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Direct and quantitative assessments of near-infrared light attenuation and spectroscopic detection depth in biological tissues using surface-enhanced Raman scattering

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Med-X 2023年第1期1卷 62-78页

作者： Li Lin Haoqi He Ruiyang Xue Yumin Zhang Ziwen Wang Shuming Nie Jian Ye State Key Laboratory of Systems Medicine for Cancer School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiP.R.China Department of Bioengineering University of Illinois at Urbana-ChampaignIllinoisUSA Shanghai Key Laboratory of Gynecologic Oncology Ren Ji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghaiP.R.China Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghaiP.R.China

Optical imaging and spectroscopic modalities are of broad interest for in-vivo molecular imaging,fluorescence guided cancer surgery,minimally invasive diagnostic procedures,and wearable ***,considerable debate still exists as to how deeply visible and near-infrared(NIR)light could penetrate normal and diseased tissues under clinically relevant *** we report the use of surface-enhanced Raman scattering(SERS)nanotags embedded in ex-vivo animal tissues for direct and quantitative measurements of light attenuation and spectroscopic detection depth at both the NIR-I and NIR-II spectral *** nanotags are well suited for this purpose because of their sharp spectral features that can be accurately differentiated from fluorescence and background *** the first time,the spectroscopic detection depth is quantitatively defined and measured as the maximal thickness of tissues through which the embedded SERS nanotags are still detected at a signal-to-noise ratio(SNR)of three(99.7%confidence level).Based on data from six types of fresh ex-vivo tissues(brain,kidney,liver,muscle,fat,and skin),we find that the maximum detection depth values range from 1—3 mm in the NIR-I window,to 3—6 mm in the NIR-II *** depth values are largely determined by two factors-the intrinsic optical properties of the tissue,and the overall SNRs of the system without the tissue(system SNR,a result of nanotag brightness,instrument efficiency,and data acquisition parameters).In particular,there is an approximately linearlogarithmic relationship between the system SNR and maximum detection ***,the detection of hidden or occult lesions can be improved by three strategies-reducing tissue attenuation,minimizing background noise,and maximizing the system’s performance as judged by SNR.

关键词： Surface-enhanced Raman scattering Near-infrared window Biological detection Detection depth

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Hydrothermally Synthesis of Binary Niznfe2o4-Cnt Nanocomposite for Energy Storage Application

SSRN

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SSRN 2023年

作者： Ghadimi, Laleh Saleh Tabrizi, Amin Goljanian Rezaie, Ehsan Parvini, Elahe Tavakoli, Mahmoud Abouzari-Lotf, Ebrahim Hajalilou, Abdollah Arsalani, Nasser Pahlevani, Majid Department of Electrical and Computer Engineering Queen's University KingstonON Canada Research Laboratory of Polymer Department of Organic and Biochemistry Faculty of Chemistry University of Tabriz Iran Laboratory for Advanced Materials Faculty of Natural Sciences Comenius University Bratislava842 15 Slovakia Soft and Printed Microelectronics Laboratory Institute of Systems and Robotics University of Coimbra Coimbra Portugal Electrochemical Energy Storage Helmholtzstraße 11 UlmD-89081 Germany

Our research aimed to enhance carbon-based electrochemical double-layer capacitors (EDLCs) by incorporating faradic redox processes. We synthesized a Ni0.5Zn0.5Fe2O4-Carbon Nanotube (NZF-CNT) nanocomposite via hydrothermal methods at various pH levels. X-ray diffraction (XRD) analysis at pH 12 confirmed the formation of spinel nickel-zinc ferrite with 15 nm particles. X-ray photoelectron spectroscopy (XPS) verified cation distribution changes, and high-resolution transmission electron microscopy (HRTEM) revealed well-arranged NZF crystals around CNTs. The successful fusion of NZF and CNTs into the nanocomposite framework was demonstrated. NZF-CNT exhibited a remarkable specific capacitance of approximately 368 F/g at 1.25 A/g, surpassing pure ferrite's 110 F/g. Even after 5000 charge/discharge cycles at 1 A/g, it retained 88.5% of its initial capacitance. Our findings showcase the potential of NZF-CNT as a promising material for energy storage devices, offering a unique combination of EDLC and pseudo-capacitive properties. This approach opens new avenues for improving supercapacitor performance and their diverse applications. © 2023, The Authors. All rights reserved.

