Abstract: The present application provides a compound dry powder inhalant, comprising baicalin, ambroxol hydrochloride, L-leucine and phosphate, wherein based on a mass of the compound dry powder inhalant, L-leucine accounts for 0-50%, phosphate accounts for 15-35%, and a total mass of baicalin and ambroxol hydrochloride accounts for 15-85%, and wherein a mass ratio of baicalin to ambroxol hydrochloride is 1:0.2 to 2. The compound dry powder inhalant has a Dv90?5 ?m. The drug combination of baicalin and ambroxol hydrochloride can effectively reduce inflammation and oxidative damage in lung tissue, alleviate pulmonary edema and histopathological changes, and reduce pulmonary dysfunction and pulmonary fibrosis.

Abstract: The present invention relates to human CCR8 (hCCR8) binders, wherein the hCCR8 binder is cross-reactive with a non-human primate CCR8. Such binders are particularly useful for the depletion of intra-tumoural regulatory T-cells and immunotherapy in general.

Abstract: The present invention relates to human CCR8 (hCCR8) binders, wherein the hCCR8 binder is cross-reactive with murine CCR8. Such binders are particularly useful for the depletion of intra-tumoural regulatory T-cells and immunotherapy in general.

Abstract: The present invention relates to human CCR8 (hCCR8) binders, wherein the hCCR8 binder is a non-blocking binder of hCCR8.

Abstract: The present invention generally provides, in various embodiments, methods of generating tagged DNA amplicons for sequencing. In one embodiment, the method comprises a) annealing a first oligonucleotide to a nucleic acid template comprising a target nucleic acid molecule sequence and a tag sequence, wherein the target nucleic acid molecule sequence comprises a locus of interest; b) performing nucleic acid template-directed nucleic acid extension from the annealed first oligonucleotide to provide a first extension product; c) circularizing the first extension product to produce a circularized DNA template; and d) performing circularized DNA template-directed nucleic acid amplification to produce a tagged DNA amplicon for sequencing. The methods are useful for linking a distant locus-of-interest to a reverse transcription primer.

Abstract: Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.

Abstract: Disclosed are methods and systems for characterizing and analyzing an electronic system design including a parallel interface. Some methods and systems identify an electronic design including a parallel interface, determine a single circuit representation including the parallel interface from the electronic design, and analyze the parallel interface to determine waveform responses of the parallel interface by using channel analysis techniques without performing circuit simulations.

Abstract: The present invention discloses a method and an apparatus for measuring a posture angle of an object. The method comprises the following steps: arranging a sensor in a measured object, the sensor being used for measuring characteristic quantities of magnetic field in three dimensional directions; actuating the sensor at the beginning of the measurement, and acquiring, by using the sensor, a current measured value of the characteristic quantity of magnetic field of the measured object in a carrier coordinate system; acquiring reference values of the characteristic quantities of magnetic field of the measured object in a geographic coordinate system; and calculating a current posture angle of the measured object according to numerical values of the characteristic quantities of magnetic field indicated by the reference value and the measured value in each direction respectively.

Abstract: Disclosed is a search system, method and apparatus. A click operation in a search frame is detected. In response to a click operation is detected, a control corresponding to the click operation is determined, the control comprising a text input control and an image input control that are preset in the search frame. The clicked control in the search frame according to the control corresponding to the click operation is enabled, and an unclicked control is concealed. Information for search through the enabled control is received, the information for search comprises a text for search or an image for search. The received information for search is sent to a server, so that the server carries out searching based on the information for search, to obtain an image search result.

Abstract: Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.

Abstract: Embodiments include herein are directed towards a method for electronic circuit design. Embodiments may include displaying, at a graphical user interface, an electronic circuit design topology environment and allowing a user to select, create, or modify an entirely single pin topology, an entirely multi-pin topology, or a combination of a single pin topology and a multi-pin topology for one or more portions of the electronic circuit design topology environment. Embodiments may also include receiving a selection of a designated portion of the electronic circuit design topology environment and generating, at the graphical user interface, a first, pin-adjustable symbol in accordance with the selected topology at the designated portion.

Abstract: The present disclosure relates to non-linear systems associated with an electronic circuit design. Embodiments may include identifying the non-linear system associated with the electronic circuit design and determining a degree of severity of non-linearity of the non-linear system associated with the electronic circuit design. If the degree of severity is less than a predefined threshold, embodiments may further include receiving a random input pattern and deriving a single impulse response characterization, wherein the random input pattern is based upon, at least in part, an electronic circuit simulation associated with the electronic circuit design.

Abstract: The present disclosure discloses a search method and apparatus. A specific implementation of the method comprises: receiving first information for searching, the first information for searching comprising an image for searching; determining an image attribute tag selected by a selection operation as being second information for searching in response to detecting the selection operation of the preset image attribute tag, the image attribute tag being used for indicating an attribute of the image; sending the received first information for searching and the determined second information for searching to a server, so that the server conducts a search according to the first information for searching and the second information for searching to obtain and send a first image search result; and receiving and displaying the first image search result sent by the server. This implementation improves the search efficiency.

Abstract: The invention provides a bus-bar assembly, a power battery over-load protection system and method, as well as a power battery assembly, wherein the bus-bar assembly comprises a first connection arm having one or more connection ends so as to be connected to an upstream battery cell; a second connection arm having one or more connection ends so as to be connected to a downstream battery cell; and a PTC unit connected between the first connection arm and the second connection arm. The bus-bar assembly, the over-load protection system, the power battery assembly and the vehicle or the like according to the invention has better safety and stability.

Abstract: Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.

Abstract: Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.

Abstract: The present disclosure relates to a computer-implemented method for use in an electronic design. Embodiments may include receiving, using at least one processor, an electronic design and linking a printed circuit board (PCB) block to a physical layout associated with the electronic design. Embodiments may further include receiving, at a layout environment, at least one simulation parameter and performing, using a finite difference time domain (“FDTD”) simulator, a time-domain simulation, based upon, at least in part, the at least one simulation parameter.

Abstract: The present disclosure discloses a searching method and apparatus. A specific embodiment of the searching method comprises: receiving a search request sent by a client, the search request including a target picture; analyzing the target picture to extract text information and an image characteristic; matching the text information with text information of each preset picture in a preset picture set to determine a first similarity, matching the image characteristic with an image characteristic of the preset picture in response to the first similarity greater than a first preset threshold, and determining whether the preset picture is determined as an identical picture based on matching results; and acquiring associated information of the identical picture, sending the identical picture and the associated information as a search result to the client to be displayed on the client. The present embodiment improves the search efficiency and reduces the labor cost of the search.

Abstract: Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.

Abstract: Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.