PEAXACT 3 Release Highlights

• Customizable chart titles and axis labels
• New baseline option for peak integration
• Drag & drop of directories
• Data tables without Excel
• Read timestamps from Opus 3D files
• New Validation Report Window
• Perform MCR and HMFA with the Application Server
• Perform parallel analyses with the Application Server
• View all release notes

All titles and labels of graphical reports can be edited when clicking on them. Your text is processed by a TeX interpreter, i.e., you can use ^ for superscripts, _ for subscripts, {} for grouping. Also, special commands for Greek letters (\alpha, \beta, \gamma, \Gamma, …) are available.

Default labels for x- and y-axis can be specified in the report preferences.

Baseline option Linear Fit - already known from the data pretreatment model - is now also available for integration models. Compare all four options at a glance:

• None: Baseline is zero; integration result may be negative if signal is negative.
• Offset: Baseline is the smallest y-value within x-limits; integration result is positive.
• Straight Line: Baseline is a straight line from lower to upper bound; integration result might be negative.
• Linear Fit: Baseline is a straight line fitted (from below) to the signal; integration result is positive.

Users without Excel can now benefit from PEAXACT's concept of Data Tables for data management. In addition to the Excel (.xls) format, PEAXACT now supports Data Tables files in the comma sperarated values (.csv) format. CSV-files are plain text files which can be edited with any common text editor.

OPUS Reaction Monitoring files and other 3D files typically store timestamps for each individual sample. Using the PEAXACT Data Inspector, these timestamps can automatically be read out and added to the Data Table. Afterwards, timestamps can be used for coloring and arranging samples in the Data Plotter and other grapical reports.

Testing the predictive capability of calibration models from time to time - and especially when changing the operating conditions of your measurement process - is essential to be sure that the calibration is still valid. The newly designed Validation Report makes model validation much easier. You can validate qualitatively or quantitatively depending on whether you provide test samples with reference values

The report now displays reference values of your test samples (blue) along with reference values of calibration (green) for a better visual evaluation. The evaluation can be done individually for each predictive feature and for each location (in case of location-dependent calibration). Quantitative measures like the prediction error RMSEP and prediction bias are shown.