Abstract: The devices, assemblies, and methods described herein utilize photoacoustic principals to create a jet of fluid using a ultrasonic resonance member and a pulsed laser light beam. The ultrasonic resonance member is a treated substrate having an liquid interface surface in contact with a fluid. When a pulsed laser light beam is applied to the treated substrate, pressure is generated via induced ultrasonic waves to urge the fluid into a jet stream.

Abstract: A diagnostic test instrument for testing power system equipment may include a chassis having a number of bays capable of receiving test circuitry modules, which may be field inserted by a user desiring to perform a particular test. The instrument may include controller circuitry that may sense in each of the bays whether a respective test circuitry module is inserted therein, and then interrogate respective test circuitry modules in each respective bay to identify a type of the respective test circuitry module. Available testing capabilities may be identified according to the type of each of the respective test circuitry modules identified in respective bays. The controller circuitry may output configuration instructions to test circuitry modules, and respective test ports included in each of the respective test circuitry modules may be selectively illuminated as a configuration instruction to visually identify an assigned functionality of the respective test ports.

Abstract: The present disclosure relates to systems, apparatuses, and methods for assembling cartridges for aerosol delivery devices. The cartridges may be assembled by coupling a base of the cartridge to a carriage that is transported via a track. The track transports the carriages between various substations at which one or more parts are added to the base. The carriage may be lifted from the track by a lifter mechanism at each substation in order to perform assembly operations on the base. An inspection system may inspect the cartridges at various stages of completion at or between the various substations.

Abstract: The present disclosure relates to a system, comprising: a first server computing device configured to store various application data relating to the system, and control a first plurality of modules to simultaneously establish multiple logically separate and secure networks within a self-supported computing environment; a second server computing device configured to control a second plurality of modules to perform out-of-band management of the system; and a third server computing device configured to control a third plurality of modules to control inbound and outbound data traffic of the logically separate and secure networks. The system is scalable by at least adding additional one or more first server computing devices to host additional application data within the self-supported computing environment's secure configuration and logical separation of networks while maintaining the second and third server computing devices.

Abstract: A slack adjuster for use with a braking system which has an increased let-out length that enables the use of brake shoes having an increased thickness. The slack adjuster includes a dual spring and canister assembly, an external yoke trigger, or a combination of both the dual spring and canister assembly and the external yoke trigger. A method of retrofitting a truck-mounted brake system is provided, in which the slack adjuster is positioned within the brake system in order to increase the let-out length while maintaining a predetermined spatial envelope within the brake system. The slack adjuster has an increased let-out length enabling the use of thicker brake shoes without requiring modification of the interacting components of the truck mounted brake system since the overall size of the slack adjuster remains the same.

Abstract: Processing image data using deep neural networks is critical to many systems that desire to understand objects and their environment using camera sensors. Image scaling is a fundamental processing task required when managing image data. Although it is possible to scale image data using standard computer or graphics processors it would be highly advantageous in terms of throughput, latency and power consumption to manage image scaling using dedicated neural network hardware. The inventions contained herein provides methods to use existing neural network hardware to preform image scaling functions. Further, the inventions contained herein describe additional circuitry that can be added to neural network hardware to further enhance image scaling capabilities and efficiencies.

Abstract: A water detecting pressure-sensing device includes a metal housing including a cavity. A pressure sensor is disposed on a die and configured to generate a signal in response to a pressure variation. A protection medium at least partially fills the cavity and covers the die. One or more electrodes are disposed on the die and are used to detect a presence of a water droplet on the protection medium.

Abstract: An uninterruptible power supply (UPS) is provided including an interface to receive first sensor data indicative of operating information of a battery and second sensor data indicative of state-of-health characteristics of the battery from one or more sensors, and configured to communicate with a computer coupled to a plurality of UPSs, and a controller configured to receive the first sensor data, provide the first sensor data to the computer, receive an estimated battery health status (EBHS) of the battery based on the first sensor data and baseline battery health characteristics from the computer, receive the second sensor data from the one or more sensors, determine an actual battery health status (ABHS) of the battery based on the second sensor data, compare the EBHS and the ABHS, and communicate information to the computer to adjust the baseline battery health characteristics based on the comparison of the EBHS and the ABHS.

Abstract: In an aspect, the present disclosure provides a method of providing a dimensionally aware prediction for an object in an image captured by an image sensor, using a scale selective machine learning system, comprising: obtaining an input comprising image data of an object at an input image scale; generating a plurality of variant images based on re-scaling the input with a plurality of different image scaling factors, each variant image comprising the object at a variant image scale; generating a plurality of scale selective predictions based on the plurality of variant images, and assigning an in-scope response when the variant image comprises the object at an in-scope image scale, and determining a location prediction for the object based on a scale selective prediction comprising the in-scope response.

Abstract: A balloon catheter comprises an elongated, tubular shaft extending in a longitudinal direction, said shaft having a proximal end and a distal end. An inflatable balloon is supported along the distal end of the shaft, the balloon when inflated including a generally cylindrical barrel section forming a working surface, and generally conical end sections that do not form a part of the working surface. The balloon further includes at least one radiopaque identifier for indicating the relative position of the working surface, said identifier being provided on at least one of the conical end sections of the balloon so as to define the extent of the working surface. Related aspects are also disclosed.

