Abstract: In one aspect, the present teachings provide a system for performing cytometry that can be operated in three operational modes. In one operational mode, a fluorescence image of a sample is obtained by exciting one or more fluorophore(s) present in the sample by an excitation beam formed as a superposition of a top-hat-shaped beam with a plurality of beams that are radiofrequency shifted relative to one another. In another operational mode, a sample can be illuminated successively over a time interval by a laser beam at a plurality of excitation frequencies in a scanning fashion. In yet another operational mode, the system can be operated to illuminate a plurality of locations of a sample concurrently by a single excitation frequency, which can be generated, e.g., by shifting the central frequency of a laser beam by a radiofrequency. The detected fluorescence radiation can be used to analyze the fluorescence content of the sample, e.g., a cell/particle.

Abstract: Machine learning framework that extracts actionable insights from disparate data sources include performing operations. A merged feature set is generated by collecting diverse data to generate aggregated data in a unified dataset and performing an autoencoding of the aggregated data to generate compressed data in a low-dimensional latent space. The merged feature set is further generated by merging the first attribute and the second attribute to obtain a merged feature set for the low-dimensional latent space. The operations include selecting a response vector from the merged feature set in the low-dimensional latent space that is aligned with a user query, decoding the response vector into natural language text, executing a large language mode (LLM) to the natural language text and the user query to generate an actionable insight.

Abstract: Systems, devices, and methods for tracking reward associated with content consumption are provided. An example method includes receiving streaming content of at least one content item from a content provider, outputting, via an application being executed on the streaming device, streaming content to a display for playback of the output content, periodically generating a plurality of heartbeat messages during execution of the application. Each heartbeat message is timestamped and includes a header containing information about the at least one content item, and one or more entries indicating a current playback state regarding the output of the streaming content when the heartbeat message is generated. The method further includes transmitting the plurality of heartbeat messages to a user engagement tracking device connected to the user device and receiving a notification indicating a total duration of content output to the display during execution of the application.

Abstract: Aspects of the present disclosure relate to automated detection of duplicate entities in a repository. Embodiments include generating a vector representation of a given entity; comparing the vector representation of the given entity to vector representations of a plurality of entities within a repository to determine a level of similarity for the given entity relative to each of the plurality of entities; selecting a similarity threshold of a set of similarity thresholds for the given entity and a particular entity based on a hierarchical relationship between the given entity and the particular entity, wherein the set of similarity thresholds comprises a sibling threshold, a parent-child threshold, and an ancestor threshold; and determining that the given entity is a duplicate of the particular entity based on a level of similarity between the given entity and the particular entity exceeding the selected similarity threshold.

Abstract: Systems and methods related to improved program guide are provided. In one example, a method includes: receiving a first user request for browsing a program guide for digital programs on a client device, transmitting data corresponding to the program guide to the client device, and displaying the program guide in a user interface. The program guide includes multiple program preview boards, and each program preview board corresponds to a digital program or a recorded digital program and includes information related to the digital program or the recorded digital program. The method further includes providing a first selectable option for the user to enable or disable a first spoiler prevention feature and enabling or disabling the first spoiler prevention feature based on the user's selection. The first spoiler prevention feature is configured to hide a part of the information related to the digital program in the corresponding program preview.

Abstract: Aspects of the present disclosure relate to automated optimization of machine learning models. Embodiments include determining a set of initial configurations for parameters associated with the machine learning model. Embodiments further include selecting a configuration based on the set of initial configurations and an evolutionary selection process comprising excluding configurations that result in a level of performance for the machine learning model that is below a threshold. Embodiments further include executing the machine learning model using the selected configuration.

Abstract: A system and method are provided to perform enhanced content evaluation.

Abstract: Systems and methods related to channel surfing are provided. In one example, a method includes receiving a user request to view presentation of a channel guide on a display, generating a channel guide including a channel list, at least one scroll indicator, and a focus indicator, and communicating the channel guide to the display. The display includes a main display area, a channel list display area overlaid on the main display area, and a focus area. The channel list is displayed in the channel list display area while the primary content of a current channel is being presented in the main display. The method further includes receiving a first user input activating the scroll indicator in a scroll direction, causing the channel identifiers to move in the channel list display area while the primary content continues to be presented in the main display area.

Abstract: Certain aspects of the disclosure provide a method of adaptive information retrieval based on both lexical and semantic relevance. In some aspects, the method includes identifying a plurality of documents based on a context of the query request, assigning an integrated score for each respective document of the plurality of documents based on a semantic score for the respective document and a lexical score for the respective document, and ranking each document of the plurality of documents based on the integrated score.

