Fractal Array Antennas and Applications

Modern celestial and other advanced wireless communication systems require feasible array antennas with reconfigurable multibeams, broadband, high end of coverage, high gain, less side-lobe level with wider side-lobe level angles, better signal-to-noise ratio and small in size than conventionally achievable. This has initiated array antenna research in different tracks, one of which is by using fractal array antennas. The investigation on fractal-shaped antennas is basically focused on two fundamental areas such as the analysis and design of fractal antenna elements and the application of fractal geometric technology to the design of array antennas. These recursively generated antennas provide new insights into the antenna properties due to their self-similar behaviour. Owing to the feasible geometric construction and advanced properties, fractal antennas find applications in advanced wireless communications, MIMO radars, satellite communications and space observations. This work concentrated here is primarily aimed on the design of fractal array antennas using concentric elliptical ring sub-array fractal geometric design methodology and the reduction of total number of antenna elements at higher expansion factors of both conventional and proposed fractal array antennas

A Higher-Order Generalized Singular Value Decomposition for Comparison of Global mRNA Expression from Multiple Organisms

The number of high-dimensional datasets recording multiple aspects of a single phenomenon is increasing in many areas of science, accompanied by a need for mathematical frameworks that can compare multiple large-scale matrices with different row dimensions. The only such framework to date, the generalized singular value decomposition (GSVD), is limited to two matrices. We mathematically define a higher-order GSVD (HO GSVD) for N≥2 matrices , each with full column rank. Each matrix is exactly factored as Di = UiΣiVT, where V, identical in all factorizations, is obtained from the eigensystem SV = VΛ of the arithmetic mean S of all pairwise quotients of the matrices , i≠j. We prove that this decomposition extends to higher orders almost all of the mathematical properties of the GSVD. The matrix S is nondefective with V and Λ real. Its eigenvalues satisfy λk≥1. Equality holds if and only if the corresponding eigenvector vk is a right basis vector of equal significance in all matrices Di and Dj, that is σi,k/σj,k = 1 for all i and j, and the corresponding left basis vector ui,k is orthogonal to all other vectors in Ui for all i. The eigenvalues λk = 1, therefore, define the “common HO GSVD subspace.” We illustrate the HO GSVD with a comparison of genome-scale cell-cycle mRNA expression from S. pombe, S. cerevisiae and human. Unlike existing algorithms, a mapping among the genes of these disparate organisms is not required. We find that the approximately common HO GSVD subspace represents the cell-cycle mRNA expression oscillations, which are similar among the datasets. Simultaneous reconstruction in the common subspace, therefore, removes the experimental artifacts, which are dissimilar, from the datasets. In the simultaneous sequence-independent classification of the genes of the three organisms in this common subspace, genes of highly conserved sequences but significantly different cell-cycle peak times are correctly classified

Performance evaluation of the time delay digital tanlock loop architectures

This article presents the architectures, theoretical analyses and testing results of modified time delay digital tanlock loop (TDTLs) system. The modifications to the original TDTL architecture were introduced to overcome some of the limitations of the original TDTL and to enhance the overall performance of the particular systems. The limitations addressed in this article include the non-linearity of the phase detector, the restricted width of the locking range and the overall system acquisition speed. Each of the modified architectures was tested by subjecting the system to sudden positive and negative frequency steps and comparing its response with that of the original TDTL. In addition, the performance of all the architectures was evaluated under noise-free as well as noisy environments. The extensive simulation results using MATLAB/SIMULINK demonstrate that the new architectures overcome the limitations they addressed and the overall results confirmed significant improvements in performance compared to the conventional TDTL system

DISCO-SCA and Properly Applied GSVD as Swinging Methods to Find Common and Distinctive Processes

