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Convergent effects of peptides on the initiation of feeding motor programs in the mollusk Aplysia

Journal of Neurophysiology 2025年第5期133卷 1368-1379页

作者： Evans, Colin G. Barry, Michael A. Reaver, Carrie N. Patel, Paras R. Chestek, Cynthia A. Perkins, Matthew H. Jing, Jian Cropper, Elizabeth C. Department of Neuroscience Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York NY United States Department of Biomedical Engineering Biointerfaces Institute University of Michigan Ann Arbor MI United States Department of Electrical Engineering and Computer Science Neurosciences Program Robotics Program University of Michigan Ann Arbor MI United States State Key Laboratory of Pharmaceutical Biotechnology Institute for Brain Sciences Chemistry and Biomedicine Innovation Center Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology Advanced Institute for Life Sciences School of Life Sciences Nanjing University Nanjing China

Neuropeptides configure the feeding network of Aplysia. For example, egestive activity is promoted by small cardioactive peptide (SCP), and ingestive activity is promoted by a combination of feeding circuit activating peptide (FCAP) and cerebral peptide 2 (CP-2). In addition, SCP and FCAP/CP-2 have a common network effect that does not contribute to motor program specification. They increase the excitability of an interneuron, B63. In this report, we further characterized the effects of peptides on B63. We performed voltage-clamp experiments and used a step protocol to look at steady-state currents. We found that SCP and FCAP/CP-2 both induced an inward current that was virtually absent in low-sodium saline. Previous work has established that B63 is unusual in the feeding circuit in that subthreshold depolarizations are autonomously generated that can trigger motor programs. Here, we show that this autonomous activity is more frequent in the presence of peptides. Previous studies have also shown that activity of the feeding central pattern generator (CPG) can be initiated by neurons that excite B63, e.g., by cerebral buccal interneuron 2 (CBI-2), a projection neuron that triggers biting-like motor programs. Here, we show that the latency of CBI-2-induced activity is decreased by stimulation of the esophageal nerve (EN) (which releases endogenous SCP). These results, taken together with previous results, indicate that peptides that act divergently to configure network activity additionally act convergently to promote motor program induction. We present data that suggest that this arrangement facilitates brief switches between ingestive and egestive motor activity. © 2025 The Authors.

关键词： central pattern generator invertebrate modulation motor program neuropeptide

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Evaluation of Cuffless Blood Pressure Estimation Accuracy at Each Heartbeat During Exercise 6th

Evaluation of Cuffless Blood Pressure Estimation Accuracy a...

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6th International Conference on Biomedical and Health Informatics, ICBHI 2024

作者： Ono, Kouki Maeda, Yuka Yoshimura, Takumi Huang, Ming Tamura, Toshiyo Master’s Program in Intelligent and Mechanical Interaction Systems University of Tsukuba Tsukuba305-8577 Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba305-8577 Japan Medical and Welfare Engineering Tokyo Metropolitan College of Industrial Technology Tokyo116-8523 Japan School of Data Science Nagoya City University Nagoya467-8501 Japan Future Robotics Organization Waseda University Tokyo169-8050 Japan

ISBN: (纸本)9783031863226

Continuous blood pressure monitoring is crucial because of its dynamic nature, influenced by factors such as physical activity and mental stress. Although cuffless blood pressure estimation is a promising technique for continuous monitoring, its accuracy during drastic fluctuations, especially during exercise, remains insufficiently validated. In this study, we evaluated a simple Pulse Arrival Time based blood pressure estimation method and several improved methods for sharp fluctuations induced by exercise. Sixteen subjects in the experiment, with data from 13 valid for analysis. The proposed method achieved an average correlation of 0.527 in systolic blood pressure, suggesting that cuffless blood pressure estimation could be applied to estimate continuous blood pressure variability during exercise. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Blood pressure

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Material informatics-driven insights into brain cancer nanocarriers: A bibliometric comparison of PLGA vs. liposomes

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OpenNano 2025年 21卷

作者： Makalew, Brilly Andro Abrori, Syauqi Abdurrahman Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta 11480 Indonesia

