Low-carbon scenario analysis on urban transport of one metropolitan in China in 2020

Purpose: This paper discussed possible ways of implementing effective energy conservation and GHG emission reduction measures by providing: the forecasts of mid-to-long term city-wide carbon emission rate; and the analysis of potential low-carbon transport solutions. Design/methodology/approach: According to the characteristics of the transport system in Beijing, based on the review and application analysis of existing transport energy and GHG emission calculation models, the comprehensive carbon emission calculation model established. Existing data were utilized with regression analysis to project the prospective traffic data in the baseline scenario at the target year of 2020 to calculate the emission amount. Four low-carbon scenarios were set in accordance with the goal of “low carbon transportation, green trip”, and the effectiveness of each low-carbon scenario was evaluated by comparing them with the baseline scenario in terms of the respective GHG emission rate. Findings: Under the current developing trend in policy environment and technical specifications, the total projected GHG (CO2) emissions from transport sector at 2020 in Beijing will reach 24.69 million t CO2; private-vehicle is the major contributor among all transport modes at 15.96 million t CO2. Practical implications: Limiting the growth in private-vehicle ownership, reducing the frequency of mid-to-long range travel and the average trip distance, and prompting the public transit oriented policies are all possible solutions to reduce carbon emission. The most effective practice involves a shift in public travel behavior. Originality/value: This paper presents a method to forecast the mid-to-long term city-wide carbon emission rate; and provides some potential low-carbon transport solutions.Peer Reviewe

Maillard reaction between pea protein isolate and maltodextrin via wet-heating route for emulsion stabilisation

Pea protein isolate (PPI)-maltodextrin (MD) conjugates were prepared by using controlled Maillard reaction at 90 °C in the solution state (wet-heating route). The degree of conjugation between PPI and MD was measured in terms of evolved colour, UV absorbance, and molecular weight change. Results showed that the degree of Maillard reaction increased with the increase in pH and reaction time; however, the PPI-MD conjugation was optimised and was successfully controlled within the initial stage at pH 7.5 and 8.0 to avoid the formation of melanonids. The random coil content of PPI significantly increased upon conjugation with MD producing more flexible structure. The functional properties of PPI in terms of solubility, surface change (zeta-potential), and emulsifying properties of PPI were significantly improved after conjugation with MD. The highest solubility PPI-MD conjugates was observed at 5 h of reaction. The canola oil-in-water (O/W) emulsion stabilised by PPI-MD 5 h conjugate at 2% of emulsifier concentration and homogenised at 60 MPa for 3 passes had the highest physical stability when subjected to 25–60 °C. These findings indicate that Maillard reaction can be controlled in the initial stage via the wet-heating route and the resulting conjugates can be much effective emulsifiers than plant proteins

On First Passage Time Related Problems for Some Insurance Risk Processes

For many decades, the study of ruin theory has long been one of the central topics of interest in insurance risk management. Research in this area has largely focused on analyzing the insurer’s solvency risk, which is essentially a standard first passage time problem. To model the manner in which the claim experience develops over time for a block of insurance business, various stochastic processes have been proposed and studied. Following the pioneer works of Lundberg [88] and Cramér [32], in which the classical compound Poisson model was proposed to model the insurer’s surplus process, there has been a considerable amount of effort devoted to constructing more realistic risk models to better characterize some practical features of the insurer’s surplus cash flows. This thesis aims to contribute to this line of research and enhance our general understanding of an insurer’s solvency risk. In most analyses of the main risk processes in risk theory, the income process is modelled by a deterministic process which accrues at a constant rate per time unit. As we know, this is a rather simplifying assumption which is far from being realistic in the insurance world, but one under which the solvency risk is typically assessed. To investigate the impact of income processes exhibiting a higher degree of variability on an insurer’s solvency risk, the first part of the thesis focuses on analyzing risk models with random income processes. In Chapter 2, we consider a generalized Sparre Andersen risk model with a random income process which renews at claim instants. Under the setting of this particular generalization of the Sparre Andersen risk model, we investigate the impact of income processes on both infinite-time and finite-time ruin quantities. In Chapter 3, we further extend the results of the risk model proposed in Chapter 2 by analyzing a renewal insurance risk model with two-sided jumps and a random income process. Another class of risk models that has drawn considerable interest in risk theory are the spectrally negative Lévy processes. Thanks to the development of the fluctuation theory of Lévy processes, first passage time analysis of Lévy insurance risk models has flourished in the last two decades, both in terms of models proposed and quantities analyzed. For example, risk models with dividends (or tax) payouts and exotic ruin have received considerable attention in the field of insurance mathematics. Leveraging the extensive literature on fluctuation identities for spectrally negative Lévy processes, the second part of the thesis considers some first passage problems in this context. In Chapter 4, we study a refracted Lévy risk model with delayed dividend pullbacks and obtain explicit expressions for two-sided exit identities for the proposed risk process. Chapter 5 introduces two types of random times with the goal of bridging the first and the last passage times’ analyses. The Laplace transforms of these two random times are derived for the class of spectrally negative Lévy processes. To ensure that the thesis flows smoothly, Chapter 1 introduces the background literature and main motivations of this thesis and provides the relevant mathematical preliminaries for the later chapters. Chapter 6 concludes the thesis with some remarks and potential directions for future research

