Abstract: Provided herein are systems and methods for using DNA polymerases to record information onto DNA for single cell high time-resolution recording and for high density data storage. The technology provides a DNA polymerase-based nano scale device that can be genetically encoded to record temporal information about the polymerase's environment into an extending single stand of DNA.

Abstract: A system for monitoring neural activity of a living subject is provided. The system may comprise a correspondence module configured to be in communication with (1) a neural module and (2) one or more additional modules comprising a sensing module, another neural module, and/or a data storage module. The neural module(s) are configured to collect neural data indicative of perceptions experienced by the living subject. The sensing module may be configured to collect (1) sensor data indicative of real-world information about an environment around the living subject, and/or (2) sensor data indicative of a physical state or physiological state of the living subject. The data storage module may be configured to store prior neural data and/or prior sensor data.

Abstract: A system for monitoring neural activity of a living subject is provided. The system may comprise a correspondence module configured to be in communication with (1) a neural module and (2) one or more additional modules comprising a sensing module, another neural module, and/or a data storage module. The neural module(s) are configured to collect neural data indicative of perceptions experienced by the living subject. The sensing module may be configured to collect (1) sensor data indicative of real-world information about an environment around the living subject, and/or (2) sensor data indicative of a physical state or physiological state of the living subject. The data storage module may be configured to store prior neural data and/or prior sensor data.

Abstract: Computer vision systems and methods for end-to end training of neural networks are provided. The system generates a fixed point algorithm for dual-decomposition of a maximum-a-posteriori inference problem and trains the convolutional neural network and a conditional random field with the fixed point algorithm and a plurality of images of a dataset to learn to perform semantic image segmentation. The system can segment an attribute of an image of the dataset by the trained neural network and the conditional random field.

Abstract: A system and method for automated detection of figure element reuse. The system can receive articles or other publications from a user input or an automated input. The system then extracts images from the articles and compares them to reference images from a historical database. The comparison and detection of matches occurs via a copy-move detection algorithm implemented by a processor of the system. The processor first locates and extracts keypoints from a submission image and finds matches between those keypoints and the keypoints from a reference image using a near neighbor algorithm. The matches are clustered and the clusters are compared for keypoint matching. Matched clusters are further compared for detectable transformations. The processor may additionally implement natural language processing to filter matches based on the context of the use of the submission image in the submission and a patch detector for removing false positive features.

Abstract: A system and method for automated detection of figure element reuse. The system can receive articles or other publications from a user input or an automated input. The system then extracts images from the articles and compares them to reference images from a historical database. The comparison and detection of matches occurs via a copy-move detection algorithm implemented by a processor of the system. The processor first locates and extracts keypoints from a submission image and finds matches between those keypoints and the keypoints from a reference image using a near neighbor algorithm. The matches are clustered and the clusters are compared for keypoint matching. Matched clusters are further compared for detectable transformations. The processor may additionally implement natural language processing to filter matches based on the context of the use of the submission image in the submission and a patch detector for removing false positive features.

Abstract: A system for monitoring neural activity of a living subject is provided. The system may comprise a correspondence module configured to be in communication with (1) a neural module and (2) one or more additional modules comprising a sensing module, another neural module, and/or a data storage module. The neural module(s) are configured to collect neural data indicative of perceptions experienced by the living subject. The sensing module may be configured to collect (1) sensor data indicative of real-world information about an environment around the living subject, and/or (2) sensor data indicative of a physical state or physiological state of the living subject. The data storage module may be configured to store prior neural data and/or prior sensor data.

Abstract: A computer implemented method for optimizing a function is disclosed. The method may comprise identifying an empirical convex envelope, on the basis of a hyperparameter, that estimates the convex envelope of the function; optimizing the empirical convex envelope; and providing the result of optimizing the empirical convex envelope as an estimate of the optimization of the first function.

Abstract: A medical evaluation system includes an I/O module, a processing module, and an analysis module. The I/O module receives sensory data obtained by a motion sensor disposed in a mobile device carried by a patient at least when the patient is in a non-clinical environment. The processing module extracts medically relevant data from the sensory data received from the sensor in the mobile device. The relevant data includes one or more features of interest in the sensory data. The analysis module derives one or more surrogate biomarkers from the relevant data. The surrogate biomarkers represent at least one of a state or a progression of a medical condition of the patient. The mobile device may be a mobile phone carried by the patient and the sensor may include at least one of an accelerometer or a gyroscope that generates the sensory data to represent movements of the patient.

Abstract: A computer implemented method for optimizing a function is disclosed. The method may comprise identifying an empirical convex envelope, on the basis of a hyperparameter, that estimates the convex envelope of the function; optimizing the empirical convex envelope; and providing the result of optimizing the empirical convex envelope as an estimate of the optimization of the first function.

Abstract: In an embodiment, a computer-implemented method of displaying information within a window displayed on a graphical user interface is disclosed. The method may comprise displaying in the window a plurality of document summaries; displaying in the window, for each document summary in the list, a relevance input object; receiving a relevance value from the relevance input object; and updating the window display with a revised plurality of document summaries, wherein the revised plurality of document summaries are ordered by a relevance determined at least in part by the relevance value. The relevance of the revised plurality of document summaries may be determined at least in part using latent semantic analysis.

Abstract: A rehabilitation dashboard system and method for the display of information relating to the treatment and care of a patient in a rehabilitation setting is disclosed.

Abstract: A medical evaluation system includes an I/O module, a processing module, and an analysis module. The I/O module receives sensory data obtained by a motion sensor disposed in a mobile device carried by a patient at least when the patient is in a non-clinical environment. The processing module extracts medically relevant data from the sensory data received from the sensor in the mobile device. The relevant data includes one or more features of interest in the sensory data. The analysis module derives one or more surrogate biomarkers from the relevant data. The surrogate biomarkers represent at least one of a state or a progression of a medical condition of the patient. The mobile device may be a mobile phone carried by the patient and the sensor may include at least one of an accelerometer or a gyroscope that generates the sensory data to represent movements of the patient.