检索结果-内蒙古大学图书馆

Component library creation and pixel array generation with micromilled droplet microfluidics

Microsystems & Nanoengineering 2025年第1期11卷 277-287页

作者： David McIntyre Diana Arguijo Kaede Kawata Douglas Densmore Biomedical Engineering Department Boston UniversityBostonMAUSA Biological Design Center Boston UniversityBostonMAUSA Electrical and Computer Engineering Department Boston UniversityBostonMAUSA

Droplet microfluidics enable high-throughput screening,sequencing,and formulation of biological and chemical systems at the *** devices are generally fabricated in a soft polymer such as polydimethylsiloxane(PDMS).However,developing design masks for PDMS devices can be a slow and expensive process,requiring an internal cleanroom facility or using an external ***,we present the first complete droplet-based component library using low-cost rapid prototyping and electrode *** fabrication method for droplet microfluidic devices costs less than$12 per device and a full design-build-test cycle can be completed within a *** microfluidic components for droplet generation,re-injection,picoinjection,anchoring,fluorescence sensing,and sorting were built and *** devices are biocompatible,low-cost,and *** show its ability to perform multistep workflows,these components were used to assemble droplet"pixel"arrays,where droplets were generated,sensed,sorted,and anchored onto a grid to produce images.

关键词： droplet microfluidics micromilled rapid prototyping electrode integrationthis soft polymer biocompatible component library pixel array

来源：评论

学校读者我要写书评

暂无评论

Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications

引用

National Science Review 2024年第2期11卷 231-263页

作者： Kyung Rok Pyun Kangkyu Kwon Myung Jin Yoo Kyun Kyu Kim Dohyeon Gong Woon-Hong Yeo Seungyong Han Seung Hwan Ko Department of Mechanical Engineering Seoul National University IEN Center for Human-Centric Interfaces and Engineering Institute for Electronics and NanotechnologyGeorgia Institute of Technology School of Electrical and Computer Engineering Georgia Institute of Technology Department of Chemical Engineering Stanford University Department of Mechanical Engineering Ajou University George W.Woodruff School of Mechanical Engineering Georgia Institute of Technology Institute of Advanced Machinery and Design(SNU-IAMD) Seoul National University

Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology. Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets, thereby presenting a breakthrough in utilizing wearable sensors for practical applications. Beyond traditional machine-learning techniques for classifying simple gestures, advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets. Machine-learning techniques have improved the ability to perceive, and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition, providing real-time feedback to users. This forms a crucial component of future wearable electronics, contributing to a robust human–machine interface. In this review, we provide a comprehensive summary covering materials, structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.

关键词： wearable sensor soft electronics artificial intelligence machine learning human–machine interfaces gesture recognition

来源：评论

学校读者我要写书评

暂无评论

Drawing Order Diagrams Through Two-Dimension Extension

引用

Journal of Graph Algorithms and Applications 2023年第9期27卷 783-802页

作者： Dürrschnabel, Dominik Hanika, Tom Stumme, Gerd Knowledge & Data Engineering Group Research Center for Information System Design & Department of Electrical Engineering and Computer Science University of Kassel Germany Institute of Computer Science University of Hildesheim Germany Berlin School of Library and Information Science Humboldt-Universität zu Berlin Germany

Ordinal real-world data such as concept hierarchies, ontologies, genealogies, or task dependencies in scheduling often has the property to not only contain pairwise comparable, but also incomparable elements. Order diagrams provide an important tool for understanding and thus discovering knowledge in such data. Easily readable drawings of such order diagrams are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work, we present the novel algorithm DimDraw to decompose an ordered set (e.g., a concept hierarchy) in linear orders and to produce a corresponding order diagram. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of its transitive incompatibility graph. To evaluate the quality of the algorithm, a user study was conducted where generated drawings were compared with ones from state-of-the-art drawing algorithms. © 2023 Brown University. All rights reserved.

