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arXiv 2019年

作者： Cao, Xiaozhi Liao, Congyu Zhang, Zijing Iyer, Siddharth Srinivasan Chen, Zhifeng Lo, Wei-Ching Liu, Huafeng Wang, Kang He, Hongjian Setsompop, Kawin Zhong, Jianhui Bilgic, Berkin Center for Brain Imaging Science and Technology Department of Biomedical Engineering Zhejiang University Zhejiang Hangzhou China Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA United States Department of Radiology Harvard Medical School CharlestownMA United States State Key Laboratory of Modern Optical Instrumentation College of Optical Science and Engineering Zhejiang University Zhejiang Hangzhou China Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States School of Biomedical Engineering Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University Guangzhou China Siemens Medical Solutions BostonMA United States Department of Neurology The First Affiliated Hospital School of Medicine Zhejiang University Hangzhou China Harvard-MIT Department of Health Sciences and Technology CambridgeMA United States Department of Imaging Sciences University of Rochester NY United States

Purpose: To rapidly obtain high isotropic-resolution T2 maps with whole-brain coverage and high geometric fidelity. Methods: A T2 blip-up/down echo planar imaging (EPI) acquisition with generalized Slice-dithered enhanced resolution (T2-BUDA-gSlider) is proposed. A radiofrequency (RF)-encoded multi-slab spin-echo EPI acquisition with multiple echo times (TEs) was developed to obtain high SNR efficiency with reduced repetition time (TR). This was combined with an interleaved 2-shot EPI acquisition using blip-up/down phase encoding. An estimated field map was incorporated into the joint multi-shot EPI reconstruction with a structured low rank constraint to achieve distortion-free and robust reconstruction for each slab without navigation. A Bloch simulated subspace model was integrated into gSlider reconstruction and utilized for T2 quantification. Results: In vivo results demonstrated that the T2 values estimated by the proposed method were consistent with gold standard spin-echo acquisition. Compared to the reference 3D fast spin echo (FSE) images, distortion caused by off-resonance and eddy current effects were effectively mitigated. Conclusion: BUDA-gSlider SE-EPI acquisition and gSlider-subspace joint reconstruction enabled distortion-free whole-brain T2 mapping in 2 min at ~1 mm3 isotropic resolution, which could bring significant benefits to related clinical and neuroscience applications. Copyright © 2019, The Authors. All rights reserved.

关键词： Spin polarization

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A Large Scale Magneto-ionic Fluctuation in the Local Environment of Periodic Fast Radio Burst Source, FRB 20180916B

arXiv

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arXiv 2022年

作者： McKinven, Ryan Gaensler, B.M. Michilli, D. Masui, K. Kaspi, V.M. Bhardwaj, M. Cassanelli, T. Chawla, P. Dong, F. Adam Fonseca, E. Leung, C. Li, D.Z. Ng, C. Patel, C. Petroff, E. Pearlman, A.B. Pleunis, Z. Rafiei-Ravandi, M. Rahman, M. Sand, K.R. Shin, K. Scholz, P. Stairs, I.H. Smith, K. Su, J. Tendulkar, S. Department of Physics McGill University 3600 rue University MontréalQCH3A 2T8 Canada McGill Space Institute McGill University 3550 rue University MontréalQCH3A 2A7 Canada Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada David A. Dunlap Department of Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Department of Physics Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Mit Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Dept. of Physics and Astronomy 6224 Agricultural Road VancouverBCV6T 1Z1 Canada Lane Department of Computer Science and Electrical Engineering 1220 Evansdale Drive PO Box 6109 MorgantownWV26506 United States Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building MorgantownWV26505 United States Department of Physics and Astronomy West Virginia University P.O. Box 6315 MorgantownWV26506 United States Cahill Center for Astronomy and Astrophysics California Institute of Technology 1216 E California Boulevard PasadenaCA91125 United States Sidrat Research PO Box 73527 RPO Wychwood TorontoONM6C 4A7 Canada Perimeter Institute for Theoretical Physics 31 Caroline Street N WaterlooONN2L 2Y5 Canada Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Mumbai400005 India National Centre for Radio Astrophysics Post Bag 3 Ganeshkhind Pune411007 India

