Abstract: The invention provides novel glucocorticosteroids, glucocorticosteroid-linkers and antibody drug conjugates (ADC's) comprising an antibody or antibody fragment which binds to an antigen expressed on immune cells, optionally an antigen expressed on human immune cells. In some instances the ADCs comprise an anti-human VISTA (V-region Immunoglobulin-containing Suppressor of T cell Activation (1)) antibody or anti-VISTA antigen-binding antibody fragment which binds to VISTA expressing cells at physiologic pH having a short serum half-life (?24-72 or 24-48 or 12-24 hours or less in a human VISTA knock-in rodent or ((?1-3.5 days or less in a human or non-human primate). In some instances these ADCs have a rapid onset of action and are potent for prolonged duration as they are very effectively internalized by immune cells in large amounts where they are cleaved releasing large amounts of active steroid payload.

Abstract: A method and system for scanning claims data, the method comprising receiving, by a computing system, contract details associated with claims, receiving, by the computer system, prescription transactions data associated with the claims, parsing, by the computer system, the transactions data into column values, and executing, by the computer system, analytics on the parsed transactions. The analytics include comparing the parsed transactions against the contract details for accurate pricing, fees, and accepted treatment protocols concerning dose and quantity, comparing the parsed transactions with independent pricing data that is based on third-party pricing data and drug information, identifying material errors in the parsed transactions, determining withholdings from payment of the claims for a portion above a tolerance level based on the identified material errors. The method further comprising presenting, by the computer system, results of the execution of the analytics to a portal.

Abstract: A paperboard container is provided for receiving a sealed lid. The container includes a bottom panel, a sidewall, and an upper rim. The sidewall extends upward from the bottom panel to define an interior of the container. The upper rim extends outward from the sidewall. The upper rim includes an overlapping seam having a first overlapping portion and a second overlapping portion. The first overlapping portion of the upper rim wraps around the second overlapping portion. The first overlapping portion includes a bonding tape positioned on an inner surface and an outer surface thereof. The first overlapping portion includes a corner cut defining at least a portion of an outer edge of the first overlapping portion.

Abstract: The invention relates to non-systemic TGR5 agonist useful in the treatment of chemotherapy-induced diarrhea, diabetes, Type II diabetes, gestational diabetes, impaired fasting glucose, impaired glucose tolerance, insulin resistance, hyperglycemia, obesity, metabolic syndrome, ulcerative colitis, Crohn's disease, disorders associated with parenteral nutrition especially during short bowel syndrome, and irritable bowel syndrome (IBS), and other TGR5 associated diseases and disorders, having the Formula: where R1, R2, R2?, R3, R4, X1, X2, X3, X4, Q, and n are described herein.

Abstract: A structural assembly for a vehicle includes a vehicle frame distinct from a vehicle body. The vehicle frame includes opposed longitudinal rails. Each rail includes a single, monolithic body having a central internal brace and a pair of opposed ends. One end of the opposed ends is fixed to a first side of the central internal brace and the other end of the opposed ends is fixed to a second side of the central internal brace that is opposite the first side.

Abstract: The present invention relates to a vehicle, which is used in particular for transporting objects, in particular workpieces. Here, preferably one or more sensor devices are provided, by means of which in particular a region surrounding the vehicle is detectable.

Abstract: An apparatus for testing cardiac devices comprises an inflow and an outflow chamber, a mount for supporting a prosthetic valve, and a fluid driving device operable to vary a pressure differential of a fluid between the inflow chamber and the outflow chamber in repeating cycles. The apparatus can comprise a bypass valve to modulate pressure characteristics across the prosthetic valve, reservoirs to maintain a pressure inside the apparatus, and compliance elements to modulate pressure characteristics in the apparatus. Methods for operating the apparatus include controlling the bypass valve to control testing characteristics across the prosthetic device, and methods for monitoring the pressure inside of the apparatus.

Abstract: Coating compositions or paint having a pigment blended with a polymer system including one or more latex polymers, wherein the polymer system contains an alkali-soluble resin having an acid value and molecular weight and provided in a preferably desired amount to demonstrate optimal performance characteristics of washability, stain resistance or scrubability without negatively impacting block resistance, especially when neutralized with a low-volatility base.

Abstract: A cathode for a battery including agglomerates of carbonaceous particles. Each carbonaceous particle includes a plurality of porous regions nested within each other. Each of the respective porous regions is characterized by one or more of a corresponding porosity or a corresponding pore density and a plurality of carbon fragments disposed across the plurality of porous regions. Each carbon fragment is separated from an adjacent carbon fragment by mesopores.

Abstract: A data pipeline validation system and method configured to partially automate testing of data pipelines in a distributed computing environment. The system includes a data pipeline analytic device equipped with various modules, such as a query generation module, data frame comparison module, and metadata management module. The query generation module employs natural language processing techniques to analyze configuration entries and dynamically generate SQL queries tailored to specific test cases. The data frame comparison module compares the results of different test cases using distributed collections, enabling parallel processing and efficient result comparison. The metadata management module captures and stores relevant metadata for traceability and auditing purposes. The system facilitates comprehensive validation of data pipelines, enabling organizations to ensure the accuracy, reliability, and integrity of data.

