Abstract: Reaction products of amines and polymers containing saturated heterocyclic moieties may be used as levelers in metal electroplating baths. The reaction products may plate metal with good surface properties and good physical reliability.

Abstract: There is provided a semiconductor device 100, comprising: at least one semiconductor chip 5, and a structure 2 thermally coupled to the at least one semiconductor chip 5, wherein the structure 2 comprises a surface located within an interior of the semiconductor device, and the surface comprises a groove 12; and a sensor 16 comprising an optical fibre 13 passing through the groove 12, wherein the sensor 16 is configured to sense a temperature of the at least one semiconductor chip 5.

Abstract: Techniques and systems are provided for predicting answers in response to one or more input queries. For instance, text from a corpus of text can be processed by a reader to generate one or multiple question and answer spaces. A question and answer space can include answerable questions and the answers associated with the questions (referred to as “question and answer pairs”). A query defining a question can be received (e.g., from a user input device) and processed by a retriever portion of the system. The retriever portion of the system can retrieve an answer to the question from the one or more pre-constructed question and answer spaces, and/or can determine an answer by comparing one or more answers retrieved from the one or more pre-constructed question and answer spaces to an answer generated by a retriever-reader system.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that implement a neural network framework for interactive multi-round image generation from natural language inputs. Specifically, the disclosed systems provide an intelligent framework (i.e., a text-based interactive image generation model) that facilitates a multi-round image generation and editing workflow that comports with arbitrary input text and synchronous interaction. In particular embodiments, the disclosed systems utilize natural language feedback for conditioning a generative neural network that performs text-to-image generation and text-guided image modification. For example, the disclosed systems utilize a trained model to inject textual features from natural language feedback into a unified joint embedding space for generating text-informed style vectors. In turn, the disclosed systems can generate an image with semantically meaningful features that map to the natural language feedback.

Abstract: The present invention regards a variety of methods and compositions for whole genome amplification and whole transcriptome amplification. In a particular aspect of the present invention, there is a method of amplifying a genome comprising a library generation step followed by a library amplification step. In specific embodiments, the library generating step utilizes specific primer mixtures and a DNA polymerase, wherein the specific primer mixtures are designed to eliminate ability to self-hybridize and/or hybridize to other primers within a mixture but efficiently and frequently prime nucleic acid templates.

Abstract: The technology described includes methods for pretraining a document encoder model based on multimodal self cross-attention. One method includes receiving image data that encodes a set of pretraining documents. A set of sentences is extracted from the image data. A bounding box for each sentence is generated. For each sentence, a set of predicted features is generated by using an encoder machine-learning model. The encoder model performs cross-attention between a set of masked-textual features for the sentence and a set of masked-visual features for the sentence. The set of masked-textual features is based on a masking function and the sentence. The set of masked-visual features is based on the masking function and the corresponding bounding box. A document-encoder model is pretrained based on the set of predicted features for each sentence and pretraining tasks. The pretraining tasks includes masked sentence modeling, visual contrastive learning, or visual-language alignment.

Abstract: A convolution apparatus including a data memory, a matrix unknit-knit device, and a convolution operation device, a convolution method, a matrix unknit-knit device, and a matrix unknit-knit method are provided. The matrix unknit-knit device unknits a first matrix stored in the data memory into s*s second matrices (or knits the s*s second matrices into the first matrix), where s is greater than 1. Pixels in each of s*s subblocks in the first matrix serve one-to-one as pixels of the s*s second matrices. A convolution operation device unknits a convolution kernel of a convolution operation with a stride of s into s*s sub-kernels, uses any one of the sub-kernels to perform a convolution operation with a stride of 1 on one corresponding second matrix, and accumulates the operation results the second matrices as the operation result of performing the convolution operation with a stride of s on the first matrix.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate a natural language model that provides user-entity differential privacy. For example, in one or more embodiments, the disclosed systems sample sensitive data points from a natural language dataset. Using the sampled sensitive data points, the disclosed systems determine gradient values corresponding to the natural language model. Further, the disclosed systems generate noise for the natural language model. The disclosed systems generate parameters for the natural language model using the gradient values and the noise, facilitating simultaneous protection of the users and sensitive entities associated with the natural language dataset. In some implementations, the disclosed systems generate the natural language model through an iterative process (e.g., by iteratively modifying the parameters).

Abstract: A domain alignment technique for cross-domain object detection tasks is introduced. During a preliminary pretraining phase, an object detection model is pretrained to detect objects in images associated with a source domain using a source dataset of images associated with the source domain. After completing the pretraining phase, a domain adaptation phase is performed using the source dataset and a target dataset to adapt the pretrained object detection model to detect objects in images associated with the target domain. The domain adaptation phase may involve the use of various domain alignment modules that, for example, perform multi-scale pixel/path alignment based on input feature maps or perform instance-level alignment based on input region proposals.

Abstract: Adapting a machine learning model to process data that differs from training data used to configure the model for a specified objective is described. A domain adaptation system trains the model to process new domain data that differs from a training data domain by using the model to generate a feature representation for the new domain data, which describes different content types included in the new domain data. The domain adaptation system then generates a probability distribution for each discrete region of the new domain data, which describes a likelihood of the region including different content described by the feature representation. The probability distribution is compared to ground truth information for the new domain data to determine a loss function, which is used to refine model parameters. After determining that model outputs achieve a threshold similarity to the ground truth information, the model is output as a domain-agnostic model.

