Abstract: A method of producing cytopathologic cell samples, the method including insonating a target tissue by ultrasound energy with a focused beam at that generates shear waves within the tissue. A method of producing cytopathologic cell samples, the method including insonating a target tissue by ultrasound energy at a first intensity level during a first period, insonating the target tissue by ultrasound energy at a second intensity level during a second period, wherein the first intensity level is higher than the second intensity level. Related apparatus and methods are also described.

Abstract: Systems and method for generating vehicle recommendations are determined using interaction information. An information data set may be mapped to a first user and include interactions based on a period of time. The interactions may be parsed by a trained machine learning model to determine trends and attributes. A user profile and a user score for different criteria may be compared to vehicle sores of multiple vehicles. Comparing the scores may identify recommended vehicles for the first user which may be transmitted to a user device of the user.

Abstract: Systems and methods for detecting accessibility failures. In some aspects, the system receives a request for evaluating accessibility for a user interface of an updated version of a software application, wherein the request includes the updated and previous versions of the software application, and previous textual data corresponding to the previous version. The system generates audio output by using a screen reader to process the user interface. Textual data is generated by processing the audio output using speech recognition. The system compares the textual data to previous textual data to determine whether feature differences are present between the updated and previous versions. The one or more feature differences are analyzed to identify a feature difference corresponding to an accessibility failure point. In response to identifying the accessibility failure point, the system determines actions for removing the accessibility failure point.

Abstract: In some implementations, a tag library device may receive, from first user devices, an indication of a set of tags with a corresponding set of properties and a corresponding set of rules. The tag library device may build a data structure that stores the set of tags in association with the corresponding set of properties and the corresponding set of rules and may transmit the data structure to second user devices such that a portion of the set of tags are included in a web site published by the second user devices. The tag library device may receive, from a platform associated with the web site, an indication of a set of events associated with the web site. The tag library device may determine statistics based on the set of events and may transmit a report including the statistics to third user devices associated with analytics for the web site.

Abstract: Provided herein are methods for diagnosing functional gastrointestinal disorders such as functional dyspepsia and irritable bowel syndrome, comprising detecting IgG antibodies in a sample obtained from a subject, wherein the IgG antibodies recognise one or more antigens from Streptococcus salivarius. Also provided are kits for detecting IgG antibodies for use in the diagnosis of functional gastrointestinal disorders, and methods for selecting subjects for treatment for functional gastrointestinal disorders.

Abstract: An exemplary process includes determining a desired pore size, selecting an initial pore size greater than the target pore size, manufacturing a porous structure with the initial pore size, forging the porous structure to form a forged part having the desired pore size, and forming an orthopedic device from the forged part.

Abstract: In some implementations, a recommendation system may input text into a machine learning model that was trained using input specific to an organization associated with the text and was refined using input specific to a portion of the organization. The recommendation system may receive, from the machine learning model, a recommendation indicating one or more visual components, stored in a database associated with the organization, to use with the text. The machine learning model may use natural language processing and sentiment detection to parse the text. Accordingly, the recommendation system may receive the one or more visual components from the database and generate an initial draft including the text and the one or more visual components.

Abstract: A data security and fraud prevention system is configured to transmit a web form to a first device, receive through the web form first data including first user private data associated with a first user, receive a request to share the web form with a second user, create a cache storage and an unique identifier associated with the web form, and mask the first user private data to prevent access to the first user private data by the second user. The data security and fraud prevention system is further configured to encrypt the unique identifier, generate a share session between the first device and a second device associated with the second user, receive through the web form second data including second user private data associated with the second user, mask the second user private data to prevent access to the second user private data by the first user, and aggregate the first data and the second data to complete the web form.

Abstract: Methods and systems for using machine learning models to organize and select modular components for user interface templates. For example, the methods and systems may use machine learning and/or artificial intelligence to generate user interfaces with a preferred number of user input fields and/or pages, in which the preferred number both satisfies any requirements for the user interface (e.g., information, categories of information, etc.), and ensures that all privacy concerns are met.

Abstract: In some implementations, a recommendation system may input text into a machine learning model that was trained using input specific to an organization associated with the text and was refined using input specific to a portion of the organization. The recommendation system may receive, from the machine learning model, a recommendation indicating one or more visual components, stored in a database associated with the organization, to use with the text. The machine learning model may use natural language processing and sentiment detection to parse the text. Accordingly, the recommendation system may receive the one or more visual components from the database and generate an initial draft including the text and the one or more visual components.

