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double-exponential fitting function  (MathWorks Inc)


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    MathWorks Inc double-exponential fitting function
    Double Exponential Fitting Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/double-exponential+function/pmc10060165-290-8-11
    Average 90 stars, based on 1 article reviews
    double-exponential fitting function - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: The Role of Prefrontal and Posterior Parietal Cortex in Generating Multiple Step Saccades.
    Article Snippet: While multiple step saccades (MSS) are occasionally reported in the healthy population, they are more evident in patients with Parkinson’s disease (PD).. Therefore, MSS has been suggested as a biological marker for the diagnosis of PD.. However, the lack of clarity on the neural mechanism underlying the generation of MSS largely impedes their application in the clinic.

    Article Title: High-temperature line strength and line shape parameters measurements of Ar- and N2-perturbed CO2 lines near 4.18 µm in a shock tube
    Article Snippet: Line strengths and line shape parameters of Arand N2-perturbed CO2 R-branch transitions (82 ≤ J′′ ≤ 90) in the ν3 fundamental band were measured in a shock tube from 730 K to 2500 K and pressure below 1.13 atm using laser absorption spectroscopy (LAS).. The retrieved absorption curves were fitted with the Voigt and the quadratic speed-dependent Voigt (qSDV) profiles to obtain the line strengths, broadening, and shift coefficients.. Line strengths were compared to values in HITEMP, HITRAN2020, and Ames2021 databases, and the HITEMP shows the best agreement with the measured results.

    Article Title: Fast and sensitive GCaMP calcium indicators for imaging neural populations
    Article Snippet: Obtained bleaching profiles were fit using a double-exponential fitting function in MATLAB to calculate their respective time constants ( τ bleach ).

    Article Title: Transcription templated assembly of the nucleolus in the C. elegans embryo
    Article Snippet: We used Matlab’s fitting function and Maximum Likelihood Estimation (Figure 2A and S1) to obtain parameters for AB8 cells: NN8−cccccccc AAAA = (1.9 ± 0.1) × 104 molecules, and KKdd = 55 ± 6 mmmmmm/μμmm3, values which are in the same range as reported in (7).

    Article Title: Transcription templated assembly of the nucleolus in the C. elegans embryo
    Article Snippet: We used Matlab’s fitting function and Maximum Likelihood Estimation (Figure 2A and S1) to obtain parameters for AB8 cells: NN8−ccccccccAAAA = (1.9 ± 0.1) × 104 molecules, and KKdd = 55 ± 6 mmmmmm/μμmm3, values which are in the same range as reported in (7).

    Article Title: A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port
    Article Snippet: 2024, 12, 405 7 of 15 operation time does not vary too much and is distributed at around 24 h. Although the sample size is not very large, the normal distribution can fit the data at the accepted level of 95% using the normal fitting function in Matlab R2022a.

    Article Title: Study on milling behavior of TiAlN coated tool with variable distribution density micro-texture
    Article Snippet: Considering that after milling titanium alloy with a ball-end milling cutter, the wear degree of different areas of the rake face is different, which indicates that the tool-chip contact conditions in this area are different, and then the micro-texture action mode is different.. To improve the effect of microtexture, this paper establishes a mathematical distribution model of variable distribution density micro-texture based on the two-zone method, builds a variable distribution density micro-texture ball-end milling titanium alloy test platform, studies the influence of variable density micro-texture parameters on tool milling behavior, and optimizes the parameters based on the improved particle swarm optimization algorithm.. The results show that the micro-texture with variable distribution density has a positive effect on the milling behavior of the tool.

    Article Title: Neuro-Fuzzification Architecture for Modeling of Electrochemical Ion-Sensing Data of Imidazole-Dicarboxylate-Based Ru(II)-Bipyridine Complex.
    Article Snippet: S4 In this study, a neural network for function fitting was coded in MATLAB 2018.



