Computation of Debris Problem Caused by Active Seismic Shots on the Lunar Surface

Computation of impact densities and velocity distribution of debris from lunar surface explosion

Quality Assessment of Linked Datasets using Probabilistic Approximation

With the increasing application of Linked Open Data, assessing the quality of datasets by computing quality metrics becomes an issue of crucial importance. For large and evolving datasets, an exact, deterministic computation of the quality metrics is too time consuming or expensive. We employ probabilistic techniques such as Reservoir Sampling, Bloom Filters and Clustering Coefficient estimation for implementing a broad set of data quality metrics in an approximate but sufficiently accurate way. Our implementation is integrated in the comprehensive data quality assessment framework Luzzu. We evaluated its performance and accuracy on Linked Open Datasets of broad relevance.Comment: 15 pages, 2 figures, To appear in ESWC 2015 proceeding

Scalable Mining of Common Routes in Mobile Communication Network Traffic Data

A probabilistic method for inferring common routes from mobile communication network traffic data is presented. Besides providing mobility information, valuable in a multitude of application areas, the method has the dual purpose of enabling efficient coarse-graining as well as anonymisation by mapping individual sequences onto common routes. The approach is to represent spatial trajectories by Cell ID sequences that are grouped into routes using locality-sensitive hashing and graph clustering. The method is demonstrated to be scalable, and to accurately group sequences using an evaluation set of GPS tagged data

Peat decomposition records in three pristine ombrotrophic bogs in southern Patagonia

Ombrotrophic bogs in southern Patagonia have been examined with regard to paleoclimatic and geochemical research questions but knowledge about organic matter decomposition in these bogs is limited. Therefore, we examined peat humification with depth by Fourier Transformed Infrared (FTIR) measurements of solid peat, C/N ratio, and δ<sup>13</sup>C and δ<sup>15</sup>N isotope measurements in three bog sites. Peat decomposition generally increased with depth but distinct small scale variation occurred, reflecting fluctuations in factors controlling decomposition. C/N ratios varied mostly between 40 and 120 and were significantly correlated (<i>R</i><sup>2</sup> > 0.55, <i>p</i> < 0.01) with FTIR-derived humification indices. The degree of decomposition was lowest at a site presently dominated by <i>Sphagnum</i> mosses. The peat was most strongly decomposed at the driest site, where currently peat-forming vegetation produced less refractory organic material, possibly due to fertilizing effects of high sea spray deposition. Decomposition of peat was also advanced near ash layers, suggesting a stimulation of decomposition by ash deposition. Values of δ<sup>13</sup>C were 26.5 ± 2‰ in the peat and partly related to decomposition indices, while δ<sup>15</sup>N in the peat varied around zero and did not consistently relate to any decomposition index. Concentrations of DOM partly related to C/N ratios, partly to FTIR derived indices. They were not conclusively linked to the decomposition degree of the peat. DOM was enriched in <sup>13</sup>C and in <sup>15</sup>N relative to the solid phase probably due to multiple microbial modifications and recycling of N in these N-poor environments. In summary, the depth profiles of C/N ratios, δ<sup>13</sup>C values, and FTIR spectra seemed to reflect changes in environmental conditions affecting decomposition, such as bog wetness, but were dominated by site specific factors, and are further influenced by ash deposition and possibly by sea spray input

Counting approximately-shortest paths in directed acyclic graphs

Given a directed acyclic graph with positive edge-weights, two vertices s and t, and a threshold-weight L, we present a fully-polynomial time approximation-scheme for the problem of counting the s-t paths of length at most L. We extend the algorithm for the case of two (or more) instances of the same problem. That is, given two graphs that have the same vertices and edges and differ only in edge-weights, and given two threshold-weights L_1 and L_2, we show how to approximately count the s-t paths that have length at most L_1 in the first graph and length at most L_2 in the second graph. We believe that our algorithms should find application in counting approximate solutions of related optimization problems, where finding an (optimum) solution can be reduced to the computation of a shortest path in a purpose-built auxiliary graph

Viral antibody dynamics in a chiropteran host

1. Bats host many viruses that are significant for human and domestic animal health, but the dynamics of these infections in their natural reservoir hosts remain poorly elucidated.<p></p> 2. In these, and other, systems, there is evidence that seasonal life-cycle events drive infection dynamics, directly impacting the risk of exposure to spillover hosts. Understanding these dynamics improves our ability to predict zoonotic spillover from the reservoir hosts.<p></p> 3. To this end, we followed henipavirus antibody levels of >100 individual E. helvum in a closed, captive, breeding population over a 30-month period, using a powerful novel antibody quantitation method.<p></p> 4. We demonstrate the presence of maternal antibodies in this system and accurately determine their longevity. We also present evidence of population-level persistence of viral infection and demonstrate periods of increased horizontal virus transmission associated with the pregnancy/lactation period.<p></p> 5.The novel findings of infection persistence and the effect of pregnancy on viral transmission, as well as an accurate quantitation of chiropteran maternal antiviral antibody half-life, provide fundamental baseline data for the continued study of viral infections in these important reservoir hosts

Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing, expression profiles, proteomics, and electronic health records are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of distributions that commonly appear in the analysis of such data. These distributions present some interesting features: they are discontinuous in the rational numbers, but continuous in the irrational numbers, and possess a certain self-similar (fractal-like) structure. The first set of examples which we present here are drawn from a high-throughput sequencing experiment. Here, the self-similar distributions appear as part of the evaluation of the error rate of the sequencing technology and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in electronic clinical data. The distributions are also relevant to identification of subclonal populations in tumors and the study of the evolution of infectious diseases, and more precisely the study of quasi-species and intrahost diversity of viral populations