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arXiv 2023年

作者： Stolz, Bernadette J. Dhesi, Jagdeep Bull, Joshua A. Harrington, Heather A. Byrne, Helen M. Yoon, Iris H.R. Laboratory for Topology and Neuroscience EPFL Station 8 Lausanne Switzerland Mathematical Institute University of Oxford Andrew Wiles Building Woodstock Rd Oxford United Kingdom Wellcome Centre for Human Genetics University of Oxford Roosevelt Dr Headington Oxford United Kingdom Ludwig Institute for Cancer Research University of Oxford Old Road Campus Research Build Roosevelt Dr Headington Oxford United Kingdom Department of Mathematics and Computer Science Wesleyan University 265 Church Street Middletown United States

Topological data analysis (TDA) is an active field of mathematics for quantifying shape in complex data. Standard methods in TDA such as persistent homology (PH) are typically focused on the analysis of data consisting of a single entity (e.g., cells or molecular species). However, state-of-the-art data collection techniques now generate exquisitely detailed multispecies data, prompting a need for methods that can examine and quantify the relations among them. Such heterogeneous data types arise in many contexts, ranging from biomedical imaging, geospatial analysis, to species ecology. Here, we propose two methods for encoding spatial relations among different data types that are based on Dowker complexes and Witness complexes. We apply the methods to synthetic multispecies data of a tumor microenvironment and analyze topological features that capture relations between different cell types, e.g., blood vessels, macrophages, tumor cells, and necrotic cells. We demonstrate that relational topological features can extract biological insight, including the dominant immune cell phenotype (an important predictor of patient prognosis) and the parameter regimes of a data-generating model. The methods provide a quantitative perspective on the relational analysis of multispecies spatial data, overcome the limits of traditional PH, and are readily *** Codes 55N31, 92C17 Copyright © 2023, The Authors. All rights reserved.

关键词： Blood vessels

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Text compression-aided transformer encoding

arXiv

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arXiv 2021年

作者： Li, Zuchao Zhang, Zhuosheng Zhao, Hai Wang, Rui Chen, Kehai Utiyama, Masao Sumita, Eiichiro Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China Kyoto619-0289 Japan

Text encoding is one of the most important steps in Natural Language Processing (NLP). It has been done well by the self-attention mechanism in the current state-of-the-art Transformer encoder, which has brought about significant improvements in the performance of many NLP tasks. Though the Transformer encoder may effectively capture general information in its resulting representations, the backbone information, meaning the gist of the input text, is not specifically focused on. In this paper, we propose explicit and implicit text compression approaches to enhance the Transformer encoding and evaluate models using this approach on several typical downstream tasks that rely on the encoding heavily. Our explicit text compression approaches use dedicated models to compress text, while our implicit text compression approach simply adds an additional module to the main model to handle text compression. We propose three ways of integration, namely backbone source-side fusion, target-side fusion, and both-side fusion, to integrate the backbone information into Transformer-based models for various downstream tasks. Our evaluation on benchmark datasets shows that the proposed explicit and implicit text compression approaches improve results in comparison to strong baselines. We therefore conclude, when comparing the encodings to the baseline models, text compression helps the encoders to learn better language representations. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal encoding

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Biallelic variants in SREBF2 cause autosomal recessive spastic paraplegia

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Journal of Genetics and Genomics 2025年

作者： Wei, Qiao Fan, Wenlu Li, Hong-Fu Wang, Pei-Shan Xu, Man Dong, Hai-Lin Yu, Hao Lyu, Jialan Luo, Wen-Jiao Chen, Dian-Fu Ge, Wanzhong Wu, Zhi-Ying Department of Medical Genetics and Center for Rare Diseases Second Affiliated Hospital Zhejiang University School of Medicine and Zhejiang Key Laboratory of Rare Diseases for Precision Medicine and Clinical Translation Zhejiang Hangzhou 310009 China Nanhu Brain-computer Interface Institute Zhejiang Hangzhou 311100 China Division of Human Reproduction and Developmental Genetics Women's Hospital Zhejiang University School of Medicine Zhejiang Hangzhou 310006 China MOE Frontier Science Center for Brain Research and Brain-Machine Integration School of Brain Science and Brain Medicine Zhejiang University Zhejiang Hangzhou 310012 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031 China

