Abstract: A light emitting base plate and a fabricating method thereof, and a displaying device. In the present disclosure, a light shielding layer is provided on a substrate, a driving functional layer is provided on the light shielding layer, and a light-emitting-device layer and a light absorbing layer are provided on the driving functional layer; the light-emitting-device layer includes a plurality of light emitting devices, and the light absorbing layer includes light absorbing structures each of which surrounds sides of one of the light emitting devices; and the light absorbing structures are configured for blocking light rays exiting from the sides of the light emitting devices.

Abstract: Methods for quantitatively separating x-ray images of a subject having three or more component materials into component images using spectral imaging or multiple-energy imaging with 2D radiographic hardware implemented with scatter removal methods. The multiple-energy system may be extended by implementing DRC multiple energy decomposition and K-edge subtraction imaging methods.

Abstract: The present disclosure relates to the field of display technology, and proposes a display panel, a preparation method thereof, and a display apparatus. The display panel includes an array substrate, a planarization layer group, and a plurality of sub-pixels. The array substrate includes a switch array formed by a plurality of switch units. The planarization layer group is provided on the array substrate, and nano-scale grooves are provided on the planarization layer group. The sub-pixels are provided on a side of the planarization layer group away from the array substrate. The sub-pixel includes a plurality of first electrodes, wherein the first electrode is connected to the switch unit of the array substrate, a nano-scale second gap is provided between two adjacent first electrodes, and an orthographic projection of the second gap on the array substrate is located within an orthographic projection of the groove on the array substrate.

Abstract: A wireless headset includes a first headset part and a second headset part. The first headset part includes a first earplug, a battery box, and a first part of a cable control box. The first part of the cable control box includes a first interface, a first wireless chip configured to receive and send a wireless signal, and a processor configured to process the wireless signal. The battery box includes a first battery. The second headset part includes a second earplug and a second part of the cable control box, and the second part of the cable control box includes a second interface. The first interface is detachably connected to the second interface. When the first interface is electrically connected to the second interface, a data path is formed between the second earplug and the processor, and the first battery supplies power to the second earplug.

Abstract: The present disclosure provides a variable region sequence of a broad-spectrum antibody against clothianidin and dinotefuran, where a gene encoding a heavy chain variable region has an amino acid sequence shown in SEQ ID NO: 2. The present disclosure further discloses a broad-spectrum intact recombinant antibody against clothianidin and dinotefuran, including a heavy chain constant region, a heavy chain variable region, a light chain constant region, and a light chain variable region, where a gene encoding the heavy chain variable region has an amino acid sequence shown in SEQ ID NO: 2. The sequence genes obtained by the present disclosure are ligated to an expression vector containing a heavy chain constant region gene and a light chain constant region gene, respectively, and an intact recombinant antibody is expressed and obtained by using mammalian cells with a double-plasmid system.

Abstract: Optically isolated micromachined (MEMS) switches and related methods are described. The optically isolated MEMS switches described herein may be used to provide isolation between electronic devices. For example, the optically isolated MEMS switches of the types described herein can enable the use of separate grounds between the receiving electronic device and the control circuitry. Isolation of high-voltage signals and high-voltage power supplies can be achieved by using an optical isolator and a MEMS switch, where the optical isolator controls the state of the MEMS switch. In some embodiments, utilizing optical isolators to provide high voltages, the need for electric high-voltage sources such as high-voltage power supplies and charge pumps may be removed, thus removing the cause of potential damage to the receiving electronic device. In one example, the optical isolator and the MEMS switch may be co-packaged on the same substrate.

Abstract: A failure detection and correction module (FDCM) uses statistical measurement to detect failures in a distributed computing system caused by hardware, software, workflow, deployment, environmental factors, etc. in a component of the computing system, the computing system, or multiple computing systems and produces corrective actions. The FDCM identifies issues from various components, correlates the estimated failures in each level of components and rolls up failures and estimated failures from each level of components to system level estimations of failures, reevaluates the system reliability factors, readjusts the system reliability and system functions from the adjusted reliability factors, and produces intelligent corrective actions to improve both system reliability and the system efficiency. Corrective action includes changing slice storing parameters and rebuild priorities on a dispersed storage system.

Abstract: A method and apparatus for generating a model, and a method and apparatus for recognizing information are provided. An implementation of the method for generating a model includes: acquiring a to-be-converted model, a topology description of the to-be-converted model, and device information of a target device; converting, based on the topology description and the device information, parameters and operators of the to-be-converted model to obtain a converted model applicable to the target device; and generating a deep learning prediction model based on the converted model. This embodiment enables the conversion of an existing model to a deep learning prediction model that can be applied to a target device.

