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2D vs 3D tracking in bacterial motility analysis

  • Digital holographic microscopy provides the ability to observe throughout a large volume without refocusing. This capability enables simultaneous observations of large numbers of microorganisms swimming in an essentially unconstrained fashion. However, computational tools for tracking large 4D datasets remain lacking. In this paper, we examine the errors introduced by tracking bacterial motion as 2D projections vs. 3D volumes under different circumstances: bacteria free in liquid media and bacteria near a glass surface. We find that while XYZ speeds are generally equal to or larger than XY speeds, they are still within empirical uncertainties. Additionally, when studying dynamic surface behavior, the Z coordinate cannot be neglected.

    Citation: Jacqueline Acres, Jay Nadeau. 2D vs 3D tracking in bacterial motility analysis[J]. AIMS Biophysics, 2021, 8(4): 385-399. doi: 10.3934/biophy.2021030

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  • Digital holographic microscopy provides the ability to observe throughout a large volume without refocusing. This capability enables simultaneous observations of large numbers of microorganisms swimming in an essentially unconstrained fashion. However, computational tools for tracking large 4D datasets remain lacking. In this paper, we examine the errors introduced by tracking bacterial motion as 2D projections vs. 3D volumes under different circumstances: bacteria free in liquid media and bacteria near a glass surface. We find that while XYZ speeds are generally equal to or larger than XY speeds, they are still within empirical uncertainties. Additionally, when studying dynamic surface behavior, the Z coordinate cannot be neglected.



    Hydraulic jumps are frequently observed in lab studies, river flows, and coastal environments. The shallow water equations, commonly known as Saint-Venant equations, have important applications in oceanography and hydraulics. These equations are used to represent fluid flow when the depth of the fluid is minor in comparison to the horizontal scale of the flow field fluctuations [1]. They have been used to simulate flow at the atmospheric and ocean scales, and they have been used to forecast tsunamis, storm surges, and flow around constructions, among other things [2,3]. Shallow water is a thin layer of constant density fluid in hydrostatic equilibrium that is bordered on the bottom by a rigid surface and on the top by a free surface [4].

    Nonlinear waves have recently acquired importance due to their capacity to highlight several complicated phenomena in nonlinear research with spirited applications [5,6,7,8]. Teshukov in [9] developed the equation system that describes multi-dimensional shear shallow water (SSW) flows. Some novel solitary wave solutions for the ill-posed Boussinesq dynamic wave model under shallow water beneath gravity were constructed [10]. The effects of vertical shear, which are disregarded in the traditional shallow water model, are included in this system to approximate shallow water flows. It is a non-linear hyperbolic partial differential equations (PDE) system with non-conservative products. Shocks, rarefactions, shear, and contact waves are all allowed in this model. The SSW model can capture the oscillatory character of turbulent hydraulic leaps, which corrects the conventional non-linear shallow water equations' inability to represent such occurrences [11]. Analytical and numerical techniques for solving such problems have recently advanced; for details, see [12,13,14,15,16,17] and the references therein.

    The SSW model consists of six non-conservative hyperbolic equations, which makes its numerical solution challenging since the concept of a weak solution necessitates selecting a path that is often unknown. The physical regularization mechanism determines the suitable path, and even if one knows the correct path, it is challenging to construct a numerical scheme that converges to the weak solution since the solution is susceptible to numerical viscosity [18].

    In the present work, we constructed the generalized Rusanov (G. Rusanov) scheme to solve the SSW model in 1D of space. This technique is divided into steps for predictors and correctors [19,20,21,22,23]. The first one includes a numerical diffusion control parameter. In the second stage, the balance conservation equation is retrieved. Riemann solutions were employed to determine the numerical flow in the majority of the typical schemes. Unlike previous schemes, the interesting feature of the G. Rusanov scheme is that it can evaluate the numerical flow even when the Riemann solution is not present, which is a very fascinating advantage. In actuality, this approach may be applied as a box solver for a variety of non-conservative law models.

    The remainder of the article is structured as follows. Section 2 offers the non-conservative shear shallow water model. Section 3 presents the structure of the G. Rusanov scheme to solve the 1D SSW model. Section 4 shows that the G. Rusanov satisfies the C-property. Section 5 provides several test cases to show the validation of the G. Rusanov scheme versus Rusanov, Lax-Friedrichs, and reference solutions. Section 6 summarizes the work and offers some conclusions.

