Abstract: A computing device includes a transport switch comprising read and write switches that provide switched circuit interconnections between input and output ports for simultaneous data communication between a plurality of memory clients and a plurality of memory banks, such as between cores of a multi-core processor simultaneously accessing L1, L2, and L3 memory banks. Embodiments implement switching designs that are derived from existing switched network architectures. Other embodiments implement a novel circuit switch design based on 8×8 building blocks. The transport switch can be non-blocking, and can be self-routing. An additional switching layer can be included to provide port rearrangement for rearrangeable non-blocking switches. A transport compiler can be used to determine port-pair configurations of the switch. A disclosed method selects optimal switch architectures for specific applications.

Abstract: A system and a method for classifying sensitive data elements in a file is provided. The method includes receiving and converting, the unstructured data file into a machine-readable format and generating, a plurality of sensitive data features. The plurality of sensitive data features represents single element of the sensitive data. The method includes generating, a plurality of adjacent elements corresponding to the single elements of the sensitive data and generating a plurality of feature categories. The method includes aggregating, the plurality of adjacent node features and the plurality of edge features. The method includes calculating and concatenating the plurality of aggregated adjacent nodes features and the plurality of aggregated edge features. The method includes comparing, the distance of the sensitive data from all of the adjacent sensitive data. The method includes classifying and predicting, the sensitive data to be a true positive or false positive sensitive data by using machine learning.

Abstract: A system and method for templatizing documents across data sources is disclosed. The system includes a scanner to scan a plurality of files to retrieve a plurality of textual content. The system includes a pre-processor module to refine an efficacy corresponding to the scanned plurality of files by using a classifier to identify textual content with a similar template. The system includes an extraction module to extract a plurality of common sequences and sub-sequences from the plurality of files. The system includes a ranking module to rank the plurality of common sequences and sub-sequences based on a score. The system includes a feature vector generating module to generate a feature vector from the plurality of common sequences and sub-sequences. The system includes a determining module to determine a threshold value for the classifier thereby developing the classifier automatically to search for positive files with similar templates in the organization.

Abstract: Disclosed are SHP2 inhibitor compositions and methods of treating diseases or disorders using an intermittent dosing schedule.

Abstract: An electrostatic discharge protection circuit, a display substrate and a display apparatus are disclosed. The electrostatic discharge protection circuit includes: a first conductive portion, having an end portion; and at least one electrostatic discharge portion, arranged on a same layer as the first conductive portion and spaced from the end portion of the first conductive portion, the at least one electrostatic discharge portion being configured to discharge electrostatic charges generated at the end portion of the first conductive portion.

Abstract: Disclosed is detecting identification documents in image-borne identification documents and protecting against loss of the image-borne identification documents. A trained deep learning (DL) stack is used to classify production images by inference as containing a sensitive image-borne identification document, with the trained stack configured with parameters determined using labelled ground truth data for the identification documents and examples of other image documents. The trained DL stack is configured to include a first set of layers closer to an input layer and a second set of layers further from the input layer, with the first set pre-trained to perform image recognition before exposing the second set of layers of the stack to the labelled ground truth data for the image-borne identification documents and examples of other image documents, and using the inferred classification of the sensitive image-borne identification document in a DLP system to protect against loss by image exfiltration.

Abstract: The invention relates to a button lithium ion battery, a preparation method thereof, and a method of producing a lithium ion cell composite flat sheet, wherein the button lithium ion battery comprises a battery housing, a cell accommodated in the battery housing and an electrolyte filled in the battery housing; the cell is formed by winding a composite flat sheet in which a first separator, a positive piece, a second separator and a negative piece are sequentially stacked and hot-laminated to form an integrated structure. The cell of the button lithium ion battery is formed by winding a composite flat sheet, so that winding efficiency can be improved, and misalignment can be avoided; moreover, chances of hand contact can be reduced, the influence of dust and water vapor can be avoided, and the quality of the lithium battery can be improved to the maximum extent.

