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arXiv 2023年

作者： Tang, Jiashen Yin, Zechuan Hart, Connor A. Blanchard, John W. Oon, Jner Tzern Bhalerao, Smriti Schloss, Jennifer M. Turner, Matthew J. Walsworth, Ronald L. Department of Physics University of Maryland College ParkMD20742 United States Quantum Technology Center University of Maryland College ParkMD20742 United States Department of Electrical Engineering and Computer Science University of Maryland College ParkMD20742 United States Fischell Department of Bioengineering University of Maryland College ParkMD20742 United States Lincoln Laboratory Massachusetts Institute of Technology LexingtonMA02421 United States

Wide-field imaging of magnetic signals using ensembles of nitrogen-vacancy (NV) centers in diamond has garnered increasing interest due to its combination of micron-scale resolution, millimeter-scale field of view, and compatibility with diverse samples from across the physical and life sciences. Recently, wide-field NV magnetic imaging based on the Ramsey protocol has achieved uniform and enhanced sensitivity compared to conventional measurements. Here, we integrate the Ramsey-based protocol with spin-bath driving to extend the NV spin dephasing time and improve magnetic sensitivity. We also employ a high-speed camera to enable dynamic wide-field magnetic imaging. We benchmark the utility of this quantum diamond microscope (QDM) by imaging magnetic fields produced from a fabricated wire phantom. Over a 270 × 270 µm2 field of view, a median per-pixel magnetic sensitivity of 4.1(1) nT/√Hz is realized with a spatial resolution . 10 µm and sub-millisecond temporal resolution. Importantly, the spatial magnetic noise floor can be reduced to the picotesla scale by time-averaging and signal modulation, which enables imaging of a magnetic-field pattern with a peak-to-peak amplitude difference of about 300 pT. Finally, we discuss potential new applications of this dynamic QDM in studying biomineralization and electrically-active cells. © 2023, CC BY.

关键词： Magnetic fields

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SmileyLlama: Modifying Large Language Models for Directed Chemical Space Exploration

arXiv

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arXiv 2024年

作者： Cavanagh, Joseph M. Sun, Kunyang Gritsevskiy, Andrew Bagni, Dorian Bannister, Thomas D. Head-Gordon, Teresa Kenneth S. Pitzer Theory Center Department of Chemistry University of California BerkeleyCA94720 United States Department of Computer Science University of Wisconsin–Madison MadisonWI53706 United States Department of Molecular Medicine The Herbert Wertheim UF Scripps Institute for Biomedical Innovation and Technology 130 Scripps Way JupiterFL33458 United States Departments of Bioengineering and Chemical and Biomolecular Engineering University of California BerkeleyCA94720 United States Chemical Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Here we show that a Large Language Model (LLM) can serve as a foundation model for a Chemical Language Model (CLM) which performs at or above the level of CLMs trained solely on chemical SMILES string data. Using supervised fine-tuning (SFT) and direct preference optimization (DPO) on the open-source Llama LLM, we demonstrate that we can train an LLM to respond to prompts such as generating molecules with properties of interest to drug development. This overall framework allows an LLM to not just be a chatbot client for chemistry and materials tasks, but can be adapted to speak more directly as a CLM which can generate molecules with user-specified properties. © 2024, CC BY.

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A spatiotemporal multi-scale computational model for FDG PET imaging at different stages of tumor growth and angiogenesis

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SCIENTIFIC REPORTS 2022年第1期12卷 1-16页

作者： Kashkooli, Farshad Moradi Abazari, Mohammad Amin Soltani, M. Ghazani, Mehran Akbarpour Rahmim, Arman Department of Mechanical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering School of Optometry and Vision Science Faculty of Science University of Waterloo Waterloo Canada Advanced Bioengineering Initiative Center Multidisciplinary International Complex K. N. Toosi University of Technology Tehran Iran Centre for Biotechnology and Bioengineering (CBB) University of Waterloo Waterloo ON Canada Faculty of Mechanical Engineering University of Tabriz Tabriz Iran Department of Integrative Oncology BC Cancer Research Institute Vancouver BC Canada Department of Physics and Astronomy University of British Columbia Vancouver BC Canada Department of Radiology University of British Columbia Vancouver BC Canada

