检索结果-内蒙古大学图书馆

CLEO: science and Innovations, S and I 2022

作者： Bai, Bijie Wang, Hongda Li, Yuzhu de Haan, Kevin Colonnese, Francesco Wan, Yujie Zuo, Jingyi Doan, Ngan B. Zhang, Xiaoran Zhang, Yijie Li, Jingxi Dong, Wenjie Darrow, Morgan Angus Kamangar, Elham Lee, Han Sung Rivenson, Yair Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Computer Science Department University of California Los AngelesCA90095 United States Physics and Astronomy Department University of California Los AngelesCA90095 United States Translational Pathology Core Laboratory University of California Los AngelesCA90095 United States Statistics Department University of California Los AngelesCA90095 United States Department of Pathology and Laboratory Medicine University of California at Davis SacramentoCA95817 United States Department of Surgery University of California Los AngelesCA90095 United States

We present deep learning-based virtual immunohistochemical (IHC) HER2 staining of label-free breast tissue sections, matching the standard IHC HER2 staining performed by histotechnologists. © Optica Publishing Gr... 详细信息

ISBN: (纸本)9781557528209

关键词： Tissue

来源：评论

学校读者我要写书评

暂无评论

3D-Printed electrochemical sensor-integrated transwell systems

引用

Microsystems & Nanoengineering 2020年第1期6卷 357-368页

作者： Pradeep Ramiah Rajasekaran Ashley Augustiny Chapin David N.Quan Jens Herberholz William E.Bentley Reza Ghodssi Institute for Systems Research University of MarylandCollege ParkMDUSA Fischell Department of Bioengineering University of MarylandCollege ParkMDUSA Department of Psychology and Neuroscience and Cognitive Science Program University of MarylandCollege ParkMDUSA Institute for Bioscience and Biotechnology Research University of MarylandCollege ParkMDUSA Robert E.Fischell Institute for Biomedical Devices University of MarylandCollege ParkMDUSA Department of Electrical and Computer Engineering University of MarylandCollege ParkMDUSA

This work presents a 3D-printed,modular,electrochemical sensor-integrated transwell system for monitoring cellular and molecular events in situ without sample extraction or microfluidics-assisted downstream *** additive manufacturing techniques such as 3D printing,shadow masking,and molding are used to fabricate this modular system,which is autoclavable,biocompatible,and designed to operate following standard operating protocols(SOPs)of cellular *** to the platform is a flexible porous membrane,which is used as a cell culture substrate similarly to a commercial transwell *** electrochemical sensors fabricated on the membrane allow direct access to cells and their products.A pair of gold electrodes on the top side of the membrane measures impedance over the course of cell attachment and growth,characterized by an exponential decrease(~160%at 10Hz)due to an increase in the double layer capacitance from secreted extracellular matrix(ECM)*** voltammetry(CV)sensor electrodes,fabricated on the bottom side of the membrane,enable sensing of molecular release at the site of cell culture without the need for downstream ***-time detection of ferrocene dimethanol injection across the membrane showed a three order-of-magnitude higher signal at the membrane than in the bulk media after reaching *** modular sensor-integrated transwell system allows unprecedented direct,real-time,and noninvasive access to physical and biochemical information,which cannot be obtained in a conventional transwell system.

关键词： transwell electrochemical culture

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Analyses of Brain MRI to Identify Sustained Attention Deficit in Treated Obstructive Sleep Apnea: A Pilot Study

引用

Sleep and Vigilance 2022年第1期6卷 179-184页

作者： Agarwal, Chirag Gupta, Saransh Najjar, Muhammad Weaver, Terri E. Zhou, Xiaohong Joe Schonfeld, Dan Prasad, Bharati Department of Medicine University of Illinois Chicago 840 S. Wood Street MC 719 Chicago 60612 IL United States Jesse Brown VA Medical Center Chicago IL United States Department of Biomedical Informatics Harvard Medical School Boston MA United States Biobehavioral Nursing Science College of Nursing University of Illinois Chicago Chicago IL United States Center for Magnetic Resonance Research University of Illinois Chicago Chicago IL United States Departments of Radiology Neurosurgery and Bioengineering University of Illinois Chicago Chicago IL United States Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL United States

Purpose: Persistent sustained attention deficit (SAD) after continuous positive airway pressure (CPAP) treatment is a source of quality of life and occupational impairment in obstructive sleep apnea (OSA). However, persistent SAD is difficult to predict in patients initiated on CPAP treatment. We performed secondary analyses of brain magnetic resonance (MR) images in treated OSA participants, using deep learning, to predict SAD. Methods: 26 middle-aged men with CPAP use of more than 6 h daily and MR imaging were included. SAD was defined by psychomotor vigilance task lapses of more than 2. 17 participants had SAD and 9 were without SAD. A Convolutional Neural Network (CNN) model was used for classifying the MR images into + SAD and − SAD categories. Results: The CNN model achieved an accuracy of 97.02 ± 0.80% in classifying MR images into + SAD and − SAD categories. Assuming a threshold of 90% probability for the MR image being correctly classified, the model provided a participant-level accuracy of 99.11 ± 0.55% and a stable image level accuracy of 97.45 ± 0.63%. Conclusion: Deep learning methods, such as the proposed CNN model, can accurately predict persistent SAD based on MR images. Further replication of these findings will allow early initiation of adjunctive pharmacologic treatment in high-risk patients, along with CPAP, to improve quality of life and occupational fitness. Future augmentation of this approach with explainable artificial intelligence methods may elucidate the neuroanatomical areas underlying persistent SAD to provide mechanistic insights and novel therapeutic targets. © 2021, This is a U.S. government work and not under copyright protection in the U.S.;foreign copyright protection may apply.

