scholarly journals Modeling Brownian Microparticle Trajectories in Lab-on-a-Chip Devices with Time Varying Dielectrophoretic or Optical Forces

Micromachines ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1265
Author(s):  
Mohammad Asif Zaman ◽  
Mo Wu ◽  
Punnag Padhy ◽  
Michael A. Jensen ◽  
Lambertus Hesselink ◽  
...  
Keyword(s):  
Lab On A Chip ◽  
Time Varying ◽  
Optical Forces ◽  
Wide Range ◽  
Hindered Diffusion ◽  
Applied Forces ◽  
Numerical Solver ◽  
Physics Model ◽  
Particle Sample ◽  
Number Of Particles

Lab-on-a-chip (LOC) devices capable of manipulating micro/nano-sized samples have spurred advances in biotechnology and chemistry. Designing and analyzing new and more advanced LOCs require accurate modeling and simulation of sample/particle dynamics inside such devices. In this work, we present a generalized computational physics model to simulate particle/sample trajectories under the influence of dielectrophoretic or optical forces inside LOC devices. The model takes into account time varying applied forces, Brownian motion, fluid flow, collision mechanics, and hindered diffusion caused by hydrodynamic interactions. We develop a numerical solver incorporating the aforementioned physics and use it to simulate two example cases: first, an optical trapping experiment, and second, a dielectrophoretic cell sorter device. In both cases, the numerical results are found to be consistent with experimental observations, thus proving the generality of the model. The numerical solver can simulate time evolution of the positions and velocities of an arbitrarily large number of particles simultaneously. This allows us to characterize and optimize a wide range of LOCs. The developed numerical solver is made freely available through a GitHub repository so that researchers can use it to develop and simulate new designs.

Understanding Distressed Residential Transaction Discounts Across Price Segments and Market Conditions

2020 ◽  
Vol 42 (1) ◽  
pp. 151-182
Author(s):  
Ramya Rajajagadeesan Aroul ◽  
J. Andrew Hansz ◽  
Mauricio Rodriguez
Keyword(s):  
Transaction Costs ◽  
Time Varying ◽  
Market Segment ◽  
Market Conditions ◽  
Large Market ◽  
Space And Time ◽  
Wide Range ◽  
Time Periods ◽  
Market Areas

In the literature, there is a wide range of discounts associated with foreclosures. Comparisons across studies are difficult as they use different methodologies across large areas over different time periods. We employ a consistent methodology across space and time. We find modest discounts, within the range of typical transaction costs, in all but the highest priced market segment. Higher priced segments could explain prior findings of substantial discounts. We find that discounts are time-varying, with discounts increasing with market distress. A one-size-fits-all approach is not appropriate when estimating distressed transaction discounts across large market areas or under changing market conditions.

Manipulation of Clinical Materials Using AC Electrokinetics

2010 ◽  
Author(s):  
Mandy L. Y. Sin ◽  
Pak Kin Wong
Keyword(s):  
Experimental Data ◽  
Sample Preparation ◽  
Theoretical Prediction ◽  
Fluid Motion ◽  
Lab On A Chip ◽  
Clinical Samples ◽  
Electrochemical Reactions ◽  
Ac Electrokinetics ◽  
Wide Range ◽  
Electrothermal Flow

AC electrokinetics is a promising approach for sample preparation and reaction enhancement in lab-on-a-chip devices. However, relative little has been done on the electrokinetic manipulation of physiological fluids and buffers with similar properties, such as conductivity. Herein, electrokinetic manipulation of fluids with a wide range of conductivities has been studied as a function of voltage and frequency. AC electrothermal flow is determined to dominate the fluid motion when the applied frequency of the AC potential is above 100 kHz. Interestingly, experimental data deviate from theoretical prediction for fluids with high conductivities (> 1 Sm−1). The deviation can be understood by voltage modulated electrochemical reactions and should be accounted for when manipulating clinical materials with high conductivities. The study will provide useful in sights in designing lab-on-a-chip devices for manipulating clinical samples in the future.

