Abstract: A low-carbon, high-purity tantalum pentoxide powder has a carbon content of no greater than 15 ppm. A preparation method for the powder includes: (1) adding a fluotantalic acid (H2TaF7) solution into a reaction kettle, controlling the temperature of the reaction kettle at 30-60° C., adding a precipitator until the pH of the reaction solution is 8-10, then stopping introducing ammonia, and aging to obtain a tantalum hydroxide slurry; (2) filtering and washing the slurry obtained in step (1), and then carrying out solid-liquid separation to obtain a tantalum hydroxide filter cake; (3) drying the filter cake obtained in step (2) to obtain white tantalum hydroxide powder; (4) calcining the tantalum hydroxide powder obtained in step (3), crushing and screening the calcined sample to obtain tantalum pentoxide powder; and (5) subjecting the tantalum pentoxide powder obtained in step (4) to heat treatment at a temperature of 1000-1500° C. to obtain the powder.

Abstract: The present disclosure provides an image processing method, an apparatus, a computing device, and a medium, which relates to deep learning technology. In the present disclosure, after acquiring the to-be-processed target image, the first similarities between the target image and the first images of categories are determined based on the first feature vector corresponding to the target image and the second feature vectors respectively corresponding to the plurality of first images. Moreover, based on the first color distribution information of the target region in the target image and the second color distribution information of the target regions in the plurality of first images, the second similarities between the target image and the plurality first images are determined, so that the image category to which the target image belongs can be determined jointly based on the first similarities and the second similarities.

Abstract: A first set of features associated with a neural network are parameterized. A decision tree is generated from the first set of features. One or more adjustments for the neural network are received at the decision tree. A second set of features associated with the adjustments at the decision tree are parameterized. The parameterized first and second set of features are combined into a plurality of parameters. From the plurality, an adjusted neural network is generated.

Abstract: Techniques are described for identifying a genetic variant in a test sample by comparing sequences reads obtained from the test sample to unique k-mers that are representative of a target genomic region. In one particular aspect, a method is described that includes generating a dictionary of a target genomic region having a set of unique k-mers by: accessing a sequence of the target genomic region, determining a set of k-mers for the target genomic region, comparing the set of k-mers for the target genomic region with one or more sets of k-mers for non-target genomic regions, and selecting the unique k-mers that do not appear in the one or more sets of k-mers for non-target genomic regions. The dictionary can then be used to identify a genetic variant in a test sample by comparing sequences reads obtained from the test sample to the unique k-mers in the dictionary.

Abstract: A self-managed DRAM module configured to reduce energy consumption. A module is described that includes a plurality of DDR channels and a management engine configured to read and write data blocks to DDR channels according to a process that includes: allocating a set of sub-channels for each DDR channel, wherein each sub-channel includes a subset of the set of DRAM chips; wherein a write operation of a data block includes: encoding the data block to generate an ECC codeword; and writing the ECC codeword into the subset of DRAM chips of a specified sub-channel; and wherein a read operation of the data block includes: reading the ECC codeword from the subset of DRAM chips of the specified sub-channel; and decoding the ECC codeword to obtain the data block.

Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to a process to facilitate abnormal document self-discovery. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an object detection component that can generate a knowledge graph with vectors corresponding with nodes representative of a page layout of a document. Additionally, the computer executable components can comprise an evaluation component that can compare the vectors to identify whether an edge is present between corresponding vectors of the knowledge graph; an encoder component that can re-code the knowledge graph; and a comparison component that can compare a structure of the knowledge graph with one or more other knowledge graphs corresponding to one or more other documents to determine if the document is abnormal.

Abstract: A system and method for table conversion including converting a table containing text in tabular form to an image, labeling each text area of the image with a bounding box, determining for each bounding box, a position information, a semantic information, and an image information, reconstructing the image into a graph form having a plurality of nodes, wherein each node represents the bounding box of the text areas of the image, inputting at least two nodes into a trained neural network to determine a relative relationship between the at least two nodes, building a knowledge graph using the relative relationship of the at least two nodes, and translating the knowledge graph into machine readable natural language.

Abstract: A method, computer program product, and computer system for generating and using a basic state layer. N task models are provided (N?2). Each task model was trained on a same pre-trained backbone model. Each task model includes M feature layers and a task layer (M?1). Each feature layer of each task model includes a parameter matrix that is different for the different models. An encoder-decoder model is trained. The encoder-decoder model includes sequentially: an input layer, an encoder, M hidden layers, a decoder, and an output layer. The encoder is a neural network that maps and compresses the parameter matrices in the input layer into the M hidden layers, which generates a basic state model. The decoder is a neural network that receives the basic state model as input and generates the output layer to be identical to the input layer.

Abstract: An example operation may include one or more of generating a three-dimensional (3D) model of an object via execution of a machine learning model on one or more images of the object, capturing a plurality of snapshots of the 3D model of the object at different angles to generate a plurality of snapshot images of the object, fusing a feature into each of the plurality of snapshots to generate a plurality of fused snapshots of the 3D model of the object, and storing the plurality of fused snapshots of the 3D model of the object in memory.

Abstract: The present disclosure provides a method for aligning a master oscillator power amplifier (MOPA) system. The method includes ramping up a pumping power input into a laser amplifier chain of the MOPA system until the pumping power input reaches an operational pumping power input level; adjusting a seed laser power output of a seed laser of the MOPA system until the seed laser power output is at a first level below an operational seed laser power output level; and performing a first optical alignment process to the MOPA system while the pumping power input is at the operational pumping power input level, the seed laser power output is at the first level, and the MOPA system reaches a steady operational thermal state.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model on training data. In one aspect, one of the methods include: obtaining a training data set comprising a plurality of training inputs; obtaining data defining an original search space of a plurality of candidate data augmentation policies; generating, from the original search space, a compact search space that has one or more global hyperparameters; and training the machine learning model on the training data using one or more final data augmentation policies generated from the compact search space.

