Housing price development in Shanghai

Rapid increase in housing prices and growing mortgage lending aroused great concern of whether there is bubble in Chinese housing market. In fact, the price-to-rent ratio and price-to-income ratio soar in most Chinese cities, especially in coastal- and some inland- areas, making housing affordability a prominent issue. The thesis tends to examine housing price movement in Shanghai over years 2002 to 2017 in order to reveal whether there was a bubble in Shanghai housing market and the possible implications. Measures like price-to-rent ratio, price-to-income ratio and cointegration test are employed to reflect the interaction between house price and market determinants like disposable income, GDP and land price etc. The house price movement shall be taken with caution in order to develop a dynamic housing market

Seedless grape breeding for disease resistance by using embryo rescue

An efficient system of seedless grape breeding for disease resistance through embryo rescue was developed by using an interspecific hybrid 'Beichun' of V. vinifera × V. amurensis as the pollen donor. Genotype and medium were confirmed to play important roles in this system, when a combined culture phase of solid plus liquid was used. 'Emerald Seedless' showed the highest percentage of plant development (19.6 %) in EMERSHAD and RAMMING (1994) medium (ER) among the females, suggesting it is more sensitive to ovule culture. To further improve the breeding efficiency, different amino acids were tested by using ovules from 'Emerald Seedless' × 'Beichun'. The addition of asparagine, glycine, arginine and glutamine (2.0 mmol·l-1 respectively) yielded a higher plant development rate than the basal medium. The best result was obtained from asparagine supplemented medium, with 55.0 % ovules generated plants. The field performance to downy mildew [Plasmopara viticola (Berk. and Curtis) Berl. and de Toni] and anthracnose [Elsinoë ampelina (de Bary) Shear] of the parents and progenies was also evaluated. Disease resistance in F1 generation demonstrates continuous variation, with some resistant progenies, accounted for 5.7 % from offsprings, beyond the range observed in the parents. No correlation was observed between the resistance to the two pathogens in this research.

Learning Motion Predictors for Smart Wheelchair using Autoregressive Sparse Gaussian Process

Constructing a smart wheelchair on a commercially available powered wheelchair (PWC) platform avoids a host of seating, mechanical design and reliability issues but requires methods of predicting and controlling the motion of a device never intended for robotics. Analog joystick inputs are subject to black-box transformations which may produce intuitive and adaptable motion control for human operators, but complicate robotic control approaches; furthermore, installation of standard axle mounted odometers on a commercial PWC is difficult. In this work, we present an integrated hardware and software system for predicting the motion of a commercial PWC platform that does not require any physical or electronic modification of the chair beyond plugging into an industry standard auxiliary input port. This system uses an RGB-D camera and an Arduino interface board to capture motion data, including visual odometry and joystick signals, via ROS communication. Future motion is predicted using an autoregressive sparse Gaussian process model. We evaluate the proposed system on real-world short-term path prediction experiments. Experimental results demonstrate the system's efficacy when compared to a baseline neural network model.Comment: The paper has been accepted to the International Conference on Robotics and Automation (ICRA2018

Thermodynamic analysis of air cycle refrigeration system for Chinese train air conditioning

AbstractThe air cycle refrigeration system used in Chinese train air conditioning engineering is investigated. The effects of possible parameters affecting system performance are examined through sensitive analysis of the thermodynamic model. The results show that, the pressure ratio should be in the range of 2-2.5, the COP will be in the range of 1-1.2, and the cold air distribution system can be used. To increase the COP, higher efficiencies of compressors, expanders and heat exchangers are expected

Microstructure and Adsorption Property of Bamboo-Based Activated Carbon Fibers Prepared by Liquefaction and Curing

In this study, activated carbon fibers (BACF) were prepared from moso bamboo by phenol liquefaction, spinning, curing, and CO2 activation. The microstructure and porous texture of BACF were investigated by Fourier transform IR spectroscopy, X-ray diffraction, and N2 adsorption at -196°C. The surface area and pore volume increased progressively after activation, and yields were found in the range of 39-59.6%. BACF showed type I isotherms with multimodal pore size distributions in th

4D trajectory optimization of commercial flight for green civil aviation

For the current development of green civil aviation, this study aims to optimize the green four-dimensional (4D) trajectory of commercial flight by taking into account conventional cost and environmental cost. Some fundamental models, efficient processing methodologies, and conventional objectives are proposed to construct the framework of trajectory optimization. Based on the environmental cost including greenhouse gas cost and harmful gas cost, green objective functions are presented. The A* algorithm and the trapezoidal collocation method are employed to optimize the lateral path and vertical profile for 4D optimization trajectory generation. A case study for the A320 from Barcelona Airport to Frankfurt Airport yields the results that the optimal costs can be obtained under different objectives and the total cost can be more optimized by adjusting the weights of environmental cost and conventional cost. The study builds an aided tool for 4D trajectory optimization and demonstrates that environmental factors and conventional factors should be taken into comprehensive consideration when constructing the flight trajectory in the future, as well as it can underpin the green and sustainable development of the air transport industry

Feature-Suppressed Contrast for Self-Supervised Food Pre-training

Most previous approaches for analyzing food images have relied on extensively annotated datasets, resulting in significant human labeling expenses due to the varied and intricate nature of such images. Inspired by the effectiveness of contrastive self-supervised methods in utilizing unlabelled data, weiqing explore leveraging these techniques on unlabelled food images. In contrastive self-supervised methods, two views are randomly generated from an image by data augmentations. However, regarding food images, the two views tend to contain similar informative contents, causing large mutual information, which impedes the efficacy of contrastive self-supervised learning. To address this problem, we propose Feature Suppressed Contrast (FeaSC) to reduce mutual information between views. As the similar contents of the two views are salient or highly responsive in the feature map, the proposed FeaSC uses a response-aware scheme to localize salient features in an unsupervised manner. By suppressing some salient features in one view while leaving another contrast view unchanged, the mutual information between the two views is reduced, thereby enhancing the effectiveness of contrast learning for self-supervised food pre-training. As a plug-and-play module, the proposed method consistently improves BYOL and SimSiam by 1.70\% $\sim$ 6.69\% classification accuracy on four publicly available food recognition datasets. Superior results have also been achieved on downstream segmentation tasks, demonstrating the effectiveness of the proposed method.Comment: Accepted by ACM MM 202