Abstract: In an aspect, the present disclosure provides a method of generating scale selective training data for use in training a machine learning system to support scale selective image classification tasks, comprising obtaining a plurality of images comprising an object of interest at a plurality of image scales; assigning a desired label to each of the plurality of images based on an image scale of the object of interest in the each image, wherein the desired label comprises an in-scope response when the image scale comprises an in-scope image scale, and generating a set of training data for use in training the machine learning system to predict a scale of the object of interest, the training data comprising the plurality of images and corresponding desired labels.

Abstract: The present disclosures provides systems and methods for generating composite based data for use in machine learning systems, such as for use in training a machine learning system on the composite based data to identify an object of interest. In an aspect, a method of generating composite based data for use in training machine learning systems comprises: receiving a plurality of images, each of the plurality of images having a corresponding label; generating a composite image comprising the plurality of images, each of the plurality of images occupying a region of the composite image; generating a response map for the composite image, the response map having a plurality of response entries, each response entry encoded with a desired label corresponding to a fragment of the composite image, and generating composite data comprising the desired label of a response entry and image data corresponding to the fragment of the composite image.

Abstract: A diagnostic test instrument for testing power system equipment may include a chassis having a number of bays capable of receiving test circuitry modules, which may be field inserted by a user desiring to perform a particular test. The instrument may include controller circuitry that may sense in each of the bays whether a respective test circuitry module is inserted therein, and then interrogate respective test circuitry modules in each respective bay to identify a type of the respective test circuitry module. Available testing capabilities may be identified according to the type of each of the respective test circuitry modules identified in respective bays. The controller circuitry may output configuration instructions to test circuitry modules, and respective test ports included in each of the respective test circuitry modules may be selectively illuminated as a configuration instruction to visually identify an assigned functionality of the respective test ports.

Abstract: A method at a computing device for sharing data, the method including defining a dynamically linked data library (DLDL) to include executable code; loading the DLDL from a first process, the loading causing a memory allocation of shared executable code, private data and shared data in a physical memory location; mapping the memory allocation of shared executable code, private data and shared data to a virtual memory location for the first process; loading the DLDL from a second process, the loading causing mapping of the memory allocation of shared executable code and the shared data for the first process to be mapped to a virtual memory location for the second process; and allocating private data in physical memory and mapping to a virtual memory location for the second process.

Abstract: The present invention is directed in part to soybean variety CL1941276, CL1941547, CL1941920, CL1941244, and/or CL1941256 breeding and development. The present invention particularly relates to soybean variety CL1941276, CL1941547, CL1941920, CL1941244, and/or CL1941256 and its seed, cells, germplasm, plant parts, and progeny, and methods of using CL1941276, CL1941547, CL1941920, CL1941244, and/or CL1941256, e.g., in a breeding program.

Abstract: The present invention is directed in part to soybean variety CW1660196, EE1803165, EE1762224, EE1762072, and/or EE1861244 breeding and development. The present invention particularly relates to soybean variety EE1803165, EE1762224, EE1762072, and/or EE1861244 and its seed, cells, germplasm, plant parts, and progeny, and methods of using EE1803165, EE1762224, EE1762072, and/or EE1861244, e.g., in a breeding program.

Abstract: The present invention is directed in part to soybean variety CL1941232, CL1941326, CL1941886, CL1941882, CL1941366, CL1941287, CL1941298, CL1941446, CL1941831, and/or CL1942000 breeding and development. The present invention particularly relates to soybean variety CL1941232, CL1941326, CL1941886, CL1941882, CL1941366, CL1941287, CL1941298, CL1941446, CL1941831, and/or CL1942000 and its seed, cells, germplasm, plant parts, and progeny, and methods of using CL1941232, CL1941326, CL1941886, CL1941882, CL1941366, CL1941287, CL1941298, CL1941446, CL1941831, and/or CL1942000, e.g., in a breeding program.

Abstract: A drainage system for use with a slack adjuster for a railway brake rigging wherein the slack adjuster includes a main spring housing, a cone nut housing enclosing a critical operating area of the slack adjuster, and an over travel housing. The drainage system includes at least one opening extending through a sidewall portion of the main spring housing. The opening is configured to allow fluid and/or contaminates to drain therethrough to reduce exposure of the critical operating area of the slack adjuster to the fluid and/or contaminants. A seal/splash guard can be provided at the intersection of the main spring housing and the cone nut housing to prevent fluid and contaminants from entering into the cone nut housing.

Abstract: A method at a computing device for sharing data, the method including defining a dynamically linked data library (DLDL) to include executable code; loading the DLDL from a first process, the loading causing a memory allocation of shared executable code, private data and shared data in a physical memory location; mapping the memory allocation of shared executable code, private data and shared data to a virtual memory location for the first process; loading the DLDL from a second process, the loading causing mapping of the memory allocation of shared executable code and the shared data for the first process to be mapped to a virtual memory location for the second process; and allocating private data in physical memory and mapping to a virtual memory location for the second process.