    The one-dimensional SSW model without a source term is

    Wt+F(W)x+K(W)hx=S(W), (2.1)
    W=(hhv1hv2E11E12E22),F(W)=(hv1R11+hv21+gh22R12+hv1v2(E11+R11)v1E12v1+12(R11v2+R12v1)E22v1+R12v2),
    K(W)=(000ghv112ghv20),S(W)=(0ghBxCf|v|v1Cf|v|v2ghv1Bx+12D11Cf|v|v2112ghv2Bx+12D12Cf|v|v1v212D22Cf|v|v22),

    while R11 and R12 are defined by the following tensor Rij=hpij, and also, E11, E12 and E22 are defined by the following tensor Eij=12Rij+12hvivj with i1,j2. We write the previous system 2.1 in nonconservative form with non-dissipative (Cf=0,D11=D12=D22=0), see [24], which can be written as follows

    Wt+(F(W)+C(W))Wx=S1(W). (2.2)

    Also, we can write the previous system as the following

    Wt+A(W)Wx=S1(W) (2.3)

    with

    A(W)=[010000gh002000000203E11v1h+2v31+ghv23E11h3v2103v1002E12v1hE11v2h+2v21v2+ghv222E12h2v1v2E11hv21v22v10E22v1h2E12v2h+v22v1E22h+v222E12h2v2v102v2v1]

    and

    S1(W)=(0ghBx0ghv1Bx12ghv2Bx0).

    System (2.3) is a hyperbolic system and has the following eigenvalues

    λ1=λ2=v1,λ3=v12E11hv21,λ4=v1+2E11hv21,
    λ5=v1gh+3(v212E11h),λ6=v1+gh+3(v212E11h).

    In order deduce the G. Rusanov scheme, we rewrite the system (2.1) as follows

    Wt+F(W)x=K(W)hx+S1(W)=Q(W). (3.1)

    Integrating Eq (3.1) over the domain [tn,tn+1]×[xi12,xi+12] gives the finite-volume scheme

    Wn+1i=WniΔtΔx(F(Wni+1/2)F(Wni1/2))+ΔtQin (3.2)

    in the interval [xi1/2,xi+1/2] at time tn. Wni represents the average value of the solution W as follows

    Wni=1Δxxi+1/2xi1/2W(tn,x)dx,

    and F(Wni±1/2) represent the numerical flux at time tn and space x=xi±1/2. It is necessary to solve the Riemann problem at xi+1/2 interfaces due to the organization of the numerical fluxes. Assume that for the first scenario given below, there is a self-similar Riemann problem solution associated with Eq (3.1)

    W(x,0)={WL,ifx<0,WR,ifx>0 (3.3)

    is supplied by

    W(t,x)=Rs(xt,WL,WR). (3.4)

    The difficulties with discretization of the source term in (3.2) could arise from singular values of the Riemann solution at the interfaces. In order to overcome these challenges and reconstruct a Wni+1/2 approximation, we created a finite-volume scheme in [19,20,21,22,23,25,26,27] for numerical solutions of conservation laws including source terms and without source terms. The principal objective here is building the intermediate states Wni±1/2 to be utilized in the corrector stage (3.2). The following is obtained by integrating Eq (3.1) through a control volume [tn,tn+θni+1/2]×[x,x+], that includes the point (tn,xi+1/2), with the objective to accomplish this:

    x+xW(tn+θni+1/2,x)dx=ΔxWni+Δx+Wni+1θni+1/2(F(Wni+1)F(Wni))+θni+1/2(ΔxΔx+)Qni+12 (3.5)

    with Wni±1/2 denoting the approximation of Riemann solution Rs across the control volume [x,x+] at time tn+θni+1/2. While calculating distances Δx and Δx+ as

    Δx=|xxi+1/2|,Δx+=|x+xi+1/2|,

    Qni+12 closely resembles the average source term Q and is given by the following

    Qni+12=1θni+12(Δx+Δx+)tn+θni+12tnx+xQ(W)dtdx. (3.6)

    Selecting x=xi, x+=xi+1 causes the Eq (3.5) to be reduced to the intermediate state, which given as follows

