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Heteronanostructural metal oxide-based gas microsensors

Microsystems & Nanoengineering 2022年第4期8卷 35-56页

作者： Lin Liu Yingyi Wang Yinhang Liu Shuqi Wang Tie Li Simin Feng Sujie Qin Ting Zhang i-Lab Key Laboratory of Multifunctional Nanomaterials and Smart SystemsSuzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of Sciences(CAS)SuzhouJiangsuChina Department of Health and Environmental Sciences Xi’an Jiaotong-Liverpool UniversitySuzhouJiangsuChina Department of Nano Science and Nano Technology Institute University of Science and Technology of ChinaSuzhouJiangsuChina NanoX Suzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of Sciences(CAS)SuzhouJiangsuChina School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaHefeiAnhuiPR China Gusu Laboratory of Materials SuzhouJiangsuPR China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghaiPR China

The development of high-performance,portable and miniaturized gas sensors has aroused increasing interest in the fields of environmental monitoring,security,medical diagnosis,and *** different detection tools,metal oxide semiconductor(MOS)-based chemiresistive gas sensors are the most popular choice in commercial applications and have the advantages of high stability,low cost,and high *** of the most important ways to further enhance the sensor performance is to construct MOS-based nanoscale heterojunctions(heteronanostructural MOSs)from MOS ***,the sensing mechanism of heteronanostructural MOS-based sensors is different from that of single MOS-based gas sensors in that it is fairly *** performance of the sensors is influenced by various parameters,including the physical and chemical properties of the sensing materials(e.g.,grain size,density of defects,and oxygen vacancies of materials),working temperatures,and device *** review introduces several concepts in the design of high-performance gas sensors by analyzing the sensing mechanism of heteronanostructural MOS-based *** addition,the influence of the geometric device structure determined by the interconnection between the sensing materials and the working electrodes is *** systematically investigate the sensing behavior of the sensor,the general sensing mechanism of three typical types of geometric device structures based on different heteronanostructural materials are introduced and discussed in this *** review will provide guidelines for readers studying the sensing mechanism of gas sensors and designing high-performance gas sensors in the future.

关键词： structural portable designing

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A Flexible and Ultrasensitive Artificial Compound Eye Using Bionic Micro-Lens Array for Drone Vision 38

A Flexible and Ultrasensitive Artificial Compound Eye Using ...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Wang, Jiachuang Zhao, Fangyu Liu, Wenyuan Qin, Nan Tao, Tiger H. State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China 2020 X-Lab Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Graduate Study University of Chinese Academy of Sciences Beijing China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China Jiangxi Nanchang China Guangdong Institute of Intelligence Science and Technology Zhuhai Guangdong Hengqin China Tianqiao and Chrissy Chen Institute for Translational Research Shanghai China

ISBN: (纸本)9798331508890

We report a bionic artificial compound eye based on flexible quantum dots film and micro electromechanical system (MEMS) fabrication process. The device integrates organic photodetector and micro-lens array, featuring the high-speed response, ultrathin thickness and extensive curvature radius. Our artificial eye exhibits significant discriminative detection to different targets with varying shapes and distances. The insect scale biomimetic compound eye provides a novel precision integration route for flexible optoelectronic devices and micro-optics, showing great potential applications in drone vision and bionic robot navigation. © 2025 IEEE.

关键词： Semiconductor quantum dots

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Emotion recognition for human-computer interaction

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Virtual Reality & Intelligent Hardware 2021年第1期3卷 I0003-I0004页

作者： Jianhua TAO National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing 100081China CAS Center for Excellence in Brain Science and Intelligence Technology Beijing 100081China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100081China

Emotion recognition is to quantify,describe and recognize different emotional states through the behavioral and physiological responses generated from emotional *** recognition is an important field due to its wide applications in many tasks,such as dialogue generation,social media analysis and intelligent *** builds a harmonious human-computer environment by enabling the computer systems and devices to recognize and interpret human *** recognition models are built using multimodal information such as audio,video,text and so *** is important to consider emotion characteristics of humans in the design and presentation of intelligent *** have selected seven papers that provide the latest updates on the development of emotion recognition technology covering micro-expression spotting and recognition,speech emotion recognition,physiological signal emotion recognition,emotional dialog generation and so on.