Hereditary spastic paraplegias (HSPs) refer to a genetically and clinically heterogeneous group of neurodegenerative disorders characterized by the degeneration of motor neurons. To date, a significant number of patients still have not received a definite genetic diagnosis. Therefore, identifying unreported causative genes continues to be of great importance. Here, we perform whole exome sequencing in a cohort of Chinese HSP patients. Three homozygous variants (p.L604W, p.S517F, and p.T984A) within the sterol regulatory element-binding factor 2 (SREBF2) gene are identified in one autosomal recessive family and two sporadic patients, respectively. Co-segregation is confirmed by Sanger sequencing in all available members. The three variants are rare in the public or in-house database and are predicted to be damaging. The biological impacts of variants in SREBF2 are examined by functional experiments in patient-derived fibroblasts and Drosophila. We find that the variants upregulate cellular cholesterol due to the overactivation of SREBP2, eventually impairing the autophagosomal and lysosomal functions. The overexpression of the mature form of SREBP2 leads to locomotion defects in Drosophila. Our findings identify SREBF2 as a causative gene for HSP and highlight the impairment of cholesterol as a critical pathway for HSP. © 2025 The Authors

关键词： Causative gene Cholesterol Hereditary spastic paraplegia Locomotion defects SREBF2

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Scenario Design Tool Based on Hybrid Input

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Ruan Jian Xue Bao/Journal of Software 2019年 30卷 48-61页

作者： Tong, Qing-Shan Zhang, Zong-Qi Huang, Jin Tian, Feng Liu, Jie Dai, Guo-Zhong Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing100190 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100190 China

Pen-based user interface relying on touch technology is one of the Post-WIMP interfaces. It discards the physical keyboard and mouse, which changed the method of human-computer interaction to some extent. Though sketch drawing software and recognition software are constantly emerging, there is no mature pen-based interface design development tool. Based on the PGIS interaction paradigm and scenario design method, this paper develops a tool named with SDT that allows hybrid input of graphics and sketchs based on pen-based interaction primitives. Firstly, based on the principle of high-cohesion and low-coupling in the field of software engineering, the "Separation-Fusion" design method is proposed. Accordingly, the overall architecture of the system is put forward. Secondly, the essential technologies are elaborated from three aspects: user interface description language, pen-based interactive primitive and mono-case, hybrid input. Thirdly, an example of a complete application is built by the SDT, which makes the availability and feasibility of the system more convincible. Finally, the advantage and effectiveness of the tool are verified by two evaluation experiments. © Copyright 2019, Institute of Software, the Chinese Academy of sciences. All rights reserved.

关键词： human computer interaction

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A Droplet-Based Multivolume Microfluidic Device for Digital Polymerase Chain Reaction

SSRN

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SSRN 2022年

作者： Wei, Chunyang Yu, Chengzhuang Li, Shanshan Meng, Jiyu Li, Tiejun Cheng, Jingmeng Li, Junwei Hebei Key Laboratory of Robotic Sensing and Human-robot Interactions School of Mechanical Engineering Hebei University of Technology Tianjin300132 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Institute of Biophysics School of Health Sciences and Biomedical Engineering Hebei University of Technology Tianjin300401 China Department of Computer Science and Electrical Engineering Hebei University of Technology Langfang065000 China

Digital PCR plays an essential role in detecting and quantifying nucleic acid targets, while there are still challenges, including reduction of cost, simplification of operations, and system miniaturization. This work proposes a droplet-based multivolume microfluidic device for easy-to-operate and integrated droplet digital PCR (ddPCR). With an elaborate " asymmetrical droplet-splitting" microstructure, we have successfully prepared a small droplet population ( n = 1.5k, Φ = 59.1 ± 2.2 μm) and a large droplet population ( n = 1.5k, Φ = 106.3 ± 3.9 μm) in the same chip for realizing multivolume design, by which the ddPCR chip achieves a dynamic range of over 10^4 for DNA molecule quantification. The chip integrates droplet generation, droplet array self-assembly, droplet dPCR, and fluorescence detection on a single device. The quantitative capability of the ddPCR chip was evaluated by measuring template DNA at concentrations from 20 to 12500 copies/μL. Benefiting from the characteristics of wide dynamic range, easy operation, and miniaturization, our ddPCR device is expected to be used in the applications involving DNA molecule quantification, including diagnosis of genetic disease, single-cell gene expression, and point of care field. © 2022, The Authors. All rights reserved.

