Abstract: An anti-ice swirl system for an aircraft engine includes a nacelle including a first nacelle section exposed to ambient environment and facing an oncoming airstream when an aircraft powered by the engine is in flight. The first nacelle section defines a circumferential D-duct. The anti-ice swirl system also includes a nozzle configured to inject into and circulate through the D-duct a controlled unsteady flow of heated fluid. The controlled unsteady flow mixes newly injected heated fluid with air inside the D-duct and mitigates icing of the first nacelle section when the aircraft is in flight.

Abstract: Blockchain-enabled industrial devices and associated systems are configured to support the use of industrial blockchains in connection with product and machine tracking, subscription-based industrial services, device lifecycle management, and other functions. Collections of industrial devices can collectively serve as an industrial blockchain system, with multiple such systems within a supply chain yielding an industrial blockchain ecosystem. This architecture can create distributed, decentralized, tamper-proof records of manufacturing statistics for a product, a product's history within the larger supply chain, industrial asset usage histories that can be leveraged in connection with lifecycle management, machine usage history for use in connection with subscription-based machine operation, and other such information.

Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: The present invention concerns a chemical mechanical polishing pad having a polishing layer. The polishing layer contains an extruded sheet. The extruded sheet is a photopolymerizable composition containing a block copolymer, a UV curable acrylate, and a photoinitiator.

Abstract: A system for use with a misregistration metrology tool (MMT), the system including a database including a plurality of process variation (PV) categories and a corresponding plurality of parameter sets and a process variation accommodation engine (PVAE) including a measurement site process variation category associator (MSPVCA) operative to associate a measurement site being measured by the MMT, at least partially based on an MMT output relating to the measurement site, with a measurement site process variation category (MSPVC), the MSPVC being one of the plurality of PV categories, a measurement site parameter set retriever (MSPSR) operative to retrieve a measurement site parameter set (MSPS) corresponding to the MSPVC and a measurement site parameter set communicator (MSPSC) operative to communicate the MSPS to the MMT.

Abstract: Disclosed herein are antimicrobial compounds compositions, pharmaceutical compositions, the method of use and preparation thereof. Some embodiments relate to boronic acid derivatives and their use as therapeutic agents, for example, ?-lactamase inhibitors (BLIs).

Abstract: Systems and methods are provided for performing image processing. An exemplary method includes: receiving neuromorphic camera data from at least one neuromorphic camera; producing, using the neuromorphic camera data, a plurality of unaligned event data, where the unaligned event data are unaligned in time; aligning the unaligned event data in time producing aligned event data; generating, using a model and the aligned event data, a plurality of aligned event volumes; and aggregating the aligned event volumes to produce an image.

Abstract: A processor may receive data regarding an emergency event. The processor may identify, using an artificial intelligence model, one or more features regarding the emergency event. The processor may determine that the one or more features are associated with one or more emergency response tasks. The processor may generate an action plan that incorporates the one or more emergency response tasks. The processor may output the action plan to a user.

Abstract: Embodiments of the present disclosure generally relate to aircraft engines and, more particularly, to aircraft engine inlet monitoring using neuromorphic sensors. In some embodiments, an event associated with debris in the inlet of an aircraft engine may be identified based on a change in a visual data characteristic from a visual neuromorphic sensor. In response to identifying the event, one or more other neuromorphic sensors coupled to the aircraft may be activated. Other embodiments may be disclosed or claimed.

Abstract: Embodiments of the present disclosure generally relate to aircraft engines and, more particularly to data acquisition for aircraft engines using thermal neuromorphic sensors. In some embodiments, an event associated with the aircraft engine may be identified based on a change in a thermal data characteristic measured from a thermal neuromorphic sensor. In response to identifying the event associated with the aircraft engine, one or more other sensors coupled to the aircraft engine may be activated and data received from the activated sensors stored in memory. Other embodiments may be disclosed or claimed.

Abstract: Embodiments of the present disclosure generally relate to aircraft engines and, more particularly, to detecting material failures associated with aircraft engines using neuromorphic sensors. In some embodiments, an event associated with a material failure in the portion of an aircraft engine is identified based on a change in a data characteristic from a neuromorphic sensor. In response to identifying the event associated with the material failure of the aircraft engine, at least one other sensor coupled to the aircraft engine is activated, where the activated sensor(s) is configured to collect data associated with the aircraft engine synchronously. Other embodiments may be disclosed or claimed.

Abstract: Embodiments of the present disclosure generally relate to aircraft engines and, more particularly to data acquisition for aircraft engines using neuromorphic sensors. In some embodiments, an event associated with the aircraft engine may be identified based on a change in a data characteristic measured from a neuromorphic sensor and, in response to identifying the event associated with the aircraft engine, at least one other sensor coupled to the aircraft engine may be activated. Other embodiments may be disclosed or claimed.