Abstract: A data security and fraud prevention system is configured to transmit a web form to a first device, receive through the web form first data including first user private data associated with a first user, receive a request to share the web form with a second user, create a cache storage and an unique identifier associated with the web form, and mask the first user private data to prevent access to the first user private data by the second user. The data security and fraud prevention system is further configured to encrypt the unique identifier, generate a share session between the first device and a second device associated with the second user, receive through the web form second data including second user private data associated with the second user, mask the second user private data to prevent access to the second user private data by the first user, and aggregate the first data and the second data to complete the web form.

Abstract: Methods and systems for using machine learning models to organize and select modular components for user interface templates. For example, the methods and systems may use machine learning and/or artificial intelligence to generate user interfaces with a preferred number of user input fields and/or pages, in which the preferred number both satisfies any requirements for the user interface (e.g., information, categories of information, etc.), and ensures that all privacy concerns are met.

Abstract: In some implementations, a recommendation system may input text into a machine learning model that was trained using input specific to an organization associated with the text and was refined using input specific to a portion of the organization. The recommendation system may receive, from the machine learning model, a recommendation indicating one or more visual components, stored in a database associated with the organization, to use with the text. The machine learning model may use natural language processing and sentiment detection to parse the text. Accordingly, the recommendation system may receive the one or more visual components from the database and generate an initial draft including the text and the one or more visual components.

Abstract: Methods and systems for using machine learning models to organize and select modular components for user interface templates. For example, the methods and systems may use machine learning and/or artificial intelligence to generate user interfaces with a preferred number of user input fields and/or pages, in which the preferred number both satisfies any requirements for the user interface (e.g., information, categories of information, etc.), and ensures that all privacy concerns are met.

Abstract: Methods and systems for a service worker framework are provided herein. When a web application is accessed through a web browsing application, the web browsing application may invoke a service worker specifically created for the web application. The service worker may serve as an intermediary between the web application and the web browsing application and may intercept application data transmitted between the web browsing application and the web application. For example, the service worker may extract and encrypt any identification data included in the application data when it is received by a web browsing application. The service worker may store the encrypted identification data, for example, within the cache of the web browsing application and send modified application data to the web application (e.g., excluding the identification data).

Abstract: Methods and systems for using machine learning models to organize and select modular components for user interface templates. For example, the methods and systems may use machine learning and/or artificial intelligence to generate user interfaces with a preferred number of user input fields and/or pages, in which the preferred number both satisfies any requirements for the user interface (e.g., information, categories of information, etc.), and ensures that all privacy concerns are met.

Abstract: A data security and fraud prevention system is configured to transmit a web form to a first device, receive through the web form first data including first user private data associated with a first user, receive a request to share the web form with a second user, create a cache storage and an unique identifier associated with the web form, and mask the first user private data to prevent access to the first user private data by the second user. The data security and fraud prevention system is further configured to encrypt the unique identifier, generate a share session between the first device and a second device associated with the second user, receive through the web form second data including second user private data associated with the second user, mask the second user private data to prevent access to the second user private data by the first user, and aggregate the first data and the second data to complete the web form.

Abstract: Methods and systems for using machine learning models to organize and select modular components for user interface templates. For example, the methods and systems may use machine learning and/or artificial intelligence to generate user interfaces with a preferred number of user input fields and/or pages, in which the preferred number both satisfies any requirements for the user interface (e.g., information, categories of information, etc.), and ensures that all privacy concerns are met.

Abstract: The present invention is directed to, among other things, processes for purifying polyether polyols via treatment with an ion exchange resin in which the ion exchange resin is disposed in a container that is operated liquid-full.

Abstract: A device receives user interface information associated with a user interface to be provided for a particular platform, and receives design information for a design of the user interface to be provided for the particular platform. The device receives a request to visually compare the user interface information and the design information, and utilizes, based on the request, a trained machine learning model to visually compare the user interface information and the design information. The device generates information, indicating defects in the user interface information, based on utilizing the trained machine learning model to visually compare the user interface information and the design information, where the defects include user interface information that does not visually match the design information. The device provides the information indicating the defects in the user interface information.