Abstract: A method for forecasting wind power output of a target wind farm. The method includes normalizing, wind power output data for each wind farm of a group of wind farms, based, at least in part, on a respective installed capacity; transforming, the normalized power output data to yield transformed normalized wind power output data. Fitting, by the temporal module, each temporal model of at least one temporal model to model input data for each wind farm. The model input data corresponds to normalized wind power output data or transformed normalized wind power output data. The method further includes fitting, by a spatial module, a DVINE copula model for the group of wind farms, based, at least in part, on at least one residual value. Each residual value is determined based, at least in part on a selected fitted temporal model for each wind farm in the group.

Abstract: A method of generating a synthetic network includes receiving, by a group structure identification module, anonymized input data related to an original network. The anonymized input data includes an anonymized list of nodes, a list of edges and a list of groups. The method further includes determining, by the group structure identification module, for each pair of nodes, a probability of an edge between the pair of nodes. A resulting list of probabilities corresponds to a summary group structure. The method further includes generating, by a synthetic random network generation module, at least one synthetic random network based, at least in part, on the determined probabilities.

Abstract: Systems and methods for reconstructing images for computed tomography are provided. Image reconstruction can be based on a realistic polychromatic physical model, and can include use of both an analytical algorithm and a single-variable optimization method. The optimization method can be used to solve the non-linear polychromatic X-ray integral model in the projection domain, resulting in an accurate decomposition for sinograms of two physical basis components.

Abstract: Ammonia is made in a system that includes a conversion reactor for performing a Haber-Bosch process. Effluent streams from the conversion reactor, which include an ammonia component and excess hydrogen and nitrogen reactants, are fed to a membrane separator that includes NaA zeolite membranes disposed on one or more hollow porous supports. The NaA zeolite membranes are highly selective for the ammonia component, allowing the ammonia to be collected from a lumen of the membranes as a product and enriching the excess hydrogen and nitrogen reactants for reuse in the conversion reactor. These systems and the methods of their use are effective to replace and/or modify the energy-intensive condensation/recycling steps in the traditional Haber-Bosch process used to condense NH3 from the exiting stream of the reactor. The selective removal of ammonia by high quality NaA membranes helps to shift the ammonia evolution reaction.

Abstract: A high-voltage power supply system including a high-voltage regulator, a function generator, and a triggering circuit. The high-voltage regulator includes a microcontroller, a digital-to-analog convertor in communication with the microcontroller, and a high-voltage DC-DC converter in communication with the digital-to-analog converter. The function generator includes a high-voltage inverter including one or more MOSFET switches. The high-voltage inverter is in communication with the microcontroller of the high-voltage regulator. The triggering circuit includes one or more high-voltage electromechanical switches.

Abstract: A system for few-view computed tomography (CT) image reconstruction is described. The system includes a preprocessing module, a first generator network, and a discriminator network. The preprocessing module is configured to apply a ramp filter to an input sinogram to yield a filtered sinogram. The first generator network is configured to receive the filtered sinogram, to learn a filtered back-projection operation and to provide a first reconstructed image as output. The first reconstructed image corresponds to the input sinogram. The discriminator network is configured to determine whether a received image corresponds to the first reconstructed image or a corresponding ground truth image. The generator network and the discriminator network correspond to a Wasserstein generative adversarial network (WGAN). The WGAN is optimized using an objective function based, at least in part, on a Wasserstein distance and based, at least in part, on a gradient penalty.

Abstract: A system for imaging, including a source of coherent light; a polarization state generator for generating polarized optical photons from the light originating in the source of coherent light; a sample environment; a polarization state analyzer for permitting photons having a desired polarization to interact with a detector; and an imaging unit for generating an image based on the interactions of the photons with the detector. The sample environment includes a plurality of electromagnets, each connected to one or more power supply components; and a controller, connected to the electromagnets and including software for generating and controlling a desired magnetic field created by each of the electromagnets in concert with each other.