Abstract: Techniques are disclosed for sharing user markings between digital documents and corresponding physically printed documents. The sharing is facilitated using an Augmented Reality (AR) device, such as a smartphone or a tablet. The device streams images of a page of a book on a display. The device accesses a corresponding digital document that is a digital version of content printed on the book. In an example, the digital document has a digital user marking, e.g., a comment associated with a paragraph of the digital document, wherein a corresponding paragraph of the physical book lacks any such comment. When the device streams the images of the page of the book on the display, the device appends the digital comment on the paragraph of the page of the book within the image stream. Thus, the user can view the digital comment in the AR environment, while reading the physical book.

Abstract: One example method involves operations for a processing device that include receiving, by a machine learning model trained to generate a search result, a search query for a text input. The machine learning model is trained by receiving pre-training data that includes multiple documents. Pre-training the machine learning model by generating, using an encoder, feature embeddings for each of the documents included in the pre-training data. The feature embeddings are generated by applying a masking function to visual and textual features in the documents. Training the machine learning model also includes generating, using the feature embeddings, output features for the documents by concatenating the feature embeddings and applying a non-linear mapping to the feature embeddings. Training the machine learning model further includes applying a linear classifier to the output features. Additionally, operations include generating, for display, a search result using the machine learning model based on the input.

Abstract: The present invention regards a variety of methods and compositions for whole genome amplification and whole transcriptome amplification. In a particular aspect of the present invention, there is a method of amplifying a genome comprising a library generation step followed by a library amplification step. In specific embodiments, the library generating step utilizes specific primer mixtures and a DNA polymerase, wherein the specific primer mixtures are designed to eliminate ability to self-hybridize and/or hybridize to other primers within a mixture but efficiently and frequently prime nucleic acid templates.

Abstract: A formaldehyde free adhesive composition and a plywood obtained from the adhesive composition is provided, and the plywood has a balanced performance, such as high adhesion strength, sufficient pot-life, and good workability.

Abstract: The present invention provides a flexible wrapping material comprising a coolant gel composition comprising, i) at least one hydrophilic polyurethane prepolymer, ii) a coolant agent, iii) water, and iv) thermally conductive filler.

Abstract: Adapting a machine learning model to process data that differs from training data used to configure the model for a specified objective is described. A domain adaptation system trains the model to process new domain data that differs from a training data domain by using the model to generate a feature representation for the new domain data, which describes different content types included in the new domain data. The domain adaptation system then generates a probability distribution for each discrete region of the new domain data, which describes a likelihood of the region including different content described by the feature representation. The probability distribution is compared to ground truth information for the new domain data to determine a loss function, which is used to refine model parameters. After determining that model outputs achieve a threshold similarity to the ground truth information, the model is output as a domain-agnostic model.

Abstract: A monitoring system for an electric vehicle that draws current from a conductor by means of a current collector that contacts a conductor in operation of the electric vehicle. The monitoring system includes a plurality of sensor modules throughout the current collector, wherein each sensor module comprises a plurality of FBG (Fibre Bragg Grating) sensors. Sensors of each module are arranged in a geometric pattern that compensates for temperature induced wavelength changes in the FBG sensors of each module. An optical source illuminates each sensor module and an optical coupler optically couples the optical source to each sensor module. An optical signal interpretation module receives optical signals from each sensor module wherein the optical signals are generated by the sensor modules in response to illumination of the sensor modules, wherein the interpretation module is configured to determine from the optical signals, a temperature-independent strain measurement for each sensor module.

Abstract: A polymer-modified cementitious composition comprising a specific aqueous polymer dispersion and a cementitious material, and such polymer-modified cementitious composition having low ammonia release and providing coating membranes made therefrom with balanced tensile strength and elongation at break.

Abstract: An information processing method, an interconnection device, and a computer-readable storage medium are provided. The interconnection device includes a request processing module configured for: receiving a data access request from at least one processor, wherein the data access request comprises a merge bit, a multicast group identifier (MGID), and a multicast transaction identifier (MTID); determining whether the data access request is a multicast request; determining whether the interconnection device receives other multicast requests if it is determined that the data access request is a multicast request based on the MGID, the MTID, and a static routing policy of a multicast group; and obtaining the other multicast requests if it is determined that the interconnection device receives the other multicast requests, merging the multicast request with the other multicast requests into a merged request, and forwarding the merged request to a next-hop device of the interconnection device.

Abstract: The present disclosure discloses a method for preparing a green slow-release preservative paper used for fruit and vegetable preservation. The method includes: step 1, preparing a core paper loaded with biological preservative; step 2, preparing a base membrane loaded with fruit and vegetable respiration inhibitor; and step 3, heating and pressing the core paper loaded with biological preservative and the base membrane loaded with fruit and vegetable respiration inhibitor to obtain the green slow-release preservative paper. The present disclosure uses a biological preservative as a main material and an absorbent paper or a non-woven fabric as an auxiliary material to prepare the green slow-release preservative paper used for fruit and vegetable preservation through a layer-by-layer film covering method.