A deeper understanding of the tumor microenvironment (TME) and its role in metabolic activity at different stages of vascularized tumors can provide useful insights into cancer progression and better support clinical assessments. In this study, a robust and comprehensive multi-scale computational model for spatiotemporal transport of F-18 fluorodeoxyglucose (FDG) is developed to incorporate important aspects of the TME, spanning subcellular-, cellular-, and tissue-level scales. Our mathematical model includes biophysiological details, such as radiopharmaceutical transport within interstitial space via convection and diffusion mechanisms, radiopharmaceutical exchange between intracellular and extracellular matrices by glucose transporters, cellular uptake of radiopharmaceutical, as well as its intracellular phosphorylation by the enzyme. Further, to examine the effects of tumor size by varying microvascular densities (MVDs) on FDG dynamics, four different capillary networks are generated by angiogenesis modeling. Results demonstrate that as tumor grows, its MVD increases, and hence, the spatiotemporal distribution of total FDG uptake by tumor tissue changes towards a more homogenous distribution. In addition, spatiotemporal distributions in tumor with lower MVD have relatively smaller magnitudes, due to the lower diffusion rate of FDG as well as lower local intravenous FDG release. Since mean standardized uptake value (SUVmean) differs at various stages of microvascular networks with different tumor sizes, it may be meaningful to normalize the measured values by tumor size and the MVD prior to routine clinical reporting. Overall, the present framework has the potential for more accurate investigation of biological phenomena within TME towards personalized medicine.

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Polarimetric infrared spectroscopic imaging using quantum cascade lasers

Polarimetric infrared spectroscopic imaging using quantum ca...

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Advanced Chemical Microscopy for Life science and Translational Medicine 2020

作者： Phal, Yamuna Yeh, Kevin Bhargava, Rohit Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL United States Departments of Bioengineering Chemical and Biomolecular Engineering Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL United States Cancer Center at Illinois University of Illinois at Urbana-Champaign UrbanaIL United States 4265 Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 N. Mathews Avenue UrbanaIL61801 United States

ISBN: (纸本)9781510632677

Infrared spectroscopic imaging has emerged as a powerful label-free diagnostic tool to study the molecular composition and organization in biological tissues and cells. We report infrared spectroscopic imaging using polarized light to study differential absorption of plane-polarized light by an oriented sample to detect valuable information, such as, birefringence and dichroism. For instance, the organization of collagen, specifically fiber orientation and alignment, is crucial in understanding the progression and metastasis of cancer. Recent advancements in the development of Quantum Cascade Lasers (QCL) sources have opened new avenues for high SNR measurements in the field of IR spectroscopy. In addition, QCL sources are intrinsically polarized and orientation information can be obtained at discrete frequencies with different polarization orientations, allowing much faster acquisition than a corresponding FT-IR approach. We demonstrate improved performance in terms of fast and comprehensive polarimetric image acquisition and analysis using custom-built QCL microscope and evaluate its impact on applications by analyzing the important spectral bands of surgical tissue sections. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Collagen

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AI-Derived Left Ventricular Mass From Noncontrast Cardiac CT: Correlation With Contrast CT Angiography and CMR

JACC: Advances

引用

JACC: Advances 2024年第10期3卷 101249-101249页

作者： Han, Donghee Shanbhag, Aakash Miller, Robert JH. Kwok, Nicholas Waechter, Parker Builoff, Valerie Newby, David E. Dey, Damini Berman, Daniel S. Slomka, Piotr Departments of Medicine (Division of Artificial Intelligence in Medicine) Imaging and Biomedical Sciences Cedars-Sinai Medical Center Los Angeles CA United States Signal and Image Processing Institute Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA United States Department of Cardiac Sciences University of Calgary Calgary AB Canada British Heart Foundation Centre for Cardiovascular Science University of Edinburgh Edinburgh United Kingdom

Background: Noncontrast computed tomography (CT) scans are not used for evaluating left ventricle myocardial mass (LV mass), which is typically evaluated with contrast CT or cardiovascular magnetic resonance imaging (CMR). Objectives: The purpose of the study was to assess the feasibility of LV mass estimation from standard, ECG-gated, noncontrast CT using an artificial intelligence (AI) approach and compare it with coronary CT angiography (CTA) and CMR. Methods: We enrolled consecutive patients who underwent coronary CTA, which included noncontrast CT calcium scanning and contrast CTA, and CMR. The median interval between coronary CTA and CMR was 22 days (interquartile range: 3-76). We utilized a no new UNet AI model that automatically segmented noncontrast CT structures. AI measurement of LV mass was compared to contrast CTA and CMR. Results: A total of 316 patients (age: 57.1 ± 16.7 years, 56% male) were included. The AI segmentation took on average 22 seconds per case. An excellent correlation was observed between AI and contrast CTA LV mass measures (r = 0.84, P < 0.001), with no significant differences (136.5 ± 55.3 g vs 139.6 ± 56.9 g, P = 0.133). Bland-Altman analysis showed minimal bias of 2.9. When compared to CMR, measured LV mass was higher with AI (136.5 ± 55.3 g vs 127.1 ± 53.1 g, P < 0.001). There was an excellent correlation between AI and CMR (r = 0.85, P < 0.001), with a small bias (−9.4). There were no statistical differences between the correlations of LV mass between contrast CTA and CMR or AI and CMR. Conclusions: The AI-based automated estimation of LV mass from noncontrast CT demonstrated excellent correlations and minimal biases when compared to contrast CTA and CMR. © 2024 The Authors

