Abstract: Embodiments of the present invention provide isolated proteins comprising antigen binding domains that bind kallikrein related peptidase 2 (hK2), including monospecific and bispecific antibodies. Additional embodiments of the invention provide polynucleotides encoding the hk2-specific proteins, vectors, host cells, and methods of making and using them.

Abstract: Systems and methods for model evaluation. A model is evaluated by performing a decomposition process for a model output, relative to a baseline input data set.

Abstract: Embodiments are presented herein of an open-loop test system for testing vertical-cavity surface-emitting lasers (VCSELs). A high-speed pulse generator may be used to produce nanoseconds pulses provided to the VCSEL device. A high-speed oscilloscope may be used to measure the resultant nanoseconds pulses across the VCSEL device. The VCSEL device voltage and VCSEL device current may be obtained from the measured nanosecond pulses according to compensation data derived from the system. A pre-test compensation procedure may be used to obtain the compensation data, which may include representative characteristics of each system component.

Abstract: A remote control device testing environment evaluates operational performance of physical implementations of remote control devices. This operational performance of the physical implementations of the remote control devices allows the integrated circuits of the remote control devices as well as integrated circuit interfaces electrically coupling these integrated circuits to each other to be evaluated. Additionally, the interconnection, such as electrical coupling to provide an example, between these integrated circuits and/or the integrated circuit interfaces can be evaluated which otherwise would not be evaluated by software simulation alone. Moreover, the evaluating of this operational performance of the physical implementations of the remote control devices allows these remote control devices to be in evaluated in a real world environment with exposure to various environmental factors, such as temperature, humidity, and/or electromagnetic interference to provide some examples.

Abstract: A system may include one or both of a light emitter and a light receiver. The system may include an optical filter adjacent one or both of the light emitter or the light receiver. The optical filter includes a wavelength selective scattering layer. The wavelength selective scattering layer may have a near-infrared scattering ratio of less than about 0.9. The filter may have a visible reflective haze ratio of greater than about 0.5. A method may include disposing the wavelength selective scattering layer adjacent one or both of the light emitter and the light receiver. An article may include the optical filter. The wavelength selective scattering layer may have an average near-infrared scattering of less than 60%, an average visible scattering of greater than 10%, and a difference between the % total visible reflectance and the % diffuse visible reflectance of less than 20.

Abstract: Systems and methods for model evaluation. A protected class model that satisfies an accuracy threshold is built by using: data sets for use by a modeling system being evaluated, and protected class membership information for each data set. A target for the protected class model is a protected class membership variable indicating membership in a protected class. Each predictor of the protected class model is a predictor of an evaluated model used by the modeling system. A target of the evaluated model is different from the target of the protected class model. Each predictor is a set of one or more variables of the data sets. For each predictor of the protected class model, a protected class model impact ranking value and a modeling system impact ranking value are determined.

Abstract: The disclosure describes techniques for interacting with visitors at a visitor interaction system. A method includes obtaining video data captured by the visitor interaction system, identifying an approach of a person, and analyzing the video data to determine an identity of the person. The method includes automatically and without user intervention determining that the person belongs to a visitor groups of a plurality of visitor groups. Each of the visitor groups corresponds to a response model that includes a plurality of response actions. At least one of the response actions includes an autonomous response action. The method includes identifying a response model corresponding to the visitor groups and initiating an autonomous response action associated with the response model. Initiating the autonomous response action including presenting a message to the person, monitoring a response to the message, and sending a report message to the user via a client device.

Abstract: Systems and methods for rendering spatial audio in accordance with embodiments of the invention are illustrated. One embodiment includes a spatial audio system, including a primary network connected speaker, including a plurality of sets of drivers, where each set of drivers is oriented in a different direction, a processor system, memory containing an audio player application, wherein the audio player application configures the processor system to obtain an audio source stream from an audio source via the network interface, spatially encode the audio source, decode the spatially encoded audio source to obtain driver inputs for the individual drivers in the plurality of sets of drivers, where the driver inputs cause the drivers to generate directional audio.

Abstract: Systems and methods for model evaluation. A protected class model that satisfies an accuracy threshold is built by using: data sets for use by a modeling system being evaluated, and protected class membership information for each data set. A target for the protected class model is a protected class membership variable indicating membership in a protected class. Each predictor of the protected class model is a predictor of an evaluated model used by the modeling system. A target of the evaluated model is different from the target of the protected class model. Each predictor is a set of one or more variables of the data sets. For each predictor of the protected class model, a protected class model impact ranking value and a modeling system impact ranking value are determined.

