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FRESH-Printing of a Multi-actuator Biodegradable Robot Arm for Articulation and Grasping 12th

FRESH-Printing of a Multi-actuator Biodegradable Robot Arm f...

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Proceedings of the 12th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2023

作者： Williamson, Avery S. Sun, Wenhuan Sukhnandan, Ravesh Coffin, Brian Majidi, Carmel Feinberg, Adam Yao, Lining Webster-Wood, Victoria A. Department of Mechanical Engineering Carnegie Mellon University PittsburghPA15218 United States Department of Biomedical Engineering Carnegie Mellon University PittsburghPA15218 United States Department of Materials Science and Engineering Carnegie Mellon University PittsburghPA15218 United States Human-Computer Interaction Institute School of Computer Science Carnegie Mellon University PittsburghPA15218 United States McGowan Institute for Regenerative Medicine Carnegie Mellon University PittsburghPA15218 United States

ISBN: (纸本)9783031388569

The recent popularity of soft robots for marine applications has established a need for the reliable fabrication of actuators that enable locomotion, articulation, and grasping in aquatic environments. These actuators should also reduce the negative impact on sensitive ecosystems by using biodegradable materials such as organic hydrogels. Freeform Reversible Embedding of Suspended Hydrogels (FRESH) printing can be used for additive manufacturing of small-scale biologically derived, marine-sourced hydraulic actuators by printing thin-wall structures out of sustainably sourced calcium-alginate hydrogels. However, controlling larger alginate robots with complex geometries and multiple actuation mechanisms remains challenging due to the reduced strength of such soft structures. For tethered hydrogel hydraulic robots, a direct interface with fluid lines is necessary for actuation, but the drag forces associated with tethered lines can quickly overcome the actuation force of distal and extremity structures. To overcome this challenge, in this study, we identify printing parameters and interface geometries to allow the working fluid to be channeled to distal components of FRESH-printed alginate robots and demonstrate a proof-of-concept biodegradable robotic arm for small object manipulation and grasping in marine environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Biodegradability

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BallistoBud: Heart Rate Variability Monitoring using Earbud Accelerometry for Stress Assessment 25

BallistoBud: Heart Rate Variability Monitoring using Earbud ...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Islam, Md Saiful Rahman, Md Mahbubur Bin Morshed, Mehrab Lin, David J Li, Yunzhi Zhou, Hao Mendes, Wendy Berry Kuang, Jilong Department of Computer Science University of Rochester RochesterNY United States Digital Health Team Samsung Research America Mountain ViewCA United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA United States Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States The Pennsylvania State University State collegePA United States Psychology Yale University New HavenCT United States

ISBN: (纸本)9798400713941

This paper examines the potential of commercial earbuds for detecting physiological biomarkers like heart rate (HR) and heart rate variability (HRV) for stress assessment. Using accelerometer (IMU) and photoplethysmography (PPG) data from earbuds, we compared these estimates with reference electrocardiogram (ECG) data from 81 healthy participants. We explored using low-power accelerometer sensors for capturing ballistocardiography (BCG) signals. However, BCG signal quality can vary due to individual differences and body motion. Therefore, BCG data quality assessment is critical before extracting any meaningful biomarkers. To address this, we introduced the ECG-gated BCG heatmap, a new method for assessing BCG signal quality. We trained a Random Forest model to identify usable signals, achieving 82% test accuracy. Filtering out unusable signals improved HR/HRV estimation accuracy to levels comparable to PPG-based estimates. Our findings demonstrate the feasibility of accurate physiological monitoring with earbuds, advancing the development of user-friendly wearable health technologies for stress management. © 2025 Copyright held by the owner/author(s).

关键词： Heart

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A Toolbox of Feminist Wonder: Theories and methods that can make a difference 26

A Toolbox of Feminist Wonder: Theories and methods that can ...