关键词： Supercapacitor

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Nonparametric Adaptive Control and Prediction: Theory and Randomized Algorithms

Nonparametric Adaptive Control and Prediction: Theory and Ra...

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IEEE Conference on Decision and Control

作者： Nicholas M. Boffi Stephen Tu Jean-Jacques Slotine John A. Paulson School of Engineering and Applied Sciences Harvard University Google Brain Robotics Nonlinear Systems Laboratory Massachusetts Institute of Technology

ISBN: (纸本)9781665436601

A key assumption in the theory of nonlinear adaptive control is that the uncertainty of the system can be expressed in the linear span of a set of known basis functions. While this assumption leads to efficient algorithms, it limits applications to very specific classes of systems. We introduce a novel nonparametric adaptive algorithm that learns an infinite-dimensional parameter density to cancel an unknown disturbance in a reproducing kernel Hilbert space. Surprisingly, the resulting control input admits an analytical expression that enables its implementation despite its underlying infinite-dimensional structure. While this adaptive input is rich and expressive – subsuming, for example, traditional linear parameterizations – its computational complexity grows linearly with time, making it comparatively more expensive than its parametric counterparts. Leveraging the theory of random Fourier features, we provide an efficient randomized implementation which recovers the computational complexity of classical parametric methods while provably retaining the expressiveness of the nonparametric input. In particular, our explicit bounds only depend polynomially on the underlying parameters of the system, allowing our proposed algorithms to efficiently scale to high-dimensional systems. As an illustration of the method, we demonstrate the ability of the algorithm to learn a predictive model for a 60-dimensional system consisting of ten point masses interacting through Newtonian gravitation.

关键词： Uncertainty Conferences Adaptive algorithms Predictive models Prediction theory Prediction algorithms Hilbert space

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Exploration of Canals: a German-Pakistani collaboration in education and research in marine robotics

Exploration of Canals: a German-Pakistani collaboration in e...

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OCEANS

作者： Francesco Maurelli Suleman Mazhar Syed Atif Mehdi Marine Systems and Robotics Jacobs University Bremen Bremen Germany Acoustic Science and Technology Laboratory Harbin Engineering University Harbin Heilongjiang China Center of Robotics University of Central Punjab Lahore Pakistan

ISBN: (纸本)9781665427883

This paper presents a collaborative project between Jacobs University Bremen and University of Central Punjab, supported by the German Academic Exchange Agency - Deutscher Akademischer Austauschdienst (DAAD). It focuses on the partnership activities and how they have been pivotal to support education and research in marine robotics. This is an example of a successful international project, which has contributed to bring together scientists from different backgrounds working for a common goal.

关键词： Jacobian matrices Irrigation Oceans Education Collaboration Robots

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A Haptic Exploration and Surface Classification of Objects with Four Typical Surface Properties

A Haptic Exploration and Surface Classification of Objects w...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Peng Qi Yunfeng Wu Tianliang Yao Bo Lu Yi Sun Jian S. Dai Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai P. R. China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Suzhou Jiangsu China Laboratory of Intelligent Systems Ecole Polytechnique Federale de Lausanne Lausanne Switzerland Department of Mechanical and Energy Engineering College of Engineering Southern University of Science and Technology Shenzhen P. R. China School of Natural Mathematical and Engineering Sciences King's College London

To effectively interact with the physical world, an intelligent robot is required to have the ability to obtain the detailed features of an unknown object. Visual devices are commonly used to detect the global geometry of an object; however, detailed information such as surface properties cannot be identified using these devices. The current study proposes an efficient haptic exploration method to recognize the physical properties of surfaces using an intelligent fingertip. Our surface-following algorithm utilizes the normal force vector and the tangential force vector at the contact point between the fingertip and the target object to predict the moving direction and implement the surface exploration. And a correction index $K$ is introduced to adjust the sliding velocity. The algorithm is proved to be robust and high performance both in simulation and lab experiments. Finally, we propose and explore a haptic prediction neural network, which enables our robot to have an accurate feel through physical interaction. In the classification experiment of four types of objects with different surface properties, the average accuracy of the proposed model is 90.2%.

