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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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Development of a Portable Face Recognition System with GPS Integration Using Raspberry Pi

Development of a Portable Face Recognition System with GPS I...

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Computer Sciences, Engineering, and Technology Innovation (ICoCSETI), International Conference on

作者： Muhammad Nurul Puji Winda Astuti Rahmanda Wulandari William Jonathan Edwards Telaumbanua Computer Engineering Department Automotive & Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Industrial Engineering Department Business Engineering Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

Face recognition systems are a rapidly evolving computer vision technology capable of accurately identifying faces. Additionally, the development of SBCs (Single Board Computers) has advanced significantly, enabling fast computational processing. The integration of face recognition systems on SBCs enables the creation of embedded face recognition systems. With the addition of GPS devices, it is possible to develop a mobile embedded face recognition system, which can contribute to enhancing infrastructure security and sustainability. This research demonstrates that A portable face recognition system based on Raspberry Pi 5 and a GPS module has been successfully developed. The system successfully detects target faces and able to send location coordinates through the Telegram application. Testing results show that the system's effective range is 1 to 4 meters, with an effective angle of 80° to 100° (from the left horizontal). The tests also indicate that systems without video output generally have higher FPS compared to systems displaying video.

关键词： Meters Computer vision Technological innovation Face recognition Streaming media Real-time systems Sustainable development Optimization Global Positioning System Testing

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Automatic Anti-Swing Gantry Crane Based on Gradient Descent Optimization Proportional Integrated Derivative (PID): A Comparison Simulation and Real Experiment

Automatic Anti-Swing Gantry Crane Based on Gradient Descent ...

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2023 International Conference on Electrical Engineering and Informatics, ICEEI 2023

作者： Qadri, Munzir Harjanto, Danang Karuna Miharja, Jonathan Astuti, Winda Mariana, Yosica Tan, Sofyan Solihin, Mahmud Iwan University of Muhammadiyah Jakarta Engineering Faculty Mechanical Engineering Department Jakarta10510 Indonesia Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Binus Aso School of Engineering Bina Nusantara University Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Ucsi University Departement of Mechanical & Mechatronics Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350381290

Transporting payload with precise swing angles and transfer times poses a challenging task in building construction, which is why gantry crane systems are extensively utilized. Various control strategies, including open-loop and closed-loop systems, have been proposed to tackle this issue. However, most of these controllers rely on a model and parameters specific to the crane system, making the process of modeling and parameter identification complex and time-consuming. To address this challenge, this work presents a practical and simulation control method for automatic gantry cranes, which is evaluated simulation and experimentally. The lab-scale Gantry crane is developed in this work, which consists of mechanical and electrical parts. Proportional Integral and Derivative (PID) and Proportional Derivative (PD) controllers which applied optimization method are implemented in the electrical part of the system. The PID and PD controller applied in controlled the position and swing angle, respectively. The Gradient Decent optimization method is the best optimization method in determining the parameter of the controller, since it has the best simulation performance in the output of the system. The experimental result is developed and compared between simulation and lab-scale Gantry crane hardware implementation part. The performance of experimental results is shown appropriately approaching the performance of the simulation result, with the approximately settling time. © 2023 IEEE.

关键词： Proportional control systems

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Analyze and Predict Car Accidents Using Different Machine Learning Algorithms

Analyze and Predict Car Accidents Using Different Machine Le...

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International Conference on Information Management and Technology (ICIMTech)

作者： Farrell Putra Harimanto Chris Andrew Henry William Muhammad Zacky Asy'ari Samuel Albert Artanto Muhammad Nurul Puji Computer Engineering Department Automotive & Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

Traffic accidents can occur from various factors, ranging from the driver themselves to problems with the vehicle. Road and traffic accidents are the most significant factor of fatalities in the world. Most of the causes of accidents are the drivers themselves. Poor physical and mental conditions can significantly impact how to drive. The driving experience is also important; the longer the driver has been driving, the more professional he will be, and vice versa. Smart City solutions can predict the severity of accidents and give information to the authorities in order to reduce the number of fatalities. This paper investigates the factors that may lead to an accident on the road. By looking at data collected from traffic-related accidents and then visualizing it to make it easy to analyze; then, from this data, we will predict the causes of traffic accidents so they can be avoided. The best algorithm based on accuracy, MAE and RMSE is Random Forest Classifier with 0.8461, 0.1663 and 0.4376, respectively.