Abstract: The present application relates to display panel. An opening area of any one of sub-pixels of the first transitional display region is larger than an opening area of a same-colored sub-pixel of the first display region and is smaller than an opening area of a same-colored sub-pixel of the second display region. An interval between any two closest sub-pixels of a same color arranged in adjacent columns in the first display region is x; an interval between any two closest sub-pixels of a same color arranged in two adjacent columns respectively in the first transitional display region and the second display region is y; an interval between any two closest sub-pixels of a same color arranged in two adjacent columns in the second display region is z, wherein x?y?z. The present application also provides a display device.

Abstract: A photosensitive sensor, a preparation method thereof, and an electronic device, wherein the photosensitive sensor includes a substrate, the substrate having a sensing area, a plurality of regularly arranged sensing units being provided in the sensing area, a shielding layer being provided on a side of the sensing units away from the substrate, the shielding layer covering the sensing area, a material of the shielding layer being a transparent conductive material, and the shielding layer being connected with a constant voltage signal terminal.

Abstract: Disclosed is a visual imaging device based on PS-OCT for early demineralization and caries of dental hard tissues, comprising a laser light source for emitting a laser light, a coupler for receiving and dividing the laser light emitted by the laser light source into a reference laser light and a detection laser light; wherein the reference laser light backtracking to the coupler and the detection laser light backtracking to the coupler are coupled and then passed through a transmission grating and a convex lens to input as an optical signal into a linear CCD detector for converting the optical signal into an electrical signal which is then input to a computer control system and collected by a built-in capture card; and the computer is configured to perform a three-dimensional reconstruction of an image and perform two-dimensional cross-section image analysis; and the computer control system is connected to the scanning galvanometer to control a vibration of the scanning galvanometer.

Abstract: The present disclosure provides a method of treating NAFLD, NASH, and atherosclerosis, comprising administering glycine-containing tripeptide molecule, or a pharmaceutically acceptable salt thereof to a subject.

Abstract: A method includes: receiving, by a computing device, input defining a custom storage class in a first dispersed storage network; receiving, by the computing device, input defining a data management rule in the first dispersed storage network; determining, by the computing device, a data object in the first dispersed storage network satisfies the data management rule; and moving, by the computing device and in response to the determining, the data object to a second dispersed storage network according to the custom storage class.

Abstract: A code completion system predicts candidates to complete a method invocation in a source code program written in a dynamically-typed programming language. A pseudo type is generated for each variable in the source code program to approximate the runtime type of the variable. The pseudo type is then used to group a set of method invocations into a classification that can be modeled by an n-order Markov chain model. The n-order Markov chain model is used to predict candidate methods more likely to complete a method invocation in a dynamically-typed programming language.

Abstract: A code completion tool uses a deep learning model to predict the likelihood of a method completing a method invocation. In one aspect, the deep learning model is a LSTM trained on features that represent the syntactic context of a method invocation derived from an abstract tree representation of the code fragment.

Abstract: An x-ray apparatus and method can improve x-ray imaging in a variety of ways. For example, the improve x-ray apparatus can reduce scatter from x-ray images acquired by two-dimensional detectors. An improved 2D x-ray apparatus can provide 3D imaging for medical and/or industrial applications. An improved 2D x-ray apparatus and method can produce separate material imaging, and composition analysis for characterization and correlation of image, densitometry, and composition information of individual component or individual material within a single subject. Non-rotational 3D microscopy, combining 2D or 3D full field x-ray imaging and high resolution 2D or 3D x-ray microscopy or spectral absorptiometry and spectroscopy can achieve a higher resolution and wider field of view in x-ray imaging and quantitative analysis in 3D and real time. The x-ray apparatus can improve tracking and/or surgical guidance in time and/or space.

Abstract: Provided are a method for transmitting voice data, a wireless headset and a TWS headset. In the method, a first wireless headset establishes a communication connection with a terminal through first connection parameter information, and a second wireless headset receives an instruction to continue transmitting voice data, wherein the instruction to continue transmitting voice data is an instruction generated after detecting a preset event indicating that the first wireless headset is about to interrupt transmission of voice data; and transmitting, by the second wireless headset, the voice data collected by the MIC of the second wireless headset to the terminal through the first connection parameter information sent by the first wireless headset.

Abstract: A failure detection and correction module (FDCM) uses statistical measurement to detect failures in a distributed computing system caused by hardware, software, workflow, deployment, environmental factors, etc. in a component of the computing system, the computing system, or multiple computing systems and produces corrective actions. The FDCM identifies issues from various components, correlates the estimated failures in each level of components and rolls up failures and estimated failures from each level of components to system level estimations of failures, reevaluates the system reliability factors, readjusts the system reliability and system functions from the adjusted reliability factors, and produces intelligent corrective actions to improve both system reliability and the system efficiency. Corrective action includes changing slice storing parameters and rebuild priorities on a dispersed storage system.