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The multi-objective optimisation of high-speed rail profile with small radius curve is studied in the paper. A multi-objective mathematical model for rail profile optimisation of high-speed railway is established. The CN60 rail profile is parameterised into a series of generalised functions of design variables. In order to guarantee the smoothness of the rail profile and meet the maximum grinding depth of rail in China, the constraints are employed. The wheel-rail vertical clearance and equivalent conicity of wheelset are taken as objective functions, and a rail wear prediction programme is compiled. Contact line method is employed to complete the detection algorithm of wheel-rail contact points. Finally, NSGA-II Algorithm is adopted to solve the Pareto-optimal front of the optimisation model. A set of solutions are retrieved from the Pareto optimal front solution as the optimised profile. The optimised rail profile and the original rail profile are matched with the LMA wheel profile (a certain worn type of wheel profiles for EMU in China) respectively. It is testified that the rail profile could effectively reduce the rail wear and improve curving performance. The new method proposed in this paper can provide some reference for the optimisation design of high-speed rail profile with small radius curve. [ABSTRACT FROM AUTHOR]

The vulnerable children refer to the special group of children with deviation in the process of children's psychological development and personality formation due to growth dilemmas. This may incur a series of serious social and family problems. The vulnerable children mainly cover the children suffering from children's psychological problems, such as childhood autism, autism, social anxiety and hypersensitivity, fear, depression, and PTSD arising from other factors. At present, the research results at home and abroad mainly focus on the psychological dynamic correlation investigation and solution discussion of a certain kind of difficult factor in the children's psychological development based on statistical data by the experimental methods, such as scale and model, and there is a blind spot in the humanistic orientation theory construction of psychological treatment for vulnerable children, causing the social reflection on children's psychological predicament from the humanistic perspective cannot be performed in related researches and going against searching for universal and integral theoretical paradigm for solving related problems. Sophisticated technologies for the observations have emerged increasingly for enabling the psychological features of vulnerable children through developmental cognitive neuroscience experiments. This paper introduces humanistic art therapy theory, focuses on the construction of a theoretical paradigm, and verifies its effectiveness based on the experimental results on the psychological development of vulnerable children, with an efficient performance. This study mainly refers to children with difficulty in social inclusion and psychological development. The results showed that two kinds of art therapy can obviously improve the psychological disorders of vulnerable children. The goal was to enhance self-cognition, strengthen emotional interaction, and implement positive motivation. [ABSTRACT FROM AUTHOR]

Concentration of power in terms of user traffic and copyright content is most evident in content platforms in China. Such concentration has generated an unexpected impact on the way we understand and appreciate creativity, on copyright enforcement and determination of liability on content platforms, and on the regulation of the cultural market by the government. Specifically, the concentration of power in content platforms has not only curbed direct online piracies to a large extent but has also accelerated the fragmentation of copyright enforcement and spawned the need for algorithmic recommendation and filtering systems, which in turn has reinforced the cultural censorship system of China. This paper argues that the employment of algorithms by platforms must be treated with prudence: the algorithmic decision-making systems employed by platforms must be transparent as much as possible, and remedies must be provided for concerned users. The algorithms employed by content platforms must be adjusted to reflect not just the interests of the platforms but also the public interest in accessing and delivering information and local policy considerations. This paper suggests that our regulatory framework should reflect the algorithmic turn of content platforms in its legal and non-legal instruments and alleviate their negative impact on society. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI), officially listed as one of essential climate variables, quantifies the structure and amount of vegetation and characterizes the interaction between vegetation and climate. The advanced MEdium Resolution Spectral Imager (MERSI-II) onboard FengYun-3D (FY-3D) can provide twice-daily global observations of earth at a spatial resolution of 250 m. Therefore, it has great potential for promoting the improvement of global LAI products and boosting the development of earth system modelling. However, the existing methods are mostly sensor-specific, they can not be directly applied to MERSI-II data for LAI generation. In this paper, we proposed a sensor-adaptive approach for LAI estimation based on MERSI-II observations. This method is composed of an LAI retrieval look-up table based on radiative transfer theory, which was calibrated by a global optimizing algorithm to adapt MERSI-II characteristics, and a backup algorithm training neural networks with MERSI-II Normalized Difference Vegetation Index (NDVI) and Moderate Resolution Imaging Spectroradiometer (MODIS) LAI. We evaluated the MERSI-II LAI retrievals by intercomparison to MODIS products over mainland China and direct validation using ground-based upscaled LAI reference maps. The assessments demonstrate that (1) the derived MERSI-II LAI products agree well with the MODIS benchmarks in both spatial and temporal respects; (2) compared to the MODIS LAI, the MERSI-II LAI retrievals with less gaps show great potential in improving spatiotemporal continuity; (3) validation versus in-situ measurements reveals acceptable accuracy of the MERSI-II LAI products with a R2 of 0.85 and RMSE of 0.82; (4) the proposed parametric optimization strategy could successfully transplant MODIS LAI algorithm to MERSI-II data. [ABSTRACT FROM AUTHOR]

