Abstract: The present disclosure provides apparatuses, systems, and methods for performing particle analysis through flow cytometry at comparatively high event rates and for gathering high resolution images of particles.

Abstract: A method for trusted notifications comprises: receiving, at a first host having at least one trusted server, a request message from a sender computing device, the request message comprising a request identifier and instructions to: update, at a second host, a recipient account associated with a recipient computing device, and to make a corresponding update at the first host to a sender account associated with the sender computing device. The method further comprises authorizing, at the first host, the request message; updating the sender account; generating a secure message at the at least one trusted server, the secure message comprising the request identifier and an indication from the at least one trusted server that the update completed; and sending the secure message from the first host to the sender computing device. The secure message can be received at the sender computer device and conveyed to the recipient computing device.

Abstract: Automated systems and methods for retrieving information from scanned documents are described herein. An example method includes reading a scanned document; and extracting a page image from the scanned document, where the page image includes text and structured data. The method also includes executing a structured data detection algorithm to detect the structured data contained in the page image and identify a plurality of elements of the structured data. Additionally, the method includes performing optical character recognition (OCR) to convert the text contained in the page image to first text data; and performing OCR to convert respective contents of each of the plurality of elements of the structured data to second text data. The method further includes executing a natural language processing (NLP) algorithm to retrieve information from the first and second text data.

Abstract: Systems and methods for generating tree-based models with improved fairness are disclosed. The disclosed process generates a first tree-based machine learning model, which is preferably trained to predict if a financial loan will be repaid. The process also determines an accuracy of the first tree-based machine learning mode. In addition, the process determines a fairness of the first tree-based machine learning model. The fairness is preferably associated with at least one of gender, race, ethnicity, age, marital status, military status, sexual orientation, and disability status. The process then generates a second different tree-based machine learning model, which is preferably trained based on the accuracy of the first tree-based machine learning model and the fairness of the first tree-based machine learning model. The process then combines the first tree-based machine learning model and the second tree-based machine learning model to produce a gradient-boosted machine learning model.

Abstract: Disclosed is a platform that manages worker users in a temporary staffing environment via an artificial machine learning model. The temporary staffing platform matches available workers to available shifts/gigs. Additional features include generating provisional or near-miss matches and informing workers how to turn those near-misses into full matches, plotting a gig-career path to develop additional skills, gamify development, and automatically generate resumes. The platform generates a set of skill tags associated with each shift/gig performed by the user. Designing of resume text files by the artificial machine learning model includes procedurally generated descriptions of experience the a user has based on the recording of each shift/gig performed by the user and the skill tags associated with each recorded shift/gig, wherein a format of the resume text file is formulated by the artificial machine learning model evaluating a mix of skill tags and employers amassed by the user.

Abstract: An audio processing unit (APU) is disclosed. The APU includes a buffer memory configured to store at least one frame of an encoded audio bitstream, where the encoded audio bitstream includes audio data and a metadata container. The metadata container includes a header and one or more metadata payloads after the header. The one or more metadata payloads include dynamic range compression (DRC) metadata, and the DRC metadata is or includes profile metadata indicative of whether the DRC metadata includes dynamic range compression (DRC) control values for use in performing dynamic range compression in accordance with at least one compression profile on audio content indicated by at least one block of the audio data.

Abstract: Systems and methods for understanding diverse machine learning models.

Abstract: Disclosed is a platform that manages worker users in a temporary staffing environment via an artificial machine learning model. The temporary staffing platform matches available workers to available shifts/gigs. Additional features include generating provisional or near-miss matches and informing workers how to turn those near-misses into full matches, plotting a gig-career path to develop additional skills, gamify development, and automatically generate resumes. The platform generates a set of skill tags associated with each shift/gig performed by the user. Designing of resume text files by the artificial machine learning model includes procedurally generated descriptions of experience the a user has based on the recording of each shift/gig performed by the user and the skill tags associated with each recorded shift/gig, wherein a format of the resume text file is formulated by the artificial machine learning model evaluating a mix of skill tags and employers amassed by the user.