Abstract: A laser powder bed fusion (LPBF) system includes a build plate, a build station piston configured to adjust the height of the build plate as a part is built on top of the build plate, and a powder chamber configured to contain loose build powder, wherein the powder chamber surrounds the build plate. The LPBF system also includes a laser system configured to direct a laser beam onto the loose build powder to form a melt pool, which forms a layer of the part as the melt pool solidifies. As each layer of the part is formed, the build station piston lowers the build plate and part by a predetermined distance corresponding to a desired thickness of a next layer of the part.

Abstract: The present disclosure provides for the generation of microstructural images of components (e.g., titanium alloys) using machine learning frameworks. More particularly, the present disclosure provides for the generation of microstructural images of components (e.g., titanium alloys) as a function of heat treatment conditions using conditional generative adversarial networks. The present disclosure advantageously provides ways to accelerate component designs (e.g., titanium alloy designs) by developing generative models which can produce synthetic yet realistic microstructures conditioned on heat treatment conditions.

Abstract: Machine learning (ML) pipeline selection includes performing cross-validation runs for dataset-pipeline combinations and building a matrix of first accuracy scores, factoring the matrix of accuracy scores into pipeline latent factors and dataset latent factors, augmenting the matrix of accuracy scores by selecting a subset of ML pipelines of a plurality of ML pipelines, then, for a new dataset, running the subset of ML pipelines with the new dataset to build and test respective ML models, obtain second accuracy scores, and augment the matrix of accuracy scores with the second accuracy scores to produce an augmented matrix of accuracy scores, factoring the augmented matrix of accuracy scores into refined pipeline latent factors and refined dataset latent factors, and identifying, based on the refined pipeline latent factors and the refined dataset latent factors, ML pipeline(s), of the plurality of ML pipelines, as most optimal for model building based on the new dataset.

Abstract: A new pepper hybrid designated as ‘VP18090009’ is disclosed. ‘VP18090009’ is a hot pepper variety of the jalapeno type exhibiting stability and uniformity. Variety ‘VP18090009’ produces extra-large fruits that are green prior to maturity and red at maturity. Additionally, variety ‘VP18090009’ has a desirable growth habit and plant height that result in high numbers of flowers and fruit.

Abstract: A neuromorphic foreign object debris (FOD) detection system includes a FOD processing system and a neuromorphic sensor. The FOD processing system includes a FOD controller including a trained artificial intelligence machine learning (AIML) model representing an area of interest. The neuromorphic sensor has a field of view (FOV) containing the area of interest and is configured to output pixel data in response to FOD appearing in the FOV. The FOD controller detects the FOD is present in the area of interest in response to receiving the pixel data, and generates an alert signal indicating the presence of the FOD.

Abstract: Disclosed examples include microelectronic devices, e.g. Integrated circuits. One example includes a microelectronic device including a nanosheet lateral drain extended metal oxide semiconductor (LDMOS) transistor with source and drain regions having a first conductivity type extending into a semiconductor substrate having an opposite second conductivity type. A superlattice of alternating layers of nanosheets of a channel region and layers of gate conductor are separated by a gate dielectric, the superlattice extending between the source region and the drain region. A drain drift region of the first conductivity type extends under the drain region and a body region of the second type extends around the source region.

Abstract: An adaptive modeling method for generating misregistration data for a semiconductor device wafer (SDW) including calculating a fitting function for a group of SDWs (GSDW) having units, including measuring an SDW in said GSDW, thereby generating test data sets corresponding to the units, removing non-unit-specific values (NUSVs) from the test data sets, thereby generating cleaned test data sets, and analyzing the cleaned test data sets, thereby generating the fitting function, and generating misregistration data for at least one additional SDW (ASDW) in the GSDW, including measuring the ASDW, thereby generating run data sets, removing NUSVs from the run data sets, thereby generating cleaned run data sets, fitting each of the cleaned run data sets to the fitting function, thereby generating coefficient sets, and calculating misregistration data for the ASDW, at least partially based on the fitting function and the coefficient sets.

Abstract: Example implementations relate to predicting the health of an aircraft component based on a hybrid digital twin. A computing system receives nominal operational data and operational data from aircraft sensors based on flights by an aircraft to evaluate an aircraft component on the aircraft. The computing system can estimate first parameters corresponding to the aircraft component based on a nominal digital twin using the nominal operational data outside respective alerts corresponding to the aircraft component and second parameters corresponding to the aircraft component based on an operational digital twin using the operational data. The computing system then estimates a first health parameter and a second health parameter for the aircraft component based on the first parameters and the second parameters, respectively.