Abstract: A magnetically coupled piston pump includes a piston, a pump body, and a set of drive magnets. The piston includes a set of piston magnets. Each piston magnet has poles arranged along a longitudinal axis of the piston, and each piston magnet is arranged in the piston so that the orientation of the poles of each piston magnet is the opposite of the orientation of each adjacent piston magnet. The piston is disposed in and permitted to move within the pump body. The set of drive magnets is arranged outside the pump body. Each drive magnet corresponds to a piston magnet, has poles arranged along the longitudinal axis, and is arranged so that the orientation of the poles is opposite the orientation of the poles of the corresponding piston magnet. A drive unit is coupled to the drive magnets for moving the drive magnets along the longitudinal axis.

Abstract: In an embodiment, there is provided an apparatus. The apparatus includes an analog front end for biosignal acquisition. The analog front end includes an instrumentation amplifier and a reconfigurable filter. The instrumentation amplifier is configured to receive a biosignal and includes a super class-AB output stage. The reconfigurable filter is coupled to an output of the instrumentation amplifier. The reconfigurable filter has a selectable gain and an adjustable bandwidth. The bandwidth is adjusted based, at least in part, on a duty cycle of a clock signal.

Abstract: Resolution of a pathological condition is promoted via the application, e.g., via injection, of a potassium osmolyte such as hyperosmolar potassium gluconate, potassium aspartate, another potassium-based salt, or combinations thereof to the condition site. The application of the potassium osmolyte increases the extracellular concentration of potassium ions, reducing the membrane potential of the cells at the condition site and including immune cell quiescence. As a result, the inflammatory response in the patient to the pathological condition is reduced or eliminated. Reducing the inflammatory response is useful in treatment of myriad conditions including arthritis, auto-immune conditions, inflammatory disorders, neurodegenerative disorders, neurodevelopmental disorders, tissue breakdown, etc.

Abstract: For a passage text and a corresponding answer text, perform a word-level soft alignment to obtain contextualized passage embeddings and contextualized answer embeddings, and a hidden level soft alignment on the contextualized passage embeddings and the contextualized answer embeddings to obtain a passage embedding matrix. Construct a passage graph of the passage text based on the passage embedding matrix, and apply a bidirectional gated graph neural network to the passage graph until a final state embedding is determined, during which intermediate node embeddings are fused from both incoming and outgoing edges. Obtain a graph-level embedding from the final state embedding, and decode the final state embedding to generate an output sequence word-by-word. Train a machine learning model to generate at least one question corresponding to the passage text and the answer text, by evaluating the output sequence with a hybrid evaluator combining cross-entropy evaluation and reinforcement learning evaluation.

Abstract: In order to produce chondroitin sulfate in an animal-free manner, engineered E. coli host cells were modified so as to reduce expression of an endogenous gene for fructosyltransferase (kfoE); reduce expression of an endogenous gene for 3?-phosphoadenosine-5?-phosphosulfate reductase (cysH); and express one or more exogenous sulfotransferases. Expression of proteins forming ATP-binding cassette transporters were also reduced to limit export of glycosaminoglycans from the cells. The recombinant microorganisms are able produce all three components identified for chondroitin sulfate production—chondroitin, sulfate donor, and sulfotransferase. These modified E. coli are capable of complete, essentially one-step biosynthesis of chondroitin sulfate at a variety of sulfation levels from simple microbial media components and glucose. This is a major advantage over current production methods that depend on the natural distribution of chondroitin sulfate types in the animal tissue.

Abstract: Coatings are disclosed that include a solvent and a silk fibroin and/or a silk fibroin-like macromolecule. These coatings are provided via self-assembly on a target surface, or co-assembly with one or more functionally active additive compounds such as organic or inorganic therapeutics. Coating growth is facilitated by the addition of effective concentrations of kosmotropic agents, such as potassium phosphate, and provide coatings that are smooth on the nanometer length scale and free of inhomogeneities. Because the method grows the coating from the surface in a non-covalent bottom-up approach, it is suitable for coating surfaces that have high curvature or complex geometry, such as porous materials or those with nano or micron-scale diameter features. These coatings can be grown on both organic and inorganic surfaces without the need for specific covalent chemistry of the surface or activation of the surface by irradiation or chemical treatment.