关键词： artificial intelligence cardiac magnetic resonance imaging computed tomography myocardial mass

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Mathematical Modeling of 18F-Fluoromisonidazole (18F-FMISO) Radiopharmaceutical Transport in Vascularized Solid Tumors

arXiv

引用

arXiv 2024年

作者： Abazari, Mohammad Amin Soltani, M. Eydi, Faezeh Rahmim, Arman Kashkooli, Farshad Moradi Department of Mechanical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering School of Optometry and Vision Science Faculty of Science University of Waterloo WaterlooN2L 3G Canada Department of Integrative Oncology BC Cancer Research Institute VancouverBCV5Z 1L3 Canada University of Waterloo WaterlooONN2L 3G Canada Cancer Biology Research Center Cancer Institute of Iran Tehran University of Medical Sciences Tehran Iran Departments of Radiology and Physics University of British Columbia VancouverBC Canada

18F-Fluoromisonidazole (18F-FMISO) is a highly promising positron emission tomography radiopharmaceutical for identifying hypoxic regions in solid tumors. This research employs spatiotemporal multi-scale mathematical modeling to explore how different levels of angiogenesis influence the transport of radiopharmaceuticals within tumors. In this study, two tumor geometries with heterogeneous and uniform distributions of capillary networks were employed to incorporate varying degrees of microvascular density. The synthetic image of the heterogeneous and vascularized tumor was generated by simulating the angiogenesis process. The proposed multi-scale spatiotemporal model accounts for intricate physiological and biochemical factors within the tumor microenvironment, such as the transvascular transport of the radiopharmaceutical agent, its movement into the interstitial space by diffusion and convection mechanisms, and ultimately its uptake by tumor cells. Results showed that both quantitative and semi-quantitative metrics of 18F-FMISO uptake differ spatially and temporally at different stages during tumor growth. The presence of a high microvascular density in uniformly vascularized tumor increases cellular uptake, as it allows for more efficient release and rapid distribution of radiopharmaceutical molecules. This results in enhanced uptake compared to the heterogeneous vascularized tumor. In both heterogeneous and uniform distribution of microvessels in tumors, the diffusion transport mechanism has a more pronounced than convection. The findings of this study shed light on the transport phenomena behind 18F-FMISO radiopharmaceutical distribution and its delivery in the tumor microenvironment, aiding oncologists in their routine decision-making processes. © 2024, CC BY.

关键词： Tumors

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Asymmetric aging effect on modern microprocessors

arXiv

引用

arXiv 2020年

作者： Gabbay, Freddy Mendelson, Avi Electrical Engineering Department Ruppin Academic Center Israel Computer Science and Electrical Engineering Departments Technion – Israel Institute of Technology Haifa3200000 Israel

Reliability, a crucial requirement in any modern microprocessor, assures correct execution over its lifetime. As mission critical components are becoming common in commodity systems, e.g., control of autonomous cars, the demand for reliable processing continues to grow. The latest process technologies have aggravated the situation by causing microprocessors to be highly vulnerable to reliability concerns. This paper examines the asymmetric aging phenomenon, which is a major reliability concern in advanced process nodes. In this phenomenon, logical elements and memory cells suffer from unequal timing degradation over lifetime and, consequently, introduce reliability concerns. Thus far, most studies approached asymmetric aging from a circuit or physical design viewpoint, but these solutions were quite limited and suboptimal. In this paper, we introduce an asymmetric aging-aware microarchitecture that aims to reduce the phenomenon’s impact. The study is mainly focused on the following subsystems: execution units, register files and memory hierarchy. Our experiments indicate that the proposed solutions incur minimal overhead while significantly mitigating asymmetric aging stress. Copyright © 2020, The Authors. All rights reserved.

