Abstract: The present disclosure generally provides compositions and methods related to the field of immunology. Specifically, disclosed herein are chemokine binding proteins and methods of use thereof.

Abstract: A p-GaN high electron mobility transistor is disclosed. The p-GaN high electron mobility transistor includes a substrate, a channel layer located on the substrate, a supply layer laminated on the channel layer, and a doped layer laminated on the supply layer. A doping concentration of the doped layer is gradually distributed, in which the doping concentration in a first doped region close to the supply layer is lower than a doping concentration in a second doped region distant from the supply layer. A gate electrode is located on the doped layer. A source electrode and a drain electrode are respectively electrically connected to the channel layer and the supply layer.

Abstract: A GaN high electron mobility transistor is disclosed. The GaN high electron mobility transistor includes a substrate, a buffer layer located on the substrate, a barrier layer laminated on the buffer layer, a channel layer laminated on the barrier layer, a supply layer laminated on the channel layer. The barrier layer has either a p-type semiconductor or a wide band gap material. A gate electrode is located on the supply layer. A source electrode and a drain electrode are electrically connected to the channel layer and the supply layer.

Abstract: An automatic injection training device is presented having an elongated housing having a tubular demo container axially and rotationally fixed relative to the elongated housing and having a tubular wall, a reloadable plunger assembly having a plunger which is movable in the demo container between a first and a second position and a first energy accumulating member that moves the plunger from the first to the second position, an actuation assembly that holds the plunger in the first position, a biased needle cover that is movable in relation to the housing from an extended position to a retracted position and from the retracted position to the extended position, wherein the needle cover member interacts with the actuation assembly for releasing the plunger when the needle cover member is moved distally.

Abstract: Systems, methods, and computer readable media related to information retrieval. Some implementations are related to training and/or using a relevance model for information retrieval. The relevance model includes an input neural network model and a subsequent content neural network model. The input neural network model and the subsequent content neural network model can be separate, but trained and/or used cooperatively. The input neural network model and the subsequent content neural network model can be “separate” in that separate inputs are applied to the neural network models, and each of the neural network models is used to generate its own feature vector based on its applied input. A comparison of the feature vectors generated based on the separate network models can then be performed, where the comparison indicates relevance of the input applied to the input neural network model to the separate input applied to the subsequent content neural network model.

Abstract: A system may use a machine-learned model to determine whether to classify a sequence of one or more words within a first document that is being edited as a candidate hyperlink based at least in part on context associated with the first document. In response to classifying the sequence of one or more words as the candidate hyperlink, the system may use the machine-learned model and based at least in part on the sequence of one or more words and the context to determine one or more candidate document to be hyperlinked from the sequence of one or more words. In response to receiving an indication of a second document being selected out of the one or more candidate documents, the system may modify the first document to associate the sequence of one or more words with a hyperlink to the second document.

Abstract: A method includes loading a wafer into a processing chamber, wherein the processing chamber is wound by a coil, and the coil is coupled to an RF system; supplying an aromatic hydrocarbon precursor into the processing chamber; after supplying the aromatic hydrocarbon precursor, turning on an RF power of the RF system to decompose the aromatic hydrocarbon precursor into active radicals and cyclize the active radicals into a graphene layer over a metal layer on the wafer; and after an entirety of the metal layer being covered by the graphene layer, turning off the RF power of the RF system to stop forming the graphene layer.

Abstract: Systems, methods, and computer readable media related to information retrieval. Some implementations are related to training and/or using a relevance model for information retrieval. The relevance model includes an input neural network model and a subsequent content neural network model. The input neural network model and the subsequent content neural network model can be separate, but trained and/or used cooperatively. The input neural network model and the subsequent content neural network model can be “separate” in that separate inputs are applied to the neural network models, and each of the neural network models is used to generate its own feature vector based on its applied input. A comparison of the feature vectors generated based on the separate network models can then be performed, where the comparison indicates relevance of the input applied to the input neural network model to the separate input applied to the subsequent content neural network model.

Abstract: A robotic system is provided for assembling parts together. In the assembly process, both parts are moving separately with one part moving on an assembly base and another part moving on a moveable arm of a robot base. Motion data is measured by an inertial measurement (IMU) sensor. Movement of the robot base or moveable arm is then compensated based on the measured motion to align the first and second parts with each other and assemble the parts together.

Abstract: A robotic assembly operation is provided for assembling a second part to a first part. During setup of the assembly operation, control parameters and a control scheme are set and changed by simulating the operation and testing whether performance requirements are met. A dry run may be performed thereafter, and test data may be collected after running the simulation to determine if the performance requirements are satisfied during the dry run. During production, production data may also be collected and control parameters may be tuned when changes occur during production in order to maintain stable assembly.

