检索结果-南通市图书馆

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

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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

Robust Machine Learning Mapping of sEMG Signals to Future Actuator Commands in Biomechatronic Devices

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Bionic Engineering 2024年第1期21卷 270-287页

作者： Ali Nasr Sydney Bell Rachel L.Whittaker Clark R.Dickerson John McPhee Systems Design Engineering University of WaterlooWaterloo N2L 3G1Canada Kinesiology and Health Sciences University of WaterlooWaterloo N2L3G3Canada

A machine learning model for regression of interrupted Surface Electromyography(sEMG)signals to future control-oriented signals(e.g.,robot’s joint angle and assistive torque)of an active biomechatronic device for high-level myoelectric-based hierarchical control is proposed.A Recurrent Neural Network(RNN)was trained using output data,initially obtained from offline optimization of the biomechatronic(human–robot)device and shifted by the prediction *** input of the RNN consisted of interrupted sEMG signals(to mimic signal disconnections)and previous kinematic signals of the assistive *** RNN with a 0.1-s prediction horizon could predict the control-oriented joint angle and assistive torque with 92%and 86.5%regression accuracy,respectively,for the test *** proposed approach permits a fast,predictive,and direct estimation of control-oriented signals instead of an iterative process that optimizes assistive torque in the inverse dynamic simulation of a multibody human–robot *** with these interrupted input signals significantly improves the regression accuracy in the case of sEMG signal *** Robust Predictive Control-oriented Machine Learning(Robust-MuscleNET)model can support volitional high-level myoelectric-based control of biomechatronic devices,such as exoskeletons,prostheses,and assistive/resistive *** work should study the application to prosthesis control as well as the repeatability of the high-level controller with electrode *** low-level hierarchical controller that manages the human–robot interaction,the assistance/resistance strategy,and the actuator coordination should also be studied.

关键词： Myoelectric-based control-Surface electromyography Machine learning Multibody system dynamics Exoskeleton Bionic

Nanozyme catalysis in a crowded environment:The impact of diffusion and surface shielding

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nano Research 2024年第7期17卷 5795-5800页

作者： Vasily G.Panferov Juewen Liu Department of Chemistry Waterloo Institute for NanotechnologyWaterlooOntario N2L 3G1Canada

Nanozymes are widely used in various applications as nanosized catalysts for replacing *** accurate estimation of the catalytic activity of nanozymes in real conditions is *** this article,for the first time,we systematically studied the effect of macromolecular molecules co-existing in the real system on the oxidoreductase(peroxidase,oxidase,and catalase)-mimicking nanozymes made of a gold nanoparticle core and a platinum shell,Prussian Blue,Mn_(2)O_(3) and CoO *** were made with horseradish *** distinguished two main mechanisms of the negative impact of macromolecules on nanozyme catalysis—slowed diffusion and surface shielding of *** the first mechanism is typical for enzymes,the second one is specific only for *** the mechanisms is essential for developing approaches to reduce the unavoidable impact of macromolecules for various analytical and biomedical applications.

关键词： molecular crowding biosensors nanoparticles

Thermal noise-driven resonant sensors

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Microsystems & Nanoengineering 2024年第3期10卷 259-271页

作者： Yan Qiao Alaaeldin Elhady Mohamed Arabi Eihab Abdel-Rahman Wenming Zhang School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghaiChina Department of Systems Design Engineering University of WaterlooWaterlooONCanada

MEMS/NEMS resonant sensors hold promise for minute mass and force ***,one major challenge is that conventional externally driven sensors inevitably encounter undesired intrinsic noise,which imposes a fundamental limitation upon their signal-to-noise ratio(SNR)and,consequently,the ***,this restriction becomes increasingly pronounced as sensors shrink to the *** this work,we propose a counterintuitive paradigm shift that turns intrinsic thermal noise from an impediment to a constituent of the sensor by harvesting it as the driving force,obviating the need for external actuation and realizing‘noise-driven’*** sensors employ the dynamically amplified response to thermal noise at resonances for stimulus *** demonstrate that lightly damped and highly compliant nano-structures with high aspect ratios are promising candidates for this class of *** overcome the phase incoherence of the drive force,three noise-enabled quantitative sensing mechanisms are *** validated our sensor paradigm by experimental demonstrating noise-driven pressure and temperature ***-driven sensors offer a new opportunity for delivering practical NEMS sensors that can function at room temperature and under ambient pressure,and a development that suggests a path to cheaper,simpler,and low-power-consumption sensors.