关键词： Alertness Daytime sleepiness MRI OSA Sleep apnea

来源：评论

学校读者我要写书评

暂无评论

Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet in Fields up to 25 T

Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet i...

引用

JSAP-OSA Joint Symposia, JSAP 2021

作者： Bao, J. Peraca, N. Marquez Tay, F. Kritzell, T.E. Li, X. Noe, G.T. Katayama, I. Takeda, J. Nojiri, H. Yamahara, H. Tabata, H. Baydin, A. Kono, J. Department of Physics and Astronomy Rice University HoustonTX United States Department of Electrical and Computer Engineering Rice University HoustonTX United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX United States Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama Japan Institute for Materials Research Tohoku University Sendai Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering University of Tokyo Japan Smalley-Curl Institute Rice University HoustonTX United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States

来源：评论

学校读者我要写书评

暂无评论

Cycle Consistency-based Uncertainty Quantification of Neural Networks in Inverse Imaging Problems

arXiv

引用

arXiv 2023年

作者： Huang, Luzhe Li, Jianing Ding, Xiaofu Zhang, Yijie Chen, Hanlong Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Computer Science Department University of California Los AngelesCA90095 United States Department of Mathematics University of California Los AngelesCA90095 United States David Geffen School of Medicine University of California Los Angeles Los AngelesCA90095 United States

Uncertainty estimation is critical for numerous applications of deep neural networks and draws growing attention from researchers. Here, we demonstrate an uncertainty quantification approach for deep neural networks used in inverse problems based on cycle consistency. We build forward-backward cycles using the physical forward model available and a trained deep neural network solving the inverse problem at hand, and accordingly derive uncertainty estimators through regression analysis on the consistency of these forward-backward cycles. We theoretically analyze cycle consistency metrics and derive their relationship with respect to uncertainty, bias, and robustness of the neural network inference. To demonstrate the effectiveness of these cycle consistency-based uncertainty estimators, we classified corrupted and out-of-distribution input image data using some of the widely used image deblurring and super-resolution neural networks as testbeds. The blind testing of our method outperformed other models in identifying unseen input data corruption and distribution shifts. This work provides a simple-to-implement and rapid uncertainty quantification method that can be universally applied to various neural networks used for solving inverse problems. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Structural tuning magnetism and topology in a magnetic topological insulator

arXiv

引用

arXiv 2023年

作者： Eckberg, Christopher Qiu, Gang Qu, Tao Kwon, Sohee Liu, Yuhang Tai, Lixuan Graf, David Chong, Su Kong Zhang, Peng Wong, Kin L. Lake, Roger K. Neupane, Mahesh R. Wang, Kang L. Fibertek Inc. HerndonVA20171 United States DEVCOM Army Research Laboratory AdelphiMD20783 United States DEVCOM Army Research Laboratory Playa Vista CA90094 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California RiversideCA92521 United States National High Magnetic Field Laboratory Florida State University TallahasseeFL32310 United States Materials Science and Engineering Program University of California RiversideCA92521 United States

To date, the most widely-studied quantum anomalous Hall insulator (QAHI) platform is achieved by dilute doping of magnetic ions into thin films of the alloyed tetradymite topological insulator (TI) (Bi1−xSbx)2Te3 (BST) [1–4]. In these films, long-range magnetic ordering of the transition metal substituants opens an exchange gap ∆ in the topological surface states, stabilizing spin-polarized, dissipationless edge channels with a nonzero Chern number C. The long-range ordering of the spatially separated magnetic ions is itself mediated by electronic states in the host TI, leading to a sophisticated feedback between magnetic and electronic properties. Here we present a study of the electronic and magnetic response of a BST-based QAHI system to structural tuning via hydrostatic pressure. We identify a systematic closure of the topological gap under compressive strain accompanied by a simultaneous enhancement in the magnetic ordering strength. Combining these experimental results with first-principle calculations we identify structural deformation as a strong tuning parameter to traverse a rich topological phase space and modify magnetism in the magnetically doped BST system. © 2023, CC BY-NC-ND.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Electrostatic Energy Harvesting from Human Interactions with Smart Paper Electronics*

Electrostatic Energy Harvesting from Human Interactions with...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Alyssa Y. Zhou Michel M. Maharbiz Department of Electrical Engineering and Computer Science University of California Berkeley CA USA Department of Electrical Engineering and Computer Science and the Department of Bioengineering University of California Berkeley CA USA

