Abstract: A computer based system for remapping prime class seat bookings is disclosed. The system remaps prime class bookings a floor class, or if the floor class is closed, into a higher, displacement class. Via remapping, airline systems, such as inventory management systems, revenue management systems, and the like, may better account for the true value of prime class bookings.

Abstract: A method includes converting, by a generative network, an input into a latent vector representation of a sample chemical compound, wherein the input is one of an order-dependent representation of the sample chemical compound and a molecular graph representation of the sample chemical compound; determining, by an output neural network, one or more properties of the sample chemical compound based on the latent vector representation of the sample chemical compound; performing, by the output neural network, an optimization routine to select a candidate latent vector representation from among a plurality of latent vector representations based on the latent vector representation of the sample chemical compound, wherein the plurality of latent vector representations includes the latent vector representation of the sample chemical compound; and identifying, by the output neural network, a candidate chemical compound based on the candidate latent vector representation.

Abstract: A method includes generating a graph of a chemical compound based on at least one of an order-dependent representation of the chemical compound and a molecular graph representation of the chemical compound, encoding the graph based on an adjacency matrix of a graph convolutional neural network (GCN), an activation function of the GCN, and one or more weights of the GCN to generate a latent vector representation of the chemical compound, and decoding the latent vector representation based on a plurality of hidden states of a neural network (NN) to generate a reproduced order-dependent representation of the chemical compound.

Abstract: The invention disclosed herewith is a computer-implemented method for evaluating the toxicity of chemical compounds. In particular, some embodiments of the invention comprise importing microarray data representing measurements of the RNA transcription from hepatocytes, and running at least one algorithm (such as a coefficient penalized linear regression algorithm) on the imported data to assess potential adverse drug effects. After the evaluation has been carried out, the results are exported to reports or databases. In some embodiments of the invention, the algorithm has been trained on reference data using machine learning techniques. In some embodiments of the invention, the evaluation of toxicity is carried out concurrently with the evaluation of efficacy, where it can be used to assess the clinical value of the compounds evaluated. In some embodiments of the invention, the evaluation of toxicity is inserted into a pharmaceutical evaluation process prior to expensive testing of toxicity in animals.

Abstract: An attitude sensing system which incorporates the precision in attitude sensing of a satellite navigation system with the dynamic tracking capabilities of an inertial measurement unit. Optimally estimated attitude and system error signals are combined with the outputs of an inertial measurement unit to control the phase differences of signals received on an interferometer array from a navigation satellite. The outputs from the inertial measurement unit and the phase differences are processed in an optimal estimator filter to produce periodically updated attitude and system error signals. This permits inertial attitude sensing to benefit from the long term accuracy of attitude estimation based upon signals from the satellite navigation system.