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arXiv 2024年

作者： Awadelkarim, Elsiddig Chada, Neil K. Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematics City University of Hong Kong Hong Kong School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China

We consider the development of unbiased estimators, to approximate the stationary distribution of Mckean-Vlasov stochastic differential equations (MVSDEs). These are an important class of processes, which frequently appear in applications such as mathematical finance, biology and opinion dynamics. Typically the stationary distribution is unknown and indeed one cannot simulate such processes exactly. As a result one commonly requires a time-discretization scheme which results in a discretization bias and a bias from not being able to simulate the associated stationary distribution. To overcome this bias, we present a new unbiased estimator taking motivation from the literature on unbiased Monte Carlo. We prove the unbiasedness of our estimator, under assumptions. In order to prove this we require developing ergodicity results of various discrete time processes, through an appropriate discretization scheme, towards the invariant measure. Numerous numerical experiments are provided, on a range of MVSDEs, to demonstrate the effectiveness of our unbiased estimator. Such examples include the Currie-Weiss model, a 3D neuroscience model and a parameter estimation problem. © 2024, CC BY-NC-SA.

关键词： Stochastic systems

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BRAIN-TO-TEXT BENCHMARK’24: LESSONS LEARNED

arXiv

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arXiv 2024年

作者： Willett, Francis R. Li, Jingyuan Le, Trung Fan, Chaofei Chen, Mingfei Shlizerman, Eli Chen, Yue Zheng, Xin Okubo, Tatsuo S. Benster, Tyler Lee, Hyun Dong Kounga, Maxwell Buchanan, E. Kelly Zoltowski, David Linderman, Scott W. Henderson, Jaimie M. Department of Neurosurgery Stanford University United States Department of Electrical & Computer Engineering University of Washington United States Department of Computer Science Stanford University United States Department of Applied Mathematics University of Washington United States China Neurosciences Phd Program Stanford University United States Wu Tsai Neurosciences Institute Department of Statistics Stanford University United States

Speech brain-computer interfaces aim to decipher what a person is trying to say from neural activity alone, restoring communication to people with paralysis who have lost the ability to speak intelligibly. The Brain-to-Text Benchmark’24 and associated competition was created to foster the advancement of decoding algorithms that convert neural activity to text. Here, we summarize the lessons learned from the competition ending on June 1, 2024 (the top 4 entrants also presented their experiences in a recorded webinar). The largest improvements in accuracy were achieved using an ensembling approach, where the output of multiple independent decoders was merged using a fine-tuned large language model (an approach used by all 3 top entrants). Performance gains were also found by improving how the baseline recurrent neural network (RNN) model was trained, including by optimizing learning rate scheduling and by using a diphone training objective. Improving upon the model architecture itself proved more difficult, however, with attempts to use deep state space models or transformers not yet appearing to offer a benefit over the RNN baseline. The benchmark will remain open indefinitely to support further work towards increasing the accuracy of brain-to-text algorithms. © 2024, CC BY.

关键词： Recurrent neural networks

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Optoelectric Raman Nanosensors: Overcoming Intrinsic Limit in Nano-biosensing

Research Square

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Research Square 2024年

作者： Lian, Bin Li, Huaizhi Guo, Jianhe Fan, Donglei Emma Materials Science and Engineering Program Texas Materials Institute The University of Texas AustinTX78712 United States Walker Department of Mechanical Engineering Texas Materials Institute The University of Texas at Austin AustinTX78712 United States Chandra Family Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX78712 United States

