Abstract: There is a need for more effective and efficient constrained-optimization-based operational load balancing. In one example, a method comprises determining constraint-satisfying operator-unit mapping arrangements that satisfy an operator unity constraint and an operator capacity constraint; for each constraint-satisfying operator-unit mapping arrangement, determining an arrangement utility measure; processing each arrangement utility measure using an optimization-based ensemble machine learning model that is configured to determine an optimal operator-unit mapping arrangement of the plurality of constraint-satisfying operator-unit mapping arrangements; and initiating the performance of one or more operational load balancing operations based on the optimal operator-unit mapping arrangement.

Abstract: Various embodiments of the present invention utilize systems, methods, and computer program products that perform measurement device calibration management by utilizing calibration offset generation machine learning models that are generated using a model training routine that comprises, for each measurement environment feature value: (i) determining a plurality of inferred measurements by a measurement device in relation to a ground-truth measurement operation via performing the ground-truth measurement operation under simulated measurement conditions characterized at least in part by varying a measurement environment feature that is associated with the measurement environment feature value across a per-feature spectrum for the measurement environment feature; and (ii) generating the calibration offset generation machine learning model based at least in part on comparing the plurality of inferred measurements and a ground-truth measurement output for the ground-truth measurement operation.

Abstract: There is a need for more effective and efficient constrained-optimization-based operational load balancing. In one example, a method comprises determining constraint-satisfying operator-unit mapping arrangements that satisfy an operator unity constraint and an operator capacity constraint; for each constraint-satisfying operator-unit mapping arrangement, determining an arrangement utility measure; processing each arrangement utility measure using an optimization-based ensemble machine learning model that is configured to determine an optimal operator-unit mapping arrangement of the plurality of constraint-satisfying operator-unit mapping arrangements; and performing one or more operational load balancing operations based on the optimal operator-unit mapping arrangement.

Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The text includes errors associated with noise in the image. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the errors from the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.

Abstract: An apparatus includes a memory and processor. The memory stores OCR and NLP algorithms. The processor receives an image of a physical document page and executes the OCR algorithm to convert the image into text. The processor identifies errors in the text, which are associated with noise in the image. The processor generates a feature vector that includes features obtained by executing the NLP algorithm on the text, and features associated with the identified errors in the text. The processor uses the feature vector to assign the image to a document category. Documents assigned to the document category share one or more characteristics, and the feature vector is associated with a probability greater than a threshold that the physical document associated with the image includes those characteristics. The processor then stores the image in a database as a page of an electronic document belonging to the assigned document category.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing risk score generation predictive data analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform risk conformance mining predictive data analysis by utilizing machine learning frameworks that include state processing machine learning models and attribute processing machine learning models, where the machine learning frameworks may be trained as part of generative adversarial machine learning frameworks.

Abstract: Aspects of the invention relate to methods for treating cancer by administering to a subject in need thereof a therapeutically effective amount of a nucleic acid molecule that is directed against a gene encoding mouse double minute 1 homolog (MDM1), mouse double minute 2 homolog (MDM2), mouse double minute 3 homolog (MDM3), mouse double minute 4 homolog (MDM4) or V-myc myelocytomatosis viral related oncogene (MYCN) for treating cancer. Further aspects of the invention relate to nucleic acid molecules and compositions comprising nucleic acid molecules.

Abstract: Various examples are directed to methods and system of managing a sensor. A measurement system may receive from the host device, a first register map describing a first configuration of the measurement system for the first sensor. The first configuration may indicate a first measurement frequency for the first sensor. The measurement system may configure a switch matrix to provide a first excitation signal to the first sensor. The measurement system may configure the switch matrix to connect an analog-to-digital converter (ADC) of the measurement system to the first sensor. The measurement system may sample a first raw sensor signal from the first sensor with the ADC at a first measurement frequency described by the first configuration. The measurement system may generate first digital measurement data based at least in part on the first raw sensor signal and send the first digital measurement data to the host device.

Abstract: There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing cross-temporal predictive data analysis. In one example, a method includes determining a time-adjusted encoding for each temporal unit of a group of temporal units, processing each time-adjusted encoding using a cross-temporal encoding machine learning model to generate a cross-temporal encoding of the group of temporal units, and performing one or more prediction-based actions based at least in part on the cross-temporal encoding.

Abstract: Various examples are directed to systems and methods for managing a sensor. A measurement system may receive, from a host device, a first register map describing a first configuration of a measurement system. The first configuration may be associated with a first sensor. The measurement system may compare the first register map to an error rule set indicating inconsistent register map arrangements. After comparing the first register map to the error rule set, the measurement system may configure a switch matrix of the measurement system to sample the first sensor according to the first configuration of the measurement system. The measurement system may receive a plurality of samples from a first sensor and generate first digital measurement data based at least in part on the plurality of samples.

