Karyopherinbeta (Kapbeta) proteins bind nuclear localization and export signals (NLSs and NESs) to mediate nucleocytoplasmic trafficking, a process regulated by Ran GTPase through its nucleotide cycle. Diversity and complexity of signals recognized by Kap betas have prevented prediction of new Kap beta substrates. The structure of Kap beta 2 (also known as Transportin) bound to one of its substrates, the NLS of hnRNP A1, that we report here explains the mechanism of substrate displacement by Ran GTPase. Further analyses reveal three rules for NLS recognition by Kap beta 2: NLSs are structurally disordered in free substrates, have overall basic character, and possess a central hydrophobic or basic motif followed by a C-terminal R/H/KX(2-5)PY consensus sequence. We demonstrate the predictive nature of these rules by identifying NLSs in seven previously known Kap beta 2 substrates and uncovering 81 new candidate substrates, confirming five experimentally. These studies define and validate a new NLS that could not be predicted by primary sequence analysis alone.

Direct methods for Visual Odometry (VO) have gained popularity due to their capability to exploit information from all intensity gradients in the image. However, low computational speed as well as missing guarantees for optimality and consistency are limiting factors of direct methods, where established feature-based methods instead succeed at. Based on these considerations, we propose a Semidirect VO (SVO) that uses direct methods to track and triangulate pixels that are characterized by high image gradients but relies on proven feature-based methods for joint optimization of structure and motion. Together with a robust probabilistic depth estimation algorithm, this enables us to efficiently track pixels lying on weak corners and edges in environments with little or high-frequency texture. We further demonstrate that the algorithm can easily be extended to multiple cameras, to track edges, to include motion priors, and to enable the use of very large field of view cameras, such as fisheye and catadioptric ones. Experimental evaluation on benchmark datasets shows that the algorithm is significantly faster than the state of the art while achieving highly competitive accuracy. Abstract-Direct methods for Visual Odometry (VO) have gained popularity due to their capability to exploit information from all intensity gradients in the image. However, low computational speed as well as missing guarantees for optimality and consistency are limiting factors of direct methods, where established feature-based methods instead succeed at. Based on these considerations, we propose a Semi-direct VO (SVO) that uses direct methods to track and triangulate pixels that are characterized by high image gradients but relies on proven feature-based methods for joint optimization of structure and motion. Together with a robust probabilistic depth estimation algorithm, this enables us to efficiently track pixels lying on weak corners and edges in environments with little or high-frequency texture. We further demonstrate that the algorithm can easily be extended to multiple cameras, to track edges, to include motion priors, and to enable the use of very large field of view cameras, such as fisheye and catadioptric ones. Experimental evaluation on benchmark datasets shows that the algorithm is significantly faster than the state of the art while achieving highly competitive accuracy.

Single zircons from two Early Cambrian volcanic horizons have been analysed using the SHRIMP ion microprobe. Full details of the analytical procedures and data reduction are given. Zircons from tuff within the Lie de Vin Formation, near Tiout, Morocco, show little spread in U-Pb age and have a mean value of 521 ± 7 Ma (2σ). Those from a bentonite within unit 5 of the Meishucun section near Kunming, southern China, show relatively dispersed U-Pb ages, revealing the presence of both detrital or xenocrystic grains as well as areas within grains that have lost radiogenic Pb. The main population has a mean age of 525 ± 7 Ma, but a mean 207 Pb/ 206 Pb age of 539 ± 34 Ma which is a maximum estimate for the bentonite age. These results conflict with previous Rb-Sr whole rock ages of c. 580 Ma for overlying Cambrian shales at Meishucun, and c. 570 Ma for Atdabanian shales from the E. Yangtse Gorges area.

The Permian-Triassic boundary records the most severe mass extinctions in Earth's history. Siberian flood volcanism, the most profuse known such subaerial event, produced 2 million to 3 million cubic kilometers of volcanic ejecta in approximately 1 million years or less. Analysis of (40)Ar/(39)Ar data from two tuffs in southern China yielded a date of 250.0 +/- 0.2 million years ago for the Permian-Triassic boundary, which is comparable to the inception of main stage Siberian flood volcanism at 250.0 +/- 0.3 million years ago. Volcanogenic sulfate aerosols and the dynamic effects of the Siberian plume likely contributed to environmental extrema that led to the mass extinctions.

In this tutorial, we provide principled methods to quantitatively evaluate the quality of an estimated trajectory from visual(-inertial) odometry (VO/VIO), which is the foundation of benchmarking the accuracy of different algorithms. First, we show how to determine the transformation type to use in trajectory alignment based on the specific sensing modality (i.e., monocular, stereo and visual-inertial). Second, we describe commonly used error metrics (i.e., the absolute trajectory error and the relative error) and their strengths and weaknesses. To make the methodology presented for VO/VIO applicable to other setups, we also generalize our formulation to any given sensing modality. To facilitate the reproducibility of related research, we publicly release our implementation of the methods described in this tutorial.