It is intrinsically difficult to detect low-concentration biomolecules with both ultra-sensitivity and high speed for early-stage disease diagnosis. The challenge originates from the small size of nanosensors, which enables ultra-sensitivity biosensing, while also substantially increases the detection time of dilute molecules. in this work, we report an original optoelectric sensing scheme, along with an innovative device design and a strategic fabrication approach to overcome such a challenge in biosensing. The proposed scheme exploits the profound optoelectric effect of semiconductor silicon nanowires, which can readily enrich trace-amounts of biomolecules at the point of laser and simultaneously detect Raman signals of focused molecules. The device design includes large arrays of silicon nanorods with electrodes integrated at their roots, and surface-distributed dense plasmonic silver nanoparticles for surface-enhanced Raman spectroscopy (SERS) detection. Operating at only -0.8 V in an electrochemical cell, these optoelectric nanosensors readily achieve a 150-fold signal enhancement, improving the detection limit of probing molecules, adenine, by five orders of magnitude, to 0.6 fM. The enhancement effect is robust, observed across concentrations from 1 μM to 1 fM. The working mechanism is general, not only for detecting small molecules, such as adenine, but also for large charged molecules, such as Vertebrate DNA. The underlying novel mechanism is unraveled by multiscale numerical simulations and calculations. This research, addressing an arduous bottleneck issues in nanobiosensing, is expected to inspire a new class of biochemical sensors, important for the practical detection of trace-amount biochemicals in solution, important for clinic relevant early-stage disease diagnostics. © 2024, CC BY.

关键词： Nanorods

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Corner cutting connects chiral colorimetry to net electric flux in lossless all-dielectric metasurfaces

arXiv

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arXiv 2024年

作者： Haddadin, Zaid Nguyen, Anna M.Y. Poulikakos, Lisa V. Department of Electrical & Computer Engineering UC San Diego La Jolla CA92093-0021 United States Department of Mechanical & Aerospace Engineering UC San Diego La Jolla CA92093-0021 United States Program of Materials Science & Engineering UC San Diego La Jolla CA92093-0021 United States

All-dielectric metasurfaces can produce structural colors, but the most advantageous design criteria are still being investigated. This work numerically studies how the two-dimensional shape of nanoparticles affects the colorimetric response under circularly polarized light (CPL) to develop a sensor distinguishing CPL orientations. Using lossless dielectric materials (silicon nitride on silicon dioxide), we achieve far-field dichroism by modifying oblong nanoparticles into L-shaped structures through corner cuts. This design suppresses one electric dipole under CPL illumination, leading to differential colorimetric responses. We link these responses to a decoupling effect in the near-field net electric flux. Our findings provide design guidelines for all-dielectric, lossless colorimetric sensors of chiral light. Copyright © 2024, The Authors. All rights reserved.

关键词： Silicon nitride

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Development of Buffer Zone into Living Lab - Garuda Smart City Framework: Systematic Review

Development of Buffer Zone into Living Lab - Garuda Smart Ci...

引用

International Conference on ICT For Smart Society (ICISS)

作者： Gunadi Emmanuel Suhono Harso Supangkat Ford Lumban Gaol Benny Ranti Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Fakultas Sains dan Teknologi Univ. Katolik Musi Charitas Palembang Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Computer Science Department Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

The phenomenon of urbanization in Indonesia is inevitable. The new residential and economic centers in suburban areas is also a problem in city development. The gradual planning and development of smart cities in a living lab require consideration of the right location for a living lab. This study wants to show that suburban areas as city buffer zones can become living laboratories for smart city development. The diversity of situations in cities and regencies across Indonesia, the potential for resources, and the problems faced are the challenges of developing a living lab - Garuda Smart City Framework. This research uses the method of reviewing the literature of research publications for the last five years (2019–2023) to obtain information on Smart City development in Indonesia. We collected selected articles from databases in Google Scholar, IEEE, and Scopus using the Publish and Perish 8. The search keywords used were garuda AND Smart city AND Framework. The findings show the potential and dynamics of buffer zones to become appropriate living laboratories. Smart city regional planning can more holistically involve neighborhoods and address urban issues.