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Automation Lamp Healing Application based on Face Expression Identification System using Convolution Neural Network (CNN)

Automation Lamp Healing Application based on Face Expression...

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International Conference on Electrical Engineering and Informatics, ICEEI

作者： Devin Onil Saduki Simangunsong Mahesh Muhammad Nurul Puji Winda Astuti Computer Engineering Department Automotive and Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

The disruption of routines, education, recreation, as well as concerns about family income and health, has left many young people feeling fearful, angry, and worried about their future. In this system, a smart system will be developed that can capture, process, and interpret facial expressions so that a person's emotions can be easily and accurately identified, which is one of the best solutions. The system will use artificial intelligence that has been trained beforehand using suitable datasets. In the processed of developing the system, Face image with the size of 48 x 48 x 1 became the input of the system, processes by Convolution layer using Relu activation function. The activation function used in the output layer is softmax because it is suitable for more than 2 classifications. by applying CNN based on Adam optimization which have result on 98.96% and 70%, for training and testing accuracy, respectively. Furthermore, the system accurately turn-on the healing lamp based on the emotion identified.

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Walk With Me: Socially Acceptable Speed and Distance Control for Mobile Wayfinding Robots

Walk With Me: Socially Acceptable Speed and Distance Control...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Karl D. Hansen Anders Clement Hans Christian Østgård Larsen Jonas Andersen Oliver Beyer Lauritsen Katrine Møller-Rahbek Department of Materials and Production Aalborg University Aalborg Denmark Students of the Robotics MSc Program at Aalborg University Aalborg Denmark

Robots can help people find their way around in complex buildings and environments. Robots are embodied, which makes it more intuitive for users to follow them around compared to, e.g., colored lines on the floor. However, they need to be socially intelligent for people to accept them. Like people, robots should keep a comfortable distance to its users when *** investigate the optimization of a guiding robot’s speed and distance when guiding to improve the user experience. Our findings indicate a correlation between the user’s speed and the distance they keep from the robot, which can be utilized to control the robot’s speed.A person tracking system is implemented on a Spot quadruped mobile robot platform from Boston Dynamics, using the on-board depth and 2D cameras plus an Intel NUC and a Jetson Nano for processing. The system uses the Mobilenet-SSDv2 CNN for user detection and Kalman filtering for *** from human-robot interaction tests on footpaths at Aalborg University is analyzed to create a linear model of the speed-distance relationship. Based on this, a control law is proposed and tested, demonstrating the ability to build a controller that allows the person following the robot to set the desired velocity of the robot.

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Car Engine and Chassis Assembly Training Simulation Using VR Technology

Car Engine and Chassis Assembly Training Simulation Using VR...

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International Conference on Electrical Engineering and Informatics, ICEEI

作者： Miguel Yehezkiel Noya Muhammad Zacky Asy'ari Christian Bernard Kuswandi Zener Lie Sukra Computer Engineering Department Automotive and Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

The process of educating and learning about the automotive industry is still ongoing, and one of the most effective techniques is the provision of direct practice. Such a system is regarded as effective, albeit with certain downsides. One of them is the restricted area and time required to conduct the exercise, as well as the significant risk of accidents during vehicle engine assembly. Based on these justifications, Vehicle Engine Assembly Simulation with Virtual Reality (VR) Technology is now available as an alternate means of educating students about the automotive industry, particularly car engine assembly. This concept employs a virtual environment that allows users to perceive the automobile world in real time through an immersive experience. VR allows users to directly disassemble automobile engines. This virtual reality application was created utilizing the Oculus Quest 2 platform and the Unity Game Engine.

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Development of a Lightweight Real-Time Application for Dynamic Hand Gesture Recognition

Development of a Lightweight Real-Time Application for Dynam...

