Graph theory reveals dysconnected hubs in 22q11DS and altered nodal efficiency in patients with hallucinations.

Schizophrenia is postulated to be the prototypical dysconnection disorder, in which hallucinations are the core symptom. Due to high heterogeneity in methodology across studies and the clinical phenotype, it remains unclear whether the structural brain dysconnection is global or focal and if clinical symptoms result from this dysconnection. In the present work, we attempt to clarify this issue by studying a population considered as a homogeneous genetic sub-type of schizophrenia, namely the 22q11.2 deletion syndrome (22q11.2DS). Cerebral MRIs were acquired for 46 patients and 48 age and gender matched controls (aged 6-26, respectively mean age = 15.20 ± 4.53 and 15.28 ± 4.35 years old). Using the Connectome mapper pipeline (connectomics.org) that combines structural and diffusion MRI, we created a whole brain network for each individual. Graph theory was used to quantify the global and local properties of the brain network organization for each participant. A global degree loss of 6% was found in patients' networks along with an increased Characteristic Path Length. After identifying and comparing hubs, a significant loss of degree in patients' hubs was found in 58% of the hubs. Based on Allen's brain network model for hallucinations, we explored the association between local efficiency and symptom severity. Negative correlations were found in the Broca's area (p < 0.004), the Wernicke area (p < 0.023) and a positive correlation was found in the dorsolateral prefrontal cortex (DLPFC) (p < 0.014). In line with the dysconnection findings in schizophrenia, our results provide preliminary evidence for a targeted alteration in the brain network hubs' organization in individuals with a genetic risk for schizophrenia. The study of specific disorganization in language, speech and thought regulation networks sharing similar network properties may help to understand their role in the hallucination mechanism.

Comparing Random-based and k-Anonymity-Based Algorithms for Graph Anonymization

Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on random-ization techniques and on k-anonymity concepts. We can use both of them to obtain an anonymized graph with a given k-anonymity value. In this paper we compare algorithms based on both techniques in orderto obtain an anonymized graph with a desired k-anonymity value. We want to analyze the complexity of these methods to generate anonymized graphs and the quality of the resulting graphs.

Unification of multi-species vertebrate anatomy ontologies for comparative biology in Uberon.

BACKGROUND: Elucidating disease and developmental dysfunction requires understanding variation in phenotype. Single-species model organism anatomy ontologies (ssAOs) have been established to represent this variation. Multi-species anatomy ontologies (msAOs; vertebrate skeletal, vertebrate homologous, teleost, amphibian AOs) have been developed to represent 'natural' phenotypic variation across species. Our aim has been to integrate ssAOs and msAOs for various purposes, including establishing links between phenotypic variation and candidate genes. RESULTS: Previously, msAOs contained a mixture of unique and overlapping content. This hampered integration and coordination due to the need to maintain cross-references or inter-ontology equivalence axioms to the ssAOs, or to perform large-scale obsolescence and modular import. Here we present the unification of anatomy ontologies into Uberon, a single ontology resource that enables interoperability among disparate data and research groups. As a consequence, independent development of TAO, VSAO, AAO, and vHOG has been discontinued. CONCLUSIONS: The newly broadened Uberon ontology is a unified cross-taxon resource for metazoans (animals) that has been substantially expanded to include a broad diversity of vertebrate anatomical structures, permitting reasoning across anatomical variation in extinct and extant taxa. Uberon is a core resource that supports single- and cross-species queries for candidate genes using annotations for phenotypes from the systematics, biodiversity, medical, and model organism communities, while also providing entities for logical definitions in the Cell and Gene Ontologies. THE ONTOLOGY RELEASE FILES ASSOCIATED WITH THE ONTOLOGY MERGE DESCRIBED IN THIS MANUSCRIPT ARE AVAILABLE AT: http://purl.obolibrary.org/obo/uberon/releases/2013-02-21/ CURRENT ONTOLOGY RELEASE FILES ARE AVAILABLE ALWAYS AVAILABLE AT: http://purl.obolibrary.org/obo/uberon/releases/

Scheduling an European basketball competition. An application of graph theory

The object of this project is to schedule a ctitious European basketball competition with many teams situated a long distances. The schedule must be fair, feasible and economical, which means that the total distance trav- eled by every team must be the minimal possible. First, we de ne the sport competition terminology and study di erent competition systems, focusing on the NBA and the Euroleague systems. Then we de ne concepts of graph theory and spherical distance that will be needed. Next we propose a com- petition system, explaining where will be allocated the teams and how will be the scheduling. Then there is a description of the programs that have been implemented, and, nally, the complete schedule is displayed, and some possible improvements are mentioned.