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ENTROPY IS NOT ENOUGH FOR TEST-TIME ADAPTATION: FROM THE PERSPECTIVE OF DISENTANGLED FACTORS

arXiv

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arXiv 2024年

作者： Lee, Jonghyun Jung, Dahuin Lee, Saehyung Park, Junsung Shin, Juhyeon Hwang, Uiwon Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of School of Computer Science and Engineering Soongsil University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of Division of Digital Healthcare Yonsei University Korea Republic of AIIS ASRI INMC and ISRC Seoul National University Korea Republic of

Test-time adaptation (TTA) fine-tunes pre-trained deep neural networks for unseen test data. The primary challenge of TTA is limited access to the entire test dataset during online updates, causing error accumulation. To mitigate it, TTA methods have utilized the model output’s entropy as a confidence metric that aims to determine which samples have a lower likelihood of causing error. Through experimental studies, however, we observed the unreliability of entropy as a confidence metric for TTA under biased scenarios and theoretically revealed that it stems from the neglect of the influence of latent disentangled factors of data on predictions. Building upon these findings, we introduce a novel TTA method named Destroy Your Object (DeYO), which leverages a newly proposed confidence metric named Pseudo-Label Probability Difference (PLPD). PLPD quantifies the influence of the shape of an object on prediction by measuring the difference between predictions before and after applying an object-destructive transformation. DeYO consists of sample selection and sample weighting, which employ entropy and PLPD concurrently. For robust adaptation, DeYO prioritizes samples that dominantly incorporate shape information when making predictions. Our extensive experiments demonstrate the consistent superiority of DeYO over baseline methods across various scenarios, including biased and wild. Project page is publicly available at https://***/DeYO/. Copyright © 2024, The Authors. All rights reserved.

关键词： Entropy

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Light-driven single-cell rotational adhesion frequency assay

引用

eLight 2022年第1期2卷 154-164页

作者： Yaoran Liu Hongru Ding Jingang Li Xin Lou Mingcheng Yang Yuebing Zheng Department of Electrical and Computer Engineering The University of Texas at AustinAustinTX 78712USA Walker Department of Mechanical Engineering The University of Texas at AustinAustinTX 78712USA Materials Science&Engineering Program and Texas Materials Institute The University of Texas at AustinAustinTX 78712USA School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China Beijing National Laboratory for Condensed Matter Physics and Laboratory of Soft Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China Songshan Lake Materials Laboratory Dongguan 523808GuangdongChina Department of Biomedical Engineering The University of Texas at AustinAustinTX 78712USA

The interaction between cell surface receptors and extracellular ligands is highly related to many physiological processes in living *** techniques have been developed to measure the ligand-receptor binding kinetics at the single-cell ***,few techniques can measure the physiologically relevant shear binding affinity over a single cell in the clinical ***,we develop a new optical technique,termed single-cell rotational adhesion frequency assay(scRAFA),that mimics in vivo cell adhesion to achieve label-free determination of both homogeneous and heterogeneous binding kinetics of targeted cells at the subcellular ***,the scRAFA is also applicable to analyze the binding affinities on a single cell in native human *** its superior performance and general applicability,scRAFA is expected to find applications in study of the spatial organization of cell surface receptors and diagnosis of infectious diseases.

关键词： diagnosis kinetics rotational

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Enhanced Prognostics and Health Management in Automated Driving Systems: Using Graph Neural Networks to Recognize Operational Contexts

Enhanced Prognostics and Health Management in Automated Driv...

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Prognostics and System Health Management Conference (PHM)

作者： Peng Su Yeqi Wang Conglei Xiang Erik Wendel Madhav Mishra DeJiu Chen Department of Engineering Design Mechatronics Division KTH Royal Institute of Technology Stockholm Sweden Embedded Systems Master Program of Electrical Engineering and Computer Science (EECS) School KTH Royal Institute of Technology Stockholm Sweden Digital Systems Division RISE Research Institutes of Sweden Gothenburg Sweden

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Prognostics and health management (PHM) is an engineering discipline that aims to maintain system behaviour and function and ensure mission success, safety and effectiveness. Addressing the challenges in prognostics and health management for modern intelligent systems, especially automated driving systems, is complex due to the contextual nature of faults. This complexity necessitates a thorough understanding of spatial, and temporal conditions, and relationships within operational scenarios and life-cycle stages. This paper introduces a framework designed to automatically recognize driving scenarios in automated driving systems using graph neural networks (GNNs). The framework extracts relational data from image frames, constructing graph-based models and transforming unstructured sensory data into structured data with diverse node types and relationships. A specific graph neural network processes the graph model to reveal and detect operational conditions and relationships. The proposed framework is evaluated using the KITTI dataset, demonstrating superior performance compared to conventional feed-forward networks such as MLP, particularly in handling relational data.

