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map o  (MathWorks Inc)


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    MathWorks Inc map o
    Map O, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 22 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/statistical+parametric+mapping+matlab+toolbox/MATLAB+Production+Server+Client+Libraries/pmc07492409-111-62-65
    Average 93 stars, based on 22 article reviews
    map o - by Bioz Stars, 2026-10
    93/100 stars

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    Modification:

    Article Title: Exploiting Online Spatially Resolved Dynamic Light Scattering and Flow-NMR for Automated Size Targeting of PISA-Synthesized Block Copolymer Nanoparticles
    Article Snippet: .. The instrument’s proprietary flow correction algorithms decoupled flow motion from diffusive motion in the phase resolved signal to yield final autocorrelation functions at each pathlength in Figure S9.1–3 A modified cumulants fitting method was used to obtain the cumulants Z-Average hydrodynamic diameter (d.nm) and a polydispersity index (PDI) for the expected monomodal distribution.4 A MATLAB™ Client interfaced with the instrument using the Open Platform Communications Unified Protocol (OPCUA) for real-time monitoring, data collection and instrument control over a network connection. ..

    Control:

    Article Title: Exploiting Online Spatially Resolved Dynamic Light Scattering and Flow-NMR for Automated Size Targeting of PISA-Synthesized Block Copolymer Nanoparticles
    Article Snippet: .. The instrument’s proprietary flow correction algorithms decoupled flow motion from diffusive motion in the phase resolved signal to yield final autocorrelation functions at each pathlength in Figure S9.1–3 A modified cumulants fitting method was used to obtain the cumulants Z-Average hydrodynamic diameter (d.nm) and a polydispersity index (PDI) for the expected monomodal distribution.4 A MATLAB™ Client interfaced with the instrument using the Open Platform Communications Unified Protocol (OPCUA) for real-time monitoring, data collection and instrument control over a network connection. ..

    other:

    Article Title: Teacups, a Python Package for the Simulation of Time-Resolved EPR Spectra of Spin-Polarized Multi-Spin Systems.
    Article Snippet: A XXXX, XXX, XXX−XXX L (39) Pribitzer, S.; Doll, A.; Jeschke, G. SPIDYAN, a MATLAB library for simulating pulse EPR experiments with arbitrary waveform excitation.

    Article Title: Comparative Study of Machine Learning and System Identification for Process Systems Engineering Dynamics
    Article Snippet: All data-driven models were implemented using a mixture of Python and MATLAB libraries/toolboxes.

    Article Title: The Fourier–Malliavin Volatility (FMVol) MATLAB® library
    Article Snippet: To describe our MATLAB® library, e generate a single trajectory of a bi-variate version of the well-known stochastic volatility model by [13]: dx1(t) = ( μ1 − 1 2 v1(t) ) dt + √ v1(t)dW 1t (23) dx2(t) = ( μ2 − 1 2 v2(t) ) dt + √ v2(t)dW 2t (24) dv1(t) = θ1(α1 − v1(t))dt + γ1 √ v1(t)dW 3t (25) dv2(t) = θ2(α2 − v2(t))dt + γ2 √ v2(t)dW 4t (26) where W 1,W 2,W 3,W 4 are correlated Brownian motions such that ⟨dW kt , dW rt ⟩ = ρk,r dt.

    Transmission Assay:

    Article Title: Process simulation and evaluation of scaled-up biocatalytic systems: Advances, challenges, and future prospects.
    Article Snippet: With the increased demand for bio-based products and the rapid development of biomanufacturing technologies, biocatalytic reactions including microorganisms and enzyme based, have become promising approaches.. Prior to the scale-up of production process, environmental and economic feasibility analysis are essential for the development of a sustainable and intelligent bioeconomy in the context of industry 4.0.. To achieve these goals, process simulation supports system optimization, improves energy and resource utilization efficiencies, and supports digital bioprocessing.



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    Image Search Results


    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox in MATLAB.

    Journal: NeuroImage

    Article Title: Investigating the neurovascular coupling across multiple motor execution and imagery conditions: a whole-brain EEG-informed fMRI analysis

    doi: 10.1016/j.neuroimage.2025.121311

    Figure Lengend Snippet: A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox in MATLAB.

    Article Snippet: fMRI analyses were performed using the Statistical Parametric Mapping (SPM) MATLAB toolbox ( http://www.fil.ion.ucl.ac.uk/spm/ , version 12) and custom MATLAB scripts.

    Techniques:

    A: Group-averaged t values showing BOLD correlates of alpha rhythms in channel C3 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). B: group-averaged t values showing neural correlates of alpha rhythms in channel C4 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). C: Group-averaged t values showing neural correlates of alpha rhythms in channel C3 during MI tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). Results are displayed using the BrainNet toolbox in MATLAB.

    Journal: NeuroImage

    Article Title: Investigating the neurovascular coupling across multiple motor execution and imagery conditions: a whole-brain EEG-informed fMRI analysis

    doi: 10.1016/j.neuroimage.2025.121311

    Figure Lengend Snippet: A: Group-averaged t values showing BOLD correlates of alpha rhythms in channel C3 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). B: group-averaged t values showing neural correlates of alpha rhythms in channel C4 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). C: Group-averaged t values showing neural correlates of alpha rhythms in channel C3 during MI tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). Results are displayed using the BrainNet toolbox in MATLAB.

    Article Snippet: fMRI analyses were performed using the Statistical Parametric Mapping (SPM) MATLAB toolbox ( http://www.fil.ion.ucl.ac.uk/spm/ , version 12) and custom MATLAB scripts.

    Techniques: