Abstract: Aspects of the disclosure relate to determining a next vehicle task for a vehicle of a fleet. Vehicle data from the vehicle, charger data about at least one charger, and demand data may be received and used to determine the next vehicle task. The vehicle may be directed to the next vehicle task. Determining a next vehicle task may further be based on predictions made using the vehicle data, the charger data, and the demand data. Heuristics may also be used in determining a next vehicle task.

Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.

Abstract: Described herein are methods for generating and using a constrained ensemble of GANs. The constrained ensemble of GANs can be used to generate synthetic data that is (1) representative of the original data, and (2) not closely resembling the original data. An example method includes generating a constrained ensemble of GANs, where the constrained ensemble of GANs includes a plurality of ensemble members. The method also includes analyzing performance of the constrained ensemble of GANs by comparing a temporary performance metric to a baseline performance metric, and halting generation of the constrained ensemble of GANs in response to the analysis. The method also includes generating a synthetic dataset using the constrained ensemble of GANs. The synthetic dataset is sufficiently similar to the original dataset to permit data sharing for research purposes but alleviates privacy concerns due to differences in mutual information between synthetic and real data.

Abstract: Example systems and methods for lesion detection are described herein. An example system includes at least one processor and a memory operably coupled to the at least one processor. The system also includes a candidate selection module configured to receive an image, determine a plurality of candidate points in the image, and select a respective volumetric region centered by each of the candidate points. A portion of a lesion has a high probability of being determined as a candidate point. The system further includes a deep learning network configured to receive the respective volumetric regions selected by the candidate selection module, and determine a respective probability of each respective volumetric region to contain the lesion. Additionally, example methods for training a deep learning network to detect lesions are described herein.

Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.

Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.

Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.