1,107 research outputs found
MODELLING THE ELECTRON WITH COSSERAT ELASTICITY
Interactions between a finite number of bodies and the surrounding fluid, in a channel for instance, are investigated theoretically. In the planar model here the bodies or modelled grains are thin solid bodies free to move in a nearly parallel formation within a quasi-inviscid fluid. The investigation involves numerical and analytical studies and comparisons. The three main features that appear are a linear instability about a state of uniform motion, a clashing of the bodies (or of a body with a side wall) within a finite scaled time when nonlinear interaction takes effect, and a continuum-limit description of the body–fluid interaction holding for the case of many bodies
Dynamic breakage and fragmentation of brittle single particle of various sizes and strength
2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Primary Care Workforce And Continuous Medical Education In China: Lessons To Learn From A Nationwide Cross-sectional Survey
published_or_final_versio
A Simple Method to Synthesize Cadmium Hydroxide Nanobelts
Cd(OH)2nanobelts have been synthesized in high yield by a convenient polyol method for the first time. XRD, XPS, FESEM, and TEM were used to characterize the product, which revealed that the product consisted of belt-like crystals about 40 nm in thickness and length up to several hundreds of micrometers. Studies found that the viscosity of the solvent has important influence on the morphology of the final products. The optical absorption spectrum indicates that the Cd(OH)2nanobelts have a direct band gap of 4.45 eV
Survey on Vision-based Path Prediction
Path prediction is a fundamental task for estimating how pedestrians or
vehicles are going to move in a scene. Because path prediction as a task of
computer vision uses video as input, various information used for prediction,
such as the environment surrounding the target and the internal state of the
target, need to be estimated from the video in addition to predicting paths.
Many prediction approaches that include understanding the environment and the
internal state have been proposed. In this survey, we systematically summarize
methods of path prediction that take video as input and and extract features
from the video. Moreover, we introduce datasets used to evaluate path
prediction methods quantitatively.Comment: DAPI 201
Oosorption in the Endoparasitoid, Pteromalus puparum
Oosorption is the resorption of oocytes in the ovaries, and is usually induced by environmental stress. It has been demonstrated in some insect species, but overall the mechanisms of oosorption are poorly understood. In this study, the oosorption in the endoparasitic wasp, Pteromalus puparum L. (Hymenoptera: Pteromalidae), was observed in response to starvation. To explore the details of oosorption in P. puparum, both levels of hemolymph vitellogenin and ovarian vitellin were determined using sandwich ELISA. The results indicated that both levels of vitellin and total protein in the ovaries were significantly decreased 48 h after eclosion in starved P. puparum, while those of vitellogenin and total protein in the hemolymph were increased. In addition, observation of the ultrastructure of mature oocytes in the ovarioles revealed changes in yolk protein content. Those protein yolk spheres and lipid yolk spheres that had accumulated in the oocytes, were transferred out of the oocytes of starved females. It was assumed that once oosorption was induced in P. puparum, vitellin in the oocytes was transported outside and released into the hemolymph. This information helps to elucidate a mechanism of oosorption in insects
Deep Markov Random Field for Image Modeling
Markov Random Fields (MRFs), a formulation widely used in generative image
modeling, have long been plagued by the lack of expressive power. This issue is
primarily due to the fact that conventional MRFs formulations tend to use
simplistic factors to capture local patterns. In this paper, we move beyond
such limitations, and propose a novel MRF model that uses fully-connected
neurons to express the complex interactions among pixels. Through theoretical
analysis, we reveal an inherent connection between this model and recurrent
neural networks, and thereon derive an approximated feed-forward network that
couples multiple RNNs along opposite directions. This formulation combines the
expressive power of deep neural networks and the cyclic dependency structure of
MRF in a unified model, bringing the modeling capability to a new level. The
feed-forward approximation also allows it to be efficiently learned from data.
Experimental results on a variety of low-level vision tasks show notable
improvement over state-of-the-arts.Comment: Accepted at ECCV 201
Changing the scattering of sheltered targets
Author name used in this publication: Lian-xing He2010-2011 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Flattening of conic reflectors via a transformation method
Author name used in this publication: He, Lian-Xing2011-2012 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
The one-sided inverse along an element in semigroups and rings
The concept of the inverse along an element was introduced by Mary in 2011. Later, Zhu et al. introduced the one-sided inverse along an element. In this paper, we first give a new existence criterion for the one-sided inverse along a product and characterize the existence of Moore–Penrose inverse by means of one-sided invertibility of certain element in a ring. In addition, we show that a∈ S † ⋂ S # if and only if (a∗a)k is invertible along a if and only if (aa∗)k is invertible along a in a ∗ -monoid S, where k is an arbitrary given positive integer. Finally, we prove that the inverse of a along aa ∗ coincides with the core inverse of a under the condition a∈ S { 1 , 4 } in a ∗ -monoid S.FCT - Fuel Cell Technologies Program(CXLX13-072)This research was supported by the National Natural Science Foundation
of China (No. 11371089), the Specialized Research Fund for the Doctoral Program of
Higher Education (No. 20120092110020), the Natural Science Foundation of Jiangsu Province
(No. BK20141327) and the Foundation of Graduate Innovation Program of Jiangsu Province
(No. KYZZ15-0049).info:eu-repo/semantics/publishedVersio
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