关键词： Set theory

来源：评论

学校读者我要写书评

暂无评论

Experimental measurement and numerical modeling of deformation behavior of breast cancer cells passing through constricted microfluidic channels

引用

Microsystems & Nanoengineering 2024年第1期10卷 129-147页

作者： Pouyan Keshavarz Motamed Hesam Abouali Mahla Poudineh Nima Maftoon Department of Systems Design Engineering University of WaterlooWaterlooON N2L 3G1Canada Center for Bioengineering and Biotechnology University of WaterlooWaterlooON N2L 3G1Canada Department of Electrical and Computer Engineering University of WaterlooWaterlooON N2L 3G1Canada

During the multistep process of metastasis,cancer cells encounter various mechanical forces which make them deform *** accurate in-silico models,capable of simulating the interactions between the mechanical forces and highly deformable cancer cells,can pave the way for the development of novel diagnostic and predictive methods for metastatic ***-network models of cancer cell,empowered by our recently proposed identification approach,promises a versatile numerical tool for developing experimentally validated models that can simulate complex interactions at cellular *** this numerical tool,we presented spring-network models of breast cancer cells that can accurately replicate the experimental data of deformation behavior of the cells flowing in a fluidic domain and passing narrow constrictions comparable to ***,using high-speed imaging,we experimentally studied the deformability of breast cancer cell lines with varying metastatic potential(MCF-7(less invasive),SKBR-3(medium-high invasive),and MDA-MB-231(highly invasive)in terms of their entry time to a constricted microfluidic *** observed that MDA-MB-231,that has the highest metastatic potential,is the most deformable cell among the ***,by focusing on this cell line,experimental measurements were expanded to two more constricted microchannel *** experimental deformability data in three constricted microchannel sizes for various cell sizes,enabled accurate identification of the unknown parameters of the spring-network model of the breast cancer cell line(MDA-MB-231).Our results show that the identifed parameters depend on the cell size,suggesting the need for a systematic procedure for identifying the size-dependent parameters of spring-network models of *** the numerical results show,the presented cell models can simulate the entry process of the cell into constricted channels with very good agreements with the measured experimen

关键词： strict passing numerical

来源：评论

学校读者我要写书评

暂无评论

Hardware,Software,and Wetware Codesign Environment for Synthetic Biology

引用

Biodesign Research 2022年第1期2022卷 136-150页

作者： Samuel M.D.Oliveira Douglas Densmore Department of Electrical and Computer Engineering Boston UniversityMA 02215USA Biological Design Center Boston UniversityMA 02215USA

Synthetic biology is the process of forward engineering living *** systems can be used to produce biobased materials,agriculture,medicine,and *** approach to designing these systems is to employ techniques from the design of embedded *** techniques include abstraction,standards,modularity,automated design,and formal semantic models of ***,these elements form the foundation of“biodesign automation,”where software,robotics,and microfluidic devices combine to create exciting biological systems of the *** paper describes a“hardware,software,wetware”codesign vision where software tools can be made to act as“genetic compilers”that transform high-level specifications into engineered“genetic circuits”(wetware).This is followed by a process where automation equipment,welldefined experimental workflows,and microfluidic devices are explicitly designed to house,execute,and test these circuits(hardware).These systems can be used as either massively parallel experimental platforms or distributed bioremediation and biosensing ***,scheduling and control algorithms(software)manage these systems’actual execution and data analysis tasks.A distinguishing feature of this approach is how all three of these aspects(hardware,software,and wetware)may be derived from the same basic specification in parallel and generated to fulfill specific cost,performance,and structural requirements.

关键词： hardware Together execution

来源：评论

学校读者我要写书评

暂无评论

Surface-dominated conductance scaling in Weyl semimetal NbAs

引用

npj Computational Materials 2024年第1期10卷 2370-2378页

作者： Sushant Kumar Yi-Hsin Tu Sheng Luo Nicholas A.Lanzillo Tay-Rong Chang Gengchiau Liang Ravishankar Sundararaman Hsin Lin Ching-Tzu Chen Department of Materials Science&Engineering Rensselaer Polytechnic Institute1108th StTroyNY 12180USA IBM Thomas J.Watson Research Center 1101 Kitchawan RoadYorktown HeightsNY 10598USA Department of Physics Cheng Kung UniversityTainan CityTaipei Department of Electrical and Computer Engineering College of Design and EngineeringNational University of SingaporeSingaporeSingapore IBM Research 257 Fuller RoadAlbanyNY 12203USA Institute of Physics Academia SinicaTaipeiTaipei

