Abstract: Various embodiments of the teachings herein include a computer-implemented method of fine-tuning Natural Language Processing (NLP) models. Some examples include: providing a training data set including a multitude of training text documents; providing a NLP model including a Neural Network (NN) based Topic Model (TM) having scalable TM parameters and a parallel large-scale pre-trained Language Model (LM) having scalable LM parameters; and fine-tuning the NLP model by jointly training the NN-based TM and the parallel large-scale pre-trained LM using a projected vector comprising a combination and projection of a document topic proportion generated by the NN-based TM based on the scalable TM parameters from an input training text document of the multitude of training text documents, and of a contextualized document representation generated by the large-scale pre-trained LM based on the scalable LM parameters from the same input training text document.

Abstract: The present invention relates to novel DLL3/CD3 binding proteins. The invention also relates to nucleic acids encoding such proteins; to methods for preparing such proteins; to host cells expressing or capable of expressing such proteins; to compositions comprising such proteins; and to uses of such proteins or such compositions, in particular for therapeutic purposes in the field of cancer diseases.

Abstract: The invention relates to method and system for automatically identifying tube elements in a Boundary Representation (B-Rep)-based Computer Aided Design (CAD) model of a tube. The method includes extracting information corresponding to the B-Rep-based CAD model of the tube; validating geometrical features of the B-Rep based CAD model of the tube based on the extracted information; classifying each of a plurality of faces of the tube into one of a set of face types; determining one or more regions on the tube using a set of connected top faces of the tube; generating a plurality of primary tube elements and a set of secondary tube elements based on shapes of the plurality of regions; determining a plurality of element parameters for each of the plurality of tube elements of the tube; and determining a plurality of tube parameters for the tube based on the plurality of element parameters.

Abstract: Various embodiments include a computer-implemented method for a language modeling, LM. In some examples, the method includes: performing a topic modeling, TM, for at least one document to acquire a first type of topic representation which represents a topic distribution for each word in the at least one document; generating a second type of topic representation based on a predefined number of key terms for each topic of the topic distribution represented by the first topic representation; generating a TM representation comprising the first type of topic representation, the second type of topic representation, or a combination of the first type of topic representation and the second type of topic representation; receiving an input sentence for the LM; and performing the LM on the input sentence based on the TM representation.

Abstract: Various embodiments of the teachings herein include a computer-implemented method for a topic modeling with a continuous learning. The method may include: extracting a current topic representation which represents a topic distribution over vocabulary within a current document; adjusting a size of the vocabulary of the current topic representation based on words used in a topic pool, wherein the topic pool includes past topic representations accumulated by each of past documents; regularizing the current topic representation by controlling a degree of topic imitation with past topic representations, based on comparison of the current topic representation and each of the past topic representations; and accumulating the regularized current topic representation into the topic pool.

Abstract: An example apparatus includes: nonlinearity function selection circuitry with an output, the nonlinearity function selection circuitry to select a type of a nonlinearity function, the nonlinearity function to model nonlinearity portions of data output from an analog-to-digital converter, nonlinearity function term generation circuitry with a first input coupled to the output, the nonlinearity function term generation circuitry to generate one or more nonlinearity function terms of the nonlinearity function based on the type of the nonlinearity function and the data, and coefficient determination circuitry with a second input coupled to the output, the coefficient determination circuitry to determine one or more nonlinearity function coefficients based on the one or more nonlinearity function terms, the nonlinearity portions of the data to be compensated based on the one or more nonlinearity function coefficients.

Abstract: The present invention relates to novel B7H6/CD3 binding proteins. The invention also relates to nucleic acids encoding such proteins; to methods for preparing such proteins; to host cells expressing or capable of expressing such proteins; to compositions comprising such proteins; and to uses of such proteins or such compositions, in particular for therapeutic purposes in the field of cancer diseases.

Abstract: The present invention relates to antibodies and fragments thereof that target the complement C3. More specifically, anti-C3 antibodies and methods of use for the treatment of various diseases or disorders are disclosed.

