The present invention is directed to a method of identifying autism spectrum disorder (ASD) phenotype 1 patients, wherein the method comprises: administering an Nrf2-activator to an ASD patient previously diagnosed with idiopathic ASD or a subject displaying clinical signs of ASD, and identifying the ASD patient as an ASD phenotype 1 patient if the patient shows a negative response after administration of the Nrf2-activator. Likewise, the present invention is directed to a method for classifying autism spectrum disorder (ASD) phenotype 1 patients, the method comprising: administering an Nrf2-activator to a subject, and observing if the subject shows a negative response after administration of the Nrf2-activator, in which the subject is a patient previously diagnosed with idiopathic ASD or a subject displaying clinical signs of ASD and in which the negative response supports classification of the subject as an ASD phenotype 1 patient.

First sensor data may be acquired from a first galvanic skin response sensor monitoring a first user. Second sensor data may be acquired from a second galvanic skin response sensor monitoring a second user. At least one programmable processor may generate a compatibility score between the first user and the second user. The generating may include executing a compatibility algorithm to generate the compatibility score based at least on a comparison of at least one type of response contained in the first sensor data and the second sensor data. A client device may generate an electronic indication of the compatibility score.

A system for assigning a social attribute class to a human subject in a predefined closed environment includes an image capturing component, a pose detection component configured to perform pose detection and tracking of a human subject in real-time, an action detection component configured to detect an action of the human subject, an activity detection component configured to relate a sequence of actions to detect an activity of the human subject, and a social attribute classification component. The social attribute classification component is configured to determine an average speed (s) of the human subject as a first social attribute, an interaction time of the human subject (T.sub.int) as a second social attribute, an analysis time (T.sub.anal) as a third social attribute, and automatically assigns a social attribute class to the human subject based on the values of the first, second and third social attributes.

Described herein are biomimetic Janus particles useful as artificial antigen presenting cells capable of activating T cells in vitro. “Bull's eye” ligand patterns mimicking either the native or reverse organization of the T cell immunological synapse are provided on the surface of nano- or micro-sized particles. Methods for activating T cells in vitro using biomimetic Janus particles described herein are also provided. T cells activated by the biomimetic Janus particles can be used in adoptive immunotherapies for treating cancer, tolerance induction in autoimmune disease, autologous immune enhancement therapy, and viral infection immunotherapy. Also described herein are methods for producing a biomimetic Janus particle.

According to the invention, is provided a data processing system for determining congruence or incongruence between the body language and the Speech of a person, comprising a self-learning machine, such as a neutralneural network, arranged for receiving as input a dataset including : approved data of a collection of analysed Speeches of persons, said approved data comprising for each analysed Speech: * a set of video sequences, comprising audio sequences and visual sequences, each audio sequence corresponding to one visual sequence, and * an approved congruence indicator for each of said video sequence—said self-learning machine being trained so that the data processing system is able to deliver as output a congruence indicator.

The present systems and methods provide a mechanism to assess viewer behavior, features of stimuli, and the interaction between viewer behavior and stimuli. The systems and methods described herein for quantifying blink response and blink inhibition provide moment-by-moments measurements of viewer engagement by measuring what is or is not engaging enough to warrant viewers' inhibition of blinking. The present disclosure describes measures of visual scanning, eye movements, blink data, and blink timing data to derive a measure of how engaged a person is with what he or she is looking at. Blink-related data as a measure of viewer engagement provides a mechanism for determining the most engaging spatial and temporal aspects of a stimulus.

A technique for enabling efficient retrieval of a digital representation of personality data of a user (402) by a client device (406) from a server (404) is disclosed, wherein the digital representation of the personality data is processed at the client device (406) to provide a user-adapted service to the user (402). A method implementation of the technique is performed by the server (404) and comprises storing a neural network being trained to compute personality data of a user based on input obtained from the user (402), receiving, from the client device (406), a request for a digital representation of personality data for a user (402), and sending, to the client device (406), the requested digital representation of the personality data of the user (402), wherein the personality data of the user is computed using the neural network based on input obtained from the user (402).

A technique for enabling efficient retrieval of a digital representation of personality data of a user (402) by a client device (406) from a server (404) is disclosed, wherein the digital representation of the personality data is processed at the client device (406) to provide a user-adapted service to the user (402). A method implementation of the technique is performed by the server (404) and comprises storing a neural network being trained to compute personality data of a user based on input obtained from the user (402), receiving, from the client device (406), a request for a digital representation of personality data for a user (402), and sending, to the client device (406), the requested digital representation of the personality data of the user (402), wherein the personality data of the user is computed using the neural network based on input obtained from the user (402).

Systems and methods for detection, classification, and diagnosis of vocal anomalies in vocal streams are disclosed. Discussed are a method for generating a biometric voiceprint for analyzing user vocal streams to detect and classify vocal anomalies and a method for notifying the appropriate party, where the notification is based on the diagnosis reported by the system. Manual classification in the event of automatic classification failure is discussed, where the manual classification data can be used as training data to improve the functionality of the classification model.

An auditory projective test is provided that emphasizes a shift in focus from visual and verbal/linguistic stimuli to an examination of the phenomena of acoustic and sonic association. The design discovers a “canon” of sound stimuli that may provide psychological associations with the aim to further inform and compliment the findings of Jung's word association test. The design includes a computer software program that gathers and calculates data in Excel format. Jung's traditional Word Association test is presented alongside the sound association test. The design may include the use of digital video recording to help observe and demonstrate behavioral responses. Additionally, the design may include the addition of a digital interface that will reintroduce the measurement of certain physiological data originally used in Jung's association experiments.