Abstract: A method includes converting, by a generative network, an input into a latent vector representation of a sample chemical compound, wherein the input is one of an order-dependent representation of the sample chemical compound and a molecular graph representation of the sample chemical compound; determining, by an output neural network, one or more properties of the sample chemical compound based on the latent vector representation of the sample chemical compound; performing, by the output neural network, an optimization routine to select a candidate latent vector representation from among a plurality of latent vector representations based on the latent vector representation of the sample chemical compound, wherein the plurality of latent vector representations includes the latent vector representation of the sample chemical compound; and identifying, by the output neural network, a candidate chemical compound based on the candidate latent vector representation.

Abstract: Methods and compositions for making DNA libraries for massive parallel next generation sequencing (NGS), comprises two parts. These methods may be referred to as Triseq sequencing. The first part includes ligating a UMI adapter, amplifying the DNA fragments in the presence of dUTP, enriching the target molecules through primer extension by using a panel of both forward and reverse primers, and removing the dU-containing template DNA. The DNA molecules are organized to primary clones and subclones, labeled by the UMI on 5? and 3? end of the DNA fragments, respectively. The second part includes sequencing the DNA library by NGS, deducing consensus sequence from each subclone, and from within each primary clone, and between the consensus sequences obtained from both forward and reverse primers.

Abstract: A compensating fastener assembly is configured to secure a fastener to a surface element. The compensating fastener assembly includes a compression limiter having a cylindrical main body and a flange, the cylindrical main body defining a channel and a longitudinal axis. The compensating fastener assembly further includes a spring defining a central passage. The central passage of the spring is configured to receive the main body of the compression limiter such that a first end of the spring is configured to be disposed adjacent the flange of the compression limiter.

Abstract: Embodiments described herein provide a computer-implemented method for predicting reaction constituents, comprising: generating a catalyst or solvent efficacy score based on reaction data; storing a graph convolutional model, generated based on the reaction data and the catalyst/solvent efficacy scores: wherein for a catalyst, graph representations of the catalyst and of a reactant and a product are inputs to the graph convolutional model; and similarly for a solvent; predicting the effectiveness of a specified catalyst/solvent based on a specified reaction definition and/or predicting a catalyst/solvent by determining whether the first and second reactions have an identical core transform.

Abstract: Compositions, systems, kits, and methods are described herein for the modulation, and in particular the reduction or inhibition, of expression of the FLCN gene or the activity of FLCN protein in a cell, animal, or human subject. Compositions, systems, and methods disclosed herein can be used to prevent, ameliorate, or treat diseases, particularly neuromuscular or neurodegenerative diseases, retinal degeneration diseases, or other TDP-43 proteinopathies. Methods are described for the modulation, and in particular the reduction or inhibition of FLCN expression or activity, comprising the use of a modulator to regulate FLCN expression or activity. Methods are also described for the development, synthesis, and production of modulators, and for therapeutic treatment of TDP-43 proteinopathies such as ALS and other related disorders.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. An update to a survey data file is detected. The updated survey data is stored in a SQL database configured to utilize a composite index of the updated survey data that optimizes database query time. A set of affected entity segment identifiers is determined. A set of affected category identifiers is determined. A set of affected cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of an affected entity segment identifier and an affected category identifier.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier.

Abstract: The present disclosure is directed to compounds of formula (I): wherein R1, R2, R3, R3a, R4, Y, and X are as described herein, as stereoisomers, enantiomers, or tautomers thereof or mixtures thereof; or pharmaceutically acceptable salts, solvates, or prodrugs thereof, and pharmaceutical compositions comprising the compounds of formula (I), as described herein, which are useful as voltage-gated sodium channel modulators and are therefore are useful in treating seizure disorders such as epilepsy.

Abstract: In embodiments, an authentication server interfaces between a user device with a self-signed certificate and a verifying computer that accepts a user name and password. The user device generates a self-signed certificate signed by a private key on the user device. The self-signed certificate is transmitted to a verifying party computer over a network. The verifying party stores the self-signed certificate with user identification data. The user migrates trust to another device by providing the root certificate and intermediate certificate as a certificate chain to a second device, which then adds a new intermediate certificate to create a longer certificate chain with the same root certificate. In subsequent communications, the verifying party receives a certificate chain including the self-signed certificate from the second user device, and matches that with the user identification data stored in a database.