关键词： computer recognition emotional

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Underexplored Subspace Mining for Sparse-Reward Cooperative Multi-Agent Reinforcement Learning

Underexplored Subspace Mining for Sparse-Reward Cooperative ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yang Yu Qiyue Yin Junge Zhang Hao Chen Kaiqi Huang School of Artificial Intelligence University of Chinese Academy of Sciences Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences CAS Center for Excellence in Brain Science and Intelligence Technology Beijing P.R.China

Learning cooperation in sparse-reward multi-agent reinforcement learning is challenging, since agents need to explore in the large joint-state space with sparse feedback. However, in cooperative games, the cooperative target is often related to partial attributes, hence there is no need to treat the whole state space equally. Therefore, we propose Underexplored Subspace Mining (USM), a novel type of intrinsic reward that encourages agents to selectively explore partial attributes instead of wasting time on the whole state space to accelerate learning. Specially, considering that the target-related attributes are varying in different games and hard to predefine, we choose to focus on the underexplored subspace as an alternative, which is an automatic aggregation of the underexplored bottom-level dimensions without any human design or learning parameters. We evaluate our method in cooperative games with discrete and continuous state space separately. Results demonstrate that USM consistently outperforms existing state-of-the-art methods, and becomes the only method that has succeeded in sparse-reward games evaluated with larger state space or more complicated cooperation dynamics.

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Astrocyte-Enabled Advancements in Spiking Neural Networks for Large Language Modeling

arXiv

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arXiv 2023年

作者： Shen, Guobin Zhao, Dongcheng Dong, Yiting Li, Yang Li, Jindong Zeng, Yi Brain-inspired Cognitive Intelligence Lab Institute of Automation Chinese Academy of Sciences China Center for Excellence in Brain Science and Intelligence Technology CAS China School of Future Technology University of Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Center for Long-term Artificial Intelligence

Within the complex neuroarchitecture of the brain, astrocytes play crucial roles in development, structure, and metabolism. These cells regulate neural activity through tripartite synapses, directly impacting cognitive processes such as learning and memory. Despite the growing recognition of astrocytes' significance, traditional Spiking Neural Network (SNN) models remain predominantly neuron-centric, overlooking the profound influence of astrocytes on neural dynamics. Inspired by these biological insights, we have developed an Astrocyte-Modulated Spiking Unit (AM-SU), an innovative framework that integrates neuron-astrocyte interactions into the computational paradigm, demonstrating wide applicability across various hardware platforms. Our Astrocyte-Modulated Spiking Neural Network (AM-SNet) exhibits exceptional performance in tasks involving memory retention and natural language generation, particularly in handling long-term dependencies and complex linguistic structures. The design of AM-SNet not only enhances its biological authenticity but also introduces novel computational dynamics, enabling more effective processing of complex temporal dependencies. Furthermore, AM-SNet shows low latency, high throughput, and reduced memory usage in practical applications, making it highly suitable for resource-constrained environments. By successfully integrating astrocytic dynamics into intelligent neural networks, our work narrows the gap between biological plausibility and neural modeling, laying the groundwork for future biologically-inspired neural computing research that includes both neurons and astrocytes. Copyright © 2023, The Authors. All rights reserved.

关键词： Neurons

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The Eyes Have It:Perception of Social Interaction Unfolds Through Pupil Dilation

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Neuroscience Bulletin 2021年第11期37卷 1595-1598页

作者： Yuhui Cheng Wenjie Liu Xiangyong Yuan Yi Jiang State Key Laboratory of Brain and Cognitive Science CAS Center for Excellence in Brain Science and Intelligence TechnologyInstitute of PsychologyChinese Academy of SciencesBeijing100101China Department of Psychology University of Chinese Academy of SciencesBeijing100049China Chinese Institute for Brain Research Beijing102206China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei230088China

Dear Editor,It is well-known that pupil size,albeit intrinsically sensitive to ambient luminance changes,can be nlodulated by many cognitive processes,especially those associated with physiological arousal[1].Compatib... 详细信息

关键词： ambient Compatible intrinsic

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An Individualized Cortical Mapping of Macaque brain Using Fusion Joint Embedding

An Individualized Cortical Mapping of Macaque Brain Using Fu...

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IEEE International Symposium on Biomedical Imaging

作者： Yuheng Lu Yue Cui Liang Ma Wen Li Linzhong Fan Tianzi Jiang Brainnetome Center Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation Chinese Academy of Sciences Beijing China Research Center for Augmented Intelligence Zhejiang Lab Hangzhou China

Rhesus macaque (Macaca mulatta) is a widely employed animal to model psychiatric and neurological diseases due to its similarity in genes, behaviors, and brain organizations with humans. With the development of non-human primate investigations and data collection, it’s urgent to characterize the individual variation of the macaque brains in terms of not only the morphological but also the functional heterogeneity. The brain atlas is a fundamental tool to map regions with distinct functions including sensorimotor and higher cognitive functions. Nowadays brain atlas mapping of a single macaque is still obtained through brain morphological registration. In this study, we proposed a fusion joint embedding method to individualize the macaque brain atlas with the consideration of individual structural connectivity. The homogeneity of the individualized parcellation improved by 7.35% and 12.1% on two independent datasets compared with the traditional morphological registration. The cross-validation indicated its reproducibility and robustness and could be generalized to involve other modalities and species.

