Abstract: A unitized storage assembly for automated loading and unloading of an associated cargo space, including individual storage units that are positioned in rows, such that each row comprises an opposing pair of individual storage units and wherein each row is movably coupled to an adjacent row. The assembly further includes an elevating mechanism coupled to one of the individual units and operative to move the row vertically or horizontally relative to the adjacent row. The assembly includes a motor operatively coupled to a wheel rotatably mounted on a bottom surface of a base of one of the individual storage units. The assembly also includes a controller that activates the elevating mechanism to raise the pair of individual storage units a predetermined height, and the motor to rotate the wheel to move the unitized storage assembly in at least one direction.

Abstract: A storage system is described which includes a base compartment with a hollow interior space defined by a back wall, a top wall, a bottom wall, a first sidewall, a second sidewall, and an opening formed opposite to the back wall, the first sidewall and the second sidewall being connected to opposing sides of the back wall by a hinge structure, each hinge structure including: a first hinge column mounted on each side of the back wall; and a second hinge column mounted on a side of each of the first sidewall and the second sidewall and connected to the first hinge column, and wherein each of the first hinge column and the second hinge column include a ridged arm and a grooved arm disposed at a right angle with respect to the ridged arm.

Abstract: Certain aspects of the present disclosure provide techniques for generating certification of greenhouse gas reduction. An example method comprising collecting first sensor data regarding a greenhouse gas (GHG) emission level of a process at a first time and establishing a baseline GHG emission metric based on the first sensor data. The method also includes implementing a change to at least one step of the process. Further, the method includes collecting second sensor data regarding the GHG emission level of the process at a second time after the first time, and calculating an updated GHG emission metric based on the second sensor data. The method includes, in response to the updated GHG emission metric being less than the baseline GHG emission metric, minting an exhaustible non-fungible token with a value representing a difference between the updated GHG emission metric and the baseline GHG emission metric.

Abstract: Method, apparatus, and article of manufacture for modeling the biological effects of a molecule are disclosed. A machine learning application may be configured to process a set of training examples regarding a biological property of interest. Once trained, the machine learning application may be configured to generate a prediction regarding a property of interest for a test molecule. Embodiments of the invention provide a meta-model configured to generate a biological effect prediction for a molecule based on the predictions generated for the test molecule by a plurality of molecular property models.

Abstract: Transglutaminase inhibitors and methods of use thereof are provided.

Abstract: Method, apparatus, and article of manufacture for modeling the biological effects of a molecule are disclosed. A machine learning application may be configured to process a set of training examples regarding a biological property of interest. Once trained, the machine learning application may be configured to generate a prediction regarding a property of interest for a test molecule. Embodiments of the invention provide a meta-model configured to generate a biological effect prediction for a molecule based on the predictions generated for the test molecule by a plurality of molecular property models.