Abstract: Rather than randomly selecting neural networks to classify a media file, the conductor can determine which neural network engines (from the conductor ecosystem of neural networks) are the best candidates to classify a particular portion/segment of the media file (e.g., audio file, image file, video files). The best candidate neural network engine(s) can depend on the nature of the input media and the characteristics of the neural network engines. In object recognition and identification, certain neural networks can classify vehicles better than others, while another group of neural networks can classify structures better. The conductor can take out the guess work and construct in real-time an inter-classifier neural network using one or more layers selected from one or more pre-trained neural network, based on attribute(s) of the media file, to classify the media file.

Abstract: Integrated circuit structures having metal-containing fin isolation regions are described. In an example, an integrated circuit structure includes a vertical stack of horizontal nanowires over a first sub-fin. A gate structure is over the vertical stack of horizontal nanowires and on the first sub-fin. A dielectric structure is laterally spaced apart from the gate structure. The dielectric structure is not over a channel structure but is on a second sub-fin. A gate cut is between the gate structure and the dielectric structure. A dielectric gate cut plug is in the gate cut. The dielectric gate plug includes a metal-containing dielectric material.

Abstract: A molecular manufacturing process includes contacting a platform molecule with (i) a biocatalyst and (ii) a chemical catalyst under conditions suitable to produce a value-added chemical.

Abstract: In summary, the present disclosure is directed to a soft gel food supplement; formulated in eleven natural antiviral ingredients; to boost the immune system. The present disclosure contains natural antiviral antibacterial ingredients that makes the human immune system a more complex network of cells and proteins that defends the body against infection. The immune system keeps a record of every germ (microbe) it has ever defeated so it can recognize and destroy the microbe quickly if it enters the body again. Covid will attack everybody in its path. However, when a variant attempts to infect those who use the present disclosure dietary supplement formula and method, the immune system is nourished and ready to boost its normal function to the utmost in recognizing and destroying the virus and its variants efficiently.

Abstract: Methods and systems for training one or more neural networks for transcription and for transcribing a media file using the trained one or more neural networks are provided. One of the methods includes: segmenting the media file into a plurality of segments; inputting each segment, one segment at a time, of the plurality of segments into a first neural network trained to perform speech recognition; extracting outputs, one segment at a time, from one or more layers of the first neural network; and training a second neural network to generate a predicted-WER (word error rate) of a plurality of transcription engines for each segment based at least on outputs from the one or more layers of the first neural network.

Abstract: One or more embodiments of the present disclosure relate generally to an interchangeable grip for a hand tool that facilitates a robust, serviceable connection between the interchangeable grip and a tool handle.

Abstract: One or more embodiments of the present disclosure relate generally to a ratchet tool including a ratchet head having a drive gear, a pawl, and a spring plunger system that applies an even and consistent distribution of loading to the pawl at a contact interface between the pawl and the drive gear during a ratcheting operation.

Abstract: A method of preparing succinic acid; the method comprising contacting glucose with an oxidizing catalyst under conditions to produce a first oxidized product; converting the first oxidized product to an aldehyde; and contacting the aldehyde with an acid catalyst under conditions suitable for the formation of succinic acid.

Abstract: In summary, the present disclosure is directed to a soft gel food supplement; formulated in eleven natural antiviral ingredients; to boost the immune system. The present disclosure contains natural antiviral antibacterial ingredients that makes the human immune system a more complex network of cells and proteins that defends the body against infection. The immune system keeps a record of every germ (microbe) it has ever defeated so it can recognize and destroy the microbe quickly if it enters the body again. Covid will attack everybody in its path. However, when a variant attempts to infect those who use the present disclosure dietary supplement formula and method, the immune system is nourished and ready to boost its normal function to the utmost in recognizing and destroying the virus and its variants efficiently.

Abstract: A system for glucaric acid production includes (a) a first input selected from the group consisting of glucuronolactone, a disaccharide feedstock, a cleaved starch, a disaccharide, glucuronic acid, or a combination thereof. In addition, the system includes (b) a first catalyst system comprising a metal oxidation catalyst; (c) a first product; (d) a second input. Further, the system includes (e) a second catalyst system comprising an enzyme. Still further, the system includes (f) a second product comprising from about 50% to about 99% glucaric acid on a dry basis.