scholarly journals Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7467
Author(s):  
Shih-Lin Lin
Keyword(s):  
Feature Extraction ◽  
Deep Learning ◽  
Fault Diagnosis ◽  
Vibration Signal ◽  
Image Feature ◽  
Signal Acquisition ◽  
Time Varying ◽  
Intelligent Fault Diagnosis ◽  
Image Block ◽  
Wide Range

Rolling bearings are important in rotating machinery and equipment. This research proposes variational mode decomposition (VMD)-DenseNet to diagnose faults in bearings. The research feature involves analyzing the Hilbert spectrum through VMD whereby the vibration signal is converted into an image. Healthy and various faults show different characteristics on the image, thus there is no need to select features. Coupled with the lightweight network, DenseNet, for image classification and prediction. DenseNet is used to build a model of motor fault diagnosis; its structure is simple, and the calculation speed is fast. The method of using DenseNet for image feature learning can perform feature extraction on each image block of the image, providing full play to the advantages of deep learning to obtain accurate results. This research method is verified by the data of the time-varying bearing experimental device at the University of Ottawa. Through the four links of signal acquisition, feature extraction, fault identification, and prediction, a mechanical intelligent fault diagnosis system has established the state of bearing. The experimental results show that the method can accurately identify four common motor faults, with a VMD-DenseNet prediction accuracy rate of 92%. It provides a more effective method for bearing fault diagnosis and has a wide range of application prospects in fault diagnosis engineering. In the future, online and timely diagnosis can be achieved for intelligent fault diagnosis.

scholarly journals Preparation and properties of plasmonic-excitonic nanoparticle assemblies

Nanophotonics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 517-547 ◽  
Author(s):  
Brian Szychowski ◽  
Matthew Pelton ◽  
Marie-Christine Daniel
Keyword(s):  
Good Control ◽  
Inorganic Nanoparticles ◽  
Rabi Splitting ◽  
Strongly Coupled ◽  
Nanoparticle Assemblies ◽  
Wide Range ◽  
Fano Interference ◽  
Potential Applications ◽  
The Individual ◽  
Number Of Particles

AbstractThe assembly of inorganic nanoparticles often leads to collective properties that are different from the combined properties of the individual components. In particular, coupling plasmonic and excitonic nanoparticles has been shown to modify their optical properties, including absorption, emission, and scattering. Because of this, these coupled assemblies have potential applications in a wide range of areas, including sensing, light harvesting, and photocatalysis. More recently, unique properties, including Fano interference and Rabi splitting, have been observed by increasing the coupling strength. However, the behavior of coupled nanoparticles is highly dependent on the exact organization of the components, including the number of particles coupled, the distance separating them, and their spatial orientation. This is especially true in the case of strongly coupled particles. Because of this, it is important to achieve synthetic techniques that not only can link particles together but also offer good control over how the particles are connected. In this review, assemblies of plasmonic and excitonic nanoparticles are reviewed, including the various methods that have been used for their construction, the properties that these systems have been predicted to possess as well as the ones that have been observed, and their current applications along with current challenges in the field and potential future applications.

scholarly journals Improvement of a nonnegative preserved efficient solver for atmospheric chemical kinetic equations

2018 ◽  
Vol 7 (3) ◽  
pp. 6657
Author(s):  
Atika RADID ◽  
Karim RHOFIR
Keyword(s):  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Atmospheric Chemistry ◽  
Iteration Process ◽  
Iterative Solution ◽  
Chemical Kinetic ◽  
Time Step ◽  
Backward Euler ◽  
Wide Range ◽  
Numerical Solver

Generally, chemical reactions from atmospheric chemistry models are described by a strongly coupled, stiff and nonlinear system of ordinary differential equations, which requires a good numerical solver. Several articles published about the solvers of chemical equations, during the numerical simulation, indicate that one renders the concentration null when it becomes negative. In order to preserve the positivity of the exact solutions, recent works have proposed a new solver called Modified-Backward-Euler (MBE). To improve this solver, we propose in this paper an iterative numerical scheme witch is better fitted to stiff problems. This new approach, called Iterative-Modified-Backward-Euler (IMBE), is based on iterative solution of the P-L structure of the implicit nonlinear ordinary differential equations on each time step. The efficiency of the iteration process is increased by using the Gauss and Successive-Over-Relaxation (SOR). In the case of fast/slow chemical kinetic reactions, we proposed an other variant called Iterative-Quasi-Steady-State-Approximation (IQSSA). The numerical exploration of stiff test problem shows clearly that this formalism is applicable to a wide range of chemical kinetics problems and give a good approximation compared to the recent solver. The numerical procedures give reasonable accurate solutions when compared to exact solution.Generally, chemical reactions from atmospheric chemistry models are described by a strongly coupled, stiff and nonlinear system of ordinary differential equations, which requires a good numerical solver. Several articles published about the solvers of chemical equations, during the numerical simulation, indicate that one renders the concentration null when it becomes negative. In order to preserve the positivity of the exact solutions, recent works have proposed a new solver called Modified-Backward-Euler (MBE). To improve this solver, we propose in this paper an iterative numerical scheme witch is better fitted to stiff problems. This new approach, called Iterative-Modified-Backward-Euler (IMBE), is based on iterative solution of the P-L structure of the implicit nonlinear ordinary differential equations on each time step. The efficiency of the iteration process is increased by using the Gauss and Successive-Over-Relaxation (SOR). In the case of fast/slow chemical kinetic reactions, we proposed an other variant called Iterative-Quasi-Steady-State-Approximation (IQSSA). The numerical exploration of stiff test problem shows clearly that this formalism is applicable to a wide range of chemical kinetics problems and give a good approximation compared to the recent solver. The numerical procedures give reasonable accurate solutions when compared to exact solution.

scholarly journals Contagion Processes on Time-Varying Networks with Homophily-Driven Group Interactions

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Li Ding ◽  
Ping Hu
Keyword(s):  
Simplicial Complex ◽  
Connectivity Pattern ◽  
Time Varying ◽  
Interaction Patterns ◽  
Epidemic Threshold ◽  
Group Interactions ◽  
Wide Range ◽  
The Impact ◽  
Many Body Interactions ◽  
Contagion Process

The complicated interaction patterns among heterogeneous individuals have a profound impact on the contagion process in the networks. In recent years, there has been increasing evidence for the emergence of many-body interactions between two or more nodes in a wide range of biological and social networks. To encode these multinode interactions explicitly, the simplicial complex is now a popular alternative to simple networks. Meanwhile, the time-varying network has been acknowledged as a key ingredient of the contagion process. In this paper, we consider the connectivity pattern of networks affected by the homophily effect associated with individual attributes and investigate the impact of homophily-driven group interactions on the contagion process in temporal networks. The simplicial complex modeling framework is adopted to capture stochastic interactions between passively selected nodes in the paradigm of activity-driven networks. We study the evolution of infection and the epidemic threshold of the contagion process by both analytical and numerical methods. Our results on statistical topological properties of instantaneous network may shed light on accurately characterizing the evolution curve of infection. Furthermore, we show the impact of the homophily-driven interaction pattern on the epidemic threshold, which generalizes the existing results on both the paradigmatic activity-driven network and the simplicial activity-driven network.

Debye Parameters of Humidity-Varying Soils for Induction Logging Techniques

2020 ◽  
Vol 35 (9) ◽  
pp. 979-984
Author(s):  
Andres Velasco ◽  
Atef Elsherbeni ◽  
Joseph Diener ◽  
Mohammed Hadi
Keyword(s):  
Differential Equation ◽  
Dispersion Analysis ◽  
Wide Range ◽  
Induction Logging ◽  
Numerical Solver ◽  
Different Soils

This paper focuses on the tabulation of calculated Debye coefficients for a wide range of soils for source waves ranging from 300 MHz to 2 GHz. Debye coefficients of different soils will produce accurate FDTD dispersive simulations for wireline logging purposes. The FDTD dispersion analysis is based on an Auxiliary Differential Equation (ADE) method which depends on the Debye coefficients. A complex set of soil data is acquired and used in a twostep numerical solver to calculate the Debye coefficients. For a wide range of soils, Debye coefficients were developed for one, two, and three pole expansions. Most fits for one pole fits were highly inaccurate, so the coefficients generated were disregarded. Coefficients for two and three term expansions were accurate and were generated and tabulated here.

Optimal Asset Allocation with Asymptotic Criteria

2003 ◽  
Vol 06 (06) ◽  
pp. 593-604 ◽  
Author(s):  
Slava Karguine
Keyword(s):  
Asset Allocation ◽  
Asset Returns ◽  
Linear Functions ◽  
Time Varying ◽  
Fast Computation ◽  
Joint Moments ◽  
Numerical Example ◽  
Conditional Expectations ◽  
Wide Range ◽  
Investment Criterion

With the assumptions that asset returns follow a stochastic multi-factor process with time-varying conditional expectations and investments are linear functions of factors, we calculate asymptotic joint moments of the logarithm of investor's wealth and the factors. These formulas enable fast computation of a wide range of investment criteria. The results are illustrated by a numerical example that shows that the optimal portfolio rules are sensitive to the specification of the investment criterion.

Time Varying Meshing Stiffness of Cracked Sun and Ring Gears of Planetary Gear Train

2015 ◽  
Vol 772 ◽  
pp. 164-168
Author(s):  
Arif Abdullah Muhammad ◽  
Guang Lei Liu
Keyword(s):  
Gear Tooth ◽  
Planetary Gear ◽  
Mesh Point ◽  
Gear Train ◽  
Time Varying ◽  
Planetary Gear Train ◽  
Meshing Stiffness ◽  
Face Width ◽  
The Face ◽  
Applied Forces

The time varying meshing stiffness of normal and cracked spur gears of planetary gear train is studied by applying the unit normal forces at mesh point on the face width along the line of action of the single gear tooth in FE based software Ansys Workbench 14.5. The tooth deflections due to the applied forces at one mesh point are noted and a deflection matrix is established which is solved using Matlab to get net deflection and finally the meshing stiffness of gear tooth at particular mesh point. The process is repeated for other mesh points of gear tooth by rotating it to get meshing stiffness for whole gear tooth.

Dynamic Model of a Sac-Type Pneumatically Driven Artificial Ventricle

1977 ◽  
Vol 99 (1) ◽  
pp. 14-19 ◽  
Author(s):  
D. B. Geselowitz ◽  
G. E. Miller ◽  
W. M. Phillips
Keyword(s):  
Dynamic Model ◽  
Circulatory System ◽  
Operating Conditions ◽  
Time Varying ◽  
Outlet Port ◽  
Mock Circulatory System ◽  
Linear Resistance ◽  
Wide Range ◽  
Artificial Ventricle ◽  
Nonlinear Resistance

Inlet and outlet pressures and flows were obtained over a wide range of operating conditions for a pneumatically driven sac-type artificial ventricle connected to a mechanical mock circulatory system. The load presented to the ventricle by the mock circulatory system was found to be characterized by a linear resistance and capacitance. A dynamic model for the ventricle which accounted for instantaneous pressures and flows was developed. The outlet port is characterized by an inertance and square law resistance; the inlet port is characterized by a nonlinear resistance dependent on the type of valve. The input to the model is the time varying sac pressure. The model predicts the fill-limited and ejection-limited modes of the artificial ventricle.

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