关键词： Drops

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Dialogue-adaptive Language Model Pre-training From Quality Estimation

arXiv

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arXiv 2020年

作者： Li, Junlong Zhang, Zhuosheng Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China

Pre-trained language models (PrLMs) have achieved great success on a wide range of natural language processing tasks by virtue of the universal language representation ability obtained by self-supervised learning on a large corpus. These models are pre-trained on standard plain texts with general language model (LM) training objectives, which would be insufficient to model dialogue-exclusive attributes like specificity and informativeness reflected in these tasks that are not explicitly captured by the pre-trained universal language representations. In this work, we propose dialogue-adaptive pre-training objectives (DAPO) derived from quality estimation to simulate dialogue-specific features, namely coherence, specificity, and informativeness. As the foundation for model pre-training, we synthesize a new dialogue corpus and build our training set with two unsupervised methods: 1) coherence-oriented context corruption, including utterance ordering, insertion, and replacement, to help the model capture the coherence inside the dialogue contexts;and 2) specificity-oriented automatic rescoring, which encourages the model to measure the quality of the synthesized data for dialogue-adaptive pre-training by considering specificity and informativeness. Experimental results on widely used open-domain response selection and quality estimation benchmarks show that DAPO significantly improves the baseline models and achieves state-of-the-art performance on the MuTual leaderboard, verifying the effectiveness of estimating quality evaluation factors into pre-training. Copyright © 2020, The Authors. All rights reserved.

关键词： Benchmarking

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Task-specific versus free-choice non-driving-related tasks: Enhancing automated driving takeover research through varied task engagement

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iscience 2025年第6期28卷

作者： Wenjun Wang Zhenyuan Wang Qingkun Li Yizi Su Chao Zeng Bo Cheng State Key Laboratory of Automotive Safety and Energy School of Vehicle and Mobility Tsinghua University Beijing 100084 China Beijing Key Laboratory of Human–Computer Interaction Institute of Software Chinese Academy of Sciences Beijing 100190 China Automotive Software Innovation Center (Chongqing) Chongqing 401331 China College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Hami Vocational and Technical College Hami 839001 China

Level 3 automated driving systems require drivers to occasionally retake control, making it crucial to understand factors influencing takeover performance. This study investigates how single versus multiple non-driving-related tasks (NDRTs) affect driver behavior, perceptions, and takeover capability. Using a high-fidelity driving simulator with 32 participants, conditions varying NDRT types and task-switching frequency were examined. Results indicate that diverse NDRT engagement and frequent task switching significantly influence takeover performance. Moreover, our decision tree models highlighted the number of NDRT types and task-switching frequency as critical predictors of driver response effectiveness. These findings underscore the importance of accounting for task engagement diversity and switching behaviors in automated vehicle system design. This study provides practical implications for optimizing human-automation interactions and enhancing the safety of automated driving systems by managing drivers’ attentiveness for their in-cabin activities.

关键词： Applied sciences computer science Artificial intelligence

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CEBRA Method: Decoding Brain Activity for Advanced Brain-computer Interface Technology

CEBRA Method: Decoding Brain Activity for Advanced Brain-Com...

引用

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

作者： Jingcheng Yang Frank Kulwa Xuanwei Liu Yiqing Lu Yufa Fu Guanglin Li Yaping Huai Xin Zhang Yongcheng Li CAS Key Laboratory of Human-Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Shenzhen Dapeng New District Nanao People’s Hospital Shenzhen China Department of Rehabilitation Medicine Shenzhen Longhua District Central Hospital Shenzhen China Brain Cognition and Brain-Computer Intelligence Integration Group Kunming University of Science and Technology Kunming China Shandong Zhongke Advanced Technology Co. Ltd. Jinan China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The emerging neurorehabilitation technology, Brain-computer Interface (BCI), provides a novel prospect for stroke recovery. However, decoding brain activity during the movement present substantial challenges, and feature extraction is crutial to build a better decoder. In this study the CEBRA method were employed to extract features first based on electroencephalogram(EEG) data during Motor Execution(ME) and Motor lmagery (Ml) tasks for 20 participants (including 10 stroke patients). The results revealed that, in MI tasks, CEBRA-RF (Random Forests) achieved an average classification accuracy of 91.33%, with an average F1-score of 91.19%, and CEBRA-SVM (Support Vector Machine) achieved an average classification accuracy of 91.32%, with an average F1-score of 90.83%. Compared to other conventional feature extraction methods, CEBRA shows significantly higher accuracy (t-test, p<0.01). However, in ME tasks, CEBRA-RF achieved an average classification accuracy of 75.67%, with an average F1-score of 75.39%, and CEBRA-SVM achieved an average classification accuracy of 76.13%, with an average F1-score of 75.80%. Nevertheless, no significant differences were observed compared to other feature extraction methods. These findings demonstrate the potential of CEBRA in decoding patients’ brain activity. The results of this study hold promise in addressing the current challenges of low decoding accuracy in BCI systems, offering a new approach for designing BCI-assisted rehabilitation systems for stroke patients.

