Abstract: Provided are a cleaning agent composition for hard articles, a method for cleaning a hard article and a method for increasing foamability of a cleaning agent composition for hard articles, excellent in cleaning durability when cleaning hard articles with foam made by foaming the composition. A cleaning agent composition for hard articles containing, (a) a nonionic surfactant containing a polyoxyalkylene alkyl or alkenyl amine in which the alkyl group or alkenyl group has 8 or more and 18 or less carbons and the oxyalkylene group has an average number of added moles of 1 or more and 8 or less, (b) a quaternary ammonium salt-type surfactant, and water, wherein a content of (c) an anionic surfactant and an amphoteric surfactant is 0 mass % or more and 20 mass % or less in a total surfactant content.

Abstract: Provided herein are methods for image segmentation. An image having a plurality of pixels arranged in a plurality of dimensions is obtained. The image is provided to a pretrained machine learning model and a plurality of amplitudes for each of the plurality of pixel is received from the model. Each of the plurality of amplitudes for each of the plurality of pixels corresponds to exactly one of the plurality of dimensions.

Abstract: A cleaning agent composition containing, (a) a nonionic surfactant containing a polyoxyalkylene alkyl or alkenyl amine [hereinafter referred to as component (a1)] in which the alkyl group or alkenyl group has 8 or more and 18 or less carbons and the oxyalkylene group has an average number of added moles of 1 or more and 8 or less, (b) a quaternary ammonium salt-type surfactant [hereinafter referred to as component (b)], (c) a polycarboxylic acid or a salt thereof, and water, wherein a content of (d) an anionic surfactant [hereinafter referred to as component (d)] is less than 35 mass % relative to a total content of components (a1) and (b), and the content of component (d) is 20 mass % or less relative to a content of all surfactants. The cleaning composition has excellent cleaning power for oil stains and denatured oil stains, and in a method of cleaning such stains.

Abstract: A method of self-testing an imaging system of a sample handling apparatus is provided. Systems and non-transitory computer readable mediums performing the method are also provided.

Abstract: A method of self-testing an imaging system of a sample handling apparatus is provided. Systems and non-transitory computer readable mediums performing the method are also provided.

Abstract: Systems and methods for overlaying image data for a biological sample on spatial analyte data are provided. A first image of the sample on a first substrate and a second image of the sample on the first substrate overlayed on a second substrate are obtained. The second substrate includes spatial fiducials and capture spots. At least one of the first substrate and the second substrate is transparent. A registration for the first image and the second image is determined, using a first pattern of the sample in the first image and a second pattern of the sample in the second image. The registration is used to overlay the first image onto a spatial dataset including spatial analyte data for the capture spots from the sample. A frame of reference of the spatial dataset is known with respect to the second image, based on the spatial fiducials of the second image.

Abstract: Provided herein are methods, compositions and systems for identifying spatial gene expression of analytes from glioblastoma derived tissue. The methods discloses herein include using templated ligation probe pairs to identify location of a disease proliferating region in a glioblastoma-derived sample by detecting analytes in the region and hybridizing a ligation product comprising the probe pairs to a capture probe on a spatial array.

Abstract: Systems and methods for spatial analysis of analytes are provided. A data structure is obtained comprising an image, as an array of pixel values, of a sample on a substrate having intersecting border regions, fiducial markers encoding N-digit codes, and a set of capture spots, where at least two border regions includes a fiducial marker. The pixel values are analyzed to identify locations of fiducial markers. The locations are aligned with locations of reference fiducial markers in a template using an alignment algorithm to obtain a final transformation between the fiducial markers in the image and the reference fiducial markers in the template. The final transformation and a coordinate system of the template are used to register the image to the set of capture spots. The registered image is then analyzed in conjunction with spatial analyte data associated with each capture spot, thereby performing spatial analysis of analytes.

Abstract: Provided herein are systems and methods for optimizing feature fill processes. The feature fill optimization systems and methods may be used to optimize feature fill from a small number of patterned wafer tests. The systems and methods may be used for optimizing enhanced feature fill processes including those that include inhibition and/or etch operations along with deposition operations. Results from experiments may be used to calibrate a feature scale behavioral model. Once calibrated, parameter space may be iteratively explored to optimize the process.

Abstract: Provided herein are systems and methods for optimizing feature fill processes. The feature fill optimization systems and methods may be used to optimize feature fill from a small number of patterned wafer tests. The systems and methods may be used for optimizing enhanced feature fill processes including those that include inhibition and/or etch operations along with deposition operations. Results from experiments may be used to calibrate a feature scale behavioral model. Once calibrated, parameter space may be iteratively explored to optimize the process.