Abstract: A system of evaluating a mobile device includes an imaging device to capture data taken along an edge of the mobile device; and a processing device to process the data and calculate a difference in distance between a surface of a display and a frame of the mobile device and compare the difference in distance to a predetermined value.

Abstract: Disclosed are systems and methods for facilitating compound identification based on analytical data obtained from an analytical instrument such as, for example, a mass spectrometer.

Abstract: Systems, apparatus, and computer-readable storage media are disclosed for analyzing samples of a well plate. Systems may include a well plate, a mass spectrometer, and a computing device. The well plate may include rows of wells. The mass spectrometer may sequentially capture a sample from each well of the rows of wells and generate spectral data that includes mass spectrum data for each captured sample. The computing device may receive the spectral data generated by the mass spectrometer, detect rows of spectral data in the spectral data, wherein each row of spectral data corresponds to a row of wells in the well plate; and generate a spectral data matrix from the detected rows of spectral data such that each row of wells comprises a corresponding row of spectral data in the spectral data matrix.

Abstract: Methods and systems for mass spectrometry are disclosed. In one example, a method comprises: receiving, by a mass spectrometer via a sampling system operably connected thereto, at least one sample containing at least one known compound; modulat-ing at least one instrument parameter of the mass spectrometer through a plurality of instrument parameter values; analyzing the at least one sample while applying each of the plurality of instrument parameter values; acquiring a plurality of mass spectral (MS) datasets each corresponding to one of the applied plurality of instrument parameter values; encoding each of the plurality of MS datasets to generate a corresponding plurality of MS results each corresponding to one of the applied instrument parameter values; and compiling and storing the MS datasets and MS results in a spectral library in association with the applied instrument parameter values.

Abstract: A mass range is fragmented and mass analyzed using n samples, producing measurements in n dimensions. Two clustering algorithms are applied to the measurements, producing two sets of clusters, and compounds in the sets are identified. Two or more compounds found in a cluster of both sets are identified. The two or more compounds are compared to groups of compounds related to a biological process to identify a group that includes the two or more compounds. An additional compound is selected from the group. The two sets are reanalyzed to identify the compound in the sets. A co-occurrence matrix is calculated that quantifies the co-occurrence of the compound and each of the two or more compounds in the sets. If no co-occurrence quantity for the compound and each of the two or more compounds in the matrix is below a threshold, the two or more compounds are verified.

Abstract: Systems and methods are disclosed for performing a DDA mass spectrometry experiment. A precursor ion survey scan of a mass range is performed to generate a precursor ion peak list. A series of steps are performed for each precursor ion peak of the peak list. A peak mass range including the precursor ion peak is selected. A precursor ion mass selection window with a width smaller than the peak mass range is canned across the peak mass range in overlapping steps, producing a series of overlapping windows across the peak mass range. Each overlapping precursor ion mass selection window of the series is fragmented. Product ions produced from each overlapping precursor ion mass selection window of the series are mass analyzed, producing a product ion spectrum for each overlapping precursor ion mass selection window of the series and a plurality of product ion spectra for the peak.

Abstract: This application relates to apparatus and methods for automatically configuring devices under test to allow for the loading of software, such as firmware and applications, onto the devices under test. In one example, a testing system includes a testing frame with multiple cabinets. Each cabinet houses a device, such as a smartphone. The testing system also includes a testing computer communicatively coupled to the devices, such as through a USB connection. The testing computer may receive, from a database, workflow data for each type of device. The workflow data characterizes a workflow to follow to configure each type of device. For each device, the testing computer determines human interface device (HID) actions based on the workflow data corresponding to the device. Further, the testing computer transmits the corresponding HID actions to each device, causing the devices to perform one or more configuration operations to allow for the loading of software.

Abstract: A method for performing mass spectrometry (MS) comprises receiving MS data corresponding to a plurality of MS runs, wherein MS data corresponding to an MS run of the plurality of MS runs comprises detected intensities for a plurality of mass over charge ratios (MZ values) during the MS run; finding a recurrent MZ value of the plurality of MZ values, wherein a detected intensity for the recurrent MZ value appears as a recurrent peak in MS data corresponding to a subset of the plurality of MS runs; and the subset of the plurality of MS runs includes at least two MS runs of the plurality of MS runs; and identifying the recurrent MZ value as corresponding to a background ion.

Abstract: Methods and systems for identifying analytes in a sample using mass spectrometry are provided. A method for identifying analytes in mass spectrometry data comprises: introducing a sample to a mass spectrometer; analyzing the sample with the mass spectrometer in a plurality of cycles; generating, for each cycle, a mass spectrum comprising at least one peak; annotating peaks in the mass spectrum based on their relationships; assigning best ion types to each peak; processing each cycle of the mass spectrum to assign a score to each of the at least one peak thereof with respect to the likely neutral mass related to the peak; grouping peaks that share a common neutral mass; and outputting the analyte neutral mass.

Abstract: Methods and systems for building and using an analyte library are provided. One aspect is a method for building an analyte library, the method comprising receiving mass spectrum data from analysis of a sample using mass spectrometry, mass spectrum data including a mass spectrum and a sample matrix, and the sample including an analyte, identifying peaks in the mass spectrum, assigning at least one ion type to the peaks, annotating the peaks for the analyte based on the sample matrix, extracting an ion fingerprint for the analyte based on the annotated peaks and storing an analyte identification entry including the ion fingerprint for the analyte.