Abstract: There is a need for more effective and efficient constrained-optimization-based operational load balancing. In one example, a method comprises determining constraint-satisfying operator-unit mapping arrangements that satisfy an operator unity constraint and an operator capacity constraint; for each constraint-satisfying operator-unit mapping arrangement, determining an arrangement utility measure; processing each arrangement utility measure using an optimization-based ensemble machine learning model that is configured to determine an optimal operator-unit mapping arrangement of the plurality of constraint-satisfying operator-unit mapping arrangements; and performing one or more operational load balancing operations based on the optimal operator-unit mapping arrangement.

Abstract: A coating composition including at least one water-based anionic polyurethane dispersion and 0.1 to 4 weight-% of nanoparticulate TiO2 having an average particle size of not more than 100 nm, based on the solids content of the coating composition. The cured coating composition is suitable as a top coat in a decorative multilayer coating system including at least one polyurethane base coat. The multilayer coating system exhibits improved non-yellowing property and cleanability. The liquid multilayer coating system is particularly suitable for balcony applications.

Abstract: There is a need for solutions for more efficient predictive data analysis systems. This need can be addressed, for example, by a system configured to receive temporal inferences for a predictive task, where each temporal inference is associated with a temporal benchmark and the temporal benchmarks include a base temporal benchmark and supplemental temporal benchmarks; generate a cross-temporal prediction for the predictive task by applying one or more cross-temporal probabilistic updates to the base temporal inference, where each cross-temporal probabilistic update is associated with a supplemental temporal benchmark; and display the cross-temporal prediction using a cross-temporal prediction interface.

Abstract: Aspects of the invention relate to methods for treating ALS comprising administering to a subject in need thereof a therapeutically effective amount of a nucleic acid molecule that is directed against a gene encoding superoxide dismutase 1 (SOD1).

Abstract: There is a need for solutions for more efficient predictive data analysis systems. This need can be addressed, for example, by a system configured to obtain, for each predictive task of a plurality of predictive tasks, a plurality of per-model inferences; generate, for each predictive task, a cross-model prediction based on the plurality of per-model inferences for the predictive task; and generate, based on each cross-model prediction associated with a predictive task, a cross-prediction for the particular predictive task, wherein determining the cross-prediction comprises applying one or more probabilistic updates to the cross-model prediction for the particular predictive task and each probabilistic update is determined based on the cross-model prediction for a related predictive task of the one or more related predictive tasks.

Abstract: In one aspect, the disclosure provides methods for treating a neurodegenerative disorder, comprising administering to a subject in need thereof a therapeutically effective amount of a nucleic acid molecule and a therapeutically effective amount of a small molecule that activates NF-?B p65 and increases expression of manganese superoxide dismutase (MnSOD/SOD2) and/or expression of a related protein or enzyme.

Abstract: The present invention provides methods, processes, and systems for the manufacture of three-dimensional articles of polymer materials using 3D printing. A syringe or an inkjet print head prints a solution of prepolymer onto a build plate. The printed prepolymer is exposed to a stimulus whereby the prepolymer is converted to the polymer. After a predetermined time, sequential layers are printed to provide the three-dimensional article. The three-dimensional article can be cured to produce the 3D article made from the final polymer.

Abstract: The present invention provides methods, processes, and systems for the manufacture of three-dimensional articles of polymer materials using 3D printing. A syringe or an inkjet print head prints a solution of prepolymer onto a build plate. The printed prepolymer is exposed to a stimulus whereby the prepolymer is converted to the polymer. After a predetermined time, sequential layers are printed to provide the three-dimensional article. The three-dimensional article can be cured to produce the 3D article made from the final polymer.

Abstract: The present invention provides methods, processes, and systems for the manufacture of three-dimensional articles made of polymers using 3D printing. A layer of prepolymer is deposited on a build plate to form a powder bed. The deposited powder bed is heated to about 50° C. to about 170° C. Then, a solution of activating agent is printed on the powder bed in a predetermined pattern, and a stimulus is applied converting the prepolymer to the final polymer. After a predetermined period of time, sequential layers are printed to provide the three-dimensional article. The three-dimensional object can be cured to produce the three-dimensional article composed of the final polymers.

Abstract: A coating composition including at least one water-based anionic polyurethane dispersion and 0.1 to 4 weight-% of nanoparticulate TiO2 having an average particle size of not more than 100 nm, based on the solids content of the coating composition. The cured coating composition is suitable as a top coat in a decorative multilayer coating system including at least one polyurethane base coat. The multilayer coating system exhibits improved non-yellowing property and cleanability. The liquid multilayer coating system is particularly suitable for balcony applications.