Arbitrary point cloud upsampling via Dual Back-Projection Network

Point clouds acquired from 3D sensors are usually sparse and noisy. Point cloud upsampling is an approach to increase the density of the point cloud so that detailed geometric information can be restored. In this paper, we propose a Dual Back-Projection network for point cloud upsampling (DBPnet). A Dual Back-Projection is formulated in an up-down-up manner for point cloud upsampling. It not only back projects feature residues but also coordinates residues so that the network better captures the point correlations in the feature and space domains, achieving lower reconstruction errors on both uniform and non-uniform sparse point clouds. Our proposed method is also generalizable for arbitrary upsampling tasks (e.g. 4x, 5.5x). Experimental results show that the proposed method achieves the lowest point set matching losses with respect to the benchmark. In addition, the success of our approach demonstrates that generative networks are not necessarily needed for non-uniform point clouds.Comment: 5 pages, 5 figure

Soft-IntroVAE for Continuous Latent space Image Super-Resolution

Continuous image super-resolution (SR) recently receives a lot of attention from researchers, for its practical and flexible image scaling for various displays. Local implicit image representation is one of the methods that can map the coordinates and 2D features for latent space interpolation. Inspired by Variational AutoEncoder, we propose a Soft-introVAE for continuous latent space image super-resolution (SVAE-SR). A novel latent space adversarial training is achieved for photo-realistic image restoration. To further improve the quality, a positional encoding scheme is used to extend the original pixel coordinates by aggregating frequency information over the pixel areas. We show the effectiveness of the proposed SVAE-SR through quantitative and qualitative comparisons, and further, illustrate its generalization in denoising and real-image super-resolution.Comment: 5 pages, 4 figure

Analysis on Alighting and Boarding Movement Laws in Subway Using Modified Social Force Model

This paper presents a multi-agent simulator based on social force model to simulate each passenger’s boarding and alighting behavior both in a train and on a platform seamlessly. Passengers can be divided into three types: to board, alight and stay in train. They have different individual attributes and follow different walking rules. Due to the characteristics of subway environment and passengers' behavior in boarding and alighting, some adjustment and improvement were made to the basic social force model: (1) In some cases during the process of boarding and alighting, the driving force targeting to destination needs to be doubled, and the repulsion force between two agents needs to be reduced. (2) Passengers who stay in the train show quite different movement from the usual pedestrian. They usually want to remain still, unless they are in front of the door. To describe their behaviors, we introduced a tangent detour force. The scope of the interaction between agents is extended and some passengers out of the visual field also should be counted. (3) Divide the repulsive force between an agent and an obstacle into the frontal force and convex corner force. These two forces have different spheres of influence and calculation methods. The agents could exhibit reasonable intelligence and diversity during alighting and boarding

遷移金属触媒による不飽和分子のヒドロアリール化及びアシロキシアルキル化反応の開発

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 金井 求, 東京大学教授 大和田 智彦, 東京大学教授 井上 将行, 東京大学講師 生長 幸之助, 東京大学講師 宮本 和範University of Tokyo(東京大学