Abstract: The present invention discloses a multi-energy complementary system for a co-associated abandoned mine and a use method. The multi-energy complementary system for a co-associated abandoned mine includes a mining mechanism, a grouting mechanism and an energy mechanism. In the present invention, the mining of coal and uranium resources is realized through the mining mechanism, the subsidence and seepage reduction of the stratum is realized through the grouting mechanism, and the effective utilization of waste resources is realized through the energy mechanism. Finally, with the efficient cooperation of the three mechanisms, safe and efficient development and utilization of co-associated resources in the full life cycle are realized, and the purposes of green and efficient mining of coal and uranium resources and secondary development of a coal seam goaf are achieved, thereby facilitating the realization of dual-carbon goals and the development of low-carbon green energy.

Abstract: Antigen binding molecules (ABMs) comprising Fab domains in non-native configurations, ABM conjugates comprising the ABMs and cytotoxic or cytostatic agents, pharmaceutical compositions containing the ABMs and ABM conjugates, methods of using the ABMs, ABM conjugates and pharmaceutical compositions for treating cancer, nucleic acids encoding the ABMs, cells engineered to express the ABMs, and methods of producing ABMs.

Abstract: In one embodiment, a first path computation element (PCE) receives a request from a gateway for service chain functions (SFs) to be applied to a traffic flow, wherein a first subset of the SFs is located in a first zone. The first PCE identifies a boundary node located at a border between the first zone and a second zone where a second subset of the SFs are located. The first PCE sends a response to the gateway indicating a path within the first zone between the gateway and the boundary node to apply the first subset of SFs to the flow. The first PCE provides information regarding the flow and the boundary node to a second PCE that uses the information to configure the boundary node to route the flow in the second zone to apply the second subset of SFs to the flow.

Abstract: Provided is a use of a mitoxantrone hydrochloride liposome in the preparation of a drug for treating urothelial cancer, breast cancer, and bone and soft tissue sarcoma. Further provided is a method for treating urothelial cancer, breast cancer, and bone and soft tissue sarcoma, and the method is to administer a therapeutically effective amount of mitoxantrone hydrochloride liposomes to a patient in need. The mitoxantrone hydrochloride liposome can effectively treat urothelial cancer, breast cancer, and bone and soft tissue sarcoma, and compared with common mitoxantrone hydrochloride injections, the mitoxantrone hydrochloride liposome has better therapeutic effect and fewer adverse reactions.

Abstract: A Pseudomonas monteilii strain with salinity-alkalinity tolerance is provided. The strain is Pseudomonas monteilii 9-2, which has been deposited in China General Microbiological Culture Collection Center (CGMCC) on Oct. 25, 2021, with an accession number of CGMCC No. 23666; and an internal transcribed spacer (ITS) sequence is shown in SEQ ID NO: 1. This application further provides an application of the Pseudomonas monteilii strain in the degradation of petroleum hydrocarbons in a saline-alkali environment.

Abstract: A pulse diagnostic device and a system of pulse diagnosis are provided. The pulse diagnostic device includes a cuff and a main monitor. The cuff includes a tube and an air bag arranged with an air path interface. A gas medium is received in the air bag. The tube is connected to the air path interface. The main monitor includes a pressure sensor and a controller. The tube extends to reach the main monitor and is connected to the pressure sensor, and the pressure sensor further connects to the controller. When the pulse diagnostic device is working, the cuff contacts an artery, the pressure sensor senses a pressure of the gas medium in the tube. The pressure sensor transmits the pressure of the gas medium to the controller. The controller obtains the pulse information and the blood pressure information based on the pressure of the gas medium.

Abstract: An intelligent experimental device for collaborative mining of associated resources includes a signal transmission mechanism, a pressure maintaining mechanism, a feeding mechanism, and a reaction mechanism. The signal transmission mechanism includes a centralized controller, an annunciator, signal receivers, a power supply, a power cord, signal transmitters, and signal sensing valves. The pressure maintaining mechanism includes ambient and axial pressure oil chambers, ambient and axial pressure pumps, ambient and axial pressure liquid distribution tanks, a comprehensive pressure distribution pipe, and hydraulic transmission pipes. The feeding mechanism includes monitoring analyzers, temperature controllers, solution transfer pipes, seepage pumps, mixture conveying pipes, a comprehensive liquid distributor, an aggregate chamber, a liquid chamber, an oil chamber, a gas chamber, a mixing chamber and an analytical purifier.

Abstract: An optical proximity sensor includes a housing, an optical emitter, and an optical detector. A first light guide disposed in a first chimney of the housing is configured to direct light from the optical emitter through the first chimney towards a target location. A second light guide disposed in a second chimney of the housing is configured to direct a returned portion of the light emitted from the optical emitter through the second chimney towards the optical detector.

Abstract: Techniques are described with respect to a system, method, and computer product for enhancement of socialization between one or more individuals wearing personal protective equipment. An associated method includes identifying a plurality of social communications between one or more individuals wearing personal protective equipment (PPE) and assigning an identifier to a participant associated with at least one of the social communications. The method further includes analyzing content of the at least one social communication and generating an augmented reality (AR) based representation of the content for presentation on an augmented reality device associated with the user, the augmented reality device presenting the content for visualization replacing PPE based at least in-part on the identifier.