In the algorithmic era, both users and the platform battle for visibility. Chinese fans are savvy users who explore the hidden algorithms behind platform functions. With the collectively developed algorithmic imaginary, digital fandom communities negotiate with the platform over algorithms to optimize the visibility of celebrities they endorse. Drawing from participatory observation and semi-structured interviews in Chinese online fandoms of an idol group, INTO1, we detailed how fans as digital users collectively explore, interpret, and creatively utilize algorithms to increase their idol's visibility. We conclude that visibility, as a representation of algorithm power, is co-defined through the constant push-and-pull between digital users and the platform. This paper contributes to both algorithm and fandom studies by describing large-scale non-professional users' daily construction of the algorithmic imaginary in the unique context of Chinese fandom and beyond. It also discusses broader civic implications of fans' algorithmic practices to wider digital users in China. [ABSTRACT FROM AUTHOR]

We propose a mathematical model to solve the railway transit network design problem, considering the total time spent in the travel of all the passengers on the network as the optimization goal. The number of passengers to be transported, train accommodating capacity, station capacity, railway section capacity, and available train number is taken as the constraints in the model. Then, we design a heuristic algorithm - fuzzy plant growth simulation algorithm to solve the model. A computing case, based on the data of the railway network of part of East China is presented to prove the efficiency and effectiveness of the proposed model and algorithm. The approach presented in this paper can help to design the service plan in the view of the railway network for the railway operators. [ABSTRACT FROM AUTHOR]

This paper proposes the nonnegative adaptive elastic-net for simultaneous nonnegative estimation and variable selection in sparse high-dimensional linear regression models. By inheriting the good features of adaptive elastic-net, the nonnegative adaptive elastic-net enjoys the oracle property even in high-dimensional settings where the dimension of covariates can be much larger than the sample size. Through the simulation, we show that the newly proposed method deals with the collinearity problem better than alternative procedures in the literature. To make the proposed method practically feasible, we extend the multiplicative updates algorithm for implementation. Finally, we illustrate the favorable finite-sample performance of the proposed method through tracking the CSI 300 index, an important stock market index in China. [ABSTRACT FROM AUTHOR]

The paper considers the design of a multimodal and multilayer inbound logistics network for iron ore to be delivered from suppliers to steel plants. To make cost-efficient logistics and transportation planning decisions, steel companies should account for uncertainty in the demand for iron ore and the economies of scale during transshipment process in the port, which are two critical elements affecting decisions. To this end, we propose a two-stage nonlinear stochastic programming model with the first stage determining the choice of the port to perform transshipment operations and the needed capacity, and the second stage selecting transportation modes after demand uncertainty has been realized. To solve this problem, we first reformulate and linearize the model based on a quantity discount policy applied to the transshipment ports, and then, we develop a scenario-based decomposition algorithm. We conduct a case study based on the data of a steel company in China to illustrate the applicability of our proposed model. Moreover, we perform numerical experiments to demonstrate the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]