Abstract: A method for automatically generating a response to a current request for information about an electronic document associated with a particular domain of knowledge includes interpreting, using a first language processing machine learning model, the electronic document to obtain interpreted data. The method includes selecting, based on the current request, a subset of feedback data included in a first knowledge store and selecting, based on the current request, a subset of domain data stored in a second knowledge store. The method includes injecting a prompt into the first language processing machine learning model or a second language processing machine learning model based on the current request, the subset of feedback data, the subset of domain data, and the interpreted data. The method includes generating, by the first language processing machine learning model or the second language processing machine learning model, the response to the request based on the injecting.

Abstract: A system for automated tax return analysis that streamlines the process of examining and optimizing tax returns. The system employs a partial tax return interpretation engine that uses natural language processing to analyze tax data from multiple years. This data is fed into a genAI module, which compares the processed information and identifies changes over time. The system's knowledge store, containing up-to-date tax rules, works in tandem with a tax situation identifier to cross-reference the detected changes and pinpoint relevant tax situations. Based on these findings, a deductions identifier determines applicable tax deductions. A report generator produces a human-readable document outlining the detected tax situations and potential deductions.

Abstract: Aspects of the present disclosure relate to automated evaluation of electronic datasets. Embodiments include receiving one or more rules related to evaluation of electronic datasets. Embodiments further include generating, via an embedding model, embedding representations of the one or more rules. Embodiments further include receiving an electronic dataset. Embodiments further include identifying a rule that is applicable to the electronic dataset based on using a machine learning model configured to search the embedding representations of the one or more rules based on the electronic dataset. Embodiments further include evaluating, using the machine learning model or an additional machine learning model, the electronic dataset based on the identified rule.

Abstract: Aspects of the present disclosure relate to assisting users in completing forms. Embodiments include retrieving data associated with a form comprising a total number of fields of the form and an indication of a level of complexity of a field of the form. Embodiments further include retrieving data associated with a user comprising a number of fields of the form the user has completed and an amount of time the user has spent completing a respective field of the form. Embodiments further include providing the data associated with the form and the data associated with the user to a machine learning model, and predicting an amount of user progress in completing the form, or a an amount of time required for the user to complete a given field of the form. Embodiments further include receiving the prediction from the machine learning model.

Abstract: Aspects of the present disclosure relate to assisting users in completing forms. Embodiments include retrieving data associated with a form comprising a total number of fields of the form and an indication of a level of complexity of a field of the form. Embodiments further include retrieving data associated with a user comprising a number of fields of the form the user has completed and an amount of time the user has spent completing a respective field of the form. Embodiments further include providing the data associated with the form and the data associated with the user to a machine learning model, and predicting an amount of user progress in completing the form, or a an amount of time required for the user to complete a given field of the form. Embodiments further include receiving the prediction from the machine learning model.

Abstract: Systems and methods for detecting errors in a data transfer uses a machine learning model to identify potential anomalies in the data transfer based on metadata. Mismatches between input data from the data transfer and output data after importing the data transfer may additionally be identified. User review and correction of data errors and potential anomalies identified using the machine learning model may be proactively prompted to ensure any errors or discrepancies are addressed before finalizing the import of the data transfer. User corrections are further used to retrain the machine learning model to enable continuous improvement and learning from the data transfer process.

Abstract: A processor may receive a data submission made through the UI. The data submission may lack data in at least one blank field provided in the UI for entering information in which no information has been entered. The processor may classify the data submission as having at least one data submission type using at least one machine learning (ML) process. The processor may determine at least one required field for the at least one data submission type. The at least one required field may require information to be entered therein. The processor may determine that the at least one blank field is also the at least one required field. The processor may cause the UI to indicate that the at least one blank field is also the at least one required field.

