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.

Abstract: Technology for providing data to a processing unit is disclosed. A computer processor may be divided into a master processing unit and consumer processing units. The master processing unit at least partially decodes a machine instruction and determines whether data is needed to execute the machine instruction. The master processing unit sends a request to memory for the data. The request may indicate that the data is to be sent from the memory to a consumer processing unit. The data sent by the memory in response to the request may be stored in local read storage that is close to the consumer processing unit for fast access. The master processing unit may also provide the machine instruction to the consumer processing unit. The consumer processing unit may access the data from the local read storage and execute the machine instruction based on the accessed data.

Abstract: Methods and systems disclosed herein relate generally to systems and methods for generating visual relationship graphs that identify relationships between objects depicted in an image. A vision-language application uses transformer encoders to generate a graph structure, in which the graph structure represents a dependency between a first region and a second region of an image. The dependency indicates that a contextual representation of the first region was derived, at least in part, by processing the second region. The contextual representation identifies a predicted identity of an image object depicted in the first region. The predicted identity is determined at least in part by identifying a relationship between the first region and other data objects associated with various modalities.

Abstract: A formaldehyde free adhesive composition and a plywood obtained by the adhesive composition is provided, and the plywood retains desired performances, such as water resistance and workability.

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 disclosure provides materials and methods related to using biomarkers for prediction of duration of response to prostate cancer treatment and for treating prostate cancer.

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 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: A power transmitting device for a contactless power supply, can include: a power transmitting antenna having a plurality of transmitting coils; where each of the plurality of transmitting coils comprises a coil turn or a plurality of concentric coil turns with a substantially coplanar setting and having a coil surface; where an axis of each of the plurality of transmitting coils is axially perpendicular to the power transmitting antenna; and where the axis of each of the plurality of transmitting coils forms a predetermined angle with respect to each other.

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.