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Transfer Learning in robotics: An Upcoming Breakthrough? A Review of Promises and Challenges

arXiv

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arXiv 2023年

作者： Jaquier, Noémie Welle, Michael C. Gams, Andrej Yao, Kunpeng Fichera, Bernardo Billard, Aude Ude, Aleš Asfour, Tamim Kragic, Danica Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany KTH Royal Institute of Technology Stockholm Sweden Jožef Stefan Institute Ljubljana Slovenia Learning Algorithms and Systems Laboratory Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland Faculty of Electrical Engineering University of Ljubljana Slovenia

Transfer learning is a conceptually-enticing paradigm in pursuit of truly intelligent embodied agents. The core concept — reusing prior knowledge to learn in and from novel situations — is successfully leveraged by humans to handle novel situations. In recent years, transfer learning has received renewed interest from the community from different perspectives, including imitation learning, domain adaptation, and transfer of experience from simulation to the real world, among others. In this paper, we unify the concept of transfer learning in robotics and provide the first taxonomy of its kind considering the key concepts of robot, task, and environment. Through a review of the promises and challenges in the field, we identify the need of transferring at different abstraction levels, the need of quantifying the transfer gap and the quality of transfer, as well as the dangers of negative transfer. Via this position paper, we hope to channel the effort of the community towards the most significant roadblocks to realize the full potential of transfer learning in robotics. Copyright © 2023, The Authors. All rights reserved.

关键词： Knowledge management

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Effective Somatosensory and Cross-Modal Evaluation in Children with Hemiparesis and Neurotypically developing Children using MSI Caterpillar*

Effective Somatosensory and Cross-Modal Evaluation in Childr...

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Maria Casado-Palacios Kristina Müller Volker Hömberg Giorgia Bertonati Claudio Campus Marco Crcpaldi Antonio Maviglia Monica Gori Unit for Visually impaired People Center for Human Technologies Istituto Italiano di Tecnologia Genova Italy Neuropediatrics St. Mauritius Therapieklinik Meerbusch Dusseldorf Germany Word Federation for Neurorehabitation European Federation of Neurorehabilitation societies Department of Informatics Bioengineering Robotics and Systems Engineering UniGe Genova Italy Electronic Design Laboratory Istituto Italiano di Tecnologia Genova Italy

ISBN: (数字)9798350307993

ISBN: (纸本)9798350308006

Motor function and tactile perception are deeply interconnected. Individuals with paresis serve as an example of this intricate interplay between motor and tactile systems, by showing that motor recovery depends on improvement in the somatosensory function. In the clinical practice, somatosensory assessment tends to be neglected, or, when conducted, faces challenges due to a lack of consistency in methodology, which might also impact the development of effective rehabilitation strategies. Somatosensory and cross-modal perception in children with hemiparesis is particularly underexplored. With this work, using a new version of the MSI Caterpillar, our goal was (1) to contribute to the understanding of somatosensory perception in children with hemiparesis, (2) investigate how cross-modal inter-actions can influence their perceptions, and (3) bridge the gap between theoretical research and practical application, offering new pathways for technological integration in clinical settings. By measuring the reaction times (RTs) in the detection of a tactile signal and the localization of tactile, audio-tactile and visual-tactile stimuli, we effectively detect somatosensory impairments in the more affected arm of children with hemiparesis compared to the non-dominant one of typically developing peers, suggest the presence of cross-modal interactions, and highlight the dominant role of vision in space location. In addition, our data revealed that attraction towards the wrist in the localization of tactile stimuli is a developmental milestone impaired in hemiparesis.