Abstract: An anion exchange membrane is composed of a copolymer of 1,1-diphenylethylene and one or more styrene monomers, such as 4-tert-butylstyrene. The copolymer includes a backbone substituted with a plurality of ionic groups coupled to phenyl groups on the backbone via hydrocarbyl tethers between about 1 and about 7 carbons in length. High-temperature conditions enabled by these copolymers enhance conductivity performance, making them particularly suitable for use in anion exchange membranes in fuel cells, electrolyzers employing hydrogen, ion separations, etc. The properties of the membranes can be tuned via the degree of functionalization of the phenyl groups and selection of the functional groups, such as quaternary ammonium groups. Several processes can be used to incorporate the desired ionic functional groups into the polymers, such as chloromethylation, radical bromination, Friedel-Crafts acylation and alkylation, sulfonation followed by amination, or combinations thereof.

Abstract: A method for x-ray photon-counting data correction. The method includes generating, by a training data generation module, training input spectral projection data based, at least in part, on a reference spectral projection data. The training input spectral projection data includes at least one of a pulse pileup distortion, a charge splitting distortion, and/or noise. The method further includes training, by a training module, a data correction artificial neural network (ANN) based, at least in part, on training data. The data correction ANN includes a pulse pileup correction ANN, and a charge splitting correction ANN. The training data includes the training input spectral projection data and the reference spectral projection data.

Abstract: A synergized pulsing-imaging network is described. A method of optimizing a magnetic resonance imaging (MRI) system includes optimizing, by a synergized pulsing-imaging network (SPIN) circuitry a pulse sequence based, at least in part, on a loss function associated with a reconstruction network. The method further includes optimizing, by the SPIN circuitry, the reconstruction network based, at least in part, on intermediate raw MRI data and based, at least in part, on a ground truth MRI image data. The intermediate raw MRI data is determined based, at least in part on the pulse sequence.

Abstract: A system for providing a solar harvesting building envelope is disclosed. The system includes a plurality of solar harvesting apparatus configured to be installed as or on a building envelope in a manner like that of traditional shingles or siding. The apparatus includes a frame having a photovoltaic end wall, and reflective base and side walls. A translucent, wedge-shaped body layer is positioned on the frame. A luminescent species film is positioned at and substantially parallel to a base of the wedge-shaped body layer, such that the luminescent species film is positioned at an angle relative to the photovoltaic end wall. Light incident on the wedge-shaped body layer is concentrated towards the photovoltaic end wall, such as through absorption and re-emission along with scattering by the luminescent species film and internal reflection by the wedge-shaped body layer and the reflective base and side walls of the frame.

Abstract: A machine learning apparatus for correcting nonphotochemical quenching (NPQ) in fluorometer data includes a trained NPQ correction circuitry. The trained NPQ correction circuitry is configured to receive actual input NPQ data. The actual input NPQ data includes daytime chlorophyll a fluorescence (Fchl) data and selected environmental data. The trained NPQ correction circuitry is further configured to generate an estimated NPQ correction factor based, at least in part, on the actual input NPQ data. The NPQ correction factor is configured to at least reduce an effect of NPQ on the daytime Fchl data.

Abstract: A neural network based corrector for photon counting detectors is described. A method for photon count correction includes receiving, by a trained artificial neural network (ANN), a detected photon count from a photon counting detector. The detected photon count corresponds to an attenuated energy spectrum. The attenuated energy spectrum is related to characteristics of an imaging object and is based, at least in part, on an incident energy spectrum. The method further includes correcting, by the trained ANN, the detected photon count to produce a corrected photon count. The method may include reconstructing, by image reconstruction circuitry, an image based, at least in part, on the corrected photon count.

Abstract: A deep neural network for motion artifact reduction includes a transformer neural network, and a synthesis neural network. The transformer neural network is configured to receive input image data comprising a target image, a prior image, and a subsequent image. The transformer neural network is configured to mitigate a temporal aspect of the motion artifact, and to provide a transformer output related to the input data. The synthesis neural network is configured to receive the transformer output, and to provide at least one output image having a reduced motion artifact relative to the input image data.