A Hybrid BP-EP-VMP Approach to Joint Channel Estimation and Decoding for FTN Signaling over Frequency Selective Fading Channels

This paper deals with low-complexity joint channel estimation and decoding for faster-than-Nyquist (FTN) signaling over frequency selective fading channels. The inter-symbol interference (ISI) imposed by FTN signaling and the frequency selective channel are intentionally separated to fully exploit the known structure of the FTN-induced ISI. Colored noise due to the faster sampling rate than that of the Nyquist signaling system is approximated by autoregressive process. A Forney style factor graph representation of the FTN system is developed and Gaussian message passing is performed on the graph. Expectation propagation (EP) is employed to approximate the message from channel decoder to Gaussian distribution. Since the inner product between FTN symbols and channel coefficients is infeasible by belief propagation (BP), we propose to perform variational message passing (VMP) on an equivalent soft node in factor graph to tackle this problem. Simulation results demonstrate that the proposed low-complexity hybrid BP-EP-VMP algorithm outperforms the existing methods in FTN system. Compared with the Nyquist counterpart, FTN signaling with the proposed algorithm is able to increase the transmission rate by over 40%, with only negligible BER performance loss

GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point Clouds

LiDAR-based 3D detection has made great progress in recent years. However, the performance of 3D detectors is considerably limited when deployed in unseen environments, owing to the severe domain gap problem. Existing domain adaptive 3D detection methods do not adequately consider the problem of the distributional discrepancy in feature space, thereby hindering generalization of detectors across domains. In this work, we propose a novel unsupervised domain adaptive \textbf{3D} detection framework, namely \textbf{G}eometry-aware \textbf{P}rototype \textbf{A}lignment (\textbf{GPA-3D}), which explicitly leverages the intrinsic geometric relationship from point cloud objects to reduce the feature discrepancy, thus facilitating cross-domain transferring. Specifically, GPA-3D assigns a series of tailored and learnable prototypes to point cloud objects with distinct geometric structures. Each prototype aligns BEV (bird's-eye-view) features derived from corresponding point cloud objects on source and target domains, reducing the distributional discrepancy and achieving better adaptation. The evaluation results obtained on various benchmarks, including Waymo, nuScenes and KITTI, demonstrate the superiority of our GPA-3D over the state-of-the-art approaches for different adaptation scenarios. The MindSpore version code will be publicly available at \url{https://github.com/Liz66666/GPA3D}.Comment: Accepted by ICCV 202

Study on characteristics of particulate emission of diesel aftertreatment with reciprocating flow

© 2021 The Authors. Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/In this article, in order to optimize diesel aftertreatment system with periodically reciprocating flow (PRF), an experimental study is conducted to investigate its characteristics such as pollution emissions, regeneration of diesel particulate filter (DPF), concentration and size distribution of particulate matter (PM) escaped as well as temperature distribution under unidirectional flow and PRF operating conditions. The effects of reciprocating flow cycle and exhaust gas flow on the performance of aftertreatment system are investigated in detail. The energy efficiency analysis of the aftertreatment system is also carried out. Experimental results show that (i) as the temperature is lower than the light-off threshold of combustible gas, the aftertreatment system cannot restrain the formation of second particles under the present experiment condition of unidirectional flow; (ii) the aftertreatment system demonstrates excellent performance of trapping particles and filter regeneration as the symmetrical temperature distribution is formed. The PM filter efficiency α_PM is 92% and the specific energy consumption β is 124% for symmetrical temperature distribution; (iii) the increase of reciprocating flow cycle could lead to the shifting of the temperature profiles, this would affect the particle size distribution; (iv) a certain increase of exhaust gas flow from engine would have insignificant change for the temperature distribution; (v) The critical energy efficiency η_c of the system could reach 96.61%.Peer reviewedFinal Published versio

Assessing slope forest effect on flood process caused by a short-duration storm in a small catchment

Land use has significant impact on the hydrologic and hydraulic processes in a catchment. This work applies a hydrodynamic based numerical model to quantitatively investigate the land use effect on the flood patterns under various rainfall and terrain conditions in an ideal V-shaped catchment and a realistic catchment, indicating the land use could considerably affect the rainfall-flood process and such effect varies with the catchment terrain, land use scenario and the rainfall events. The rainfall-flood process is less sensitive for the side slope than the channel slope. For a channel slope lower than the critical value in this work, the forest located in the middle of the catchment slope could most effectively attenuate the flood peak. When the channel slope is higher than the critical one, forest located in the downstream of the catchment could most significantly mitigate the peak discharge. Moreover, the attenuation effect becomes more obvious as the rainfall becomes heavier. The fragmentation of vegetation does not reduce the flood peak in a more obvious way, compared with the integral vegetation patterns with the same area proportion. The research can help more reasonably guide the land use plan related to flood risk

Successful treatment discontinuation in CML patients with full-dose and low-dose TKI: Results from real-world practice

Background: In clinical studies, some patients who achieve deep molecular response (DMR) can successfully discontinue tyrosine kinase inhibitor (TKI). TKI dose reduction is also an important aspect of alleviating adverse effects and improving quality of life. This study aimed to explore the outcome after drug withdrawal in Chinese CML patients.Methods: We conducted a retrospective analysis of the outcome of 190 patients who stopped TKI. 27 patients experienced dose reduction before TKI discontinuation. The median duration of TKI treatment and MR4 before discontinuation was 82 months and 61 months.Results: With median follow-up after stopping TKI treatment of 17 months, the estimated TFR (Treatment Free Remission) were 76.9% (95%CI, 70.2%–82.4%), 68.8% (95%CI, 61.3%–75.2%), and 65.5% (95%CI, 57.4%–72.5%) at 6, 12 and 24 months. For full-dose and low-dose TKI groups, the TFR at 24 months was 66.7% and 55.8% (p = 0.320, log-rank). Most patients (56/57) quickly achieved MMR after restarting TKI treatment. Multivariable analysis showed that patients with TKI resistance had a higher risk of molecular relapse than patients without TKI resistance (p < 0.001).Conclusion: TFR rates were not impaired in patients experiencing dose reduction before TKI discontinuation compared to patients with full-dose TKI. Our data on Chinese population may provide a basis for the safety and feasibility of TKI discontinuation, including discontinuation after dose reduction, in clinical practice