone were not able to adequately predict the propensity of deformation twinning.

Partial soi power LDMOS with a variable low-kappa; Dielectric buried layer and a buried P layer

A power LDMOS on partial silicon on insulator (PSOI) with a variable low-κ dielectric (VLKD) buried layer and a buried p (BP) layer is proposed (VLKD BPSOI). At a low κ value, the electric field strength in the buried dielectric (EI) is enhanced, and a Si window makes the substrate share the vertical voltage drop, leading to a high vertical breakdown voltage (BV). Moreover, three interface field peaks are introduced by the BP, the Si window, and the VLKD, which modulate the fields in the SOI layer, the VLKD layer, and the substrate; consequently, a high BV is obtained. Furthermore, the BP reduces the specific on-resistance (Ron), and the Si window alleviates the self-heating effect (SHE). The BV for VLKD BPSOI is enhanced by 34.5%, and Ron is decreased by 26.6%, compared with those for the conventional PSOI, and VLKD BPSOI also maintains a low SHE. © 2006 IEEE.