Abstract: A model generation apparatus according to one aspect of the present invention acquires a plurality of learning datasets each constituted by a first sample of a first time of predetermined data obtained in time series and feature information included in a second sample of the predetermined data of a future second time relative to the first time, and trains a prediction model, by machine learning, to predict feature information of the second time from the first sample of the first time, for each learning dataset. In the model generation apparatus, a rarity degree for is set each learning dataset, and, in the machine learning, the model generation apparatus trains more preponderantly on learning datasets having a higher rarity degree.

Abstract: A zinc anode material for secondary cells includes zinc-containing particles that are coated with a coating composition containing at least one oxide of a metal selected from titanium, zirconium, magnesium, tin and yttrium. The surface localization ratio of the coating composition of Equation (1) ranges from 1.6 to 16. In Equation (1), the surface metal atomic ratio of the coating composition is represented by Equation (2), and the bulk metal atomic ratio of the coating composition is represented by Equation (3).

Abstract: A zinc anode material for secondary cells includes zinc-containing particles that are coated with a coating composition containing at least one oxide of a metal selected from titanium, zirconium, magnesium, tin and yttrium. The surface localization ratio of the coating composition of Equation (1) ranges from 1.6 to 16. In Equation (1), the surface metal atomic ratio of the coating composition is represented by Equation (2), and the bulk metal atomic ratio of the coating composition is represented by Equation (3).

Abstract: An x-ray CT image processing method which carries out a statistical estimate in prior knowledge relating to the movement and the x-ray absorption coefficient of a measurement subject comprises: a step of hypothesizing that the measurement subject changes smoothly over time, and defining a first probability model (prior knowledge of the measurement subject over all times) relating to movement and a second probability model (projected image observation model over all times) relating to observation; and a step of carrying out a statistical estimate dependent on both the first probability model and the second probability model. The first probability model relating to the movement of the measurement subject and the second model relating to observation are defined as probability models with which statistical estimates are carried out at the outset, and motion and CT images are simultaneously estimated by carrying out induction based on the probability models.

Abstract: In a metamaterial, a dielectric layer includes a host medium and dielectric bodies disposed in rows with predetermined intervals therebetween is sandwiched between a pair of conductive mesh plates each having holes, thereby forming a functional layer including dielectric resonators corresponding to the dielectric bodies. The metamaterial is configured by laminating the functional layers. The holes and the dielectric resonators are positioned coaxially and an electromagnetic wave is propagated in each of the functional layers in a propagation direction perpendicular to a multi-layered laminate surface such that the metamaterial function as a left-handed metamaterial in relation to the propagation direction perpendicular to the multi-layered surface.