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Modeling the Temporal Dynamics of EEG Signals in Selective Listening

IEEE Transactions on Consumer Electronics 2025年

作者： Cai, Siqi Zhang, Ran Zhu, Hongxu Li, Haizhou National University of Singapore Department of Electrical and Computer Engineering Singapore Singapore South China University of Technology Shien-Ming Wu School of Intelligent Engineering China Fano Hong Kong Hong Kong The Chinese University of Hon g Kong Shenzhen Research Institute of Big Data School of Data Science Shenzhen518172 China University of Bremen Machine Listening Lab Bremen28359 Germany

Human brain possesses an extraordinary ability to attend to a specific sound source in a multi-talk, noisy environment such as a cocktail party. Auditory attention detection (AAD) aims to automatically identify such attentive neural activity from brain signals, such as electroencephalography (EEG). Given the dynamic and nonlinear nature of EEG signals, we propose a spiking long short-term memory (LSTM) network to capture the temporal features from EEG data. Additionally, we introduce a spiking temporal attention mechanism that dynamically assigns differentiated weights, thereby enhancing the representation of EEG features. We evaluate our proposed spiking temporal LSTM model, named ST-LSTM, on a widely used AAD dataset through a wide range of experiments. The experiments demonstrate that ST-LSTM outperforms other competing models, especially in low-latency settings. Moreover, with low power consumption, ST-LSTM offers a practical solution for edge computing implementations such as neuro-steered hearing aids, and other portable brain-computer interfaces. © 1975-2011 IEEE.

关键词： Hearing aids

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A novel burners arrangement of an entrained-flow gasifier studied by experimental and simulation methods

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Energy 2025年 330卷

作者： Yue Lu Zhengqi Li Xin Zhang Chunchao Huang Yufei Wang Zhichao Chen School of Mechanical and Electrical Engineering Changchun University of Science and Technology Changchun 130022 China School of Energy Science and Engineering Harbin Institute of Technology Harbin 150001 China

In the entrained flow gasification process, the multi-burner arrangement is widely used. The burner arrangement affects the airflow movement and the gasification performance. A novel burner arrangement is proposed in this study: four burners counter-biased arrangement. The swirl airflow can be formed in the gasifier under the arrangement. While ensuring sufficient mixing of the burner jets, the swirl intensity can be adjusted by changing the burner biased angles. The PDA experiment and simulation results show that when using the counter-biased burner arrangement with the same biased angles, effective swirl cannot be formed in the gasifier. When using the counter-biased burner arrangement with different biased angles, a rotating flow field is formed in the gasifier, and the residence time of the particles is prolonged. When the angle between A 1 and A 2 burners is 102°, the residence time of fine slag particles in the furnace is up to 4.3 s.

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Conditional Generative Modeling for Amorphous Multi-Element Materials

arXiv

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arXiv 2025年

作者： Li, Honglin Liu, Chuhao Guo, Yongfeng Luo, Xiaoshan Chen, Yijie Liu, Guangsheng Li, Yu Wang, Ruoyu Wang, Zhenyu Wu, Jianzhuo Ma, Cheng Xie, Zhuohang Lv, Jian Ding, Yufei Zhang, Huabin Luo, Jian Zhong, Zhicheng Li, Mufan Wang, Yanchao Li, Wan-Lu Key Laboratory of Material Simulation Methods and Software Ministry of Education College of Physics Jilin University Changchun China Aiiso Yufeng Li Family Department of Chemical and Nano Engineering University of California La Jolla San DiegoCA United States Institute of Molecular Engineering Plus College of Chemistry Fuzhou University Fuzhou China College of Chemistry and Molecular Engineering Peking University Beijing China School of Physics Nankai University Tianjin China Institute of Modern Physics Fudan University Shanghai China Program in Materials Science and Engineering University of California La Jolla San DiegoCA United States School of Artificial Intelligence and Data Science University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China International Center of Future Science Jilin University Changchun China Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Center for Renewable Energy and Storage Technologies Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Suzhou Lab Suzhou215123 China

Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneering predictive framework for amorphous multi-element materials, establishing a new paradigm by integrating physics-informed generative modeling with particle swarm optimization, using chemical short-range order as an explicit constraint. By systematically navigating the disordered energy landscape, ApolloX enables the targeted design of thermodynamically stable amorphous configurations. It accurately predicts atomic-scale arrangements, including composition-driven metal clustering and amorphization trends, which are well-validated by experiments, while also guiding synthesis by leveraging sluggish diffusion to control elemental distribution and disorder. The resulting structural evolution, governed by composition, directly impacts catalytic performance, leading to improved activity and stability with increasing amorphization. This predictive-experimental synergy transforms the discovery of amorphous materials, unlocking new frontiers in catalysis, energy storage, and functional disordered systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Amorphization

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Modular HfOx-RRAM for On-Demand Micromodular Electronics

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年

作者： Kurup, Siddharth Bhattacharya, Swagat Banner, Rebecca K. Yue, Kaifan Ayyappan, Praveen Raj Aziz, Daniel Elly, Hubert N. Barton, Kira L. Hasler, Jennifer Filler, Michael A. Vogel, Eric M. Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA30332 United States Georgia Institute of Technology School of Materials Science and Engineering AtlantaGA30332 United States University of Michigan Department of Robotics Ann ArborMI48109 United States Georgia Institute of Technology School of Chemical and Biomolecular Engineering AtlantaGA30332 United States University of Michigan Department of Mechanical Engineering Ann ArborMI48109 United States

Micromodular metal-HfOx-metal resistive random-access memories (RRAM) were fabricated, transferred to foreign substrates, and contacted using high-resolution electrohydrodynamic jet (e-jet) printing. The modular RRAM exhibited bipolar switching at low operating voltages and multi-level analog resistance states programmable using variable amplitude voltage pulses. These variable resistance RRAMs were also integrated with an amplifier and a bandpass filter to modulate their gain and corner frequencies. This work enables integration of high-quality RRAM devices in modular circuits and paves the way for microscale heterogeneous integration at the device level. © 1980-2012 IEEE.

关键词： RRAM

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Unveiling spatiotemporal patterns and key drivers of soil conservation from a "historical-future-intervention" perspective: A case study of the Danjiangkou Reservoir Area, China

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Journal of Environmental Management 2025年 386卷 125771页

作者： Zhao, Pengcheng Wang, Lihui Zheng, Xiaodi Li, Yang Lu, Lijie Yang, Yunjie Huang, Jinliang Du, Yun Ling, Feng Key Laboratory for Environment and Disaster Monitoring and Evaluation Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan430077 China University of Chinese Academy of Sciences Beijing100049 China Hubei Provincial Academy of Eco-environmental Sciences Wuhan430072 China Faculty of Computing Harbin Institute of Technology Harbin150006 China School of Geography and Information Engineering China University of Geosciences Wuhan430074 China

The soil conservation of ecosystems in water source areas is crucial for ensuring water quality and supply. It is primarily shaped by natural factors like rainfall intensity, soil characteristics, and topography, alongside the impact of human activities. As the starting point and core water source area of the South-to-North Water Diversion Middle Route Project, the Danjiangkou Reservoir has experienced increasing risks of soil erosion under the combined effects of extreme climate events and land cover changes. Effectively assessing these changes and formulating policies to address future challenges is of great significance for the stable operation of the reservoir and the long-term, sustainable transfer of clean water. This study incorporates human intervention factors to generate three future development scenarios for the DRA, including protection priority, natural development, and economic priority, corresponding to SSP1-2.6, SSP2-4.5, and SSP5-8.5 stem from the future climate, social, and economic scenarios (CMIP6-SSP-RCP), respectively. Additionally, we uses land use/land cover (LULC) data from 2000 to 2020 as historical input and applies the LULC simulation model model (PLUS) to predict land use types for the 2025–2035 period under the current land use continuation scenario, and employ the InVEST model to quantify SC (soil conservation) services for both the 2000–2020 period and the different future scenarios (2025–2035). The findings indicate that the land use structure in the reservoir area has undergone changes over the past two decades, with a reduction in forest and grassland, leading to a gradual weakening of soil conservation capacity. Among the future scenarios, the protection-priority scenario, which involves human intervention, offers the highest soil conservation. LULC is identified as a major variable influencing these changes. The findings offer scientific evidence and support for future land use and soil conservation management in the DRA. © 2025

关键词： Danjiangkou reservoir area Historical-future-intervention perspective Land use prediction PLUS model Soil conservation

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High temperature deformation behavior and processing map of hot isostatically pressed Ti-47.5Al-2Cr-2Nb-0.2W-0.2B alloy using gas atomization powders

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Journal of Iron and Steel Research International 2017年第4期24卷 435-441页

作者： Ying Bao Dong-ye Yang Na Liu Guo-qing Zhang Zhou Li Fu-yang Cao Jian-fei Sun School of Materials Science and Engineering Harbin Institute of Technology School of Materials Science and Engineering Harbin University of Science and Technology Science and Technology on Advanced High Temperature Structural Materials Laboratory Beijing Institute of Aeronautical Materials

The hot compressive deformation behavior of hot isostatically pressed Ti-47.5Al-2Cr-2Nb-0.2W-0.2B alloy using gas atomization powders was systematically investigated and the processing map was obtained in the temperature range of 1323-1473 Kand strain rate range of 0.001-0.5s^（-1）.The calculated activation energy in the above variational ranges of temperature and strain rate possesses a low activation energy value of approximately 365.6kJ/mol based on the constitutive relationship models developed with the Arrhenius-type constitutive model respectively considering the strain rate and deformation *** hot working flow behavior during the deformation process was analyzed combined with the microstructural ***,the processing maps during the deformation process were established based on the dynamic material model and Prasad instability criterion under different deformation ***,the optimal hot processing window of this alloy corresponding to the wide temperature range of 1353-1453 Kand the low strain rate of 0.001-0.1s^（-1） was obtained.

关键词： Hot compressive deformation TiAl alloy Constitutive equation Processing map Gas atomization Hot isostatic pressing

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Frequency dependence of magnetization and giant magneto impedance effect of amorphous wires

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International Journal of Minerals,Metallurgy and Materials 2013年第4期20卷 375-378页

作者： Shu-ling Zhang Jian-fei Sun Da-wei Xing Da-qing Fang Lu-cai Wang School of Materials Science and Engineering Taiyuan University of Science and Technology School of Materials Science and Engineering Harbin Institute of Technology

The frequency dependence of magnetization process and giant magneto impedance （GMI） effect of Co-rich melt-extracted amorphous wires was studied by Kerr effect and impedance analyzer, respectively. It is demonstrated that the transverse Kerr intensity and the corresponding GMI response increase with increasing frequency, which contributes to the upgraded skin effect. However, the skin depth has a slothful trend with frequency when it is up to the megahertz range, which gives rise to the transformation of magnetization. The process is much more sensitive to the direct current magnetic field and the sensitive change of the circular permeability, and GMI response is observed as its consequence. This proves that the evolution of circumferential magnetization and the corresponding permeability with the direct current magnetic field is the essence of GMI response, and a much more sensitive magnetization promises a better GMI response.

关键词： amorphous wires magnetization giant magneto impedance Kerr magneto-optical effect melt extraction

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Understanding Older Adults' (Dis)Engagement with Design Materials 25

Understanding Older Adults' (Dis)Engagement with Design Mate...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Alisha Pradhan Ben Jelen Ramprabu Thangaraj Katie A. Siek Shannon Jette Amanda Lazar Department of Informatics Ying Wu College of Computing New Jersey Institute of Technology Newark New Jersey USA Computer Science and Software Engineering Rose-Hulman Institute of Technology Terre Haute Indiana USA Ying Wu College of Computing New Jersey Institute of Technology Newark New Jersey USA Luddy School of Informatics Computing and Engineering Indiana University Bloomington Indiana USA University of Maryland College Park Maryland USA College of Information Studies University of Maryland College Park Maryland USA

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Plant Diseases Detection and Soil Quality Identification Techniques for Agriculture Professionals

Plant Diseases Detection and Soil Quality Identification Tec...

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Advanced Computing Technologies (ICoACT), International Conference on

作者： M. A. Y. Peer Mohamed Appa V. Ganesh Karthikeyan Tasneem K. H. Khan R. Vaishnavi Karthika D. Vijaya Kumar S. P. Ramesh R. Saravanakumar Department of Artificial Intelligence and Machine Learning School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamil Nadu India School of Computing SASTRA Deemed to be University Thirumalaisamudram Thanjavur Tamil Nadu India Department of Chemistry Anjuman College of Engineering & Technology Sadar Nagpur India Department of Computer Science and Engineering VSB College of Engineering Technical Campus Coimbatore Tamil Nadu India Department of Mechanical Engineering Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu India Department of Computer Science and Engineering School of Computer Science & Engineering Galgotias University Greater Noida Uttar Pradesh India Iconix Software Solution Tirunelveli Tamil Nadu India

ISBN: (数字)9798331509859

ISBN: (纸本)9798331509866

Human civilization requires food production. Plant leaves and harvesting illnesses affected scientists' soil quality assessments. Plagues slow species growth. The right disease classification may reduce plant damage. Many diseases are hard to classify. Farmers misinterpret soil and plant leaf diseases. Hand-made soil quality and pathogen estimates are difficult. Without soil quality monitoring and plant disease classification, agricultural goods might be severely destroyed. Image processing may boost agricultural yield. Several methods utilize images of damaged leaves or crops to diagnose plant diseases and soil quality. Research has improved sickness categorization and diagnosis in several ways. Recent statements, actions, and debates need more. Global farming uses technology. CNN and ANN are artificial neural networks. Deep or traditional Machine Learning (ML) relies on the issue, data, and computing power. When processing and data resources are available, deep learning (DL), which uses convolutional neural networks (CNNs) and artificial neural networks (ANNs), is used for several challenging visual identification and classification tasks. It excels on its own datasets but struggles on others. This study's data, assessment criteria, and conclusions will help plant leaf and crop detection and soil quality measuring researchers.

关键词： Deep learning Plant diseases Visualization Machine learning algorithms Crops Soil Feature extraction Classification algorithms Convolutional neural networks Diseases

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Liquid metal anode enables zinc-based flow batteries with ultrahigh areal capacity and ultralong duration

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science Advances 2025年第18期11卷 eads3919页

作者： Wang, Shengnan Yang, Deshuai Zhang, Pu Guo, Yihui Liu, Xingjun Zhao, Ming Zhu, Jiaxiong Li, Pei Li, Xianfeng Fan, Jun Zhi, Chunyi Department of Materials Science and Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon999077 Hong Kong School of Materials Science and Engineering Harbin Institute of Technology Shenzhen518055 China Division of Energy Storage Dalian Institute of Chemical Physics Chinese Academy of Sciences 457 Zhongshan Road Dalian116023 China

Zinc-based flow batteries (Zn-FBs) are promising candidates for large-scale energy storage because of their intrinsic safety and high energy density. Unlike that conventional flow batteries operate on the basis of liquid-liquid conversions, the Zn anode in Zn-FBs adopts a solid-liquid conversion reaction, presenting challenges such as dendrite formation, poor reversibility, and low areal capacity, limiting its long-duration energy storage (LDES) applications. Here, we developed a liquid metal (LM) electrode that evolves the deposition/dissolution reaction of Zn into an alloying/dealloying process within the LM, thereby achieving extraordinary areal capacity and dendrite-free Zn-FBs with outstanding cycling stability. Both Zn-I2 and Zn-Br2 flow batteries using LM electrodes exhibited an ultrahigh areal capacity of 640 milliampere-hours per square centimeter, corresponding to an ultralong discharge duration of ~16 hours, thus exceeding the LDES standard defined by the US Department of Energy. This study breaks the solid-liquid working mode of the Zn anode, offering an effective solution for LDES applications with Zn-FBs. Copyright © 2025 The Authors, some rights reserved.

关键词： Flow batteries

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