SAR image reconstruction and autofocus by compressed sensing

Cataloged from PDF version of article.A new SAR signal processing technique based on compressed sensing is proposed for autofocused image reconstruction on subsampled raw SAR data. It is shown that, if the residual phase error after INS/GPS corrected platform motion is captured in the signal model, then the optimal autofocused image formation can be formulated as a sparse reconstruction problem. To further improve image quality, the total variation of the reconstruction is used as a penalty term. In order to demonstrate the performance of the proposed technique in wide-band SAR systems, the measurements used in the reconstruction are formed by a new under-sampling pattern that can be easily implemented in practice by using slower rate A/D converters. Under a variety of metrics for the reconstruction quality, it is demonstrated that, even at high under-sampling ratios, the proposed technique provides reconstruction quality comparable to that obtained by the classical techniques which require full-band data without any under-sampling. (C) 2012 Elsevier Inc. All rights reserved

SAR image reconstruction by expectation maximization based matching pursuit

Cataloged from PDF version of article.Synthetic Aperture Radar (SAR) provides high resolution images of terrain and target reflectivity. SAR systems are indispensable in many remote sensing applications. Phase errors due to uncompensated platform motion degrade resolution in reconstructed images. A multitude of autofocusing techniques has been proposed to estimate and correct phase errors in SAR images. Some autofocus techniques work as a post-processor on reconstructed images and some are integrated into the image reconstruction algorithms. Compressed Sensing (CS), as a relatively new theory, can be applied to sparse SAR image reconstruction especially in detection of strong targets. Autofocus can also be integrated into CS based SAR image reconstruction techniques. However, due to their high computational complexity, CS based techniques are not commonly used in practice. To improve efficiency of image reconstruction we propose a novel CS based SAR imaging technique which utilizes recently proposed Expectation Maximization based Matching Pursuit (EMMP) algorithm. EMMP algorithm is greedy and computationally less complex enabling fast SAR image reconstructions. The proposed EMMP based SAR image reconstruction technique also performs autofocus and image reconstruction simultaneously. Based on a variety of metrics, performance of the proposed EMMP based SAR image reconstruction technique is investigated. The obtained results show that the proposed technique provides high resolution images of sparse target scenes while performing highly accurate motion compensation. (C) 2014 Elsevier Inc. All rights reserved

The Genetic Basis of the Polycystic Ovary Syndrome: A Literature Review Including Discussion of PPAR-γ

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder of the women of reproductive age. Familial clustering of PCOS has been consistently reported suggesting that genetic factors play a role in the development of the syndrome although PCOS cases do not exhibit a clear pattern of Mendelian inheritance. It is now well established that PCOS represents a complex trait similar to type-2 diabetes and obesity, and that both inherited and environmental factors contribute to the PCOS pathogenesis. A large number of functional candidate genes have been tested for association or linkage with PCOS phenotypes with more negative than positive findings. Lack of universally accepted diagnostic criteria, difficulties in the assignment of male phenotype, obscurity in the mode of inheritance, and particularly small sample size of the study populations appear to be major limitations for the genetic studies of PCOS. In the near future, utilizing the genome-wide scan approach and the HapMap project will provide a stronger potential for the genetic analysis of the syndrome

Multi-Scale Deformable Alignment and Content-Adaptive Inference for Flexible-Rate Bi-Directional Video Compression

The lack of ability to adapt the motion compensation model to video content is an important limitation of current end-to-end learned video compression models. This paper advances the state-of-the-art by proposing an adaptive motion-compensation model for end-to-end rate-distortion optimized hierarchical bi-directional video compression. In particular, we propose two novelties: i) a multi-scale deformable alignment scheme at the feature level combined with multi-scale conditional coding, ii) motion-content adaptive inference. In addition, we employ a gain unit, which enables a single model to operate at multiple rate-distortion operating points. We also exploit the gain unit to control bit allocation among intra-coded vs. bi-directionally coded frames by fine tuning corresponding models for truly flexible-rate learned video coding. Experimental results demonstrate state-of-the-art rate-distortion performance exceeding those of all prior art in learned video coding.Comment: Accepted for publication in IEEE International Conference on Image Processing (ICIP) 202

A particle swarm optimization based SAR motion compensation algorithm for target image reconstruction

