Identical approximative sequence for various notions of universality

AbstractIn this paper, we examine various notions of universality, which have already been proved generic. Our main purpose is to prove that generically they occur simultaneously with the same approximative sequence

PETROLOGICAL CHARACTERS OF THE EARLY CRETACEOUS BOEOTHIAN FLYSCH, (CENTRAL GREECE)

This paper is aimed to study the petrographic characters of the Boeothian Flysch, an Early Cretaceous turbidite deposit which marks the boundary between the External/Internal Hellenides in central-southern Greece, in order to define a preliminary palaeogeographic reconstruction of the Pindos segment of the Alpine Tethys. The Boeothian Flysch is mainly made up by basal conglomerates and arenaceous-pelitic lithofacies, locally interlayered with Calpionellid micrite limestones. This formation is here supposed to belong to the Early Cretaceous flysch family, which marks the contact between the internal and external areas along all the western and central European Alpine Chains for more than 7,000 km, from the Gibraltar Arc to the Balkans via the Calabria-Peloritani Arc. Provenance of these flysch is commonly connected to internal areas, mainly made up by Hercynian crystalline basements and, locally, by ophiolitic complexes. The petrographic data obtained from representative sandstones of the Boeothian Flysch suggest a provenance from internal sources, formed by a Jurassic carbonate platform, metamorphic basements and by ophiolitic complexes, which can be identified with the Pelagonian Terranes (Auct.). An Early Cretaceous uplift and rejuvenation processes, probably related to the late Cretaceous tectogenesis, widely recorded in almost all the central-western Alpine Tethis, affected these internal domains with consequent production of abundant detrital supply in the innermost sector of the Pindos Ocean, whose external margin was bounded by the Parnassos microcontinent

Modeling cell proliferation in human acute myeloid leukemia xenografts

Motivation: Acute myeloid leukemia (AML) is one of the most common hematological malignancies, characterized by high relapse and mortality rates. The inherent intra-tumor heterogeneity in AML is thought to play an important role in disease recurrence and resistance to chemotherapy. Although experimental protocols for cell proliferation studies are well established and widespread, they are not easily applicable to in vivo contexts, and the analysis of related time-series data is often complex to achieve. To overcome these limitations, model-driven approaches can be exploited to investigate different aspects of cell population dynamics. Results: In this work, we present ProCell, a novel modeling and simulation framework to investigate cell proliferation dynamics that, differently from other approaches, takes into account the inherent stochasticity of cell division events. We apply ProCell to compare different models of cell proliferation in AML, notably leveraging experimental data derived from human xenografts in mice. ProCell is coupled with Fuzzy Self-Tuning Particle Swarm Optimization, a swarm-intelligence settings-free algorithm used to automatically infer the models parameterizations. Our results provide new insights on the intricate organization of AML cells with highly heterogeneous proliferative potential, highlighting the important role played by quiescent cells and proliferating cells characterized by different rates of division in the progression and evolution of the disease, thus hinting at the necessity to further characterize tumor cell subpopulations. Availability and implementation: The source code of ProCell and the experimental data used in this work are available under the GPL 2.0 license on GITHUB at the following URL: https://github.com/aresio/ProCell

Increasing maritime situation awareness via trajectory detection, enrichment and recognition of events

The research presented in this paper aims to show the deployment and use of advanced technologies towards processing surveillance data for the detection of events, contributing to maritime situation awareness via trajectories’ detection, synopses generation and semantic enrichment of trajectories. We first introduce the context of the maritime domain and then the main principles of the big data architecture developed so far within the European funded H2020 datAcron project. From the integration of large maritime trajectory datasets, to the generation of synopses and the detection of events, the main functions of the datAcron architecture are developed and discussed. The potential for detection and forecasting of complex events at sea is illustrated by preliminary experimental results

A new mathematical model for the interpretation of translational research evaluating six CTLA-4 polymorphisms in high-risk melanoma patients receiving adjuvant interferon

Adjuvant therapy of stage IIB/III melanoma with interferon reduces relapse and mortality by up to 33% but is accompanied by toxicity-related complications. Polymorphisms of the CTLA-4 gene associated with autoimmune diseases could help in identifying interferon treatment benefits. We previously genotyped 286 melanoma patients and 288 healthy (unrelated) individuals for six CTLA-4 polymorphisms (SNP). Previous analyses found no significant differences between the distributions of CTLA-4 polymorphisms in the melanoma population vs. controls, no significant difference in relapse free and overall survivals among patients and no correlation between autoimmunity and specific alleles. We report new analysis of these CTLA-4 genetic profiles, using Network Phenotyping Strategy (NPS). It is graph-theory based method, analyzing the SNP patterns. Application of NPS on CTLA-4 polymorphism captures allele relationship pattern for every patient into 6-partite mathematical graph P. Graphs P are combined into weighted 6-partite graph S, which subsequently decomposed into reference relationship profiles (RRP). Finally, every individual CTLA-4 genotype pattern is characterized by the graph distances of P from eight identified RRP's. RRP's are subgraphs of S, collecting equally frequent binary allele co-occurrences in all studied loci. If S topology represents the genetic "dominant model", the RRP's and their characteristic frequencies are identical to expectation-maximization derived haplotypes and maximal likelihood estimates of their frequencies. The graphrepresentation allows showing that patient CTLA-4 haplotypes are uniquely different from the controls by absence of specific SNP combinations. New function-related insight is derived when the 6-partite graph reflects allelic state of CTLA-4. We found that we can use differences between individual P and specific RRPs to identify patient subpopulations with clearly different polymorphic patterns relatively to controls as well as to identify patients with significantly different survival. © 2014 Pancoska et al

Understanding children’s constructions of meanings about other children: implications for inclusiveeducation

This paper explores the factors that influence the way children construct meanings about other children, and especially those who seem to experience marginalisation, within school contexts. The research involved an ethnographic study in a primary school in Cyprus over a period of 5 months. Qualitative methods were used, particularly participant observations and interviews with children. Interpretation of the data suggests that children's perceptions about other children, and especially those who come to experience marginalisation, are influenced by the following factors: other children and the interactions between them; adults’ way of behaving in the school; the existing structures within the school; and the cultures of the school and the wider educational context. Even though the most powerful factor was viewed to be the adults’ influence, it was rather the interweaving between different factors that seemed to lead to the creation of particular meanings for other children. In the end, it is argued that children's voices should be seen as an essential element within the process of developing inclusive practices.<br/

Big data analytics for time critical maritime and aerial mobility forecasting

The correlated exploitation of heterogeneous data sources offering very large archival and streaming data is important to increase the accuracy of computations when analysing and predicting future states of moving entities. Aiming to significantly advance the capacities of systems to improve safety and effectiveness of critical operations involving a large number of moving entities in large geographical areas, this paper describes progress achieved towards time critical big data analytics solutions to user-defined challenges in the air-traffic management and maritime domains. Besides, this paper presents further research challenges concerning data integration and management, predictive analytics for trajectory and events forecasting, and visual analytics