Abstract: Systems and methods for interactive pathogen detection are described including receiving at least one target genome file and at least one near-neighbor genome file and analyzing the target genome file and the near-neighbor genome file to generate a plurality of raw e-probes unique to a target pathogen. Each raw e-probe includes a unique nucleic acid signature sequence selected from along a length of the pathogen genome of the target pathogen. The plurality of raw e-probes are curated to provide a curated e-probe set. The curated e-probe set can be in silico validated and/or in vitro validated. The resulting e-probe set can be used to determine presence of the target pathogen in a sample metagenome in an e-probe diagnostic system.

Abstract: In some embodiments, a processor receives natural language data for performing an identified cybersecurity task. The processor can provide the natural language data to a first machine learning (ML) model. The first ML model can automatically infer a template query based on the natural language data. The processor can receive user input indicating a finalized query and to provide the finalized query as input to a system configured to perform the identified computational task. The processor can provide the finalized query as a reference phrase to a second ML model, the second ML model configured to generate a set of natural language phrases similar to the reference phrase. The processor can generate supplemental training data using the set of natural language phrases similar to the reference phrase to augment training data used to improve performance of the first ML model and/or the second ML model.

Abstract: In some embodiments, a processor receives, via an interface, natural language data associated with a user request for performing an identified computational task associated with a cybersecurity management system. The processor is configured to provide the natural language data as input to a machine learning (ML) model. The ML model is configured to automatically infer a template query based on the natural language data. The processor is further configured to cause the template query to be displayed, via the interface. The processor is further configured to receive, via the interface, user input indicating a finalized query associated with the identified computational task, and to provide the finalized query as input to a system configured to perform the identified computational task. The processor is further configured to modify a security setting in the cybersecurity management system based on the performance of the identified computational task.

Abstract: In one or more embodiments, a command is repeatedly input a predetermined number of times into a machine learning model to generate a plurality of different natural language (NL) descriptions. The plurality of different NL descriptions are input into the machine learning model to generate a plurality of different check commands. A plurality of similarity metrics are determined by comparing each check command from the plurality of different check commands to the command. A check command from the plurality of different check commands that is most similar to the command is identified based on the plurality of similarity metrics. An NL description from the plurality of different NL descriptions is caused to be displayed, the NL description previously input into the machine learning model to generate the check command.

Abstract: Systems and methods for quantifying the duration of S1 and/or S2 heart sounds, in order to identify markers of heart failure and/or lung failure, are provided. Cardiac cycles containing S1 and S2 sound can be identified in a phonocardiogram and normalized. In order to quantify S1 and S2 sound length, the envelope of the absolute value of the signal can be obtained for each cycle. The sound waves of two components can be separated using the identified single sound wave. These features can be correlated to measures of heart failure and/or lung failure.

Abstract: Due to the threat of virus attacks and ransom ware, an apparatus and methods for protecting backup storage devices from malicious software virus attacks is explored. An independent backup storage system is connected to a primary storage server over an undiscoverable communications line. The backup storage system is a read-only backup storage system most of the time buffering the backup storage system from a virus or attack on the primary storage server. The backup storage system changes from a read-only backup storage system to a read/write backup storage system only during a backup window of time where data is backed up to the backup storage system. A snapshot of the backup data is maintained in the backup storage system and can be made available at numerous points of time in the past if the data primary storage server becomes corrupted.

Abstract: An automated system attempts to characterize code as safe or unsafe. For intermediate code samples not placed with sufficient confidence in either category, human-readable analysis is automatically generated to assist a human reviewer in reaching a final disposition. For example, a random forest over human-interpretable features may be created and used to identify suspicious features in a manner that is understandable to, and actionable by, a human reviewer. Similarly, a k-nearest neighbor algorithm may be used to identify similar samples of known safe and unsafe code based on a model for, e.g., a file path, a URL, an executable, and so forth. Similar code may then be displayed (with other information) to a user for evaluation in a user interface. This comparative information can improve the speed and accuracy of human interventions by providing richer context for human review of potential threats.

Abstract: Systems and methods are disclosed for selecting cohorts. In one implementation, a model-assisted selection system for identifying candidates for placement into a cohort includes a data interface and at least one processing device. The at least one processing device is programmed to access, via the data interface, a database from which feature vectors associated with an individual from among a population of individuals can be derived; derive, for the individual, one or more feature vectors from the database; provide the one or more feature vectors to a model; receive an output from the model; and determine whether the individual from among the population of individuals is a candidate for the cohort based on the output received from the model.

Abstract: In some embodiments, a method includes processing at least a portion of a received file into a first set of fragments and analyzing each fragment from the first set of fragments using a machine learning model to identify within each fragment first information potentially relevant to whether the file is malicious. The method includes forming a second set of fragments by combining adjacent fragments from the first set of fragments and analyzing each fragment from the second set of fragments using the machine learning model to identify second information potentially relevant to whether the file is malicious. The method includes identifying the file as malicious based on the first information within at least one fragment from the first set of fragments and the second information within at least one fragment from the second set of fragments. The method includes performing a remedial action based on identifying the file as malicious.

Abstract: A system includes a processor configured to receive requirement values, from a vehicle-providing entity, for a plurality of predefined tunable routing parameters. The processor is also configured to select and assign entity-associated, routing parameter consideration-levels, based on the values correlated to a predefined schema of consideration-levels for each parameter. The processor is further configured to receive a plurality of pick-up requests and determine, using the entity-associated routing parameter consideration-levels, a routing-plan for a plurality of vehicles to service the requests such that the received values are met.