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26th ACM Conference on computer-Supported Cooperative Work and Social Computing, CSCW 2023

作者： Hansson, Karin Bardzell, Shaowen Bhandari, Aparajita Boulicault, Marion Doyle, Dylan Thomas Erete, Sheena Cerratto Pargman, Teresa Lazem, Shaimaa Muller, Michael Normark, Maria Petterson, Adrian Rosén, Anton Poikolainen Taylor, Alex S. Thomas, Jakita O. Watson, Julia Södertörn University The School of Natural Sciences Technology and Environmental Studies Sweden Georgia Institute of Technology The School of Interactive Computing United States Cornell University Department of Communication United States University of Edinburgh Department of Philosophy United States University of Colorado Boulder Department of Information Science United States University of Maryland College of Information United States Stockholm University The Department of Computer and Systems Sciences Sweden City for Scientific Research and Technological Applications The Informatics Research Institute Egypt Ibm Research Human Centered Ai United States Uppsala University Department of Informatics and Media Sweden University of Toronto Faculty of Information Canada Aalto University The School of Arts Design and Architecture Finland City University of London The Centre for Human Computer Interaction Design United Kingdom Auburn University Department of Computer Science and Software Engineering United States University of Toronto Department of Computer Science Canada

ISBN: (纸本)9798400701290

This one-day hybrid workshop builds on previous feminist CSCW workshops to explore feminist theoretical and methodological approaches that have provided us with useful tools to see things differently and make space for change. Since its inception over a decade ago, feminist HCI has progressed from the margins to mainstream HCI, with numerous references in the literature. Feminist HCI has also evolved to incorporate other critical HCI practices such as Queer HCI, participatory design, and speculative design. While feminist approaches have grown in popularity and become mainstream, it is getting more difficult to distinguish the feminist emancipatory core from other attempts of developing and improving society in various ways. In this workshop, we therefore want to revisit our feminist roots, where theory is a liberatory and creative practice, motivated by affect, curiosity, and wonder. From this standpoint, we consider which of our feminist tools can make a significant difference today, in a highly datafied world. The goal of this workshop is to;1) create an inventory of feminist theories and concepts that have had an impact on our work as designers, educators, researchers, and activists;2) develop a feminist toolbox for the CSCW community to strengthen our feminist literacy. © 2023 Owner/Author.

关键词： Computation theory

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A Generalized Outage Prediction Model for Various Types of Extreme Climate Events in Texas

A Generalized Outage Prediction Model for Various Types of E...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Lee, Jangjae Lee, Sangkeun Matthew Paal, Stephanie German Chinthavali, Supriya Texas A&m University Zachry Department of Civil and Environmental Engineering College StationTX77843 United States Oak Ridge National Laboratory Computer Science and Mathematics Division Oak RidgeTN37831 United States Oak Ridge National Laboratory Geospatial Science and Human Security Division Oak RidgeTN37831 United States

ISBN: (纸本)9798350362480

This study proposes a generalized model for predicting power outages for various types of extreme weather events. To accomplish the objective of this research, diverse features (e.g., weather data, geographical features, socio-demographic data, and infrastructure information) were leveraged as independent features, while the target variable was the number of customers who had problems with their electricity at the county level. Using the time of occurrence of extreme weather as defined by the National Weather Service, the top ten influential events were selected using the impact index based on cumulative power outages due to each type of extreme weather event. Additionally, a generalized model was created to predict power outages using weather data from one hour before the outage, outage data from one hour prior, as well as socio-demographic, geographic, and infrastructure information and this model was evaluated. The model was developed in two ways: first, as an Ensemble model trained using individual extreme weather events, and second, as a Unified model using all types of extreme weather conditions. As a result of evaluating the model using mean directional accuracy (MDA), one of the evaluation metrics, the ensemble model showed an accuracy of over 0.4 for weather event types such as Winter Storms, Cold/Wind Chill, Frost/Freeze, and Ice Storms. Although this study focused on creating a model specific to Texas, it is possible to expand the data to develop a nationwide model. © 2024 IEEE.

关键词： Extreme weather

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Self-Prompting Large Language Models for Zero-Shot Open-Domain QA

Self-Prompting Large Language Models for Zero-Shot Open-Doma...