BACKGROUND: In systems biology it is common to obtain for the same set of biological entities information from multiple sources. Examples include expression data for the same set of orthologous genes screened in different organisms and data on the same set of culture samples obtained with different high-throughput techniques. A major challenge is to find the important biological processes underlying the data and to disentangle therein processes common to all data sources and processes distinctive for a specific source. Recently, two promising simultaneous data integration methods have been proposed to attain this goal, namely generalized singular value decomposition (GSVD) and simultaneous component analysis with rotation to common and distinctive components (DISCO-SCA). RESULTS: Both theoretical analyses and applications to biologically relevant data show that: (1) straightforward applications of GSVD yield unsatisfactory results, (2) DISCO-SCA performs well, (3) provided proper pre-processing and algorithmic adaptations, GSVD reaches a performance level similar to that of DISCO-SCA, and (4) DISCO-SCA is directly generalizable to more than two data sources. The biological relevance of DISCO-SCA is illustrated with two applications. First, in a setting of comparative genomics, it is shown that DISCO-SCA recovers a common theme of cell cycle progression and a yeast-specific response to pheromones. The biological annotation was obtained by applying Gene Set Enrichment Analysis in an appropriate way. Second, in an application of DISCO-SCA to metabolomics data for Escherichia coli obtained with two different chemical analysis platforms, it is illustrated that the metabolites involved in some of the biological processes underlying the data are detected by one of the two platforms only; therefore, platforms for microbial metabolomics should be tailored to the biological question. CONCLUSIONS: Both DISCO-SCA and properly applied GSVD are promising integrative methods for finding common and distinctive processes in multisource data. Open source code for both methods is provided

Mathematically universal and biologically consistent astrocytoma genotype encodes for transformation and predicts survival phenotype

DNA alterations have been observed in astrocytoma for decades. A copy-number genotype predictive of a survival phenotype was only discovered by using the generalized singular value decomposition (GSVD) formulated as a comparative spectral decomposition. Here, we use the GSVD to compare whole-genome sequencing (WGS) profiles of patient-matched astrocytoma and normal DNA. First, the GSVD uncovers a genome-wide pattern of copy-number alterations, which is bounded by patterns recently uncovered by the GSVDs of microarray-profiled patient-matched glioblastoma (GBM) and, separately, lower-grade astrocytoma and normal genomes. Like the microarray patterns, the WGS pattern is correlated with an approximately one-year median survival time. By filling in gaps in the microarray patterns, the WGS pattern reveals that this biologically consistent genotype encodes for transformation via the Notch together with the Ras and Shh pathways. Second, like the GSVDs of the microarray profiles, the GSVD of the WGS profiles separates the tumor-exclusive pattern from normal copy-number variations and experimental inconsistencies. These include the WGS technology-specific effects of guanine-cytosine content variations across the genomes that are correlated with experimental batches. Third, by identifying the biologically consistent phenotype among the WGS-profiled tumors, the GBM pattern proves to be a technology-independent predictor of survival and response to chemotherapy and radiation, statistically better than the patient's age and tumor's grade, the best other indicators, and MGMT promoter methylation and IDH1 mutation. We conclude that by using the complex structure of the data, comparative spectral decompositions underlie a mathematically universal description of the genotype-phenotype relations in cancer that other methods miss

Unusual Isomeric Corniculatolides from Mangrove, <i>Aegiceras corniculatum</i>

Four new isomeric macrolides of combretastatin D-2 congeners named isocorniculatolide A (<b>1</b>), 11-<i>O</i>-methylisocorniculatolide A (<b>2</b>), 11-<i>O</i>-methylcorniculatolide A (<b>3</b>), and 12-hydroxy-11-<i>O</i>-methylcorniculatolide A (<b>4</b>), and the known corniculatolide A (<b>5</b>), arjunolic acid, and maslinic acid were isolated from the CHCl₃ extract of the bark of <i>Aegiceras corniculatum</i>. The structures of the new compounds (<b>1</b>–<b>4</b>) were elucidated by a combination of spectroscopic analysis (<b>1</b>–<b>5</b>), chemical modifications, and single-crystal X-ray analysis (<b>1</b>)