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Human-like object concept representations emerge naturally in multimodal large language models

arXiv

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arXiv 2024年

作者： Du, Changde Fu, Kaicheng Wen, Bincheng Sun, Yi Peng, Jie Wei, Wei Gao, Ying Wang, Shengpei Zhang, Chuncheng Li, Jinpeng Qiu, Shuang Chang, Le He, Huiguang Laboratory of Brain Atlas and Brain-Inspired Intelligence Institute of Automation Chinese Academy of Sciences Beijing100190 China Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Institute of Neuroscience Chinese Academy of Sciences Shanghai200031 China University of Chinese Academy of Sciences Beijing100049 China School of Automation Science and Engineering South China University of Technology China

The conceptualization and categorization of natural objects in the human mind have long intrigued cognitive scientists and neuroscientists, offering crucial insights into human perception and cognition. Recently, the rapid development of Large Language Models (LLMs) has raised the attractive question of whether these models can also develop human-like object representations through exposure to vast amounts of linguistic and multimodal data. In this study, we combined behavioral and neuroimaging analysis methods to uncover how the object concept representations in LLMs correlate with those of humans. By collecting large-scale datasets of 4.7 million triplet judgments from LLM and Multimodal LLM (MLLM), we were able to derive low-dimensional embeddings that capture the underlying similarity structure of 1,854 natural objects. The resulting 66-dimensional embeddings were found to be highly stable and predictive, and exhibited semantic clustering akin to human mental representations. Interestingly, the interpretability of the dimensions underlying these embeddings suggests that LLM and MLLM have developed human-like conceptual representations of natural objects. Further analysis demonstrated strong alignment between the identified model embeddings and neural activity patterns in many functionally defined brain ROIs (e.g., EBA, PPA, RSC and FFA). This provides compelling evidence that the object representations in LLMs, while not identical to those in the human, share fundamental commonalities that reflect key schemas of human conceptual knowledge. This study advances our understanding of machine intelligence and informs the development of more human-like artificial cognitive systems. © 2024, CC BY-NC-ND.

关键词： brain

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Multimodal sentiment analysis based on recurrent neural network and multimodal attention 2

Multimodal sentiment analysis based on recurrent neural netw...

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2nd Multimodal Sentiment Analysis Challenge and Workshop, MuSe 2021, held in conjunction with the ACM Multimedia 2021

作者： Cai, Cong He, Yu Sun, Licai Lian, Zheng Liu, Bin Tao, Jianhua Xu, Mingyu Wang, Kexin School of Artificial Intelligence University of CAS National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of CAS CAS Center for Excellence in Brain Science and Intelligence Technology China

ISBN: (纸本)9781450386784

Automatic estimation of emotional state has a wide application in human-computer interaction. In this paper, we present our solutions for the MuSe-Stress and MuSe-Physio sub-challenge of Multimodal Sentiment Analysis (MuSe 2021). The goal of these two sub-challenges is to perform continuous emotion predictions from people in stressed dispositions. To this end, we first extract both handcrafted features and deep representations from multiple modalities. Then, we explore the Long Short-Term Memory network and Transformer Encoder with Multimodal Multi-head Attention to model the complex temporal dependencies in the sequence. Finally, we adopt the early fusion, late fusion and model fusion to boost the model's performance by exploiting complementary information from different modalities. Our method achieves CCC of 0.6648, 0.3054 and 0.5781 for valence, arousal and arousal plus EDA (anno12_EDA). The results of valence and anno12_EDA outperform the baseline system with corresponding CCC of 0.5614 and 0.4908, and both rank Top3 in these challenges. © 2021 ACM.

关键词： Emotion Recognition

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Modulation of Predator Cue-Evoked Tonic Immobility by Acetylcholine Released in the Basolateral Complex of the Amygdala

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Neuroscience Bulletin 2021年第11期37卷 1599-1604页

作者： Nan Liu Kang Huang Pengfei Wei Xiaolei Liu Liping Wang Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science Guangdong Provincial Key Laboratory of Brain Connectome and BehaviorCAS Center for Excellence in Brain Science and Intelligence TechnologyBrain Cognition and Brain Disease InstituteShenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research InstitutionsShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China University of the Chinese Academy of Sciences Beijing100049China

Dear Editor,Tonic immobility(TI),also termed"feigning death," is the ultimate defensive response to in escapable *** some predators do not like to eat dead animals.

关键词： threat Release Ton

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