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2024 Conference of the North American Chapter of the Association for Computational Linguistics: human Language Technologies, NAACL 2024

作者： Li, Junlong Wang, Jinyuan Zhang, Zhuosheng Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China SJTU-Paris Elite Institute of Technology Shanghai Jiao Tong University China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9798891761148

Open-Domain Question Answering (ODQA) aims to answer questions without explicitly providing specific background documents. This task becomes notably challenging in a zero-shot setting where no data is available to train tailored retrieval-reader models. While recent Large Language Models (LLMs) like GPT-3 have demonstrated their effectiveness in zero-shot ODQA using direct prompting methods, these methods still fall short of fully harnessing the potential of LLMs when implicitly invoked. In this paper, we propose a Self-Prompting framework to explicitly utilize the massive knowledge encoded in the parameters of LLMs and their strong instruction understanding abilities. Concretely, we prompt LLMs step by step to generate multiple pseudo QA pairs with background passages and explanations entirely from scratch. These generated elements are then utilized for in-context learning. Experimental results show that our method significantly surpasses previous state-of-the-art zero-shot methods on three widely-used ODQA datasets and even achieves comparable performance with various customized fine-tuned models on full training data. ©2024 Association for Computational Linguistics.

关键词： Zero-shot learning

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Firing Pattern of Cells in the Hippocampus and Basolateral Amygdala during Novelty Recognition

Firing Pattern of Cells in the Hippocampus and Basolateral A...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Xiaoxin Ren Yimeng Wang Ling Wang Jiajia Yang Chenguang Zheng Academy of Medical Engineering and Translational Medicine Medical College Tianjin University Tianjin China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Novelty recognition is essential for exploring and collecting unknown but interesting information, in which multiple brain regions related to cognitive memory are involved. Dorsal hippocampus (dHPC) is revealed to be closely associated with spatial memory and basolateral amygdala (BLA) is reported recently to be related to state-dependent encoding of exploratory behavior. However, how the firing pattern of cells in these two brain regions responds to novelty dynamically remains unclear. In this study, we observed that the representations of cells in BLA exhibited shift towards novelty, whereas dHPC cells maintained strong stability after the introduction of novelty, which are both engaged in the execution of novel recognition. Our study may provide new evidence for underlying the internal mechanisms of perception of novelty in the brain.

关键词： Brain In vivo Firing Cells (biology) Encoding Pattern recognition Object recognition Engineering in medicine and biology Hippocampus

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Isoform Function Prediction Based on Heterogeneous Graph Attention Networks

Isoform Function Prediction Based on Heterogeneous Graph Att...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Guo, Kuo Li, Yifan Chen, Hao Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Institute of Image Processing and Pattern Recognition Shanghai200240 China Carnegie Mellon University School of Computer Science Computational Biology Department PittsburghPA15213 United States

ISBN: (纸本)9798350337488

Isoforms refer to different mRNA molecules transcribed from the same gene, which can be translated into proteins with varying structures and functions. Predicting the functions of isoforms is an essential topic in bioinformatics as it can provide valuable insights into the intricate mechanisms of gene regulation and biological processes. Conventionally, gene function labels are standardized in Gene Ontology (GO) terms. However, traditional methods for predicting isoform function are largely limited by the absence of isoform-specific labels, sparse annotations, and the vast number of GO terms. To address these issues, we propose HANIso, a deep learning-based method for isoform function prediction. HANIso leverages a pretrained protein language model to extract features from protein sequences. It also integrates heterogeneous information, such as isoform sequence features, GO annotations, and isoform interaction data, using a Heterogeneous Graph Attention Network (HAN). This allows the model to learn the importance of different sources of information and their semantic relationships through the attention mechanism. Our method can predict function labels at both the gene level and isoform level. We conduct experiments on two species datasets, and the results demonstrate that our method outperforms existing methods on both AUROC and AUPRC. HANIso has the potential to overcome the limitations of traditional methods and provide a more accurate and comprehensive understanding of isoform function. © 2023 IEEE.

