An Implementation of Fully Convolutional Network for Surface Mesh Segmentation

This thesis presents an implementation of a 3-Dimensional triangular surface mesh segmentation architecture named Shape Fully Convolutional Network, which is proposed by Pengyu Wang and Yuan Gan in 2018. They designed a deep neural network that has a similar architecture as the Fully Convolutional Network, which provides a good segmentation result for 2D images, on 3D triangular surface meshes. In their implementation, 3D surface meshes are represented as graph structures to feed the network. There are three main barriers when applying the Fully Convolutional Network to graph-based data structures. • First, the pooling operation is much harder to apply to general graphs. • Second, the convolution order on a graph structure is unstable. • Third, the raw data of surface meshes cannot be directly applied to the network. To solve these problems, first, all the nodes inside the graph are re-ordered into a 1-dimensional list based on a multi-level graph coarsening algorithm, which allows the pooling operation to be applied as easily as a 1D pooling. Second, a self-defined generating layer is added before each convolution layer in the network to generate the neighbors of each node on the graph, and at the same time, sort all neighbors based on the L2 similarity to keep the convolution operation in a stable manner. Finally, three translation and rotation free low-level geometric features are pre-processed and used as input to train the network. This Shape Fully Convolution Network can effectively learn and predict triangular face-wise labels. In the end, to achieve a better result, the final labeling is optimized by the multi-label graph cut algorithm, which gives punishment to the predicted result based on the smoothness of the surface. The experiments show that the model can effectively learn and predict triangle-wise labels on surface meshes and yields good segmentation results

Integrated Image and Location Analysis for Wound Classification: A Deep Learning Approach

The global burden of acute and chronic wounds presents a compelling case for enhancing wound classification methods, a vital step in diagnosing and determining optimal treatments. Recognizing this need, we introduce an innovative multi-modal network based on a deep convolutional neural network for categorizing wounds into four categories: diabetic, pressure, surgical, and venous ulcers. Our multi-modal network uses wound images and their corresponding body locations for more precise classification. A unique aspect of our methodology is incorporating a body map system that facilitates accurate wound location tagging, improving upon traditional wound image classification techniques. A distinctive feature of our approach is the integration of models such as VGG16, ResNet152, and EfficientNet within a novel architecture. This architecture includes elements like spatial and channel-wise Squeeze-and-Excitation modules, Axial Attention, and an Adaptive Gated Multi-Layer Perceptron, providing a robust foundation for classification. Our multi-modal network was trained and evaluated on two distinct datasets comprising relevant images and corresponding location information. Notably, our proposed network outperformed traditional methods, reaching an accuracy range of 74.79% to 100% for Region of Interest (ROI) without location classifications, 73.98% to 100% for ROI with location classifications, and 78.10% to 100% for whole image classifications. This marks a significant enhancement over previously reported performance metrics in the literature. Our results indicate the potential of our multi-modal network as an effective decision-support tool for wound image classification, paving the way for its application in various clinical contexts

Experimental study on working capacity of carbon canister based on Euro VI

In order to study the gasoline working capacity and durability of the carbon canister, the gasoline working capacity test of the carbon canister was conducted under different test conditions. The results showed that the gasoline working capacity of the canister carbon decreased with the increase of fuel vapor loading rate. The fuel vapor volume ratio of the inlet has little effect on the gasoline working capacity. After 300 gasoline working capacity test cycles, the working capacity of butane decreased by about 20%. The fuel vapor adsorption amount in first cycle of each carbon canister is far greater than the desorption amount in first cycle, and also far greater than the adsorption and desorption amount in the subsequent cycles, which indicated that a large amount of fuel vapor occupied the active sites after the first use of the carbon canister and cannot desorb

Energy Charge as an Indicator of Pexophagy in Pichia pastoris

Pichia pastoris is a good model for pexophagy research owing to its diverse pexophagy modes (macropexophagy and micropexophagy) exhibited during carbon-source shift from methanol to other carbon sources. The critical condition that triggers activation of macropexophagy and micropexophagy is important for clarifying the P. pastoris pexophagy mechanism and human peroxisomal disorders. In this study, the pexophagy modes of P. pastoris were confirmed by green fluorescent protein expression and alcohol oxidase and formate dehydrogenase activities. Furthermore, intracellular energy charge (EC) was found to be a determinant of pexophagy activation. During methanol induction, the EC was about 0.5. And the final EC value was related to the pexophagy mode when carbon source switched from methanol to others. Macropexophagy and micropexophagy occurred when the EC increased to 0.6–0.75 and above 0.75, respectively. Thus, different EC values were considered as the important factor to trigger different pexophagy modes in P. pastoris. The results obtained in this study could help in achieving better control of the pexophagy modes to study the pexophagy mechanism