Fast radio burst (FRB) source 20180916B exhibits a 16.33-day periodicity in its burst activity. It is as of yet unclear what proposed mechanism produces the activity, but polarization information is a key diagnostic. Here, we report on the polarization properties of 44 bursts from FRB 20180916B detected between 2018 December and 2021 December by CHIME/FRB, the FRB project on the Canadian Hydrogen Intensity Mapping Experiment the Canadian Hydrogen Intensity Mapping Experiment. In contrast to previous observations, we find significant variations in the Faraday rotation measure (RM) of FRB 20180916B. Over the nine month period 2021 April-2021 December we observe an apparent secular increase in RM of ∼ 50 radm-2(a fractional change of over 40%) that is accompanied by a possible drift of the emitting band to lower frequencies. This interval displays very little variation in the dispersion measure (ΔDM 0.8 pc cm-3) which indicates that the observed RM evolution is likely produced from coherent changes in the Faraday-active medium's magnetic field. Burst-to-burst RM variations appear unrelated to the activity cycle phase. The degree of linear polarization of our burst sample ( 80%) is consistent with the negligible depolarization expected for this source in the 400-800 MHz bandpass of CHIME. FRB 20180916B joins other repeating FRBs in displaying substantial RM variations between bursts. This is consistent with the notion that repeater progenitors may be associated with young stellar populations by their preferential occupation of dynamic magnetized environments commonly found in supernova remnants, pulsar wind nebulae or near high mass stellar companions. © 2022, CC BY.

关键词： Hydrogen

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A CHIME/FRB study of burst rate and morphological evolution of the periodically repeating FRB 20180916B

arXiv

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arXiv 2023年

作者： Sand, Ketan R. Breitman, Daniela Michilli, Daniele Kaspi, Victoria M. Chawla, Pragya Fonseca, Emmanuel McKinven, Ryan Nimmo, Kenzie Pleunis, Ziggy Shin, Kaitlyn Andersen, Bridget C. Bhardwaj, Mohit Boyle, P.J. Brar, Charanjot Cassanelli, Tomas Cook, Amanda M. Curtin, Alice P. Dong, Fengqiu Adam Eadie, Gwendolyn M. Gaensler, B.M. Kaczmarek, Jane Lanman, Adam Leung, Calvin Masui, Kiyoshi W. Rahman, Mubdi Pandhi, Ayush Pearlman, Aaron B. Petroff, Emily Rafiei-Ravandi, Masoud Scholz, Paul Shah, Vishwangi Smith, Kendrick Stairs, Ingrid Stenning, David C. Department of Physics McGill University 3600 rue University MontréalQCH3A 2T8 Canada Trottier Space Institute McGill University 3550 rue University MontréalQCH3A 2A7 Canada Scuola Normale Superiore Piazza dei Cavalieri 7 PisaI-56126 Italy MIT Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Department of Physics Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building MorgantownWV26505 United States Department of Physics and Astronomy West Virginia University P.O. Box 6315 MorgantownWV26506 United States Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Department of Physics Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Department of Electrical Engineering Universidad de Chile Av. Tupper 2007 Santiago8370451 Chile David A. Dunlap Department of Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Department of Physics and Astronomy University of British Columbia 6224 Agricultural Road VancouverBCV6T 1Z1 Canada Department of Statistical Sciences University of Toronto 700 University Ave 9th Floor TorontoONM5G 1X6 Canada CSIRO Space and Astronomy Parkes Observatory P.O. Box 276 ParkesNSW2870 Australia Department of Computer Science Math Physics and Statistics University of British Columbia KelownaBCV1V 1V7 Canada NHFP Einstein Fellow United States Sidrat Research 124 Merton Street Suite 507 TorontoONM4S 2Z2 Canada Perimeter Institute for Theoretical Physics 31 Caroline Street N WaterlooONN25 2YL Canada Department of Physics and Astronomy York Univer

