Search results for: Yu-Chen Luo
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9

Search results for: Yu-Chen Luo

9 Park Improvements in a High-Density City: Ecological, Social and Economy Concerns

Authors: Yuchen Niu, Liang Zhao, Fangfang Xie, Weiyu Liu

Abstract:

In the past decades, rapid urbanization in China has significantly promoted economic growth and caused a large number of environmental problems. In consideration of land resources shortage, high-density cities will become a common phenomenon in the future. How to improve the living environment under high density is a new challenge. Shenzhen is a typical high-density city, but also the forefront of China's development and reform area. This study selects 9 urban parks with different natural attributes in Shenzhen and explores the relationship of natural, economic, and social conditions within the service scope. Based on correlation analysis and system analysis, the results indicate that improvement of park design and management methods contribute to obtaining higher ecological value and promote economic and social development.

Keywords: correlation analysis, high-density city, park improvement, urban green spaces

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8 Antiviral Activity of Interleukin-11 in Response to Porcine Epidemic Diarrhea Virus Infection

Authors: Li Yuchen, Wu Qingxin, Jin Yuxing, Yang Qian

Abstract:

Interleukin-11 (IL-11), a well-known anti-inflammatory factor, helps to protect against intestinal epithelium damage caused by physical or chemical factors. However, little is known about the role of IL-11 during viral infection. Herein, high mRNA and protein levels of IL-11 were found in epithelial cells and jejunum of piglets during porcine epidemic diarrhea virus (PEDV) infection, and IL-11 expression was positively correlated with the level of viral infection. Pretreatment with recombinant porcine IL-11 (pIL-11) suppressed PEDV replication in Vero E6 cells, while IL-11 knockdown promoted viral infection. Furthermore, pIL-11 inhibited viral infection by preventing PEDV-mediated apoptosis of cells through activating the IL-11/STAT3 signal pathway. Conversely, application of a STAT3 phosphorylation inhibitor significantly antagonized the anti-apoptosis function of pIL-11 and counteracted its inhibition of PEDV. Our data suggested that that IL-11 is a novel PEDV-inducible cytokine, and its production enhances the anti-apoptosis ability of epithelial cells against PEDV infection. The potential uses of IL-11 as a novel therapeutic against devastating viral diarrhea in piglets deserves more attention and study.

Keywords: Interleukin-11, Porcine epidemic diarrhea virus, STAT3, anti-apoptosis

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7 An Alternative Framework of Multi-Resolution Nested Weighted Essentially Non-Oscillatory Schemes for Solving Euler Equations with Adaptive Order

Authors: Zhenming Wang, Jun Zhu, Yuchen Yang, Ning Zhao

Abstract:

In the present paper, an alternative framework is proposed to construct a class of finite difference multi-resolution nested weighted essentially non-oscillatory (WENO) schemes with an increasingly higher order of accuracy for solving inviscid Euler equations. These WENO schemes firstly obtain a set of reconstruction polynomials by a hierarchy of nested central spatial stencils, and then recursively achieve a higher order approximation through the lower-order precision WENO schemes. The linear weights of such WENO schemes can be set as any positive numbers with a requirement that their sum equals one and they will not pollute the optimal order of accuracy in smooth regions and could simultaneously suppress spurious oscillations near discontinuities. Numerical results obtained indicate that these alternative finite-difference multi-resolution nested WENO schemes with different accuracies are very robust with low dissipation and use as few reconstruction stencils as possible while maintaining the same efficiency, achieving the high-resolution property without any equivalent multi-resolution representation. Besides, its finite volume form is easier to implement in unstructured grids.

Keywords: finite-difference, WENO schemes, high order, inviscid Euler equations, multi-resolution

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6 Alcohols as a Phase Change Material with Excellent Thermal Storage Properties in Buildings

Authors: Dehong Li, Yuchen Chen, Alireza Kaboorani, Denis Rodrigue, Xiaodong (Alice) Wang

Abstract:

Utilizing solar energy for thermal energy storage has emerged as an appealing option for lowering the amount of energy that is consumed by buildings. Due to their high heat storage density, and non-corrosive and non-polluting properties, alcohols can be a good alternative to petroleum-derived paraffin phase change materials (PCMs). In this paper, ternary eutectic PCMs with suitable phase change temperatures were designed and prepared using lauryl alcohol (LA), cetyl alcohol (CA), stearyl alcohol (SA), and xylitol (X). The differential scanning calorimetry (DSC) results revealed that the phase change temperatures of LA-CA-SA, LA-CA-X, and LA-SA-X were 20.52°C, 20.37°C, and 22.18°C, respectively. The latent heat of phase change of the ternary eutectic PCMs was all stronger than that of the paraffinic PCMs at roughly the same temperature. The highest latent heat was 195 J/g. It had good thermal energy storage capacity. The preparation mechanism was investigated using Fourier-transform Infrared Spectroscopy (FTIR), and it was found that the ternary eutectic PCMs were only physically mixed among the components. Ternary eutectic PCMs had a simple preparation process, suitable phase change temperature, and high energy storage density. They are suitable for low-temperature architectural packaging applications.

