On the Suitability of Suffix Arrays for Lempel-Ziv Data Compression

Lossless compression algorithms of the Lempel-Ziv (LZ) family are widely used nowadays. Regarding time and memory requirements, LZ encoding is much more demanding than decoding. In order to speed up the encoding process, efficient data structures, like suffix trees, have been used. In this paper, we explore the use of suffix arrays to hold the dictionary of the LZ encoder, and propose an algorithm to search over it. We show that the resulting encoder attains roughly the same compression ratios as those based on suffix trees. However, the amount of memory required by the suffix array is fixed, and much lower than the variable amount of memory used by encoders based on suffix trees (which depends on the text to encode). We conclude that suffix arrays, when compared to suffix trees in terms of the trade-off among time, memory, and compression ratio, may be preferable in scenarios (e.g., embedded systems) where memory is at a premium and high speed is not critical.

Facile synthesis of freestanding Si nanowire arrays by one-step template-free electro-deoxidation of SiO2 in molten salt

This communication presents a novel kind of silicon nanomaterial: freestanding Si nanowire arrays (Si NWAs), which are synthesized facilely by one-step template-free electro-deoxidation of SiO2 in molten CaCl2. The self-assembling growth process of this material is also investigated preliminarily.

Silicon nanowire arrays coupled with cobalt phosphide spheres as low-cost photocathodes for efficient solar hydrogen evolution

We demonstrate the first example of silicon nanowire array photocathodes coupled with hollow spheres of the emerging earth-abundant cobalt phosphide catalysts. Compared to bare silicon nanowire arrays, the hybrid electrodes exhibit significantly improved photoelectrochemical performance toward the solar-driven H2 evolution reaction.

High-aspect-ratio tridimensional electrode arrays for neural applications

Tese de Doutoramento em Engenharia Biomédica.

Flexible gastrointestinal motility pressure sensors based on aluminum thin-film strain-gauge arrays

This paper reports on an innovative approach to measuring intraluminal pressure in the upper gastrointestinal (GI) tract, especially monitoring GI motility and peristaltic movements. The proposed approach relies on thin-film aluminum strain gauges deposited on top of a Kapton membrane, which in turn lies on top of an SU-8 diaphragm-like structure. This structure enables the Kapton membrane to bend when pressure is applied, thereby affecting the strain gauges and effectively changing their electrical resistance. The sensor, with an area of 3.4 mm2, is fabricated using photolithography and standard microfabrication techniques (wet etching). It features a linear response (R2 = 0.9987) and an overall sensitivity of 2.6 mV mmHg−1. Additionally, its topology allows a high integration capability. The strain gauges’ responses to pressure were studied and the fabrication process optimized to achieve high sensitivity, linearity, and reproducibility. The sequential acquisition of the different signals is carried out by a microcontroller, with a 10-bit ADC and a sample rate of 250 Hz. The pressure signals are then presented in a user-friendly interface, developed using the Integrated Development Environment software, QtCreator IDE, for better visualization by physicians.

Experimental investigation of heat transfer characteristics from arrays of free impinging circular jets and hole channels

Free Tube Jet - Impingemenet - Heat Transfer - Arrary - Infrared Techuique - Hole Channels - Heat Transfer Uniformaty

Modeling of micro- and nanostructures made of films and crystals/fibers arrays

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

Profiling of T-cell receptor signaling complex assembly in human CD4 T-lymphocytes using RP protein arrays.

