Abstract: This disclosure provides recombinant DNA constructs and transgenic plants having enhanced traits such as increased yield, increased nitrogen use efficiency, and enhanced drought tolerance or water use efficiency. Transgenic plants may include field crops as well as plant propagules and progeny of such transgenic plants. Methods of making and using such transgenic plants are also provided. This disclosure also provides methods of producing seed from such transgenic plants, growing such seed, and selecting progeny plants with enhanced traits. Also disclosed are transgenic plants with altered phenotypes which are useful for screening and selecting transgenic events for the desired enhanced trait.

Abstract: The present disclosure provides a transgenic corn comprising event MON87403 that exhibits increased grain yield. The disclosure also provides cells, plant parts, seeds, plants, commodity products related to the event, and DNA molecules that are unique to the event and were created by the insertion of transgenic DNA into the genome of a corn plant. The disclosure further provides methods for detecting the presence of said corn event nucleotide sequences in a sample, probes and primers for use in detecting nucleotide sequences that are diagnostic for the presence of said corn event.

Abstract: This disclosure provides recombinant DNA constructs and transgenic plants having enhanced traits such as increased yield, increased nitrogen use efficiency, and enhanced drought tolerance or water use efficiency. Transgenic plants may include field crops as well as plant propagules and progeny of such transgenic plants. Methods of making and using such transgenic plants are also provided. This disclosure also provides methods of producing seed from such transgenic plants, growing such seed, and selecting progeny plants with enhanced traits. Also disclosed are transgenic plants with altered phenotypes which are useful for screening and selecting transgenic events for the desired enhanced trait.

Abstract: Documents needing to be analyzed for various reasons, such as financial crimes, are ranked by examining the topicality and sentiment present in each document for a given subject of interest. In one approach a given document is classified to determine its category, and entity recognition is used to identify the subject of interest. Passages from the document that relate to the entity are grouped and analyzed for sentiment to generate a sentiment score. Documents are then ranked based on the sentiment scores. In another approach, a classification probability score is computed for each passage representing a likelihood that the passage relates to a category of interest, and the document is ranked based on the sentiment scores and the classification probability scores. The category classification uses an ensemble of natural language text classifiers. One of the classifiers is a naïve Bayes classifier with feature vectors generated using Word2Vec modeling.

Abstract: The present disclosure provides a transgenic corn comprising event MON87403 that exhibits increased grain yield. The disclosure also provides cells, plant parts, seeds, plants, commodity products related to the event, and DNA molecules that are unique to the event and were created by the insertion of transgenic DNA into the genome of a corn plant. The disclosure further provides methods for detecting the presence of said corn event nucleotide sequences in a sample, probes and primers for use in detecting nucleotide sequences that are diagnostic for the presence of said corn event.

Abstract: An approach is provided for generating process flow documentation. Headings and subheadings are identified in multiple system documents specifying actions required to be taken in response to service requests, which are specified by process flows. A portion of a system document included in the multiple system documents is mapped to a process block of a process flow included in the process flows. The portion is specified by a heading or subheading in the system document. The mapping is based on a similarity score indicating an amount of similarity between (i) the heading or subheading and (ii) a name of the process block, or based on a matching of the portion of the system document to the process block by a semantic understanding of the portion provided by a machine learning system.

Abstract: An approach is provided in which the approach applies, by a first node, a first axiom to a set of data points to generate a set of first outputs. The approach applies, by a second node, a second axiom to the set of data points to generate a set of second outputs. The first node and the second node are part of a computer network that includes multiple nodes. The approach computes a first nuance based on a set of disagreements between the set of first outputs and the set of second outputs, and adjusts a reliability of the first node in the computer network based on the first nuance.

Abstract: The present disclosure provides a transgenic corn comprising event MON87403 that exhibits increased grain yield. The disclosure also provides cells, plant parts, seeds, plants, commodity products related to the event, and DNA molecules that are unique to the event and were created by the insertion of transgenic DNA into the genome of a corn plant. The disclosure further provides methods for detecting the presence of said corn event nucleotide sequences in a sample, probes and primers for use in detecting nucleotide sequences that are diagnostic for the presence of said corn event.

Abstract: This disclosure provides recombinant DNA constructs and transgenic plants having enhanced traits such as increased yield, increased nitrogen use efficiency, and enhanced drought tolerance or water use efficiency. Transgenic plants may include field crops as well as plant propagules and progeny of such transgenic plants. Methods of making and using such transgenic plants are also provided. This disclosure also provides methods of producing seed from such transgenic plants, growing such seed, and selecting progeny plants with enhanced traits. Also disclosed are transgenic plants with altered phenotypes which are useful for screening and selecting transgenic events for the desired enhanced trait.

Abstract: Documents needing to be analyzed for various reasons, such as financial crimes, are ranked by examining the topicality and sentiment present in each document for a given subject of interest. In one approach a given document is classified to determine its category, and entity recognition is used to identify the subject of interest. Passages from the document that relate to the entity are grouped and analyzed for sentiment to generate a sentiment score. Documents are then ranked based on the sentiment scores. In another approach, a classification probability score is computed for each passage representing a likelihood that the passage relates to a category of interest, and the document is ranked based on the sentiment scores and the classification probability scores. The category classification uses an ensemble of natural language text classifiers. One of the classifiers is a naïve Bayes classifier with feature vectors generated using Word2Vec modeling.

Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.

Abstract: The present disclosure provides a transgenic corn comprising event MON87403 that exhibits increased grain yield. The disclosure also provides cells, plant parts, seeds, plants, commodity products related to the event, and DNA molecules that are unique to the event and were created by the insertion of transgenic DNA into the genome of a corn plant. The disclosure further provides methods for detecting the presence of said corn event nucleotide sequences in a sample, probes and primers for use in detecting nucleotide sequences that are diagnostic for the presence of said corn event.

Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.

Abstract: The present disclosure provides a transgenic corn comprising event MON87403 that exhibits increased grain yield. The disclosure also provides cells, plant parts, seeds, plants, commodity products related to the event, and DNA molecules that are unique to the event and were created by the insertion of transgenic DNA into the genome of a corn plant. The disclosure further provides methods for detecting the presence of said corn event nucleotide sequences in a sample, probes and primers for use in detecting nucleotide sequences that are diagnostic for the presence of said corn event.

Abstract: This disclosure provides recombinant DNA constructs and transgenic plants having enhanced traits such as increased yield, increased nitrogen use efficiency, and enhanced drought tolerance or water use efficiency. Transgenic plants may include field crops as well as plant propagules and progeny of such transgenic plants. Methods of making and using such transgenic plants are also provided. This disclosure also provides methods of producing seed from such transgenic plants, growing such seed, and selecting progeny plants with enhanced traits. Also disclosed are transgenic plants with altered phenotypes which are useful for screening and selecting transgenic events for the desired enhanced trait.

Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.

Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.

Abstract: Documents needing to be analyzed for various reasons, such as financial crimes, are ranked by examining the topicality and sentiment present in each document for a given subject of interest. In one approach a given document is classified to determine its category, and entity recognition is used to identify the subject of interest. Passages from the document that relate to the entity are grouped and analyzed for sentiment to generate a sentiment score. Documents are then ranked based on the sentiment scores. In another approach, a classification probability score is computed for each passage representing a likelihood that the passage relates to a category of interest, and the document is ranked based on the sentiment scores and the classification probability scores. The category classification uses an ensemble of natural language text classifiers. One of the classifiers is a naïve Bayes classifier with feature vectors generated using Word2Vec modeling.

Abstract: Documents needing to be analyzed for various reasons, such as financial crimes, are ranked by examining the topicality and sentiment present in each document for a given subject of interest. In one approach a given document is classified to determine its category, and entity recognition is used to identify the subject of interest. Passages from the document that relate to the entity are grouped and analyzed for sentiment to generate a sentiment score. Documents are then ranked based on the sentiment scores. In another approach, a classification probability score is computed for each passage representing a likelihood that the passage relates to a category of interest, and the document is ranked based on the sentiment scores and the classification probability scores. The category classification uses an ensemble of natural language text classifiers. One of the classifiers is a naïve Bayes classifier with feature vectors generated using Word2Vec modeling.

Abstract: The present disclosure provides a transgenic corn comprising event MON87403 that exhibits increased grain yield. The disclosure also provides cells, plant parts, seeds, plants, commodity products related to the event, and DNA molecules that are unique to the event and were created by the insertion of transgenic DNA into the genome of a corn plant. The disclosure further provides methods for detecting the presence of said corn event nucleotide sequences in a sample, probes and primers for use in detecting nucleotide sequences that are diagnostic for the presence of said corn event.