Abstract: Systems and methods are described for analyzing user data, for instance for eligibility of a user for one or more programs. The user data is analyzed in two or more stages, with each stage including rules and/or program qualification criteria specific to that stage. In some examples, the systems and methods used trained machine learning models for at least one stage of the analysis. The systems and methods disclose identifying one or more programs that the user is eligible for, and in some cases, applying the one or more programs to the user's account.

Abstract: A distributed acquisition environment downloads a snapshot of a large dataset from one or more remote environments. The download may occur regularly to enable the distributed acquisition environment to operate on a nearly up-to-date instance of the large dataset. The download may begin when a computing device receives a request to load a dataset into memory of the distributed acquisition environment. The dataset may be divided into one or more data segments. Each data segment of the one or more data segments is associated with a data loader of one or more data loaders of the distributed acquisition environment. The one or more data segments are transferred to a temporary location within a cloud environment. The data loaders of the distributed acquisition environment to then download the one or more data segments from the temporary location.

Abstract: Data selection systems and techniques are described. For instance, a system receives a data set with a plurality of data elements. The system generates a plurality of random values. The system generates a ranking of the plurality of random values. The system selects a subset of the plurality of data elements based on a comparison between the ranking and a predetermined threshold. The predetermined threshold is based on a predetermined proportion of the plurality of data elements to be included in the subset. The system outputs a randomization scheme that includes the ranking and the predetermined proportion, wherein a second selection of a second subset of the plurality of data elements is based on the randomization scheme. The system output an indication of the subset and the second subset.

Abstract: Systems and methods provide a framework through which dynamic verification values are generated for different instruments for use in real-time instrument utilizations. In response to an authorization request associated with an instrument and including a dynamic verification value, a system obtains a secret code associated with the instrument. The system dynamically generates a reference dynamic verification value using record data associated with the instrument, the secret code, and a current time interval. The reference dynamic verification value is compared to the received dynamic verification value to determine if these values match. If so, the system fulfills the authorization request.

Abstract: Data selection systems and techniques are described. For instance, a system receives a data set with a plurality of data elements. The system generates a plurality of random values. The system generates a ranking of the plurality of random values. The system selects a subset of the plurality of data elements based on a comparison between the ranking and a predetermined threshold. The predetermined threshold is based on a predetermined proportion of the plurality of data elements to be included in the subset. The system outputs a randomization scheme that includes the ranking and the predetermined proportion, wherein a second selection of a second subset of the plurality of data elements is based on the randomization scheme. The system output an indication of the subset and the second subset.

Abstract: Systems and methods are described for analyzing user data, for instance for eligibility of a user for one or more programs. The user data is analyzed in two or more stages, with each stage including rules and/or program qualification criteria specific to that stage. In some examples, the systems and methods used trained machine learning models for at least one stage of the analysis. The systems and methods disclose identifying one or more programs that the user is eligible for, and in some cases, applying the one or more programs to the user's account.

Abstract: Systems and methods are described for analyzing user data, for instance for eligibility of a user for one or more programs. The user data is analyzed in two or more stages, with each stage including rules and/or program qualification criteria specific to that stage. In some examples, the systems and methods used trained machine learning models for at least one stage of the analysis. The systems and methods disclose identifying one or more programs that the user is eligible for, and in some cases, applying the one or more programs to the user's account.

Abstract: A system determines an amount of time available for responding to a request regarding eligibility for a client account for a modification based on a confidence grade for the client. The system transmits a first query and a second query. The system uses trained machine learning model(s) to determine respective estimated receipt times of first and second datasets responsive to the first and second queries, and to determine respective importance levels of the first and second datasets to determining the confidence grade. The system generates a preliminary confidence grade based on the first dataset, and delays generation of the confidence grade until the second dataset is received based on the estimated receipt times and importance levels. The system updates the preliminary confidence grade using the second dataset to generate the confidence grade, determines the eligibility determination, and updates the training of the machine learning models.

Abstract: A system determines an amount of time available for responding to a request regarding eligibility for a client account for a modification based on a confidence grade for the client. The system transmits a first query and a second query. The system uses trained machine learning model(s) to determine respective estimated receipt times of first and second datasets responsive to the first and second queries, and to determine respective importance levels of the first and second datasets to determining the confidence grade. The system generates a preliminary confidence grade based on the first dataset, and delays generation of the confidence grade until the second dataset is received based on the estimated receipt times and importance levels. The system updates the preliminary confidence grade using the second dataset to generate the confidence grade, determines the eligibility determination, and updates the training of the machine learning models.

