裂隙岩石中的地震速度:对Hudson理论的实验验证

由于裂缝或裂隙的存在,不同油气层和含水层中流体的流动得到加强。通过研究对储层中纵横波传播的影响后可对其进行检测。这种影响可通过一些理论(包括Hudson)来预测。虽然Hundon理论已用于计算裂缝密度,但这种理论预测仍未用分布有已知裂缝     

罩式退火炉的控制系统

茹尔克拉钢厂罩式退火炉由于应用于符合现代化工艺规范的仪表和分布式控制系统，而大大提高了产品的质量和产量，并使能耗显著降低。     

“发动”艺术

“艺术”、“设计”、“奥迪”,三个彼此独立却息息相关的名词。作为全球最强设计品牌之一的奥迪,在过去四十多年中,从未间断与全球顶级艺术和设计领域的亲密对话与无间合作。如今,奥迪已经成为全球诸多顶级艺术与设计活动及顶尖艺术家最亲密的合作伙伴,“跨界”更成为品牌对艺术与设计支持的独特标签。     

Dynamic proteome in enigmatic preeclampsia: an account of molecular mechanisms and biomarker discovery

The coevolution of genomics and proteomics has led to advancements in the field of diagnosis and molecular mechanisms of disease. Proteomics is now stepping into the field of obstetrics, where early diagnosis of pregnancy complication such as preeclampsia (PE) is imperative. PE is a multifactorial disease characterized by hypertension with proteinuria, which is a leading cause of maternal and neonatal morbidity and mortality occurring in 5-7% of pregnancies worldwide. This review discusses the probable molecular mechanisms that lead to PE and summarizes the proteomics research carried out in understanding the pathogenicity of PE, and for identifying the candidate biomarker for diagnosis of the disease.     

A neuron membrane mesh representation for visualization of electrophysiological simulations

We present a process to automatically generate three-dimensional mesh representations of the complex, arborized cell membrane surface of cortical neurons (the principal information processing cells of the brain) from nonuniform morphological measurements. Starting from manually sampled morphological points (3D points and diameters) from neurons in a brain slice preparation, we construct a polygonal mesh representation that realistically represents the continuous membrane surface, closely matching the original experimental data. A mapping between the original morphological points and the newly generated mesh enables simulations of electrophysiolgical activity to be visualized on this new membrane representation. We compare the new mesh representation with the state of the art and present a series of use cases and applications of this technique to visualize simulations of single neurons and networks of multiple neurons.     

A deformable surface model for real-time water drop animation

A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.     

Detection of sudden pedestrian crossings for driving assistance systems

In this paper, we study the problem of detecting sudden pedestrian crossings to assist drivers in avoiding accidents. This application has two major requirements: to detect crossing pedestrians as early as possible just as they enter the view of the car-mounted camera and to maintain a false alarm rate as low as possible for practical purposes. Although many current sliding-window-based approaches using various features and classification algorithms have been proposed for image-/video-based pedestrian detection, their performance in terms of accuracy and processing speed falls far short of practical application requirements. To address this problem, we propose a three-level coarse-to-fine video-based framework that detects partially visible pedestrians just as they enter the camera view, with low false alarm rate and high speed. The framework is tested on a new collection of high-resolution videos captured from a moving vehicle and yields a performance better than that of state-of-the-art pedestrian detection while running at a frame rate of 55 fps.