Abstract: A computer-implemented method for recalibrating nacelle-positions of a plurality of wind turbines in a wind park is implemented by a nacelle calibration computing device including a processor and a memory device coupled to the processor. The method includes identifying at least two associated wind turbines included within the wind park wherein each associated wind turbine includes location information, determining a plurality of predicted wake features for the associated wind turbines based at least partially on the location information of each associated wind turbine, retrieving a plurality of historical performance data related to the associated wind turbines, determining a plurality of current wake features based on the plurality of historical performance data, identifying a variance between the predicted wake features and the current wake features, and determining a recalibration factor for at least one of the associated wind turbines based on the identified variance.

Abstract: The present invention provides a microscope slide for analyzing a tissue sample. The slide includes an elongate planar substrate, which comprises a first major surface having a sample-affixing area within which a tissue sample may be affixed; a first positive control sample affixed on the first major surface at a first location adjacent to the sample-affixing area; and a second positive control sample affixed on the first major surface at a second location adjacent to the sample-affixing area. The first and second locations are spaced such that quality of the staining of the first and second positive control samples is indicative of the quality of the staining of the tissue sample. Also provided are a kit containing the microscope slide and a method of making and a method of using the microscope slide.

Abstract: A control system for use with a plurality of wind turbines includes a processor and a memory device coupled to the processor. The memory device is configured to store a plurality of program modules that, when executed by the processor, configure the processor to receive data representative of a power generation of a first wind turbine of the plurality of wind turbines, and determine an expected power generation of a second wind turbine of the plurality of wind turbines based on the power generation of the first wind turbine.

Abstract: The present invention provides a microscope slide for analyzing a tissue sample. The slide includes an elongate planar substrate, which comprises a first major surface having a sample-affixing area within which a tissue sample may be affixed; a first positive control sample affixed on the first major surface at a first location adjacent to the sample-affixing area; and a second positive control sample affixed on the first major surface at a second location adjacent to the sample-affixing area. The first and second locations are spaced such that quality of the staining of the first and second positive control samples is indicative of the quality of the staining of the tissue sample. Also provided are a kit containing the microscope slide and a method of making and a method of using the microscope slide.

Abstract: A computer-implemented method for recalibrating nacelle-positions of a plurality of wind turbines in a wind park is implemented by a nacelle calibration computing device including a processor and a memory device coupled to the processor. The method includes identifying at least two associated wind turbines included within the wind park wherein each associated wind turbine includes location information, determining a plurality of predicted wake features for the associated wind turbines based at least partially on the location information of each associated wind turbine, retrieving a plurality of historical performance data related to the associated wind turbines, determining a plurality of current wake features based on the plurality of historical performance data, identifying a variance between the predicted wake features and the current wake features, and determining a recalibration factor for at least one of the associated wind turbines based on the identified variance.

Abstract: A method of analyzing a biological sample suspected of having classic Hodgkin lymphoma, comprising (1) detecting, in a single sample, for the expression of at least two biomarkers selected from CD30, CD15, CD20, CD45, CD3, Pax-5, CD79A, BOB1 and OCT-2; and (b) analyzing the sample based on the presence, absence and/or expression level of the at least two biomarkers. Also provided is a method wherein all the nine biomarkers are analyzed on a single sample. Further provided are method for diagnosing classical Hodgkin lymphoma, as well as system and kit that comprise the means for executing the novel methods.

Abstract: A method for providing a composite image of a single biological sample from a patient suspected of having classical Hodgkin lymphoma, comprising the steps of generating a first image of the biological sample including the presence, absence and/or expression level of a first biomarker, generating a second image of the biological sample including the presence, absence and/or expression level of a second biomarker, and generating a composite image that provides the relative location or expression of both biomarkers. Also provided is a method of analyzing a biological sample, comprising providing a composite image of the biological sample according to the method for providing a composite image, and analyzing the expression of the biomarkers of interest from the composite image. Further provided are method for diagnosing classical Hodgkin lymphoma, as well as system and kit that comprise the means for executing the novel methods.

Abstract: Exemplary embodiments enable determination of spatial proximity between two or more features in biological tissue. An exemplary method includes identifying a morphological feature in an image of the biological tissue based on expression levels of a first biomarker indicative of the morphological feature, and receiving a result of a segmentation analysis performed on the image of the biological tissue identifying a set of morphological units in the image external to the morphological feature. An exemplary method includes determining an expression level of a second biomarker corresponding to each unit in the set of morphological units in the image of the biological tissue, and determining a spatial distance between the morphological feature and each unit in the set of morphological units.

Abstract: The invention relates generally to a process of analyzing and visualizing the expression of biomarkers in an individual cell wherein the cell is examined to develop patterns of expression by using a grouping algorithm, and a system to perform and display the analysis.

