Abstract: The invention provides treatments of organic waste. The invention provides a method for treating organic waste (and in particular, animal waste such as waste from a cow) and uses of a composition that is capable of generating a reactive species in methods of reducing biological degradation of organic waste, in the treatment of organic waste. The invention also provides organic waste treated by the methods of the invention and uses of this treated organic waste. The invention also provides a method for improving the production of volatile fatty acids (VFA) and medium-chain carboxylic acids (MCCAs) during anaerobic digestion (AD) of organic waste.

Abstract: Organic photovoltaic materials (OPV) and devices using the same are provided, as well as methods of fabricating and using the same. An OPV material can be used as a photo-absorbing layer for mechanoluminescent (ML) light (e.g., in a flexible organic ML photodiode). The OPV material can include, for example, a blend of a donor polymer (e.g., P3HT) and a non-halogenated, non-fullerene acceptor (e.g., Y6).

Abstract: The invention provides treatments of organic waste. The invention provides a method for treating organic waste (and in particular, animal waste such as waste from a cow) and uses of a composition that is capable of generating a reactive species in methods of reducing biological degradation of organic waste, in the treatment of organic waste. The invention also provides organic waste treated by the methods of the invention and uses of this treated organic waste. The invention also provides a method for improving the production of volatile fatty acids (VFA) and medium-chain carboxylic acids (MCCAs) during anaerobic digestion (AD) of organic waste.

Abstract: A non-fogging eyewear assembly, comprising an outer lens assembly including an optionally heated outer transparent lens having inner and outer faces, an eyewear chassis configured to be worn by a user, and an inner lens assembly integrated within the eyewear chassis, with said inner lens assembly including an optionally heated inner transparent lens having inner and outer faces. A seal is affixed along a periphery of the outer face of the inner transparent lens assembly, and so that means for releasably coupling the outer lens assembly to the inner lens assembly causes the outer lens to compress against and be spaced apart from the inner lens by the seal to form a gap therebetween and prevent moisture from entering the airspace that exists between the inner and outer lenses. The outer lens assembly is thus releasably decouplable from the inner lens assembly so that it can be easily replaced if damaged.

Abstract: The invention generally relates to compositions and methods for reducing methane production in animals, in particular by controlling oxidation-reduction potential in the digestive tract.

Abstract: A neural network system that includes: multiple subnetworks that includes: a first subnetwork including multiple first modules, each first module including: a pass-through convolutional layer configured to process the subnetwork input for the first subnetwork to generate a pass-through output; an average pooling stack of neural network layers that collectively processes the subnetwork input for the first subnetwork to generate an average pooling output; a first stack of convolutional neural network layers configured to collectively process the subnetwork input for the first subnetwork to generate a first stack output; a second stack of convolutional neural network layers that are configured to collectively process the subnetwork input for the first subnetwork to generate a second stack output; and a concatenation layer configured to concatenate the pass-through output, the average pooling output, the first stack output, and the second stack output to generate a first module output for the first module.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, by a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, by the first sequence-training speech model, one or more first neural network parameters; determining, by the first sequence-training speech model, one or more optimized first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; obtaining, by a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances; obtaining one or more second neural network parameters; and determining, by the second sequence-training speech model, one or more optimized second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters.

Abstract: The invention relates to the use of an antibiotic-free antimicrobial feed additive in a method of improving the health of animals and/or reducing methane production of animals. The invention also provides an antimicrobial composition which is used at a low concentration, an antimicrobial composition which has a low ratio of iodide ions to hydrogen peroxide, and uses of these compositions as antimicrobial agents. The invention also provides the use of an antimicrobial composition in combination with an antibiotic as an antimicrobial agent.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, by a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, by the first sequence-training speech model, one or more first neural network parameters; determining, by the first sequence-training speech model, one or more optimized first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; obtaining, by a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances; obtaining one or more second neural network parameters; and determining, by the second sequence-training speech model, one or more optimized second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters.

Abstract: Organic photovoltaic materials (OPV) and devices using the same are provided, as well as methods of fabricating and using the same. An OPV material can be used as a photo-absorbing layer for mechanoluminescent (ML) light (e.g., in a flexible organic ML photodiode). The OPV material can include, for example, a blend of a donor polymer (e.g., P3HT) and a non-halogenated, non-fullerene acceptor (e.g., Y6).

