XPS研究中几种参数对CdS中Cd 3d结合能的影响

本文着重从仪器本身参数方面和样品方面讨论了由于各参数的不同，对电子结合能的影响。通过半导体ＣｄＳ膜的研究，探讨了Ｃｄ　３ｄ５／２，Ｃｄ　３ｄ３／２特征峰结合能的变化规律，分析了这种变化在测试中带来的影响。

Application of forecasting structural cracks technique of 3D move in Chengdao buried hill

3DMove software, based on the three-dimension structural model of geologic interpretation, can forecast reservoir cracks from the point of view of formation of the structural geology, and analyze the characteristics of the cracks. 3DMove software dominates in forecasting cracks. We forecast the developments and directions of the cracks in Chengbei buried hill with the application of forecasting technique in 3DMove software, and obtain the chart about strain distributing on top in buried hill and the chart about relative density and orientation and the chart about the analysis of crack unsealing. In Chengbei 30 buried hill zone, north-west and north-east and approximately east-west cracks in Cenozoic are very rich and the main directions in every fault block are different. Forecasting results that are also verified by those of drilling approximately accord with the data from well logging, the case of which shows that the technique has the better ability in forecasting cracks, and takes more effects on exploration and exploitation of crack reservoir beds in ancient buried hill reservoirs.

The manganese superoxide dismutase gene in bay scallop Argopecten irradians: Cloning, 3D modelling and mRNA expression

A novel manganese superoxide dismutase (MnSOD) was cloned from bay scallop Argopecten irradians by 3' and 5' rapid amplification of cDNA ends (RACE) PCR. The full-length cDNA of MnSOD was of 1207 bp with a 678 bp open reading frame encoding 226 amino acids. The deduced amino acid sequence contained a putative signal peptide of 26 amino acids. Sequence comparison showed that the MnSOD of A. irradians shared high identity with MnSOD in invertebrates and vertebrates, such as MnSOD from abalone Haliotis discus discus (ABG88843) and frog Xenopus laevis (AAQ63483). Furthermore, the 3D structure of bay scallop MnSOD was predicted by SWISS-MODEL Protein Modelling Server and compared with those of other MnSODs. The overall structure of bay scallop MnSOD was similar to those of zebrafish Danio rerio, fruit fly Drosophila melanogaster, Chinese shrimp Fenneropenaeus chinensis, human Homo sapiens, and had the highest similarity to scallop Mizuhopecten yessoensis and abalone H. discus discus. A quantitative real-time PCR (qRT-PCR) assay was developed to detect the mRNA expression of MnSOD in different tissues and the temporal expression in haemocytes following challenge with the bacterium Vibrio anguillarum. A higher-level of mRNA expression of MnSOD was detected in gill and mantle. The expression of MnSOD reached the highest level at 3 h post-injection with V. anguillarum and then slightly recovered from 6 to 48 h. The results indicated that bay scallop MnSOD was a constitutive and inducible protein and thus could play an important role in the immune responses against V anguillarum infection. (c) 2008 Elsevier Ltd. All rights reserved.

基于显微视觉的微纳尺度3D检测方法

微观尺度下的观测与操作是进行微纳米科学技术研究与实现、微纳米特性发现与利用、加工制造的重要技术手段。因此微纳米操作的关键技术问题主要包括两个方面：微纳米操作的观测成像，通过成像微纳米尺度下的物体可以被观测者所感知和观测；利用感知与观测信息指导微纳米尺度下机械操作控制。深度信息在计算机视觉的研究中占有着重要的地位，它使我们更好地理解现实世界中物体的3D关系。因此，利用深度信息实现3D测量逐渐被应用于微纳米操作的观测成像领域。工作域显微图像是唯一能反映被控目标体运动和位置的反馈信息，自然对象的深度信息也只能从此中获得。虽然很难自动地从这个平面图像中获得，但根据显微镜点扩散模型的光学特点，可以构造合理的模糊度判据，实现对象深度信息恢复。本文作者以微观尺度下的3D视觉观测与可视化为应用背景，通过分析几何光学成像中的各种成像规律。建立图像的模糊度判据，并利用该判据完成了微观尺度下的3D视觉观测与可视化。主要工作包括：（1）分析光学成像的基本原理，了解光学成像过程中聚焦和离焦成像现象发生条件和描述方法；分析图像清晰/模糊程度与景物深度变化之间的关系规律，进而给出基于光学图像信息的微观景物深度测量理论依据；（2）结合序列图像的清晰/模糊程度变化规律，分析不同测度算子对于清晰/模糊程度响应的灵敏度与适应性；提出建立适宜的模糊测度算子方法。（3）基于模糊测度算子和模糊化测度分布模型，提出建立微观尺度下的显微视觉图像与实际景物的模糊度-深度关系模型的获取实验方法。设计实验系统与实验方法，完成微观3D视觉观测；（4）通过基于模糊化测度的微观景物深度信息获取研究，提出微观景物的3D重建方法，实现微观尺度下的3D重建及其可视化方法，完成实验验证。本文就微纳米技术研究中的显微成像离焦现象进行了分析，给出了建立基于模糊测度的微米尺度下离焦度与景物深度信息关系的方法；分析了不同梯度算子所具有的不同模糊测度响应；并以实验验证了利用这种模糊测度可以对微观尺度下的景物进行深度信息获取,并且利用深度信息进行3D重建。

