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arXiv 2020年

作者： She, Xichen Zhai, Yaya Henao, Ricardo Woods, Christopher W. Chiu, Christopher Ginsburg, Geoffrey S. Song, Peter X.K. Hero, Alfred O. Department of Biostatistics University of Michigan Ann ArborMI48109 United States Department of Computational Medicine and Bioinformatics University of Michigan Ann ArborMI48109 United States Center for Applied Genomics and Precision Medicine Duke University DurhamNC27708 United States Department of Infectious Disease Imperial College London LondonW2 1PG United Kingdom Departments of Electrical Engineering and Computer Science Biomedical Engineering and Statistics University of Michigan Ann ArborMI48109 United States

Objective: To develop a multi-channel device event segmentation and feature extraction algorithm that is robust to changes in data distribution. Methods: We introduce an adaptive transfer learning algorithm to classify and segment events from non-stationary multi-channel temporal data. Using a multivariate hidden Markov model (HMM) and Fisher’s linear discriminant analysis (FLDA) the algorithm adaptively adjusts to shifts in distribution over time. The proposed algorithm is unsupervised and learns to label events without requiring a priori information about true event states. The procedure is illustrated on experimental data collected from a cohort in a human viral challenge (HVC) study, where certain subjects have disrupted wake and sleep patterns after exposure to a H1N1 influenza pathogen. Results: Simulations establish that the proposed adaptive algorithm significantly outperforms other event classification methods. When applied to early time points in the HVC data the algorithm extracts sleep/wake features that are predictive of both infection and infection onset time. Conclusion: The proposed transfer learning event segmentation method is robust to temporal shifts in data distribution and can be used to produce highly discriminative event-labeled features for health monitoring. Significance: Our integrated multisensor signal processing and transfer learning method is applicable to many ambulatory monitoring applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Wearable sensors

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Interactive control approach to 3D shape reconstruction

arXiv

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arXiv 2019年

作者： Islam, Bipul Liu, Ji Yezzi, Anthony Sandhu, Romeil Department of Computer Science & Biomedical Informatics Stony Brook University Stony BrookNY11794 United States Department of Electrical and Computer Engineering Stony Brook University Stony BrookNY11794 United States Department of Electrical and Computer Engineering Georgia Tech AtlantaGA30309 United States Departments of Applied Mathematics & Statistics Stony Brook University Stony BrookNY11794 United States

The ability to accurately reconstruct the 3D facets of a scene is one of the key problems in robotic vision. However, even with recent advances with machine learning, there is no high-fidelity universal 3D reconstruction method for this optimization problem as schemes often cater to specific image modalities and are often biased by scene abnormalities. Simply put, there always remains an "information" gap due to the dynamic nature of real-world scenarios. To this end, we demonstrate a feedback control framework which invokes operator inputs (also prone to errors) in order to augment existing reconstruction schemes. For proof-of-concept, we choose a classical region-based stereoscopic reconstruction approach and show how an ill-posed model can be augmented with operator input to be much more robust to scene artifacts. We provide necessary conditions for stability via Lyapunov analysis and perhaps more importantly, we show that the stability depends on a notion of absolute curvature. Mathematically, this aligns with previous work that has shown Ricci curvature as proxy for functional robustness of dynamical networked systems. We conclude with results that show how our method can improve standalone reconstruction schemes. Copyright © 2019, The Authors. All rights reserved.

关键词： Stereo image processing

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A structural haplotype in the 17q21.31 MAPT region is associated with increased risk for chronic traumatic encephalopathy endophenotypes

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Cell Reports Medicine 2025年第5期6卷 102084-102084页

