Abstract: A method of forming a reinforced panel may include engaging a reinforcement component having a faying surface with a first portion of a heated press, engaging an uncured panel component with an opposing second portion of the press, the panel component having a faying surface complementarily-configured with respect to the faying surface of the reinforcement component, treating the faying surface of the reinforcement component such that the faying surface is active for co-bonding with respect to the panel component, actuating the press to direct the first and second portions of the press toward each other, such that the faying surfaces are complementarily engaged under pressure; and heating the first and second portions of the press to a curing temperature associated with the panel component to substantially simultaneously co-bond the faying surfaces of the reinforcement component and the panel component together, cure the panel component, and form the reinforced panel.

Abstract: An aircraft includes external structures, and one or more thermal emitters integrated with one or more of the external structures. The one or more thermal emitters are configured to generate heat to deice the one or more external structures. The one or more thermal emitters are configured to receive electrical power from one or more of an auxiliary power unit of the aircraft, a power distribution system of the aircraft, one or more engines of the aircraft, or an external power cart that is separate and distinct from the aircraft.

Abstract: The present application discloses a method, system, and computer system for managing data using keys. The method includes receiving a request to access data stored within a tenant database associated with a tenant, wherein the data is encrypted based at least in part on a tenant service encryption key (TSEK) corresponding to the tenant database, determining a wrapper key used in connection with encrypting the TSEK based at least in part on a TSEK metadata stored in association with the TSEK, determining a top-level key used in connection with encrypting the wrapper key based at least in part on wrapper key metadata stored in association with the encrypted version of the wrapper key, obtaining the data stored within the tenant database, comprising decrypting at least part of the data based at least in part on (i) the TSEK, (ii) the wrapper key, and (iii) the top-level key, and providing the data in response to the request. The TSEK metadata is stored in the tenant database.

Abstract: Compositions including a polyamide, and compaction rollers for an automated fiber placement machine incorporating the composition are provided. The polyamide may be a reaction product of at least one diamine and an aromatic dicarboxylic acid, a hydroxy benzoic acid, or their respective ester or acyl halide derivatives. The at least one diamine may include an amino terminated perfluorinated alkyl ether polymer or oligomer. The composition may have a thermal conductivity of from about 0.2 to about 50 Watts per meter Kelvin (Wm?1K?1).

Abstract: The present application discloses a method, system, and computer system for managing data using keys. The method includes receiving a request to access data stored within a tenant database associated with a tenant, wherein the data is encrypted based at least in part on a tenant service encryption key (TSEK) corresponding to the tenant database, determining a wrapper key used in connection with encrypting the TSEK based at least in part on a TSEK metadata stored in association with the TSEK, determining a top-level key used in connection with encrypting the wrapper key based at least in part on wrapper key metadata stored in association with the encrypted version of the wrapper key, obtaining the data stored within the tenant database, comprising decrypting at least part of the data based at least in part on (i) the TSEK, (ii) the wrapper key, and (iii) the top-level key, and providing the data in response to the request. The TSEK metadata is stored in the tenant database.

Abstract: A method facilitating business continuity of an enterprise computer network includes receiving an initiate network recovery message at a disaster recovery orchestration platform identifying an enterprise computer network to be recovered. Predetermined network configuration information associated with the enterprise computer network is retrieved from a storage device accessible to the disaster recovery orchestration platform. A virtual recovered enterprise network is built in a virtual computing environment based at least in part on the predetermined network configuration information. A system to facilitate business continuity of an enterprise computer network is also provided. The system includes a disaster recovery orchestration platform, a storage device, and at least one communication interface. The disaster recovery orchestration platform including at least one platform computing device. Each platform computing device including at least one processor and associated memory.

Abstract: Described herein are apparatus and methods for performing inference into the identity of an object. For an object of a plurality of objects, the apparatus receives feature-location information identifying a feature at first location on a first object of the plurality and a feature at a second location on a second object of the plurality. The apparatus activates a first set of location cells that collectively represent the first location on the first object corresponding to a feature on an object of the plurality of objects and a second set of location cells that collectively represent the second location on the second object corresponding to a feature on an object of the plurality of objects. The apparatus activates a set of displacement cells representing displacement of the first set of location cells and the second set of location cells and identifies one or more objects by processing the displacement cells.

Abstract: Compositions including a polyimide and one or more thermally conductive fillers, and compaction rollers for an automated fiber placement machine incorporating the compositions are provided. The polyimide may be a polymeric reaction product of a dianhydride and one or more diamines. The one or more diamines may include a fluorine-containing alkyl ether diamine. The one or more thermally conductive fillers may include one or more of a carbon-based filler, boron nitride, a metal, or combinations thereof. The compositions may have a thermal conductivity of from about 0.2 to about 50 Watts per meter Kelvin (Wm?1 K?1).

Abstract: An inference system performs inference, such as object recognition, based on sensory inputs generated by sensors and control information associated with the sensory inputs. The sensory inputs describe one or more features of the objects. The control information describes movement of the sensors or known locations of the sensors relative to a reference point. For a particular object, an inference system learns a set of object-location representations of the object. An object-location representation is a unique characterization of an object-centric location relative to the particular object. The inference system also learns a set of feature-location representations associated with the object-location representation that indicate presence of features at the corresponding object-location pair.

