177,141 research outputs found
Time-Domain Heart Rate Variability Analysis with the SPINE-HRV Toolkit
No full textWe present a tool-kit for the time domain Heart Rate Variability (HRV) analysis, namely SPINE-HRV (Signal Processing In Node Environment-HRV). The HRV is based on the analysis (time and frequency domain) of the R-peak to R-peak intervals (RR-interval). The tool-kit is composed of a wearable Heart Activity Monitoring System (HAMS) to collect the RR-interval (RRi), and a processing application developed using the SPINE framework. The HAMS used to acquire the RRi signal is self-developed; the hardware system consists of a chest belt communicating wireless with a receiver node. The RRi signal is processed using the SPINE framework through a time domain analysis of HRV. That analysis provides seven common parameters known in medicine literature to help cardiologists in the diagnosis related to several heart diseases. The results have been validated with a commonly used high accuracy HRV software tool
Molecular dissociation in hot, dense hydrogen
No full textWe present a path-integral Monte Carlo study of dissociation in dense hydrogen (1.75 less than or equal to r(s) less than or equal to 2.2 with r(s) the Wigner sphere radius). As the temperature is lowered from 10(5) to 5000 K, a molecular hydrogen gas forms spontaneously from a neutral system of protons and electrons. At high density, r(s) < 2.0, thermally activated dissociation is accompanied by decreasing pressure, signaling the presence of a first order transition and critical point. The decrease in electron kinetic energy during dissociation is responsible for the pressure decrease and transition. At lower density the phase transition disappears
Computing the free distance of turbo codes and serially concatenated codes with interleavers: algorithms and applications
No full textWe present a new algorithm for computing the free distance dfree of parallel and serially concatenated codes with interleavers, the parameter that dominates the code performance at very high signal-to-noise ratios (SNRs). The knowledge of dfree allows one to analytically estimate the error floor, which may prevent the use of concatenated codes in applications requiring very low error rates. The algorithm is based on the new notion of constrained subcodes, and permits the computation of large distances for large interleavers without a constraint on the input sequence weight (e.g., up to dfree=40 for a rate-1/3 turbo code with interleaver length N=3568). Applications to practical cases of relevant interest, i.e., (1) the new Consultative Committee for Space Data Systems (CCSDS) standard for deep-space telemetry and (2) the new UMTS/3GPP standard for third-generation personal communications, are presented for the first time. Other related aspects, like a study on the free distance distribution of turbo codes with small/medium interleaver length, and a comparison between parallel and serial concatenation behavior, are also discussed
Prediction of subcellular localization in eukaryotes at the basis of large scale genome annotation
No full textIn this work we present an integrated platform for large-scale eukaryotic genome annotation based on the prediction of subcellular localization, GPI-anchor prediction and membrane protein discrimination into inner and outer classes.
Large scale proteomic projects have determined a huge number of aminoacidic sequences whose functions are, in the largest part, still unknown. In eukaryotes compartmentalization plays a major role in intracellular biochemical pathways. However the determination of subcellular localization with experimental high-throughput procedures is a difficult task and computational procedures are needed.
We developed BaCelLo (1), a predictor for five classes of subcellular localizations (secretory pathway, cytoplasm, nucleus, mitochondrion and chloroplast) that is based on different SVMs organized in a decision tree. The system exploits the information derived from the aminoacidic sequence and from the evolutionary information contained in alignment profiles. It analyzes the whole sequence composition and the compositions of both the N- and C-termini. The training set is curated in order to avoid redundancy. For
the first time a balancing procedure is introduced in order to mitigate the effect of biased training sets.
Three kingdom-specific predictors are implemented: for animals, plants and fungi, respectively. When distributing the proteins from animals and fungi into four classes, accuracy of BaCelLo reach 74% and 76%, respectively; a score of 67% is obtained when proteins from plants are distributed into five classes.
BaCelLo outperforms the other presently available methods for the same task and gives more balanced accuracy and coverage values for each class. BaCelLo is also described in Nature Protocols, in the Bioinformatics section (2) BaCelLo can be accessed at http://www.biocomp.unibo.it/bacello/.
BaCelLo is currently under integration in a workflow which will allow GO functional integration, prediction of GPI-anchors and discrimination between inner and outer membrane proteins. The workflow will be tested on large-scale genome annotation.
With a suite of machine learning based methods, developed in house (BaCelLo, SpepLip (3) and ENSEMBLE (4)), we presently built eSLDB (eukaryotic Subcellular Localization DataBase) (5) an online database collecting the annotations of subcellular localization of eukaryotic proteomes. So far five proteomes have been processed and stored: Homo sapiens, Mus musculus, Caenorhabditis elegans, Saccharomyces cerevisiae and Arabidospis thaliana. For each sequence, the database lists localization
obtained adopting three different approaches: 1) experimentally determined (when available); 2) homology based (when possible); 3) predicted. All the data are available at the website and can be searched by sequence, by protein code and/or by protein description.
