Abstract: The disclosure discloses a method for detecting an intrusion in parallel based on an unbalanced data Deep Belief Network, which reads an unbalanced data set DS; under-samples the unbalanced data set using the improved NCR algorithm to reduce the ratio of the majority type samples and make the data distribution of the data set balanced; the improved differential evolution algorithm is used on the distributed memory computing platform Spark to optimize the parameters of the deep belief network model to obtain the optimal model parameters; extract the feature of data of the data set, and then classify the intrusion detection by the weighted nuclear extreme learning machine, and finally train multiple weighted nuclear extreme learning machines of different structures in parallel by multithreading as the base classifier, and establish a multi-classifier intrusion detection model based on adaptive weighted voting for detecting the intrusion in parallel.

Abstract: A method for video encoding includes determining a filter shape of a cross-component filter applied to a chroma coding block (CB), generating a first intermediate CB by applying a loop filter to the chroma CB, and generating a second intermediate CB by applying, to a corresponding luma CB, the cross-component filter applied to the chroma CB and having the determined filter shape. The method further includes determining a filtered chroma CB based on the first intermediate CB and the second intermediate CB by combining the loop filtered chroma CB with the cross-component filtered luma CB, and generating coded information of the chroma CB in a coded video bitstream. Determining the filter shape includes determining the filter shape of the cross-component filter based on the number of the filter coefficients and based on at least one of (i) the chroma subsampling format or (ii) the chroma sample type.

Abstract: A machine learning model trained with a triplet loss function classifies input strings into one of multiple hierarchical categories. The machine learning model is pre-trained using masking language modeling on a corpus of unlabeled strings. The machine learning module includes an attention-based bi-directional transformer layer. Following initial training, the machine learning model is refined by additional training with a loss function that includes cross-entropy loss and triplet loss. This provides a deep learning solution to classify input strings into one or more hierarchical categories. Embeddings generated from inputs to the machine learning model capture language similarities that can be visualized in a cartesian plane where strings with similar meanings are grouped together.

Abstract: The present invention belongs to the field of petrochemical industry, and discloses a method for selective hydrogenation of butadiene extraction tail gas and a selective hydrogenation apparatus thereof.

Abstract: This application relates to a file loading method performed at an electronic device, and a non-transitory computer-readable storage medium thereof. The method including: receiving, in response to a user operation, an instruction for loading a target file; determining an associated feature of at least one piece of resource information in the target file; determining a type of the resource information according to the associated feature of the resource information; and loading the resource information by using a loading algorithm corresponding to the type of the resource information.

Abstract: A method (700) of biasing a tunable laser (310) during burst-on and burst-off states includes receiving a burst mode signal (514) indicative of the burst-on state or the burst-off state and when the burst mode signal is indicative of the burst-on state: delivering a first bias current (IGAIN) to an anode of a gain-section diode (590a) disposed on a shared substrate of the tunable laser; and delivering a second bias current (IPH) to an anode of phase-section diode (590b) disposed on the shared substrate. The second bias current is less than the first bias current. When the burst mode signal transitions to be indicative of the burst-off state, the method also includes delivering the first bias current to the anode of the gain-section diode; and delivering the second bias current to the anode of the phase-section diode wherein the first bias current is less than the second bias current.

Abstract: A coal uncovering construction method for blasting large cross-section gas tunnels includes: analyzing stress distribution characteristics in front of a tunnel boring working face, and then determining a thickness calculation model of a reserved rock wall based on a limit equilibrium theory; establishing a tunnel model, simulating a construction condition and analyzing a construction result, and determining a thickness of the reserved rock wall; and fixing a detonator through a fixed sand ring, fitting the detonator with a construction hole by adjusting an adjustable protective plate, then embedding the detonator into a blast hole, and blasting the detonator for tunnel construction. Furthermore, an extension ring is fixed between the fixed sand ring and the adjustable protective plate.

Abstract: The present disclosure relates to generating a complex entity index based on a combination of atomic and deep learned attributes associated with instances of a complex entity. For example, systems described herein generate a multi-dimensional representation of entity instances based on evaluation of digital content associated with the respective entity instances. Systems described herein further generate an index representation in which similarity of entity instances are illustrated and presented via an interactive presentation that enables a user to traverse instances of an entity to observe similarities and differences between instances of an entity that have similar embeddings to one another within a multi-dimensional index space.

Abstract: This disclosure describes a machine learning system that includes a contrastive learning based two-tower model for retrieval of relevant chemical reaction procedures given a query chemical reaction. The two-tower model uses attention-based transformers and neural networks to convert tokenized representations of chemical reactions and chemical reaction procedures to embeddings in a shared embedding space. Each tower can include a transformer network, a pooling layer, a normalization layer, and a neural network. The model is trained with labeled data pairs that include a chemical reaction and the text of a chemical reaction procedure for that chemical reaction. New queries can locate chemical reaction procedures for performing a given chemical reaction as well as procedures for similar chemical reactions. The architecture and training of the model make it possible to perform semantic matching based on chemical structures. The model is highly accurate providing an average recall at K=5 of 95.9%.

Abstract: Performing collaborative search engine searching. The method includes receiving user input at a user interface for performing a plurality searches on a first search engine. The method further includes receiving user input at the user interface applying one or more augmentation AI models to searches in the plurality of searches. The method further includes creating a shareable, executable package executable by one or more search engines based on the plurality of searches and the applied AI models that when executed by the search engines causes the search engines to apply the AI models to searches performed at the search engines.

Abstract: An immersion fluid recovery system and an immersion fluid recovery method using said system.

Abstract: The present disclosure relates to methods and systems for searching and finding one or more tables that contain an answer to a query within documents. The methods and systems receive the query with query terms and search a table index for one or more related tables to the query terms. The methods and systems locate an answer to the query in the cells of the related tables and provide an output with the answer highlighted in the cells of the related tables in response to the query.

Abstract: The present disclosure relates to methods and systems for converting Portable Document Format (PDF) documents to LaTeX files. The methods and systems use machine learning models to identify and extract PDF portions of a PDF document. The methods and systems create a LaTeX file for the PDF document using the PDF portions extracted by the machine learning models. The methods and systems provide an output with the LaTeX file for the PDF document. The LaTeX file is used to perform different actions on the PDF document.

Abstract: The disclosure belongs to the field of genetic engineering and discloses an expression cassette of a gene including overlapping open reading frames and an application thereof in an insect cell. The expression cassette includes from 5? to 3? and operably linked: a promoter capable of driving transcription in the insect cell; an artificially constructed sequence; overlapping open reading frames missing only a first translation start codon; wherein the artificially constructed sequence includes a first intron and a second intron with splicing activity in the insect cell, the first intron and the second intron share a 5? part or a 3? part, and the artificially constructed sequence does not include a translation start codon; during a post-transcriptional processing process, through an alternative splicing function of the first intron and the second intron, a translation start codon AUG can be formed.

Abstract: Contrast agents, compositions including contrast agents, methods of forming contrast agents, and methods of imaging. Contrast agents may have a desirable solubility in liquids, such as aqueous liquids. Methods of forming contrast agents may include contacting a polymer that includes anhydride functional groups with one or more compounds. Methods of imaging may include administering to patients a contrast agent or composition including a contrast agent.

Abstract: The present invention relates to the field of disease therapy and immunology. Specifically, disclosed are an anti-CD73 antibody or an antigen-binding fragment thereof, a nucleic acid molecule encoding same, an immunoconjugate comprising same, a bispecific molecule and a pharmaceutical composition, as well as use thereof in enhancing immune response and/or treating tumors.

Abstract: Claim verification is facilitated by identifying a selection of textual content within a user interface, accessing a claim detection module, inputting the textual content into the claim detection module to detect one or more claims within the selection of textual content, accessing an evidence extraction module, using the evidence extraction module to automatically search one or more reference repositories for one or more related references that have content that is related to the detected one or more claims, automatically determining whether the content in the one or more related references supports or refutes the one or more claims using a claim verification module, and, in response to determining a set of references of the one or more related references supports or refutes the one or more claims, presenting a support indicator or a refute indicator within the user interface in association with the one or more claims.

Abstract: Disclosed herein is a model flow that generates eligibility criteria for a clinical trial based on eligibility criteria associated with a protocol title of the trial. Unlike standard black-box generation models, the techniques disclosed herein leverage existing knowledge to enhance the title. The enhanced title also acts as an intermediate between the title and the generated criteria clauses, enabling explicit control of the generated content as well as an explanation of why the generated content is relevant. The resulting workflow is knowledge-grounded, controllable, transparent, and interpretable.

Abstract: A monitoring system operable to monitor an oilfield additive system having multiple components. The oilfield additive system is operable to transfer an additive-containing substance for injection into a wellbore. The monitoring system includes sensors each associated with, and operable to generate information related to an operational parameter of, a corresponding one of the oilfield additive system components. The monitoring system also includes a monitoring device in communication with the sensors and operable to record the information generated by the sensors to generate a database. The database includes information indicative of maintenance aspects of the oilfield additive system and/or the oilfield additive system components.

Abstract: The methods and systems may automatically generate criteria for the different sections of the protocol document for a clinical study. The methods and systems use machine learning models to identify medical articles that are associated with the clinical study of a protocol document. The machine learning models analyze the medical articles and generate recommended criteria for the different sections of the protocol document based on the analysis.