pivlab matlab algorithm Search Results


particle image velocimetry algorithm  (MathWorks Inc)
96
MathWorks Inc particle image velocimetry algorithm
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
Particle Image Velocimetry Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pivlab matlab algorithm  (MathWorks Inc)
93
MathWorks Inc pivlab matlab algorithm
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
Pivlab Matlab Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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source matlab toolbox  (MathWorks Inc)
96
MathWorks Inc source matlab toolbox
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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algorithms partek flow software partek  (Partek)
86
Partek algorithms partek flow software partek
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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aaactcgagtt agaggactgctcg  (Addgene inc)
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Addgene inc aaactcgagtt agaggactgctcg
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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10319 prk5 myc rhoa q63l  (Addgene inc)
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Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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pcmv vsv g addgene  (Addgene inc)
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Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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resource source identifier recombinant dna pcmv deltar8 2 addgene  (Addgene inc)
94
Addgene inc resource source identifier recombinant dna pcmv deltar8 2 addgene
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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umacult ali medium  (STEMCELL Technologies Inc)
90
STEMCELL Technologies Inc umacult ali medium
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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poly-l-lysine-g-polyethylene glycol (pll-g-peg)  (Susos AG)
90
Susos AG poly-l-lysine-g-polyethylene glycol (pll-g-peg)
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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cytochalasin d  (Cayman Chemical)
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Cayman Chemical cytochalasin d
Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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dowsiltm cy 52–276 a&b  (Dow Corning)
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Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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Image Search Results


Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image velocimetry algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.

Journal: Advanced Intelligent Systems

Article Title: Acoustically Actuated Flow in Microrobots Powered by Axisymmetric Resonant Bubbles

doi: 10.1002/aisy.202300465

Figure Lengend Snippet: Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image velocimetry algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.

Article Snippet: We analyze the flow velocity at the inlet side (Figure 5a) using the particle image velocimetry algorithm (PIVlab toolbox, MATLAB)[38] and determine the peak velocity by analyzing the particle velocity along the sectional line perpendicular to the flow direction (Figure 5b, Movie S3, Supporting Information).

Techniques: