Abstract: Techniques are described herein for producing machine-generated findings given a set of user experience test results. In some embodiments, the system generates the findings using an artificial intelligence and machine learning engine. The findings may highlight areas that are predicted to provide the most insight into optimizing a product's design. A finding may be generated based on all or a subset of the test result elements, including qualitative and/or quantitative data contained therein. A finding may summarize a subset of the UX test results that are interrelated. A finding may link a summary to one or more references extracted from the set of test results to show support for the machine-generated insights in the underlying raw test data. Machine-generated findings reports may provide near instantaneous guidance for optimizing product designs while removing extraneous information from a vast quantity of raw test result data.

Abstract: Methods are provided for targeting cells for depletion, including, without limitation, cancer cells, in a regimen comprising contacting the targeted cells with a combination of agents, including (i) an agent that blockades CD47 activity; and (ii) an antibody that specifically binds to EGFR. In some embodiments the cancer cells have a mutated form of one or more of KRAS, NRAS and BRAF. The level of depletion of the targeted cell is enhanced relative to a regimen in which a single agent is used; and the effect may be synergistic relative to a regimen in which a single agent is used.

Abstract: A method for pricing data recovery for a sequence of time periods based on an estimate of the amount of data that will be recovered. For the first period, the price is the backup capacity times a price rate times an assumed recovery rate, which is a pre-determined number. For subsequent periods, the price is the backup capacity times the price rate times the actual amount of data recovered in the prior time period. The method also includes a data backup and recovery method using the data recovery pricing method, which provides tracker software to measure the amount of data recovered.

Abstract: A method for pricing data recovery for a sequence of time periods based on an estimate of the amount of data that will be recovered. For the first period, the price is the backup capacity times a price rate times an assumed recovery rate, which is a pre-determined number. For subsequent periods, the price is the backup capacity times the price rate times the actual amount of data recovered in the prior time period. The method also includes a data backup and recovery method using the data recovery pricing method, which provides tracker software to measure the amount of data recovered.

Abstract: A harness manufactured from transverse and longitudinal fabric belts with adjustable buckles attached to the ends of the belts and shoulder straps attached to the longitudinal belts that while fastened around the suitcase converts a carry-on suitcase into a backpack. At least one transverse fabric belt is intended to be strapped around the suitcase and two longitudinal belts strapped around the suitcase in longitudinal direction. The adjustable buckles provide tightening of the belts strapped around the suitcase. The shoulder straps attached to the longitudinal belts allows carrying the suitcase on ones back in easy and convenient manner.