Abstract: Images of an object may be captured via a camera at a mobile computing device at different viewpoints. The images may be used to identify components of the object and to identify damage estimates estimating damage to some or all of the components. Capture coverage levels corresponding with the components may be determined, and then recording guidance may be provided for capturing additional images to increase the capture coverage levels.

Abstract: Therapeutic compositions and an associated method for improving a Toll-like receptor (TLR)-related condition, including determining a set of peptide sequences associated with a microorganism-related modulator of a TLR, determining a first set of binding parameters for the set of peptide sequences in relation to the TLR, selecting a target subset of peptide sequences from the set of peptide sequences based on the first set of binding parameters, reengineering the target subset of peptide sequences based on mutating amino acid residues of the target subset of peptide sequences, determining a second set of binding parameters for the reengineered target subset of peptide sequences in relation to the TLR, and identifying a first peptide for use in a therapeutic composition for improving the TLR-related condition, based on the second set of binding parameters for the reengineered target subset of peptide sequences.

Abstract: An electronic device (10) includes an electronic component (14); at least one electrically conductive loop or winding (18) disposed around the electronic component; and an electronic controller (24) configured to: obtain (102) a magnetic field direction from a received ambient magnetic field measurement signal; determine (104) at least one magnetic field shim current based on the obtained magnetic field direction; and energize (106) the at least one electrically conductive loop or winding to flow the determined at least one magnetic field shim current.

Abstract: Novel images may be generated using an image generator implemented on a processor. The image generator may receive as input neural features selected from a neural texture atlas. The image generator may also receive as input one or more position guides identifying position information for a plurality of input image pixels. The novel images may be evaluated using an image discriminator to determine a plurality of optimization values by comparing each of the plurality of novel images with a respective one of a corresponding plurality of input images. Each of the novel images may be generated from a respective camera pose relative to an object identical to that of the respective one of the corresponding plurality of input images. The image generator and the neural features may be updated based on the optimization values and stored on a storage device.

Abstract: Using approximated bin intervals to label the histograms provides clarity and allows for the histogram to be more intuitively understood. A dataset may comprise a plurality of records having a plurality of features including one or more continuous features. A selection of a continuous feature may be obtained. A bin width based on a number of bins and feature statistics of the continuous feature may be determined. An approximated bin interval range is determined by applying a bin mask based on the bin width to the feature statistics. An approximated bin width is determined based on the number of bins and the approximated bin interval range. Approximated bin intervals for the histogram are determined based on the approximated bin width. A histogram is generated having bins with intervals based the approximated bin intervals.

Abstract: Images of an object may be captured via a camera at a mobile computing device at different viewpoints. The images may be used to identify components of the object and to identify damage estimates estimating damage to some or all of the components. Capture coverage levels corresponding with the components may be determined, and then recording guidance may be provided for capturing additional images to increase the capture coverage levels.

Abstract: Using approximated bin intervals to label the histograms provides clarity and allows for the histogram to be more intuitively understood. A dataset may comprise a plurality of records having a plurality of features including one or more continuous features. A selection of a continuous feature may be obtained. A bin width based on a number of bins and feature statistics of the continuous feature may be determined. An approximated bin interval range is determined by applying a bin mask based on the bin width to the feature statistics. An approximated bin width is determined based on the number of bins and the approximated bin interval range. Approximated bin intervals for the histogram are determined based on the approximated bin width. A histogram is generated having bins with intervals based the approximated bin intervals.

Abstract: Systems and methods include reception of a set of data including continuous features and a discrete feature, each continuous feature associated with a plurality of values and the discrete feature associated with a plurality of discrete values, determine, for each continuous feature, a relationship factor representing a relationship between the discrete feature and the continuous feature based on the plurality of values associated with the continuous feature and the plurality of discrete values, identify one of the continuous features associated with a largest one of the determined relationship factors, generate, for each of the other features, a correlation factor representing a correlation between the continuous feature and the identified continuous feature, determine, for each of the continuous features other than the identified continuous feature, a composite relationship score based on the relationship factor and the correlation factor associated with the feature, and present a visualization associated wi

Abstract: Images may be captured at an image capture device mounted on an image capture device gimbal capable of rotating the image capture device around a nodal point in one or more dimensions. Each of the plurality of images may be captured from a respective rotational position. The images may be captured by a designated camera that is not located at the nodal point in one or more of the respective rotational positions. A designated three-dimensional point cloud may be determined based on the plurality of images. The designated three-dimensional point cloud may include a plurality of points each having a respective position in a virtual three-dimensional space.

Abstract: Using approximated bin intervals to label the histograms provides clarity and allows for the histogram to be more intuitively understood. A dataset may comprise a plurality of records having a plurality of features including one or more continuous features. A selection of a continuous feature may be obtained. A bin width based on a number of bins and feature statistics of the continuous feature may be determined. An approximated bin interval range is determined by applying a bin mask based on the bin width to the feature statistics. An approximated bin width is determined based on the number of bins and the approximated bin interval range. Approximated bin intervals for the histogram are determined based on the approximated bin width. A histogram is generated having bins with intervals based the approximated bin intervals.