Abstract: Data selection systems and techniques are described. For instance, a system receives a data set with a plurality of data elements. The system generates a plurality of random values. The system generates a ranking of the plurality of random values. The system selects a subset of the plurality of data elements based on a comparison between the ranking and a predetermined threshold. The predetermined threshold is based on a predetermined proportion of the plurality of data elements to be included in the subset. The system outputs a randomization scheme that includes the ranking and the predetermined proportion, wherein a second selection of a second subset of the plurality of data elements is based on the randomization scheme. The system output an indication of the subset and the second subset.

Abstract: An apparatus includes a housing and a sample preparation module disposed within the housing. The sample preparation module has a base including a wall defining a sample reservoir. The apparatus includes a flexible heater having a first end and a second end. The first end of the flexible heater is coupled to a connector to be in electrical communication with a power source. A carrier is coupled to and supports the flexible heater such that the second end of the flexible heater is disposed within the sample reservoir spaced apart from the wall. The apparatus can also include an input retention lid that can be disposed partially within the sample reservoir and includes a retention screen to prevent solid reagents within the sample reservoir from migrating upward.

Abstract: A system determines an amount of time available for responding to a request regarding eligibility for a client account for a modification based on a confidence grade for the client. The system transmits a first query and a second query. The system uses trained machine learning model(s) to determine respective estimated receipt times of first and second datasets responsive to the first and second queries, and to determine respective importance levels of the first and second datasets to determining the confidence grade. The system generates a preliminary confidence grade based on the first dataset, and delays generation of the confidence grade until the second dataset is received based on the estimated receipt times and importance levels. The system updates the preliminary confidence grade using the second dataset to generate the confidence grade, determines the eligibility determination, and updates the training of the machine learning models.

Abstract: In response to receipt of a request for an assessment of a user at a system and from a client terminal, the system identifies a duration of time available for responding to the request and starts a timer. The system transmits requests for information about the user to data sources. The system can and receive some responsive datasets back from the data sources, and can determine which responsive datasets are optimal to wait for and which are not based on how closely the timer is approaching the duration of time available for responding to the request. The system generates the assessment of the user based on the datasets that the system received before the timer reached a threshold time that is based on the duration of time available for responding to the request, and sends the assessment of the user to the client terminal.

Abstract: A system and method for isolating and separating lipoaspirate particles. The system includes a generally cylindrical container having a lid and a bottom wherein the container includes at least one input port positioned to permit a lipoaspirate fluid to enter the container above the bottom; and a source of a vacuum coupled to the container to provide a partial vacuum during use of the system.

Abstract: Methods of treating and or preventing substance abuse/dependence, and alcohol abuse/dependence in particular. Combinations of medications are also disclosed.

Abstract: Methods of treating and or preventing substance abuse/dependence, and alcohol abuse/dependence in particular. Combinations of medications are also disclosed.

Abstract: An embodiment of the present invention is a technique to fabricate a metal interconnect. A first metal trace is printed on a die attached to a substrate or a cavity of a heat spreader in a package to electrically connect the first metal trace to a power contact in the substrate. A device is mounted on the first metal trace. The device receives power from the substrate when the package is powered.

Abstract: A system and method for isolating and separating lipoaspirate particles. The system includes a generally cylindrical container having a lid and a bottom wherein the container includes at least one input port positioned to permit a lipoaspirate fluid to enter the container above the bottom; and a source of a vacuum coupled to the container to provide a partial vacuum during use of the system.

Abstract: An embodiment of the present invention is a technique to fabricate a metal interconnect. A first metal trace is printed on a die attached to a substrate or a cavity of a heat spreader in a package to electrically connect the first metal trace to a power contact in the substrate. A device is mounted on the first metal trace. The device receives power from the substrate when the package is powered.

Abstract: An embodiment of the present invention is a technique to fabricate a metal interconnect. A first metal trace is printed on a die attached to a substrate or a cavity of a heat spreader in a package to electrically connect the first metal trace to a power contact in the substrate. A device is mounted on the first metal trace. The device receives power from the substrate when the package is powered.