Direct Computation of 3D Shape Invariants and the Focus of Expansion

Structure from motion often refers to the computation of 3D structure from a matched sequence of images. However, a depth map of a surface is difficult to compute and may not be a good representation for storage and recognition. Given matched images, I will first show that the sign of the normal curvature in a given direction at a given point in the image can be computed from a simple difference of slopes of line-segments in one image. Using this result, local surface patches can be classified as convex, concave, parabolic (cylindrical), hyperbolic (saddle point) or planar. At the same time the translational component of the optical flow is obtained, from which the focus of expansion can be computed.

A Self-Organizing Multiple-View Representation of 3D Objects

We explore representation of 3D objects in which several distinct 2D views are stored for each object. We demonstrate the ability of a two-layer network of thresholded summation units to support such representations. Using unsupervised Hebbian relaxation, we trained the network to recognise ten objects from different viewpoints. The training process led to the emergence of compact representations of the specific input views. When tested on novel views of the same objects, the network exhibited a substantial generalisation capability. In simulated psychophysical experiments, the network's behavior was qualitatively similar to that of human subjects.

An Efficient Correspondence Based Algorithm for 2D and 3D Model Based Recognition

A polynomial time algorithm (pruned correspondence search, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image, is presented. Efficient verification algorithms, based on a linear representation of location constraints, are given for the case of affine transformations among vector spaces and for the case of rigid 2D and 3D transformations with scale. Some preliminary experiments suggest that PCS is a practical algorithm. Its similarity to existing correspondence based algorithms means that a number of existing techniques for speedup can be incorporated into PCS to improve its performance.

Distance Metric Between 3D Models and 3D Images for Recognition and Classification

Similarity measurements between 3D objects and 2D images are useful for the tasks of object recognition and classification. We distinguish between two types of similarity metrics: metrics computed in image-space (image metrics) and metrics computed in transformation-space (transformation metrics). Existing methods typically use image and the nearest view of the object. Example for such a measure is the Euclidean distance between feature points in the image and corresponding points in the nearest view. (Computing this measure is equivalent to solving the exterior orientation calibration problem.) In this paper we introduce a different type of metrics: transformation metrics. These metrics penalize for the deformatoins applied to the object to produce the observed image. We present a transformation metric that optimally penalizes for "affine deformations" under weak-perspective. A closed-form solution, together with the nearest view according to this metric, are derived. The metric is shown to be equivalent to the Euclidean image metric, in the sense that they bound each other from both above and below. For Euclidean image metric we offier a sub-optimal closed-form solution and an iterative scheme to compute the exact solution.

3D Pose from Three Corresponding Points Under Weak-Perspective Projection

Model-based object recognition commonly involves using a minimal set of matched model and image points to compute the pose of the model in image coordinates. Furthermore, recognition systems often rely on the "weak-perspective" imaging model in place of the perspective imaging model. This paper discusses computing the pose of a model from three corresponding points under weak-perspective projection. A new solution to the problem is proposed which, like previous solutins, involves solving a biquadratic equation. Here the biquadratic is motivate geometrically and its solutions, comprised of an actual and a false solution, are interpreted graphically. The final equations take a new form, which lead to a simple expression for the image position of any unmatched model point.

View-Based Models of 3D Object Recognition and Class-Specific Invariances

This paper describes the main features of a view-based model of object recognition. The model tries to capture general properties to be expected in a biological architecture for object recognition. The basic module is a regularization network in which each of the hidden units is broadly tuned to a specific view of the object to be recognized.

Relative Affine Structure: Canonical Model for 3D from 2D Geometry and Applications

We propose an affine framework for perspective views, captured by a single extremely simple equation based on a viewer-centered invariant we call "relative affine structure". Via a number of corollaries of our main results we show that our framework unifies previous work --- including Euclidean, projective and affine --- in a natural and simple way, and introduces new, extremely simple, algorithms for the tasks of reconstruction from multiple views, recognition by alignment, and certain image coding applications.

Inferring 3D Structure with a Statistical Image-Based Shape Model

We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure'' model. The 3D shape of a class of objects may be represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes can then be estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We augment the shape model to incorporate structural features of interest; novel examples with missing structure parameters may then be reconstructed to obtain estimates of these parameters. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a dataset of thousands of pedestrian images generated from a synthetic model, we can perform accurate inference of the 3D locations of 19 joints on the body based on observed silhouette contours from real images.