Abstract: An accelerator for bitonic sorting includes a plurality of compare-exchange circuits and a first-in, first-out (FIFO) buffer associated with each of the compare-exchange circuits. An output of each FIFO buffer is a FIFO value. The compare-exchange circuits are configured to, in a first mode, store a previous value from a previous compare-exchange circuit or a memory to its associated FIFO buffer and pass a FIFO value from its associated FIFO buffer to a subsequent compare-exchange circuit or the memory; in a second mode, compare the previous value to the FIFO value, store the greater value to its associated FIFO buffer, and pass the lesser value to the subsequent compare-exchange circuit or the memory; and in a third mode, compare the previous value to the FIFO value, store the lesser value to its associated FIFO buffer, and pass the greater value to the subsequent compare-exchange circuit or the memory.

Abstract: The invention relates to method and system for classifying faces of a Boundary Representation (B-Rep) model using Artificial Intelligence (AI).

Abstract: The present invention relates to anti-SIRP? (Signal regulatory protein alpha) antibodies and antigen-binding fragments thereof for therapeutic and diagnostic methods and compositions using them.

Abstract: Disclosed are antibodies and fragments thereof that target the A-domain of Neuropilin-1 (Nrp1A). Also disclosed are methods of using the anti-Nrp1A antibodies for the treatment of various diseases or disorders.

Abstract: A radar hardware accelerator (HWA) includes a fast Fourier transform (FFT) engine including a pre-processing block for providing interference mitigation and/or multiplying a radar data sample stream received from ADC buffers within a split accelerator local memory that also includes output buffers by a pre-programmed complex scalar or a specified sample from an internal look-up table (LUT) to generate pre-processed samples. A windowing plus FFT block (windowed FFT block) is for multiply the pre-processed samples by a window vector and then processing by an FFT block for performing a FFT to generate Fourier transformed samples. A post-processing block is for computing a magnitude of the Fourier transformed samples and performing a data compression operation for generating post-processed radar data. The pre-processing block, windowed FFT block and post-processing block are connected in one streaming series data path.

Abstract: The present invention relates to anti-SIRP? (Signal regulatory protein alpha) antibodies and antigen-binding fragments thereof for therapeutic and diagnostic methods and compositions using them.

Abstract: The present invention relates to anti-SIRP? (Signal regulatory protein alpha) antibodies and antigen-binding fragments thereof for therapeutic and diagnostic methods and compositions using them.

Abstract: The present invention relates to novel tri-specific binding molecules. The invention also relates to nucleic acids encoding such binding molecules; to methods for preparing such binding molecules; to host cells expressing or capable of expressing such binding molecules; to compositions comprising such binding molecules; and to uses of such binding molecules or such compositions, in particular for therapeutic purposes in the field of cancer diseases.

Abstract: Described herein is a medical device including a frame having proximal and distal ends. The frame includes a proximal disc at the proximal end, a distal disc at the distal end, and a connecting segment extending between the proximal end and the distal end and connecting the proximal and distal discs. Each of the proximal and distal discs includes a respective plurality of lobes. Each lobe is defined by a peripheral strut. The medical device also includes at least one patch. The at least one patch is coupled to at least one of the proximal and distal discs of the frame.

Abstract: The present disclosure provides improved medical delivery devices for delivering a medical device into a subject. In one embodiment, the medical delivery device includes a non-porous composite inner layer constructed of a lubricious material having a plurality of pores and a thermoplastic elastomer reflowed into the plurality of pores. In other embodiments, the medical delivery device further includes a thermoplastic elastomer coated braided metallic member surrounding the nonporous composite inner layer to provide strength and structure to the device.

Abstract: A method and system for automatically performing a discovery of topics within temporal ordered text document collections are provided. The method includes generating a bag of words vector for each text document collection using a predefined dictionary. The method also includes iteratively calculating, based on the generated bag of words vectors, for each text document collection, a hidden topic vector representing topics of the respective text document collection using a calculated hidden state vector memorizing a hidden state of all previous text document collections.

Abstract: The present invention relates to new anti-angiopoietin 2 (ANGPT2) neutralizing antibodies for therapeutic and diagnostic methods and composition using them.