Abstract: Systems and methods for quantifying the duration of S1 and/or S2 heart sounds, in order to identify markers of heart failure and/or lung failure, are provided. Cardiac cycles containing S1 and S2 sound can be identified in a phonocardiogram and normalized. In order to quantify S1 and S2 sound length, the envelope of the absolute value of the signal can be obtained for each cycle. The sound waves of two components can be separated using the identified single sound wave. These features can be correlated to measures of heart failure and/or lung failure.

Abstract: Systems and methods are disclosed for monitoring models for bias. In one implementation, a system for automatically assessing a deployed model for selection of a cohort may include a processing device programmed to: apply the deployed model to data representing a first plurality of individuals, the data including at least one characteristic of the first plurality of individuals; based on the application, select a subset of the first plurality of individuals as a cohort; receive data representing a second plurality of individuals labeled as within the cohort, the data including the at least one characteristic of the second plurality of individuals; compare the selected subset and the second plurality of individuals along the at least one characteristic; and determine whether the comparison results in a difference between the selected subset and the second plurality of individuals greater than a threshold.

Abstract: Due to the threat of virus attacks and ransom ware, an apparatus and methods for protecting backup storage devices from malicious software virus attacks is explored. An independent backup storage system is connected to a primary storage server over an undiscoverable communications line. The backup storage system is a read-only backup storage system most of the time buffering the backup storage system from a virus or attack on the primary storage server. The backup storage system changes from a read-only backup storage system to a read/write backup storage system only during a backup window of time where data is backed up to the backup storage system. A snapshot of the backup data is maintained in the backup storage system and can be made available at numerous points of time in the past if the data primary storage server becomes corrupted.

Abstract: In some embodiments, a processor can receive an input string associated with a potentially malicious artifact and convert each character in the input string into a vector of values to define a character matrix. The processor can apply a convolution matrix to a first window of the character matrix to define a first subscore, apply the convolution matrix to a second window of the character matrix to define a second sub score and combine the first subscore and the second subscore to define a score for the convolution matrix. The processor can provide the score for the convolution matrix as an input to a machine learning threat model, identify the potentially malicious artifact as malicious based on an output of the machine learning threat model, and perform a remedial action on the potentially malicious artifact based on identifying the potentially malicious artifact as malicious.

Abstract: A computer-implemented method of processing audio data, the method comprising receiving input audio data (x) comprising a time-series of amplitude values; transforming the input audio data (x) into an input frequency band decomposition (X1) of the input audio data (x); transforming the input frequency band decomposition (X1) into a first latent representation (Z); processing the first latent representation (Z) by a first deep neural network to obtain a second latent representation (Z{circumflex over (?)}, Z1{circumflex over (?)}); transforming the second latent representation (Z{circumflex over (?)}, Z1{circumflex over (?)}) to obtain a discrete approximation (X3{circumflex over (?)}); element-wise multiplying the discrete approximation (X3{circumflex over (?)}) and a residual feature map (R, X5{circumflex over (?)}) to obtain a modified feature map, wherein the residual feature map (R, X5{circumflex over (?)}) is derived from the input frequency band decomposition (X1); processing a pre-shaped frequency band

Abstract: A method for tracking injection site information includes displaying, on a user interface, a plurality of injection zones, each of the plurality of injection zones representing a segment of the body suitable for medication injection and including a graphical indicator indicating a period of time since a most recent previous injection in the injection zone. The method also includes receiving, via the user interface, injection information relating to a new injection in a particular injection zone. The method also includes updating a graphical indicator of the particular injection zone on the user interface to indicate a new date and time of injection to the particular injection zone.

Abstract: A battery module includes features to optimize cooling while providing electrical isolation and cell gas-venting channels. The battery module can include the integration of a heatsink in order to improve thermal performance. Thermally conductive pads can be provided to create an electrically isolated interface between a plurality of series-connected battery-cell lead plates, at different potentials, and the heatsink. Optimization, by stacking thin and thick thermally conductive pads, allows for creation of gas-venting channels along the positive cell terminal locations. In some arrangements, a plurality of fluid paths are disposed between the inlet and the outlet of the battery module to provide heat convective airflow through the battery module.

Abstract: Due to the threat of virus attacks and ransom ware, an apparatus and methods for protecting backup storage devices from malicious software virus attacks is explored. An independent backup storage system is connected to a primary storage server over an undiscoverable communications line. The backup storage system is a read-only backup storage system most of the time buffering the backup storage system from a virus or attack on the primary storage server. The backup storage system changes from a read-only backup storage system to a read/write backup storage system only during a backup window of time where data is backed up to the backup storage system. A snapshot of the backup data is maintained in the backup storage system and can be made available at numerous points of time in the past if the data primary storage server becomes corrupted.

Abstract: In some embodiments, a method includes processing at least a portion of a received file into a first set of fragments and analyzing each fragment from the first set of fragments using a machine learning model to identify within each fragment first information potentially relevant to whether the file is malicious. The method includes forming a second set of fragments by combining adjacent fragments from the first set of fragments and analyzing each fragment from the second set of fragments using the machine learning model to identify second information potentially relevant to whether the file is malicious. The method includes identifying the file as malicious based on the first information within at least one fragment from the first set of fragments and the second information within at least one fragment from the second set of fragments. The method includes performing a remedial action based on identifying the file as malicious.