关键词： Reliability

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Efficient product formulas for commutators and applications to quantum simulation

引用

Physical Review Research 2022年第1期4卷 013191-013191页

作者： Yu-An Chen Andrew M. Childs Mohammad Hafezi Zhang Jiang Hwanmun Kim Yijia Xu Google Quantum AI 340 Main Street Venice California 90291 USA Department of Physics and Joint Quantum Institute NIST/University of Maryland College Park Maryland 20742 USA Condensed Matter Theory Center University of Maryland College Park Maryland 20472 USA Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Department of Computer Science University of Maryland College Park Maryland 20742 USA Institute for Advanced Computer Studies University of Maryland College Park Maryland 20742 USA Departments of Electrical and Computer Engineering and Institute for Research in Electronics and Applied Physics University of Maryland College Park Maryland 20742 USA Institute for Physical Science and Technology University of Maryland College Park Maryland 20742 USA

We construct product formulas for exponentials of commutators and explore their applications. First, we directly construct a third-order product formula with six exponentials by solving polynomial equations obtained using the operator differential method. We then derive higher-order product formulas recursively from the third-order formula. We improve over previous recursive constructions, reducing the number of gates required to achieve the same accuracy. In addition, we demonstrate that the constituent linear terms in the commutator can be included at no extra cost. As an application, we show how to use the product formulas in a digital protocol for counterdiabatic driving, which increases the fidelity for quantum state preparation. We also discuss applications to quantum simulation of one-dimensional fermion chains with nearest- and next-nearest-neighbor hopping terms, and two-dimensional fractional quantum Hall phases.

关键词： Fractional quantum Hall effect Quantum algorithms Quantum computation Quantum control Quantum simulation Abstract algebra

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Valley-polarized Exitonic Mott Insulator in WS2/WSe2 Moiré Superlattice

arXiv

引用

arXiv 2023年

作者： Lian, Zhen Meng, Yuze Ma, Lei Maity, Indrajit Yan, Li Wu, Qiran Huang, Xiong Chen, Dongxue Chen, Xiaotong Chen, Xinyue Blei, Mark Taniguchi, Takashi Watanabe, Kenji Tongay, Sefaattin Lischner, Johannes Cui, Yong-Tao Shi, Su-Fei Department of Chemical and Biological Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Departments of Materials The Thomas Young Centre for Theory and Simulation of Materials Imperial College London United Kingdom Department of Physics and Astronomy University of California RiversideCA92521 United States Department of Materials Science and Engineering University of California RiversideCA92521 United States Materials Science and Engineering Program School for Engineering of Matter Transport and Energy Arizona State University TempeAZ85287 United States International Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Research Center for Functional Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Department of Electrical Computer & Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

Strongly enhanced electron-electron interaction in semiconducting moiré superlattices formed by transition metal dichalcogenides (TMDCs) heterobilayers has led to a plethora of intriguing fermionic correlated states1–7. Meanwhile, interlayer excitons in a type-II aligned TMDC heterobilayer moiré superlattice, with electrons and holes separated in different layers8,9, inherit this enhanced interaction and strongly interact with each other, promising for realizing tunable correlated bosonic quasiparticles10,11 with valley degree of freedom. We employ photoluminescence spectroscopy to investigate the strong repulsion between interlayer excitons and correlated electrons in a WS2/WSe2 moiré superlattice and combine with theoretical calculations to reveal the spatial extent of interlayer excitons and the band hierarchy of correlated states. We further find that an excitonic Mott insulator state emerges when one interlayer exciton occupies one moiré cell, evidenced by emerging photoluminescence peaks under increased optical excitation power. Double occupancy of excitons in one unit cell requires overcoming the energy cost of exciton-exciton repulsion of about 30-40 meV, depending on the stacking configuration of the WS2/WSe2 heterobilayer. Further, the valley polarization of the excitonic Mott insulator state is enhanced by nearly one order of magnitude. Our study demonstrates the WS2/WSe2 moiré superlattice as a promising platform for engineering and exploring new correlated states of fermion, bosons, and a mixture of both12 © 2023, CC BY.

关键词： Excitons

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Virtual Histological Staining of Label-Free Autopsy Tissue Sections via Deep Learning

Virtual Histological Staining of Label-Free Autopsy Tissue S...

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Yuzhu Li Nir Pillar Jingxi Li Tairan Liu Di Wu Songyu Sun Guangdong Ma Kevin De Haan Luzhe Huang Yijie Zhang Sepehr Hamidi Anatoly Urisman Tal Keidar Haran William Dean Wallace Jonathan E. Zuckerman Aydogan Ozcan Electrical and Computer Engineering Department Bioengineering Department California NanoSystems Institute (CNSI) Computer Science Department University of California Los Angeles CA USA School of physics Xi'an Jiaotong University Xi'an Shaanxi China Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles CA USA Department of Pathology University of California San Francisco CA USA Department of Pathology Hadassah Hebrew University Medical Center Jerusalem Israel Department of Pathology Keck School of Medicine University of Southern California Los Angeles CA USA Department of Surgery University of California Los Angeles CA USA

We present deep learning-based virtual staining of label-free autopsy tissue sections, eliminating severe autolysis-induced artifacts caused by delayed fixation inherent in traditional histochemical H&E staining.

ISBN: (纸本)9798350369311

关键词： Deep learning Autopsy Lasers and electrooptics Electro-optical waveguides

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