Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

A survey on deep learning in medical image analysis

This article is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component individuallyq We prove that under some suitable assumptions, it is possible to recover both the low-rank and the sparse components exactly by solving a very convenient convex program called Principal Component Pursuit; among all feasible decompositions, simply minimize a weighted combination of the nuclear norm and of the e1 norm. This suggests the possibility of a principled approach to robust principal component analysis since our methodology and results assert that one can recover the principal components of a data matrix even though a positive fraction of its entries are arbitrarily corrupted. This extends to the situation where a fraction of the entries are missing as well. We discuss an algorithm for solving this optimization problem, and present applications in the area of video surveillance, where our methodology allows for the detection of objects in a cluttered background, and in the area of face recognition, where it offers a principled way of removing shadows and specularities in images of faces.

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Robust principal component analysis

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models pre-trained from natural image dataset to medical image tasks. In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computer-aided detection (CADe) problems, namely thoraco-abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation, CNN model analysis and valuable insights can be extended to the design of high performance CAD systems for other medical imaging tasks.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

Images containing faces are essential to intelligent vision-based human-computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face, regardless of its 3D position, orientation and lighting conditions. Such a problem is challenging because faces are non-rigid and have a high degree of variability in size, shape, color and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research.

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Detecting faces in images: a survey

Both experimental method and numerical method are used to analyze the large variation in the material ductility of high pressure die casting (HPDC) Aural-2 alloy in the present work. The X-ray tomography (XRT) technique is used to characterize and reveal the significant variation of the internal porosity for the investigated material. The Mises plasticity model in conjunction with a mixed Swift-Voce hardening law, and a stress state dependent fracture initiation criterion are used to accurately describe the deformation response of the material. Very good agreement with the experimental results is obtained in the predicted average force-displacement responses for the calibrated stress states. A probabilistic damage mechanics model is put forward to depict the apparent stochastic ductile fracture behavior over a wide range of stress states. The 5th and 95th percentiles of the fracture initiation locus are recalibrated based on the proposed probabilistic ductile fracture model, which could provide an almost perfect prediction of the maximum and minimum bounds of force-displacement curves.

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Combined Probabilistic Approach and Stress State Dependency on the Failure Modeling of HPDC Aural-2 Alloy

The present invention provides multilayer films, packages formed from such films, and methods of making multilayer films. In one aspect, a multilayer film comprises multilayer film comprising at least 3 layers, each layer having opposing facial surfaces and arranged in the order A/B/C, wherein Layer A comprises a high density polyethylene having a M w,cc /M n,cc of at least 6.0, a M z,abs of at least 500,000 grams/mol as measured by triple detector GPC, and a density of 0.957 - 0.970 g/cm 3 , wherein the high density polyethylene comprises at least 90 percent by weight of Layer A; Layer B comprises a gas permeation layer, wherein a top facial surface of Layer B is in adhering contact with a bottom facial surface of Layer A; and Layer C comprises a high density polyethylene having a M w,cc /M n,cc of at least 6.0, a M z,abs of at least 500,000 grams/mol as measured by triple detector GPC, and a density of 0.957 - 0.970 g/cm 3 , wherein the high density polyethylene comprises at least 90 percent by weight of Layer C and wherein a top facial surface of Layer C is in adhering contact with a bottom facial surface of Layer B, wherein the film is oriented in the machine direction and wherein the film exhibits a normalized carbon dioxide transmission rate of at least 3000 cm 3 •mil/100 in 2 /day when measured according to ASTM F-2476 at 23 °C, 0% relative humidity, and 1 atm, and wherein the film exhibits a ratio of the carbon dioxide transmission rate to an oxygen transmission rate of at least 4.0, when the oxygen transmission rate is measured according to ASTM D3985 at 23 °C, 0% relative humidity, and 1 atm.

Multilayer films, articles comprising the same, methods of manufacturing multilayer films

In order to improve the efficiency of New Generation intelligent substation transformation and expansion, the overall design scheme of the secondary simulation automatic test system of intelligent substation, as well as the key technologies and key functions of the system is introduced. The design and implementation methods of three functional modules of intelligent terminal simulation, merged unit simulation and automatic closed-loop test are expounded. The research results have been applied in several substations.

Design and Implementation of New Generation Substation Secondary Simulation Automatic Test System

Ozone micro-bubble aeration using the ceramic ultrafiltration membrane with superior oxidation performance for 2, 4-D elimination.

Objective Design a new cross-linked polyethylene (XLPE) insulation material without cross-linking by-products (an alternative to peroxide cross-linking). Investigate the process of covalent bonds forming and reaction mechanism of four reaction systems. Method Theoretical calculation of the reaction potential energy information of the eleven reaction channels is used density functional theory at B3LYP/6-311+G(d,p) level. Results The calculation results show that the epoxy and reactive functional groups between two poly-ethylene copolymers can react in situ, form covalent bonds, and realize a network XLPE. This reaction process is cross-linking byproduct-free. The reactivity of carboxylic acid functional group is stronger among four reaction systems considered. Discussion The reaction Gibbs energy barriers of synergistic reaction are lower than that of step by step reaction. The reaction channel of attacking tertiary carbon site CH on epoxy is more kinetically favorable than that of attacking secondary carbon site CH2 on epoxy. Conclusion The cross-linking of epoxy and reactive functional groups between two polyethylene copolymers in situ would be beneficial to avoid forming cross-linking byproducts of peroxide cross-linking process, which is a promising method for design thermoplastic insulation materials for power cables. 

Theoretical study on the reaction mechanism of a new
 XLPE
 insulation material without cross‐linking byproducts: An alternative to peroxide cross‐linking

Weimin Huang

Papers

Combined Probabilistic Approach and Stress State Dependency on the Failure Modeling of HPDC Aural-2 Alloy

Multilayer films, articles comprising the same, methods of manufacturing multilayer films

Design and Implementation of New Generation Substation Secondary Simulation Automatic Test System

Ozone micro-bubble aeration using the ceramic ultrafiltration membrane with superior oxidation performance for 2, 4-D elimination.

Theoretical study on the reaction mechanism of a new XLPE insulation material without cross‐linking byproducts: An alternative to peroxide cross‐linking