Abstract: To address post-booking and other issues, an application may be run on a user device, such as a mobile device, to provide improved, real-time travel organization and messaging. Some embodiments may also be configured to create, maintain, update, and delete a trip container to which trip content can be automatically or manually associated. In some instances, a user may be required to pay a fee to download the application and/or be required to pay a periodic subscription fee to facilitate ongoing functionality of the application. In addition to or instead of downloading the application, hardware (e.g., circuitry), firmware and/or other particular machine components can be configured to implement some or all aspects of the application.

Abstract: A method includes identifying device description files corresponding to first and second field devices associated with an industrial process control system. The method also includes comparing multiple field device characteristics of the first and second field devices using the device description files. The method further includes identifying any differences between the device characteristics of the first field device and the device characteristics of the second field device. In addition, the method includes determining a compatibility of the first and second field devices based on any identified differences. The field device characteristics can relate to field device attributes, field device function blocks, and function block parameters of the first and second field devices.

Abstract: A method includes identifying device description files corresponding to first and second field devices associated with an industrial process control system. The method also includes comparing multiple field device characteristics of the first and second field devices using the device description files. The method further includes identifying any differences between the device characteristics of the first field device and the device characteristics of the second field device. In addition, the method includes determining a compatibility of the first and second field devices based on any identified differences. The field device characteristics can relate to field device attributes, field device function blocks, and function block parameters of the first and second field devices.

Abstract: To address post-booking and other issues, an application may be run on a user device, such as a mobile device, to provide improved, real-time travel organization and messaging. Some embodiments may also be configured to create, maintain, update, and delete a trip container to which trip content can be automatically or manually associated. In some instances, a user may be required to pay a fee to download the application and/or be required to pay a periodic subscription fee to facilitate ongoing functionality of the application. In addition to or instead of downloading the application, hardware (e.g., circuitry), firmware and/or other particular machine components can be configured to implement some or all aspects of the application.

Abstract: Provided are methods and compositions for reducing the toxicity of certain hydrophobic therapeutic agents, especially polyene antibiotics, in particular, Amphotericin B (AmB), and therapeutics such as paclitaxel, tamoxifen, an acylated prodrug or an acylated cis-platin, by incorporating these agents within micelles comprising an amphiphilic block-forming copolymer. Where the polyene is amphotericin B, desirably the spacer is an alkyl molecule of aabout 2 to about 8 carbon atoms, desirably 6 carbon atoms, and the core is an N-alkyl molecule of about 8 to about 28 carbon atoms, desirably 12 to 22 carbon atoms, advantageously, 12 to 18 carbon atoms, and as specifically embodied, 18 carbon atoms (stearate moiety). For the formulation of a larger polyene, the spacer and core are proportionately larger than those for amphotericin B. As specifically exemplified herein, the polymer backbone is a PEO of about 270 units with about 10-30 core-forming PLAA subunits, and advantageously about 14-24.

Abstract: A redox flow battery 1 has a stack of individual cells, shown diagrammatically as a single cell 1, with anolyte and catholyte compartments 2,3 divided from each other by an ionically selective and conductive separator 4 and having respective electrodes 4,5. The battery has anolyte and catholyte tanks 6,7, with respective pumps 8,9 and a pipework 10, 11. In use, the pumps circulate the electrolytes An,Ca to and from the tanks 8,9, to the compartments 2,3 and back to the tanks. Electricity flows to a load L. The electrolyte lines are provided with tappings 21,22 via which fresh electrolyte F can be added and further tappings 23,24 via which spent electrolyte S can be withdrawn, the respective tappings being for anolyte and catholyte. On recharging, typically via a coupling 25 for lines 26 to all the tappings, a remote pump 27 pumps fresh anolyte and fresh catholyte from remote storages 28 and draws spent electrolyte to other remote storages 29.

Abstract: Data items are represented by trees and stored in a database, the collection of data items defining a forest. Queries and masks are also represented by trees. A method for navigating the forest of data items is disclosed in the context of a graphical user interface. A set of operations on trees are defined such that the data items can be queried on the basis of structure as well as node values. That is, the query can include a specification of the relationship between nodes in a tree, as well as the data in the nodes themselves. Exemplary implementations of such operations are disclosed in the context of a database update procedure. Additionally disclosed are methods for efficiently storing and processing the forest of data items.