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, by a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, by the first sequence-training speech model, one or more first neural network parameters; determining, by the first sequence-training speech model, one or more optimized first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; obtaining, by a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances; obtaining one or more second neural network parameters; and determining, by the second sequence-training speech model, one or more optimized second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image processing using deep neural networks. One of the methods includes receiving data characterizing an input image; processing the data characterizing the input image using a deep neural network to generate an alternative representation of the input image, wherein the deep neural network comprises a plurality of subnetworks, wherein the subnetworks are arranged in a sequence from lowest to highest, and wherein processing the data characterizing the input image using the deep neural network comprises processing the data through each of the subnetworks in the sequence; and processing the alternative representation of the input image through an output layer to generate an output from the input image.

Abstract: A device consisting of a digital camera with a microscope objective lens, a disc where plant material can be mounted and automatically rotated, and two other cameras for determining the plant material's shape and size, that allows images of intact cannabis trichomes to be taken, without destruction or damage to the plant material, and automatically counts and calculates the density of the trichomes on the inflorescence surface. This does not require taking any plant cuttings, does not require the use of a microscope or microscope slides, and allows multiple measurements to be taken of a single inflorescence sample in quick succession, without the need for manual image analysis.

Abstract: The present invention relates to cure accelerators useful for anaerobic curable compositions, such as adhesives and sealants. The cure accelerators may be embraced generally within the structure below where X is CH2, O, S, NR?, CR?R?? or C?O; R is hydrogen or (meth)acryl; R6 is hydrogen, halogen, amino, carboxyl, nitro, alkyl, alkenyl, alkynyl, hydroxyalkyl, hydroxyalkenyl, hydroxyalkynyl, or alkaryl; and A and A1 are each individually selected from hydrogen or taken together create a ring structure of 5 to 12 total ring atoms, wherein the ring structure may be cycloaliphatic, cycloheteroaliphatic or aromatic or combinations thereof with or without substitution by one or more hydroxyl or (meth)acryl groups; and n is 0 or 1, provided that when R is hydrogen, A and A? cannot both be hydrogen or taken together cannot be naphthyl.

Abstract: A system and method for securing a pump are disclosed. The system includes a pump that contains a medicament delivery system, a processor operably coupled to the pump, a user interface in operable communication with the processor, a plurality of sensors in operable communication with the processor, and a housing. The housing includes a frame, a door, and a locking mechanism that can be selectively unlocked to allow the door to partially detach from the frame. The security system includes a swivel door assembly, which includes physical redundancies to selectively prevent access to the internal space of the swivel door assembly and a plurality of alarms. For example, in response to receiving an input from the plurality of sensors, the processor initiates at least one of the plurality of alarms to provide an indication to a user that an event has occurred.

Abstract: A system, method, and computer-readable medium are disclosed automatic validation of light emitting diodes (LEDs) of disk drives in disk processor enclosures (DPEs) or disk array enclosures (DAEs) during the manufacturing and integration of computer systems. An automated test script is performed in support of the integration of the computer system that includes the LEDs and includes a validation and checking step for the LEDs. A determination is made if a camera is properly calibrated to identify the LEDs as part of the validating and checking step for the LEDs. A DPE or DAE that contains disk drive units that include the LEDs are identified, and an indication is performed as to which LEDs pass or fail.

Abstract: A method is provided that non-coding RNA profiles can be exploited as a means of monitoring, assessing, comparing, establishing and/or determining certain cell characteristics and/or profiles. Accordingly, the use of non-coding RNA molecules for characterising and/or profiling cells is provided.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image processing using deep neural networks. One of the methods includes receiving data characterizing an input image; processing the data characterizing the input image using a deep neural network to generate an alternative representation of the input image, wherein the deep neural network comprises a plurality of subnetworks, wherein the subnetworks are arranged in a sequence from lowest to highest, and wherein processing the data characterizing the input image using the deep neural network comprises processing the data through each of the subnetworks in the sequence; and processing the alternative representation of the input image through an output layer to generate an output from the input image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, by a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, by the first sequence-training speech model, one or more first neural network parameters; determining, by the first sequence-training speech model, one or more optimized first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; obtaining, by a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances; obtaining one or more second neural network parameters; and determining, by the second sequence-training speech model, one or more optimized second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters.

Abstract: Structured documents are processed using convolutional neural networks. For example, the processing can include receiving a rendered form of a structured document; mapping a grid of cells to the rendered form; assigning a respective numeric embedding to each cell in the grid, comprising, for each cell: identifying content in the structured document that corresponds to a portion of the rendered form that is mapped to the cell, mapping the identified content to a numeric embedding for the identified content, and assigning the numeric embedding for the identified content to the cell; generating a matrix representation of the structured document from the numeric embeddings assigned to the cells of the grids; and generating neural network features of the structured document by processing the matrix representation of the structured document through a subnetwork comprising one or more convolutional neural network layers.