Abstract: A data set of cell profile data is stored. The cell profile data includes multiplexed biometric image data describing the expression of a plurality of biomarkers. Cell profile data is generated from tissue samples drawn from a cohort of patients having an assessment related to the commonality. Multiple sets of clusters of similar cells are generated from the data set; the proportion of cells in each cluster is examined for an association with a diagnosis, a prognosis, or a response; and a predictive set of clusters is selected based on model performance. One predictive set of clusters is selected based on a comparison of the performance of at least one model of the plurality of sets of clusters. Display techniques that aid in understanding the characteristics of a cluster are disclosed.

Abstract: Embodiments disclosed herein include methods, systems, and devices for determining a positive or negative correlation between a clinical outcome and one or more features of biological tissue. An exemplary user interface enables a user to select a clinical outcome and one or more aspects of a displayed field-of-view of biological tissue. Exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of the user-selected aspects of the field-of-view of biological tissue. For example, exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of one or more biological units in the biological tissue.

Abstract: Exemplary embodiments enable determination of spatial proximity between two or more features in biological tissue. An exemplary method includes identifying a morphological feature in an image of the biological tissue based on expression levels of a first biomarker indicative of the morphological feature, and receiving a result of a segmentation analysis performed on the image of the biological tissue identifying a set of morphological units in the image external to the morphological feature. An exemplary method includes determining an expression level of a second biomarker corresponding to each unit in the set of morphological units in the image of the biological tissue, and determining a spatial distance between the morphological feature and each unit in the set of morphological units.

Abstract: Embodiments disclosed herein include methods, systems, and devices for determining a positive or negative correlation between a clinical outcome and one or more features of biological tissue. An exemplary user interface enables a user to select a clinical outcome and one or more aspects of a displayed field-of-view of biological tissue. Exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of the user-selected aspects of the field-of-view of biological tissue. For example, exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of one or more biological units in the biological tissue.

Abstract: Transactional risk and return analysis systems provided herein include a transaction database and a market database. The transaction database includes data regarding transactions with associated attributes and the market database includes market data. A portfolio model uses such data to estimate a risk prediction for each transaction. A risk prediction model is generated based on the portfolio model and estimates a risk prediction for a prospective transaction, and a case cash flow analyzer produces a risk-breakeven spread. A transaction evaluator uses the risk prediction model and the risk-breakeven spread to calculated transaction risk and return data for a prospective transaction.

Abstract: A stored data set comprises cell profile data including multiplexed biometric image data describing the expression of biomarkers. The data set includes an association of the cell profile data with a field of view level or a patient-level assessment. Cell features are calculated based on the cell's expression of each of the biomarkers. Moments of cell features are calculated from the data set, and combinations are examined for an association with an assessment. A predictive set of moments is selected based on the performance of the combination.

Abstract: A data set of cell profile data is stored. The cell profile data includes multiplexed biometric image data describing the expression of a plurality of biomarkers. Cell profile data is generated from tissue samples drawn from a cohort of patients having an assessment related to the commonality. Multiple sets of clusters of similar cells are generated from the data set; the proportion of cells in each cluster is examined for an association with a diagnosis, a prognosis, or a response; and a predictive set of clusters is selected based on model performance. One predictive set of clusters is selected based on a comparison of the performance of at least one model of the plurality of sets of clusters. Display techniques that aid in understanding the characteristics of a cluster are disclosed.

Abstract: Cell profile data is stored. The cell profile data comprises multiplexed biometric images capturing the expression of a plurality of biomarkers by at least one tissue sample from a patient with respect to at least one field of view. Individual cells are delineated and segmented into compartments. At least one cell feature is calculated based on the cell's expression of each of a plurality of biomarkers. A first moment is calculated for each cell feature. The moments are examined for an association with a diagnosis, a prognosis of a response to treatment of a condition or disease. Apparatus for performing the foregoing steps are disclosed.

Abstract: A data set of cell profile data is stored. The cell profile data includes multiplexed biometric image data describing the expression of a plurality of biomarkers with respect to a field of view in which individual cells are delineated and segmenting into compartments. Each cell in the field is assigned to a single cluster in a selected set of clusters based on cell similarity; cell similarity is determined based on a plurality of selected cell attributes. The proportion of cells in each cluster is observed. The observed proportions are examined for an association with a diagnosis, a prognosis, or a response derived from a known association of the selected set of clusters with at least one piece of meta-information including a field of view level assessment or a patient-level assessment.

Abstract: A control system for use with a plurality of wind turbines includes a processor and a memory device coupled to the processor. The memory device is configured to store a plurality of program modules that, when executed by the processor, configure the processor to receive data representative of a power generation of a first wind turbine of the plurality of wind turbines, and determine an expected power generation of a second wind turbine of the plurality of wind turbines based on the power generation of the first wind turbine.

Abstract: The present disclosure relates to an approach by which low-performing turbines may be identified from among a plurality of wind turbines, such as may be present at a wind power plant. In accordance with one embodiment, low-performing turbines are identified from among pairs of turbines and based upon a comparison of the observed and expected performance of the turbines within each pair.