    Wni+1/2=12(Wni+Wni+1)θni+1/2Δx(F(Wni+1)F(Wni))+θni+12Qni+12, (3.7)

    where the approximate average value of the solution W in the control domain [tn,tn+θni+1/2]×[xi,xi+1] is expressed by Wni+1/2 as the following

    Wni+1/2=1Δxxi+1xiW(x,tn+θni+1/2)dx (3.8)

    by selecting θni+1/2 as follows

    θni+1/2=αni+1/2ˉθi+1/2,ˉθi+1/2=Δx2Sni+1/2. (3.9)

    This choice is contingent upon the results of the stability analysis[19]. The following represents the local Rusanov velocity

    Sni+1/2=maxk=1,...,K(max(λnk,i,λnk,i+1)), (3.10)

    where αni+1/2 is a positive parameter, and λnk,i represents the kth eigenvalues in (2.3) evaluated at the solution state Wni. Here, in our case, k=6 for the shear shallow water model. One can use the Lax-Wendroff technique again for αni+1/2=ΔtΔxSni+1/2. Choosing the slope αni+1/2=˜αni+1/2, the proposed scheme became a first-order scheme, where

    ˜αni+1/2=Sni+1/2sni+1/2, (3.11)

    and

    sni+1/2=mink=1,...,K(max(λnk,i,λnk,i+1)). (3.12)

    In this case, the control parameter can be written as follows:

    αni+1/2=˜αni+1/2+σni+1/2Φ(rmi+1/2), (3.13)

    where ˜αni+1/2 is given by (3.11), and Φi+1/2=Φ(ri+1/2) is a function that limits the slope. While for

    ri+1/2=Wi+1qWiqWi+1Wi,q=sgn[F(Xn+1,Wni+1/2)]

    and

    σni+1/2=ΔtΔxSni+1/2Sni+1/2sni+1/2.

    One may use any slope limiter function, including minmod, superbee, and Van leer [28] and [29]. At the end, the G. Rusanov scheme for Eq (2.3) can be written as follows

    {Wni+12=12(Wni+Wni+1)αni+122Snj+12[F(Wni+1)F(Wni)]+αni+122Snj+12Qni+12,Wn+1i=Wnirn[F(Wni+12)F(Wni12)]+ΔtnQin. (3.14)

    With a definition of the C-property [30], the source term in (2.1) is discretized in the G. Rusanov method in a way that is well-balanced with the discretization of the flux gradients. According to [30,31], if the following formulas hold, a numerical scheme is said to achieve the C-property for the system (3.1).

    (hp11)n= constant,hn+B= constantandvn1=vn2=0. (4.1)

    When we set v1=v2=0 in the stationary flow at rest, we get system (3.1), which can be expressed as follows.

    t(h0012hp1112hp1212hp22)+x(0hp11+12gh2hp12000)=(0ghBx0000)=Q(x,t). (4.2)

    We can express the predictor stage (3.14) as follows after applying the G. Rusanov scheme to the previous system

    Wni+12=(12(hni+hni+1)αni+124Sni+12(hni+hni+1)[(hni+1+Bi+1)(hni+Bi)]αni+122Sni+12((hp11)ni+1(hp11)niαni+122Sni+12((hp12)ni+1(hp12)ni)14((hp11)ni+1+(hp11)ni)14((hp12)ni+1+(hp12)ni)14((hp22)ni+1+(hp22)ni)). (4.3)

    Also, we can write the previous equations as follows

    Wni+12=(hni+120αni+122Sni+12((hp12)ni+1(hp12)ni)12(hp11)ni+1212(hp12)ni+1212(hp22)ni+12), (4.4)

    and the stage of the corrector updates the solution to take on the desired form.

    ((h)n+1i(hv1)n+1i(hv2)n+1i(E11)n+1i(E12)n+1i(E22)n+1i)=((h)ni(hv1)ni(hv2)ni(E11)ni(E12)ni(E22)ni)ΔtnΔx(0g2((hni+12)2(hni12)2)(hp12)ni+12(hp12)ni12000) (4.5)
    +(0ΔtnQni0000).

    The solution is stationary when Wn+1i=Wni and this leads us to rewrite the previous system (4.5) as follows

    Δtn2Δxg((hni+12)2(hni12)2)ΔtnQni.