This study explores a comparative analysis of PLGA nanoparticles and liposomes as potential carriers for brain cancer drug delivery, with a special focus on how material informatics enhances their design, biocompatibility, and drug release profiles to improve treatment efficacy and contribute to sustainable health outcomes. The investigation employed a bibliometric analysis using Scopus and VOSviewer to uncover the role of material informatics in optimizing these nanocarriers. The analysis revealed that material informatics, particularly through the application of machine learning and molecular dynamics simulations, significantly optimizes the performance of both PLGA nanoparticles and liposomes. The results highlighted distinct strengths of each nanocarrier: PLGA nanoparticles excel in biodegradability, while liposomes offer superior drug encapsulation capabilities. However, material informatics techniques bridged these enhancing drug release kinetics, stability, and biocompatibility. These improvements are crucial for effective delivery across the blood-brain barrier, a major challenge in brain cancer treatment. The integration of computational modelling, machine learning, and high-throughput screening enabled by material informatics is shown to be a key factor in advancing the design and optimization of these nanocarriers. By leveraging these tools, researchers can develop more personalized and efficient drug delivery systems tailored to address the specific challenges of glioblastoma therapy, ultimately contributing to sustainable health outcomes © 2024 The Author(s)

关键词： Bibliometric analysis Brain cancer Drug delivery Liposomes Material informatics Nanocarriers PLGA nanoparticles VOSviewer

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Dual-UNet: An End-to-End Deep Learning Framework for the Automatic Chronic Diabetic Wound Segmentation

Dual-UNet: An End-to-End Deep Learning Framework for the Aut...

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Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Mustafa Alhababi Gregory Auner Hafiz Malik Lubna Alazzawi Muteb Aljasem Electrical and Computer Engineering Wayne State University Detroit MI USA Department of Smart Sensors and Integrated Microsystems Program Wayne State University Detroit MI USA Electrical and Computer Engineering University of Michigan-Dearborn Dearborn MI USA Electronics and Computer Engineering & Robotics Engineering Bowling Green State University Bowling Green OH USA

ISBN: (数字)9798350353839

ISBN: (纸本)9798350353846

Foot ulcers are one of the chronic wounds commonly occurring in diabetic patients and are associated with a high risk of major or minor amputations. Evaluation and measurement of such wounds are done manually by experts to assess the wound healing and suggest further treatment. Manual assessment methods can cause infections at times and are less feasible in the existence of pandemic situations. The development of artificial intelligence has brought a revolution in many domains of medical imaging. Deep learning-based computer-aided approaches can be applied to assist clinicians in assessing and monitoring chronic wounds. Wound segmentation helps to measure wound area which is useful for assessing its healing progress. In this research work, a deep learning-based segmentation method, namely Dual-UNet is presented for precisely segmenting the diabetic foot ulcers images. The foot ulcer images are passed to Dual-UNet to generate the mask image having the segmented wound area. We proposed two modified UNets each having a customized encoder and decoder with skip connections, atrous spatial pyramid pooling (ASPP) block, and output block to improve the segmentation results. We assessed our framework by performing experimentation on two benchmark datasets, named the foot ulcer segmentation (FUSeg) challenge and the AZH segmentation dataset. Additionally, we have also assessed our Dual-UNet for cross-corpora validation to demonstrate the generalization capability of the proposed approach. The qualitative and quantitative results highlight the accuracy and effectiveness of the Dual-UN et framework for segmenting chronic diabetic wounds. Future research should focus on the development of large and diverse wound datasets and improving the results for cross-corpora evaluation.