Protected surface states arising fromnon-trivial bandstructure topology in semimetals can potentially enable advanced device functionalities in compute,memory,interconnect,sensing,and *** necessitates a fundamental understanding of surface-state transport in nanoscale topological ***,we investigate quantum transport in a prototypical topological semimetal NbAs to evaluate the potential of this class of materials for beyond-Cu interconnects in highly-scaled integrated *** density functional theory(DFT)coupled with non-equilibrium Green’s function(NEGF)calculations,we show that the resistance-areaRAproduct in NbAs films decreases with decreasing thickness at the nanometer scale,in contrast to a nearly constant RA product in ideal Cu *** anomalous scaling originates from the disproportionately large number of surface conduction states which dominate the ballistic conductance by up to 70%in NbAs thin *** also show that this favorable RA scaling persists even in the presence of surface defects,in contrast to RA sharply increasing with reducing thickness for films of conventional metals,such as Cu,in the presence of surface *** results underscore the potential of topological semimetals as future back-end-of-line(BEOL)interconnect metals.

关键词： scaling topological conductance

来源：评论

学校读者我要写书评

暂无评论

Hyperspectral Tensor Completion Using Low-Rank Modeling and Convex Functional Analysis

引用

IEEE Transactions on Neural Networks and Learning Systems 2024年第8期35卷 10736-10750页

作者： Lin, Chia-Hsiang Liu, Yangrui Chi, Chong-Yung Hsu, Chih-Chung Ren, Hsuan Quek, Tony Q. S. National Cheng Kung University Department of Electrical Engineering Tainan70101 Taiwan National Tsing Hua University Department of Electrical Engineering Hsinchu300044 Taiwan National Cheng Kung University Department of Statistics Tainan70101 Taiwan National Central University Center for Space and Remote Sensing Research Taoyuan320317 Taiwan Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore487372 Singapore National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan

Hyperspectral tensor completion (HTC) for remote sensing, critical for advancing space exploration and other satellite imaging technologies, has drawn considerable attention from recent machine learning community. Hyperspectral image (HSI) contains a wide range of narrowly spaced spectral bands hence forming unique electrical magnetic signatures for distinct materials, and thus plays an irreplaceable role in remote material identification. Nevertheless, remotely acquired HSIs are of low data purity and quite often incompletely observed or corrupted during transmission. Therefore, completing the 3-D hyperspectral tensor, involving two spatial dimensions and one spectral dimension, is a crucial signal processing task for facilitating the subsequent applications. Benchmark HTC methods rely on either supervised learning or nonconvex optimization. As reported in recent machine learning literature, John ellipsoid (JE) in functional analysis is a fundamental topology for effective hyperspectral analysis. We therefore attempt to adopt this key topology in this work, but this induces a dilemma that the computation of JE requires the complete information of the entire HSI tensor that is, however, unavailable under the HTC problem setting. We resolve the dilemma, decouple HTC into convex subproblems ensuring computational efficiency, and show state-of-the-art HTC performances of our algorithm. We also demonstrate that our method has improved the subsequent land cover classification accuracy on the recovered hyperspectral tensor. © 2012 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Real-time deep learning-assisted mechano-acoustic system for respiratory diagnosis and multifunctional classification

引用

npj Flexible Electronics 2024年第1期8卷 192-203页

作者： Hee Kyu Lee Sang Uk Park Sunga Kong Heyin Ryu Hyun Bin Kim SangHoon Lee Danbee Kang Sun Hye Shin Ki Jun Yu Juhee Cho Joohoon Kang Il Yong Chun Hye Yun Park Sang Min Won Department of Electrical and Computer Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Department of Clinical Research Design and Evaluation SAIHSTSungkyunkwan UniversitySeoulRepublic of Korea Patient-Centered Outcomes Research Institute Samsung Medical CenterSeoulRepublic of Korea Center for Clinical Epidemiology Samsung Medical CenterSeoulRepublic of Korea Division of Pulmonary and Critical Care Medicine Department of MedicineSamsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea School of Electrical and Electronic Engineering Yonsei UniversitySeoulRepublic of Korea School of Advanced Materials Science and Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Center for Neuroscience Imaging Research Institute for Basic ScienceSuwonRepublic of Korea

Epidermally mounted sensors using triaxial accelerometers have been previously used to monitor physiological processes with the implementation of machine learning(ML)algorithm *** findings from these previous studies have established a strong foundation for the analysis of highresolution,intricate signals,typically through frequency domain *** this study we integrate a wireless mechano-acoustic sensor with a multi-modal deep learning system for the real-time analysis of signals emitted by the laryngeal prominence area of the thyroid cartilage at frequency ranges up to 1 *** interface provides real-time data visualization and communication with the ML server,creating a system that assesses severity of chronic obstructive pulmonary disease and analyzes the user’s speech patterns.