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    Confocal microscopic analysis of enhancer activity of mSE078 fragments using PCP-PP7 system in MEF cells. ( A ) Left: Schematic representation of mkrn1 P -12 × PP7-SE reporter plasmid construct. Right: Schematic representation of PCP-PP7 system used in this study. ( B ) Confocal microscopic analysis of tdPCP-CFP (transcript), SOX2-mCherry and p300-GFP signals in MEF cells. Cells were imaged after 24 h-post transfections of four plasmids. Left: 40× magnification images; Right: closed-up images of single cells. ( C ) Quantification of CFP (PCP), mCherry (SOX2) and GFP (p300) foci. Error bars indicate standard errors of means (SEM) from at least 15 nuclei. Quantification was done using ImageJ software. Particle size larger than 2 × 2 μm 2 was calculated. ( D ) Pearson's coefficients of CFP and GFP signals to mCherry signals. Pearson's coefficients were calculated using ImageJ software. Error bars indicate SEMs from ten nuclei. ( E ) Fluorescence recovery after photobleaching (FRAP) measuring SOX2-mCherry condensates in MEF cells co-transfected with PCP-CFP, SOX2-mCherry and p300-GFP plasmids. Photobleaching was initiated at 0 s. Curve shows mean (red dot) and SEM (black bar) of mCherry intensity of five regions. FRAP recovery curves were fitted to the double <t>exponential</t> function. P -values were calculated using one-way ANOVA. (ns) P < 0.1234; (*) P < 0.0332; (**) P < 0.0021; (***) P < 0.0002; (****) P < 0.0001.
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    Incremental stress–strain curves. ( A ) Strain versus time curve for electrospun 75:25 fibrinogen:PCL fiber. The fiber was pulled to a small strain (~10%) and held constant for approximately 30–40 s; this process was repeated with a slightly larger strain at each time. ( B ) Stress versus time curve. At constant strain, the stress relaxes and decays exponentially with time. ( C ) Representative stress relaxation curves. A double <t>exponential</t> curve is fitted to the relaxation curve (R 2 = 0.99) to determine the relaxation times. The fast and slow relaxation times for this curve were 1.8 s and 21 s. ( D ) Moduli versus strain curve. The total modulus, Y tot , (stars) and relaxed, elastic modulus, Y 0 , (dots) decrease as the strain increases. ( E ) The graph shows statistical differences between the slow and fast relaxation times of the fibers with two different ratios. The fiber diameter was 99 nm. ** indicates a p -value < 0.01; **** indicates a p -value < 0.0001.
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    Incremental stress–strain curves. ( A ) Strain versus time curve for electrospun 75:25 fibrinogen:PCL fiber. The fiber was pulled to a small strain (~10%) and held constant for approximately 30–40 s; this process was repeated with a slightly larger strain at each time. ( B ) Stress versus time curve. At constant strain, the stress relaxes and decays exponentially with time. ( C ) Representative stress relaxation curves. A double <t>exponential</t> curve is fitted to the relaxation curve (R 2 = 0.99) to determine the relaxation times. The fast and slow relaxation times for this curve were 1.8 s and 21 s. ( D ) Moduli versus strain curve. The total modulus, Y tot , (stars) and relaxed, elastic modulus, Y 0 , (dots) decrease as the strain increases. ( E ) The graph shows statistical differences between the slow and fast relaxation times of the fibers with two different ratios. The fiber diameter was 99 nm. ** indicates a p -value < 0.01; **** indicates a p -value < 0.0001.
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    Incremental stress–strain curves. ( A ) Strain versus time curve for electrospun 75:25 fibrinogen:PCL fiber. The fiber was pulled to a small strain (~10%) and held constant for approximately 30–40 s; this process was repeated with a slightly larger strain at each time. ( B ) Stress versus time curve. At constant strain, the stress relaxes and decays exponentially with time. ( C ) Representative stress relaxation curves. A double <t>exponential</t> curve is fitted to the relaxation curve (R 2 = 0.99) to determine the relaxation times. The fast and slow relaxation times for this curve were 1.8 s and 21 s. ( D ) Moduli versus strain curve. The total modulus, Y tot , (stars) and relaxed, elastic modulus, Y 0 , (dots) decrease as the strain increases. ( E ) The graph shows statistical differences between the slow and fast relaxation times of the fibers with two different ratios. The fiber diameter was 99 nm. ** indicates a p -value < 0.01; **** indicates a p -value < 0.0001.
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    Incremental stress–strain curves. ( A ) Strain versus time curve for electrospun 75:25 fibrinogen:PCL fiber. The fiber was pulled to a small strain (~10%) and held constant for approximately 30–40 s; this process was repeated with a slightly larger strain at each time. ( B ) Stress versus time curve. At constant strain, the stress relaxes and decays exponentially with time. ( C ) Representative stress relaxation curves. A double <t>exponential</t> curve is fitted to the relaxation curve (R 2 = 0.99) to determine the relaxation times. The fast and slow relaxation times for this curve were 1.8 s and 21 s. ( D ) Moduli versus strain curve. The total modulus, Y tot , (stars) and relaxed, elastic modulus, Y 0 , (dots) decrease as the strain increases. ( E ) The graph shows statistical differences between the slow and fast relaxation times of the fibers with two different ratios. The fiber diameter was 99 nm. ** indicates a p -value < 0.01; **** indicates a p -value < 0.0001.
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    Image Search Results


    Confocal microscopic analysis of enhancer activity of mSE078 fragments using PCP-PP7 system in MEF cells. ( A ) Left: Schematic representation of mkrn1 P -12 × PP7-SE reporter plasmid construct. Right: Schematic representation of PCP-PP7 system used in this study. ( B ) Confocal microscopic analysis of tdPCP-CFP (transcript), SOX2-mCherry and p300-GFP signals in MEF cells. Cells were imaged after 24 h-post transfections of four plasmids. Left: 40× magnification images; Right: closed-up images of single cells. ( C ) Quantification of CFP (PCP), mCherry (SOX2) and GFP (p300) foci. Error bars indicate standard errors of means (SEM) from at least 15 nuclei. Quantification was done using ImageJ software. Particle size larger than 2 × 2 μm 2 was calculated. ( D ) Pearson's coefficients of CFP and GFP signals to mCherry signals. Pearson's coefficients were calculated using ImageJ software. Error bars indicate SEMs from ten nuclei. ( E ) Fluorescence recovery after photobleaching (FRAP) measuring SOX2-mCherry condensates in MEF cells co-transfected with PCP-CFP, SOX2-mCherry and p300-GFP plasmids. Photobleaching was initiated at 0 s. Curve shows mean (red dot) and SEM (black bar) of mCherry intensity of five regions. FRAP recovery curves were fitted to the double exponential function. P -values were calculated using one-way ANOVA. (ns) P < 0.1234; (*) P < 0.0332; (**) P < 0.0021; (***) P < 0.0002; (****) P < 0.0001.