关键词： alternative splicing gene ontology heterogeneous graph attention network isoform function prediction protein language model

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The Pattern of CA1 c-Fos Expressing Place Cells Correlates with Learning Progression

The Pattern of CA1 c-Fos Expressing Place Cells Correlates w...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Ning Wang Anqi Zhang Jiajia Yang Ling Wang Chenguang Zheng Academy of Medical Engineering and Translational Medicine Medical College Tianjin University Tianjin China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Spatial memory supported by the hippocampus is a critical cognitive function in daily life. It helps us to navigate to salient goal locations. Hippocampal place cells stably represent the spatial location, while c-Fos-expressing cells (engram cells) contain rich information about the environment, contributing to the encoding and retrieving of memories. However, the role of cFos as a gateway to a more profound comprehension of the mechanisms underlying the process of goal-oriented spatial memory remained poorly understood. In this study, we labeled rats’ c-Fos + neurons by Channelrhodopsin-2 during memory encoding of a specific goal location. A subset of place cells whether they expressed c-Fos was identified optogenetically. As the rats learned the new goal locations, the spatial correlation between task periods remained stable for the c-Fos - place cell, while increased for the c-Fos + place cell. This finding shed light on the processing of goal-oriented spatial memories by the hippocampal network involved in c-Fos. C-Fos - place cells consistently maintained a stable representation of the locations, while c-Fos + place cells exhibited significant flexibility of the goal.

关键词： Correlation Navigation Neurons Cells (biology) Logic gates Encoding Optogenetics Engineering in medicine and biology Hippocampus

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Enhanced Transient Response of Ultrasound Neuromodulation Mediated by Large Conductance Mechanosensitive Ion Channel

Enhanced Transient Response of Ultrasound Neuromodulation Me...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Xin Li Guoying Zhang Chenguang Zheng Yutao Tian Academy of Medical Engineering and Translational Medicine Medical College Tianjin University Tianjin China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Ultrasound neuromodulation, a burgeoning field aimed at enhancing brain function and behavior, relies on the intricate electrophysiological responses of neurons driven by ion channel dynamics. However, achieving targeted and precise modulation with ultrasound poses a significant challenge. A hypothesis is that mechanosensitive (MS) ion channels may play a pivotal role in achieving the desired specificity in ultrasound effects. Our study involved augmenting MscL-G22S channel expression in specific areas of rats’ hippocampus (HP) and primary visual cortex (V1) via AAV virus delivery. We recorded local field potentials (LFPs) to assess the modulation effect and identified distinct evoked-related potentials (ERPs) in regions overexpressing MscL-G22S channels under anesthesia. Notable variations in the amplitude of negative peaks were observed in the ERPs between HP and V1, highlighting a nuanced response to ultrasound stimulation. These results highlight the complexity and promise of MS channel-mediated neuromodulation, offering critical insights into the development of targeted ultrasound interventions to improve brain function.

关键词： Visualization Ultrasonic imaging Local field potentials Modulation Ions Brain modeling Complexity theory Neuromodulation Hippocampus Viruses (medical)

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Astrocytic TRPA1 as a target in reversing social avoidance by low-intensity focused ultrasound stimulation in mice

Astrocytic TRPA1 as a target in reversing social avoidance b...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Ganjiang Wei Ling Wang Jingnan Zhu Xiao Wang Yuran Zang Jiajia Yang Chenguang Zheng Academy of Medical Engineering and Translational Medicine Medical College Tianjin University Tianjin China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Social avoidance is a prominent clinical feature of multiple neuropsychiatric disorders. Increasing evidence showed that the medial prefrontal cortex (mPFC) regulates social avoidance with suppression of excitatory neurons. Our previous study found that the low-intensity focused ultrasound (LIFUS), as a novel noninvasive neuromodulation technique, could alleviate the social avoidance of social defeat stress (SDS) model mice by increasing the mPFC excitation. However, the underlying target of LIFUS on mPFC neurons in social defeated mice remains unclear. Here we injected AAV-shRNA to knock down astrocytic TRPA1 in the mPFC, and investigated whether astrocytic TRPA1 played a crucial role in LIFUS modulation. We found that the social avoidance of SDS mice with TRPA1 knocked down was not affected by LIFUS. Furthermore, LIFUS didn’t induce enhanced expression of membrane NMDAR2A and NMDAR2B in SDS mice with TRPA1 knocked down, compared with that in mice infected with the control virus. It is believed that LIFUS can act on astrocytic TRPA1 to improve social avoidance and hence synaptic function.

关键词： Ultrasonic imaging Modulation Brain modeling Mice Biomembranes Neuromodulation Engineering in medicine and biology Viruses (medical) Stress Immune system

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