Waters Technologies Ireland Limited

Exemplary embodiments provide computer-implemented methods, mediums, and apparatuses configured to provide an interactive analytical method debugger for an analytical laboratory system. The analytical laboratory system may include a laboratory analytical device with a number of settings, parameters, etc. The laboratory analytical device may process a sample according to an analytical method that (among other things) defines a configuration for the device. The settings for the method may be organized into categories. The interactive debugger identifies problems with the method (e.g., incompatibilities, values out of range, etc.) and automatically allow the user to view the category of the method that is relevant to addressing the issue. Possible solutions may be proposed in the debugger interface, allowing the user to quickly identify and address the problem. Embodiments are particularly well-suited to situations where a method is ported from an old device to a new device.

Exemplary embodiments provide techniques for creating or modifying a tenancy. The tenancy creation process may be divided into a plurality of independent stages, where each stage provisions services or resources in a cloud computing environment independent of provisioning others of the plurality of services or resources. If the current stage fails, the failure may be detected and programmatically corrected. For example, upon detecting that the first stage has failed, the system may retrieve a retry policy uniquely associated with the first stage and process the retry policy. The progress made by each of the independent stages may be logged, and the log may be used in connection with the retry policy. In some embodiments, relationships within an organization may be modeled by a graph database, which allows permissions to be more efficiently assigned than with other types of data structures.

Exemplary embodiments relate to methods, mediums, and systems to improve chromatographic peak detection and integration using machine learning techniques. An analytical integration tool determines peak locations using second derivative local maxima and identifies peak bounds where the second derivative changes sign. Various issues can cause this process to generate false positives or false negatives, or improper peak boundaries. To address this problem, users typically make manual changes to the integrated chromatograms. The proposed solution employs a machine learning approach that learns from user behaviour itself, using previous manual corrections on similar chromatograms to train models, rather than relying solely on mathematical algorithms that cannot capture individual standard operating procedures. This ensemble modelling approach combines the integration tool's outputs with manual corrections mined from histories of manual corrections, using a boosting paradigm to improve results.

An application hub is provided for applications of an analytical services platform. The analytical services platform may receive data from analytical devices and provide services, such as filtering, processing and visualizing the data. The application hub may act as a landing site for users on client devices to launch applications for the analytical services platform. The application hub may provide a web page to the client devices over a network that provides a user interface listing applications for the analytical services platform. Users may launch the applications through the user interface, such as by selecting user interface elements for the applications. The user interface may identify what applications have been installed on a client device and what applications have not been installed. The user interface may also identify when an application needs to be upgraded. Since the application hub is intended to be a single landing site for al applications, a single login may be provided.

An application hub is provided for applications of an analytical services platform. The analytical services platform may receive data from analytical devices and provide services, such as filtering, processing and visualizing the data. The application hub may act as a landing site for users on client devices to launch applications for the analytical services platform. The application hub may provide a web page to the client devices over a network that provides a user interface listing applications for the analytical services platform. Users may launch the applications through the user interface, such as by selecting user interface elements for the applications. The user interface may identify what applications have been installed on a client device and what applications have not been installed. The user interface may also identify when an application needs to be upgraded. Since the application hub is intended to be a single landing site for al applications, a single login may be provided.

Exemplary embodiments provides computer-implemented methods, mediums, and apparatuses configured to monitor the health of analytical chemistry systems. A monitoring system may be highly coupled to laboratory analytical instruments that it monitors. It may receive data and/or trends in the data as that data is generated by the instrument. Consequently, it can be configured to recognize when that data or trend signals a problem that needs to be corrected. A kiosk of the monitoring system may be configured to be in direct communication with the analytical chemistry system and to execute an action from the issue resolution structure to make the adjustment. Because the monitoring system is part of the direct physical control of the instrument(s), it can fix problems very quickly.