Abstract: The technology disclosed relates to distributing a trained master deep learning (DL) stack with stored parameters to a plurality of organizations, to detect organization sensitive data in images, referred to as image-borne organization sensitive documents, and protecting against loss of the image-borne organization sensitive documents. Disclosed is providing organizations with a DL stack update trainer, under the organizations' control, configured to allow the organizations to perform update training to generate updated DL stacks, without the organizations forwarding images of organization-sensitive training examples, and to save non-invertible features derived from the images, ground truth labels for the images, and parameters of the updated DL stacks.

Abstract: Disclosed is an automatically adjustable shadowless operating lamp. The automatically adjustable shadowless operating lamp comprises a telescopic support rod. The telescopic support rod is rotatably connected with a first lighting assembly and a second lighting assembly with a same structure, the second lighting assembly is positioned above the first lighting assembly, and the second lighting assembly moves independently with the first lighting assembly; the first lighting assembly comprises a first adjusting part, the first adjusting part is rotationally connected with the telescopic support rod, and is hinged with an adjusting rod through an adjusting piece, a tail end of the adjusting rod is fixedly connected with a second adjusting part, and the adjusting rod is hinged with an operating lamp through the second adjusting part.

Abstract: A multi-layered microfluidic system featuring tissue chambers for cells in a first layer and a plurality of medium channels for culture medium in a second layer. The tissue chambers fluidly connect to the medium channels such that media flows from the medium channels to the tissue chambers, forming large-scale perfused capillary networks. The capillary networks can undergo angiogenesis and vertical anastomosis. The multi-layered configuration of the system of the present invention allows for flexibility in design.

Abstract: Embodiments of the present disclosure provide an array substrate, a display panel, and a display apparatus. The array substrate includes: a display region for displaying an image; a non-display region; a shift register provided in the non-display region; a gate line provided in the display region and extending along a first direction; and a gate signal output line, provided in the non-display region and having a first end and a second end. The first end of the gate signal output line is connected to the shift register, and the second end of the gate signal output line is connected to the gate line at a side of the gate line in a second direction perpendicular to the first direction.

Abstract: An SoC maintains the full flexibility of a general-purpose microprocessor while providing energy efficiency similar to an ASIC by implementing software-controlled virtual hardware architectures that enable the SoC to function as a virtual ASIC. The SoC comprises a plurality of “Stella” Reconfigurable Multiprocessors (SRMs) supported by a Network-on-a-Chip that provides efficient data transfer during program execution. A hierarchy of programmable switches interconnects the programmable elements of each of the SRMs at different levels to form their virtual architectures. Arithmetic, data flow, and interconnect operations are also rendered programmable. An architecture index” points to a storage location where pre-determined hardware architectures are stored and extracted during program execution. The programmed architectures are able to mimic ASIC properties such as variable computation types, bit-resolutions, data flows, and amount and proportions of compute and data flow operations and sizes.

Abstract: An SoC maintains the full flexibility of a general-purpose microprocessor while providing energy efficiency similar to an ASIC by implementing software-controlled virtual hardware architectures that enable the SoC to function as a virtual ASIC. The SoC comprises a plurality of “Stella” Reconfigurable Multiprocessors (SRMs) supported by a Network-on-a-Chip that provides efficient data transfer during program execution. A hierarchy of programmable switches interconnects the programmable elements of each of the SRMs at different levels to form their virtual architectures. Arithmetic, data flow, and interconnect operations are also rendered programmable. An architecture index” points to a storage location where pre-determined hardware architectures are stored and extracted during program execution. The programmed architectures are able to mimic ASIC properties such as variable computation types, bit-resolutions, data flows, and amount and proportions of compute and data flow operations and sizes.