FRB 20180916B is a repeating Fast Radio Burst (FRB) with a 16.3-day periodicity in its activity. In this study, we present morphological properties of 60 FRB 20180916B bursts detected by CHIME/FRB between 2018 August and 2021 December. We recorded raw voltage data for 45 of these bursts, enabling microseconds time resolution in some cases. We studied variation of spectro-temporal properties with time and activity phase. We find that the variation in Dispersion Measure (DM) is .1 pc cm−3 and that there is burst-to-burst variation in scattering time estimates ranging from ∼0.16 to over 2 ms, with no discernible trend with activity phase for either property. Furthermore, we find no DM and scattering variability corresponding to the recent change in rotation measure from the source, which has implications for the immediate environment of the source. We find that FRB 20180916B has thus far shown no epochs of heightened activity as have been seen in other active repeaters by CHIME/FRB, with its burst count consistent with originating from a Poissonian process. We also observe no change in the value of the activity period over the duration of our observations and set a 1σ upper limit of 1.5 × 10−4 day day−1 on the absolute period derivative. Finally, we discuss constraints on progenitor models yielded by our results, noting that our upper limits on changes in scattering and dispersion measure as a function of phase do not support models invoking a massive binary companion star as the origin of the 16.3-day periodicity. © 2023, CC BY.

关键词： Dispersions

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Joint multi-contrast variational network reconstruction (jVN) with application to rapid 2D and 3D imaging

arXiv

引用

arXiv 2019年

作者： Polak, Daniel Cauley, Stephen Bilgic, Berkin Gong, Enhao Bachert, Peter Adalsteinsson, Elfar Setsompop, Kawin Department of Physics and Astronomy Heidelberg University Heidelberg Germany Department of Radiology A. A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA United States Siemens Healthcare GmbH Erlangen Germany Harvard Medical School BostonMA United States Harvard-MIT Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Subtle Medical Inc Menlo ParkCA United States Heidelberg Germany Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

Purpose: To improve the image quality of highly accelerated multi-channel MRI data by learning a joint variational network that reconstructs multiple clinical contrasts jointly. Methods: Data from our multi-contrast acquisition was embedded into the variational network architecture where shared anatomical information is exchanged by mixing the input contrasts. Complementary k-space sampling across imaging contrasts and Bunch-Phase/Wave-Encoding were used for data acquisition to improve the reconstruction at high accelerations. At 3T, our joint variational network approach across T1w, T2w and T2-FLAIR-weighted brain scans was tested for retrospective under-sampling at R=6 (2D) and R=4x4 (3D) acceleration. Prospective acceleration was also performed for 3D data where the combined acquisition time for whole brain coverage at 1 mm isotropic resolution across three contrasts was less than three minutes. Results: Across all test datasets, our joint multi-contrast network better preserved fine anatomical details with reduced image-blurring when compared to the corresponding single-contrast reconstructions. Improvement in image quality was also obtained through complementary k-space sampling and Bunch-Phase/Wave-Encoding where the synergistic combination yielded the overall best performance as evidenced by exemplarily slices and quantitative error metrics. Conclusion: By leveraging shared anatomical structures across the jointly reconstructed scans, our joint multi-contrast approach learnt more efficient regularizers which helped to retain natural image appearance and avoid over-smoothing. When synergistically combined with advanced encoding techniques, the performance was further improved, enabling up to R=16-fold acceleration with good image quality. This should help pave the way to very rapid high-resolution brain exams. Copyright © 2019, The Authors. All rights reserved.

关键词： Image quality

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Regret bounds and regimes of optimality for user-user and item-item collaborative filtering

arXiv

引用

arXiv 2017年

作者： Bresler, Guy Karzand, Mina Department of Electrical Engineering and Computer Science MIT Wisconsin Institute of Discovery University of Wisconsin Madison

We consider an online model for recommendation systems, with each user being recommended an item at each time-step and providing ‘like’ or ‘dislike’ feedback. Each user may be recommended a given item at most once. A latent variable model specifies the user preferences: both users and items are clustered into types. All users of a given type have identical preferences for the items, and similarly, items of a given type are either all liked or all disliked by a given user. We assume that the matrix encoding the preferences of each user type for each item type is randomly generated;in this way, the model captures structure in both the item and user spaces, the amount of structure depending on the number of each of the types. The measure of performance of the recommendation system is the expected number of disliked recommendations per user, defined as expected regret. We propose two algorithms inspired by user-user and item-item collaborative filtering (CF), modified to explicitly make exploratory recommendations, and prove performance guarantees in terms of their expected regret. For two regimes of model parameters, with structure only in item space or only in user space, we prove information-theoretic lower bounds on regret that match our upper bounds up to logarithmic factors. Our analysis elucidates system operating regimes in which existing CF algorithms are nearly optimal. Copyright © 2017, The Authors. All rights reserved.