关键词： noise resonant overcome

A novel alcohol dehydrogenase in the hyperthermophilic crenarchaeon Hyperthermus butylicus

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

mLife 2024年第2期3卷 317-325页

作者： Ching Tse Kesen Ma Department of Biology University of WaterlooWaterlooOntarioCanada

Hyperthermus butylicus is a hyperthermophilic crenarchaeon that produces 1-butanol as an end product.A thermostable alcohol dehydrogenase(ADH)must be present in *** to act as the key enzyme responsible for this production;however,the gene that encodes the ADH has not yet been identified.A novel ADH,HbADH2,was purified from a cell-free extract of ***,and its characteristics were *** gene that encodes HbADH2 was demonstrated to be HBUT_RS04850 and annotated as a hypothetical protein in ***2 was found to be a primary-secondary ADH capable of using a wide range of substrates,including butyraldehyde and *** had the highest specificity constant,calculated as k_(cat)/K_(m),with kcat and apparent K_(m) values of 8.00±0.22 s^(-1) and 0.59±0.07 mM,*** apparent Km values for other substrates,including ethanol,1-propanol,2-propanol,butanol,acetaldehyde,propanal,and acetone,were 4.36±0.42,4.69±0.41,3.74±0.46,2.44±0.30,1.27±0.18,1.55±0.20,and 0.68±0.04 mM,*** optimal pH values for catalyzing aldehyde reduction and alcohol oxidation were 6.0 and 9.0,respectively,while the optimal temperature was higher than 90°C due to the increase in enzymatic activity from 60℃ to 90℃.Based on its substrate specificity,enzyme kinetics,and thermostability,HbADH2 may be the ADH that catalyzes the production of 1-butanol in *** putative conserved motif sites for NAD(P)^(+)and iron binding were identified by aligning HbADH2 with previously characterized Fe-containing ADHs.

关键词： butanol hyperthermophile Hyperthermus butylicus novel alcohol dehydrogenase thermostability

Use of subword tokenization for domain generation algorithm classification

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Cybersecurity 2024年第2期7卷 1-12页

作者： Sea Ran Cleon Liew Ngai Fong Law university of waterloo WaterlooCanada Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityKowloonHong Kong

Domain name generation algorithm(DGA)classification is an essential but challenging *** feature-extract-ing machine learning(ML)methods and deep learning(DL)models such as convolutional neural networks and long short-term memory have been ***,the performance of these approaches varies with different types of *** features in the ML methods can characterize random-looking DGAs better than Word-looking *** improve the classification performance on word-looking DGAs,subword tokenization is employed for the DL *** experimental results proved that the subword tokenization can provide excellent classification performance on the word-looking *** then propose an integrated scheme that chooses an appropriate method for DGA classification depending on the nature of the *** show that the integrated scheme outperformed existing ML and DL methods,and also the subword DL methods.