Abstract: A computing device includes a transport switch comprising read and write switches that provide switched circuit interconnections between input and output ports for simultaneous data communication between a plurality of memory clients and a plurality of memory banks, such as between cores of a multi-core processor simultaneously accessing L1, L2, and L3 memory banks. Embodiments implement switching designs that are derived from existing switched network architectures. Other embodiments implement a novel circuit switch design based on 8×8 building blocks. The transport switch can be non-blocking, and can be self-routing. An additional switching layer can be included to provide port rearrangement for rearrangeable non-blocking switches. A transport compiler can be used to determine port-pair configurations of the switch. A disclosed method selects optimal switch architectures for specific applications.

Abstract: A quaternary lactam compound of formula (I). The compound is used in the manufacture of a medicament for the treatment and/or prevention of thrombotic or thromboembolic disorders.

Abstract: Embodiments of the present disclosure relate to a data driving circuit, a driving method thereof, an array substrate, and a display panel. The data driving circuit includes a data driver, a multiplex circuit, and a control circuit. The data driver includes M data output terminals, and each of the data output terminals provides a data signal to L data lines via the multiplex circuit. The multiplex circuit includes M×L switch groups, and each of the switch groups includes N switch tubes and is coupled between one data line and the corresponding data output terminal. Each switch tube is coupled to one of L×N gate control terminals of the control circuit. Each gate control terminal is coupled to M switch tubes that are spaced apart from each other by (L×N×1) switch tubes. In the embodiments, M is an integer, and L and N are integers greater than or equal to 2.

Abstract: A pressure regulator module for a chip-based microfluidic platform is provided. The module includes a microfluidic channel for passing flowable material from the inlet region through the outlet region and into a downstream compartment; one or more microvalves fluidly connected to the microfluidic channel and upstream of the outlet region; and one or more reservoirs fluidly connected to the microvalves, for receiving flowable material diverted by the microvalves, where a flow of flowable material passing from the inlet region toward the downstream compartment is at least partially diverted by the microvalves into the reservoirs as a result of a pressure increase in the microfluidic channel. In some versions, the microvalves are capillary burst valves. A microfluidic chip containing the module and a method of using the module are provided.

Abstract: Disclosed is detecting identification documents in image-borne identification documents and protecting against loss of the image-borne identification documents. A trained deep learning (DL) stack is used to classify production images by inference as containing a sensitive image-borne identification document, with the trained stack configured with parameters determined using labelled ground truth data for the identification documents and examples of other image documents. The trained DL stack is configured to include a first set of layers closer to an input layer and a second set of layers further from the input layer, with the first set pre-trained to perform image recognition before exposing the second set of layers of the stack to the labelled ground truth data for the image-borne identification documents and examples of other image documents, and using the inferred classification of the sensitive image-borne identification document in a DLP system to protect against loss by image exfiltration.

Abstract: The technology disclosed relates to distributing a trained master deep learning (DL) stack with stored parameters to a plurality of organizations, to detect organization sensitive data in images, referred to as image-borne organization sensitive documents, and protecting against loss of the image-borne organization sensitive documents. Disclosed is providing organizations with a DL stack update trainer, under the organizations' control, configured to allow the organizations to perform update training to generate updated DL stacks, without the organizations forwarding images of organization-sensitive training examples, and to save non-invertible features derived from the images, ground truth labels for the images, and parameters of the updated DL stacks.

Abstract: Disclosed are methods and systems for detecting screenshot images and protecting against loss of sensitive screenshot-borne data. One disclosed method includes collecting examples of the screenshot images and non-screenshot images and creating labelled ground-truth data for the examples. The method also includes applying re-rendering of at least some of the collected example screenshot images to represent different variations of screenshots that may contain sensitive information, and further includes training a deep learning stack by forward inference and back propagation using labelled ground-truth data for the screenshot images and the examples of the non-screenshot images. The method further includes using results of the back propagation to configure parameters of the trained DL stack for inference from images in production. Also disclosed is applying a screenshot robot to collect the examples of the screenshot images and non-screenshot images.