Abstract: A modified Kalman filter may include one or more neural networks to augment or replace components of the Kalman filter in such a way that the human interpretability of the filter's inner functions is preserved. The neural networks may include a neural network to account for bias in measurement data, a neural network to account for unknown controls in predicting a state of an object, a neural network ensemble that is trained differently based on different sensor data, a neural network for determining the Kalman gain, and/or a set of Kalman filters including various neural networks that determine independent estimated states, which may be fused using Bayesian fusion to determine a final estimated state.

Abstract: Disclosed herein are methods, compositions, and kits for rapid molecular diagnostics that integrate sample processing (including sample inactivation, sample lysis, nucleases inhibition, nucleic acid extraction, nucleic acid stabilization), nucleic acid amplification, and result readout into a single unified-one-pot reaction, enabling the molecular assay to be completed with minimal steps inside a single reaction vessel.

Abstract: A transceiver circuit includes a receiver front end utilizing a ring oscillator, and a transmitter front end utilizing a pass-gate circuit in a first feedback path across a last-stage driver circuit. The transceiver circuit provides low impedance at low frequency and high impedance at high frequency, and desirable peaking behavior.

Abstract: Fibrous structures containing filaments and solid additives, and more particularly to fibrous structures containing filaments and solid additives wherein the fibrous structure has three or more regions that exhibit different characteristics and/or properties and methods for making same, are provided.

Abstract: A package comprising a first metallization portion, a first integrated device coupled to the first metallization portion, a second integrated device coupled to the first metallization portion, a second metallization portion coupled to the first metallization portion through a first plurality of pillar interconnects, a first chiplet located between the first metallization portion and the second metallization portion, wherein the first chiplet is configured to be electrically coupled to the first integrated device through the first metallization portion, and a second chiplet located between the first metallization portion and the second metallization portion, wherein the second chiplet is configured to be electrically coupled to the second integrated device through the first metallization portion.

Abstract: A package comprising a first metallization portion, a first integrated device coupled to the first metallization portion through a first plurality of pillar interconnects, and a first chiplet located between the first integrated device and the first metallization portion. The first chiplet is coupled to the first integrated device through a first plurality of inter pillar interconnects. The first chiplet may include an active chiplet. The first chiplet may include a passive chiplet.

Abstract: Methods and systems for determining information for a specimen are provided. One system includes a computer subsystem and one or more components executed by the computer subsystem that include a deep learning (DL) model trained without labeled data (e.g., in an unsupervised or self-supervised manner) and configured to generate a reference for a specimen from one or more inputs that include at least a specimen image or data generated from the specimen image. The computer subsystem is configured for determining information for the specimen from the reference and at least the specimen image or the data generated from the specimen image.

Abstract: Methods and systems for determining information for a specimen are provided. One system includes a computer subsystem and one or more components executed by the computer subsystem that include a deep learning (DL) model trained without labeled data (e.g., in an unsupervised or self-supervised manner) and configured to generate a reference for a specimen from one or more inputs that include at least a specimen image or data generated from the specimen image. The computer subsystem is configured for determining information for the specimen from the reference and at least the specimen image or the data generated from the specimen image.

Abstract: Disclosed is a diagnostic panel of methylated genomic loci encoding microRNA (mgmiR) markers that demonstrated 90% sensitivity and 100% specificity in the detection of head and neck squamous cell carcinoma (HNSCC). These results represent the first use of quantitative MS-PCR for the detection of mgmiRs. In addition, this panel demonstrates the ability to detect hypermethylation in the adjacent mucosa of cancer patients, suggesting its utility in early detection. This panel is also capable of detecting cancer by using saliva, blood and FNA tissue samples.

Abstract: Disclosed are exemplary embodiments of thermal management and/or electromagnetic interference (EMI) mitigation materials including coated fillers (e.g., coated thermally-conductive, electrically-conductive, dielectric absorbing, and/or electromagnetic wave absorbing particles, sand particles coated with a binder, other coated functional fillers, combinations thereof, etc.). For example, a thermal management and/or EMI mitigation material may comprise a thermal interface material (TIM) including one or more coated fillers (e.g., coated thermally-conductive particles, sand particles coated with a binder, etc.), whereby the TIM is suitable for providing a thermal management solution for one or more batteries and/or battery packs (e.g., a battery pack for electric vehicle, etc.), or other device(s), etc.

Abstract: Disclosed is a diagnostic panel of methylated genomic loci encoding microRNA (mgmiR) markers that demonstrated 90% sensitivity and 100% specificity in the detection of head and neck squamous cell carcinoma (HNSCC). These results represent the first use of quantitative MS-PCR for the detection of mgmiRs. In addition, this panel demonstrates the ability to detect hypermethylation in the adjacent mucosa of cancer patients, suggesting its utility in early detection. This panel is also capable of detecting cancer by using saliva, blood and FNA tissue samples.