The RP protein (RPP) array approach immobilizes minute amounts of cell lysates or tissue protein extracts as distinct microspots on NC-coated slide. Subsequent detection with specific antibodies allows multiplexed quantification of proteins and their modifications at a scale that is beyond what traditional techniques can achieve. Cellular functions are the result of the coordinated action of signaling proteins assembled in macromolecular complexes. These signaling complexes are highly dynamic structures that change their composition with time and space to adapt to cell environment. Their comprehensive analysis requires until now relatively large amounts of cells (>5 x 10(7)) due to their low abundance and breakdown during isolation procedure. In this study, we combined small scale affinity capture of the T-cell receptor (TCR) and RPP arrays to follow TCR signaling complex assembly in human ex vivo isolated CD4 T-cells. Using this strategy, we report specific recruitment of signaling components to the TCR complex upon T-cell activation in as few as 0.5 million of cells. Second- to fourth-order TCR interacting proteins were accurately quantified, making this strategy specially well-suited to the analysis of membrane-associated signaling complexes in limited amounts of cells or tissues, e.g., ex vivo isolated cells or clinical specimens.

Affymetrix Whole-Transcript Human Gene 1.0 ST array is highly concordant with standard 3' expression arrays.

The recently released Affymetrix Human Gene 1.0 ST array has two major differences compared with standard 3' based arrays: (i) it interrogates the entire mRNA transcript, and (ii) it uses DNA targets. To assess the impact of these differences on array performance, we performed a series of comparative hybridizations between the Human Gene 1.0 ST and the Affymetrix HG-U133 Plus 2.0 and the Illumina HumanRef-8 BeadChip arrays. Additionally, both RNA and DNA targets were hybridized on HG-U133 Plus 2.0 arrays. The results show that the overall reproducibility of the Gene 1.0 ST array is best. When looking only at the high intensity probes, the reproducibility of the Gene 1.0 ST array and the Illumina BeadChip array is equally good. Concordance of array results was assessed using different inter-platform mappings. Agreements are best between the two labeling protocols using HG-U133 Plus 2.0 array. The Gene 1.0 ST array is most concordant with the HG-U133 array hybridized with cDNA targets. This may reflect the impact of the target type. Overall, the high degree of correspondence provides strong evidence for the reliability of the Gene 1.0 ST array.

Substantial deletion overlap among divergent Arabidopsis genomes revealed by intersection of short reads and tiling arrays.

ABSTRACT: Identification of small polymorphisms from next generation sequencing short read data is relatively easy, but detection of larger deletions is less straightforward. Here, we analyzed four divergent Arabidopsis accessions and found that intersection of absent short read coverage with weak tiling array hybridization signal reliably flags deletions. Interestingly, individual deletions were frequently observed in two or more of the accessions examined, suggesting that variation in gene content partly reflects a common history of deletion events.

Direct detection of a BRAF mutation in total RNA from melanoma cells using cantilever arrays.

Malignant melanoma, the deadliest form of skin cancer, is characterized by a predominant mutation in the BRAF gene. Drugs that target tumours carrying this mutation have recently entered the clinic. Accordingly, patients are routinely screened for mutations in this gene to determine whether they can benefit from this type of treatment. The current gold standard for mutation screening uses real-time polymerase chain reaction and sequencing methods. Here we show that an assay based on microcantilever arrays can detect the mutation nanomechanically without amplification in total RNA samples isolated from melanoma cells. The assay is based on a BRAF-specific oligonucleotide probe. We detected mutant BRAF at a concentration of 500 pM in a 50-fold excess of the wild-type sequence. The method was able to distinguish melanoma cells carrying the mutation from wild-type cells using as little as 20 ng µl(-1) of RNA material, without prior PCR amplification and use of labels.

Avoiding sensor blindness in Geiger mode avalanche photodiode arrays fabricated in a conventional CMOS process

The need to move forward in the knowledge of the subatomic world has stimulated the development of new particle colliders. However, the objectives of the next generation of colliders sets unprecedented challenges to the detector performance. The purpose of this contribution is to present a bidimensional array based on avalanche photodiodes operated in the Geiger mode to track high energy particles in future linear colliders. The bidimensional array can function in a gated mode to reduce the probability to detect noise counts interfering with real events. Low reverse overvoltages are used to lessen the dark count rate. Experimental results demonstrate that the prototype fabricated with a standard HV-CMOS process presents an increased efficiency and avoids sensor blindness by applying the proposed techniques.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.