Abstract: A computing system includes a processor having access to data associated with a plurality of devices of a network. The processor is configured to leverage the data to execute a loss model that estimates cyber risk loss distribution of the network associated with healthcare environment and infrastructure using bond percolation on a mixed random graphs approach.

Abstract: A single molecule sensing or detecting device includes a first electrode and a second electrode separated from the first electrode by a gap. The first electrode and the second electrode have an opening formed therethrough. At least one of the first electrode and the second electrode is functionalized with a recognition molecule. The recognition molecule has an effective length LI and is configured to selectively bind to a target molecule having an effective length L2. The size of the gap is configured to be greater than L2, but less than or equal to the sum of LI and L2.

Abstract: High-temperature thermochemical energy storage materials using doped magnesium-transition metal spinel oxides are provided. —transition metal spinel oxides, such as magnesium manganese oxide (MgMn)3O4, are promising candidates for high-temperature thermochemical energy storage applications. However, the use of these materials has been constrained by the limited extent of their endothermic reaction. Embodiments described herein provide for doping magnesium-transition metal spinel oxides to produce a material of low material costs and with high energy densities, creating an avenue for plausibly sized modules with high energy storing capacities.

Abstract: This disclosure describes systems and methods for critical angle reflection (CAR) imaging to quantify molecular binding kinetics on a glass surface in some embodiments. CAR is a label-free method that measures the reflectivity change near a critical angle in response to molecular binding induced refractive index changes on the sensor surface. The sensitivity and dynamic range of CAR is tunable by varying the incident angle of light, which allows for optimizing the measurement for ligands with different sizes in both biomolecular and cell-based studies.

Abstract: Various embodiments of a system and associated method for detecting and localizing gunshots are disclosed herein.

Abstract: A urine collection assembly includes a container; a funnel removably coupled to the container, the funnel in fluid communication with the container; a first collection chamber in selective communication with the funnel; a valve configured to allow selective communication between the first collection chamber and the funnel; a second collection chamber in selective communication with the funnel; and a lid removably coupleable to the funnel. A saddle may be removably coupleable to the funnel and configured to guide urine into the container.

Abstract: An electrochemical impedance spectrogram (EIS) measurement system includes a working electrode configured to provide a triangular excitation signal to a subject, and a counter electrode configured to measure an electrical parameter in response to the triangular excitation signal. Based on the triangular excitation signal and the measured electrical parameter, an EIS of the subject is obtained. A method for measuring an EIS of a subject includes causing a triangular excitation signal to be applied to a subject and obtaining electrical parameter measurements in response to the triangular excitation signal. The EIS of the subject is obtained based on the triangular excitation signal and the electrical parameter measurements.

Abstract: Provided herein are methods and compositions for rapid, highly sensitive detection of SARS-CoV-2 in biological samples. In particular, provided herein is a rapid, low-cost method for detecting SARS-CoV-2 that provides reliable, visible test results and does not require PCR reagents, elaborate biosafety precautions, or sophisticated laboratory equipment.

Abstract: Sub-micrometer bioparticles are separated by size in a microfluidic channel utilizing a ratchet migration mechanism. A structure within the microfluidic channel includes an array of micro-posts arranged in laterally shifted rows. Reservoirs are disposed at each end of the microfluidic channel. A biased AC potential is applied across the channel via electrodes immersed into fluid in each of the reservoirs to induce a non-uniform electric field through the microfluidic channel. The applied potential comprises a first waveform with a first frequency that induces electro-kinetic flow of sub-micrometer bioparticles in the microfluidic channel, and an intermittent superimposed second waveform with a higher frequency. The second waveform selectively induces a dielectrophoretic trapping force to selectively impart ratchet migration based on particle size for separating the sub-micrometer bioparticles by size in the microfluidic channel.

Abstract: Compounds of General Formula I may harvest electrogenerated excitons via metal-assisted delayed fluorescence (MADF). The compounds have utility in light emitting diodes and light emitting devices.

Abstract: Provided herein are dynamic adaptive scheduling (DAS) systems. In some embodiments, the DAS systems include a first scheduler, a second scheduler that is slower than the first scheduler, and a runtime preselection classifier that is operably connected to the first scheduler and the second scheduler, which runtime preselection classifier is configured to effect selective use of the first scheduler or the second scheduler to perform a given scheduling task. Related systems, computer readable media, and additional methods are also provided.