作者： Han, Xudong Zhang, Yichi Petrosky, Jillian N. Bald, Sarah Sherva, Richard M. Labadorf, Adam Cherry, Jonathan D. Chung, Jaeyoon Farrell, Kurt Abdolmohammadi, Bobak Durape, Shruti Martin, Brett M. Palmisano, Joseph N. Farrell, John J. Alvarez, Victor E. Huber, Bertrand R. Dwyer, Brigid Daneshvar, Daniel H. Jun, Gyungah R. Lunetta, Kathryn L. Goldstein, Lee E. Katz, Douglas I. Cantu, Robert C. Shenton, Martha E. Cummings, Jeffrey L. Reiman, Eric M. Stern, Robert A. Alosco, Michael L. Tripodis, Yorghos Farrer, Lindsay A. Stein, Thor D. Crary, John F. McKee, Ann C. Mez, Jesse Bioinformatics Graduate Program Boston University Boston MA United States Section of Biomedical Genetics Department of Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Department of Neurology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston University Alzheimer's Disease Research Center Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston VA Healthcare System Boston MA United States Boston University Chronic Traumatic Encephalopathy Center Boston University Boston MA United States Department of Pathology and Laboratory Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Pathology Neuroscience and Artificial Intelligence & Human Health Neuropathology Brain Bank & Research CoRE Friedman Brain Institute Ronald M. Loeb Center for Alzheimer's Disease Icahn School of Medicine at Mount Sinai New York NY United States Biostatistics and Epidemiology Data Analytics Center Boston University School of Public Health Boston MA United States Bedford VA Healthcare System Bedford MA United States Braintree Rehabilitation Hospital Braintree MA United States Department of Physical Medicine and Rehabilitation Harvard Medical School Boston MA United States Department of Rehabilitation and Human Performance Brain Injury Research Center Icahn School of Medicine at Mount Sinai New York NY United States Department of Neurology Icahn School of Medicine at Mount Sinai New York NY United States Department of Biostatistics Boston University School of Public Health Boston MA United States Department of Ophthalmology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Biomedical Electrical & Computer Engineering Boston University College of Engineering Boston MA United States Departments of Radiology and Psychiatry Boston University Chobanian & Avedisia

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repetitive head impact (RHI) exposure. Genetic variation in the 17q21.31 region, containing microtubule-associated protein tau (MAPT), has been implicated in tauopathies but has not been investigated in CTE. The region includes a megabase-long inversion (H1/H2) and copy-number variations, including α, β, and γ segments, which can be characterized as nine segregating structural haplotypes. We leveraged array SNP data and a reference panel across the 17q21.31 region to impute structural haplotypes and test their association with CTE endophenotypes in 447 European ancestry brain donors with RHI exposure. The H1β1γ1 haplotype was significantly associated with dementia and semi-quantitative tau burden in multiple cortical and medial temporal regions commonly affected in CTE. H1β1γ1 differential expression analyses in dorsolateral frontal cortex implicated cis-acting genes and inflammatory pathways. Taken together, the H1β1γ1 haplotype may help explain CTE heterogeneity among those with similar RHI exposure. © 2025 The Authors

关键词： 17q21.31 chronic traumatic encephalopathy dementia differential gene expression immune system MAPT repetitive head impacts structural haplotypes tauopathy traumatic brain injury

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Controlled mechanical assembly of complex 3D mesostructures and strain sensors by tensile buckling

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npj Flexible Electronics 2018年第1期2卷 120-126页

作者： Xiaogang Guo Xueju Wang Dapeng Ou Jilong Ye Wenbo Pang Yonggang Huang John A.Rogers Yihui Zhang Department of Engineering Mechanics Center for Mechanics and Materials and Center for Flexible Electronics TechnologyAMLTsinghua University100084 BeijingPeople’s Republic of China Department of Materials Science and Engineering Northwestern UniversityEvanstonIL 60208USA State Key Laboratory of Tribology Tsinghua University100084 Beijing People’s Republic of China Center for Nano and Micro Mechanics Tsinghua University100084 Beijing People’s Republic of China Departments of Civil and Environmental Engineering Mechanical Engineeringand Materials Science and EngineeringNorthwestern UniversityEvanstonIL 60208USA Departments of Materials Science and Engineering Biomedical EngineeringNeurological SurgeryChemistryMechanical EngineeringElectrical Engineering and Computer ScienceCenter for Bio-Integrated ElectronicsSimpson Querrey Institute for BioNanotechnologyNorthwestern UniversityEvanstonIL 60208USA