关键词： system diagnosis mounted

来源：评论

学校读者我要写书评

暂无评论

Towards Atomic Defect-Aware Physical design of Silicon Dangling Bond Logic on the H -Si (100)-2× 1 Surface

Towards Atomic Defect-Aware Physical Design of Silicon Dangl...

引用

2024 design, Automation and Test in Europe Conference and Exhibition, DATE 2024

作者： Walter, Marcel Croshaw, Jeremiah Hang Ng, Samuel Sze Walus, Konrad Wolkow, Robert Wille, Robert Technical University Of Munich Design Automation Germany University Of Alberta Department Of Physics Edmonton Canada Quantum Silicon Inc. Edmonton Canada University Of British Columbia Department Of Electrical And Computer Engineering Vancouver Canada Software Competence Center Hagenberg GmbH Austria

ISBN: (纸本)9798350348590

Recent advancements in Silicon Dangling Bond (SiDB) fabrication have transitioned from manual to automated processes. However, sub-nanometer substrate defects remain a significant challenge, thus preventing the fabrication of functional logic. Current design automation techniques lack defect-aware strategies. This paper introduces an idea for a surface defect model based on experimentally verified defects, which can be applied to enhance the robustness of established gate libraries. Additionally, a prototypical automatic placement and routing algorithm is presented, utilizing STM data from physical experiments to obtain dot- accurate circuitry resilient to atomic surface defects. Initial evaluations on surfaces with varying defect rates demonstrate their critical impact, suggesting that fabrication processes must achieve defect rates of around 0.1 % to further advance this circuit technology. © 2024 EDAA.

关键词： Surface defects

来源：评论

学校读者我要写书评

暂无评论

Assessment of Serum Creatinine and Serum Sodium Prognostic Potential in Heart Failure Patients Using Machine Learning 46

Assessment of Serum Creatinine and Serum Sodium Prognostic P...

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Alyounis, Sona Khandoker, Ahsan Stefanini, Cesare Hadjileontiadis, Leontios Scuola Superiore Sant'Anna Creative Engineering Design Lab The BioRobotics Institute Pontedera Italy Khalifa University of Science and Technology Healthcare Engineering Innovation Center Department of Biomedical Engineering P.O. Box 127788 Abu Dhabi United Arab Emirates Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki Greece

ISBN: (纸本)9798350371499

Heart failure (HF) is the leading etiology for hospital admissions and ranks among the foremost contributors to mortality. This complex clinical syndrome with various phenotypes is categorized by left ventricle ejection fraction levels (LVEF), namely preserved (HFpEF), mid-range (HFmEF), and reduced (HFrEF). This study investigates the prognostic impact of serum creatinine and serum sodium levels in HF patients across these three classes using machine learning tools. A comprehensive dataset of HF patients' medical records including serum sodium and serum creatinine was utilized. Machine learning regression models were employed to predict the LVEF levels. Additionally, classification models were implemented to categorize patients into HFpEF, HFmEF, and HFrEF classes. Regression analyses revealed the predictive capabilities of serum sodium and serum creatinine in estimating the progression of HF severity. Furthermore, classification models successfully differentiated between the three EF classes, providing valuable insights into the classification patterns of HF patients based on these biomarkers. The results demonstrated the significance of serum sodium serum creatinine as prognostic markers in HF, and this contributes to a more nuanced approach to HF management, paving the way for targeted interventions and improved patient outcomes. Moreover, this study highlights the potential of machine learning techniques to enhance risk stratification and classification in HF patients, enabling personalized prognostication and treatment strategies. © 2024 IEEE.

关键词： Creatinine

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：