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

An open source browser-based software tool for graph drawing and visualisation

In this research work we searched for open source libraries which supports graph drawing and visualisation and can run in a browser. Subsequent these libraries were evaluated to find out which one is the best for this task. The result was the d3.js is that library which has the greatest functionality, flexibility and customisability. Afterwards we developed an open source software tool where d3.js was included and which was written in JavaScript so that it can run browser-based.

WebGraphEd, an open source graph drawing editor for the web

WebGraphEd is an open source software for graph visualization and manipulation. It is especially designed to work for the web platform through a web browser. The web application has been written in JavaScript and compacted later, which makes it a very lightweight software. There is no need of additional software, and the only requirement is to have an HTML5 compliant browser. WebGraphEd works with scalable vector graphics (SVG), which it makes possible to create lossless graph drawings.

A note on the periodic orbits and topological entropy of graph maps

This paper deals with the relationship between the periodic orbits of continuous maps on graphs and the topological entropy of the map. We show that the topological entropy of a graph map can be approximated by the entropy of its periodic orbits.

Unification of Emission Measurements in Paper and Pulp Mills

Tässä diplomityössä tavoitteena on selvittää käytännöt ja menetelmät, joilla UPM-Kymmenen sellu-, paperi- ja vaneritehtaat ympäri maailman mittaavat ja laskevat ilmapäästönsä. Tämä tehdään kyselylomakkeella, joka lähetetään tehtaiden ympäristöpäälliköille. Kaikki tärkeimmät seikat ilmapäästöihin liittyen, kuten vaaditut jatkuvatoimiset mittaukset, jaksottaiset mittaukset, raportointikäytäntö, kalibrointi jne. kysytään lomakkeessa. Kyselylomakkeessa painotetaan mittauskäytäntöä sellutehtaissa sekä energiantuotannossa. Saatujen tulosten perusteella annetaan ehdotuksia sekä ohjeita tulevaisuutta varten, jotta mittaustulosten kokoaminen helpottuisi ja vertailukelpoisuus paranisi. Työn kirjallisuusosuudessa selvitetään yleisimmät päästölähteet sekä päästökomponentit paperi –ja selluteollisuudessa. Näiden ei toivottujen yhdisteiden syntymekanismit sekä menetelmät niiden poistamiseksi savukaasuista on myös lyhyesti kuvailtu. Myös erilaiset analysointi- ja näytteenottomenetelmät on kerrottu. Erot tehtaiden ympäristöluvissa käydään läpi, jakaen tehtaat kolmeen maantieteelliseen ryhmään. Lupakäytäntöjen osalta Suomen osuutta on painotettu, sillä UPM-Kymmene on varsin Suomikeskeinen yhtiö tehtaiden lukumääriin ja sijainteihin katsottuna. Viranomaismääräykset sekä päästörajat muutamista tehtaista on esitetty havainnollistaakseen alueellisia eroja.

Lossless Compression Methods for Multispectral Images: Development and Comparisons

Main purpose of this thesis is to introduce a new lossless compression algorithm for multispectral images. Proposed algorithm is based on reducing the band ordering problem to the problem of finding a minimum spanning tree in a weighted directed graph, where set of the graph vertices corresponds to multispectral image bands and the arcs’ weights have been computed using a newly invented adaptive linear prediction model. The adaptive prediction model is an extended unification of 2–and 4–neighbour pixel context linear prediction schemes. The algorithm provides individual prediction of each image band using the optimal prediction scheme, defined by the adaptive prediction model and the optimal predicting band suggested by minimum spanning tree. Its efficiency has been compared with respect to the best lossless compression algorithms for multispectral images. Three recently invented algorithms have been considered. Numerical results produced by these algorithms allow concluding that adaptive prediction based algorithm is the best one for lossless compression of multispectral images. Real multispectral data captured from an airplane have been used for the testing.

A Note on the periodic orbits and topological entropy of graph maps

This paper deals with the relationship between the periodic orbits of continuous maps on graphs and the topological entropy of the map. We show that the topological entropy of a graph map can be approximated by the entropy of its periodic orbits