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Smart devices are quickly becoming ubiquitous with the rise of portable biosensors and the internet of things. There exists particular interest in enhancing common objects to have smart capabilities and finding inexpensive solutions for diagnostic tools. One such example is transforming paper items into interactive devices and point-of-care analytic products. Due to the lightweight, flexible, and cost-efficient qualities of paper, unobtrusively powering these devices remains an outstanding problem. In this paper, we demonstrate an electrostatic human-touch powered energy harvesting system, integrated with flexible painted conductive electrodes on paper. This system harvests 8.5 nJ of energy and reaches a voltage of 1.3 V on a 10 nF energy storage capacitor. This technology not only provides a method of powering paper-based products with routine human gestures but can also detect human touch for input communication to sensors.

关键词： Electrodes Energy harvesting Capacitance Capacitors Fingers Ink Photovoltaic cells

来源：评论

学校读者我要写书评

暂无评论

StyleKQC: A Style-Variant Paraphrase Corpus for Korean Questions and Commands

arXiv

引用

arXiv 2021年

作者： Cho, Won Ik Moon, Sangwhan Kim, Jong In Kim, Seok Min Kim, Nam Soo Department of Electrical and Computer Engineering INMC Seoul National University Korea Republic of Department of Computer Science Tokyo Institute of Technology Japan Google LLC Interdisciplinary Program in Cognitive Science Seoul National University Korea Republic of

Paraphrasing is often performed with less concern for controlled style conversion. Especially for questions and commands, style-variant paraphrasing can be crucial in tone and manner, which also matters with industrial applications such as dialog systems. In this paper, we attack this issue with a corpus construction scheme that simultaneously considers the core content and style of directives, namely intent and formality, for the Korean language. Utilizing manually generated natural language queries on six daily topics, we expand the corpus to formal and informal sentences by human rewriting and transferring. We verify the validity and industrial applicability of our approach by checking the adequate classification and inference performance that fit with conventional fine-tuning approaches, at the same time proposing a supervised formality transfer task. © 2021, CC BY-SA.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Opto-thermoelectric pulling of light-absorbing particles

引用

Light(science & Applications) 2020年第1期9卷 1686-1696页

作者： Linhan Lin Pavana Siddhartha Kollipara Abhay Kotnala Taizhi Jiang Yaoran Liu Xiaolei Peng Brian A.Korgel Yuebing Zheng 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 State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijing 100084People’s Republic of China McKetta Department of Chemical Engineering The University of Texas at AustinAustinTX 78712USA Department of Electrical and Computer Engineering The University of Texas at AustinAustinTX 78712USA

Optomechanics arises from the photon momentum and its exchange with low-dimensional *** is well known that optical radiation exerts pressure on objects,pushing them along the light ***,optical pulling of an object against the light path is still a counter-intuitive ***,we present a general concept of optical pulling-opto-thermoelectric pulling(OTEP)—where the optical heating of a light-absorbing particle using a simple plane wave can pull the particle itself against the light *** irradiation orientation-directed pulling force imparts self-restoring behaviour to the particles,and three-dimensional(3D)trapping of single particles is achieved at an extremely low optical intensity of 10^(−2)mWμm^(−2).Moreover,the OTEP force can overcome the short trapping range of conventional optical tweezers and optically drive the particle flow up to a macroscopic *** concept of selfinduced opto-thermomechanical coupling is paving the way towards freeform optofluidic technology and lab-on-achip devices.

关键词： absorbing light trapping

来源：评论

学校读者我要写书评

暂无评论

cytoNet: Spatiotemporal network analysis of cell communities (vol 18, e1009846, 2022)

引用

PLOS COMPUTATIONAL BIOLOGY 2022年第11期18卷 e1009846页

作者： Mahadevan, A. S. Long, B. L. Hu, C. W. Ryan, D. T. Grandel, N. E. Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania United States of America Department of Bioengineering Rice University Houston Texas United States of America Department of Biomedical Engineering University of Texas at San Antonio San Antonio Texas United States of America Department of Computer Science University of Texas at San Antonio San Antonio Texas United States of America Systems Synthetic and Physical Biology Program Rice University Houston Texas United States of America Biophysics Graduate Program University of California Berkeley California United States of America Department of Oral & Maxillofacial Surgery University of Texas Health Science Center at San Antonio San Antonio Texas United States of America Department of Electrical and Computer Engineering Rice University Houston Texas United States of America Department of Biosciences Rice University Houston Texas United States of America UTSA–UT Health Joint Graduate Group in Biomedical Engineering San Antonio Texas United States of America Programs in Integrated Biomedical Sciences Translational Sciences Radiological Sciences University of Texas Health Science Center at San Antonio San Antonio Texas United States of America UTSA AI MATRIX Consortium San Antonio Texas United States of America

We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet’s capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo , 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin α4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.

关键词： Calcium imaging Fluorescence imaging Growth factors Centrality Cell cycle and cell division Endothelial cells Network analysis Stem cells

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：