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This research presents a novel active detection model utilizing deep reinforcement learning to accurately detect traffic objects in real-world scenarios. The model employs a deep Q-network based on LSTM-CNN that identifies and aligns target zones with specific categories of traffic objects through implementing a top-down approach with efficient feature extraction of the environment. The model integrates historical and current actions and observations to make a comprehensive analysis. The design of the state space and reward function takes into account the impact of time steps to enable the model to complete the task in fewer steps. Tests conducted demonstrate the model's proficiency, exhibiting exceptional precision and performance in locating traffic signal lights and speed limit signs. The findings of this study highlight the efficacy and potential of the deep reinforcement learning-based active detection model in traffic-related applications, underscoring its robust detection abilities and promising performance., Comment: 14 pages, 4 figures, having passed the preliminary review by experts, about to be submitted to a relevant conference

ObjectivesNon-Hodgkin's lymphoma (NHL) primarily derived from the base of the tongue, is rare. Human papillomavirus (HPV) and Epstein-Barr virus (EBV) are important aetiological risk factors for tumours of the head and neck. This study describes the clinicopathological features of NHL in the tongue base and the status of HPV and EBV in these cases.MethodsSeven cases were identified from the Pathological Registry Database at Peking Union Medical College Hospital (PUMCH). The study utilized immunochemistry, in situ hybridization (ISH), and gene rearrangement to confirm the disease and and performed a clinical follow up for each case.ResultsAll 7 lymphomas were localized at the base of the tongue. Six of the cases exhibited tongue base masses with smooth surface membranes. One case presented as multiple deep ulcers. The most common histologic subtype was diffuse large B-cell lymphoma (DLBCL), which occurred in five cases. The other two cases were mantle cell lymphoma (MCL) and peripheral T cell lymphoma, not otherwise specified (PTCL, NOS). One of the DLBCL cases was positive for HPV DNA and diffusely expressed P16 protein. During the follow up period, the MCL patient and an elderly DLBCL patient died. The remaining five patients were alive through the end of follow up.ConclusionsMost lymphomas of the tongue base manifest as an endogenous mass without membranous change. The most common subtype of NHLs of the tongue base is DLBCL, and the occurrence at this site may have a good prognosis. With proper therapy, even late stage tongue base lymphomas can be suppressed and remain in remission.

ObjectivesNon-Hodgkin's lymphoma (NHL) primarily derived from the base of the tongue, is rare. Human papillomavirus (HPV) and Epstein-Barr virus (EBV) are important aetiological risk factors for tumours of the head and neck. This study describes the clinicopathological features of NHL in the tongue base and the status of HPV and EBV in these cases.MethodsSeven cases were identified from the Pathological Registry Database at Peking Union Medical College Hospital (PUMCH). The study utilized immunochemistry, in situ hybridization (ISH), and gene rearrangement to confirm the disease and and performed a clinical follow up for each case.ResultsAll 7 lymphomas were localized at the base of the tongue. Six of the cases exhibited tongue base masses with smooth surface membranes. One case presented as multiple deep ulcers. The most common histologic subtype was diffuse large B-cell lymphoma (DLBCL), which occurred in five cases. The other two cases were mantle cell lymphoma (MCL) and peripheral T cell lymphoma, not otherwise specified (PTCL, NOS). One of the DLBCL cases was positive for HPV DNA and diffusely expressed P16 protein. During the follow up period, the MCL patient and an elderly DLBCL patient died. The remaining five patients were alive through the end of follow up.ConclusionsMost lymphomas of the tongue base manifest as an endogenous mass without membranous change. The most common subtype of NHLs of the tongue base is DLBCL, and the occurrence at this site may have a good prognosis. With proper therapy, even late stage tongue base lymphomas can be suppressed and remain in remission.

ObjectivesNon-Hodgkin's lymphoma (NHL) primarily derived from the base of the tongue, is rare. Human papillomavirus (HPV) and Epstein-Barr virus (EBV) are important aetiological risk factors for tumours of the head and neck. This study describes the clinicopathological features of NHL in the tongue base and the status of HPV and EBV in these cases.MethodsSeven cases were identified from the Pathological Registry Database at Peking Union Medical College Hospital (PUMCH). The study utilized immunochemistry, in situ hybridization (ISH), and gene rearrangement to confirm the disease and and performed a clinical follow up for each case.ResultsAll 7 lymphomas were localized at the base of the tongue. Six of the cases exhibited tongue base masses with smooth surface membranes. One case presented as multiple deep ulcers. The most common histologic subtype was diffuse large B-cell lymphoma (DLBCL), which occurred in five cases. The other two cases were mantle cell lymphoma (MCL) and peripheral T cell lymphoma, not otherwise specified (PTCL, NOS). One of the DLBCL cases was positive for HPV DNA and diffusely expressed P16 protein. During the follow up period, the MCL patient and an elderly DLBCL patient died. The remaining five patients were alive through the end of follow up.ConclusionsMost lymphomas of the tongue base manifest as an endogenous mass without membranous change. The most common subtype of NHLs of the tongue base is DLBCL, and the occurrence at this site may have a good prognosis. With proper therapy, even late stage tongue base lymphomas can be suppressed and remain in remission.

Traffic intersections are important scenes that can be seen almost everywhere in the traffic system. Currently, most simulation methods perform well at highways and urban traffic networks. In intersection scenarios, the challenge lies in the lack of clearly defined lanes, where agents with various motion plannings converge in the central area from different directions. Traditional model-based methods are difficult to drive agents to move realistically at intersections without enough predefined lanes, while data-driven methods often require a large amount of high-quality input data. Simultaneously, tedious parameter tuning is inevitable involved to obtain the desired simulation results. In this paper, we present a novel adaptive and planning-aware hybrid-driven method (TraInterSim) to simulate traffic intersection scenarios. Our hybrid-driven method combines an optimization-based data-driven scheme with a velocity continuity model. It guides the agent's movements using real-world data and can generate those behaviors not present in the input data. Our optimization method fully considers velocity continuity, desired speed, direction guidance, and planning-aware collision avoidance. Agents can perceive others' motion planning and relative distance to avoid possible collisions. To preserve the individual flexibility of different agents, the parameters in our method are automatically adjusted during the simulation. TraInterSim can generate realistic behaviors of heterogeneous agents in different traffic intersection scenarios in interactive rates. Through extensive experiments as well as user studies, we validate the effectiveness and rationality of the proposed simulation method., Comment: 13 pages, 12 figures