Abstract: A fuel tank cap includes a seal cap body and a detaching-proof unit. The cap body has a handheld wall and a surrounding wall that extends from the handheld wall and that is formed with an engaging groove. The detaching-proof unit includes a ring sleeve member and a connection member. The ring sleeve member has an outer ring wall that surrounds the surrounding wall, and a resilient wall that extends the outer ring wall and that is engaged resiliently with the engaging groove. The connection member is connected to the ring sleeve member to be connected to a cap installation portion of a vehicle body.

Abstract: A method includes placing a wafer on a wafer holder, depositing a film on a front surface of the wafer, and blowing a gas through ports in a redistributor onto a back surface of the wafer at a same time the deposition is performed. The gas is selected from a group consisting of nitrogen (N2), He, Ne, and combinations thereof.

Abstract: A method includes forming a device region over a substrate; forming a first dielectric layer over the device region; forming an opening in the first dielectric layer; conformally depositing a first conductive material along sidewalls and bottom surfaces of the opening; depositing a second conductive material on the first conductive material to fill the opening, wherein the second conductive material is different from the first conductive material; and performing a first thermal process to form an interface region extending from a first region of the first conductive material to a second region of the second conductive material, wherein the interface region includes a homogeneous mixture of the first conductive material and the second conductive material.

Abstract: Provided are human polyclonal immunoglobulin products for use in treating or preventing coronavirus disease. Further provided are methods for making such compositions in a transgenic ungulate, e.g. using a transchromosomic bovine (TcB) system.

Abstract: The present disclosure provides embodiments of semiconductor devices. In one embodiment, the semiconductor device includes a dielectric layer and a fin-shaped structure disposed over the dielectric layer. The fin-shaped structure includes a first p-type doped region, a second p-type doped region, and a third p-type doped region, and a first n-type doped region, a second n-type doped region, and a third n-type doped region interleaving the first p-type doped region, the second p-type doped region, and the third p-type doped region. The first p-type doped region, the third p-type doped region and the third n-type doped region are electrically coupled to a first potential. The second p-type doped region, the first n-type doped region and the second n-type doped region are electrically coupled to a second potential different from the first potential.

Abstract: Creating data warehouse views for input tables including: selecting, by a workbook manager, a subset of columns of an input table stored in a cloud-based data warehouse, wherein the subset of columns excludes one or more metadata columns of the input table; generating, by the workbook manager, a view of the input table based on the subset of columns; and storing, by the workbook manager, the view of the input table in the cloud-based data warehouse.

Abstract: The present application provides a method of training a natural language processing model, which relates to a field of artificial intelligence, and in particular to a field of natural language processing. A specific implementation scheme includes: performing a semantic learning for multi-tasks on an input text, so as to obtain a semantic feature for the multi-tasks, wherein the multi-tasks include a plurality of branch tasks; performing a feature learning for each branch task based on the semantic feature, so as to obtain a first output result for each branch task; calculating a loss for each branch task according to the first output result for the branch task; and adjusting a parameter of the natural language processing model according to the loss for each branch task. The present application further provides a method of processing a natural language, an electronic device, and a storage medium.

Abstract: A method and apparatus for training a question solving model, a question solving method and apparatus, an electronic device and a readable storage medium are disclosed. The method for training a question solving model includes: acquiring a first sample question; inputting the first sample question and a solving step grabbing template into a large language model to obtain a first sample solving step; inputting the first sample question, the first sample solving step and an answer grabbing template into the large language model to obtain a first sample answer; pre-training a step planning model according to the first sample question and the first sample solving step; pre-training the large language model according to the first sample question, the first sample solving step and the first sample answer; and acquiring the question solving model according to the step planning model and the large language model obtained by pre-training.

Abstract: A battery includes an electrode plate assembly. An electrode plate assembly includes an electrode plate and a conduction element. The electrode plate includes a current collector. The current collector includes a first conductive material layer, an insulating material layer, and a second conductive material layer. The current collector is provided with a through opening. The conduction element includes a first conduction part, a second conduction part, and a third conduction part. The first conduction part is disposed on a first side of the current collector and electrically connected to the first conductive material layer. The second conduction part is disposed on a second side of the current collector and electrically connected to the second conductive material layer. The third conduction part is disposed at the through opening and electrically connected to both the first conduction part and the second conduction part.

Abstract: A graphics system is provided. The graphics system includes a frame buffer, a timing controller, and a processing unit. The processing unit generating an output video frame based on a raw video frame. The output video frame includes the main window and a picture-in-picture window overlaid on the main window, and the picture-in-picture window is generated by zooming in a target region of the main window. The timing controller is configured to generates a first vertical synchronization signals to control the input timing for the processing unit to write the raw video frame into the frame buffer, and generate a second vertical synchronization signal to control an output timing for the processing unit to read the raw video frame from the frame buffer and generating the output video frame, such that specific timing conditions are met.

Abstract: The present disclosure provides a dialog method and system, an electronic device and a storage medium, and relates to the field of artificial intelligence (AI) technologies such as deep learning and natural language processing. A specific implementation scheme involves: rewriting a corresponding dialog state based on received dialog information of a user; determining to-be-used dialog action information based on the dialog information of the user and the dialog state; and generating a reply statement based on the dialog information of the user and the dialog action information. According to the present disclosure, the to-be-used dialog action information can be determined based on the dialog information of the user and the dialog state; and then the reply statement is generated based on the dialog action information, thereby providing an efficient dialog scheme.

Abstract: A casing assembly includes a frame, a support member, and an elastic holder, where the frame includes a frame bottom plate and a partition, the partition is disposed on the frame bottom plate and includes an engagement structure located at a side of the partition located away from the frame bottom plate, the support member is disposed on the frame bottom plate, and the elastic holder is disposed on the frame bottom plate and includes a holding structure movable with respect to the frame bottom plate.

Abstract: A large model optimization training method in the artificial intelligence fields, such as large models, deep learning, natural language processing, may include: taking, as candidate queries, queries collected from a predetermined data source and capable of serving as input to a large model in response to determining that an optimization triggering condition is met; screening out target queries from the candidate queries, the target queries being queries which cannot be correctly processed by the large model; and constructing respectively corresponding training samples according to the target queries, the training samples being used for carrying out optimization training on the large model.