TVL₁ Planarity Regularization for 3D Shape Approximation

The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within. This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy

Comparison of results from tests of association in unrelated individuals with uncollapsed and collapsed sequence variants using tiled regression

Tiled regression is an approach designed to determine the set of independent genetic variants that contribute to the variation of a quantitative trait in the presence of many highly correlated variants. In this study, we evaluate the statistical properties of the tiled regression method using the Genetic Analysis Workshop 17 data in unrelated individuals for traits Q1, Q2, and Q4. To increase the power to detect rare variants, we use two methods to collapse rare variants and compare the results with those from the uncollapsed data. In addition, we compare the tiled regression method to traditional tests of association with and without collapsed rare variants. The results show that collapsing rare variants generally improves the power to detect associations regardless of method, although only variants with the largest allelic effects could be detected. However, for traditional simple linear regression, the average estimated type I error is dependent on the trait and varies by about three orders of magnitude. The estimated type I error rate is stable for tiled regression across traits

Mass dependence of light nucleus production in ultrarelativistic heavy ion collisions

Light nuclei can be produced in the central reaction zone via coalescence in relativistic heavy ion collisions. E864 at BNL has measured the production of ten light nuclei with nuclear number of A=1 to A=7 at rapidity $y\simeq1.9$ and $p_{T}/A\leq300MeV/c$. Data were taken with a Au beam of momentum of 11.5 A $GeV/c$ on a Pb or Pt target with different experimental settings. The invariant yields show a striking exponential dependence on nuclear number with a penalty factor of about 50 per additional nucleon. Detailed analysis reveals that the production may depend on the spin factor of the nucleus and the nuclear binding energy as well.Comment: (6 pages, 3 figures), some changes on text, references and figures' lettering. To be published in PRL (13Dec1999

Digital relief generation from 3D models

It is difficult to extend image-based relief generation to high-relief generation, as the images contain insufficient height information. To generate reliefs from three-dimensional (3D) models, it is necessary to extract the height fields from the model, but this can only generate bas-reliefs. To overcome this problem, an efficient method is proposed to generate bas-reliefs and high-reliefs directly from 3D meshes. To produce relief features that are visually appropriate, the 3D meshes are first scaled. 3D unsharp masking is used to enhance the visual features in the 3D mesh, and average smoothing and Laplacian smoothing are implemented to achieve better smoothing results. A nonlinear variable scaling scheme is then employed to generate the final bas-reliefs and high-reliefs. Using the proposed method, relief models can be generated from arbitrary viewing positions with different gestures and combinations of multiple 3D models. The generated relief models can be printed by 3D printers. The proposed method provides a means of generating both high-reliefs and bas-reliefs in an efficient and effective way under the appropriate scaling factors

Genomics of Divergence along a Continuum of Parapatric Population Differentiation

MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1)

Measurements of Light Nuclei Production in 11.5 A GeV/c Au+Pb Heavy-Ion Collisions

We report on measurements by the E864 experiment at the BNL-AGS of the yields of light nuclei in collisions of Au(197) with beam momentum of 11.5 A GeV/c on targets of Pb(208) and Pt(197). The yields are reported for nuclei with baryon number A=1 up to A=7, and typically cover a rapidity range from y(cm) to y(cm)+1 and a transverse momentum range of approximately 0.1 < p(T)/A < 0.5 GeV/c. We calculate coalescence scale factors B(A) from which we extract model dependent source dimensions and collective flow velocities. We also examine the dependences of the yields on baryon number, spin, and isospin of the produced nuclei.Comment: 21 figures-to be published in Phys. Rev.

Paired-End Analysis of Transcription Start Sites in Arabidopsis Reveals Plant-Specific Promoter Signatures

Understanding plant gene promoter architecture has long been a challenge due to the lack of relevant large-scale data sets and analysis methods. Here we present a publicly available, large-scale transcription start site (TSS) dataset in plants using a high-resolution method for analysis of 5’ ends of mRNA transcripts. Our dataset is produced using the Paired-End Analysis of Transcription Start Sites (PEAT) protocol, providing millions of TSS locations from wild-type Col-0 Arabidopsis whole root samples. Using this dataset, we grouped TSS reads into “TSS tag clusters” and categorized clusters into three spatial initiation patterns: narrow peak, broad with peak, and weak peak. We then designed a machine learning model that predicts the presence of TSS tag clusters with outstanding sensitivity and specificity for all three initiation patterns. We used this model to analyze the transcription factor binding site content of promoters exhibiting these initiation patterns. In contrast to the canonical notions of TATA-containing and more broad “TATA-less” promoters, the model shows that, in plants, the vast majority of transcription start sites are TATA-free, and are defined by a large compendium of known DNA sequence binding elements. We present results on the usage of these elements, and provide our Plant PEAT Peaks (3PEAT) model that predicts the presence of TSSs directly from sequence.Keywords: Transcription factor, Start site, Arabidopsis, MicroRNA, Gene regulatio

Wnt Signaling Is Required for Early Development of Zebrafish Swimbladder

10.1371/journal.pone.0018431PLoS ONE63

Extensive Copy-Number Variation of Young Genes across Stickleback Populations

MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Barriers to chimpanzee gene flow at the south-east edge of their distribution

Populations on the edge of a species' distribution may represent an important source of adaptive diversity, yet these populations tend to be more fragmented and are more likely to be geographically isolated. Lack of genetic exchanges between such populations, due to barriers to animal movement, can not only compromise adaptive potential but also lead to the fixation of deleterious alleles. The south-eastern edge of chimpanzee distribution is particularly fragmented, and conflicting hypotheses have been proposed about population connectivity and viability. To address this uncertainty, we generated both mitochondrial and MiSeq-based microsatellite genotypes for 290 individuals ranging across western Tanzania. While shared mitochondrial haplotypes confirmed historical gene flow, our microsatellite analyses revealed two distinct clusters, suggesting two populations currently isolated from one another. However, we found evidence of high levels of gene flow maintained within each of these clusters, one of which covers an 18,000 km2 ecosystem. Landscape genetic analyses confirmed the presence of barriers to gene flow with rivers and bare habitats highly restricting chimpanzee movement. Our study demonstrates how advances in sequencing technologies, combined with the development of landscape genetics approaches, can resolve ambiguities in the genetic history of critical populations and better inform conservation efforts of endangered species