Abstract: Systems and methods are disclosed for analyzing a sample using overlapping precursor isolation windows. A mass analyzer of a tandem mass spectrometer is instructed to select and fragment at least two overlapping precursor isolation windows across a precursor ion mass range of a sample using a processor. The tandem mass spectrometer includes a mass analyzer that allows overlapping precursor isolation windows across the mass range of the sample.

Abstract: In one aspect, a method of operating a mass spectrometer is disclosed, which comprises ionizing a sample to generate a plurality of ions, and introducing at least a portion of the ions into an inlet orifice of the mass spectrometer. At least a portion of the ions and/or fragments thereof is detected by a downstream detector to generate a plurality of ion detection events, and the ion detection events are monitored to determine an ion count. The ion count is compared with a reference level to determine whether the detected level exceeds the reference level.

Abstract: Methods and systems for identifying one or more analytes in a sample are provided. One aspect is a method of predicting an identity of analytes in an unknown sample, the method comprising accessing a database comprising a plurality of results from analyzing samples using mass spectrometry to identify analytes, the plurality of results including annotated ion fingerprints, training a machine learning model with the plurality of results, and applying the machine learning model to the unknown sample to predict an identity of one or more analytes in the unknown sample.

Abstract: Systems and methods for performing mass analysis. An example method may include ejecting, from a first well of a well plate, a first sample into a transport fluid; ionizing the first sample and the transport fluid to generate first ions; detecting the first ions over a first period of time; and when a count rate of the detected first ions is above a background count rate threshold, accumulating a count of the detected first ions. The method may also include ejecting, from a second well of the well plate, a second sample into the transport fluid; ionizing the second sample and the transport fluid to generate second ions; detecting the second ions over a second period of time; and when a count rate of the detected second ions is above the background count rate threshold, accumulating a count of the detected second ions.

Abstract: During each time cycle, a precursor ion transmission window is stepped in k overlapping steps that are ?m m/z apart entirely across a mass range from a starting mlm/z. The window is stepped n?1 more times starting at n?1 different offsets from ml between ml and ml+?m. A total of n scans of the mass range. A total of k×n product ion spectra are produced that are a function of precursor ion m/z for each time cycle. A product ion is selected from the spectra. For at least one time cycle, an intensity of the product ion as a function of precursor ion m/z is reconstructed with a resolving power greater than ?m by combining intensities of the product ion measured during each of the n scans using a linear reconstruction algorithm, such as Drizzle.

Abstract: A method of operating a system including a differential mobility spectrometer (DMS) and a mass spectrometer. A sample is introduced to the DMS. The sample is analyzed with the DMS. Data is generated based at least in part on an analyte ion generated from the sample and at least one transport gas composition. Library data of the analyte ion is accessed from a library. The generated data is compared to the library data. A signal is sent when the generated data deviates from the library data by more than a predetermined threshold.

Abstract: Methods and systems for improving peak integration in mass spectrometry. A method may include accessing an ion data series; generating a set of prospective peak integrations for a target peak in the ion data series; providing, as input to a trained machine learning model, at least one peak characteristic for each prospective peak integration in the set of prospective peak integrations; processing the provided input, by the trained machine learning model, to generate an output from the trained machine learning model; based on the output, generating a ranking of one or more of the prospective peak integrations; and based on one of the prospective peak integrations, generating an ion amount represented by the target peak.

Abstract: Systems and methods are disclosed for analyzing a sample using overlapping precursor isolation windows. A mass analyzer of a tandem mass spectrometer is instructed to select and fragment at least two overlapping precursor isolation windows across a precursor ion mass range of a sample using a processor. The tandem mass spectrometer includes a mass analyzer that allows overlapping precursor isolation windows across the mass range of the sample.

Abstract: Systems and methods for defect detection on displays are disclosed according to various embodiments. In one example, a disclosed method for detecting defects on an electronic device display comprises connecting an electronic device to a server computer having a processor and a non-transitory computer readable storage medium storing test software for testing the electronic device display. The method further comprises displaying an outline on the electronic device display, where the outline traces a perimeter of the electronic device display, and where the outline comprises pixels of a first color. The first color differs from a color of a pixel that is not on the perimeter of the electronic device display. The method further comprises capturing a digital image of the electronic device while the electronic device is displaying the outline, transmitting the digital image to the server computer, and analyzing the digital image at the server computer.

Abstract: An uncertainty weighted average of the equalized amounts of two or more quantifier ions is calculated from a quantitation experiment itself. n known i ions of a compound are mass analyzed over time in each of m different samples, producing n XIC peaks for each of the m samples. A reference ion j is selected that is a j ion of the n i ions or a hypothetical ion j. A ratio r(j,i) of a peak area of the j ion to a peak area of each ion of the n i ions is calculated for each of the m samples, producing m r(j,i) ratios for each of the n i ions. An expected ratio rq(j,i) is calculated for each ion of the n i ions from the m r(j,i) ratios for each of the n i ions. For each sample, the uncertainty weighted average is calculated using rq(j,i).