关键词： Graph neural networks Data models Safety Complexity theory Data mining Prognostics and health management Intelligent systems

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Morphological Investigation and Ph Sensing Properties of β-Ga2O3 Egfet-Ph Sensor

SSRN

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SSRN 2023年

作者： Wuu, Dong-Sing Yadlapalli, Bharath Kumar Chou, Hsin-Yu Chiang, Jung-Lung Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung411030 Taiwan Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Nantou54561 Taiwan

In our study, β-Ga2O3 particles of various morphologies deposited on FTO glass substrates through hydrothermal method under different pH conditions and pre-stirring temperatures. The particles examined using XRD, FESEM, FTIR and Raman spectroscopy instruments. The results showed that the β-Ga2O3 microrods prepared with pH=3.15 solution at different pre-stirring temperatures followed by hydrothermal reaction had several crystalline orientations ([−401], [002], [403]). The FTIR and Raman spectra measurements confirmed the existence of Ga−O−Ga and Ga−OH bending modes. In the range of pH=3-11, the EGFET-pH sensor prepared with β-Ga2O3 microrods shown a high current-pH sensitivity of 0.541 (mA)1/2 /pH with a linearity of 97.83 % and a high voltage-pH sensitivity of 73.99 mV/pH with linearity of 96.85 %. These results suggest that β-Ga2O3 microrods have pH sensitivity higher than the ideal Nernstian response. This confirms the use of β-Ga2O3 microrods as a sensing membrane in high-performance pH sensors or biosensors. © 2023, The Authors. All rights reserved.

关键词： Gallium compounds

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Ga2O3 nanorods synthesized by hydrothermal method for dual-functional sensing of pH value and glucose

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Sensors and Actuators A: Physical 2023年 363卷

作者： Chou, Hsin-Yu Yadlapalli, Bharath Kumar Yen, Chao-Chun Singh, Anoop Kumar Chiang, Jung-Lung Wuu, Dong-Sing Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung411030 Taiwan Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Nantou54561 Taiwan

In this work, hydrothermal (HT)-synthesized gallium oxide (Ga2O3) nanorods were applied on indium tin oxide (ITO) glass substrates to create a dual-functional pH-glucose sensing device. Extended-gate field-effect transistors (EGFETs) were designed for pH and glucose sensing, and the response to pH levels ranging from 1 to 11 was tested using both chemical bath deposition (CBD) and high-pressure hydrothermal methods. Two sensor configurations, Ga2O3(CBD)/ITO/glass and Ga2O3(HT)/ITO/glass, were immersed in solution pH1 to 11 and cultured medium for hydrogen ion and glucose sensing. The results demonstrated that, for pH sensing in different samples, both IDS-VDS analysis and IDS-VGS analysis showed superior linearity and sensitivity with the HT method. For glucose detection, the HT method was selected for further experiments due to its maintained concentration-dependent relationship and selectivity towards various common sugars. When using culture medium DMEM as the sample (4.5 mg/ml glucose concentration), the accuracy of glucose estimation reached 99%. Stability and biocompatibility tests were also conducted, and the results indicated consistent performance. In summary, the HT-synthesized Ga2O3 nanorods exhibited high sensitivity, selectivity, and stability without affecting cell growth. Therefore, they hold great potential for applications not only in general blood glucose sensing but also in studying cell microenvironment metabolism. © 2023 Elsevier B.V.

关键词： Nanorods

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