Abstract: Disclosed is a platform that provides temporary staff along with administrative infrastructure to employers who have temporary staffing needs. Administrative issues are monitored via dynamically generated geofences and mobile devices (mobile phones) carried by worker-users. The geofences serve as time clock and behavioral monitor zone.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing data about a medical encounter using neural networks. One of the methods includes obtaining features for a medical encounter associated with the patient, each feature representing a corresponding health event associated with the medical encounter and each of the plurality of features belonging to a vocabulary of possible features that each represent a different health event; and generating respective final embeddings for each of the features for the medical encounter by applying a sequence of one or more self-attention blocks to the features for the medical encounter, wherein each of the one or more self-attention blocks receives a respective block input for each of the features and applies self-attention over the block inputs to generate a respective block output for each of the features.

Abstract: Disclosed herein are systems for imaging and ablating a sample. An imaging/ablating device (110) includes an optical assembly (112), a sample stage (114), and a receiver (116). The optical assembly (112) is disposed in an inverted position below the sample stage (114) and the receiver (116) is positioned above the sample stage (112). The optical assembly enables imaging of a sample disposed on the sample stage (114). The optical assembly (112) also enables ablation of a region of interest within the sample. The laser light propagated from the optical assembly during ablation propagates substantially in the same direction as the direction of travel of the ablation plume (20) toward the receiver (116).

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: 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: Antisense oligonucleotides (ASOs) are provided which are capable of modulating splicing by preventing inclusion of an UNC13A cryptic exon into an UNC13A mature mRNA. Such ASOs may be used as a medicament, for example, to treat neurodegenerative disorders, particularly those associated with TDP-43 pathology.

Abstract: Disclosed is a platform that provides temporary staff along with administrative infrastructure to employers who have temporary staffing needs. Administrative issues are monitored via dynamically generated geofences and mobile devices (mobile phones) carried by worker-users. The geofences serve as time clock and behavioral monitor zone.

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: Method, system, device, and non-transitory computer-readable medium for presenting a conversation. A computer-implemented method may include: obtaining, via a first virtual participant, a first set of audio data associated with the first conversation while the first conversation occurs; transcribing the first set of audio data into a first set of text data while the first conversation occurs; obtaining a set of annotations associated with the set of text data while the first conversation occurs; identifying one or more topic transitions based at least in part upon the set of text data; generating a conversation summary based at least in part upon the one or more topic transitions; obtaining a first set of visual data associated with the conversation; and presenting the set of annotations, the conversation summary, and the first set of visual data embedded in the first set of text data to the first group of actual participants.

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: Antisense oligonucleotides (ASOs) are provided which are capable of modulating splicing by preventing inclusion of an UNC13A cryptic exon into an UNC13A mature mRNA. Such ASOs may be used as a medicament, for example, to treat neurodegenerative disorders, particularly those associated with TDP-43 pathology.

Abstract: Systems and cache-based methods for explaining tree-based models using interventional Shapley values are disclosed. With this technology, interventional Shapley values are used to compute attribution values from a leaf-wise approach within tree-based machine learning models. Reference traversal tables and test traversal tables are created and stored for each leaf of a decision tree. Based on the created tables, a subset of traversal permutations and respective subset size are determined on a tree by tree, leaf by leaf and feature by feature basis. For each of the nodes in a traversal path to each of the leaves, partial attribution values are generated, and an attribution for the node is adjusted based on the generated partial attribution values and a multiplier indicated in the reference traversal tables. An output explanation of a score can advantageously be obtained with reduced computational complexity and runtime.

Abstract: Methods, non-transitory computer readable media, and model evaluations systems for understanding diverse machine learning models (MLMs) are disclosed. In some examples, a feature contribution value is determined for features included in a reference or evaluation input data set. The evaluation input data set represents a protected class population and each feature contribution value identifies a contribution by a feature to a difference in output generated by an MLM for the evaluation input data set. Model explanation information is generated using the feature contribution values and execution of the MLM is monitored. The model explanation information explains the difference in output generated by the MLM for the evaluation input data set and includes information relating to a model-based decision. A report is generated from a knowledge graph for the MLM and output via a GUI to an operator device that includes the model explanation information.

Abstract: Method, system, device, and non-transitory computer-readable medium for presenting a conversation. A computer-implemented method may include: obtaining, via a first virtual participant, a first set of audio data associated with the first conversation while the first conversation occurs; transcribing the first set of audio data into a first set of text data while the first conversation occurs; obtaining a set of annotations associated with the set of text data while the first conversation occurs; identifying one or more topic transitions based at least in part upon the set of text data; generating a conversation summary based at least in part upon the one or more topic transitions; obtaining a first set of visual data associated with the conversation; and presenting the set of annotations, the conversation summary, and the first set of visual data embedded in the first set of text data to the first group of actual participants.

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: In some embodiments, the present disclosure provides an exemplary method that may include steps of accessing a set of data records; receiving an instruction to perform an action; determining input data associated with the instruction; verifying the input data; identifying a pattern of behavior associated with each type of data; converting verified input data of a particular data type into a uniform secure data state; dynamically enabling a communication session between at least two security modules; orchestrating a delay within the communication session; and automatically programming a plurality of controls to modify the communication session.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of identifying a plurality of entities seeking to interact with each other; determining a set of artifacts associated with each entity of the plurality of entities; Utilizing a cloud-based functionality to dynamically connect at least two entities based on a determination of the set of artifacts shared between the at least two entities; dynamically integrating a plurality of protocols into an interaction session associated with the at least two entities; verifying the plurality of protocols associated with the interaction session; initiating the interaction session between at least two entities based on the plurality of protocols and the set of artifacts; and automatically modifying the interaction session to orchestrate a transfer of at least one artifact of the set of artifacts between the at least two entities.

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: Systems and methods for zero-shot prompt ensembling for zero-shot classification with text-image models can include utilizing a pre-trained text-image model to perform downstream tasks based on prompt-based weighting. The systems and methods may adjust for frequency-based bias and may automatically determine different prompt associations with a given downstream task. The systems and methods can aggregate weighted text embeddings and then determine a classification output based on similarity measures between an image embedding and the aggregated weighted text embeddings.