Abstract: A multi-tube burner system for efficient mixing of fuel and air for combustion is disclosed. The multi-tube burner system includes an air supply plenum, a multi-tube burner, and a combustor. Further, the multi-tube burner includes a set of tubes including the air supply section to receive combustion air and supply the received combustion air to a mixing section. Furthermore, the multi-tube burner includes a set of fuel pipes to receive fuel from a set of fuel inlets and supply the received fuel to a set of fuel plenums. Furthermore, a pair of fuel receiving channels receive the fuel from the set of fuel plenums and a fuel injector pin injects the received fuel from the pair of fuel receiving channels to the mixing section. Further, a set of mixing holes allow egression of the combustion air and the fuel mixture from the mixing section to the combustor.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Described herein are the preparation and use of novel bromo-phosphonomethylphenylalanine amino acid derivatives (BrPmp) and BrPmp-containing peptides as specific, irreversible protein tyrosine phosphatase inhibitors, which are suitable for application in peptide synthesis. These derivatives are particularly advantageous since their synthesis is both easy and scalable, and they are suitable for peptide synthesis. The BrPmp derivatives described herein can be appropriately protected to allow for solid phase peptide synthesis (SPPS) and incorporation into peptides for preparation of protein tyrosine phosphatase inhibitors and inhibitor libraries. The peptides and peptide libraries can be used to identify new protein tyrosine phosphatase specific sequences and profile protein tyrosine phosphatase activity in cell lysates, diagnostic samples and biopsy samples.

Abstract: Described herein are the preparation and use of novel bromo-phosphonomethylphenylalanine amino acid derivatives (BrPmp) and BrPmp-containing peptides as specific, irreversible protein tyrosine phosphatase inhibitors, which are suitable for application in peptide synthesis. These derivatives are particularly advantageous since their synthesis is both easy and scalable, and they are suitable for peptide synthesis. The BrPmp derivatives described herein can be appropriately protected to allow for solid phase peptide synthesis (SPPS) and incorporation into peptides for preparation of protein tyrosine phosphatase inhibitors and inhibitor libraries. The peptides and peptide libraries can be used to identify new protein tyrosine phosphatase specific sequences and profile protein tyrosine phosphatase activity in cell lysates, diagnostic samples and biopsy samples.

Abstract: A front end client-server application configured to synchronize requirements between a requirements repository and a testing repository. The front end client-server application validates a requirement, processes at least one filter associated with the requirement, determines a requirement type of the requirement, and processes the requirement. In addition, the method comprises updating a testing application in accordance with the processed requirement. In addition, it can be determined whether a plurality of requirements received by the front end client-server application that need to be synchronized contain traceability relationships. If so, the front end client-server application replicates the traceability relationship between the requirements to be synchronized and any relevant, existing requirements at the testing repository. Furthermore, the front end client-server application allows a user to customize the requirements synchronization process.

Abstract: The present invention provides a system and method for transmitting data securely over a wireless network between two different computing devices. The deficiencies of limited wireless bandwidth and frequent connection “breaks” in the wireless network are overcome through intelligent packetization schemes.