Recent research establishes methods of controlled mechanical assembly as versatile routes to three-dimensional(3D)mesostructures from patterned 2D films,with demonstrated applicability to a broad range of materials(e.g.,semiconductors,polymers,metals,and their combinations)and length scales(e.g.,from sub-microscale to centimeter scale).Previously reported schemes use pre-stretched elastomeric substrates as assembly platforms to induce compressive buckling of 2D precursor structures,thereby enabling their controlled transformation into 3D ***,we introduce tensile buckling as a different,complementary strategy that bypasses the need for a pre-stretched platform,thereby simplifying the assembly process and opening routes to additional classes of 3D geometries unobtainable with compressive buckling.A few basic principles in mechanics serve as guidelines for the design of 2D precursor structures that achieve large out-of-plane motions and associated 3D transformations due to tensile *** and computational studies of nearly 20 examples demonstrate the utility of this approach in the assembly of complex 3D mesostructures with characteristic dimensions from micron to millimeter *** results also establish the use of nonlinear mechanics modeling as a mechanism for designing systems that yield desired 3D geometries.A strain sensor that offers visible readout and large detectable strain range through a collection of mechanically triggered electrical switches and LEDs serves as an application example.

关键词： strain buckling thereby

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Ambient temperature fluctuations exhibit inverse-cubic spectral behavior over time scales from a minute to a day

arXiv

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arXiv 2019年

作者： Lowen, Steven B. Mohan, Nishant Teich, Malvin Carl Boston University Photonics Center BostonMA02215 United States Boston University Department of Electrical & Computer Engineering BostonMA02215 United States Harvard Medical School BostonMA02115 United States Boston University Department of Biomedical Engineering BostonMA02215 United States Massachusetts General Hospital Wellman Center for Photomedicine BostonMA02114 United States Wasatch Photonics MorrisvilleNC27560 United States Boston University Departments of Electrical & Computer Engineering Biomedical Engineering and Physics BostonMA02215 United States Columbia University Department of Electrical Engineering New YorkNY10027 United States

Ambient temperature fluctuations are of importance in a wide variety of scientific and technological arenas. In a series of experiments carried out in our laboratory over a 1.5-year period, we discovered that these fluctuations exhibit 1/f3 spectral behavior over the frequency range 1.0 × 10−5 ≤ f ≤ 2.5 × 10−2 Hz, corresponding to 40 s ≤ Tf ≤ 1.2 d, where Tf = 1/f. This result, which is novel, emerges over a broad range of conditions. For longer time periods, 1.2 f ≤ 12 d, corresponding to the frequency range 1.0×10−6 ≤ f −5 Hz, we observed 1/f2 spectral behavior. This latter result is in agreement with that observed in data collected at European weather stations. Scalograms computed from our data are consistent with the periodograms. Copyright © 2019, The Authors. All rights reserved.

关键词： Temperature distribution

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Photon-count fluctuations exhibit inverse-square spectral behavior that extends to < 1 µHz

arXiv

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arXiv 2019年

作者： Mohan, Nishant Lowen, Steven B. Teich, Malvin Carl Boston University Photonics Center BostonMA02215 United States Boston University Department of Biomedical Engineering BostonMA02215 United States Massachusetts General Hospital Wellman Center for Photomedicine BostonMA02114 United States Wasatch Photonics MorrisvilleNC27560 United States Boston University Department of Electrical & Computer Engineering BostonMA02215 United States Harvard Medical School BostonMA02115 United States Boston University Departments of Electrical & Computer Engineering Biomedical Engineering and Physics BostonMA02215 United States Columbia University Department of Electrical Engineering New YorkNY10027 United States

A broad variety of light sources exhibit photon-count fluctuations that display inverse-square spectral behavior at extremely low frequencies. These sources include light-emitting diodes, superluminescent diodes, laser diodes, incandescent sources, and betaluminescent sources. In a series of experiments carried out over a 1.5-year period, the photon-count fluctuations for these sources were found to exhibit a 1/f2 spectral signature over the frequency range 1.0×10−6 ≤ f ≤ 5.0×10−4 Hz, corresponding to 33 min ≤ Tf ≤ 11.6 d, where Tf ≡ 1/f. The lower time limit is established by the photodetector noise floor while the upper time limit is determined by the duration of the individual experiments. Scalograms computed from our data are consistent with the periodograms. The universal character of this inverse-square spectral behavior stands in sharp contrast to the optical spectra of these sources, which differ markedly. Time traces of the photon-count fluctuations are examined to shed light on the origin of this enigmatic baseband spectral behavior. Copyright © 2019, The Authors. All rights reserved.