Abstract: This application describes, among other things, machine-learning models for performing specific clinical tasks. An example method includes receiving a prompt at a first computing system in communication with a machine-learning model trained to assist in performing a clinic task that includes generating a report of a patient's medical records, guiding a patient through a care plan, creating patient care guidelines based on a patient's health profile, identifying patients requiring follow-up at a hospital, identifying changes in a standard of care for a disease setting, or evaluating unstructured data associated with a patient to identify a cohort of similar patients. Based on the prompt, a natural language response is generated that is responsive to the prompt and is based on an analysis by the machine-learning model of a repository of data that is determined to be relevant to the prompt. And the natural language response is provided to second computing system.

Abstract: This application describes, amongst other things, methods and systems for building and deploying agents. An example method includes obtaining orchestration data about a set of task-specific components selected to provide a response to the prompt, where each respective task-specific components in the set of task-specific components is configured to assist with a respective clinical task of the one or more clinical tasks. The method further includes, determining an order in which each respective task-specific components of the set of task-specific components should be utilized to prepare a complete response to the prompt that address the one or more clinical tasks based on the obtained orchestration data about the set of task-specific components. The method also includes, in accordance with the determined order, providing first data related to the prompt to a first task-specific component and receiving a first response from the first task-specific component.

Abstract: This application describes, among other things, systems and methods for deploying a task-specific machine-learning model. An example method includes receiving a prompt associated with one or more commands and a plurality of tokens. A first task-specific machine-learning model is identified based on a first command of the one or more commands. Some or all of the tokens of the plurality of tokens are applied to a node associated with the first task-specific machine-learning model, and a plurality of restricted data is received. Based on evaluating the plurality of restricted data, a correlation between the first node and a second node is determined. If the correlation satisfies a threshold condition, a plurality of text data different than the prompt is generated, otherwise the some or all of the tokens are again provided to the first node. Some or all of the tokens are then traversed and applied to the second node.

Abstract: This application describes, among other things, systems and methods for configuring a task-specific machine-learning model. An example method includes, based on a request to modify a machine-learning model for performing a clinical task, retrieving a corresponding node architecture defining conditional logic for performing the clinical task. The conditional logic is executed based on a first order, including an input node, an output node, and an intermediate node, of a first set of interconnected nodes including a data source node, a machine-learning model node, and a conditional logic node. A representation is generated including a first feature for configuring conditional logic of the node architecture and a second feature for configuring a parameter of a node in the first set of interconnected nodes. A selection of the first or second feature defines a second order of a second set of interconnected nodes, causing the node architecture's conditional logic to be updated.

Abstract: This application describes, among other things, systems and methods for interacting with a task-specific orchestration. An example method includes obtaining medical data from one or more data collections. A set of user interface elements is presented at a user interface, where each respective user interface element of the set of user interface elements represents a respective task-specific orchestration that includes one or more respective machine-learning models fine-tuned for a specific task or domain based on the medical data. When a user interface element representing a respective task-specific orchestration is selected, at least some of the medical data is provided to the respective task-specific orchestration, and a different user interface is presented for communicating with the respective task-specific orchestration. Based on receiving a prompt at the different user interface, a response object is generated by the task-specific orchestration based on the prompt and at least some of the medical data.

Abstract: This application describes, among other things, methods of selecting a task-specific machine-learning model for addressing a clinical task. An example method includes receiving a prompt from a user. Based on determining that the prompt requests assistance with a clinical task, a machine-learning model trained to select from among a plurality of task-specific machine-learning models each trained to assist with one of a plurality of clinical tasks selects a respective task-specific machine-learning model from among the plurality of task-specific machine-learning models based on the prompt. The prompt is provided to the selected task-specific machine-learning model. And a response received from the selected task-specific machine-learning model is provided to the user.

Abstract: This application describes, among other things, methods of generating task-specific agent modules based on user requests. An example method includes receiving a request from a user for performance of a specific task. In response to the request, an agent module to perform the specific task is generated. The generating includes selecting a set of agent building blocks from a plurality of available agent building blocks, where each agent building block in the plurality of available agent building blocks has a respective assigned function, and connecting the set of agent building blocks to form the agent module. The agent module is caused to be executed, and information from the request is provided to the agent module. Based on providing information from the request to the agent module, a response for performing the specific task is received and provided to the user.

Abstract: A portable aquatic exercise device for performing callisthenic workouts using water weight includes an outer bag having an outer surface and an inner surface wherein the inner surface of the outer bag creates an interior. The outer bag has a top end and a bottom end. The top end has an aperture and the bottom end has an opening. The opening has a draw string positioning the opening from an open position to a closed position. A pair of ropes is coupled to the outer surface of the outer bag. An inner bag is positioned within the interior of the outer bag. An inside of the inner bag is fills with water wherein expanding against the outer bag. A hole of the inner bag has an insert. A cap is positioned on the aperture of the outer bag and engages by threading to the insert of the inner bag.