Abstract: Provided herein are pharmaceutical compositions comprising a substantially amorphous form of 6-(4-((5-cyclopropyl-3-(2,6-dichlorophenyl)isoxazol-4-yl)methoxy)piperidin-1-yl)-1-methyl-1H-indole-3-carboxylic acid, such as solid dispersions of 6-(4-((5-cyclopropyl-3-(2,6-dichlorophenyl)isoxazol-4-yl)methoxy)piperidin-1-yl)-1-methyl-1H-indole-3-carboxylic acid; methods of preparation thereof, and methods of use thereof.

Abstract: Embodiments of the application provide a display panel, a display screen and a display device. The display panel includes a backplane, a color filter layer, and a black matrix between the backplane and the color filter layer. The backplane includes a base substrate, the color filter layer includes a plurality of sub-pixel color filters, and the plurality of sub-pixel color filters are arranged along a plane of the color filter layer and spliced together to form the color filter layer.

Abstract: A spiral bristle (201) includes: a first component (231), a second component (233), and a third component (235), with each of the second and third components (233, 235) wrapping around the first component (231) in a helical and spaced-apart manner, the second and third components (233, 235) isolated from one another by the first component (231). An oral care implement includes the spiral bristle.

Abstract: Embodiments of the present disclosure provide a method and apparatus of training a model, an electronic device, a storage medium and a development system, which relate to a field of deep learning. The method may include calling a training preparation component to set at least a loss function and an optimization function for training the model, in response to determining that a training preparation instruction is received. The method further includes calling a training component to set a first data reading component, in response to determining that a training instruction is received. The first data reading component is configured to load a training data set for training the model. In addition, the method may further include training the model based on the training data set from the first data reading component, by using the loss function and the optimization function through the training component.

Abstract: An interface card cage includes a first assembly and a second assembly. The first assembly includes a first side wall, a second side wall, and a bent portion. The second side wall has an opening. The bent portion and the first side wall extend in different directions. The bent portion includes a protrusion extending from the bent portion. The second assembly includes an assembly part having a slot. The assembly part includes a first side plate and a second side plate. The first side plate has a recess. The assembly part has a first edge and a second edge. A direction from the first edge to the second edge is different from a direction from the first side plate to the second side plate. The bent portion of the first assembly is located in the slot. The protrusion is located in the recess.

Abstract: The disclosure provides an expansion card cage including a cage, a latch and a fastener. The cage includes a back plate, a first mount plate, and a second mount plate. The back plate has two surfaces opposite to each other and two openings. The first mount plate and the second mount plate respectively protrude from the two surfaces of the back plate. The first mount plate is configured for an installation of a riser card configured for an insertion of an expansion card. The openings of the back plate are configured to expose the expansion card. The second mount plate has a fixation hole. The latch has a through hole. The fastener is disposed through the through hole of the latch and fixed in the fixation hole of the second mount plate so as to force the latch to press against a tab portion of the expansion card.

Abstract: Gene expression signature predictive of cancer patient response to multi-kinase inhibitor is disclosed. Also disclosed are methods predicting the efficacy of the multi-kinase inhibitor for treating cancer in a patient. Also disclosed are methods for distinguishing responders from non-responders to a multi-kinase inhibitor in treating cancer. Also disclosed are methods for treating a cancer patient with a multi-kinase inhibitor.

Abstract: A method of cleaning a chamber for an electronics manufacturing system includes flowing a gas mixture comprising oxygen and a carrier gas into a remote plasma generator. The method further includes generating a plasma from the gas mixture by the remote plasma generator and performing a remote plasma cleaning of the chamber by flowing the plasma into an interior of the chamber, wherein the plasma removes a plurality of organic contaminants from the chamber.

Abstract: The disclosure provides methods and compositions, e.g., kits, for identifying or authenticating a sample, e.g., a tumor model, based on the genotype of the sample at a group of SNP loci.

Abstract: The disclosure provides including a casing, a mother board, a hard disk drive module, a fan module, and an expansion module. The casing has a hard disk drive accommodation area, a fan accommodation area, and a motherboard accommodation area located between the hard disk drive accommodation area and the fan accommodation area. The motherboard is disposed in the motherboard accommodation area. The hard disk drive module includes hard disk drives. The fan module includes fans. The expansion module is selectively disposed in the hard disk drive accommodation area with the hard disk drives, or disposed in the fan accommodation area with the fans.

Abstract: This disclosure includes technologies for video recognition in general. The disclosed system can automatically detect various types of actions in a video, including reportable actions that cause shrinkage in a practical application for loss prevention in the retail industry. The temporal evolution of spatio-temporal features in the video are used for action recognition. Such features may be learned via a 4D convolutional operation, which is adapted to model low-level features based on a residual 4D block. Further, appropriate responses may be invoked if a reportable action is recognized.