Abstract: Aspects of the present disclosure relate to automated evaluation of hierarchical documents. Embodiments include generating a canonical representation of each hierarchical path within a document; assigning weights to each hierarchical path within the document based on the canonical representation of the hierarchical path; calculating a first score for each hierarchical path within the document based on: a corresponding weight for the hierarchical path; and identifying one or more errors within the hierarchical path based on the canonical representation of the hierarchical path; calculating a second score for each hierarchical path within the document based on: the corresponding weight for the hierarchical path; and determining whether a value within the canonical representation of the hierarchical path complies with a rule; and calculating a composite score for the document based on the first score and the second score for each hierarchical path within the document.

Abstract: Aspects of the present disclosure relate to automated detection of duplicate entities in a repository. Embodiments include generating a vector representation of a given entity; comparing the vector representation of the given entity to vector representations of a plurality of entities within a repository to determine a level of similarity for the given entity relative to each of the plurality of entities; selecting a similarity threshold of a set of similarity thresholds for the given entity and a particular entity based on a hierarchical relationship between the given entity and the particular entity, wherein the set of similarity thresholds comprises a sibling threshold, a parent-child threshold, and an ancestor threshold; and determining that the given entity is a duplicate of the particular entity based on a level of similarity between the given entity and the particular entity exceeding the selected similarity threshold.

Abstract: Certain aspects of the present disclosure describe a method of information retrieval. In certain aspects, the method includes identifying a set of relevant nodes of a document graph embedding semantic units associated with the document based on a document search query. The method further includes reconstructing a structural context for each relevant node in the set of relevant nodes. The method further includes processing the set of relevant nodes and the structural context of each relevant node with a large language model to generate a contextual response to the document search query.

Abstract: A system and method are provided for personalizing large language models in query systems.

Abstract: A system and method are provided for personalizing large language models in query systems.

Abstract: At least one processor can generate a classification of a document including a plurality of sections according to at least one of a structure of at least one of the plurality of sections, a hierarchy of the plurality of sections, and a content of at least one of the plurality of sections. The at least one processor can determine a chunking strategy optimized for the classification from among a plurality of available chunking strategies, divide the document into a plurality of chunks according to the chunking strategy, and generate respective vector representations of respective ones of the plurality of chunks. At least one database can contain the vector representations and supply the vector representations to retrieval augmented generation (RAG) operations performed by at least one large language model (LLM).

Abstract: Certain aspects of the disclosure provide systems and methods for validating application programing interface requests, including GraphQL requests. In certain aspects, a method of validation includes assessing a parsability of the request, verifying the executability of the request, and evaluating a hierarchical correctness of the requests. The method may further include assigning an accuracy metric to the request based on the parsability, the executability, and hierarchical correctness of the request. If the accuracy metric satisfies a threshold, the request may be executed to generate a response.

Abstract: Aspects of the present disclosure include methods for characterizing particles of a sample in a flow stream. Methods according to certain embodiments include generating frequency-encoded fluorescence data from a particle of a sample in a flow stream; and calculating phase-corrected spatial data of the particle by performing a transform of the frequency-encoded fluorescence data with a phase correction component. In certain embodiments, methods include generating an image of the particle in the flow stream based on the phase-corrected spatial data. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to calculate phase-corrected spatial data from frequency-encoded fluorescence data of a particle a flow stream are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for practicing the subject methods are also provided.

Abstract: A cell sorting system that automatically generates a sorting strategy based on examples of target events provided by an operator. The target events can be selected using measurements ranging from traditional flow cytometry measurements to derived measurements that are computationally expensive to complex measurements such as images.

Abstract: In one aspect, a method of sorting cells in a flow cytometry system is disclosed, which includes illuminating a cell with radiation having at least two optical frequencies shifted from one another by a radiofrequency to elicit fluorescent radiation from the cell, detecting the fluorescent radiation to generate temporal fluorescence data, and processing the temporal fluorescence data to arrive at a sorting decision regarding the cell without generating an image (i.e., a pixel-by-pixel image) of the cell based on the fluorescence data. In other words, while the fluorescence data can contain image data that would allow generating a pixel-by-pixel fluorescence intensity map, the method arrives at the sorting decision without generating such a map. In some cases, the sorting decision can be made with a latency less than about 100 microseconds. In some embodiments, the above method of sorting cells can have a sub-cellular resolution, e.g.

Abstract: Non-parametric transforms such as t-distributed stochastic neighbor embedding (tSNE) are used to analyze multi-parametric data such as data derived from flow cytometry or other particle analysis systems and methods. These transforms may be included for dimensionality reduction and identification of subpopulations (e.g., gating). By nature, non-parametric transforms cannot transform new observations without training a new transformation based on the entire dataset including the new observations. The features described parameterize non-parametric transforms using a neural network thereby allowing a small training dataset to be transformed using non-parametric techniques. The training dataset may then be used to generate an accurate parametric model for assessing additional events in a manner consistent with the initial events.