Abstract: A holder for storing a collectible, such as a stack of banknotes, having a first housing assembled with a second housing and defining an enclosed space therein. A collectible receiving structure is disposed within the enclosed space and spaced from an outer perimeter wall. A locking structure disposed within the enclosed space, the locking structure having a first locking member formed with the first housing and a second locking member formed with the second housing and configured so that before the first housing is assembled with the second housing the first locking member is movable relative to the second locking member.

Abstract: A holder for storing a collectible, such as a stack of banknotes, having a first housing assembled with a second housing and defining an enclosed space therein. A collectible receiving structure is disposed within the enclosed space and spaced from an outer perimeter wall. A locking structure disposed within the enclosed space, the locking structure having a first locking member formed with the first housing and a second locking member formed with the second housing and configured so that before the first housing is assembled with the second housing the first locking member is movable relative to the second locking member.

Abstract: A system and method for generating non-fungible tokens for collectibles. The system authenticates physical ownership of a collectible before allowing a requesting entity to generate a non-fungible token for the collectible. The system generates a fiat currency value for the non-fungible token based on the total number of non-fungible tokens already generated for the collectible and the current value of the collectible. The system tracks non-fungible tokens generated for the collectible to ensure that the proportional cost of generating a non-fungible token strictly increases as the total number of non-fungible tokens generated for the collectible increases.

Abstract: In some embodiments, a method can include augmenting a set of images of collectables to generate a set of synthetic images of collectables. The method can further include combining the set of images of collectables and the set of synthetic images of collectables to produce a training set. The method can further include training a set of machine learning models based on the training set. Each machine learning model from the set of machine learning models can generate a grade for an image attribute from a set of image attributes. The set of image attributes can include an edge, a corner, a center, or a surface. The method can further include executing, after training, the set of machine learning models to generate a set of grades for an image of collectable not included in the training set.

Abstract: A system for analyzing the chemical composition of a sample, comprising exciting a portion of the sample to generate atomic spectral emissions; a spectrometer for determining atomic emission characteristics; processor for receiving an output from the spectrometer, analyzing said output to determine atomic composition, said processor predicting at least one of (i) an origin of the sample, (ii) a treatment applied to said sample, (iii) a composition of the sample, and (iv) a feedback signal for controlling a process. Calibration samples are also provided for standardizing readings from the spectrometer.