GEORGE MASON UNIVERSITY

Hyperspectral imaging (HSI) of biofluids for biometric applications is disclosed. A HSI device scans a region of a human subject's skin with sweat thereon, without requiring the human subject to touch any surface. The resulting HSI data is processed to identify aspects of the data that represent physical and/or chemical features that uniquely identify the subject. Processing the HSI data includes identifying one or more particular metabolites in the subject's sweat by analyzing wavelengths which those metabolites reflect. Processing the HSI data includes identifying one or more glands beneath the outermost surface of the subject's skin based on HSI-detected wavelength reflectance and wavelength penetration. The disclosed system may generate and store an identity profile corresponding to a human's unique identity features, as determined based on the HSI data processing. A subject's identity is verified by comparing subsequent HSI scans of his skin with sweat thereon to his stored identity profile.

An imaging system providing object motion preprocessing allows a switchable division of signals from different pixels into groups of center and surround pixels of arbitrary shapes and positions allowing tailoring of motion detection to particular objects whose motion should be identified, for example, using smaller center regions for smaller objects.

The present disclosure relates to affinity matrix compositions, kits comprising the same, and methods of using same for separating analytes, including biomarkers, from liquid samples. In certain embodiments, the methods described herein are useful for diagnosing and/or treating, preventing, or ameliorating a disease or disorder in a subject, including but not limited to infections with pathogens (e.g., borreliosis and tuberculosis).

A wireless multi-edge computing (MEC)-based road-side unit (RSU) (RSU-MEC) system and method for traffic management. The traffic management system includes: a first fifth-generation cellular (5G) roadside unit (RSU), the first RSU operable to couple to a first mobile user element (UE) via a first wireless link; a second 5G RSU, the second RSU operable to couple to a second mobile UE via a second wireless link; a first multi-access edge computing (MEC) host of the first 5G RSU, operable to provide one or more of compute resources, storage resources, and network resources by executing at least a first application to manage vehicle traffic flow in a first cellular zone; and a second MEC host of the second RSU, operable to provide one or more of compute resources, storage resources, and network resources by executing at least a second application to manage vehicle traffic flow in a second cellular zone, the second application being coupled to the first application via an application programming interface (API) in a manner that facilitates management of vehicle traffic flow in a combined cellular zone by the first application and the second application.

Aspects of the present disclosure generally relate to systems and processes for automated skin feature detection and analysis, and more particularly to identifying and assessing the characteristics and age of skin contusions, bruises, and other similar skin features using a deep learning model. Images of a patient's body part are captured via a digital camera with a light source. The parameters of the light source are determined, and other information is gathered, including skin color and medical history of the patient/subject. Images of an injured area are combined with contextual clinical information as inputs to a machine learning model. The machine learning model detects and estimates characteristics of skin features. In an exemplary embodiment, the machine learning model detects bruises on the skin, and estimates their age and outputs the estimate to an end user along with a measurement of the uncertainty in the estimate.

The present disclosure generally relates to a system for prediction of drug resistance, caused by genetic variations of proteins, in cancer patients who are candidates for chemotherapy treatment. More specifically, the disclosure provides methods that combine proteins involved in cancer drug resistance into a set of signaling network models to predict cancer drug resistance based on single and multiple protein variants that can be found in a patient's tumor sample. Said method allows a physician to predict whether a patient is likely to respond to treatment with a given chemotherapeutic reagent.

Systems and methods for countering the usage of autonomous or semi-autonomous vehicles for ramming attacks on a roadway are disclosed. Digital representations of physical trajectories (e.g., roadway travel routes) across which vehicles are expected or permitted to travel are generated based at least on travel-related data (e.g., sensor readings) received from the vehicles over wireless networks. The disclosed systems and methods further generate digital representations of physical trajectories across which vehicles are not permitted to travel, such that the impermissible physical trajectories constitute a deviation from a safe travel route. Additional travel-related data is continuously received from the vehicles in real-time, and the additional data may be combined with non-vehicle data (e.g., pedestrian travel data) and compared to the generated digital representations of permissible and impermissible physical trajectories to determine if the vehicles' physical trajectory is indicative of a harmful impermissible physical trajectory, such as a vehicular ramming attack.

A semantic-driven immersive telepresence system for bandwidth-efficient transmission of three-dimensional human representations. The system extracts compact semantic details from captured image data instead of transmitting complete raw 3D content. Color semantics are derived by estimating scene lighting characteristics using a lightweight model, combined with pre-captured base skin and clothing color. Motion semantics are extracted via keypoint detection of body joints, facial features, and hand positions. A regression-based method using keypoint-anchored vertices (KAVs) maps sparse keypoints to parametric human model parameters in real-time. The system transmits compressed semantic information over networks and reconstructs human representations at receiving devices. A multi-stage neural rendering pipeline with patch-based processing generates photo-realistic visual output. The approach significantly reduces bandwidth requirements compared to traditional bit-by-bit transmission of point clouds or meshes while maintaining low latency, real-time performance, and high visual quality suitable for interactive telepresence applications.

A system and method for predictive modeling of cellular systems assesses compound effectiveness on cellular metabolic and inflammatory states. Cellular samples are exposed to metabolic MRX sensors detecting oxidative stress, reporting cytoskeletal organization, or monitoring mitochondrial morphology, dynamics, or compartment-specific redox activity. Images of MRX sensor-labeled samples are captured using an imaging device and analyzed by trained predictive models to determine compound impact on immunological activation, inflammatory status, oxidative stress, mitochondrial function, and bio-energetic state. The system supports multisensor integration and spectral unmixing to generate multidimensional metabolic or ROS related MRX fingerprints that characterize cellular phenotypes, drug responses, and enable comparison to reference states. Preprocessing modules perform image normalization, augmentation, segmentation, and feature extraction to enhance model performance. Predictive models classify treatment conditions, identify perturbation-specific signatures, and enable compound ranking or mechanism-of-action inference. The system provides an objective, scalable, and high-content platform for drug screening, toxicity assessment, and inflammation research.

In an embodiment, a method comprising: adding a composition comprising a photochromic dye to a sample having an opioid compound to form a reacted product; illuminating an electromagnetic ray having a wavelength between about 100 nm to about 600 nm on the photochromic dye; and detecting the opioid compound in the sample.