The Regenerative Braking Energy (RBE) of metro trains plays an important role in metro energy saving. If the regenerative energy can be directly absorbed by the adjacent trains, the investment in other RBE usage equipments like super capacitors will be reduced. To increase the RBE usage, the overlaps of traction and braking processes of adjacent trains can be increased by timetable optimization or real-time train regulation. But if the overlaps cannot be realized, the RBE cannot be efficiently absorbed by the other trains. To solve this problem, this paper proposes an optimal train control method to absorb the RBE of the braking train by adjusting the speed profile of an adjacent train that runs at non-braking stage. A speed profile adjustment algorithm for the adjacent train is given considering the speed limits and gradients, in which a traction process is incorporated in the adjusted speed profile. Connected and unconnected DC power supply networks are both considered. In the connected DC power supply network, the RBE of the braking train can be absorbed by the adjacent adjusted train, which runs in the different power supply section. To test the robustness of the proposed algorithm, random train delays are considered in the simulations. The interstation running time will be regulated to reduce the train delay by a linear programming model, based on which, the speed profile of the cooperative train will be adjusted. Simulations are conducted based on a whole day data of Beijing Metro Line 4. The simulation results show that the proposed method improves the energy efficiency over 13% by improving RBE usage, and the proposed method also shows strong robustness in the train delay simulations, which makes it a promising method to be applied in real metro system.

MOTIVATION: The output of electrospray ionization-liquid chromatography mass spectrometry (ESI-LC-MS) is influenced by multiple sources of noise and major contributors can be broadly categorized as baseline, random and chemical noise. Noise has a negative impact on the identification and quantification of peptides, which influences the reliability and reproducibility of MS-based proteomics data. Most attempts at denoising have been made on either spectra or chromatograms independently, thus, important 2D information is lost because the mass-to-charge ratio and retention time dimensions are not considered jointly. RESULTS: This article presents a novel technique for denoising raw ESI-LC-MS data via 2D undecimated wavelet transform, which is applied to proteomics data acquired by data-independent acquisition MS (DIA-MS). We demonstrate that denoising DIA-MS data results in the improvement of peptide identification and quantification in complex biological samples. AVAILABILITY AND IMPLEMENTATION: The software is available on Github (https://github.com/CMRI-ProCan/CRANE). The datasets were obtained from ProteomeXchange (Identifiers-PXD002952 and PXD008651). Preliminary data and intermediate files are available via ProteomeXchange (Identifiers-PXD020529 and PXD025103). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Construction of 3D environments from photorealistic images is important for many industries, including virtual reality, games and tourism among others. Extensive work has been undertaken using multiple stereo vision systems and fusion processing to create full 3D virtual environments. To improve the efficiency and accuracy, a stereo panoramic imaging system is used. A 3D environment can be created by using two panoramic images from a one-shot camera system. However a whole 3D scene is not always required, so a system which reconstructs 3D data only in a region of interest has been developed. A new structured light projection system for region of interest reconstruction is presented and tested. Based on the experimental tests, conclusions have been derived for highlighting the advantages of the approach.

This paper reports the problem of colour distortion in panoramic imaging. Particularly when image mosaicing is used for panoramic imaging, the images are captured under different lighting conditions and viewpoints. The paper analyses several linear approaches for their colour transform and mapping. A new approach of colour histogram based colour correction is provided, which is robust to image capturing conditions such as viewpoints and scaling. The procedure for the colour correction is introduced and implemented. The conclusions are derived after experimental tests.