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Cysticercosis of the eye

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International Journal of Ophthalmology(English edition) 2017年第8期10卷 1319-1324页

作者： Rebika Dhiman Saranya Devi Kavitha Duraipandi Parijat Chandra Murugesan Vanathi Radhika Tandon seema sen Dr Rajendra Prasad Centre for Ophthalmic Sciences All India Institute of Medical Sciences New Delhi 110029 India

Cysticercosis is a preventable and eradicable cause of blindness endemic in the Indian subcontinent, South- East Asia and other developing countries. Ocular and orbital cysticercosis has varied presentations depending upon the site of involvement, number of lesion and the host immune response. In this article we present a review of the various clinical manifestations, diagnosis and management protocol for orbital and ocular cysticercosis. Owing to its varied presentation, cysticercosis may pose a diagnostic challenge to the health professionals. Early diagnosis and management can prevent the vision loss and optimize visual outcomes.

关键词： cysticercosis orbital cysticercosis ocular cysticercosis intracameral cysticercosis

Drone-YOLOv7: small target detection in UAV remote sensing images using YOLOv7-tiny with dynamic head

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Optoelectronics Letters 2025年

作者： Yang Ye Yang sen Tong Jigang Wang Zenghui Tianjin University of Technology Department of Electrical Engineering， University of South Africa

In the task of detecting targets in unmanned aerial vehicles （UAVs） aerial images， the challenge arises from small size and wide scale span of targets， making their location， extraction and feature distinction difficult. Similar categories are susceptible to confusion. To address these issues， an improved YOLOv7-tiny aerial detection algorithm is proposed. Firstly， to improve the identification of small targets， a small target detection layer is added while removing the maximum target detection layer to enhance the localization ability of small targets and make the model lightweight. Secondly， a CBAM （Convolutional Block Attention Module） attention mechanism is incorporated at the connection between the backbone and neck to focus on the target area and eliminate interference. Additionally， to further enhance the classification and location capabilities of the targets， the detection head is replaced with a dynamic head （DYHead） with a unified channel number to fuse scale， space and task awareness in a single module. Finally， to overcome the difficulty of extracting features， the neck is replaced with a CS-FPN （Cross-Scale Feature Pyramid Network） structure with cross-scale connections to amplify feature fusion. Comparative experiments on the VisDrone2021 dataset show that the proposed model can improve mAP50and mAP0.5:0.95by 8.3% and 6.1%， respectively， compared to the original YOLOv7-tiny model， and significant improvements are also observed on CARPK and SeaDronesSee datasets.

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Point-voxel dual transformer for LiDAR 3D object detection

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Optoelectronics Letters 2025年

作者： Tong Jigang Yang Fanhang Yang sen Du Shengzhi Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot La-boratory， Tianjin University of Technology， 391 Binshui West Road Department of Electrical Engineering， Tshwane University of Technology

Deep learning for point clouds faces the challenge of their inherent unordered nature， which makes traditional CNN-like methods not directly applicable. However， due to the inherent permutation invariance， transformers provide solutions to unordered points problems faced in LiDAR-based object detection. In this paper， a two-stage LiDAR 3D object detection framework is presented， namely Point-Voxel Dual Transformer (PV-DT3D)， which is a transformer-based method. In the proposed PV-DT3D， point-voxel fusion features are used for proposal refinement. Specifically， in the PV-DT3D， keypoints are sampled from entire point cloud scene and used to encode representative scene features via a proposal-aware voxel set abstraction module. Subsequently， following the generation of proposals by the region proposal networks (RPN)， the internal encoded keypoints are fed into dual transformer encoder-decoder architecture. In 3D object detection， the proposed PV-DT3D is the first to take advantage of both pointwise transformer and channel-wise architecture to capture contextual information from the perspective of spatial and channel dimensions. Experiments conducted on the highly competitive KITTI 3D car detection leaderboard show that， the PV-DT3D achieves superior detection accuracy among state-of-the-art point-voxel-based methods.