关键词： Botnet detection Domain names Network security Machine learning-based botnet detection

Efficiency improvement by using metal–insulator‑semiconductor structure in InGaN/GaN micro‑light‑emitting diodes

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Optoelectronics 2024年第1期17卷 77-84页

作者： Jian Yin David Hwang Hossein Zamani Siboni Ehsanollah Fathi Reza Chaji Dayan Ban Department of Electrical and Computer Engineering Waterloo Institute NanotechnologyUniversity of WaterlooWaterlooON N2L 3G1Canada Vuereal InC. 440 Philip StreetUnit 100WaterlooON N2L 5R9Canada

InGaN/GaN micro-light-emitting diodes(micro-LEDs)with a metal–insulator-semiconductor(MIS)structure on the sidewall are proposed to improve *** this MIS structure,a sidewall electrode is deposited on the insulating layer-coated sidewall of the device mesa between a cathode on the bottom and an anode on the ***(EL)measurements of fabricated devices with a mesa diameter of 10μm show that the application of negative biases on the sidewall electrode can increase the device external quantum efficiency(EQE).In contrast,the application of positive biases can decrease the *** band structure analysis reveals that the EQE is impacted because the application of sidewall electric fields manipulates the local surface electron density along the mesa sidewall and thus controls surface Shockley–Read–Hall(SRH)*** suggested strategies,reducing insulator layer thickness and exploring alternative materials,can be implemented to further improve the EQE of MIS micro-LEDs in future fabrication.

关键词： Micro-LED GaN EQE improvement Micro-fabrication

SRMD:Sparse Random Mode Decomposition

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Communications on Applied Mathematics and Computation 2024年第2期6卷 879-906页

作者： Nicholas Richardson Hayden Schaeffer Giang Tran university of waterloo WaterlooONCanada university of British Columbia VancouverBCCanada university of California Los AngelesCAUSA

Signal decomposition and multiscale signal analysis provide many useful tools for timefrequency *** proposed a random feature method for analyzing time-series data by constructing a sparse approximation to the *** randomization is both in the time window locations and the frequency sampling,which lowers the overall sampling and computational *** sparsification of the spectrogram leads to a sharp separation between time-frequency clusters which makes it easier to identify intrinsic modes,and thus leads to a new data-driven mode *** applications include signal representation,outlier removal,and mode *** benchmark tests,we show that our approach outperforms other state-of-the-art decomposition methods.

关键词： Sparse random features Signal decomposition Short-time Fourier transform

Machine learning modeling for fuel cell-battery hybrid power system dynamics in a Toyota Mirai 2 vehicle under various drive cycles

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy and AI 2024年第3期17卷 406-418页

作者： Adithya Legala Matthew Kubesh Venkata Rajesh Chundru Graham Conway Xianguo Li Southwest Research Institute San AntonioTXUSA Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooOntarioCanada

Electrification is considered essential for the decarbonization of mobility sector, and understanding and modeling the complex behavior of modern fuel cell-battery electric-electric hybrid power systems is challenging, especially for product development and diagnostics requiring quick turnaround and fast computation. In this study, a novel modeling approach is developed, utilizing supervised machine learning algorithms, to replicate the dynamic characteristics of the fuel cell-battery hybrid power system in a 2021 Toyota Mirai 2nd generation (Mirai 2) vehicle under various drive cycles. The entire data for this study is collected by instrumenting the Mirai vehicle with in-house data acquisition devices and tapping into the Mirai controller area network bus during chassis dynamometer tests. A multi-input - multi-output, feed-forward artificial neural network architecture is designed to predict not only the fuel cell attributes, such as average minimum cell voltage, coolant and cathode air outlet temperatures, but also the battery hybrid system attributes, including lithium-ion battery pack voltage and temperature with the help of 15 system operating parameters. Over 21,0000 data points on various drive cycles having combinations of transient and near steady-state driving conditions are collected, out of which around 15,000 points are used for training the network and 6,000 for the evaluation of the model performance. Various data filtration techniques and neural network calibration processes are explored to condition the data and understand the impact on model performance. The calibrated neural network accurately predicts the hybrid power system dynamics with an R-squared value greater than 0.98, demonstrating the potential of machine learning algorithms for system development and diagnostics.

关键词： Artificial neural network(ANN) Proton exchange membrane fuel cell(PEMFC) Fuel cell electric vehicle(FCEV) Fuel cell-battery electric-electric hybrid power system Data based models Lithium-ion battery(LiB)