High-resolution imaging of two bipolar proto-planetary nebulae

Sub-arcsecond resolution V and I images have been obtained for two proto-planetary nebulae. Both are found to show a definite bipolar morphology. A circumstellar disk is clearly seen in the V - I color image, suggesting that the bipolar lobes are due to starlight scattered into the polar openings. This indicates that bipolar morphologies develop early in the evolution of planetary nebulae, even before the onset of photoionization. © 1996. The American Astronomical Society. All rights reserved.published_or_final_versio

Digit-only sauropod pes trackways from China - evidence of swimming or a preservational phenomenon?

For more than 70 years unusual sauropod trackways have played a pivotal role in debates about the swimming ability of sauropods. Most claims that sauropods could swim have been based on manus-only or manus-dominated trackways. However none of these incomplete trackways has been entirely convincing, and most have proved to be taphonomic artifacts, either undertracks or the result of differential depth of penetration of manus and pes tracks, but otherwise showed the typical pattern of normal walking trackways. Here we report an assemblage of unusual sauropod tracks from the Lower Cretaceous Hekou Group of Gansu Province, northern China, characterized by the preservation of only the pes claw traces, that we interpret as having been left by walking, not buoyant or swimming, individuals. They are interpreted as the result of animals moving on a soft mud-silt substrate, projecting their claws deeply to register their traces on an underlying sand layer where they gained more grip during progression. Other sauropod walking trackways on the same surface with both pes and manus traces preserved, were probably left earlier on relatively firm substrates that predated the deposition of soft mud and silt . Presently, there is no convincing evidence of swimming sauropods from their trackways, which is not to say that sauropods did not swim at all

Learning with Biased Complementary Labels

In this paper, we study the classification problem in which we have access to easily obtainable surrogate for true labels, namely complementary labels, which specify classes that observations do \textbf{not} belong to. Let $Y$ and $\bar{Y}$ be the true and complementary labels, respectively. We first model the annotation of complementary labels via transition probabilities $P(\bar{Y}=i|Y=j), i\neq j\in\{1,\cdots,c\}$, where $c$ is the number of classes. Previous methods implicitly assume that $P(\bar{Y}=i|Y=j), \forall i\neq j$, are identical, which is not true in practice because humans are biased toward their own experience. For example, as shown in Figure 1, if an annotator is more familiar with monkeys than prairie dogs when providing complementary labels for meerkats, she is more likely to employ "monkey" as a complementary label. We therefore reason that the transition probabilities will be different. In this paper, we propose a framework that contributes three main innovations to learning with \textbf{biased} complementary labels: (1) It estimates transition probabilities with no bias. (2) It provides a general method to modify traditional loss functions and extends standard deep neural network classifiers to learn with biased complementary labels. (3) It theoretically ensures that the classifier learned with complementary labels converges to the optimal one learned with true labels. Comprehensive experiments on several benchmark datasets validate the superiority of our method to current state-of-the-art methods.Comment: ECCV 2018 Ora

Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy

Augmenting X-ray imaging with 3D roadmap to improve guidance is a common strategy. Such approaches benefit from automated analysis of the X-ray images, such as the automatic detection and tracking of instruments. In this paper, we propose a real-time method to segment the catheter and guidewire in 2D X-ray fluoroscopic sequences. The method is based on deep convolutional neural networks. The network takes as input the current image and the three previous ones, and segments the catheter and guidewire in the current image. Subsequently, a centerline model of the catheter is constructed from the segmented image. A small set of annotated data combined with data augmentation is used to train the network. We trained the method on images from 182 X-ray sequences from 23 different interventions. On a testing set with images of 55 X-ray sequences from 5 other interventions, a median centerline distance error of 0.2 mm and a median tip distance error of 0.9 mm was obtained. The segmentation of the instruments in 2D X-ray sequences is performed in a real-time fully-automatic manner.Comment: Accepted to MICCAI 201

