Abstract: The present application discloses a multifunctional iron frame and seat, including a driving mechanism, a leg support mechanism, and a linkage mechanism. The leg support mechanism includes a leg support skeleton and a support plate. The linkage mechanism is connected between the driving mechanism and the leg support skeleton. When the multifunctional iron frame is rotated from a sitting state to a first position, the leg support skeleton rotates relative to the seat frame, and a rotation radius of the support plate at the first position is not greater than in the sitting state. When the multifunctional iron frame is rotated from the first position to a lying state, the leg support skeleton rotates relative to the seat frame and the support plate slides relative to the leg support skeleton. The rotation radius of the support plate in the first position is smaller than that in the lying state.

Abstract: Disclosed is an intelligent monitoring method for soil moisture status based on remote sensing technology, including the following steps: dividing a monitoring region into a plurality of sub-regions by a processing end, acquiring image data of various sub-regions on the basis of remote sensing satellites, acquiring multi-source data related to soil moisture status of the monitoring region on the basis of sensor devices, and pre-processing the image data and the multi-source data; comprehensively analyzing the image data and the multi-source data, and assessing soil moisture status of the various sub-regions; and comprehensively analyzing overall soil moisture status of the monitoring region according to the soil moisture status of the various sub-regions. The soil moisture status of the monitoring region is assessed after the multi-source data is comprehensively analyzed by the monitoring method, bringing about a more comprehensive and accurate analysis.

Abstract: Apparatuses and methods for dental image analysis including determining pixel sizes of an image. A pixel size enables conversion of a two-dimension image-based measurement into a 3D measurement. The pixel sizes vary over the image due to differences in distance between the camera taking the image and the object of interest. A three-dimensional model may be registering to the two-dimension image, and the pixel sizes may be identified on a per-object (e.g., per-tooth) basis, per-region basis or at each point in the image. The pixel size scaling may be used to identify features in the image for diagnostic or other dental application purposes.

Abstract: Provided are a new compound as represented by formula (I) having a dual antagonistic effect of an angiotensin II receptor and an endothelin receptor, and the use thereof in the preparation of a drug.

Abstract: Systems and methods of simulating dental treatments are disclosed. A method may include capturing a first 2D image of a patient's face, including the patient's teeth, building a parametric 3D model of the patient's teeth and gingiva based on the first 2D image, developing a simulated outcome of a dental treatment of the patient's teeth by rendering the parametric 3D model with the patient's teeth in one or more positions and/or orientations corresponding to the treatment goals of the dental treatment plan, and rendering a second 2D image of the patient's face with gingiva and teeth according to a simulated outcome of the dental treatment plan. As noted herein, the dental treatment plan may include orthodontic and/or restorative elements. The simulated outcome may correspond to estimated outcomes and/or intended outcomes of the dental treatment plan.

Abstract: Described herein is are compositions and methods for treating an articulating joint disorders, comprising systemically administering to a subject a nucleoside reverse transcriptase inhibitor (NRTI).

Abstract: Systems and methods of simulating dental treatments are disclosed. A method may include capturing a first 2D image of a patient's face, including the patient's teeth, building a parametric 3D model of the patient's teeth and gingiva based on the first 2D image, developing a simulated outcome of a dental treatment of the patient's teeth by rendering the parametric 3D model with the patient's teeth in one or more positions and/or orientations corresponding to the treatment goals of the dental treatment plan, and rendering a second 2D image of the patient's face with gingiva and teeth according to a simulated outcome of the dental treatment plan. As noted herein, the dental treatment plan may include orthodontic and/or restorative elements. The simulated outcome may correspond to estimated outcomes and/or intended outcomes of the dental treatment plan.

Abstract: Provided is an amorphous silicon thin-film transistor including an amorphous silicon semiconductor layer, a source electrode, and a drain electrode that are successively disposed on a base substrate. Ions doped by an ion implantation process are present in a region, proximal to the source electrode and the drain electrode, of the amorphous silicon semiconductor layer. A concentration of the ions in a surface region, proximal to the source electrode and the drain electrode, of the amorphous silicon semiconductor layer is greater than or equal to 5*10{circumflex over (?)}20 atoms/cc.

Abstract: A method for treatment-based photo guidance may include receiving a treatment plan, determining the movement of a first one or more teeth based on the movement of tooth models in the treatment plan, and determining one or more photo views for capturing the movement of the first one or more teeth.

Abstract: A method for dental treatment may include receiving photos of a patient's dentition, gathering treatment parameters for at treatment plan. The treatment parameters may represent attributes of the treatment plan selected by a doctor for the patient's dentition of a patient. The method may include generating, using the photos and the treatment parameters, one or more intelligent guidance rules to guide application of at least a portion of the treatment parameters to the patient's dentition, generating instructions to apply the intelligent patient guidance rules to the patient's dentition, and providing the instructions to the patient to apply the at least a portion of the treatment plan in accordance with the intelligent patient guidance rules.

