CVLight: Decentralized Learning for Adaptive Traffic Signal Control with Connected Vehicles

This paper develops a decentralized reinforcement learning (RL) scheme for multi-intersection adaptive traffic signal control (TSC), called "CVLight", that leverages data collected from connected vehicles (CVs). The state and reward design facilitates coordination among agents and considers travel delays collected by CVs. A novel algorithm, Asymmetric Advantage Actor-critic (Asym-A2C), is proposed where both CV and non-CV information is used to train the critic network, while only CV information is used to execute optimal signal timing. Comprehensive experiments show the superiority of CVLight over state-of-the-art algorithms under a 2-by-2 synthetic road network with various traffic demand patterns and penetration rates. The learned policy is then visualized to further demonstrate the advantage of Asym-A2C. A pre-train technique is applied to improve the scalability of CVLight, which significantly shortens the training time and shows the advantage in performance under a 5-by-5 road network. A case study is performed on a 2-by-2 road network located in State College, Pennsylvania, USA, to further demonstrate the effectiveness of the proposed algorithm under real-world scenarios. Compared to other baseline models, the trained CVLight agent can efficiently control multiple intersections solely based on CV data and achieve the best performance, especially under low CV penetration rates.Comment: 29 pages, 14 figure

Hy-Tracker: A Novel Framework for Enhancing Efficiency and Accuracy of Object Tracking in Hyperspectral Videos

Hyperspectral object tracking has recently emerged as a topic of great interest in the remote sensing community. The hyperspectral image, with its many bands, provides a rich source of material information of an object that can be effectively used for object tracking. While most hyperspectral trackers are based on detection-based techniques, no one has yet attempted to employ YOLO for detecting and tracking the object. This is due to the presence of multiple spectral bands, the scarcity of annotated hyperspectral videos, and YOLO's performance limitation in managing occlusions, and distinguishing object in cluttered backgrounds. Therefore, in this paper, we propose a novel framework called Hy-Tracker, which aims to bridge the gap between hyperspectral data and state-of-the-art object detection methods to leverage the strengths of YOLOv7 for object tracking in hyperspectral videos. Hy-Tracker not only introduces YOLOv7 but also innovatively incorporates a refined tracking module on top of YOLOv7. The tracker refines the initial detections produced by YOLOv7, leading to improved object-tracking performance. Furthermore, we incorporate Kalman-Filter into the tracker, which addresses the challenges posed by scale variation and occlusion. The experimental results on hyperspectral benchmark datasets demonstrate the effectiveness of Hy-Tracker in accurately tracking objects across frames

EA-BEV: Edge-aware Bird' s-Eye-View Projector for 3D Object Detection

In recent years, great progress has been made in the Lift-Splat-Shot-based (LSS-based) 3D object detection method, which converts features of 2D camera view and 3D lidar view to Bird's-Eye-View (BEV) for feature fusion. However, inaccurate depth estimation (e.g. the 'depth jump' problem) is an obstacle to develop LSS-based methods. To alleviate the 'depth jump' problem, we proposed Edge-Aware Bird's-Eye-View (EA-BEV) projector. By coupling proposed edge-aware depth fusion module and depth estimate module, the proposed EA-BEV projector solves the problem and enforces refined supervision on depth. Besides, we propose sparse depth supervision and gradient edge depth supervision, for constraining learning on global depth and local marginal depth information. Our EA-BEV projector is a plug-and-play module for any LSS-based 3D object detection models, and effectively improves the baseline performance. We demonstrate the effectiveness on the nuScenes benchmark. On the nuScenes 3D object detection validation dataset, our proposed EA-BEV projector can boost several state-of-the-art LLS-based baselines on nuScenes 3D object detection benchmark and nuScenes BEV map segmentation benchmark with negligible increment of inference time

CBX4 Provides an Alternate Mode of Colon Cancer Development via Potential Influences on Circadian Rhythm and Immune Infiltration

The circadian machinery is critical for the normal physiological functions and cellular processes. Circadian rhythm disruption has been associated with immune suppression which leads to higher cancer risk, suggesting a putative tumor protective role of circadian clock homeostasis. CBX4, as an epigenetic regulator, has been explored for its involvement in tumorigenesis. However, little is known about the correlation between CBX4 and circadian rhythm disruption in colon cancer as well as the potential impact on the tumor immunity. A significant upregulation of CBX4 was identified in the TCGA colon adenocarcinoma (COAD) samples when compared with the normal controls (p < 0.001). This differential expression was confirmed at the protein level using colon adenocarcinoma tissue array (p < 0.01). CBX4 was up-regulated in the recurred/progressed colon cancer cases compared with the disease-free samples (p < 0.01), suggesting CBX4 as a potential predictor for poor prognosis. With regard to nodular metastasis, CBX4 was found to be associated with early onset of metastatic diseases but not late progression. The circadian rhythm is orchestrated by the alternating activation and suppression of the CLOCK/ARNTL-driven positive loop and the PER/CRY-controlled negative loop. In COAD, CBX4 was negatively correlated with CLOCK (p < 0.001), and positively correlated with PER1 (p < 0.001), PER3 (p < 0.01), and CRY2 (p < 0.001) as well as NR1D1 (p < 0.001), a critical negative regulator of the circadian clock. These interactions consistently impacted on patient survival based on the colorectal cancer cohorts GSE17536 and GSE14333 of PrognoScan. CBX4 showed significant negative correlations with infiltrating B cells (p < 0.05) and CD4+ T cells (p < 0.01), and positive correlations with myeloid derived suppressor cells (MDSCs) (p < 0.05) and cancer associated fibroblast (CAFs) (p < 0.001), as well as a low immunoscore. Moreover, CBX4 displayed significant correlations with diverse immune metagenes. PER1 and PER3, consistent with their coordinated expression with CBX4, also had strong correlations with these gene representatives in COAD, suggesting a potential interaction of CBX4 with the circadian machinery. Our studies implicate that CBX4 may contribute to colon cancer development via potential influence on circadian rhythm and immune infiltration. These findings provide new insights into deciphering the function of CBX4, and may contribute to the development of new targeting strategies

Highly controllable and reliable ultra-thin Parylene deposition

Thanks to the excellent barrier property and fabrication accessibility, Parylene has been actively used in the microelectromechanical system. An ultra-thin Parylene film with thickness smaller than 100 nm is usually required to precisely tune the surface property of substrate or protect the functional unit. The commercially available regular Parylene deposition is a dimer mass determined chemical vapor deposition process with a high output (i.e. a low deposition precision in term of thickness control), around 1.6 μm/g (the ratio of film thickness to the loaded dimer mass) for the machine in the author’s lab. Therefore, it is hard to controllably and reliably prepare a Parylene film with thickness smaller than 100 nm, which requires a dimer mass less than 62.5 mg. This paper reported a method to prepare ultra-thin Parylene films with the nominal thickness down to 1 nm. A home-made deposition chamber was put inside and connected with the regular machine chamber through a microfabricated orifice with feature size smaller than 1 mm. According to the free molecular flow theory, the pressure inside the deposition chamber can be predictably and controllably reduced, thereby an ultra-low output of Parylene deposition, as low as 0.08 nm/g, was successfully obtained. The deposition precision was increased by 4 orders of magnitude compared to that of a direct Parylene deposition. This highly controllable and reliable ultra-thin Parylene deposition technique will find promising applications in flexible electronics and biomedical microdevices

The Role of Alternatively spliced Fibroblast Growth Factor Receptor 2 Isoforms in Breast Cancer

Recent genome-wide association studies identified FGFR2 as one of breast cancer susceptibility genes. FGFR2 expression was down-regulated in breast carcinomas when compared with paired normal epithelium. Stable retroviral transduction of FGFR2-IIIb and its alternatively spliced FGFR2-IIIc variants was achieved in breast cancer MDA-MB-231, T47D and near normal MCF-10A cells. Our findings revealed a direct reduction of breast cancer cell growth and motility, a significant arrest of transformed morphogenetic changes including the Epithelial to Mesenchymal transition (EMT), anchorage independent growth, and the formation of growth-arrested 3D acinar architectures, and suppressive actions on orthotopically xenografted epithelial neoplasms and surrounding tumor stroma. These tumor protective effects were concordant with physical interactions between the two FGFR2 isoforms and IKKβ. Consistent with these interactions we noted FGFR2 to inhibit NF-κB signaling, including decreased nuclear RelA/p65 NF-κB localization, down-regulation of a transfected NF-κB luciferase reporter, reduced production of NF-κB-dependent transcripts, Interleukin-6 and p-STAT3.MAS