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Data Blocks

As you have seen before, OPUS files usually eonsist of several data blocks. These can be deleted individually from the file, not only removed from the display , using the Delete Data Block command. All corresponding data of a deleted data block, like search tables and integration results, will also be lost  [Pg.54]


The data volume, which can be imported as data block or single slices, can be cutted or rebinned (e.g. if the data set is very large) and interpolated (e.g. interpolating intermediate slices between measured CT cuts in the case of 2D-CT). [Pg.495]

Each flic is a sequence of data blocks containing individual data items. Data blocks represent logical grouping of data that arc related in some way,... [Pg.120]

Write a program in BASIC to calculate the dissociation energy of Ilj". This can be done by lilling in an appropriate data block using one or more DATA statements. [Pg.330]

The estimation of all the terms of Eq. (5.5) is possible for the balanced case and q repeated measurements in each cell of the data block represented in Fig. 5.1. Schemes for this and some reduced variants of three-way ANOVA are given in Scheffe [1961] Ahrens [1967] Dunn and Clark [1974] Graf et al. [1987] Sachs [1992]. [Pg.131]

The control path for the data reduction functions is depicted in Figure 4, which is an expanded view of the "Reduce Data" Block in Figure 2. The mainline functions provide a direct path from the raw data to a finished result with a minimum amount of input from the user. The functions in the right hand column are used mainly to make minor changes in the parameters controlling interactive data reduction. [Pg.135]

Generate principal components plots of data blocks... [Pg.200]

Fig. 26. Example of the data reduction process. Each data block of a multi-block sequence (in this case simple FIDs) is reduced to a single value by means of averaging over a predefined data window and plotted against the block s x-value. The resulting relaxation curve is then fitted to estimate its decay rate(s). The algorithm gives a lot of freedom in setting the data window and including/excluding any number of initial or final blocks. Notice that in the PP case shown here, the T-value decreases from left to right. This helps to minimize thermal variations of the magnet. Fig. 26. Example of the data reduction process. Each data block of a multi-block sequence (in this case simple FIDs) is reduced to a single value by means of averaging over a predefined data window and plotted against the block s x-value. The resulting relaxation curve is then fitted to estimate its decay rate(s). The algorithm gives a lot of freedom in setting the data window and including/excluding any number of initial or final blocks. Notice that in the PP case shown here, the T-value decreases from left to right. This helps to minimize thermal variations of the magnet.
Fig. 4. spectrum showing the three quaternary carbons Cl, C2 and C3 of compound 2 dissolved in CDiCN (bottom) and heteronuclear NOE spectra simultaneously acquired with pulse sequence II. Three data blocks a, b and c corresponding to three experiments with the number N of proton resonances selected for simultaneous saturation set to 1 (a), 5 (b) and 10 (c) are depicted. Five spectra with the initial saturation of protons 3, 1, 1 3" and 2 are presented. The additional five NOE difference spectra acquired in case c, with the irradiation of the sixth methyl and of four NH (NHa) proton resonances are not shown. (Continued on... [Pg.33]

If necessary, pre-echo control occurs at this point. This is done by using an actual threshold estimation which would be valid for the current block even if the sound which could cause pre-echo artifacts would be deleted from the signal. A good approximation for this hypothetical deletion is to use the data of the last block as an estimate for the current block. To have data of earlier blocks available, the preliminary estimated threshold is stored. It will be used for pre-echo control in the next input data block. [Pg.47]

An AR(30)-NAR(Q) model was fitted to data blocks containing 5000 samples of the distorted data. The non-linear terms allowed in the model were of the form ... [Pg.111]

The mean square error in the concentration estimate can be computed just as in PCR, although the value of cin will differ. It is also possible to provide a number of equivalent equations for this error using t and q which are left to the reader. In the case of the concentration estimates, it is usual to adjust the sum of squares according to the number of PLS components, because this number is often similar in magnitude to the number of objects in the dataset for example, there are 25 spectra in case study 1, but we might want to look at the error when ten PLS components are calculated. These error terms will also be discussed in Section 3.1. Note an interesting difference between the conventional equations for errors in the x and c data blocks in the former the mean is subtracted from the overall sum of... [Pg.14]

By plotting the eigenvalues (or errors in modelling the x block), it is also possible to determine prediction errors for the x data block. However, the main aim of calibration is to predict concentrations rather than spectra, so this information, whereas useful, is less frequently employed in calibration. [Pg.20]

With these newer methods of protein separation and amino acid analysis he prepared serum protein fractions by serial salting out with ammonium sulfate and by the Sober and Peterson DEAE cellulose columns (42), using the sera of reptile, fowl, and mammalian blood. Some of the amino acid analyses were carried out by the automatic amino acid methods of Hirs, Moore, and Stein (18). Fortified with this plethora of data, Block now had the opportunity to re-examine not only the ratio of the basic amino acids, but at least 12 amino acids in a variety of protein fractions prepared by at least two different procedures. With the aid of a statistician he determined the significance of the constancy of the molar ratios of pairs of amino acids and found that in spite of the marked variation of the absolute amounts of an amino acid, the molar ratios of certain pairs remain relatively constant among the numerous protein components of animal sera. [Pg.26]

PARM(i) Parameter array defined in KINETICS data block... [Pg.105]

RATES, USER PRINT, or USER PUNCH BASIC programs to store a value. The value may be retrieved by any of these BASIC programs. The value persists until overwritten using a PUT statement with the same set oT subscripts, or until the end of the run. For a KINETICS data block, the BASIC programs for the rate expressions are evaluated in the order in which they are defined in the input file. [Pg.106]

RXN Amount of reaction (moles) as defined in -steps in REACTION data block for a batch-reaction calculation, otherwise zero... [Pg.106]

Usually (but not exclusively) the error is calculated on the concentration data matrix (c), and we will resttict the discussion below to errors in concentration for brevity it is important to understand that similar equations can be obtained for the .r data block. [Pg.314]

Lower weight fraction range (first data block) 0... [Pg.124]

Upper weight fraction range (second data block) 1... [Pg.124]

INFINITE.DAT This file contains WFAC s for each infinitely dilute solvent system. Each data block is constructed as follows ... [Pg.135]

Let nib denote the number of w orking responses in block b and nj, the number of events in that data block. Then the coefficients in Eq. (C.1-2) can take either of the following forms as directed bv the user ... [Pg.218]


See other pages where Data Blocks is mentioned: [Pg.724]    [Pg.92]    [Pg.717]    [Pg.15]    [Pg.281]    [Pg.239]    [Pg.447]    [Pg.92]    [Pg.89]    [Pg.373]    [Pg.375]    [Pg.391]    [Pg.10]    [Pg.206]    [Pg.339]    [Pg.100]    [Pg.102]    [Pg.109]    [Pg.110]    [Pg.132]    [Pg.354]    [Pg.285]    [Pg.137]    [Pg.138]    [Pg.140]    [Pg.239]    [Pg.165]   


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Block data statements, FORTRAN

Block diagram algebra for sampled data systems

Delete data block

X-block data

Y-block data

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