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Hyperbolic cosine transformer for LiDAR 3D object detection

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Optoelectronics Letters 2025年

作者： Tong Jigang Yang Fanhang Yang sen Du Shengzhi Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory， Tianjin University of Technology Department of Electrical Engineering， Tshwane University of Technology

Recently， Transformer has achieved great success in computer vision. However， it is constrained because the spatial and temporal complexity grows quadratically with the number of large points in 3D object detection applications from point clouds. Previous point-wise methods are suffering from time consumption and limited receptive fields to capture information among points. To address these limitations， we propose the cosh-attention， which reduces the computation complexity of space and time from the quadratic order to linear order with respect to the number of points. In the cosh-attention， the traditional softmax operator is replaced by non-negative ReLU activation and hyperbolic-cosine-based operator with re-weighting mechanism. Then based on the key component， cosh-attention， we present a two-stage hyperbolic cosine transformer (ChTR3D) for 3D object detection from point clouds. It refines proposals by applying cosh-attention in linear computation complexity to encode rich contextual relationships among points. Extensive experiments on the widely used KITTI dataset and Waymo Open Dataset demonstrate that， compared with vanilla attention， the cosh-attention significantly improves the inference speed with competitive performance. Experiment results show that， among two-stage state-of-the-art methods using point-level features to refine proposals， the proposed ChTR3D is the fastest one.

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Design of a terahertz slotted waveguide array antenna based on photonic crystal

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Optoelectronics Letters 2025年

作者： PAN Wu YE Kuan ZHANG Zhen LI Renpu QIU sen HUANG Lei College of Photoelectronic Engineering， Chongqing University of Posts and Telecommunications Chongqing Municipal Key Laboratory of Photoelectric Information sensing and Transmission Technology， Chongqing University of Posts and Telecommunications Laboratory of Quantum Information Technology， Chongqing University of Posts and Telecommunications

In this paper， a terahertz slotted waveguide array antenna is designed based on photonic crystal， which can realize efficient radiation of terahertz waves. The electromagnetic wave is fed from the rectangular waveguide at the bottom of the antenna， coupled to photonic crystal waveguide through photonic crystal cavity， and radiated outward through slots at the top layer of antenna. The simulation results show that the antenna achieves a peak gain of 13.45dBi at 360 GHz， a half-power beamwidth of 10.9o， and a side lobe level of -13.9dB. The antenna based on photonic crystal has the advantages of low profile， low loss， and high radiation efficiency， which can be applied to terahertz wireless communication systems.

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基于Faster R-CNN和Mask R-CNN的滑坡自动识别研究

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大地测量与地球动力学 2025年第1期45卷 1-4,12页

作者：于宪煜杨森湖北工业大学土木建筑与环境学院武汉市430068

基于高分一号影像,以三峡库区库首段为例,通过目视解译出160个滑坡样本,按照9∶1比例分为训练样本和验证样本,分别利用Faster R-CNN和Mask R-CNN算法构建滑坡自动识别模型。为进一步对比分析不同样本比例下两种模型的性能,分别采用8∶2... 详细信息

基于高分一号影像,以三峡库区库首段为例,通过目视解译出160个滑坡样本,按照9∶1比例分为训练样本和验证样本,分别利用Faster R-CNN和Mask R-CNN算法构建滑坡自动识别模型。为进一步对比分析不同样本比例下两种模型的性能,分别采用8∶2、7∶3、6∶4的样本比例进行计算。研究结果表明,Mask R-CNN模型识别结果准确率、召回率和F 1分数等3项指标均优于Faster R-CNN;且经过交叉验证,证明Mask R-CNN模型的性能更为稳定。

关键词：深度学习滑坡识别 Mask R-CNN Faster R-CNN 交叉验证

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Enhanced subacute ischemic stroke treatment via multistage drug delivery system design for combination therapy

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Science China Chemistry 2025年

作者： Xihan Xu Juan-Juan Li Jiamin Li Hui-Yan Zhang Yilin Qi Bing-sen Shi Tianqi Li Shan-Shan Su Weitao Zhao Chang Chen Zhongying Gong Huiyu Liu Ke-Rang Wang Dong-Sheng Guo Xue Xue State Key Laboratory of Medicinal Chemical Biology College of Pharmacy Nankai University College of Chemistry State Key Laboratory of Elemento-Organic Chemistry Key Laboratory of Functional Polymer Materials (Ministry of Education) Frontiers Science Center for New Organic Matter Collaborative Innovation Center of Chemical Science and EngineeringNankai University College of Chemistry and Materials Science State Key Laboratory of New Pharmaceutical Preparations and Excipients Key Laboratory of Medicinal Chemistry and Molecular Diagnosis (Ministry of Education) Key Laboratory of Chemical Biology of Hebei Province Hebei Research Center of the Basic Discipline of Synthetic Chemistry Hebei University Department of Neurology Tianjin First Central Hospital School of Medicine Nankai University Beijing Advanced Innovation Center for Soft Matter Science and Engineering State Key Laboratory of Organic-Inorganic Composites Beijing Laboratory of Biomedical Materials Bionanomaterials & Translational Engineering Laboratory Beijing Key Laboratory of BioprocessBeijing University of Chemical Technology

The management of acute ischemic stroke remains challenging due to its abrupt onset and the narrow treatment window,resulting in high rates of disability and *** therapy for neuroprotection and neurorepair strategies provided new hopes for subacute stroke *** we designed a multistage nanodelivery system that matches the unique microenvironment of the subacute phase of stroke,which utilizes calixarene as a building block to effectively load the neuroprotective drug *** calixarene is designed with glycosidic linkages targeting the glucose transporter 1 (GLUT1)on the blood-brain barrier (BBB) and azo bonds that are responsive to hypoxic ***,the decomposed calixarene molecules themselves possess intrinsic bio-activation to modulate inflammatory responses,achieving a multistage therapeutic approach that transitions from targeting to release and finally to *** approach combines anti-inflammation and neuroprotection,providing a multi-level treatment *** system was validated in a rat model of permanent middle cerebral artery occlusion (pMCAO),demonstrating that intravenous administration of the nanodelivery system repairs brain damage and improves motor function 24 h post-pMCAO *** work offers a precise and integrative strategy for stroke patients missing the acute therapy window to improve functional recovery and enhance the effect of comprehensive treatment.

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Real-time recognition of human lower-limb locomotion based on exponential coordinates of relative rotations

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Science China(Technological Sciences) 2021年第7期64卷 1423-1435页

作者： XU sen DING Ye State Key Laboratory of Mechanical System and Vibration School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai200240China

This paper proposes a data-driven method using a parametric representation of relative rotations to classify human lower-limb locomotion, which is designed for wearable robots. Three Inertial measurement units(IMUs) are mounted on the subject's waist,left knee, and right knee, respectively. Features for classification comprise relative rotations, angular velocities, and waist acceleration. Those relative rotations are represented by the exponential coordinates. The rotation matrices are normalized by Karcher mean and then the Support Vector Machine(SVM) method is used to train the data. Experiments are conducted with a time-window size of less than 40 ms. Three SVM classifiers telling 3, 5 and 6 rough lower-limb locomotion types respectively are trained, and the average accuracies are all over 98%. With the combination of those rough SVM classifiers, an easy SVMbased ensembled-system is proposed to classify 16 fine locomotion types, achieving the average accuracy of 98.22%, and its latency is 18 ms when deployed to an onboard computer.

关键词： locomotion recognition exponential coordinate relative rotation support vector machine

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A novel(2+1)-dimensional integrable KdV equation with peculiar solution structures

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Chinese Physics B 2020年第8期29卷 176-181页

作者： sen-Yue Lou School of Physical Science and Technology Ningbo UniversityNingbo 315211China

The celebrated(1+1)-dimensional Korteweg de-Vries(KdV)equation and its(2+1)-dimensional extension,the Kadomtsev-Petviashvili(KP)equation,are two of the most important models in physical *** KP hierarchy is explicitly written out by means of the linearized operator of the KP equation.A novel(2+1)-dimensional KdV extension,the cKP3-4 equation,is obtained by combining the third member(KP3,the usual KP equation)and the fourth member(KP4)of the KP *** integrability of the cKP3-4 equation is guaranteed by the existence of the Lax pair and dual Lax *** cKP3-4 system can be bilinearized by using Hirota's bilinear operators after introducing an additional auxiliary *** solutions of the cKP3-4 equation possess some peculiar and interesting properties which are not valid for the KP3 and KP4 *** instance,the soliton molecules and the missing D'Alembert type solutions(the arbitrary travelling waves moving in one direction with a fixed model dependent velocity)including periodic kink molecules,periodic kink-antikink molecules,few-cycle solitons,and envelope solitons exist for the cKP3-4 equation but not for the separated KP3 equation and the KP4 equation.

关键词： (2+1)-dimensional KdV equations Lax and dual Lax pairs soliton and soliton molecules D’Alembert type waves

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