Search results for: Xiaobo Liu

Authors: Norita Ahmad, Reza Barkhi, Xiaobo Xu

Abstract:

We design an experimental study to learn about the cognitive implications of the use of avatars in a Virtual World (VW) (i.e., Second Life). The results support our proposed model, where a positive flow experience with VW influences the attitude towards VW, in turn influencing intention to use VW. Furthermore, VW flow experience can itself be impacted by perceived peer influence, familiarity with VW, and personality of the individuals behind the avatars in VW.

Keywords: avatar, flow experience, personality type, second life, virtual world

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Authors: Qiao Fan, Xiaobo Guo, Junxian Zhu, Xiaohu Ding, Ching-Yu Cheng, Tien-Yin Wong, Mingguang He, Heping Zhang, Xueqin Wang

Abstract:

A systematic, simultaneous analysis of multiple phenotypes in genome-wide association studies (GWASs) draws a great attention to integrate the signals from single phenotypes with increased power. However, lacking an interpretable and efficient multivariate GWAS analysis impede the application of such approach. In this study, we propose to decompose the multivariate model into a series of simple univariate models. This transformation illuminates what exactly the individual trait contributes to the significant signals from the multivariate analyses. By employing our approach in the analysis of three myopia-related endophenotypes from the Singapore Malay Eye Study (SIMES), we identify novel candidate loci which were successfully validated in an independent Guangzhou Twin Eye Study (GTES).

Keywords: GWAS multivariate, multiple traits, myopia, association

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Authors: Xiaobo Xi, Ruihong Zhang

Abstract:

At present, the orchard ditching and fertilizing technology has a series of problems, such as easy tree roots damage, high energy consumption and uneven fertilizing. In this paper, a gas explosion subsoiling and fertilizer injection machine was designed, which used high pressure gas to shock soil body and then injected fertilizer. The drill pipe mechanism with pneumatic chipping hammer excitation and hydraulic assistance was designed to drill the soil. The operation of gas and liquid fertilizer supply was controlled by PLC system. The 3D model of the whole machine was established by using SolidWorks software. The machine prototype was produced, and field experiments were carried out. The results showed that soil fractures were created and diffused by gas explosion, and the subsoiling effect radius reached 40 cm under the condition of 0.8 MPa gas pressure and 30 cm drilling depth. What’s more, the work efficiency is 0.048 hm²/h at least. This machine could meet the agronomic requirements of orchard, garden and city greening fertilization, and the tree roots were not easily damaged and the fertilizer evenly distributed, which was conducive to nutrient absorption of root growth.

Keywords: gas explosion subsoiling, fertigation, pneumatic chipping hammer exciting, soil compaction

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

Abstract:

Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Xiaobo Wang, Zhen-Yu Chen

Abstract:

Higher plasma total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) are independent risk factors of cardiovascular disease while high-density lipoprotein cholesterol (HDL-C) is protective. Vitamin D is well-known for its regulatory role in calcium homeostasis. Its potential important role in cardiovascular disease has recently attracted much attention. This study was conducted to investigate effects of different dosage of calcitriol on plasma lipoprotein profile and the underlying mechanism. Sixty male Syrian Golden hamsters were randomly divided into 6 groups: no-cholesterol control (NCD), high-cholesterol control (HCD), groups with calcitriol supplementation at 10/20/40/80ng/kg body weight (CA, CB, CC, CD), respectively. Calcitriol in medium-chain triacylglycerol (MCT) oil was delivered to four experimental groups via oral gavage every other day, while NCD and HCD received MCT oil in the equivalent amount. NCD hamsters were fed with non-cholesterol diet while other five groups were maintained on diet containing 0.2% cholesterol to induce a hypercholesterolemic condition. The treatment lasts for 6 weeks followed by sample collection after hamsters sacrificed. Four experimental groups experienced a reduction in average food intake around 11% compared to HCD with slight decrease in body weight (not exceeding 10%). This reduction reflects on the deceased relative weights of testis, epididymal and perirenal adipose tissue in a dose-dependent manner. Plasma calcitriol levels were measured and was corresponding to oral gavage. At the end of week 6, lipoprotein profiles were improved with calcitriol supplementation with TC, non-HDL-C and plasma triglyceride (TG) decreased in a dose-dependent manner (TC: r=0.373, p=0.009, non-HDL-C: r=0.479, p=0.001, TG: r=0.405, p=0.004). Since HDL-C of four experiment groups showed no significant difference compared to HCD, the ratio of nHDL-C to HDL-C and HDL-C to TC had been restored in a dose-dependent manner. For hamsters receiving the highest level of calcitriol (80ng/kg) showed a reduction of TC by 11.5%, nHDL-C by 24.1% and TG by 31.25%. Little difference was found among six groups on the acetylcholine-induced endothelium-dependent relaxation or contraction of thoracic aorta. To summarize, calcitriol supplementation in hamster at maximum 80ng/kg body weight for 6 weeks lead to an overall improvement in plasma lipoprotein profile with decreased TC and TG level. The molecular mechanism of its effects is under investigation.

Keywords: cholesterol, vitamin D, calcitriol, hamster

Procedia PDF Downloads 236

Authors: Xiaobo Rui, Zhoumo Zeng, Yibo Li

Abstract:

A novel tri-cantilever energy harvester with magnetic oscillator was presented, which could convert the ambient vibration into electrical energy to power the low-power devices such as wireless sensor networks. The most common way to harvest vibration energy is based on the use of linear resonant devices such as cantilever beam, since this structure creates the highest strain for a given force. The highest efficiency will be achieved when the resonance frequency of the harvester matches the vibration frequency. The limitation of the structure is the narrow effective bandwidth. To overcome this limitation, this article introduces a broadband tri-cantilever harvester with nonlinear stiffness. This energy harvester typically consists of three thin cantilever beams vertically arranged with Neodymium Magnets ( NdFeB)magnetics at its free end and a fixed base at the other end. The three cantilevers have different resonant frequencies by designed in different thicknesses. It is obviously that a similar advantage of multiple resonant frequencies as piezoelectric cantilevers array structure is built. To achieve broadband energy harvesting, magnetic interaction is used to introduce the nonlinear system stiffness to tune the resonant frequency to match the excitation. Since the three cantilever tips are all free and the magnetic force is distance dependent, the resonant frequencies will be complexly changed with the vertical vibration of the free end. Both model and experiment are built. The electromechanically coupled lumped-parameter model is presented. An electromechanical formulation and analytical expressions for the coupled nonlinear vibration response and voltage response are given. The entire structure is fabricated and mechanically attached to a electromagnetic shaker as a vibrating body via the fixed base, in order to couple the vibrations to the cantilever. The cantilevers are bonded with piezoelectric macro-fiber composite (MFC) materials (Model: M8514P2). The size of the cantilevers is 120*20mm2 and the thicknesses are separately 1mm, 0.8mm, 0.6mm. The prototype generator has a measured performance of 160.98 mW effective electrical power and 7.93 DC output voltage via the excitation level of 10m/s2. The 130% increase in the operating bandwidth is achieved. This device is promising to support low-power devices, peer-to-peer wireless nodes, and small-scale wireless sensor networks in ambient vibration environment.

Keywords: tri-cantilever, ambient vibration, energy harvesting, magnetic oscillator

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