    This lead to the following

    Qni=g8Δx(hni+1+2hni+hni1)(Bi+1Bi1). (4.6)

    Afterward, when the source term in the corrector stage is discretized in the earlier equations, this leads to the G. Rusanov satisfying the C-property.

    In order to simulate the SSW system numerically, we provide five test cases without a source term using the G. Rusanov, Rusanov, and Lax-Friedrichs schemes to illustrate the effectiveness and precision of the suggested G. Rusanov scheme. The computational domain for all cases is L=[0,1] divided into 300 gridpoints, and the final time is t=0.5s, except for test case 2, where the final time is t=10s. We evaluate the three schemes with the reference solution on the extremely fine mesh of 30000 cells that was produced by the traditional Rusanov scheme. Also, we provide one test case with a source term using the G. Rusanov scheme in the domain [0,1] divided into 200 gridpoints and final time t=0.5. We select the stability condition [19] in the following sense

    Δt=CFLΔxmaxi(|αni+12Sni+12|), (5.1)

    where a constant CFL=0.5.

    This test case was studied in [24] and [32], and the initial condition is given by

    (h,v1,v2,p11,p22,p12)={(0.01,0.1,0.2,0.04,0.04,1×108)ifxL2,(0.02,0.1,0.2,0.04,0.04,1×108)ifx>L2. (5.2)

    The solution include five waves, which are represented by 1 shock and 6 rarefaction. We compare the numerical results with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells. Figures 13 show the numerical results and variation of parameter of control. We note that all waves are captured by this scheme and the numerical solution agrees with the reference solution. Table 1 shows the CPU time of computation for the three schemes by using a Dell i5 laptop, CPU 2.5 GHZ.

    Figure 1.  High water h and velocity v1.
    Figure 2.  Velocity v2 and pressure p11.
    Figure 3.  Pressure p12 and control of parameter αn.
    Table 1.  CPU time for the G. Rusanov, Rusanov, and Lax-Friedrichs schemes.
    Scheme G. Rusanov Rusanov Lax-Friedrichs
    CPU time 0.068005 0.056805 0.0496803

     | Show Table
    DownLoad: CSV

    This test case (the shear waves problem) was studied in [24] and [32], and the initial condition is given by

    (h,v1,v2,p11,p22,p12)={(0.01,0,0.2,1×104,1×104,0)ifxL2,(0.01,0,0.2,1×104,1×104,0)ifx>L2. (5.3)

    The solution is represented by two shear waves with only transverse velocity discontinuities, the p12 and p22 elements of a stress tensor. We compare the numerical results by G. Rusanov, Rusanov, and Lax-Friedrichs with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells and a final time t=10s, see Figures 4 and 5. We observe that Figure 5 displays a spurious rise in the central of the domain of computation, which has also been seen in the literature using different methods, see [24,32].

    Figure 4.  Velocity v2 and pressure p12.
    Figure 5.  Pressure p22 at time t=5s.

    This test case was studied in [24] with the following initial condition

    (h,v1,v2,p11,p22,p12)={(0.02,0,0,4×102,4×102,0)ifxL2,(0.01,0,0,4×102,4×102,0)ifx>L2. (5.4)

    The solution for h, v1, and p11 consists of two shear rarefaction waves, one moving to the right and the other moving to the left, and a shock wave to the right. See Figures 6 and 7 which show the behavior of the height of the water, velocity, pressure, and variation of the parameter of control.

    Figure 6.  Height water h and velocity v1 at final time t=0.5s.
    Figure 7.  Pressure p11 and parameter of control α at final time t=0.5s.

    We take the same example, but with another variant of the modified test case, where p12=1×108 is set to a small non-zero value. We notice that the behavior of h, v1, and p11 is the same, but there is a change in the behavior of p12 such that it displays all of the five waves (four rarefaction and one shock) of the shear shallow water model, see Figures 8 and 9.

    Figure 8.  Height water h and velocity v1 at final time t=0.5s.
    Figure 9.  Pressure p11 and Pressure p12 at final time t=0.5s.

    This test case was studied in [24] with the following initial condition

    (h,v1,v2,p11,p22,p12)={(0.02,0,0,1×104,1×104,0)ifxL2,(0.03,0.221698,0.0166167,1×104,1×104,0)ifx>L2. (5.5)

    The solution for this test case consists of a single shock wave. We compare the numerical results with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells and a final time t=0.5s. Figures 10 and 11 show the numerical results, and we note that all waves are captured by this scheme and the numerical solution agrees with the reference solution, but the solution of p11 does not agree with the exact solution [24]. There is an oscillation with Lax-Friedrichs scheme in the water height h and the pressure p11.

