Abstract: An agricultural system includes: one or more weight sensors that detect a weight of material in a first material receptacle and generate sensor data indicative thereof; one or more processors; memory; and computer executable instructions, stored in the memory, that, when executed by the one or more processors, configure the one or more processors to: determine a change in weight of material in the first material receptacle based on first sensor data indicative of a weight of material in the first material receptacle at a first time and second sensor data indicative of a weight of material in the first material receptacle at a second time; determine a material transfer rate indicative of a rate at which a material transfer subsystem transfers material based on the determined change in weight; and determine a fill level of material in a second material receptacle based on the determined material transfer rate.

Abstract: Multi-faceted machine learning model systems and methods are disclosed that integrate historical data, user-specific criteria, and prioritized real-time event updates. The machine learning model systems and methods may be selected and weighed to optimize simulation accuracy based on event type, player status, and user-defined constraints, such as risk tolerance and preference for specific teams, sports or players. The machine learning model is applied to a first historical outcome and a second historical outcome to generate a predictive outcome responsive to a user query, the user query having a first keyword vector and a second keyword vector. The machine learning model is applied to a real-time event and the predictive outcome to generate an updated predictive outcome. A prediction error indicative of a difference between the predictive outcome and the updated predictive outcome can be determined.

Abstract: A system and method for measuring mutual inductance between adjacent first communication transmission line and second communication transmission line is disclosed. The system includes a mutual inductance measurement circuit that includes a coupling generator which biases the first communication transmission line with a current ramp signal; a sample and hold circuit which captures an induced voltage on the second communication transmission line using a switched capacitor storage element; a switched capacitor integrator configured to integrate the induced voltage onto an output voltage node; and a comparator configured to switch states once the switched capacitor integration has surpassed a reference trippoint.

Abstract: Fungal sweet-taste modifying protein variants (designated Honey Truffle Sweetener (HTS) protein variants), and polynucleotides encoding the protein variants are described. Specifically, Myd (HTS) protein variants with sweet taste modulation activity, and the cDNA encoding the same, are described, along with methods for isolating such cDNA and for isolating and expressing such proteins. Also disclosed are sweetening compositions which include the proteins of the invention, and methods to provide improved flavor to a product for oral administration.

Abstract: Systems and methods disclosed herein include a portable air pump and inflator system comprising an electric air compressor, a compressor housing enclosing the electric air compressor, an air hose attached or attachable to an air outlet of the electric air compressor, and a housing base attached to the compressor housing. The housing base comprises a rigid base portion that is attached to the compressor housing and a plurality of flexible foot extensions that extend from the rigid base portion. The flexible foot extensions are configured to support the portable air pump and inflator system on a surface and dampen vibrations caused by the operation of the electric air compressor.

Abstract: Systems, apparatuses, and methods are provided for enhancing users' overall experiences with physical items by supplementing their physical experiences with digital experiences. According to an embodiment, a user uses an electronic device to scan a smart tag associated with an item to obtain an item identifier of the item. The electronic device sends the item identifier to a server, which selects digital content related to the item and sends the selected digital content to the user's electronic device for display.

Abstract: A computer system, while displaying a first view, including a first representation of a first portion of a physical environment, detects a request to activate a first type of computer-generated sensory adjustment, and in response, displays a second representation of the first portion of the physical environment with a first display property adjusted relative to the first representation in accordance with the first type of computer-generated sensory adjustment. The computer system detects a request to activate a second type of computer-generated sensory adjustment, and in response, displays a third representation of the first portion of the physical environment with the first display property adjusted relative to the first representation in accordance with the first type of computer-generated sensory adjustment, and a second display property adjusted relative to the second representation in accordance with the second type of computer-generated sensory adjustment.

Abstract: A method may include detecting, by a computer executing a machine-learning model, a vehicle located within an area, detecting, by the computer executing the machine-learning model, a person approaching the vehicle, and, in response to the person approaching the vehicle, executing, by the computer executing the machine-learning model, a deterrence action.

Abstract: Computerized systems and methods for digital histopathology analysis are disclosed. In one embodiment, a series of deep learning networks are used that train, in succession, on datasets of successively increasing relevance. In some examples, learned parameters from at least a portion of one deep learning network are transferred to a next deep learning network in a succession of deep learning networks. In some examples, at least one of the deep learning networks includes a self-supervised learning network. In some examples, at least one of the deep learning networks includes an attention-based learning network. These and other examples and details are disclosed herein in various contexts including, for example evaluating genotypes of cancer tissue (e.g., bladder, prostate, or lung cancer) using histopathology images. In some examples, the context is to assist in predicting presence or absence of certain cancer genotypes and/or predicting patient responses to a new treatment.

Abstract: An antenna system comprises a driven antenna element connected to a printed circuit board (PCB), and a plurality of PCB extenders provided by electrical conductors connected to a PCB ground plane for cooperation with the driven antenna element in signal communication. In an eyewear device that incorporates the antenna system, the plurality of PCB extenders are provided by conductive structural elements incorporated in an eyewear frame.

Abstract: The disclosures herein relate to novel compounds of Formula (1a): and salts thereof, wherein W, Z, L, R1 and R2 are defined herein, and their use in treating, preventing, ameliorating, controlling or reducing the risk of disorders associated with CGRP receptors.