关键词： Somatosensory Wrist Location awareness Visualization Pediatrics Tactile sensors Motors

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Application of graph-curvature features in computer-aided diagnosis for histopathological image identification of gastric cancer

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Intelligent Medicine 2024年第3期4卷 141-152页

作者： Ruilin He Chen Li Xinyi Yang Jinzhu Yang Tao Jiang Marcin Grzegorzek Hongzan Sun Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information EngineeringNortheastern UniversityShenyangLiaoning 110016China Key Laboratory of Intelligent Computing in Medical Image Ministry of EducationNortheastern UniversityShenyangLiaoning 110016China School of Intelligent Medicine Chengdu University of Traditional Chinese MedicineChengduSichuan 610075China International Joint Institute of Robotics and Intelligent Systems Chengdu University of Information TechnologyChengduSichuan 610225China Institute for Medical Informatics University of LuebeckLuebeckGermany Department of Knowledge Engineering University of Economics in KatowiceKatowicePoland Shengjing Hospital of China Medical University ShenyangLiaoning 110136China

Background Histopathology diagnosis is often regarded as the final diagnostic method for malignant tumors;however,it has some *** study explored a computer-aided diagnostic method that can be used to identify benign and malignant gastric cancer using histopathological *** The most suitable process was selected through multiple experiments by comparing multiple meth-ods and features for ***,the U-net was applied to segment the ***,the nucleus was extracted from the segmented image,and the minimum spanning tree(MST)diagram structure that can cap-ture the topological information was *** third step was to extract the graph-curvature features of the histopathological image according to the MST ***,by inputting the graph-curvature features into the classifier,the recognition results for benign or malignant cancer can be *** During the experiment,we used various methods for *** the image segmentation stage,U-net,watershed algorithm,and Otsu threshold segmentation methods were *** found that the U-net method,combined with multiple indicators,was the most suitable for segmentation of histopathological *** the feature extraction stage,in addition to extracting graph-edge and graph-curvature features,several basic im-age features were extracted,including the red,green and blue feature,gray-level co-occurrence matrix feature,histogram of oriented gradient feature,and local binary pattern *** the classifier design stage,we exper-imented with various methods,such as support vector machine(SVM),random forest,artificial neural network,K nearest neighbors,VGG-16,and *** comparison and analysis,it was found that classifica-tion results with an accuracy of 98.57%can be obtained by inputting the graph-curvature feature into the SVM classifier.

关键词： Gastric cancer Graph-curvature feature Image identification

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Autonomous Navigation of Low Cost Underwater Vehicle for Shallow Freshwater Applications

Autonomous Navigation of Low Cost Underwater Vehicle for Sha...

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OCEANS

作者： Syed Atif Mehdi Suleman Mazhar Francesco Maurelli Center of Robotics University of Central Punjab Lahore Pakistan Acoustic Science and Technology Laboratory Harbin Engineering University Harbin Heilongjiang China Marine Systems and Robotics Jacobs University Bremen Bremen Germany

ISBN: (纸本)9781665427883

To perform underwater navigation, a robot has to be designed and developed with multiple sensors and robust mapping and navigation algorithms that can withstand challenging underwater conditions. This paper discusses communication between Pixhawk and Jetson in the case of autonomous navigation and ground station in manual operation mode. The information from IMU and depth sensor is used to perceive the underwater environment by developing a map. The generated map is then used for path planning and autonomous navigation. Experiments performed in a swimming pool environment demonstrate the developed framework’s capabilities to be usable in shallow freshwater scenarios.

关键词： Costs Navigation Oceans Robot sensing systems Path planning Sensors Underwater vehicles

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Efficient Planar Pose Estimation via UWB Measurements

Efficient Planar Pose Estimation via UWB Measurements

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IEEE International Conference on robotics and Automation (ICRA)

作者： Haodong Jiang Wentao Wang Yuan Shen Xinghan Li Xiaoqiang Ren Biqiang Mu Junfeng Wu Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Data Science the Chinese University of HongKong Shenzhen P. R. China College of Control Science and Engineering and the State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou P. R. China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing P. R. China School of Mechatronic Engineering and Automation Shanghai University Shanghai P. R. China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing P. R. China

State estimation is an essential part of autonomous systems. Integrating the Ultra-Wideband (UWB) technique has been shown to correct the long-term estimation drift and bypass the complexity of loop closure detection. However, few works on robotics treat UWB as a stand-alone state estimation solution. The primary purpose of this work is to investigate planar pose estimation using only UWB range measurements. We prove the excellent property of a two-step scheme, which says we can refine a consistent estimator to be asymptotically efficient by one step of Gauss-Newton iteration. Grounded on this result, we design the GN-ULS estimator, which reduces the computation time significantly compared to previous methods and presents the possibility of using only UWB for real-time state estimation.

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