关键词： Collaborative filtering

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Toward a feature-cue-based analysis of modification patterns in speech: Alignment of canonical and realized acoustic cue labels

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Proceedings of Meetings on Acoustics 2019年第1期39卷

作者： Christine Soh Tanya Talkar Jeung-Yoon Choi Stefanie Shattuck-Hufnagel 1Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139 USA csoh@mit.edu 2Harvard Medical School: Speech and Hearing Bioscience and Technology Boston MA 02115 USA ttalkar@g.harvard.edu 3MIT: Massachusetts Institute of Technology Cambridge MA 02139 USA jyechoi@mit.edu sshuf@mit.edu

Acoustic cues are properties of the speech signal that provide information about the distinctive features of the speaker’s intended words and phonemes. Analysis of acoustic cues can indicate reductions and modifications in speech, in which landmarks and other feature cues are deleted, inserted, or substituted for others, and can be informative in distinguishing underlying causes of speech impairments. To extract this information about modifications, we need to determine which predicted canonical labels the realized labels correspond to. We propose an algorithm that uses a time-based alignment method for the landmarks as well as a modified labeling scheme to more accurately find correspondences between realized landmarks and the underlying distinctive features. Additionally, we propose a method for expanding the alignment to include other feature cues. The results show improved alignment not only for the realized landmark labels but also for the labels of other feature cues, enabling accurate and holistic analysis of modifications in speech, at the more detailed level of cues to distinctive features rather than the phoneme or phone level.

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Hydrogel‐Enabled Transfer Printing: Hydrogel‐Enabled Transfer‐Printing of Conducting Polymer Films for Soft Organic Bioelectronics (Adv. Funct. Mater. 6/2020)

引用

Advanced Functional Materials 2020年第6期30卷

作者： Shiming Zhang Haonan Ling Yihang Chen Qingyu Cui Jiahua Ni Xiaochen Wang Martin C. Hartel Xiang Meng KangJu Lee Junmin Lee Wujin Sun Haisong Lin Sam Emaminejad Samad Ahadian Nureddin Ashammakhi Mehmet R. Dokmeci Ali Khademhosseini Department of Bioengineering University of California‐Los Angeles Los Angeles CA 90095 USA Center for Minimally Invasive Therapeutics (C‐MIT) University of California‐Los Angeles Los Angeles CA 90095 USA California NanoSystems Institute University of California‐Los Angeles Los Angeles CA 90095 USA Department of Mechanical and Aerospace Engineering University of California‐Los Angeles Los Angeles CA 90095 USA Department of Materials Science and Engineering University of California‐Los Angeles Los Angeles CA 90095 USA Department of Electrical Engineering and Computer Science University of Michigan – Ann Arbor Ann Arbor MI 48109 USA Department of Engineering Physics Polytechnique Montreal Montreal QC H3C 3A7 Canada Department of Electrical and Computer Engineering University of California‐Los Angeles Los Angeles CA USA Department of Radiology University of California‐Los Angeles Los Angeles CA 90095 USA Department of Chemical and Biomolecular Engineering University of California‐Los Angeles Los Angeles CA 90095 USA

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Flexible neural representation for physics prediction

arXiv

引用

arXiv 2018年

作者： Mrowca, Damian Zhuang, Chengxu Wang, Elias Haber, Nick Fei-Fei, Li Tenenbaum, Joshua B. Yamins, Daniel L.K. Department of Computer Science StanfordCA94305 United States Department of Psychology StanfordCA94305 United States Department of Electrical Engineering StanfordCA94305 United States Department of Pediatrics StanfordCA94305 United States Department of Biomedical Data Science StanfordCA94305 Wu Tsai Neurosciences Institute StanfordCA94305 United States Department of Brain and Cognitive Sciences MIT CambridgeMA02139 United States Department of Computer Science and Artificial Intelligence Laboratory MIT CambridgeMA02139 United States