关键词： Support vector machines Brain Accuracy Stroke (medical condition) Feature extraction Motors Brain-computer interfaces Neurorehabilitation Decoding Paralysis

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Designing a Pseudo-Haptics Study for Virtual Anesthesia Skills Development

Designing a Pseudo-Haptics Study for Virtual Anesthesia Skil...

引用

IEEE Games Media Entertainment (GEM)

作者： Bill Kapralos Alvaro Quevedo KC Collins Celina Da Silva Eva Peisachovich Kamen Kanev Michael Jenkin Adam Dubrowski Fahad Alam maxSIMhealth. Ontario Tech University Oshawa Ontario Canada Software and Informatics Research Centre. Ontario Tech University Oshawa Ontario Canada Collaborative Human Immersive Interaction Lab Toronto Canada School of Information Technology Carleton University Ottawa Ontario Canada Department of Health York University Toronto Ontario Canada Research Institute of Electronics Shizuoka University Hamamatsu Japan Department of Electrical Engineering and Computer Science Lassonde School of Engineering York University Canada Faculty of Health Sciences Ontario Tech University Oshawa Ontario Canada Department of Anesthesia Sunnybrook Health Science Centre Toronto Ontario Canada

ISBN: (纸本)9781665461399

Pseudo-haptics refers to the simulation of haptic sensations without the use of haptic interfaces, using, for example, audiovisual feedback and kinesthetic cues. Given the COVID-19 pandemic and the shift to online learning, there has been a recent interest in pseudo-haptics as it can help facilitate psychomotor skills development away from simulation centers and laboratories. Here we present work-in-progress that describes the study design of a pseudo-haptics for virtual anesthesia skills development. We anticipate this work will provide greater insight to pseudo-haptics and its application to anesthesia-based training.

关键词： Training COVID-19 Pandemics Laboratories Entertainment industry Games Media

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High-resolution two-photon transcranial imaging of brain using direct wavefront sensing

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Photonics Research 2021年第6期9卷 1144-1156页

作者： CONGPING CHEN ZHONGYA QIN SICONG HE SHAOJUN LIU SHUN-FAT LAU WANJIE WU DAN ZHU NANCY Y.IP JIANAN Y.QU Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina State Key Laboratory of Molecular Neuroscience The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina Center of Systems Biology and Human Health The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhanChina MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical EngineeringSchool of Engineering SciencesHuazhong University of Science and TechnologyWuhanChina Division of Life Science The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina Molecular Neuroscience Center The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina

Imaging of the brain in its native state at high spatial resolution poses major challenges to visualization ***-photon microscopy integrated with the thinned-skull or optical clearing skull technique provides a minimally invasive tool for in vivo imaging of the cortex of mice without activating immune response and inducing brain ***,the imaging contrast and spatial resolution are severely compromised by the optical heterogeneity of the skull,limiting the imaging depth to the superficial *** this work,an optimized configuration of an adaptive optics two-photon microscope system and an improved wavefront sensing algorithm are proposed for accurate correction for the aberrations induced by the skull window and brain *** this system,we achieved subcellular resolution transcranial imaging of layer 5 pyramidal neurons up to 700μm below pia in living *** addition,we investigated microglia–plaque interaction in living brain of Alzheimer’s disease and demonstrated high-precision laser dendrotomy and single-spine ablation.

关键词： resolution photon system

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