    Journal: Nucleic Acids Research

    Article Title: Molecular basis for SOX2-dependent regulation of super-enhancer activity

    doi: 10.1093/nar/gkad908

    Figure Lengend Snippet: Confocal microscopic analysis of enhancer activity of mSE078 fragments using PCP-PP7 system in MEF cells. ( A ) Left: Schematic representation of mkrn1 P -12 × PP7-SE reporter plasmid construct. Right: Schematic representation of PCP-PP7 system used in this study. ( B ) Confocal microscopic analysis of tdPCP-CFP (transcript), SOX2-mCherry and p300-GFP signals in MEF cells. Cells were imaged after 24 h-post transfections of four plasmids. Left: 40× magnification images; Right: closed-up images of single cells. ( C ) Quantification of CFP (PCP), mCherry (SOX2) and GFP (p300) foci. Error bars indicate standard errors of means (SEM) from at least 15 nuclei. Quantification was done using ImageJ software. Particle size larger than 2 × 2 μm 2 was calculated. ( D ) Pearson's coefficients of CFP and GFP signals to mCherry signals. Pearson's coefficients were calculated using ImageJ software. Error bars indicate SEMs from ten nuclei. ( E ) Fluorescence recovery after photobleaching (FRAP) measuring SOX2-mCherry condensates in MEF cells co-transfected with PCP-CFP, SOX2-mCherry and p300-GFP plasmids. Photobleaching was initiated at 0 s. Curve shows mean (red dot) and SEM (black bar) of mCherry intensity of five regions. FRAP recovery curves were fitted to the double exponential function. P -values were calculated using one-way ANOVA. (ns) P < 0.1234; (*) P < 0.0332; (**) P < 0.0021; (***) P < 0.0002; (****) P < 0.0001.

    Article Snippet: FRAP recovery curves were fitted to the double exponential function in GraphPad Prism software v.8.3.0 (GraphPad software, Boston, MA, USA).

    Techniques: Activity Assay, Plasmid Preparation, Construct, Transfection, Software, Fluorescence

    Incremental stress–strain curves. ( A ) Strain versus time curve for electrospun 75:25 fibrinogen:PCL fiber. The fiber was pulled to a small strain (~10%) and held constant for approximately 30–40 s; this process was repeated with a slightly larger strain at each time. ( B ) Stress versus time curve. At constant strain, the stress relaxes and decays exponentially with time. ( C ) Representative stress relaxation curves. A double exponential curve is fitted to the relaxation curve (R 2 = 0.99) to determine the relaxation times. The fast and slow relaxation times for this curve were 1.8 s and 21 s. ( D ) Moduli versus strain curve. The total modulus, Y tot , (stars) and relaxed, elastic modulus, Y 0 , (dots) decrease as the strain increases. ( E ) The graph shows statistical differences between the slow and fast relaxation times of the fibers with two different ratios. The fiber diameter was 99 nm. ** indicates a p -value < 0.01; **** indicates a p -value < 0.0001.

    Journal: Nanomaterials

    Article Title: The Mechanical Properties of Blended Fibrinogen:Polycaprolactone (PCL) Nanofibers

    doi: 10.3390/nano13081359

    Figure Lengend Snippet: Incremental stress–strain curves. ( A ) Strain versus time curve for electrospun 75:25 fibrinogen:PCL fiber. The fiber was pulled to a small strain (~10%) and held constant for approximately 30–40 s; this process was repeated with a slightly larger strain at each time. ( B ) Stress versus time curve. At constant strain, the stress relaxes and decays exponentially with time. ( C ) Representative stress relaxation curves. A double exponential curve is fitted to the relaxation curve (R 2 = 0.99) to determine the relaxation times. The fast and slow relaxation times for this curve were 1.8 s and 21 s. ( D ) Moduli versus strain curve. The total modulus, Y tot , (stars) and relaxed, elastic modulus, Y 0 , (dots) decrease as the strain increases. ( E ) The graph shows statistical differences between the slow and fast relaxation times of the fibers with two different ratios. The fiber diameter was 99 nm. ** indicates a p -value < 0.01; **** indicates a p -value < 0.0001.

    Article Snippet: Individual stress relaxation curves were fitted to this double exponential function in Origin (OriginLab Corporation, Northampton, MA, USA).

    Techniques: