Abstract: A molecule representation is extracted from a document and associated with the document in a metadata database. For example, an image of a molecular structure may be extracted from a document and stored in the metadata database in a text-based representation such as SMILES. The metadata database may be searched to identify documents that mention a particular molecule. Continuing the example, the metadata database may be searched with a SMILES representation to identify the document and other documents that refer to the same molecule. The metadata database may index documents based on different types of molecule representations, including text-based, image-based, graph-based, name, abbreviation, etc. This allows search over multiple representations of a molecule, improving accuracy and thoroughness. These improvements reduce the time and computational resources needed to search for documents that refer to a particular molecule.

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: 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: The present disclosure relates to efficiently receiving and processing input tasks in a way that is scalable and which reduces both the quantity of tokens processed by a foundation model (e.g., an LLM) as well as the number of API calls that are made in processing the input tasks. A system batches a set of inputs to provide as a single batch of input(s) into an LLM. The system generates one or more permutations of the batched input(s) to determine outputs based on variable orders in which the input data is provided within the respective permutations of the batched inputs. The system further may eliminate one or more of the data inputs within the respective batches to facilitate smaller batched inputs without sacrificing accuracy in a set of outputs generated by the LLM responsive to the batch permutations.

Abstract: A baculovirus vector and a use thereof in the preparation of a recombinant adeno-associated virus (rAAV) in an insect cell are provided. The baculovirus vector includes an exogenous gene expression cassette and a stable sequence. The stable sequence is located at a site 5 kb or less from the exogenous gene expression cassette, and the stable sequence is a conserved noncoding element (CNE) sequence or a nucleocapsid assembly-essential element (NAE) sequence. When an insect cell is infected with a recombinant baculovirus (rBV) constructed in this way, after multiple continuous passages, production levels of the rBV and the rAAV still remain relatively stable.

Abstract: An expression cassette containing overlapping open reading frames and an application thereof are provided. The overlapping open reading frames are overlapping open reading frames of a first ORF and a second ORF and include in sequence from a 5? end to a 3? end: a first promoter at least used to drive gene transcription of the first ORF; a 5? part of a gene of the first ORF; an intron; and a 3? part of a gene of the second ORF, the intron including a second promoter used only to drive gene transcription of the second ORF. By arranging two promoters in a single expression cassette in the disclosure, the two promoters are used to drive the expression of proteins of the overlapping reading frames and regulate the relative expression time and expression intensity of different proteins.

Abstract: The present disclosure relates to methods and systems for sharing with a plurality of users a chat session that uses large language models to provide responses for input messages received for the chat session. The methods and systems provide access to the chat session to the users and update the chat session in response to any changes made to the chat session by any of the users. The methods and systems allow the users to resume the chat session at a future time using the chat session history.

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: The present disclosure relates to methods and systems for automatically generating documents for a specific topic using large language models. The methods and systems receive an input query that identifies a topic for the document. The methods and systems automatically generate, using the large language models, a framework for the document with sections and subsections for the document. The methods and systems write the document, using the large language models, and provide references for the data sources used to obtain the data that the large language model used to write the document.

Abstract: The present disclosure relates to methods and systems for using large language models to support research activities. The methods and systems include a copilot engine that creates input prompts to provide to the large language model to use in generating responses to input messages. The copilot engine infers an intent of the input messages and sends the intent with the input message in the input prompt to the large language model. The large language model generates different types of responses for different intents.

Abstract: The present disclosure relates to methods and systems for sharing with a plurality of users a chat session that uses large language models to provide responses for input messages received for the chat session. The methods and systems provide access to the chat session to the users and update the chat session in response to any changes made to the chat session by any of the users. The methods and systems allow the users to resume the chat session at a future time using the chat session history.

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: A relevance system ranks a set of medical studies based on a relevance of each medical study in the set of medical studies to a patient profile. The relevance system includes a relevance model. The relevance model determines a relevance of each medical study to the patient profile based on a semantic relationship score, a concept relationship score, and a term-occurrence score. The semantic relationship score is a measure of a similarity in semantic meaning of a medical study and a patient profile. The concept relationship score is a measure of the closeness of medical concepts in a medical study to medical concepts in a patient profile. The term-occurrence score is a measure of occurrences of terms in a medical study that also appear in a patient profile and the statistical significances of the terms.

