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Autonomous exploration requires the robot to explore an unknown environment while constructing an accurate map with the SLAM (Simultaneous Localization and Mapping) techniques. Without prior information, the exploratory performance is usually conservative due to the limited planning horizon. This paper exploits a prior topo-metric graph of the environment to benefit both the exploration efficiency and the pose graph accuracy in SLAM. Based on recent advancements in relating pose graph reliability with graph topology, we are able to formulate both objectives into a SLAM-aware path planning problem over the prior graph, which finds a fast exploration path with informative loop closures that globally stabilize the pose graph. Furthermore, we derive theoretical thresholds to speed up the greedy algorithm to the problem, which significantly prune non-optimal loop closures in iterations. The proposed planner is incorporated into a hierarchical exploration framework, with flexible features including path replanning and online prior map update that adds additional information to the prior graph. Extensive experiments indicate that our method has comparable exploration efficiency to others while consistently maintaining higher mapping accuracy in various environments. Our implementations will be open-source on GitHub., Comment: 8 pages, 6 figures

We present an efficient Neural Neighborhood Search (N2S) approach for pickup and delivery problems (PDPs). In specific, we design a powerful Synthesis Attention that allows the vanilla self-attention to synthesize various types of features regarding a route solution. We also exploit two customized decoders that automatically learn to perform removal and reinsertion of a pickup-delivery node pair to tackle the precedence constraint. Additionally, a diversity enhancement scheme is leveraged to further ameliorate the performance. Our N2S is generic, and extensive experiments on two canonical PDP variants show that it can produce state-of-the-art results among existing neural methods. Moreover, it even outstrips the well-known LKH3 solver on the more constrained PDP variant. Our implementation for N2S is available online., Comment: Accepted at IJCAI 2022 (short oral)

Exploiting multi-scale features has shown great potential in tackling semantic segmentation problems. The aggregation is commonly done with sum or concatenation (concat) followed by convolutional (conv) layers. However, it fully passes down the high-level context to the following hierarchy without considering their interrelation. In this work, we aim to enable the low-level feature to aggregate the complementary context from adjacent high-level feature maps by a cross-scale pixel-to-region relation operation. We leverage cross-scale context propagation to make the long-range dependency capturable even by the high-resolution low-level features. To this end, we employ an efficient feature pyramid network to obtain multi-scale features. We propose a Relational Semantics Extractor (RSE) and Relational Semantics Propagator (RSP) for context extraction and propagation respectively. Then we stack several RSP into an RSP head to achieve the progressive top-down distribution of the context. Experiment results on two challenging datasets Cityscapes and COCO demonstrate that the RSP head performs competitively on both semantic segmentation and panoptic segmentation with high efficiency. It outperforms DeeplabV3 [1] by 0.7% with 75% fewer FLOPs (multiply-adds) in the semantic segmentation task., Comment: Accepted to RA-L 2021. in IEEE Robotics and Automation Letters. The contents of this paper were also selected by the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021) Program Committee for presentation at the Conference

Target detection and tracking provides crucial information for motion planning and decision making in autonomous driving. This paper proposes an online multi-object tracking (MOT) framework with tracking-by-detection for maneuvering vehicles under motion uncertainty in dynamic road context. We employ a point cloud based vehicle detector to provide real-time 3D bounding boxes of detected vehicles and conduct the online bipartite optimization of the maneuver-orientated data association between the detections and the targets. Kalman Filter (KF) is adopted as the backbone for multi-object tracking. In order to entertain the maneuvering uncertainty, we leverage the interacting multiple model (IMM) approach to obtain the \textit{a-posterior} residual as the cost for each association hypothesis, which is calculated with the hybrid model posterior (after mode-switch). Road context is integrated to conduct adjustments of the time varying transition probability matrix (TPM) of the IMM to regulate the maneuvers according to road segments and traffic sign/signals, with which the data association is performed in a unified spatial-temporal fashion. Experiments show our framework is able to effectively track multiple vehicles with maneuvers subject to dynamic road context and localization drift., Comment: Submitted to ICRA 2020

Background Stathmin as a critical protein involved in microtubule polymerization, is necessary for survival of cancer cells. However, extremely little is known about Stathmin in glioblastoma. So, this study was designed to elucidate the function of Stathmin gene in the tumorigenesis and progression of glioblastoma cells. Method The lentiviral interference vector pLV3-si-Stathmin targeting Stathmin gene and the control vector pLV3-NC were established for the co-transfection of 293T cells together with the helper plasmids. Viral titer was determined via limiting dilution assay. Then pLV3-si-Stathmin and pLV3-NC were stably co-transfected into U373 and U87-MG glioblastoma cells. Expression levels of Stathmin protein in each group were determined by using Western Blot, and the proliferation and migration ability of the cells with downregulated Stathmin were evaluated through CCK8 assay and transwell invasion assay, respectively. Cell cycles and cell apoptosis were detected with flow cytometry. Finally, the effect of Stathmin in tumor formation was determined in nude mice. Result DNA sequencing and viral titer assay indicated that the lentiviral interference vector was successfully established with a viral titer of 4 × 108 TU/ml. According to the results from Western Blotting, Stathmin protein expression level decreased significantly in the U373 and U87-MG cells after transfected with pLV3-si-Stathmin, respectively, compared with those transfected with pLV3-NC. In glioblastoma cells, the cell proliferation and migration were greatly inhibited after the downregulation of Stathmin protein. Flow cytometry showed that much more cells were arrested in G2/M phasein Stathmin downregulated group, compared with the non-transfection group and NC group. But Stathmin downregulation did not induce significant cell apoptosis. Tumor formation assay in nude mice showed that tumor formation was delayed after Stathmin downregulation, with a reduction in both tumor formation rate

In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indicate that the PSA is a promising algorithm for constrained optimization., Comment: 6 pages, 1 figure

Hepatitis B virus (HBV) infection-related hepatocellular carcinoma (HCC) represents a major health problem worldwide. HBV X (HBx) protein is the most common open reading frame that may undergo mutations, resulting in the development of HCC. This study aimed to determine specific HBx mutations that differentiate the central- and para-tumor tissues, and identify their association with HCC development. HBx gene from HCC tumor and para-tumor tissues of 47 HCC patients was amplified, sequenced and statistically analyzed. A novel combination of 2 mutations at residues 10 and 144 was identified which might play a significant role in HCC development. Expression vectors carrying HBx with the specific mutations were constructed and transfected into HepG2 and p53-null HepG2 cells. Compared to wild type (WT) and single mutation of HBx at residue 10 or 144, the 10/144 double mutations strongly up-regulated p21 expression and prolonged G1/S transition in WT- and p53-null HepG2 cells. Apoptosis was also inhibited by HBx harboring 10/44 double-mutation. Binding of 10/144 double-mutant HBx to p53 was lower than WT HBx. Conclusively, the 10/144 double mutation of HBx might play a crucial role in HCC formation.

Locally advanced rectal cancer is currently treated with preoperative radiochemotherapy, but the response is not uniform. Most patients benefit from preoperative CRT, however, a small proportion of a patient population is less likely to respond to the treatment. The purpose of this study was to measure neoadjuvant therapy combined with Ki-67 and VEGF expression in pretreatment biopsies and postoperative specimens，serum carcinoembryonic antigen (CEA) and CA19-9 level from patients with locally advanced rectal cancer receiving intensive neoadjuvant treatment and to correlate the findings with clinical outcome.