Abstract: Methods and systems for training one or more neural networks for transcription and for transcribing a media file using the trained one or more neural networks are provided. One of the methods includes: segmenting the media file into a plurality of segments; inputting each segment, one segment at a time, of the plurality of segments into a first neural network trained to perform speech recognition; extracting outputs, one segment at a time, from one or more layers of the first neural network; and training a second neural network to generate a predicted-WER (word error rate) of a plurality of transcription engines for each segment based at least on outputs from the one or more layers of the first neural network.

Abstract: There is provided a cartridge for storing and dispensing liquid for use with an inkjet printer, the cartridge comprising: a collapsible reservoir enclosing an internal space for storage of the liquid, wherein: the reservoir comprises a first wall portion and a second wall portion, the first wall portion defining a first region of the internal space, the second wall portion defining a second region of the internal space, the first region and the second region being in fluid communication with each another; and the first wall portion and the second wall portion are configured such that at least a part of the second wall portion collapses more easily than the first wall portion when the liquid is withdrawn from the reservoir; an outlet configured to dispense the liquid; and a holder configured to receive an electronic data storage device, wherein the holder is provided on the first wall portion.

Abstract: A trickle bed reactor, comprising a plurality of catalyst beds connected in series and progressively increasing in catalyst mass in a direction from upstream to downstream; and a plurality of heat exchangers, wherein each of the heat exchangers is located between two of the plurality of catalyst beds, and wherein each of the heat exchangers does not exchange heat with an outer surface of a vessel that contains any of the catalyst beds.

Abstract: Methods and systems for training one or more neural networks for transcription and for transcribing a media file using the trained one or more neural networks are provided. One of the methods includes: segmenting the media file into a plurality of segments; inputting each segment, one segment at a time, of the plurality of segments into a first neural network trained to perform speech recognition; extracting outputs, one segment at a time, from one or more layers of the first neural network; and training a second neural network to generate a predicted-WER (word error rate) of a plurality of transcription engines for each segment based at least on outputs from the one or more layers of the first neural network.

Abstract: Provided herein are devices, systems, and methods for biological sample collection. In particular, provided herein are devices, systems, and methods that employ small, hand-held devices that collect small volumes of biological samples, such as vitreous from the eye, for diagnostic and other purposes.

Abstract: Provided is a semisolid softgel fill material that includes water and/or other polar solvents, along with a high amount of a nonpolar component, such as an oil. Also provided are methods and systems for producing softgels including the fill material. The softgels produced by the methods and systems provided herein have a normal appearance and retain their structural integrity, even when dried according to conventional methods. Further, when the fill material is added to water or other liquid, as it would be following ingestion, the fill material forms small droplets, thereby enhancing digestion and absorption of the fill material.

Abstract: Methods and systems for classifying a multimedia file using interclass data is disclosed. One of the methods includes receiving, from a first transcription engine, one or more transcription results of one or more audio segments of the multimedia file; identifying a first transcription result for a first audio segment having a low confidence of accuracy; identifying a first image data of the multimedia file corresponding to the first segment; receiving, from an image classification engine trained to classify image data, an image classification result of one or more portions of the first image data in response to requesting the image classification engine to classify the first image data; and selecting, based at least on the image classification result of the one or more portions of the first image data, a second transcription engine to re-classify the first audio segment.

Abstract: Provided herein are embodiments of systems and methods for classifying one or more objects in an image. One of the methods includes: receiving object classification results of the image from one or more classification engines, the object classification results comprise classification of one or more objects and confidence scores associated with the one or more objects; aggregating the object classification results from the one or more classification engines to generate a list of confidence scores associated with each of the one or more objects, the list of confidence scores comprises one or more confidence scores from one or more classification engines; calculating an overall certainty score for each of the one or more objects based at least on the list of confidence scores; and generating a first orchestrated classification result based the overall certainty score for each of the one or more object.

Abstract: Methods and systems for training one or more neural networks for transcription and for transcribing a media file using the trained one or more neural networks are provided. One of the methods includes: segmenting the media file into a plurality of segments; extracting, using a first neural network, audio features of a first and second segment of the plurality of segments; and identifying, using a second neural network, a best-candidate engine for each of the first and second segments based at least on audio features of the first and second segments. A best-candidate engine is a neural network having a highest predicted transcription accuracy among a collection of neural networks.