Abstract: This disclosure includes technologies for action recognition in general. The disclosed system may automatically detect various types of actions in a video, including reportable actions that cause shrinkage in a practical application for loss prevention in the retail industry. Further, appropriate responses may be invoked if a reportable action is recognized. In some embodiments, a three-branch architecture may be used in a machine learning model for action and/or activity recognition. The three-branch architecture may include a main branch for action recognition, an auxiliary branch for learning/identifying an actor (e.g., human parsing) related to an action, and an auxiliary branch for learning/identifying a scene related to an action. In this three-branch architecture, the knowledge of the actor and the scene may be integrated in two different levels for action and/or activity recognition.

Abstract: An oral care implement including an elongated body having a head portion supporting plurality of tooth cleaning elements and a handle portion defining an outer surface. A grip control component is disposed on the handle portion and includes a pair of transversely spaced apart control surfaces separated by a longitudinally extending channel. The control surfaces are elevated above the outer surface of the handle portion and positioned to engage a user's thumb. The control component is operable to tilt the head portion at an upward or downward angle relative to a vertical plane of a user's teeth when the control component is grasped between the user's thumb and forefinger for producing a proper brushing angle at the gum line.

Abstract: Methods and systems for training machine vision models (MVMs) with “noisy” training datasets are described. A noisy set of images is received, where labels for some of the images are “noisy” and/or incorrect. A progressively-sequenced learning curriculum is designed for the noisy dataset, where the images that are easiest to learn machine-vision knowledge from are sequenced near the beginning of the curriculum and images that are harder to learn machine-vision knowledge from are sequenced later in the curriculum. An MVM is trained via providing the sequenced curriculum to a supervised learning method, so that the MVM learns from the easiest examples first and the harder training examples later, i.e., the MVM progressively accumulates knowledge from simplest to most complex. To sequence the curriculum, the training images are embedded in a feature space and the “complexity” of each image is determined via density distributions and clusters in the feature space.

Abstract: An optical plate includes at least two first optical portions for respectively covering two light emitting modules, and at least one second optical portion for covering a gap between the light emitting modules. Each first optical portion receives light rays emitted from a respective light emitting module and causes the same to emit along a predetermined direction. The second optical portion has first and second inner inclined surfaces, and first and second outer inclined surfaces. The inner inclined surfaces guide the light rays emitted from the respective light emitting modules toward the outer inclined surfaces, respectively, such that the light rays emitting out therefrom are parallel to the predetermined direction.

Abstract: Disclosed are a method of forming a plasma coating on a component, an apparatus for forming the coating, a component, and a processing apparatus; the apparatus for forming the coating includes: a vacuum chamber; a first coating material source, a second coating material source, and a component, which are disposed in the vacuum chamber; wherein the first coating material source includes oxygen atoms and yttrium atoms, and the second coating material source includes one of yttrium fluoride, aluminum-oxygen compound, or zirconium-oxygen compound; a first exciting device configured for exciting out the yttrium atoms and oxygen atoms from within the first coating material source; a second exciting device configured for exciting out atoms from within the second coating material source; wherein collision of the yttrium atoms and oxygen atoms excited out of the first coating material source and the atoms excited out of the second coating material source produces a chemical reaction to form on the component a plasma r

Abstract: An oral care implement including an elongated body having a head portion supporting plurality of tooth cleaning elements and a handle portion defining an outer surface. A grip control component is disposed on the handle portion and includes a pair of transversely spaced apart control surfaces separated by a longitudinally extending channel. The control surfaces are elevated above the outer surface of the handle portion and positioned to engage a user's thumb. The control component is operable to tilt the head portion at an upward or downward angle relative to a vertical plane of a user's teeth when the control component is grasped between the user's thumb and forefinger for producing a proper brushing angle at the gum line.

Abstract: Methods and systems for training machine vision models (MVMs) with “noisy” training datasets are described. A noisy set of images is received, where labels for some of the images are “noisy” and/or incorrect. A progressively-sequenced learning curriculum is designed for the noisy dataset, where the images that are easiest to learn machine-vision knowledge from are sequenced near the beginning of the curriculum and images that are harder to learn machine-vision knowledge from are sequenced later in the curriculum. An MVM is trained via providing the sequenced curriculum to a supervised learning method, so that the MVM learns from the easiest examples first and the harder training examples later, i.e., the MVM progressively accumulates knowledge from simplest to most complex. To sequence the curriculum, the training images are embedded in a feature space and the “complexity” of each image is determined via density distributions and clusters in the feature space.

Abstract: Aspects of this disclosure include technologies for detecting irregular scans, specifically when a retail system fails to collect the genuine information of a product. The disclosed retail system retrieves images covering a specific region, e.g., the designated scanning area. Further the disclosed retail system uses neural networks to detect the product from such images and track a moving path of the product over the specific region. Irregular scans may be detected when the tracked product in the images does not match what is collected by the scanner of the retail system.

Abstract: Provided in the disclosure relates to a panel of gene expression markers for cancer patient treated or to be treated by karenitecin. The disclosure provides methods and compositions, e.g., kits, for evaluating gene expression levels of the markers and methods of using such gene expression levels to predict a cancer patient's response to karenitecin. Such information can be used in determining prognosis and treatment options for cancer patients.