Abstract: Compositions including a poly(arylene ether), and compaction rollers for an automated fiber placement machine incorporating the composition are provided. The poly(arylene ether) may be a reaction product of at least one disubstituted benzophenone and at least one polyol. The at least one polyol may include at least one fluorinated diol. The composition may have a thermal conductivity of from about 0.2 to about 50 Watts per meter Kelvin (Wm?1K?1).

Abstract: An inference system performs inference, such as object recognition, based on sensory inputs generated by sensors and control information associated with the sensory inputs. The sensory inputs describe one or more features of the objects. The control information describes movement of the sensors or known locations of the sensors relative to a reference point. For a particular object, an inference system learns a set of object-location representations of the object. An object-location representation is a unique characterization of an object-centric location relative to the particular object. The inference system also learns a set of feature-location representations associated with the object-location representation that indicate presence of features at the corresponding object-location pair.

Abstract: A noise model is iteratively trained to simulate introduction of noise by a capture device, by use of a denoiser and a training data set of pairs of noisy signals. First and second noisy signals of each pair are independently sampled by the capture device from source information corresponding to the pair. Each iteration of training obtains first and second denoised signals from respective noisy signals, then optimizes at least one loss function which sums first and second terms to train both the noise model and the denoiser, where the first term is based on the first denoised signal and the second noisy signal, and the second term is based on the second denoised signal and the first noisy signal. By using noisy samples, the complexities of obtaining “clean” signals are avoided. By using “cross-sample” loss functions, convergence on undesired training results is avoided without complex regularization.

Abstract: A computer-implemented system and method for estimating a Cumulative Distribution Function (CDF) are provided. The method includes: receive input data representing a volume V of a target space indicating a future target event; compute, using the trained neural network, an estimation of a first flux through a boundary of the volume V; compute, using the trained neural network, an estimation of a second flux through a boundary of a volume W of a base space based on the estimation of the first flux through the boundary of the volume V; generate, using the trained neural network, an estimation of a CDF for the volume V based on the second flux through the boundary of the volume W; compute a probability for the future target event based on the estimated CDF for the volume V; and generate a control command based on the probability for the future target event.

Abstract: A system for machine learning architecture for time series data prediction. The system may be configured to: maintain a data set representing a neural network having a plurality of weights; obtain time series data associated with a data query; generate, using the neural network and based on the time series data, a predicted value based on a sampled realization of the time series data and a normalizing flow model, the normalizing flow model based on a latent continuous-time stochastic process having a stationary marginal distribution and bounded variance; and generate a signal providing an indication of the predicted value associated with the data query.

Abstract: The methods and systems are directed to computational approaches for training and using machine learning algorithms to predict the conditional marginal distributions of the position of agents at flexible evaluation horizons and can enables more efficient path planning. These methods model agent movement by training a deep neural network to predict the position of an agent through time. A neural ordinary differential equation (neural ODE) that represents this neural network can be used to determine the log-likelihood of the agent's position as it moves in time.

Abstract: Disclosed herein are systems and methods for efficient 3D structure estimation from images of a transmissive object, including cryo-EM images. The method generally comprises, receiving a set of 2D images of a target specimen from an electron microscope, carrying out a reconstruction technique to determine a likely molecular structure, and outputting the estimated 3D structure of the specimen. The described reconstruction technique comprises: establishing a probabilistic model of the target structure; optimizing using stochastic optimization to determine which structure is most likely; and, optionally utilizing importance sampling to minimize computational burden.

Abstract: A sparse neural network is trained such that weights or layer outputs of the neural network satisfy sparsity constraints. The sparsity is controlled by pruning one or more subsets of weights based on their signal-to-noise ratio (SNR). During the training process, an inference system generates outputs for a current layer by applying a set of weights for the current layer to a layer output of a previous layer. The set of weights for the current layer may be modeled as random variables sampled from probability distributions. The inference system determines a loss function and updates the set of weights by backpropagating error terms obtained from the loss function. This process is repeated until a convergence criterion is reached. One or more subsets of weights are then pruned based on their SNR depending on sparsity constraints for the weights of the neural network.

Abstract: A method for laying up a composite material includes steps of (1) depositing the composite material onto a substrate; (2) compacting the composite material with a compaction roller, the compaction roller and the substrate defining a nip; and (3) projecting a plasma flume proximate the nip to heat at least one of the composite material and the substrate.

Abstract: Compositions including a poly(arylene ether), and compaction rollers for an automated fiber placement machine incorporating the composition are provided. The poly(arylene ether) may be a reaction product of at least one disubstituted benzophenone and at least one polyol. The at least one polyol may include at least one fluorinated diol. The composition may have a thermal conductivity of from about 0.2 to about 50 Watts per meter Kelvin (Wm?1K?1).

Abstract: Compositions including a polyamide, and compaction rollers for an automated fiber placement machine incorporating the composition are provided. The polyamide may be a reaction product of at least one diamine and an aromatic dicarboxylic acid, a hydroxy benzoic acid, or their respective ester or acyl halide derivatives. The at least one diamine may include an amino terminated perfluorinated alkyl ether polymer or oligomer. The composition may have a thermal conductivity of from about 0.2 to about 50 Watts per meter Kelvin (Wm?1K?1).