Scan data, manipulation

The ion-trap and Q-ToF instruments are, because of the way that they operate, unable to carry out precursor-ion scans. Computer manipulation of data generated during product-ion scans of the Q-ToF system, however, can yield equivalent data to that produced directly by precursor-ion scans on other instruments and an evaluation of this software-based approach has been carried out [14],... 

These initial experiments show that results can be obtained from this system that are comparable to those from the continuous flow reactor. The analytical system satisfies the requirements for accurate and rapid repetitive analysis. Scanning of 12 masses is possible at rates of approximately 100 ms/scan with good results. Further data manipulations are expected to yield additional results from this type of experiments. 

FTIR spectroscopy to a particular pesticide, the methods have general applications to numerous compounds. Most of these utilize the high sensitivity of FTIR, and the data manipulation capability of the system. In several of the gas evolution studies, spectra were acquired at less than one-minute intervals. While this is not really "rapid scanning," the high resolution required for vapor phase spectra would not have been possible with a normal dispersive instrument. Several other techniques using FTIR show promise in the area of pesticide analysis. 

The next bottleneck in the process was the collection, storage and analysis of the data. The whole data manipulation area, known as informatics, became a major source of research into the storage and analysis of data. It was also clear that the presentation of data was a problem since complete data sets often contained results as a function of a whole series of variables, which meant trying to find trends or an optimum of multidimensional data sets. To represent this data requires displays as surfaces or even more complex representations, which are certainly difficult for the imaccustomed to interpret and imderstand. Consequently, data-mining tools were employed and further developed to help scan the data sets for relationships. 

You can use a scanner and a software program that performs optical character recognition to create a data file from hard copy. Once imported into Excel, the data may have to be manipulated to get it into a useable form. The following example shows how to record a simple Excel macro for converting scanned data with blank lines and other undesired features into useful columnar data. 

It turns out that the mathematics behind the required interpretation procedure are straightforward, and require few assumptions. In fact, the mathematical formulation behind temperature scanning could have been written down many decades earlier. One might speculate that it was not formulated sooner because the dominant paradigm of kinetic studies required that rate data be collected at isothermal conditions. But, even if the equations had been written earlier, one would still have had to wait for computers to handle the massive amounts of data manipulation required to arrive at conventional rates of reaction using raw temperature scanning results. 

The advent of computers of reasonable price and their application to spectrometers, spurred by the rapid development of the Fourier transform technique, brought about a number of improvements that nowadays are integral parts of modern spectrometers, such as microprocessor control, self-checking routines, rapid scanning and visual display systems as well as opportunities for data manipulation and reduction, thus augmenting sensitivity, precision and fastness of data acquisition. 

Fig. 3. Raw DSC data showing the reproducibility obtained with successive scans. The only data manipulation performed is subtraction of the first buffer vs buffer scan ftom all succeeding scans. The buffer vs buffer baselines centered on 0 p,W are three repetitive scans (without reloading) on 10 mM potassium acetate (pH 5. 7) and 0.3 M KCl. The four protein vs buffer scans were collected with four separate loadings of the same sample (Sac7d, 1.6 mg/ml in the above buffer). The deviation observed is on the order of 1 p.W and is comparable to that observed for repetitive scans of buffer. Data were collected on a Calorimetry Sciences Nano II instrument with gold cylindrical cells.

---