Indoor Navigation in Facilities with Repetitive Structures.

Most facilities are structured in a repetitive manner. In this paper, we propose an algorithm and its partial implementation for a cellular guide in such facilities without GPS use. The complete system is based on iBeacons-like components, which operate on BLE technology, and their integration into a navigation application. We assume that the user's location is determined with sufficient accuracy. Our main goal revolves around leveraging the repetitive structure of the given facility to optimize navigation in terms of storage requirements, energy efficiency in the cellular device, algorithmic complexity, and other aspects. To the best of our knowledge, there is no prior experience in addressing this specific aim. In order to provide high performance in real time, we rely on optimal saving and the use of pre-calculated and stored navigation sub-routes. Our implementation seamlessly integrates iBeacon communications, a pre-defined indoor map, diverse data structures for efficient information storage, and a user interface, all working cohesively under a single supervision. Each module can be considered, developed, and improved independently. The approach is mainly directed to places, such as passenger ships, hotels, colleges, and so on. Because of the fact that there are "replicated" parts on different floors, stored once and used for multiple routes, we reduce the amount of information that must be stored, thus helping to reduce memory usage and as a result, yielding a better running time and energy consumption.

Electroencephalography functional connectivity-A biomarker for painful polyneuropathy.

BACKGROUND AND PURPOSE: Advanced analysis of electroencephalography (EEG) data has become an essential tool in brain research. Based solely on resting state EEG signals, a data-driven, predictive and explanatory approach is presented to discriminate painful from non-painful diabetic polyneuropathy (DPN) patients. METHODS: Three minutes long, 64 electrode resting-state recordings were obtained from 180 DPN patients. The analysis consisted of a mixture of traditional, explanatory and machine learning analyses. First, the 10 functional bivariate connections best differentiating between painful and non-painful patients in each EEG band were identified and the relevant receiver operating characteristic was calculated. Later, those connections were correlated with selected clinical parameters. RESULTS: Predictive analysis indicated that theta and beta bands contain most of the information required for discrimination between painful and non-painful polyneuropathy patients, with area under the receiver operating characteristic curve values of 0.93 for theta and 0.89 for beta bands. Assessing statistical differences between the average magnitude of functional connectivity values and clinical pain parameters revealed that painful DPN patients had significantly higher cortical functional connectivity than non-painful ones (p = 0.008 for theta and p = 0.001 for alpha bands). Moreover, intra-band analysis of individual significant functional connections revealed a positive correlation with average reported pain in the previous 3 months in all frequency bands. CONCLUSIONS: Resting state EEG functional connectivity can serve as a highly accurate biomarker for the presence or absence of pain in DPN patients. This highlights the importance of the brain, in addition to the peripheral lesions, in generating the clinical pain picture. This tool can probably be extended to other pain syndromes.

Entropy-Based Approach for the Detection of Changes in Arabic Newspapers' Content.

A new method for the recognition of meaningful changes in social state based on transformations of the linguistic content in Arabic newspapers is suggested. The detected alterations of the linguistic material in Arabic newspapers play an indicator role. The currently proposed approach acts in an "online" fashion and uses pre-trained vector representations of Arabic words. After a pre-processing stage, the words in the issues' texts are substituted by vectors obtained within a word embedding methodology. The approach typifies the consistent linguistic template by the similarity of the embedded vectors. A change in the distributions of the issue-grounded samples indicates a difference in the underlying newspaper template. A two-step procedure implements the concept, where the first step compares the similarity distribution of the current issue versus the union of ones corresponding to several of its predecessors. A repeating under-sampling approach accompanied by a two-sample test stabilizes the sampling and returns a collection of the resultant p-values. In the second stage, the entropy of these sets is sequentially calculated, such that the change points of the time series obtained in this way indicate the changes in the newspaper content. Numerical experiments provided on the following issues of several Arabic newspapers published in the Arab Spring period demonstrate the high reliability of the method.

Evaluating the number of different genomes in a metagenome by means of the compositional spectra approach.

Determination of metagenome composition is still one of the most interesting problems of bioinformatics. It involves a wide range of mathematical methods, from probabilistic models of combinatorics to cluster analysis and pattern recognition techniques. The successful advance of rapid sequencing methods and fast and precise metagenome analysis will increase the diagnostic value of healthy or pathological human metagenomes. The article presents the theoretical foundations of the algorithm for calculating the number of different genomes in the medium under study. The approach is based on analysis of the compositional spectra of subsequently sequenced samples of the medium. Its essential feature is using random fluctuations in the bacteria number in different samples of the same metagenome. The possibility of effective implementation of the algorithm in the presence of data errors is also discussed. In the work, the algorithm of a metagenome evaluation is described, including the estimation of the genome number and the identification of the genomes with known compositional spectra. It should be emphasized that evaluating the genome number in a metagenome can be always helpful, regardless of the metagenome separation techniques, such as clustering the sequencing results or marker analysis.

Detecting non-uniform clusters in large-scale interaction graphs.

Graph clustering becomes difficult as the graph size and complexity increase. In particular, in interaction graphs, the clusters are small and the data on the underlying interaction are not only complex, but also noisy due to the lack of information and experimental errors. The graphs representing such data consist of (possibly overlapping) clusters of non-uniform size with some false positive and false negative links. In this article, we propose a new approach, assuming that clusters in the graphs of protein-protein interaction (PPI) networks resemble corrupted cliques. Therefore, the problem can be reduced to looking for clusters only among nodes of approximately similar degrees. This idea was implemented using a soft version of the Farthest-Point-First (FPF) clustering algorithm with the Jaccard distance function modified to perform on slightly overlapping clusters. The StripClust program developed by us was tested on a synthetic network and on the yeast PPI network.

Hidden ancient repeats in DNA: mapping and quantification.

We have shown, in a previous paper, that tandem repeating sequences, especially triplet repeats, play a very important role in gene evolution. This result led to the formulation of the following hypothesis: most of the genomic sequences evolved through everlasting acts of tandem repeat expansions with subsequent accumulation of changes. In order to estimate how much of the observed sequences have the repeat origin we describe the adaptation of a text segmentation algorithm, based on dynamic programming, to the mapping of the ancient expansion events. The algorithm maximizes the segmentation cost, calculated as the similarity of obtained fragments to the putative repeat sequence. In the first application of the algorithm to segmentations of genomic sequences, a significant difference between the natural sequences and the corresponding shuffled sequences is detected. The natural fragments are longer and more similar to the putative repeat sequences. As our analysis shows, the coding sequences allow for repeats only when the size of the repeated words is divisible by three. In contrast, in the non-coding sequences, all repeated word sizes are present. It was estimated, that in Escherichia coli K12 genome, about 35.5% of sequence can be detectably traced to original simple repeat ancestors. The results shed light on the genomic sequence organization, and strongly confirm the hypothesis about the crucial role of triplet expansions in gene origin and evolution.

Robust classifying of prokaryotic genomes.

In this paper, we propose a method to classify prokaryotic genomes using the agglomerative information bottleneck method for unsupervised clustering. Although the method we present here is closely related to a group of methods based on detecting the presence or absence of genes, our method is different because it uses gene lengths as well. We show that this amended method is reliable. For robustness evaluation, we apply bootstrap and jackknife techniques to input data. As a result, we are able to propose an approach to determine the stability level of a cladogram. We demonstrate that the genome tree produced for a selected small group of genomes looks a lot like a phylogenetic tree of this group.

Multiple levels of meaning in DNA sequences, and one more.

If we define a genetic code as a widespread DNA sequence pattern that carries a message with an impact on biology, then there are multiple genetic codes. Sequences involved in these codes overlap and, thus, both interact with and constrain each other, such as for the triplet code, the intron-splicing code, the code for amphipathic alpha helices, and the chromatin code. Nucleosomes preferentially are located at the ends of exons, thus protecting splice junctions, with the N9 positions of guanines of the GT and AG junctions oriented toward the histones. Analysis of protein-coding sequences reveals numerous traces of tandem repeats, apparently formed by triplet expansion, which in effect is a genome inflation ``code''. Our data are consistent with the hypothesis that expansion of simple tandem repetition of certain aggressive triplets has been a characteristic of life from its emergence. Such expanding triplets appear to be the major factor underlying observed codon usage biases.

Nucleosome positioning patterns derived from human apoptotic nucleosomes.

This communication reports on the nucleosome positioning patterns (bendability matrices) for the human genome, derived from over 8_million nucleosome DNA sequences obtained from apoptotically digested lymphocytes. This digestion procedure is used here for the first time for the purpose of extraction and sequencing of the nucleosome DNA fragments. The dominant motifs suggested by the matrices of DNA bendability calculated for light and heavy isochores are significantly different. Both, however, are in full agreement with the linear description YRRRRRYYYYYR, and with earlier derivations by N-gram extensions. Thus, the choice of the nucleosome positioning patterns crucially depends on the G + C composition of the analyzed sequences.

Large-scale genome clustering across life based on a linguistic approach.

With the availability of genome sequences, the possibility of new phylogenetic reconstructions arises in order to reveal genomic relationships among organisms. According to the compositional-spectra (CS) approach proposed in our previous studies, any genomic sequence can be characterized by a distribution of frequencies of imperfect matching of words (oligonucleotides). In the current application of CS-analysis, we attempted to analyze the cluster structure of genomes across life. It appeared that compositional spectra show a clear three-group clustering of the compared prokaryotic and eukaryotic genomes. Unexpectedly, this grouping seriously differs from the classical Universal Tree of Life structure represented by common kingdoms known as Eubacteria, Archaebacteria, and Eukarya. The revealed CS-clustering displays high stability, putatively reflecting its objective nature, and still enigmatic biological significance that may result from convergent evolution driven by ecological selection. We believe that our approach provides a new and wider (compared to traditional methods) perspective of extracting genomic information of high evolutionary relevance.