关键词： Light sources

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Breast cancer histopathology using infrared spectroscopic imaging: The impact of instrumental configurations

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Clinical Spectroscopy 2021年 3卷

作者： Shachi Mittal Tomasz P. Wrobel Michael Walsh Andre Kajdacsy-Balla Rohit Bhargava Department of Bioengineering and Beckman Institute for Advanced Science and Technology University of Illinois at Urbana−Champaign Urbana IL United States Department of Materials Science and Biomedical Engineering University of Wisconsin – Eau Claire WI United States Department of Pathology University of Illinois at Chicago IL United States Departments of Mechanical Science and Engineering Electrical and Computer Engineering Chemical and Biomolecular Engineering and Chemistry University of Illinois at Urbana−Champaign Urbana IL United States Cancer Center at Illinois University of Illinois at Urbana−Champaign Urbana IL United States

Digital analysis of cancer specimens using spectroscopic imaging coupled to machine learning is an emerging area that links spatially localized spectral signatures to tissue structure and disease. In this study, we examine the role of spatial-spectral tradeoffs in infrared spectroscopic imaging configurations for probing tumors and the associated microenvironment profiles at different levels of model complexity. We image breast tissue using standard and high-definition Fourier Transform Infrared (FT-IR) imaging and systematically examine the localization, spectral origins, and utility of data for classification. Results demonstrate that higher spatial detail provides high sensitivity and specificity of tissue segmentation, despite the increased subcellular variability. High definition imaging also allows accurate analysis of complex, multiclass models of breast tissue without compromising accuracy. A comparison of results also highlights the key differences in the data distributions and classification performance across modalities to better guide decision making for acquiring and analyzing IR imaging data for specific histopathological models.

关键词： High definition imaging Standard definition Breast pathology Machine learning Tissue segmentation

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A framework and resource for global collaboration in non-human primate neuroscience

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Current Research in Neurobiology 2023年 4卷 100079页

作者： Hartig, Renée Klink, P. Christiaan Polyakova, Zlata Dehaqani, Mohammad-Reza A. Bondar, Igor Merchant, Hugo Vanduffel, Wim Roe, Anna Wang Nambu, Atsushi Thirumala, M. Shmuel, Amir Kapoor, Vishal Gothard, Katalin M. Evrard, Henry C. Basso, Michele A. Petkov, Christopher I. Mitchell, Anna S. Max Planck Institute for Biological Cybernetics Max-Planck-Ring 11 Tübingen 72076 Germany Functional and Comparative Neuroanatomy Laboratory Werner Reichardt Centre for Integrative Neuroscience Eberhard Karls University of Tübingen Otfried-Müller-Straße 25 Tübingen 72076 Germany Department of Psychiatry and Psychotherapy University Medical Center Johannes Gutenberg-University Mainz 55131 Germany Nathan S. Kline Institute for Psychiatric Research Center for Biomedical Imaging and Neuromodulation Orangeburg New York 10962 United States Department of Vision and Cognition Netherlands Institute for Neuroscience Royal Netherlands Academy of Arts and Sciences Meibergdreef 47 Amsterdam 1105 BA Netherlands Laboratory of Visual Brain Therapy Sorbonne Université Institut National de la Santé et de la Recherche Médicale Centre National de la Recherche Scientifique Institut de la Vision Paris F-75012 France Experimental Psychology Helmholtz institute Utrecht University Heidelberglaan 1 Utrecht 3584 CS Netherlands Center for Human Nature Artificial Intelligence and Neuroscience Hokkaido University Sapporo 060-0812 Japan School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iran Department of Brain and Cognitive Sciences Cell Science Research Center Royan Institute for Stem Cell Biology and Technology ACECR Tehran Iran Institute of Higher Nervous Activity and Neurophysiology Russian Academy of Sciences Moscow Russian Federation Institute of Neurobiology Universidad Nacional Autónoma de México Campus Juriquilla Department of Neurophysiology Querétaro 76230 Mexico Laboratory for Neuro- and Psychophysiology Department of Neurosciences KU Leuven Medical School Leuven 3000 Belgium Leuven Brain Institute KU Leuven Leuven 3000 Belgium Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlest

As science and technology evolve, there is an increasing need for promotion of international scientific exchange. Collaborations, while offering substantial opportunities for scientists and benefit to society, also present challenges for those working with animal models, such as non-human primates (NHPs). Diversity in regulation of animal research is sometimes mistaken for the absence of common international welfare standards. Here, the ethical and regulatory protocols for 13 countries that have guidelines in place for biomedical research involving NHPs were assessed with a focus on neuroscience. Review of the variability and similarity in trans-national NHP welfare regulations extended to countries in Asia, Europe and North America. A tabulated resource was established to advance solution-oriented discussions and scientific collaborations across borders. Our aim is to better inform the public and other stakeholders. Through cooperative efforts to identify and analyze information with reference to evidence-based discussion, the proposed key ingredients may help to shape and support a more informed, open framework. This framework and resource can be expanded further for biomedical research in other countries. © 2023

关键词： Ethics Macaque Marmoset Regulations Requirements Welfare

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Author Correction: Diversity amongst human cortical pyramidal neurons revealed via their sag currents and frequency preferences

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Nature communications 2022年第1期13卷 1689页

作者： Homeira Moradi Chameh Scott Rich Lihua Wang Fu-Der Chen Liang Zhang Peter L Carlen Shreejoy J Tripathy Taufik A Valiante Krembil Brain Institute University Health Network Toronto ON Canada. Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada. Max Planck Institute of Microstructure Physics Halle Germany. Departments of Medicine & Physiology University of Toronto Toronto ON Canada. Institute of Biomedical Engineering University of Toronto Toronto ON Canada. Krembil Centre for Neuroinformatics Centre for Addiction and Mental Health Toronto ON Canada. Institute of Medical Sciences University of Toronto Toronto ON Canada. Department of Psychiatry University of Toronto Toronto ON Canada. Krembil Brain Institute University Health Network Toronto ON Canada. taufik.valiante@uhn.ca. Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada. taufik.valiante@uhn.ca. Institute of Biomedical Engineering University of Toronto Toronto ON Canada. taufik.valiante@uhn.ca. Institute of Medical Sciences University of Toronto Toronto ON Canada. taufik.valiante@uhn.ca. Division of Neurosurgery Department of Surgery University of Toronto Toronto ON Canada. taufik.valiante@uhn.ca.

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Adaboost based Parameterized Methods for Wireless Sensor Networks

Adaboost based Parameterized Methods for Wireless Sensor Net...

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International Conference On Smart Technologies For Smart Nation (SmartTechCon)

作者： Yadahalli, Safi Nighot, Mininath K. Department of Electrical and Computer Engineering Oakland University Rochester MI USA Departments of Biomedical Engineering and Electrical Engineering The State University of New York at Buffalo Buffalo NY USA

ISBN: (纸本)9781538605691

In the new distributed architecture, intrusion detection is one of the main requirements. In our research, two adaboost algorithms have been proposed. The very first procedure is a traditional online adaboost algorithm, where we make use of decision stumps. Decision stumps will be regarded as weak classifiers. In the following second procedure we make use of an enhanced online adaboost algorithm with online Gaussian Mixture Model (GMM) which will be referred as weak classifiers. Additionally we will be having distributed incursion detection framework, where local parameterized models for incursion detection are formed in every node by Adaboost procedures. Global detection models are also built up at every node by the combination of local parametric models by means of minor quantity of examples in the node. This arrangement is attained by a procedure constructed on the Particle Swarm Optimization (PSO) and also Support Vector Machines(SVM). Incursions will be detected using Global model in every node. Data collected on experimental results shows enhanced online adaboost process with GMM gives improved and high detection rate and reduced false alarms than the previous Adaboost processes. Our two algorithms outperform the current incursion detection procedures. It can be seen that our SVM and PSO based algorithms efficiently combines local models into global models at every node. The Global models in the node can identify and alarm incursions types which can be found in different nodes without sharing of samples of those incursion types.

关键词： network intrusions network incursions Dynamic distributed detection Adaboost learning parameterized model

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