Preparation and Applications of Rare-Earth-Doped Ferroelectric Oxides

Ferroelectric oxides possess abundant fascinating physical functionalities, such as electro-optic, acousto-optic, and nonlinear optical characteristics, etc. However, most pristine ferroelectric oxides exhibit no efficient luminescent properties due to the indirect and wide bandgap. Rare-earth-doped phosphors demonstrate advantages such as sharp emission bandwidths, large Stokes shift, high photonstability, and low toxicity. The combination of rare-earth ions and ferroelectric oxides has shown great potential in optical sensing, lighting, solar cells, and other applications. Rare-earth-doped ferroelectric oxides exhibit efficient upconversion or downconversion luminescence in the range of ultraviolet (UV) to near-infrared (NIR) regions. In this article, the preparation process of rare-earth-doped ferroelectric oxides and the preparation methods of thin films are introduced. Their recent applications in optical sensing, lighting, and solar cells are highlighted. The review concludes with a brief summary of all related branches and discusses the potential direction of this field

Analysis on the progress of evaporative emission (type IV) standards for light-duty vehicles in China

This paper briefly introduces the progress of evaporative emission standards for light-duty vehicles in developed countries such as the United States and Europe, and the test procedures specified in the latest evaporative emission standard were concluded. Moreover, the development of evaporative emission standards for light-duty vehicles in China was comparatively analyzed. The evaporative emission test data from 2004 to 2019 was randomly selected for analysis of the trend of evaporative emission performance of vehicles in China with the use of EPR. Affected by the more stringent China 6 Evaporative Emissions standards issued in 2016, the EPR value of the evaporative emission test conducted according to the China 5 had continuously decreased to 41% in 2018. Subsequently, the EPR value increased again to a value of 60% in 2018 and 2019 due to strengthen of the emission limit from 2g to 0.7g and the raise of deterioration factor. Finally, based on the world's latest evaporative emission standards, the development trend of evaporative emission standards for light-duty vehicles in China is forecasted. The application of canister bench aging test, BETP, running loss emission test, and a test cycle with Chinese characteristics may be more conducive to control the light-duty vehicle emissions. Compared with the LEV 3, the evaporative emission limit of 0.7g/test specified in China 6 is still relatively larger. In addition, strengthen the control of durability test and in-use emission performance test would makes the HC emission less during the actual operation of the vehicle

Studied on the effect of refueling rate on fuel system refueling based on STAR-CCM+

A model of fuel system which is with ORVR is established based on STAR CCM +, to study the influence of different refueling velocity on the formation of liquid seal in refueling process. The simulation results show that the increase of refueling rate leads to the formation of liquid seal in the process of fuel flow, but it will lead to the deterioration of refueling smoothness. When the refueling rate is 15L/min, there is no liquid seal formed at the bottom of the refueling pipe, because of the small gas resistance formed in the refueling process, and when the refueling flow rate reaches 37L/min, a stable dynamic liquid seal can be formed at the bottom of the refueling pipe but the fuel accumulation at the refueling port has taken place. When the refueling flow rate reaches40L/min and 45L/min, a stable dynamic liquid seal is formed at the bottom of the refueling pipe at 4s, but until 4 seconds, fuel has been submerged in the refueling muzzle. At 10 seconds, the fuel accumulation state is the same as 5 seconds, indicating that the gun PSO had taken happened

Controls on Organic Matter Accumulation from an Upper Slope Section on the Early Cambrian Yangtze Platform, South China

The early Cambrian witnessed profound environmental changes and biological evolution in Earth’ history. During this period, organic-rich shales were widely distributed over almost the entire Yangtze Block. However, the dominant factor that drove the significant accumulation of organic matter (OM) remains controversial and is still debated. Here, we analyzed TOC, organic carbon isotopes, iron speciation, major and trace elements for the lower Cambrian Niutitang Formation in the upper slope Meiziwan section, to investigate the dominant factor controlling OM accumulation. High contents of TOC and Baxs reveal an OM-enriched feature of the Niutitang Formation, and the coupled relationship between them suggest a strong production control on OM accumulation at Meiziwan. Meanwhile, negative relationships between TOC and chemical index of alteration (CIA) values as well as Al contents suggest that influence of chemical weathering and terrestrial input on OM accumulation were limited. Fairly low CoEF × MnEF values provide strong evidence that the deposition of organic-rich shales was under the control of oceanic upwelling event. The upwelling event would bring nutrient-rich deep waters into surface water, stimulating phytoplankton bloom and primary productivity in surface water and facilitating OM enrichment. Meanwhile, enhanced accumulation of OM would have promoted subsequent bacterial sulfate reduction, leading to the occurrence of occasional euxinia (evidenced by iron speciation and redox-sensitive trace element data) and promoting preservation of OM. Taken together, our results shed light on the critical role of oceanic upwelling on the marine primary productivity on the earliest Cambrian Yangtze Platform