Keywords: thermal energy storage, buildings, phase change materials, alcohols

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5 Hygrothermal Performance of Sheep Wool in Cold and Humid Climates

Authors: Yuchen Chen, Dehong Li, Bin Li, Denis Rodrigue, Xiaodong (Alice) Wang

Abstract:

When selecting insulation materials, not only should their thermal efficiency be considered, but also their impact on the environment. Compared to conventional insulation materials, bio-based materials not only have comparable thermal performance, but they also have a lower embodied energy. Sheep wool has the advantages of low negative health impact, high fire resistance, eco-friendliness, and high moisture resistance. However, studies on applying sheep wool insulation in cold and humid climates are still insufficient. The purpose of this study is to simulate the hygrothermal performance of sheep wool insulation for the Quebec City climate, as well as analyze the mold growth risks. The results show that a sheep wool wall has better thermal performance than a reference wall and that both meet the minimum requirements of the Quebec Code for the thermal performance of above-ground walls. The total water content indicates that the sheep wool wall can reach dynamic equilibrium in the Quebec climate and can dry out. At the same time, a delay of almost four months in the maximum total water content indicates that the sheep wool wall has high moisture absorption compared to the reference wall. The hygrothermal profiles show that the sheathing-insulation interface of both walls is at the highest risk for condensation. When the interior surface gypsum was replaced by stucco, the mold index significantly dropped.

Keywords: sheep wool, water content, hygrothermal performance, mould growth risk

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4 Parametric Models of Facade Designs of High-Rise Residential Buildings

Authors: Yuchen Sharon Sung, Yingjui Tseng

Abstract:

High-rise residential buildings have become the most mainstream housing pattern in the world’s metropolises under the current trend of urbanization. The facades of high-rise buildings are essential elements of the urban landscape. The skins of these facades are important media between the interior and exterior of high- rise buildings. It not only connects between users and environments, but also plays an important functional and aesthetic role. This research involves a study of skins of high-rise residential buildings using the methodology of shape grammar to find out the rules which determine the combinations of the facade patterns and analyze the patterns’ parameters using software Grasshopper. We chose a number of facades of high-rise residential buildings as source to discover the underlying rules and concepts of the generation of facade skins. This research also provides the rules that influence the composition of facade skins. The items of the facade skins, such as windows, balconies, walls, sun visors and metal grilles are treated as elements in the system of facade skins. The compositions of these elements will be categorized and described by logical rules; and the types of high-rise building facade skins will be modelled by Grasshopper. Then a variety of analyzed patterns can also be applied on other facade skins through this parametric mechanism. Using these patterns established in the models, researchers can analyze each single item to do more detail tests and architects can apply each of these items to construct their facades for other buildings through various combinations and permutations. The goal of these models is to develop a mechanism to generate prototypes in order to facilitate generation of various facade skins.

Keywords: facade skin, grasshopper, high-rise residential building, shape grammar

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3 Efficient Implementation of Finite Volume Multi-Resolution Weno Scheme on Adaptive Cartesian Grids

Authors: Yuchen Yang, Zhenming Wang, Jun Zhu, Ning Zhao

Abstract:

An easy-to-implement and robust finite volume multi-resolution Weighted Essentially Non-Oscillatory (WENO) scheme is proposed on adaptive cartesian grids in this paper. Such a multi-resolution WENO scheme is combined with the ghost cell immersed boundary method (IBM) and wall-function technique to solve Navier-Stokes equations. Unlike the k-exact finite volume WENO schemes which involve large amounts of extra storage, repeatedly solving the matrix generated in a least-square method or the process of calculating optimal linear weights on adaptive cartesian grids, the present methodology only adds very small overhead and can be easily implemented in existing edge-based computational fluid dynamics (CFD) codes with minor modifications. Also, the linear weights of this adaptive finite volume multi-resolution WENO scheme can be any positive numbers on condition that their sum is one. It is a way of bypassing the calculation of the optimal linear weights and such a multi-resolution WENO scheme avoids dealing with the negative linear weights on adaptive cartesian grids. Some benchmark viscous problems are numerical solved to show the efficiency and good performance of this adaptive multi-resolution WENO scheme. Compared with a second-order edge-based method, the presented method can be implemented into an adaptive cartesian grid with slight modification for big Reynolds number problems.

Keywords: adaptive mesh refinement method, finite volume multi-resolution WENO scheme, immersed boundary method, wall-function technique.

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2 The Role of the Gut Microbiome of Marine Invertebrates in the Degradation of Complex Algal Substrates

Authors: Yuchen LI, Martyn Kurr, Peter Golyshin

Abstract:

Biological invasion is a global problem. Invasive species can threaten local ecosystems by competing for resources, consuming local species, and reproducing faster than natives. Sargassum muticum is an invasive algae in the UK. It negatively impacts local algae through overshading and can cause reductions in local biodiversity. One possibility for its success is herbivore release. According to the Enemy Release Hypothesis, invasives are less impacted by local herbivores than natives. In many species, gastrointestinal (GI) tract microbes have been found as a key factor in food preference and similar mechanisms may exist in the relationship between local consumers and S. muticum. Some populations of native Littorina snails accept S. muticum as a food source, while others avoid it. This project aims to establish the relationship between GI tract microbes and the feeding preferences of L. littorea, when offered both native algae and S. muticum. Individuals of L. littorea from a site invaded by S. muticum around 18 years ago were compared to those from an un-invaded site nearby. Sargassum-experienced snails are more likely to consume it than those naïve, and pronounced differences were found in the GI-tract microbial communities through 16S (prokaryote) and 18S (eukaryote) sequencing. Sargassum-naïve snails were then exposed to a faecal pellets from experienced snails to ‘inoculate’ them with microbes from the exposed snails. Preliminary results suggest these faecal-pellet-exposed but otherwise Sargassum-naïve snails subsequently begun consuming S. muticum. It is unclear if these results are due to genuine changes in GI-tract microbes or through some other mechanism, such as behavioural responses to chemical cues in the faecal pellets, but these results are nevertheless of significance for invasive ecology, suggesting that foraging preferences for an invasive prey type are malleable and possibly programmable in laboratory settings.

Keywords: invasive algae, sea snails, gut microbiome, biocontrol

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1 Vehicle Timing Motion Detection Based on Multi-Dimensional Dynamic Detection Network

Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

Abstract:

Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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