Abstract: The present invention relates to an automatic injection training device comprising an elongated housing having a distal end and an opposite proximal end and extending along a longitudinally axis (L); a tubular demo container axially and rotationally fixed relative to the elongated housing and having a tubular wall extending along the longitudinally axis (L); a reloadable plunger assembly comprising a plunger rod which is movable in the demo container between a first and a second position and a first energy accumulating element configured to move the plunger rod from the first to the second position; an actuation assembly configured to hold the plunger rod in the first position and to release the plunger rod from the first position.

Abstract: A method for analyzing an electrocardiography (ECG) signal is provided. The ECG signal is measured through a sensor. One or more specified waveforms in the ECG signal are detected. Multiple ECG features from each specified waveform are captured. The ECG features are input into multiple candidate models to obtain multiple candidate scores. Each candidate score is compared with a standard value to obtain an ideal score among the candidate scores. One of the candidate models corresponding to the ideal score is selected as a risk prediction model to predict disease risk through the risk prediction model.

Abstract: The present invention relates to an automatic injection training device (10) comprising an elongated housing (12) having a distal end (14) and an opposite proximal end (16) and extending along a longitudinally axis (L); a tubular demo container (128) axially and rotationally fixed relative to the elongated housing (12) and having a tubular wall (140) extending along the longitudinally axis (L); a reloadable plunger assembly (104) comprising a plunger rod (106) which is movable in the demo container (128) between a first and a second position and a first energy accumulating element (110) configured to move the plunger rod (106) from the first to the second position; an actuation assembly (42) configured to hold the plunger rod (106) in the first position and to release the plunger rod (106) from the first position.

Abstract: The present invention discloses a method for detecting skin conditions, and the method includes the steps of: capturing a skin image from a suspected subject; decomposing the skin image into an RBX image through RBX color-space transformation; and determining skin condition of the subject according to a parameter of a color model of the RBX image.

Abstract: The present invention provides a driving circuit for a gamma voltage generator of a source driver. The gamma voltage generator includes a resistor string having a plurality of tap nodes, among which a plurality of first tap nodes are respectively connected to a plurality of first buffers. The driving circuit includes a second buffer, a digital-to-analog converter (DAC) and a control circuit. The second buffer is connected to a second tap node other than the plurality of first tap nodes among the plurality of tap nodes. The DAC is coupled to the second buffer. The control circuit, coupled to the DAC, is configured to receive a plurality of first control signals for the plurality of first buffers and calculate a second control signal for the DAC according to the plurality of first control signals.

Abstract: A method for acquiring shadow-free images of a document for scanning or other purposes is applied in a device. The method includes training a shadow prediction model based on sample documents of a sample library and inputting a background color and a shadow mask of each of the sample documents extracted by the shadow prediction model into a predetermined shadow removing network for training, to obtain a shadow removing model. The method further includes obtaining a background color and a shadow mask of the document through the shadow prediction model and removing the shadows of the document based on the shadow removing model. The device utilizing the method is also disclosed.

Abstract: A method for recognition of characters by optical means in an unclear or non-optimal image of an object document, the image carrying shadows or other impediments inputs the document into a shadow prediction model to obtain a shadow mask. A determination is made as to whether the shadow mask of the document affect an optical character recognition (OCR) performance. The method further inputs the document into a shadow removing model for removal of shadows to obtain an intermediate document if the shadow mask are deemed to affect the OCR performance, then OCR can then be performed on the final object document.

Abstract: A method includes loading a wafer into a processing chamber, wherein the processing chamber is wound by a coil, and the coil is coupled to an RF system; supplying an aromatic hydrocarbon precursor into the processing chamber; after supplying the aromatic hydrocarbon precursor, turning on an RF power of the RF system to decompose the aromatic hydrocarbon precursor into active radicals and cyclize the active radicals into a graphene layer over a metal layer on the wafer; and after an entirety of the metal layer being covered by the graphene layer, turning off the RF power of the RF system to stop forming the graphene layer.

Abstract: A system may use a machine-learned model to determine whether to classify a sequence of one or more words within a first document that is being edited as a candidate hyperlink based at least in part on context associated with the first document. In response to classifying the sequence of one or more words as the candidate hyperlink, the system may use the machine-learned model and based at least in part on the sequence of one or more words and the context to determine one or more candidate document to be hyperlinked from the sequence of one or more words. In response to receiving an indication of a second document being selected out of the one or more candidate documents, the system may modify the first document to associate the sequence of one or more words with a hyperlink to the second document.