关键词： Deep learning Image segmentation Pandemics Computational modeling Manuals Wounds Diabetes Decoding Information technology Monitoring

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Goal-Conditioned Reinforcement Learning Approach for Autonomous Parking in Complex Environments

Goal-Conditioned Reinforcement Learning Approach for Autonom...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Taeyoung Kim Taemin Kang Seungah Son Kuk Won Ko Dongsoo Har CCS Graduate School of Mobility Korea Advanced Institute of Science and Technology(KAIST) Daejeon Rep. of Korea The Robotics Program Korea Advanced Institute of Science and Technology(KAIST) Daejeon Rep. of Korea Department of Future Mobility Engineering Halla University Wonju Rep. of Korea

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

In complex urban environments, autonomous vehicle parking is challenged by irregularly parked cars, static obstacles, and narrow spaces. Traditional parking methods are often limited to well-structured parking lots and fail to adapt to unstructured scenarios like alleyways with obstacles and randomly positioned vehicles. This paper addresses this limitation by applying goal-conditioned reinforcement learning to enable autonomous vehicles to park in congested environments based on specified target positions and orientations. A custom simulation environment is developed using Pygame to simulate parking scenarios across four progressive levels of difficulty, with obstacles to test adaptability. Three RL algorithms, SAC, HER, and an improved HER variant, are implemented to compare the performance in the simulation environment. Experimental results demonstrate that the proposed approach significantly improves parking success rates and trajectory efficiency in complex scenarios, contributing to robust, adaptable parking solutions for autonomous vehicles in real-world applications.

关键词： Training Space vehicles Three-dimensional displays Urban areas Reinforcement learning Trajectory Reliability Vehicle dynamics Autonomous vehicles Testing

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Reward Generation via Large Vision-Language Model in Offline Reinforcement Learning

arXiv

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arXiv 2025年

作者： Lee, Younghwan Luu, Tung M. Lee, Donghoon Yoo, Chang D. Electrical Engineering KAIST Daejeon Korea Republic of Robotics Program KAIST Daejeon Korea Republic of

In offline reinforcement learning (RL), learning from fixed datasets presents a promising solution for domains where real-time interaction with the environment is expensive or risky. However, designing dense reward signals for offline dataset requires significant human effort and domain expertise. Reinforcement learning with human feedback (RLHF) has emerged as an alternative, but it remains costly due to the human-in-the-loop process, prompting interest in automated reward generation models. To address this, we propose Reward Generation via Large Vision-Language Models (RG-VLM), which leverages the reasoning capabilities of LVLMs to generate rewards from offline data without human involvement. RG-VLM improves generalization in long-horizon tasks and can be seamlessly integrated with the sparse reward signals to enhance task performance, demonstrating its potential as an auxiliary reward signal. © 2025, CC BY.

关键词： Reinforcement learning

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Distributed Certifiably Correct Range-Aided SLAM

arXiv

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arXiv 2025年

作者： Thoms, Alexander Papalia, Alan Velasquez, Jared Rosen, David M. Narasimhan, Sriram Sensing and Robotics for Infrastructure Laboratory University of California Los Angeles Los Angeles United States The Massachusetts Institute of Technology The MIT-WHOI Joint Program in Oceanography/Applied Ocean Science & Engineering Woods Hole CambridgeMA United States Robust Autonomy Lab Northeastern University BostonMA United States

Reliable simultaneous localization and mapping (SLAM) algorithms are necessary for safety-critical autonomous navigation. In the communication-constrained multi-agent setting, navigation systems increasingly use point-to-point range sensors as they afford measurements with low bandwidth requirements and known data association. The state estimation problem for these systems takes the form of range-aided (RA) SLAM. However, distributed algorithms for solving the RA-SLAM problem lack formal guarantees on the quality of the returned estimate. To this end, we present the first distributed algorithm for RA-SLAM that can efficiently recover certifiably globally optimal solutions. Our algorithm, distributed certifiably correct RA-SLAM (DCORA), achieves this via the Riemannian Staircase method, where computational procedures developed for distributed certifiably correct pose graph optimization are generalized to the RA-SLAM problem. We demonstrate DCORA’s efficacy on real-world multi-agent datasets by achieving absolute trajectory errors comparable to those of a state-of-the-art centralized certifiably correct RA-SLAM algorithm. Additionally, we perform a parametric study on the structure of the RA-SLAM problem using synthetic data, revealing how common parameters affect DCORA’s performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Navigation systems

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Dual Quaternion-Based Control for Dynamic Robot Formations