Abstract: Images may be captured at an image capture device mounted on an image capture device gimbal capable of rotating the image capture device around a nodal point in one or more dimensions. Each of the plurality of images may be captured from a respective rotational position. The images may be captured by a designated camera that is not located at the nodal point in one or more of the respective rotational positions. A designated three-dimensional point cloud may be determined based on the plurality of images. The designated three-dimensional point cloud may include a plurality of points each having a respective position in a virtual three-dimensional space.

Abstract: Embodiments of a method and system for improved microbiome sequencing can include: generating guide RNA complexes for a set of targets corresponding to a set of taxa associated with the microorganism-related condition; processing the biological sample with the gRNA complexes to generate microorganism nucleic acid fragments comprising a set of end regions associated with the set of targets; ligating the set of end regions with a set of adapters sharing an adapter sequence; and amplifying the set of targets based on the ligated set of end regions and a set of primers sharing a primer sequence associated with the adapter sequence.

Abstract: Three-dimensional points may be projected onto first locations in a first image of an object captured from a first position in three-dimensional space relative to the object and projected onto second locations a virtual camera position located at a second position in three-dimensional space relative to the object. First transformations linking the first and second locations may then be determined. Second transformations transforming first coordinates for the first image to second coordinates for the second image may be determined based on the first transformations. Based on these second transformations and on the first image, a second image of the object from the virtual camera position.

Abstract: Images may be captured at an image capture device mounted on an image capture device gimbal capable of rotating the image capture device around a nodal point in one or more dimensions. Each of the plurality of images may be captured from a respective rotational position. The images may be captured by a designated camera that is not located at the nodal point in one or more of the respective rotational positions. A designated three-dimensional point cloud may be determined based on the plurality of images. The designated three-dimensional point cloud may include a plurality of points each having a respective position in a virtual three-dimensional space.

Abstract: Systems and methods include reception of a set of data including continuous features and a discrete feature, each continuous feature associated with a plurality of values and the discrete feature associated with a plurality of discrete values, determine, for each continuous feature, a relationship factor representing a relationship between the discrete feature and the continuous feature based on the plurality of values associated with the continuous feature and the plurality of discrete values, identify one of the continuous features associated with a largest one of the determined relationship factors, generate, for each of the other features, a correlation factor representing a correlation between the continuous feature and the identified continuous feature, determine, for each of the continuous features other than the identified continuous feature, a composite relationship score based on the relationship factor and the correlation factor associated with the feature, and present a visualization associated wi

Abstract: One or more two-dimensional images of a three-dimensional object may be analyzed to estimate a three-dimensional mesh representing the object and a mapping of the two-dimensional images to the three-dimensional mesh. Initially, a correspondence may be determined between the images and a UV representation of a three-dimensional template mesh by training a neural network. Then, the three-dimensional template mesh may be deformed to determine the representation of the object. The process may involve a reprojection loss cycle in which points from the images are mapped onto the UV representation, then onto the three-dimensional template mesh, and then back onto the two-dimensional images.

Abstract: The present disclosure involves systems, software, and computer implemented methods for ranking time dimensions. One example method includes receiving a request for an insight analysis for a dataset that includes a value dimension and a set of multiple date dimensions. Each date dimension is converted into a time series and a value quality factor is determined for each time series that represents a level of data quality for the time series. A time series informative factor is determined for each time series that represents how informative the time series is within a specified time window. An insight score is determined, for each time dimension, based on the determined value quality factors and the determined time series informative factors. The insight score for the time dimension is provided, for at least some of the time dimensions.

Abstract: Embodiments of a method and/or system can include administering, to a patient with one or more conditions associated with at least one of TMA, TMAO, and/or derivatives thereof, a therapeutically effective amount of a compound for affecting inhibiting one or more CutC enzymes and/or CntA enzymes associated with microorganisms from at least one taxon from a set of microorganism taxa.

Abstract: Damage to an object such as a vehicle may be detected and presented based at least in part on image data. In some configurations, image data may be detected by causing the object to pass through a gate or portal on which cameras are located. Alternatively, or additionally, image data may be selected by a user operating a camera and moving around the object. The cameras may capture image data, which may be combined and analyzed to detect damage. Some or all of the image data and/or analysis of the image data may be presented in a viewer, which may allow a user to perform actions such as navigating around the object in a virtual environment, identifying and viewing areas of the object where damage has been detected, and accessing the results of the analysis.

Abstract: A method for characterizing compatibility of a drug for a user includes collecting a set of samples from a set of individuals comprising a set of first individuals who respond to a therapy for a microbiome-related condition and a set of second individuals who do not respond to the therapy for the microbiome-related condition and determining one or more datasets based on the set of samples. A set of microbiome features is extracted from the one or more microbiome datasets, the microbiome features facilitating differentiation between individuals who respond and individuals who do not respond to the therapy. A companion diagnostics model is determined based on the set of microbiome features. The compatibility of the drug for the user is then determined using the companion diagnostics model.