Abstract: A high precision weighing system and weighing method has a weighing plate and weighing unit separation mechanism and a weight loading mechanism. The weighing plate and weighing unit separation mechanism controls separation of a weighing plate and a weighing unit, so that the weighing plate or the weighing plate and its carried material do not apply force to the weighing unit. The weight loading mechanism loads a weight onto the weighing unit or removes a weight from the weighing unit; the weighing system records a weighing value of the weighing unit during the action of the weighing plate and weighing unit separation mechanism and a sensitivity value during the action of the weight loading mechanism. The weighing system modifies the weighing value at the time of the most recent combination of the weighing plate and the weighing unit based on the recorded weighing and sensitivity values, achieving a high precision.

Abstract: Embodiments of catalyst systems and methods of synthesizing catalyst systems are provided. The catalyst system may include a core comprising a zeolite; and a shell comprising a microporous fibrous silica. The shell may be in direct contact with at least a majority of an outer surface of the core. The catalyst system may have a Si/Al molar ratio greater than 5. At least a portion of the shell may have a thickness of from 50 nanometers (nm) to 360 nm.

Abstract: A displacement detector may include a substrate and a membrane having an inner surface facing the substrate. A mounting area may be arranged to fix the membrane along at least part of the perimeter of the membrane, wherein the mounting area, the inner surface and the substrate enclose a back volume. An acoustic compliance of the back volume may be arranged to be the same or larger than an acoustic compliance of the membrane. An optical sensor may be configured to generate a sensor signal indicative of a displacement of the membrane.

Abstract: The present invention provides methods to promote the differentiation of pluripotent stem cells. In particular, the present invention provides an improved method for the formation of pancreatic endoderm, pancreatic hormone expressing cells and pancreatic hormone secreting cells. The present invention also provides methods to promote the differentiation of pluripotent stem cells without the use of a feeder cell layer.

Abstract: The present invention provides methods to promote the differentiation of pluripotent stem cells. In particular, the present invention provides an improved method for the formation of pancreatic endoderm, pancreatic hormone expressing cells and pancreatic hormone secreting cells. The present invention also provides methods to promote the differentiation of pluripotent stem cells without the use of a feeder cell layer.

Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: The present invention provides methods to promote the differentiation of pluripotent stem cells. In particular, the present invention provides an improved method for the formation of pancreatic endoderm, pancreatic hormone expressing cells and pancreatic hormone secreting cells. The present invention also provides methods to promote the differentiation of pluripotent stem cells without the use of a feeder cell layer.

Abstract: The present invention provides methods to promote the differentiation of pluripotent stem cells into insulin producing cells. In particular, the present invention provides a method to produce cells expressing markers characteristic of the pancreatic endocrine lineage that co-express NKX6.1 and insulin and minimal amounts of glucagon.

Abstract: The present invention provides solid forms of an MK2 inhibitor, compositions thereof, and methods of using the same.

Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: The present disclosure relates to methods of early identification and detection of neurotoxicity associated with the administration of chimeric antigen receptor (CAR) T cell therapy and mitigation strategies to reduce the occurrence and/or severity of treatment associated neurotoxicity.

Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: The present invention provides a method for lowering blood glucose levels in an animal by transplanting a population of pancreatic endocrine precursor cells into an animal.

Abstract: The present invention provides a method for lowering blood glucose levels in an animal by transplanting a population of pancreatic endocrine precursor cells into an animal.

Abstract: Salts and solid forms of 3-(4-((4-(morpholinomethyl)benzyl)oxy)-1-oxoisoindolin-2-yl)piperidine-2,6-dione, or a stereoisomer thereof, are disclosed. Compositions comprising and methods of using the salts and solid forms are also disclosed.

Abstract: An embodiment includes calculating an efficacy value of a context assigned to an asset, the efficacy value being based at least in part on a percentage of assets assigned to the context. The embodiment also includes calculating, responsive to the calculated efficacy value being within a predetermined range, a normalized relevance value of a first tag associated with the asset. The embodiment also includes generating relative relevance value for the first tag and a reason code associated with a basis for the relative relevance value of the first tag based at least in part on the normalized relevance value of the first tag. The embodiment also includes initiating, responsive to generating the relative relevance value and the reason code for the first tag, a database command on a training dataset stored in the database that includes the first tag.

Abstract: Salts and solid forms of 3-(4-((4-(morpholinomethyl)benzyl)oxy)-1-oxoisoindolin-2-yl)piperidine-2,6-dione, or a stereoisomer thereof, are disclosed. Compositions comprising and methods of using the salts and solid forms are also disclosed.

Abstract: An embodiment includes calculating an efficacy value of a context assigned to an asset, the efficacy value being based at least in part on a percentage of assets assigned to the context. The embodiment also includes calculating, responsive to the calculated efficacy value being within a predetermined range, a normalized relevance value of a first tag associated with the asset. The embodiment also includes generating relative relevance value for the first tag and a reason code associated with a basis for the relative relevance value of the first tag based at least in part on the normalized relevance value of the first tag. The embodiment also includes initiating, responsive to generating the relative relevance value and the reason code for the first tag, a database command on a training dataset stored in the database that includes the first tag.

Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: The present invention provides solid forms of an MK2 inhibitor, compositions thereof, and methods of using the same.