Abstract: Disclosed are techniques for an AI system with a large language mode (LLM) with improved accuracy and reliability in solving mathematical problems. An initial query is transformed into a template query by replacing the original input values with variables. Multiple prompts are sent to the LLM, each being different from one another, and contextually related to the template query. Multiple results are responsively received from the LLM, each result including an analytical expression to solve the mathematical problem. Each of the expressions is evaluated using a numerical evaluation tool with variables of the expression being assigned a common set of randomly sampled values. A consensus is achieved when the evaluated expressions satisfy a consensus condition, such as when all outputs match consistently over N experiments or trials. After the consensus condition is reached, the original inputs are evaluated with one or more of the expressions, and the solution is output.

Abstract: Machine learning to predict a layout type that each of a plurality of portions of a document appears in. This is done even though the computer-readable representation of the document does not contain information at the granularity of the prediction to be made that identifies which layout type that each of the plurality of document portions belongs in. For each of a plurality of the portions, the machine-learning system predicts the layout type that the respective portion appears in, and indexes the document using the predictions so as to result in a computer-readable index. The index represents a predicted layout type associated with each of the plurality of portions of the document. Thus, the index can be used to search based on position of a searched term within the document.

Abstract: The disclosure discloses an expression cassette for expressing a gene including overlapping open reading frames in an insect cell and an application thereof. 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; the overlapping open reading frames missing only a first translation start codon; wherein the artificially constructed sequence includes a native or engineered intron with splicing activity in the insect cell, the intron includes ATG or the intron is located between any two adjacent nucleotides in ATG. A recombinant adeno-associated virus vector including the expression cassette of the disclosure regulates relative expressions of VP1, VP2, and VP3 proteins, and relative expressions of Rep78 and Rep52 proteins by using a designed intron sequence and through an intron splicing function for large-scale production of rAAV.

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: An integrated pressure condensing boiler is provided which relates to the technical field of boilers. The integrated pressure condensing boiler includes a pressure-bearing housing, a heat-exchange furnace arranged in the pressure-bearing housing, a combustion chamber communicating with the heat-exchange furnace and cooling tube groups fixed in the heat-exchange furnace. Heat-exchange medium flows from bottom to top in the pressure-bearing housing and in the cooling tube groups, and exchanges heat with high-temperature flue gas flowing from top to bottom in the heat-exchange furnace, thus achieving a counterflow heat exchanging. The heat-exchange furnace includes a multi-stage heat-exchange chamber with each heat-exchange chamber being cylindrical. The heat-exchange chambers are arranged in sequence from top to bottom to achieve a flue gas diffusing manner that high-temperature flue gas diffuses from center part to periphery and then gathers from periphery to center part.

Abstract: The present disclosure relates to utilizing a dynamic knowledge graph enrichment system to dynamically and automatically maintain knowledge graphs shared between groups of user identifiers with up-to-date findings and discoveries. In particular, the dynamic knowledge graph enrichment system changes static shared knowledge graphs into dynamically evolving ones utilizing statistical guarantees that automatically incorporate new edge connections into a shared knowledge graph after verifying the reliability and veracity of the proposed edge connections being offered. Further, the dynamic knowledge graph enrichment system facilitates forming new connections between different shared knowledge graphs that previously went undetected by flexibly facilitating exploration over multiple knowledge graphs and providing synergistic knowledge graph updates.

Abstract: A method (600) for tuning a tunable laser (310) includes delivering a bias current (IDBR) to an anode of a distributed Bragg reflector (DBR) section diode (D2) disposed on a shared substrate of the tunable laser and receiving a burst mode signal (440) indicative of a burst-on state or a burst-off state. When the burst mode signal is indicative of the burst-off state, the method includes offsetting the bias current at the anode of the DBR section diode by one of sourcing a push current with the bias current to the anode of the DBR section diode or sinking a pull current away from the bias current at the anode of the DBR section diode. When the burst mode signal is indicative of the burst-on state, the method also includes ceasing any offsetting of the bias current at the anode of the DBR section diode.