Abstract: Data items are represented by trees and stored in a database, the collection of data items defining a forest. Queries and masks are also represented by trees. A method for navigating the forest of data items is disclosed in the context of a graphical user interface. A set of operations on trees are defined such that the data items can be queried on the basis of structure as well as node values. That is, the query can include a specification of the relationship between nodes in a tree, as well as the data in the nodes themselves. Exemplary implementations of such operations are disclosed in the context of a database update procedure. Additionally disclosed are methods for efficiently storing and processing the forest of data items.

Abstract: Data items are represented by trees and stored in a database, the collection of data items defining a forest. Queries and masks are also represented by trees. A method for navigating the forest of data items is disclosed in the context of a graphical user interface. A set of operations on trees are defined such that the data items can be queried on the basis of structure as well as node values. That is, the query can include a specification of the relationship between nodes in a tree, as well as the data in the nodes themselves. Exemplary implementations of such operations are disclosed in the context of a database update procedure. Additionally disclosed are methods for efficiently storing and processing the forest of data items.

Abstract: Provided are methods and compositions for reducing the toxicity of certain hydrophobic therapeutic agents, especially polyene antibiotics, in particular, Amphotericin B (AmB), and therapeutics such as paclitaxel, tamoxifen, an acylated prodrug or an acylated cis-platin, by incorporating these agents within micelles comprising an amphiphilic block-forming copolymer. Where the polyene is amphotericin B, desirably the spacer is an alkyl molecule of aabout 2 to about 8 carbon atoms, desirably 6 carbon atoms, and the core is an N-alkyl molecule of about 8 to about 28 carbon atoms, desirably 12 to 22 carbon atoms, advantageously, 12 to 18 carbon atoms, and as specifically embodied, 18 carbon atoms (stearate moiety). For the formulation of a larger polyene, the spacer and core are proportionately larger than those for amphotericin B. As specifically exemplified herein, the polymer backbone is a PEO of about 270 units with about 10-30 core-forming PLAA subunits, and advantageously about 14-24.

Abstract: A method is provided for treating a Th1 mediated disease state by administration to a subject of a slow release vehicle such as a liposome or microsphere formulation containing an antigenic peptide and a Th1 specific immunomodulator wherein the antigenic peptide contains a T cell epitope and is released from the vehicle at a rate in the range from about 10 to 2 weight percent of the peptide in 24 hours at 37° C.

Abstract: A heterologous sandwich immunoassay has been developed for human TF antigen using a monoclonal antibody as the catcher and labelled peanut agglutinin as the probe. Since human TF antigen is shed by tumor cells, a positive determination of the TF antigen in a patient sample indicates the presence of cancer. The test can also be used to monitor the course of conventional chemotherapy or radiotherapy by monitoring the amount of TF antigen in a fluid sample from a patient being so treated. Because of the sensitivity of the assay method, cancer can be detected in very early stages by the assay method of the present invention.

Abstract: Human tumor associated Thomsen-Friedenreich (TF) antigen is purified from adenocarcinoma conditioned media, adenocarcinoma cell detergent extracts or plural effusion fluid by affinity chromatography using an insolubilized TF-specific monoclonal antibody, MAb 49H.8. The TF antigen is a glycoprotein characterized by a non-cryptic Gal .beta.(1.fwdarw.3) GalNAc epitope, a molecular weight in excess of 1,000,000 daltons, and extractability with perchloric acid, the epitope being sensitive to alkali and periodate but resistant to acid. A heterologous sandwich immunoassay has been developed for human TF antigen using a monoclonal antibody as the catcher and labelled peanut agglutinin as the probe. Since human TF antigen is shed by tumor cells, a positive determination of the TF antigen in a patient sample indicates the presence of cancer.