A Network Architecture for Point Cloud Classification via Automatic Depth Images Generation

© 2018 IEEE. We propose a novel neural network architecture for point cloud classification. Our key idea is to automatically transform the 3D unordered input data into a set of useful 2D depth images, and classify them by exploiting well performing image classification CNNs. We present new differentiable module designs to generate depth images from a point cloud. These modules can be combined with any network architecture for processing point clouds. We utilize them in combination with state-of-the-art classification networks, and get results competitive with the state of the art in point cloud classification. Furthermore, our architecture automatically produces informative images representing the input point cloud, which could be used for further applications such as point cloud visualization

Akzeptanz von Tiergesundheitsplänen bei Landwirten – Ergebnisse einer Befragung bei 60 Betrieben

In organic farming the ambitious claims in enhancing and keeping animal health are often not realised. The implementation of animal health plans should clear this deficit effectively. Experiences with British and Danish herd health plans showed that the acceptance of plans is an essential part for its successful transfer into practice. But anyhow, this aspect has not been regarded sufficiently. To avoid similar mistakes like done in former institution tests a social study is integrated into German projects that deal with the implementation of animal health plans in poultry, dairy, and pig hus-bandry. To get more information about the acceptance, the study requires farmers’ attitudes to herd health plans, the motivation to animal health and financial and work capabilities as well

Finding Nested Common Intervals Efficiently

International audienceIn this paper, we study the problem of effi ciently fi nding gene clusters formalized by nested common intervals between two genomes represented either as permutations or as sequences. Considering permutations, we give several algorithms whose running time depends on the size of the actual output rather than the output in the worst case. Indeed, we first provide a straightforward O(n^3) time algorithm for finding all nested common intervals. We reduce this complexity by providing an O(n^2) time algorithm computing an irredundant output. Finally, we show, by providing a third algorithm, that fi nding only the maximal nested common intervals can be done in linear time. Considering sequences, we provide solutions (modi cations of previously de ned algorithms and a new algorithm) for di fferent variants of the problem, depending on the treatment one wants to apply to duplicated genes

Anthropology and GIS: Temporal and Spatial Distribution of the Philippine Negrito Groups

The Philippine negrito groups comprise a diverse group of populations speaking over 30 different languages, who are spread all over the archipelago, mostly in marginal areas of Luzon Island in the north, the central Visayas islands, and Mindanao in the south. They exhibit physical characteristics that are different from more than 100 Philippine ethnolinguistic groups that are categorized as non-negritos. Given their numbers, it is not surprising that Philippine negritos make up a major category in a number of general ethnographic maps produced since the nineteenth century. Reports from various ethnological surveys during this period, however, have further enriched our understanding regarding the extent and distribution of negrito populations. Using the data contained in these reports, it is possible to plot and create a map showing the historical locations and distribution of negrito groups. Using geographic information systems (GIS), the location and distribution of negrito groups at any given time can be overlaid on historical or current maps. In the present study, a GIS layer was compiled and extracted from the 2000 Philippine Census of population at the village level and overlaid on existing maps of the Philippines. The maps that were generated from this project will complement ongoing anthropological and genetic studies of negrito groups that inhabit different locations within the Philippine archipelago

Detection and validation of circular DNA fragments using nanopore sequencing

Occurrence of extra-chromosomal circular DNA is a phenomenon frequently observed in tumor cells, and the presence of such DNA has been recognized as a marker of adverse outcome across cancer types. We here describe a computational workflow for identification of DNA circles from long-read sequencing data. The workflow is implemented based on the Snakemake workflow management system. Its key step uses a graph-theoretic approach to identify putative circular fragments validated on simulated reads. We then demonstrate robustness of our approach using nanopore sequencing of selectively enriched circular DNA by highly sensitive and specific recovery of plasmids and the mitochondrial genome, which is the only circular DNA in normal human cells. Finally, we show that the workflow facilitates detection of larger circular DNA fragments containing extrachromosomal copies of the MYCN oncogene and the respective breakpoints, which is a potentially useful application in disease monitoring of several cancer types

Shared probe design and existing microarray reanalysis using PICKY

<p>Abstract</p> <p>Background</p> <p>Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations.</p> <p>Results</p> <p><smcaps>PICKY</smcaps> 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. <smcaps>PICKY</smcaps> 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, <smcaps>PICKY</smcaps> does not sacrifice the quality of shared probes when choosing them. The latest <smcaps>PICKY</smcaps> 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making <smcaps>PICKY</smcaps> 2.1 more versatile to microarray users.</p> <p>Conclusions</p> <p>Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.</p

Efficient and accurate P-value computation for Position Weight Matrices

<p>Abstract</p> <p>Background</p> <p>Position Weight Matrices (PWMs) are probabilistic representations of signals in sequences. They are widely used to model approximate patterns in DNA or in protein sequences. The usage of PWMs needs as a prerequisite to knowing the statistical significance of a word according to its score. This is done by defining the P-value of a score, which is the probability that the background model can achieve a score larger than or equal to the observed value. This gives rise to the following problem: Given a P-value, find the corresponding score threshold. Existing methods rely on dynamic programming or probability generating functions. For many examples of PWMs, they fail to give accurate results in a reasonable amount of time.</p> <p>Results</p> <p>The contribution of this paper is two fold. First, we study the theoretical complexity of the problem, and we prove that it is NP-hard. Then, we describe a novel algorithm that solves the P-value problem efficiently. The main idea is to use a series of discretized score distributions that improves the final result step by step until some convergence criterion is met. Moreover, the algorithm is capable of calculating the exact P-value without any error, even for matrices with non-integer coefficient values. The same approach is also used to devise an accurate algorithm for the reverse problem: finding the P-value for a given score. Both methods are implemented in a software called TFM-PVALUE, that is freely available.</p> <p>Conclusion</p> <p>We have tested TFM-PVALUE on a large set of PWMs representing transcription factor binding sites. Experimental results show that it achieves better performance in terms of computational time and precision than existing tools.</p

Nanoscale transient magnetization gratings excited and probed by femtosecond extreme ultraviolet pulses

We utilize coherent femtosecond extreme ultraviolet (EUV) pulses derived from a free electron laser (FEL) to generate transient periodic magnetization patterns with periods as short as 44 nm. Combining spatially periodic excitation with resonant probing at the dichroic M-edge of cobalt allows us to create and probe transient gratings of electronic and magnetic excitations in a CoGd alloy. In a demagnetized sample, we observe an electronic excitation with 50 fs rise time close to the FEL pulse duration and ~0.5 ps decay time within the range for the electron-phonon relaxation in metals. When the experiment is performed on a sample magnetized to saturation in an external field, we observe a magnetization grating, which appears on a sub-picosecond time scale as the sample is demagnetized at the maxima of the EUV intensity and then decays on the time scale of tens of picoseconds via thermal diffusion. The described approach opens prospects for studying dynamics of ultrafast magnetic phenomena on nanometer length scales