Abstract: Methods, apparatuses and compositions for generating highly sensitive and accurate sequencing results of massive parallel sequencing (NGS). The methods and compositions may be referred to as SubDivision-Seq, and may comprise two parts. The first part includes making a target-enriched DNA library, organizing the UMIs on DNA molecules to form primary clones and subdividing the primary clones into subclones. The second part includes sequencing the DNA library by NGS, deducing consensus sequence from each subclone, then deducing consensus sequence in each primary clone.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A cognitive intelligence (CI) datapoint identifier cache datastructure is generated, the CI datapoint identifier cache datastructure configured to comprise a category identifier and an entity segment identifier. A CI datapoint value cache datastructure is generated, the CI datapoint value cache datastructure configured to comprise a set of module datastructures, each module datastructure corresponding to a module identifier associated with the category identifier, each module datastructure comprising a set of metric datastructures, each metric datastructure corresponding to a set of calculated metrics.

Abstract: In embodiments, an authentication server interfaces between a user device with a self-signed certificate and a verifying computer that accepts a user name and password. The user device generates a self-signed certificate signed by a private key on the user device. The self-signed certificate is transmitted to a verifying party computer over a network. The verifying party stores the self-signed certificate with user identification data, including at least one of a user name, user address, user email, user phone number, user tax ID, user social security number and user financial account number. In subsequent communications, the verifying party receives a certificate chain including the self-signed certificate, and matches that with the user identification data stored in a database.

Abstract: The present disclosure is directed to compounds of formula (I): wherein X, Y, Z, R1, R2a, R2b, R3, and L are as described herein, as stereoisomers, enantiomers, or tautomers thereof or mixtures thereof; or pharmaceutically acceptable salts, solvates, or prodrugs thereof, and pharmaceutical compositions comprising the compounds of formula (I), as described herein, which are useful as voltage-gated sodium channel modulators and are therefore are useful in treating seizure disorders such as epilepsy.

Abstract: The present invention provides compounds of Formula I?, or pharmaceutically acceptable salts thereof, pharmaceutical compositions thereof, and methods of use thereof for treating cellular proliferative disorders (e.g., cancer).

Abstract: The disclosure provides methods for predicting surface-presenting peptides using binding and surface-presentation characteristics. The method can include accessing a trained machine-learning model that is configured to generate an output that indicates an extent to which the one or more expression levels and the one or more peptide-presentation metrics are related in accordance with a population-level relationship between expression and presentation. For each peptide of the set of peptides for a tissue sample, a score can be determined using the machine-learning model and genomic and transcriptomic data corresponding to the peptide. The score is predictive of whether a corresponding peptide is a surface-presenting peptide that binds to an MHC molecule and is presented on a cell surface.

Abstract: A fastener assembly that is configured to securely couple to a component includes a bolt, a limiter, and a grommet. The bold has a head, a shaft, and a medial ridge disposed around a portion of the shaft. The limiter has a brim and a tube, with the tube extending away from the brim. A grommet has a central passage extending through a top section. The top section further includes a central wall and a bottom surface. At least one tab extends from the bottom surface.

Abstract: Methods for generating a composite biomarker that identifies a predicted level of responsiveness of a subject to a particular type of an immunotherapy treatment is provided. The method can include generating genomic metrics that represent one or more characteristics corresponding to one or more DNA sequences. The method can also include generating transcriptomic metrics represent one or more characteristics corresponding to a set of peptides that are translated from a corresponding RNA sequence of the one or more RNA sequences. The method can also include generating a composite biomarker score derived from the set of genomic metrics and the set of transcriptomic metrics. The method can also include determining, based on the composite biomarker score, a predicted level of responsiveness of the subject to a particular type of an immunotherapy treatment.

Abstract: Systems and methods are disclosed that facilitate providing a real-time training session between a mentor's communication device and a mentee's communication device, in which the mentor's communication device is granted control over the mentee's communication device in order to provide real-time instruction and video annotation. Mentee (player) data and progression over time are stored, and updatable ranked lists of mentees are generated for recruiting purposes, the wherein rankings are a function of player metrics, attributes, and progression over time. The systems and methods facilitate matching, mentor search and filter, scheduling, live chat, notifications, a rating system, and robust mentor profiles which include bios, photos, areas of expertise, and an introduction video.

Abstract: A method includes generating a graph of a chemical compound based on at least one of an order-dependent representation of the chemical compound and a molecular graph representation of the chemical compound, encoding the graph based on an adjacency matrix of a graph convolutional neural network (GCN), an activation function of the GCN, and one or more weights of the GCN to generate a latent vector representation of the chemical compound, and decoding the latent vector representation based on a plurality of hidden states of a neural network (NN) to generate a reproduced order-dependent representation of the chemical compound.

Abstract: The present invention provides compounds of Formula I?, or pharmaceutically acceptable salts thereof, pharmaceutical compositions thereof, and methods of use thereof for treating cellular proliferative disorders (e.g., cancer).