Dual Quaternion-Based Control for Dynamic Robot Formations

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Juan I. Giribet Harrison Neves Marciano Ignacio Mas Alejandro S. Ghersin Daniel Khede Dourado Villa Mário Sarcinelli-Filho Artificial Intelligence and Robotics Lab. (LINAR) Universidad de San Andrés Argentina CONICET - Consejo Nacional de Investigaciones Científicas y Técnicas Argentina Graduate Program on Electrical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil Instituto Tecnológico de Buenos Aires Argentina

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This paper evaluates a dual quaternion-based control algorithm designed to manage dynamic changes in the number of vehicles in robot formations. By defining a virtual structure, the algorithm coordinates the formation's position, orientation, and shape parameters, ensuring seamless transitions when the number of vehicles changes. The approach enables a low-level controller to calculate commands for individual robots while maintaining the overall formation integrity. The strategy's performance is analyzed through simulations and experimental results, demonstrating its effectiveness in handling variations in the number of vehicles of robotic formations.

关键词： Geometry Analytical models Shape Robot kinematics Heuristic algorithms Quaternions Transportation Autonomous aerial vehicles Stability analysis Vehicle dynamics

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Fixed Frequency, Variable Amplitude (FiFVA) Actuation Systems for Micro Aerial Vehicles

Fixed Frequency, Variable Amplitude (FiFVA) Actuation System...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ratti, Jayant Jones, Emanuel Vachtsevanos, George Robotics Program School of Electrical and Computer Engineering USA

ISBN: (纸本)9781612843858

Micro Aerial Vehicles (MAVs) have gained a significant amount of research lately, with a number of universities and industry sponsors paving the way with micro flying robots to perform Intelligence, Surveillance and Reconnaissance (ISR) Missions. However, much of the work done in flapping wing MAVs till date has not shown performance improvements over their Vertical Take Off and Landing (VTOL), rotary-wing counterparts. Research and development over the years has shown that insects and birds have unmatched flying capabilities in the Low Reynolds Number Regime. Their phenomenal flight performance is attributed to among others the highly energy efficient actuation systems and their power to weight ratios. The paper proposes and illustrates new and energy-efficient actuation mechanisms and incorporating them into MAVs. The paper begins by elaborating on the background of our research and the need for energy efficiency in MAVs;followed by showcasing resonant, elastic/restorative actuation mechanisms and their control methodology to reduce flight-actuation energy requirements. In conclusion, the paper contrasts and compares all the actuation systems for power intake, scalability and mechanical complexity.

关键词： Actuators Coils Couplings Frequency modulation Gears Springs Switches

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OriSnake: Design, Fabrication, and Experimental Analysis of a 3-D Origami Snake Robot

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IEEE robotics and Automation Letters 2018年第3期3卷 1993-1999页

作者： Luo, Ming Yan, Ruibo Wan, Zhenyu Qin, Yun Santoso, Junius Skorina, Erik H. Onal, Cagdas D. Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States

Snake robots offer a useful and unique mobility platform for search-and-rescue applications. However, existing prototypes made of rigid links and joints are hampered by a lack of flexibility that limits their utility in highly cluttered, maze-like environments, and their heavy weight limits their energy-efficiency and performance in three-dimensional (3-D) tasks. To address these challenges, this letter presents a new approach using cylindrical, origami continuum modules driven by internal cables and electric motors, as well as a local feedback control system on each module. Thus, we can distribute actuation, sensing, and control for highly scalable soft robotic continuum origami systems. Using this approach, we develop a 3-D origami robotic snake that is able to locomote using lateral undulation and sidewinding gaits similar to those used by biological snakes. The proposed snake robot is a continuously deformable, lightweight, modular, and low cost robotic system made of a folded thin plastic body. We detail the design, fabrication, and control of this first 3-D origami robotic snake prototype, focusing on the analysis of locomotion parameters for each gait. We experimentally search for the optimal parameters for both types of locomotion, with maximum speeds characterized as 40.5 mm/s (0.1 body-lengths per second) for lateral undulation and 35 mm/s (0.09 body-lengths per second) for sidewinding locomotion. © 2016 IEEE.

关键词： Fabrication

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