Humans have a remarkable capacity to understand the physical dynamics of objects in their environment, flexibly capturing complex structures and interactions at multiple levels of detail. Inspired by this ability, we propose a hierarchical particle-based object representation that covers a wide variety of types of three-dimensional objects, including both arbitrary rigid geometrical shapes and deformable materials. We then describe the Hierarchical Relation Network (HRN), an end-to-end differentiable neural network based on hierarchical graph convolution, that learns to predict physical dynamics in this representation. Compared to other neural network baselines, the HRN accurately handles complex collisions and nonrigid deformations, generating plausible dynamics predictions at long time scales in novel settings, and scaling to large scene configurations. These results demonstrate an architecture with the potential to form the basis of next-generation physics predictors for use in computer vision, robotics, and quantitative cognitive science. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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DeepFaceLIFT: Interpretable personalized models for automatic estimation of self-reported pain

arXiv

引用

arXiv 2017年

作者： Liu, Dianbo Peng, Fengjiao Shea, Andrew Rudovic, Ognjen Picard, Rosalind Media Lab Mit CambridgeMA United States Computer Science and Artificial Intelligence Laboratory Mit CambridgeMA United States Department of Electrical Engineering and Computer Science Mit CambridgeMA United States

Previous research on automatic pain estimation from facial expressions has focused primarily on "one-size-fits-all" metrics (such as PSPI). In this work, we focus on directly estimating each individual's self-reported visual-analog scale (VAS) pain metric, as this is considered the gold standard for pain measurement. The VAS pain score is highly subjective and context-dependent, and its range can vary significantly among different persons. To tackle these issues, we propose a novel two-stage personalized model, named DeepFaceLIFT, for automatic estimation of VAS. This model is based on (1) Neural Network and (2) Gaussian process regression models, and is used to personalize the estimation of self-reported pain via a set of hand-crafted personal features and multi-task learning. We show on the benchmark dataset for pain analysis (The UNBC-McMaster Shoulder Pain Expression Archive) that the proposed personalized model largely outperforms the traditional, unpersonalized models: the intra-class correlation improves from a baseline performance of 19% to a personalized performance of 35% while also providing confidence in the model's estimates - in contrast to existing models for the target task. Additionally, DeepFaceLIFT automatically discovers the pain-relevant facial regions for each person, allowing for an easy interpretation of the pain-related facial cues. Copyright © 2017, The Authors. All rights reserved.

关键词： Benchmarking

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High-sensitivity spin-based electrometry with an ensemble of nitrogen-vacancy centers in diamond

引用

Physical Review A 2017年第5期95卷 053417-053417页

作者： Edward H. Chen Hannah A. Clevenson Kerry A. Johnson Linh M. Pham Dirk R. Englund Philip R. Hemmer Danielle A. Braje Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02142 USA MIT Lincoln Laboratory Lexington Massachusetts 02420 USA Department of Electrical and Computer Engineering Texas A&M University College Station Texas 77843-3128 USA

We demonstrate a spin-based, all-dielectric electrometer based on an ensemble of nitrogen-vacancy (NV−) defects in diamond. An applied electric field causes energy-level shifts symmetrically away from the NV−'s degenerate triplet states via the Stark effect; this symmetry provides immunity to temperature fluctuations allowing for shot-noise-limited detection. Using an ensemble of NV−s, we demonstrate shot-noise-limited sensitivities approaching 1 (V/cm)/Hz under ambient conditions, at low frequencies (<10 Hz), and over a large dynamic range (20 dB). A theoretical model for the ensemble of NV−s fits well with measurements of the ground-state electric susceptibility parameter 〈k⊥〉. Implications of spin-based, dielectric sensors for micron-scale electric-field sensing are discussed.

关键词： Electro-optical spectra Fine & hyperfine structure Metrology Optical pumping Nitrogen vacancy centers in diamond Solid-state detectors Nuclear spin resonance Optically detected magnetic resonance

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