A computer-implemented method for estimating a state-action value function for a Fitted Q-iteration is provided including obtaining a set of tuples D and a discount factor γ, each of the set of tuples including a state s, an action a, a reward r, and a resulting state s′, constructing a zero-suppressed decision diagram (ZDD) of feature vectors {ϕ(s′, a′)|a′∈(s′)} for each of the resulting states s′ of the set of tuples, where the feature vector ϕ(s, a) is a sparse bit vector {0,1}.sup.D and (s′) is the set of actions applicable at state s′, updating parameters w∈.sup.D, θ of a state-action value function Q (s, a; w, θ); and repeating the updating step a predetermined times by incrementing t.

A method of improving agricultural treatment includes identifying a mineralogical feature based on a collected soil sample, generating a soil clay characterization based on the mineralogical feature, and generating an agricultural prescription. A system includes a processor and a memory storing instructions that, when executed by the processor, cause the system to identify a mineralogical feature based on a collected soil sample, generate a soil clay characterization based on the mineralogical feature, and generate an agricultural prescription. A non-transitory computer readable medium containing program instructions that, when executed, cause a computer to identify a mineralogical feature based on a soil sample, generate a soil clay characterization based on the mineralogical feature, and generate an agricultural prescription.

A method of improving agricultural treatment includes identifying a mineralogical feature based on a collected soil sample, generating a soil clay characterization based on the mineralogical feature, and generating an agricultural prescription. A system includes a processor and a memory storing instructions that, when executed by the processor, cause the system to identify a mineralogical feature based on a collected soil sample, generate a soil clay characterization based on the mineralogical feature, and generate an agricultural prescription. A non-transitory computer readable medium containing program instructions that, when executed, cause a computer to identify a mineralogical feature based on a soil sample, generate a soil clay characterization based on the mineralogical feature, and generate an agricultural prescription.

A computer implemented method for determining performance properties of an oil-containing product for cosmetics, the oil-containing product for cosmetics comprising different oils forming a mixture, the method comprising the steps of: providing to a processing device via an input channel o performance properties for each of the different oils o a measure for the ratio of the different oils in the mixture, o a data driven model and/or a rigorous model determining with a processing device determined performance properties of the oil-containing product for cosmetics comprising the mixture, based on o the data driven model o the performance properties for each of the different oils o the measure for the ratio of the different oils in the mixture, providing via an output channel o the determined performance properties of the oil-containing product for personal care and/or o the measure for the ratio of the different oils in the mixture and/or o a formulation of the mixture, and or o a formulation of the oil-containing product for personal care.

A computer implemented method for determining performance properties of an oil-containing product for cosmetics, the oil-containing product for cosmetics comprising different oils forming a mixture, the method comprising the steps of: providing to a processing device via an input channel o performance properties for each of the different oils o a measure for the ratio of the different oils in the mixture, o a data driven model and/or a rigorous model determining with a processing device determined performance properties of the oil-containing product for cosmetics comprising the mixture, based on o the data driven model o the performance properties for each of the different oils o the measure for the ratio of the different oils in the mixture, providing via an output channel o the determined performance properties of the oil-containing product for personal care and/or o the measure for the ratio of the different oils in the mixture and/or o a formulation of the mixture, and or o a formulation of the oil-containing product for personal care.

The present invention relates to the perfumery industry. More particularly, the present invention relates to assays and methods for screening and identifying compositions and/or ingredients that intensify a subjects perception of target odorant compounds based on the use of particular olfactory receptors activated by the target odorant compound.

The present invention relates to the perfumery industry. More particularly, the present invention relates to assays and methods for screening and identifying compositions and/or ingredients that intensify a subjects perception of target odorant compounds based on the use of particular olfactory receptors activated by the target odorant compound.

A variation in the performance value of a polymer being manufactured can be reduced. A prediction device (10A) that, in manufacturing of a polymer, predicts a performance value indicating performance of the polymer in a polymerization tank after a raw material is fed, and may include: an acquisition unit (111) that acquires, as a prediction observation value, an observation value observed, in current manufacturing of the polymer, as a value related to the manufacturing of the polymer; and a prediction unit (112) that predicts the performance value of the polymer being currently manufactured at a predetermined timing, from the prediction observation value acquired by the acquisition unit, by using a relation between an observation value acquired in past manufacturing of the same type of polymer as the polymer, and a performance value of the polymer at the predetermined timing in the past manufacturing.

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.

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.