Abstract: Systems and methods for generating tree-based models with improved fairness are disclosed. The disclosed process generates a first tree-based machine learning model, which is preferably trained to predict if a financial loan will be repaid. The process also determines an accuracy of the first tree-based machine learning mode. In addition, the process determines a fairness of the first tree-based machine learning model. The fairness is preferably associated with at least one of gender, race, ethnicity, age, marital status, military status, sexual orientation, and disability status. The process then generates a second different tree-based machine learning model, which is preferably trained based on the accuracy of the first tree-based machine learning model and the fairness of the first tree-based machine learning model. The process then combines the first tree-based machine learning model and the second tree-based machine learning model to produce a gradient-boosted machine learning model.

Abstract: Provided herein are nucleic acid constructs, host insect cells, and methods for producing recombinant AAV capsids with high potency at high yield.

Abstract: The present disclosure provides apparatuses, systems, and methods for performing particle analysis through flow cytometry at comparatively high event rates and for gathering high resolution images of particles.

Abstract: The present disclosure provides apparatuses, systems, and methods for performing particle analysis through flow cytometry at comparatively high event rates and for gathering high resolution images of particles.

Abstract: A weld system includes: a robot control module configured to actuate a robot and move a welder along a joint of metal workpieces during welding, the welder being attached to the robot; a weld control module configured to, during the welding, apply power to the welder, supply a shield gas, and supply electrode material; a vision sensor configured to, during the welding, optically measure distances between the vision sensor and locations, respectively, on an outer surface of a weld bead created along the joint by the welder; and a weld module configured to: determine a strength of the weld bead at a location based on: the distances at the location along the joint; and at least one parameter from at least one of the robot control module during the welding, the weld control module during the welding, and a sensor configured to capture data of the welding during the welding.

Abstract: A method for encapsulating transaction instrument information in a transaction includes storing, in association with a first transaction and by a processor of the primary transaction processor server, payment data associated with a payment instrument used to settle a cost of a first transaction. The primary transaction processor server transmits the transaction data to a payment network processor. The primary transaction processor server receives an authorization package from the payment network processor that includes a cryptograph and a first network token. The processor of the primary transaction processor server generates a secondary token, and stores a correlation record to a computer-readable memory. The correlation record associates the secondary token to a second object stored by the primary transaction processor. The processor of the primary transaction processor server transmits a second transaction package including at least one of the network token and the secondary token to a merchant device.

Abstract: The present disclosure relates to fiber optic connection systems including fiber optic connector having retractable noses for protecting bare fiber ends of ferrule-less connectors. In certain examples, the retractable noses are used in combination with protective shutters. In other examples, the retractable noses can accommodate multiple optical fibers.

Abstract: Disclosed is a platform that makes use of hybrid model employing both heuristic and machine learning models to adaptively generate recommendations based on requested circumstances in a temporary staffing platform. The hybrid model is based on a set of training data surrounding historical temporary staffing outcomes. The heuristic model portion identifies matches between current queries to past outcomes and the machine learning model portion trains to derive new recommendations where no match exists. Queries are received and executed upon in real-time as opposed to pre-computing based on the frequency of changes to the recommendation to what would otherwise be the same query. The hybrid model is therefore configured to optimize for real-time responses to individual queries. The data surrounding the historical temporary staffing outcomes includes data relating to users, data relating to shifts, and data derived from a combination of both.

Abstract: A fishing lure having interchangeable inserts includes a lure body having a front end, a rear end, a left side, a right side, a top side, and a bottom side. At least the left side, but in some embodiments also the right side, includes an insert slot with an opening proximate the rear end. The insert slot has at least one pair of opposing flanges. An insert engages the insert slot and has a catch at a forward end thereof adapted for engaging the snap aperture of the lure body. An outer surface of the insert with a natural attractant is visible through the insert slot between the flanges. The insert is preferably one of many available inserts that all have varying outer surface characteristics, such as color, pattern, texture, attachments, and the like. A fishing lure attachment cooperative with the inserts is used with existing fishing lures.

Abstract: The present disclosure provides apparatuses, systems, and methods for performing particle analysis through flow cytometry at comparatively high event rates and for gathering high resolution images of particles.

Abstract: An audio processing unit (APU) is disclosed. The APU includes a buffer memory configured to store at least one frame of an encoded audio bitstream, where the encoded audio bitstream includes audio data and a metadata container. The metadata container includes a header and one or more metadata payloads after the header. The one or more metadata payloads include dynamic range compression (DRC) metadata, and the DRC metadata is or includes profile metadata indicative of whether the DRC metadata includes dynamic range compression (DRC) control values for use in performing dynamic range compression in accordance with at least one compression profile on audio content indicated by at least one block of the audio data.