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IEEE International Conference on Mechatronics and Automation

作者： Oluwaleke Yusuf Maki Habib Department of Mechanical Engineering Robotics Control and Smart Systems (RCSS) Program The American University in Cairo (AUC) Cairo Egypt

Hand Gesture Recognition (HGR) is a form of perceptual computing with applications in human-machine interaction, virtual/augmented reality, and human behavior analysis. Within the HGR domain, several frameworks have been developed with different combinations of input modalities and network architectures with varying levels of efficacy. Such frameworks maximized performance at the expense of increased hardware and computational requirements. These drawbacks can be tackled by transforming the relatively complex dynamic hand gesture recognition task into a simpler image classification task. This paper presents a skeleton-based HGR framework that implements data-level fusion for encoding spatiotemporal information from dynamic gestures into static representational images. Said static images are subsequently processed by a custom, end-to-end trainable multi-stream CNN architecture for gesture classification. Our framework reduces the hardware and computational requirements of the HGR task while remaining competitive with the state-of-the-art on the CNR, FPHA, LMDHG, SHREC2017, and DHG142S benchmark datasets. We demonstrated the practical utility of our framework by creating a lightweight real-time application that makes use of skeleton data extracted from RGB video streams captured by a standard inbuilt PC webcam. The application operates successfully with minimal CPU and RAM footprint while achieving 93.46% classification accuracy with approximately 2s latency at 15 frames per second.

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Quantitative Analysis of Ankle Spasticity Through Electromyography Signal

Quantitative Analysis of Ankle Spasticity Through Electromyo...

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Medical Technologies National Conference (TIPTEKNO)

作者： Ayse Gurluk Hafiz Muhammad Bilal Elif Hocaoglu Living Robotics Laboratory Graduate School of Health Sciences Physiotherapy and Rehabilitation Program Istanbul Medipol University Istanbul Türkiye Living Robotics Laboratory Graduate School of Engineering and Natural Sciences Electrical-Electronics Engineering and Cyber-Systems Program Istanbul Medipol University Istanbul Türkiye Department of Electrical and Electronics Engineering Living Robotics Laboratory Istanbul Medipol University Istanbul Türkiye

ISBN: (数字)9798331529819

ISBN: (纸本)9798331529826

This study presents a more accurate evaluation method for assessing ankle spasticity compared to conventional goniometric techniques by utilizing measurements obtained from Inertial Measurement Units (IMU) and surface electromyography (sEMG) devices. Integrating IMU and EMG sensors provides substantial benefits for accurately determining the range of motion (ROM) associated with spasticity during targeted movements. In this study, the proposed method provides precise measurement and an objective evaluation of onset time detection of antagonistic muscle co-contraction, and accordingly the ROM of the actuated joint. Moreover, the implementation of cost-effective wearable sensors enables the monitoring of muscle spasticity in clinical environments and can be particularly valuable in regions with limited access to experienced therapists, providing a more efficient approach to tracking spasticity levels.

关键词： Ankle Measurement units Inertial navigation Muscles Electromyography Sensors Reliability Motion control Read only memory Monitoring

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Unified Editing of Panorama, 3D Scenes, and Videos Through Disentangled Self-Attention Injection

arXiv

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arXiv 2024年

作者： Kwon, Gihyun Park, Jangho Ye, Jong Chul Kim Jaechul Graduate School of AI KAIST Korea Republic of Department of Bio and Brain Engineering KAIST Korea Republic of Robotics Program KAIST Korea Republic of

While text-to-image models have achieved impressive capabilities in image generation and editing, their application across various modalities often necessitates training separate models. Inspired by existing method of single image editing with self attention injection and video editing with shared attention, we propose a novel unified editing framework that combines the strengths of both approaches by utilizing only a basic 2D image text-to-image (T2I) diffusion model. Specifically, we design a sampling method that facilitates editing consecutive images while maintaining semantic consistency utilizing shared self-attention features during both reference and consecutive image sampling processes. Experimental results confirm that our method enables editing across diverse modalities including 3D scenes, videos, and panorama images. © 2024, CC BY.

关键词： Semantics

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