Abstract: Caprolactam-derived solvents for use as processing solvents and/or coalescing agents for polyurethane dispersions (PUDs). The caprolactam-derived solvents are suitable for processing solvents and coalescing agents in PUDs created through traditional PUD manufacturing processes or as coalescing agents in PUDs created through solvent-free PUD manufacturing processes. Blends of more than one caprolactam-derived solvent may be used as the processing solvent and/or coalescing agent.

Abstract: Caprolactam-derived solvents for use as processing solvents and/or coalescing agents for polyurethane dispersions (PUDs). The caprolactam-derived solvents are suitable for processing solvents and coalescing agents in PUDs created through traditional PUD manufacturing processes or as coalescing agents in PUDs created through solvent-free PUD manufacturing processes. Blends of more than one caprolactam-derived solvent may be used as the processing solvent and/or coalescing agent.

Abstract: Solvents that are suitable for use with polyurethane-polyurea based rheology modifying agents of the type which, in the past, have generally been formulated as solids or viscous liquids. The present solvents enable the rheology modifying agents to be prepared and formulated in a liquid or solution form more suited to prepare coating formulations that include polyurethane-polyurea based rheology modifying agents. The present solvents are N-alkyl substituted caprolactams, including N-methyl caprolactam, N-ethyl caprolactam, N-butyl caprolactam, and mixtures thereof, which are aprotic, non-toxic, have good solvency for polar groups such as those found in polyurethanes and polyureas, are thermally stable, and have high boiling points and low vapor pressure.

Abstract: Bioreactors and methods of stimulating continuous growth of hairy root biomass in such bioreactors are provided.

Abstract: The present disclosure provides a PVC or CPVC solvent cement and a composition for forming a PVC or CPVC coating on an object. The solvent cement and the coating composition each include one or more caprolactam-derived solvents and a polymer selected from the group of polyvinyl chloride and chlorinated polyvinyl chloride. The one or more caprolactam-derived solvents include a linear alkyl group of 1, 2 or 4 unsubstituted carbons or an alkoxymethyl group of 2 or 3 unsubstituted carbons bonded to a nitrogen heteroatom.

Abstract: Solvents that are suitable for use with polyurethane-polyurea based rheology modifying agents of the type which, in the past, have generally been formulated as solids or viscous liquids. The present solvents enable the rheology modifying agents to be prepared and formulated in a liquid or solution form more suited to prepare coating formulations that include polyurethane-polyurea based rheology modifying agents. The present solvents are N-alkyl substituted caprolactams, including N-methyl caprolactam, N-ethyl caprolactam, N-butyl caprolactam, and mixtures thereof, which are aprotic, non-toxic, have good solvency for polar groups such as those found in polyurethanes and polyureas, are thermally stable, and have high boiling points and low vapor pressure.

Abstract: Caprolactam-derived solvents for use as processing solvents and/or coalescing agents for polyurethane dispersions (PUDs). The caprolactam-derived solvents are suitable for processing solvents and coalescing agents in PUDs created through traditional PUD manufacturing processes or as coalescing agents in PUDs created through solvent-free PUD manufacturing processes. Blends of more than one caprolactam-derived solvent may be used as the processing solvent and/or coalescing agent.

Abstract: There is provided a computer implemented data driven classification and troubleshooting system and method. The system has an interface application enabled to receive data. The system has an associative memory software in communication with the interface application via an API. The associative memory software has an associative memory and a machine learning algorithm. The system has one or more individual areas, within the associative memory, requiring one or more troubleshooting actions to improve accuracy of the individual areas. The system has at least one troubleshooting tool enabled by the interface application. The at least one troubleshooting tool enables or performs the troubleshooting actions. The system has a quality rating metric (QRM) that measures a strength and an assurance that one or more predictions of the associative memory are correct. The one or more troubleshooting actions results in improving the accuracy and the performance of the associative memory.

Abstract: A composition including a caprolactam-derived solvent and a crop protective active ingredient. An emulsifiable concentrate including a caprolactam-derived solvent, an organic co-solvent, an emulsifier, and a crop protective active ingredient is also provided.

Abstract: A composition including a crop nutrition active ingredient and a first solvent that mitigates or eliminates disadvantages associated with traditional solvents. A composition including the crop nutrition active ingredient, the first solvent, a second solvent, and a surfactant is also provided. The first solvent includes at least one caprolactam-derived solvent.

Abstract: A computer implemented data driven classification and data quality checking system is provided. The system has an interface application enabled to receive data and has an associative memory software. The system has a data driven associative memory model configured to categorize one or more fields of received data and to analyze the received data. The system has a data quality rating metric associated with the received data. The system has a machine learning data quality checker for the received data, and is configured to add the received data to a pool of neighboring data, if the data quality rating metric is greater than or equal to a data quality rating metric threshold. The machine learning data quality checker is configured to generate and communicate an alert of a potential error in the received data, if the data quality rating metric is less than the data quality rating metric threshold.

