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gausssian 09 software  (Gaussian inc)

 
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    Gaussian inc gausssian 09 software
    Gausssian 09 Software, supplied by Gaussian 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/continuous+complex+gaussian+wavelet+transform/gaussian09/us10137212-511-30-40
    Average 90 stars, based on 1 article reviews
    gausssian 09 software - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    Software:

    Article Title: Novel Dual-Mode Fluorescent Sensor for Detecting Chlorpyrifos and Cu(II)
    Article Snippet: .. The optimized structures and molecular orbitals (MOs) of the sensor and its proposed complex with Cu 2+ were investigated with Gaussian 09 software (Gaussian, Inc., Wallingford, Connecticut, United States) through density functional theory (DFT)-B3LYP calculation with 6-311G** and LanL2DZ mixed basis sets. ..

    Functional Assay:

    Article Title: Novel Dual-Mode Fluorescent Sensor for Detecting Chlorpyrifos and Cu(II)
    Article Snippet: .. The optimized structures and molecular orbitals (MOs) of the sensor and its proposed complex with Cu 2+ were investigated with Gaussian 09 software (Gaussian, Inc., Wallingford, Connecticut, United States) through density functional theory (DFT)-B3LYP calculation with 6-311G** and LanL2DZ mixed basis sets. ..

    other:

    Article Title: 15N CP/MAS NMR as a Tool for Mechanistic Study of Mechanical-stimuli Responsive Materials: Evidence for the Conformational Change of Emissive Dimethylacridane Derivative
    Article Snippet: It is based on the Gaussian(R) 09 system (copyright 2009, Gaussian, Inc.), the Gaussian(R) 03 system (copyright 2003, Gaussian, Inc.), the Gaussian(R) 98 system (copyright 1998, Gaussian, Inc.), the Gaussian(R) 94 system (copyright 1995, Gaussian, Inc.), the Gaussian 92(TM) system (copyright 1992, Gaussian, Inc.), the Gaussian 90(TM) system (copyright 1990, Gaussian, Inc.), the Gaussian 88(TM) system (copyright 1988, Gaussian, Inc.), the Gaussian 86(TM) system (copyright 1986, Carnegie Mellon University), and the Gaussian 82(TM) system (copyright 1983, Carnegie Mellon University).

    Article Title: Reducing Overprediction of Molecular Crystal Structures via Threshold Clustering
    Article Snippet: MJ Frisch, et al., Gaussian09 Revision D.01 (Gaussian Inc.) (2013).96 4.

    Article Title:
    Article Snippet: Fox, Gaussian 09 2009, Gaussian, Inc., Wallingford CT. 25.



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    (A) Slow trend and surrogate data of one participant. The slow trend is the slow trend of congruent condition in the FFA, there were 18 different slow trends; the surrogate data were generated by adding a <t>Gaussian</t> curve peaked at 400 ms and white noise (different for each participant) to the slow trend for each participant. Thus, 18 sets of surrogate data were generated. Subsequent analyses of these surrogate data are identical to how we analyzed the real data. (B) Left: Averaged surrogate data ( n =18, mean ± SEM), smoothed (60 ms bin) as a function of mask-to-probe SOA (200-780 ms in steps of 20 ms). Middle: Slow trends averaged across participants. Right: Average smoothed-and-detrended data, extracted by subtracting slow trends shown in Middle from smoothed (60 ms bin) data shown in left (thick lines). (C) Average spectrum for detrended data (extracted by subtracting slow trends from the surrogate data without smoothing). The statistical threshold of significance ( p < 0.05, multiple comparison corrected) calculated by performing a permutation test was shown with a dashed line.
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    Image Search Results


    (A) Slow trend and surrogate data of one participant. The slow trend is the slow trend of congruent condition in the FFA, there were 18 different slow trends; the surrogate data were generated by adding a Gaussian curve peaked at 400 ms and white noise (different for each participant) to the slow trend for each participant. Thus, 18 sets of surrogate data were generated. Subsequent analyses of these surrogate data are identical to how we analyzed the real data. (B) Left: Averaged surrogate data ( n =18, mean ± SEM), smoothed (60 ms bin) as a function of mask-to-probe SOA (200-780 ms in steps of 20 ms). Middle: Slow trends averaged across participants. Right: Average smoothed-and-detrended data, extracted by subtracting slow trends shown in Middle from smoothed (60 ms bin) data shown in left (thick lines). (C) Average spectrum for detrended data (extracted by subtracting slow trends from the surrogate data without smoothing). The statistical threshold of significance ( p < 0.05, multiple comparison corrected) calculated by performing a permutation test was shown with a dashed line.

    Journal: bioRxiv

    Article Title: Fluctuations of fMRI activation patterns reveal theta-band dynamics of visual object priming

    doi: 10.1101/148635

    Figure Lengend Snippet: (A) Slow trend and surrogate data of one participant. The slow trend is the slow trend of congruent condition in the FFA, there were 18 different slow trends; the surrogate data were generated by adding a Gaussian curve peaked at 400 ms and white noise (different for each participant) to the slow trend for each participant. Thus, 18 sets of surrogate data were generated. Subsequent analyses of these surrogate data are identical to how we analyzed the real data. (B) Left: Averaged surrogate data ( n =18, mean ± SEM), smoothed (60 ms bin) as a function of mask-to-probe SOA (200-780 ms in steps of 20 ms). Middle: Slow trends averaged across participants. Right: Average smoothed-and-detrended data, extracted by subtracting slow trends shown in Middle from smoothed (60 ms bin) data shown in left (thick lines). (C) Average spectrum for detrended data (extracted by subtracting slow trends from the surrogate data without smoothing). The statistical threshold of significance ( p < 0.05, multiple comparison corrected) calculated by performing a permutation test was shown with a dashed line.

    Article Snippet: To assess MVPA classification accuracies as a function of time (mask-to-probe SOA) and frequency, the detrended temporal profile for each condition was transformed using the continuous complex Gaussian wavelet (order = 4; e.g., FWHM =1.32 s for 1 Hz wavelet) transforms (Wavelet toolbox, MATLAB), with frequencies ranging from 1 to 25 Hz in steps of 2 Hz.

    Techniques: Generated, Comparison