    Figure 10.  Water height h and velocity v1 at final time t=0.5s.
    Figure 11.  Pressure p11 at final time t=0.5s.

    This test case (the shear waves problem) was studied in [24] and [32] with the following initial condition

    (h,v1,v2,p11,p22,p12)={(0.02,0,0,1×104,1×104,0)ifxL2,(0.01,0,0,1×104,1×104,0)ifx>L2. (5.6)

    The solution of this test case has a single shock wave and a single rarefaction wave, separated by a contact discontinuity. We compare the numerical results with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells and a final time t=0.5s. Figures 12 and 13 show the numerical results, and we note that all waves are captured by this scheme and the numerical solution agrees with the reference solution, but the solution of p11 does not agree with the reference solution [24].

    Figure 12.  Water height h and velocity v1 at final time t=0.5s.
    Figure 13.  Pressure p11 at final time t=0.5s.

    In this test case, we take the previous test case 3 and we added the discontinuous fond topography with the following initial condition

    (h,v1,v2,p11,p22,p12,B)={(0.02,0,0,4×102,4×102,1×108,0)ifxL2,(0.01,0,0,4×102,4×102,1×108,0.01)ifx>L2. (5.7)

    We simulate this test case with the G. Rusanov scheme with 200 gridpoints on the domain L=[0,1] at the final time t=0.5s, and we note that the behavior of the solution for h consists of one shear rarefaction wave moving to the left, a contact discontinuity after that two shear rarefaction waves, one moving to the right and the other moving to the left (see the left side of Figure 14. The right side of the Figure 14 shows the behavior of the velocity v1, which it consists of a rarefaction wave, a contact discontinuity after that, and two shear rarefactions. The left side of Figure 14 displays the behavior of the velocity v1. It is composed of two shear rarefactions followed by a contact discontinuity and three rarefaction waves moving to the right. The the right side of Figure 14 displays the behavior of the velocity v2. It is composed of two shear rarefactions moving to the left followed by a contact discontinuity after that, and two rarefaction waves moving to the right.

    Figure 14.  Water height h and velocity v1 at final time t=0.5s.
    Figure 15.  Pressure p11 and velocity v2 at final time t=0.5s.

    In summary, we have reported five numerical examples to solve the SSW model. Namely, we implemented the G. Rusanov, Rusanov, and Lax-Friedrichs schemes. We also compared the numerical solutions with the reference solution obtained by the classical Rusanov scheme on the very fine mesh of 30000 gridpoints. The three schemes were capable of capturing shock waves and rarefaction. Also, we have given the last numerical test with a source term. Finally, we discovered that the G. Rusanov scheme was more precise than the Rusanov and Lax-Friedrichs schemes.

    The current study is concerned with the SSW model, which is a higher order variant of the traditional shallow water model since it adds vertical shear effects. The model features a non-conservative structure, which makes numerical solutions problematic. The 1D SSW model was solved using the G. Rusanov technique. We clarify that this scheme satisfied the C-property. Several numerical examples were given to solve the SSW model using the G. Rusanov, Rusanov, Lax-Friedrichs, and reference solution techniques. The simulations given verified the G. Rusanov technique's high resolution and validated its capabilities and efficacy in dealing with such models. This approach may be expanded in a two-dimensional space.

    H. S. Alayachi: Conceptualization, Data curation, Formal analysis, Writing - original draft; Mahmoud A. E. Abdelrahman: Conceptualization, Data curation, Formal analysis, Writing - original draft; K. Mohamed: Conceptualization, Software, Formal analysis, Writing - original draft.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number 445-9-753.

    The authors declare that they have no competing interests.


    Acknowledgments



    The authors acknowledge the support of the National Science Foundation Grant Number 1828793. Portions of this work were supported under a contract from the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. We thank Louis Sumrall for the S. putrefaciens dataset.

    Conflict of interest



    The authors declare no conflict of interest.

    Author contributions:



    Acres—processed DHM data, performed tracking, prepared figures, wrote paper.
    Nadeau—collected and processed DHM data, wrote paper.

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