Furthermore a more complex search can be performed combining different search fields and keys. All the data contained in the database can be freely downloaded in flat file format. The Database is available at: http://gpcr.biocomp.unibo.it/esldb/
An algorithm to compute the free distance of turbo codes
No full textA new algorithm for computing the free distance of turbo codes is applied to the CCSDS and the UMTS standard codes. Results on the free distance behaviour for increasing interleaver length are also presented
The relation between Lyman α absorbers and gas-rich galaxies in the local universe
No full textWe use high-resolution hydrodynamical simulations to investigate the spatial correlation between weak (N(H) (I) < 10(15) cm(-2)) Ly alpha absorbers and gas-rich galaxies in the local Universe. We confirm that Ly alpha absorbers are preferentially expected near gas-rich galaxies and that the degree of correlation increases with the column density of the absorber. The real-space galaxy auto-correlation is stronger than the cross-correlation (correlation lengths r(0,gg) = 3.1 +/- 0.1 Mpc h(-1) and r(0,ag) = 1.4 +/- 0.1 Mpc h(-1), respectively), in contrast with the recent results of Ryan-Weber, and the auto-correlation of absorbers is very weak. These results are robust to the presence of strong galactic winds in the hydrodynamical simulations. In redshift space, a further mismatch arises since at small separations the distortion pattern of the simulated galaxy-absorber cross-correlation function is different from the one measured by Ryan-Weber. However, when sampling the intergalactic medium along a limited number of lines-of-sight, as in the real data, uncertainties in the cross-correlation estimates are large enough to account for these discrepancies. Our analysis suggests that the statistical significance of difference between the cross-correlation and auto-correlation signal in current data sets is similar to 1 sigma only
Performance of DCSK in Multipath Environments: AComparison with Systems Using Gold Sequences
No full textA performance comparison is developed between a chaotic communication system and a spread spectrum system with similar features in terms of bandwidth and transceiver structure but based on more conventional Gold sequences. Comparison is made in the presence of noise and multipath contributions which degrade the channel quality. It is shown that, because of its more favourable correlation properties, the chaotic scheme exhibits lower error rates, at a parity of the bandwidth expansion factor. The same favourable correlation properties are also used to explain and show, through a numerical example, the benefits of chaotic segments in a multi-user environment
PredGPI: a GPI-anchor predictor
No full textBackground
Several eukaryotic proteins associated to the extracellular leaflet of the plasma membrane carry a Glycosylphosphatidylinositol (GPI) anchor, which is linked to the C-terminal residue after a proteolytic cleavage occurring at the so called ω-site. Computational methods were developed to discriminate proteins that undergo this post-translational modification starting from their aminoacidic sequences. However more accurate methods are needed for a reliable annotation of whole proteomes.
Results
Here we present PredGPI, a prediction method that, by coupling a Hidden Markov Model (HMM) and a Support Vector Machine (SVM), is able to efficiently predict both the presence of the GPI-anchor and the position of the ω-site. PredGPI is trained on a non-redundant dataset of experimentally characterized GPI-anchored proteins whose annotation was carefully checked in the literature.
Conclusion
PredGPI outperforms all the other previously described methods and is able to correctly replicate the results of previously published high-throughput experiments. PredGPI reaches a lower rate of false positive predictions with respect to other available methods and it is therefore a costless, rapid and accurate method for screening whole proteomes
The prediction of protein subcellular localization from sequence: a shortcut to functional genome annotation
No full textAutomated sequence annotation is a major goal of post-genomic era with hundreds of genomes in the databases, from both prokaryotes and eukaryotes. While the number of fully sequenced chromosomes from microbial organisms exponentially increased in the last decade above 600, presently we know the whole DNA content of only 25 eukaryotic organisms, including Homo sapiens. However, the process of genome annotation is far from being completed. This is particularly relevant in eukaryotes, whose cells contain several subcellular compartments, or organelles, enclosed by membranes, where different relevant functions are performed. Translocation across the membrane into the organelles is a highly regulated and complex cellular process. Indeed different proteins and/or protein isoforms, originated from genes by alternative splicing, may be conveyed to different cell compartments, depending on their specific role in the cell. During recent years the prediction of subcellular localization (SL) by computational means has been an active research area. Several methods are presently available based on different notions and addressing different aspects of SL. This review provides a short overview of the most well performing methods described in the literature, highlighting their predictive capabilities and different applications
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