Dynamic contrast-enhanced MRI of primary rectal cancer at 3T: correlation with positron emission tomography

postprintThe 2010 Joint Annual Meeting of ISMRM-ESMRMB, Stockholm, Sweden, 1-7 May 2010

Quantitative analysis of indexes from DWI and PET/CT in primary rectal cancer

postprintThe Joint Annual Scientific Meeting of ISMRM-ESMRMB, Stockholm, Sweden, 1-7 May 2010

STEM materials: a new frontier for an intelligent sustainable world

Materials are addressed as possible enablers for solutions to many global societal challenges. A foresight exercise has been conducted to identify research paths to design, with a new approach, a generation of materials which can provide multi-functionalities. These material systems have been named ???stem???, in analogy to living cells where a base of primitive units can be designed and assembled for self-reacting to external inputs. These materials will embed a concept of ???internet in things???, where their processing capacity will enable the systems to interact with the environment and express diverse functionalities. Stem materials do not exist yet, but many clues from diferent theoretical and experimental results suggest they can be developed, and because living organisms exist. This article aims at launching this new approach and promoting the structuring of a multi-disciplinary community to fll the research gaps

Comparison of DWIBS and 18F-FDG PET/CT in newly diagnosed lymphoma

postprintThe 2010 Joint Annual Meeting of ISMRM-ESMRMB, Stockholm, Sweden, 1-7 May 2010

Quantitative assessment of diffusion-weighted MR imaging in patients with primary rectal cancer: Correlation with FDG-PET/CT

Purpose: The aim of the study was to assess correlations between parameters on diffusionweighted imaging and 2-deoxy-2-[ 18F]fluoro-D-glucose- positron emission tomography/computed tomography (FDG-PET/CT) in rectal cancer. Procedures: Thirty-three consecutive patients with pathologically confirmed rectal adenocarcinoma were included in this study. Apparent diffusion coefficient (ADC) maps were generated to calculate ADC mean (average ADC), ADC min (lowest ADC), tumor volume, and total diffusivity index (TDI). PET/CT exams were performed within 1 week of magnetic resonance imaging. Standardized uptake values (SUVs) were normalized to the injected FDG dose and body weight. SUV max (maximum SUV), SUV mean (average SUV), tumor volume, and total lesion glycolysis (TLG) were calculated using a 50% threshold. Results: Significant negative correlations were found between ADC min and SUV max (r=-0.450, p=0.009), and between ADC mean and SUV mean (r=-0.402, p=0.020). A significant positive correlation was found between TDI and TLG (r=0.634, p<0.001). Conclusion: The significant negative correlations between ADC and SUV suggest an association between tumor cellularity and metabolic activity in primary rectal adenocarcinoma. © Academy of Molecular Imaging and Society for Molecular Imaging, 2010.published_or_final_versionSpringer Open Choice, 21 Feb 201

Dual-gated bilayer graphene hot electron bolometer

Detection of infrared light is central to diverse applications in security, medicine, astronomy, materials science, and biology. Often different materials and detection mechanisms are employed to optimize performance in different spectral ranges. Graphene is a unique material with strong, nearly frequency-independent light-matter interaction from far infrared to ultraviolet, with potential for broadband photonics applications. Moreover, graphene's small electron-phonon coupling suggests that hot-electron effects may be exploited at relatively high temperatures for fast and highly sensitive detectors in which light energy heats only the small-specific-heat electronic system. Here we demonstrate such a hot-electron bolometer using bilayer graphene that is dual-gated to create a tunable bandgap and electron-temperature-dependent conductivity. The measured large electron-phonon heat resistance is in good agreement with theoretical estimates in magnitude and temperature dependence, and enables our graphene bolometer operating at a temperature of 5 K to have a low noise equivalent power (33 fW/Hz1/2). We employ a pump-probe technique to directly measure the intrinsic speed of our device, >1 GHz at 10 K.Comment: 5 figure