Abstract: Systems and techniques are provided for providing machine learning-based customized recommendations based on accessible ingredients to for making craft cocktails. For example, a process can include obtaining ingredient inventory information indicative of one or more ingredient items associated with a user and determining, using a trained neural network, one or more candidate recipes based on the ingredient inventory information. Based on determining that a given candidate recipe includes at least one missing ingredient item that is not included in the ingredient inventory information, a recommended substitution can be determined for the missing ingredient item. A plurality of recipe recommendations can be generated, using the trained neural network, based on the one or more candidate recipes and one or more recommended substitutions, wherein the plurality of recipe recommendations includes at least one recipe recommendation that is modified based on the recommended substitution.

Abstract: Provided herein is a method for enabling communications between a user and one or more recipients. The method comprises using one or more sensors to track at least one position or motion characteristic of the user thereby generating sensor data, wherein the at least one position or motion characteristic is associated with an eye or a head of the user. The method further comprises processing the sensor data to identify the one or more recipients with whom the user intends to communicate. The method further comprises processing data associated with non-audible speech of the user to generate one or more utterances, wherein the one or more utterances comprises audio or text intended by the user for the one or more recipients.

Abstract: The specification describes an acid condensation catalyst comprising: a zeolite having a pore size of 10 tetrahedral atoms, a porosity of ?0.05 mL/g in the range of 20-100 ?, and a silica: alumina ratio (SAR) of 10 to 50; an alumina binder in which the zeolite is dispersed; and at least one metal; wherein the acid condensation catalyst has a porosity of ?0.06 mL/g in the range of 20-100 ? as measured by physisorption using the BJH method. Also described is a method for preparing the catalyst, and a process of carrying out acid condensation on a feed stream comprising one or more oxygenated compounds, which is carried out in the presence of a catalyst as described.

Abstract: An A-Arm assembly for All-Terrain Vehicles. The A-arm assembly comprises an A-Arm with a slug. The slug can enhance assembly of an A-Arm and reduce manufacturing costs. An A-Arm slug can enable efficient assembly of A-Arms to an ATV. The slug can accommodate different style A-Arms, for example, the slug can have a beveled or angled face to match a square end of an A-Arm. Alternatively, the slug can have an angled spindle connecting portion and square faces that match an A-Arm.

Abstract: A breathing assistance apparatus has a housing with an engagement feature and an electrical component in the housing and a removable component 171. The electrical component has a receptacle 233. The removable component 171 has an electrical connector 178 that is a close or tight fit in the receptacle 233 of the electrical component to assist with holding the removable component 171 in connection with the electrical component. The removable component has a tab 172 with a terminal end portion 172b that can be flexed relative to the rest of the removable component. An engagement feature 174 is provided on the terminal end portion of the tab and engages with the engagement feature of the housing is to inhibit disconnection of the removable component from the housing in the absence of actuating the terminal end portion 172a of the removable component to flex the tab.

Abstract: The present disclosure is directed to processing iron-containing feedstocks using oxalic acid to cost-effectively and cleanly transform low-cost iron feedstocks into iron-containing products (e.g., metallic iron and/or iron oxide) of high purity. In general, the methods of production using the systems described herein may include leaching low-purity iron feedstocks using a lixiviant including oxalic acid and an iron-complexing additive. The iron-complexing additive may suppress formation of iron (II) oxalate crystals and iron (III) oxalate crystals as leaching of a low-purity iron feedstock is carried out using oxalic acid, thus improving process kinetics and increasing the amount of iron that goes into solution during the leaching operation and ultimately recovered as a high-purity iron-containing product (e.g., metallic iron and/or iron oxide).

Abstract: Methods, apparatus, and processor-readable storage media for security-related risk detection using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data related to at least one user associated with at least one interaction; identifying information pertaining to the at least one user by processing at least a portion of the obtained data using one or more artificial intelligence techniques; determining, based at least in part on at least a portion of the identified information, one or more security risks associated with the at least one user within a context of the at least one interaction; and performing one or more automated actions based at least in part on the one or more determined security risks.

Abstract: An apparatus and method for signaling and transmitting data through an optical link is described. The apparatus may include a connector including a first plurality of contacts compatible with an enhanced SFP (SFP+) connector. The connector further includes an additional contact formed at a space adjacent to the first plurality of contacts. A tone generator couples to the additional contact to receive a first signal and to generate a first distinct tone indicative of the first signal for transmission via the additional contact. The method may include generating a first distinct tone indicative of a first signal providing control or status of an apparatus and transmitting or receiving a differential data signal over a portion of a first plurality of contacts compatible with an enhanced SFP (SFP+) connector. The first distinct tone is transmitted over the additional contact formed in a space adjacent to the first plurality of contacts.

Abstract: Systems, computer program products, and methods are described herein for automated security verification across network devices. The method includes determining a first end-point device configuration of a first end-point device associated with a network. The method also includes determining, via a machine learning model, one or more first end-point device tests based on the first end-point device configuration. The one or more first end-point device tests is based on at least one of the one or more first end-point device programs installed on the first end-point device. The method further includes causing an execution of at least one of the one or more first end-point device tests on the first end-point device. The method still further includes determining a first end-point device validation rating based on the execution of the at least one of the one or more first end-point device tests on the first end-point device.