Abstract: In one embodiment, a method includes determining an attack tactic risk score for one or more attack tactics based on a dataset of actual loss events and determining an incident risk score for an incident based on the one or more attack tactic risk scores. The method also includes determining a priority value for an asset. The asset is associated with the incident. The method further includes generating an asset risk score for the asset based on the priority value of the asset and the incident risk score.

Abstract: In one embodiment, a method includes receiving a historical text document that is associated with a breach event. The method also includes searching for an attack tactic within the historical text document using a machine learning algorithm. The method further includes generating a probability that the attack tactic exists within the historical text document, comparing the probability to a predetermined probability threshold, and categorizing the historical text document based on the probability.

Abstract: A priming system for an engine system having a throttle valve configured to regulate a flow of air and fuel into an intake manifold of an engine is disclosed. The priming system may include a first sensor configured to generate a signal indicative of an engine speed, an auxiliary fuel line configured to direct fuel from a fuel source to a location between an outlet of the throttle valve and the intake manifold, an auxiliary fuel valve disposed in the auxiliary fuel line, and a controller in communication with the first sensor and the auxiliary fuel valve. The controller may be configured determine the engine speed based on the first signal and close the auxiliary fuel valve when the engine speed is greater than or equal to a threshold engine speed. The threshold engine speed may be less than an idle speed of the engine.

Abstract: A method for estimating error in expression data. In one embodiment, the method includes single molecule sequencing a plurality of expression tags from an organism; removing expression tags that ambiguously relate to multiple genes; assigning each remaining expression tag to a respective gene; selecting a random subset of the expression tags; and counting the number of expression tags associated with each gene. The process of selecting a random subset of the expression tags; and counting the number of expression tags associated with each gene is repeated a predetermined number of times, both for expression tags sequenced before and after exposure of the organism to a perturbation. The method also includes the step of calculating a measure of error in response to the counts of the number of expression tags before and after the perturbation.

Abstract: Systems and methods for identifying populations of events in a multi-dimensional data set are described. The populations may, for example, be sets or clusters of data representing different white blood cell components in sample processed by a flow cytometer. The methods use a library consisting of one or more one finite mixture models, each model representing multi-dimensional Gaussian probability distributions with a density function for each population of events expected in the data set. The methods further use an expert knowledge set including one or more data transformations and one or more logical statements. The transformations and logical statements encode a priori expectations as to the populations of events in the data set. The methods further use program code by which a computer may operate on the data, a finite mixture model selected from the library, and the expert knowledge set to thereby identify populations of events in the data set.

Abstract: Systems and methods for identifying populations of events in a multi-dimensional data set, e.g., seven dimensional flow cytometry data of a blood sample. The populations may, for example, be sets or clusters of data representing different white blood cell components in the sample. The methods use a library consisting of one or more one finite mixture models, each model component comprising parameters representing multi-dimensional Gaussian probability density functions, one density for each population of events expected in the data set. The methods further use an expert knowledge set comprising one or more data transformations for operation on the multi-dimensional data set and one or more logical statements. The transformations and logical statements encode a priori expectations as to the relationships between different event populations in the data set.

Abstract: Novel zacrp3x2 polypeptides, polynucleotides encoding the polypeptides, and related compositions and methods are disclosed. Also disclosed are antibodies to the zacrp3x2 protein or fragments thereof.

Abstract: The present invention relates to polynucleotide and polypeptide molecules, and variants thereof, for Zzp1, a novel Zona Pellucida protein. The polypeptides, and polynucleotides encoding them, are fertility modulating and may be used for delivery and therapeutics. The present invention also includes antibodies to the Zzp1 polypeptides.

Abstract: Mammalian glycoprotein hormone-1 (Zlut1) polypeptides, polynucleotides encoding the polypeptides, antibodies that specifically bind to the polypeptides, expression vectors comprised of the polynucleotides, and host cells transformed with the expression vectors.

Abstract: A nestable octagonal tray having tapered, glued side walls of low height. The tray has an octagonal bottom panel, four trapezoidal side walls each attached at its shorter parallel edge to the bottom panel, four trapezoidal side flaps each attached at its longer parallel edge to the bottom panel, and eight substantially rectangular glue flaps each attached along its base to one of the non-parallel sides of the trapezoidal side walls. The side flaps and glue flaps are adhered in overlapping relation.