Abstract: A method for image-based orthodontic treatment may include receiving image data of a patient's dentition and an orthodontic appliance, identifying, from the image data, the orthodontic appliance, calculating a misalignment height of a misalignment of the orthodontic appliance with respect to the patient's dentition, determining whether the misalignment height satisfies a misalignment threshold, and in response to satisfying the misalignment threshold, providing a notification.

Abstract: A method of dental treatment may include receiving photos of a person's dentition, identifying a stage of a treatment plan administered to the person's dentition, gathering a three-dimensional (3D) model of the person's dentition corresponding to the stage of the treatment plan, projecting attributes of the 3D model of the person's dentition onto an image plane to get a projected representation of the person's dentition at the stage of the treatment plan, comparing the photos to the projected representation to derive an error image representing the comparison, and analyzing the error image for discrepancies, wherein the discrepancies represent one or more deviations of the person's dentition from the stage of the treatment plan.

Abstract: Methods, apparatuses, and systems are disclosed for simulating a tooth whitening procedure. The simulation may generally obtain a patient's two-dimensional or three-dimensional dental scan and color space convert color information from a first or native color space to a color space based on an International Commission on Illumination color space (CIELAB). The simulation may include modifying color information in the CIELAB color space then returning the modified color information to the native color space.

Abstract: An item recall method includes: behavior data is acquired, where the behavior data includes items and item information of each item; target behavior data containing a retrieval category word is extracted from the behavior data; retrieval words of each item and a retrieval frequency of each retrieval word are acquired in a reverse correlation manner; word segmentation is performed on the item information to obtain multiple item segmented words; a similarity between all retrieval words and the multiple item segmented words is calculated; whether the similarity is greater than a first preset threshold or not is determined, and if yes, then a retrieval word is extracted as an expansion word of the retrieval category word; and item recall is performed according to the retrieval category word and the expansion word.

Abstract: Methods and apparatuses (including systems and devices), including computer-implemented methods for segmenting, correcting and/or modifying a three-dimensional (3D) model of a subject's oral cavity to determine individual components such as teeth, gingiva, tongue, palate, etc., that may be selective and/or collectively digitally manipulated. In some implementations, artificial intelligence uses libraries of labeled 2D images and 3D dental models to learn how to segment a 3D dental model of a subject's oral cavity using 2D images, height map and/or other data and projection values that relate the 2D images to the 3D model. As noted herein, the dental classes can include a variety of intra-oral and extra-oral objects and can be represented as binary values, discrete values, a continuum of height map data, etc. In some implementations, several dental classes are predicted concurrently.

Abstract: A method includes determining depth values associated with a first set of pixel locations in a first image of a mouth. One or more function is generated for one or more color channels based on intensities of the one or more color channels at the first set of pixel locations and depth values associated with the first set of pixel locations. Image data comprising a new representation of the teeth is received, wherein the image data comprises a second set of pixel locations and new depth values associated with the second set of pixel locations. A new image is generated based on the image data and the one or more functions.

Abstract: The present disclosure provides a method of treating cancer in a subject in need thereof comprising administering a therapeutically effective amount of a MALT-1 inhibitor to the subject; optionally in combination with a checkpoint inhibitor, wherein the MALT-1 inhibitor is administered at a continuous daily dose over a treatment cycle.

Abstract: Systems and methods of simulating dental treatments are disclosed. A method may include capturing a first 2D image of a patient's face, including the patient's teeth, building a parametric 3D model of the patient's teeth and gingiva based on the first 2D image, developing a simulated outcome of a dental treatment of the patient's teeth by rendering the parametric 3D model with the patient's teeth in one or more positions and/or orientations corresponding to the treatment goals of the dental treatment plan, and rendering a second 2D image of the patient's face with gingiva and teeth according to a simulated outcome of the dental treatment plan. As noted herein, the dental treatment plan may include orthodontic and/or restorative elements. The simulated outcome may correspond to estimated outcomes and/or intended outcomes of the dental treatment plan.

Abstract: A method for dental treatment may include receiving photos capturing a state of a patient's dentition of a patient at a specific time, retrieving a first treatment plan to treat the patient's dentition, identifying an intended arrangement of the first treatment plan at the specific time, evaluating the photo parameters of the photos to generate alignment data to align the intended arrangement of the first treatment plan and the photos, generating an alignment mesh using the alignment data, the alignment mesh comprising a three-dimensional (3D) mesh representation of the patient's dentition at the specific time, performing an evaluation of the first treatment plan for modifications using the alignment mesh, and identifying proposed modifications to the first treatment plan based on the evaluation.