Abstract: A method for improving accuracy and quality of received data is provided. The method provides a computer implemented data driven classification and data quality checking system. The method uses the associative memory software to build a data driven associative memory model that enables a machine learning data quality checker for receiving data. The method categorizes one or more fields of received data, analyzes the received data, and calculates a data quality rating metric, by comparing the received data with a pool of neighboring data in the category of field of the received data. The method accepts and adds the received data, if the data quality rating metric is greater than or equal to a data quality rating metric threshold, and generates and communicates an alert of a potential error in the received data, if the data quality rating metric is less than the data quality rating metric threshold.

Abstract: There is provided a computer implemented data driven classification and troubleshooting system and method. The system has an interface application enabled to receive data. The system has an associative memory software in communication with the interface application via an API. The associative memory software has an associative memory and a machine learning algorithm. The system has one or more individual areas, within the associative memory, requiring one or more troubleshooting actions to improve accuracy of the individual areas. The system has at least one troubleshooting tool enabled by the interface application. The at least one troubleshooting tool enables or performs the troubleshooting actions. The system has a quality rating metric (QRM) that measures a strength and an assurance that one or more predictions of the associative memory are correct. The one or more troubleshooting actions results in improving the accuracy and the performance of the associative memory.

Abstract: A computer implemented data driven classification and data quality checking system is provided. The system has an interface application enabled to receive data and has an associative memory software. The system has a data driven associative memory model configured to categorize one or more fields of received data and to analyze the received data. The system has a data quality rating metric associated with the received data. The system has a machine learning data quality checker for the received data, and is configured to add the received data to a pool of neighboring data, if the data quality rating metric is greater than or equal to a data quality rating metric threshold. The machine learning data quality checker is configured to generate and communicate an alert of a potential error in the received data, if the data quality rating metric is less than the data quality rating metric threshold.

Abstract: A method for improving accuracy and quality of received data is provided. The method provides a computer implemented data driven classification and data quality checking system. The method uses the associative memory software to build a data driven associative memory model that enables a machine learning data quality checker for receiving data. The method categorizes one or more fields of received data, analyzes the received data, and calculates a data quality rating metric, by comparing the received data with a pool of neighboring data in the category of field of the received data. The method accepts and adds the received data, if the data quality rating metric is greater than or equal to a data quality rating metric threshold, and generates and communicates an alert of a potential error in the received data, if the data quality rating metric is less than the data quality rating metric threshold.

Abstract: A system, method and computer program product are provided for identifying a qualified candidate from among a plurality of initial candidates in an efficient and reliable manner. In the context of a system, an associative memory is provided that is configured to store information regarding a plurality of candidate entities and at least one requisition entity. The associative memory is also configured to store information regarding attributes associated with candidate and requisition entities. Further, the associative memory is configured to store information regarding associations between the entities. The system also includes a receiver module configured to receive one or more query terms. The system may also include an identification module configured to identify the qualified candidate based upon the query terms and the associations between the candidate entities and the at least one requisition entity that are provided by the associative memory.

Abstract: Methods of manufacturing collagen and other extracellular matrix components from SCCs are disclosed. The extracellular matrix components are useful in cosmetic applications, and can be manufactured free of immunogenic concerns and contaminants while controlling for other factors that commonly impact product quality and usefulness.

Abstract: The invention relates to methods identify or characterize compounds that can be used to treat specified clinical disorders such as hyperglycemia and type 2 diabetes. Compounds that can be used in these methods include 4?-fluoro-17?-ethynylandrost-5-ene-3?,7?,17?-triol, 4?-fluoro-17?-ethynylandrost-5-ene-3?,7?,17?-triol, 4?-fluoro-17?-ethynylandrost-5-ene-3?,7?,17?-triol and 4?-fluoro-17?-ethynylandrost-5-ene-3?,17?-triol-7-one.

Abstract: A new class of fluorinated or polyhalogenated triazepentadienes are disclosed. The synthesized triazapentadienes are thermally stable, soluble in typical solvents and have several metal binding sites for complexation with metal ions. The compounds are prepared as colorless crystalline solids. Synthesis takes advantage of a reaction with triethylamine. Synthesized triazapentadienes (with and without complexed metals) inhibit bacterial growth of both Gram positive and Gram-negative bacteria.

Abstract: The invention provides 17?-ethynylandrost-5-ene-3?, 7?, 17?-triol for use in methods to treat, e.g., hyperglycemia or diabetes patients having a body mass index of at least about 31 (?30.5, ?31 or ?32), wherein the patients are not concurrently treated with metformin and optionally another antidiabetic agent. In these methods, the patient will generally have a fasting insulin level of at least 4 ?U/mL or another characteristic as described herein.