Abstract: A system and associated methods for accurate localization of seizure onset zone (SOZ) from independent components (IC) of resting state functional magnetic resonance imaging (rs-fMRI) to improve surgical outcomes in children with Drug Resistant Epilepsy (DRE) are disclosed. The system and methods define a phased approach, where fMRI noise-related biomarkers are used through high fidelity image processing techniques to eliminate noise ICs. Then SOZ markers are used through a maximum likelihood-based classifier to determine SOZ localizing ICs.

Abstract: Synthetic antimicrobial peptides, compositions comprising thereof, and methods of use for modulating one or more symptoms of an infection in a subject are disclosed. In some aspects, the infection is caused by mycobacteria, for example, a nontuberculous mycobacterium such as Mycobacterium abscessus. In other aspects, the infection is caused by Escherichia coli, Pseudomonas aeruginosa, or methicillin-resistant Staphylococcus aureus (MRSA). Also disclosed are methods of identifying synthetic antimicrobial peptides against a pathogen with no known effective treatment using a library of synthetic peptides.

Abstract: Systems and methods are provided for predicting microhardness properties of a weld that defines a weld joint between at least two workpieces. The system includes a processor programmed to: receive temperature data that includes temperature values each attributed to a corresponding one of a plurality of points of the weld at corresponding times during a welding process used to produce the weld, determine peak temperature values and cooling rate values for each of the points of the weld based on the temperature values, predict a three-dimensional (3D) distribution of microhardness values of the weld based on a machine learning method that evaluates the peak temperature values and the cooling rate values, and generate display data based on the 3D distribution of microhardness values.

Abstract: A processor is configured to implement a machine learning model that is trained to select transcripts in blood for distinguishing neurodegenerative diseases. The algorithm is developed via machine learning and leverages concepts associated with blood-based changes in mRNA gene expression for differentiating patients of any neurodegenerative disease regardless of the proteins or their post-translational modifications occurring in disease.

Abstract: Based on traffic images characteristics, a general pre-processing system and method reduces input size of neural network object recognition models to focus on necessary regions. The system includes a light neural network (binary or low precision; based on configuration) to detect target regions for further processing and applies a deeper model to those specific regions. The present disclosure provides experimentation results on various types of methods, such as conventional convolutional neural networks, transformers, and adaptive models, to show the scalability of the system.

Abstract: A consensus-based decentralized multi-robot approach is presented for reconstructing a discrete distribution of features, modeled as an occupancy grid map, that represent information contained in a bounded planar 2D environment, such as visual cues used for navigation or semantic labels associated with object detection. The robots explore the environment according to a random walk modeled by a discrete-time discrete-state (DTDS) Markov chain and estimate the feature distribution from their own measurements and the estimates communicated by neighboring robots, using a distributed Chernoff fusion protocol. Under this decentralized fusion protocol, each robot's feature distribution converges to the ground truth distribution in an almost sure sense.

Abstract: Systems and methods for a wearable “exo-shell” to improve the gait of elderly people during obstacle avoidance tasks are disclosed. With payload and energy expenditure as a main focus of this design, the present system leverages switchable, passive systems, in combination with lightweight materials that minimize additional metabolic costs, while remaining as “transparent” to the user as possible when inactive.

Abstract: A method for increasing the temperature-resiliency of a neural network, the method comprising loading a neural network model into a resistive nonvolatile in-memory-computing chip, training the deep neural network model using a progressive knowledge distillation algorithm as a function of a teacher model, the algorithm comprising injecting, using a clean model as the teacher model, low-temperature noise values into a student model and changing, now using the student model as the teacher model, the low-temperature noises to high-temperature noises, and training the deep neural network model using a batch normalization adaptation algorithm, wherein the batch normalization adaptation algorithm includes training a plurality of batch normalization parameters with respect to a plurality of thermal variations.

Abstract: Composite material can include a matrix material, a fiber dispersed in the matrix material, and an ultraviolet (UV)-light sensitive mechanophore grafted to a surface of the fiber. A method for making a fiber-reinforced polymer composite can include contacting a fiber in a first solution, rinsing and then drying intermediate fiber, contacting dried fiber in a third solution, rinsing, and then drying the rinsed fiber thereby generating functionalized fiber that is sensitive to ultraviolet light. The functionalized fiber can be combined with a polymer matrix material, cured, and irradiated, thereby generating a fiber-reinforced polymer composite.