A new SAR motion compensation algorithm is proposed for robust reconstruction of target images even under large deviations of the platform from intended flight path. Phase error due to flight path deviations is estimated as a solution to an optimization problem in terms of the positions of the reflectivity centers of the target. Particle swarm optimization is used to obtain phase error estimates efficiently. The quality of the reconstructions is demonstrated by using simulation studies. © 2010 IEEE

Off-grid sparse SAR image reconstruction by EMMP algorithm

A new and robust sparse SAR image reconstruction technique is proposed for off-grid targets in the CS framework. In the proposed approach, basis vectors corresponding to on-grid point reflectors are perturbed on a finer grid to find the appropriate bases for the reconstruction of off-grid targets. To provide efficiency of the reconstruction, the EMMP algorithm is applied to find reflectivity center locations. As demonstrated by simulations, the proposed approach significantly improves the performance of sparse SAR image reconstruction. © 2013 IEEE

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for \u3ci\u3eGalanthus\u3c/i\u3e L. Using the relative complexity measure

Background: Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. Result: In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. Conclusions: Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters

Nonadditive entropy and nonextensive statistical mechanics - Some central concepts and recent applications

We briefly review central concepts concerning nonextensive statistical mechanics, based on the nonadditive entropy $S_q=k\frac{1-\sum_{i}p_i^q}{q-1} (q \in {\cal R}; S_1=-k\sum_{i}p_i \ln p_i)$. Among others, we focus on possible realizations of the $q$-generalized Central Limit Theorem, including at the edge of chaos of the logistic map, and for quasi-stationary states of many-body long-range-interacting Hamiltonian systems.Comment: 15 pages, 9 figs., to appear in Journal of Physics: Conf.Series (IOP, 2010

Cocaine- and amphetamine-regulated transcript promoter regulated by nicotine in nerve growth factor-treated PC12 cells

Nicotine and cocaine- and amphetamine-regulated transcripts (CART) have several overlapping functions, such as the regulation of reward, feeding behavior, stress response, and anxiety. Previous studies showed that nicotine regulates CART expression in various brain regions. However, the molecular mechanisms underlying this regulation are not known. This study investigated the regulatory effect of nicotine on promoter activity of the CART gene in PC12 cells, which were differentiated into a neuronal phenotype by nerve growth factor (NGF) treatment. Two vectors containing reporter genes (Gaussia luciferase or mCherry) and the 1,140-bp upstream of the transcriptional start site of the mouse CART gene are used to analyze the CART promoter activity. Transient transfection of PC12 cells with either vector displayed strong promoter activity in both undifferentiated and differentiated PC12 cells. CART promoter activity in the PC12 cell line is increased by forskolin or NGF treatment. In differentiated PC12 cells, exposure to 50 nM nicotine for 6 h increased CART promoter activity. However, treatment with higher nicotine doses for 6 h and treatment with all nicotine doses for 24 h showed no effect. A nicotine concentration of 50 nM is comparable to brain nicotine levels experienced by chronic smokers over long periods of time. Taken together, these data indicate that nicotine may exert some of its actions through the regulation of CART transcription in the brain

Grain engineering for improved charge carrier transport in two-dimensional lead-free perovskite field-effect transistors

Controlling crystal growth and reducing the number of grain boundaries are crucial to maximize the charge carrier transport in organic-inorganic perovskite field-effect transistors (FETs). Herein, the crystallization and growth kinetics of a Sn(ii)-based 2D perovskite, using 2-thiopheneethylammonium (TEA) as the organic cation spacer, were effectively regulated by the hot-casting method. With increasing crystalline grain size, the local charge carrier mobility is found to increase moderately from 13 cm2 V−1 s−1 to 16 cm2 V−1 s−1, as inferred from terahertz (THz) spectroscopy. In contrast, the FET operation parameters, including mobility, threshold voltage, hysteresis, and subthreshold swing, improve substantially with larger grain size. The optimized 2D (TEA)2SnI4 transistor exhibits hole mobility of up to 0.34 cm2 V−1 s−1 at 295 K and a higher value of 1.8 cm2 V−1 s−1 at 100 K. Our work provides an important insight into the grain engineering of 2D perovskites for high-performance FETs