Abstract: The disclosure relates to methods of treating and/or preventing scarring that would otherwise result from an incision to an area of skin. The methods comprise administering a composition comprising tropoelastin to an area of skin that is to receive an incision and/or after the incision. It is also contemplated that the compositions may reduce scar discoloration. Methods of preventing or reducing keloid re-occurrence are also provided.

Abstract: Disclosed are vanadium (V) compounds and pharmaceutical compositions comprising these vanadium compounds. Also disclosed are methods of making and using these vanadium compounds, for example, to treat cancer (e.g., including brain cancer).

Abstract: A crafting apparatus (10) includes a working portion (22) and a base portion (20). The working portion (22) includes a lower surface (32) and an upper surface (34). The upper surface (34) defines a working three dimensional Cartesian coordinate system (X-Y-Z). The base portion (20) includes a lower surface (24) and an upper surface (26). The lower surface (32) of the working portion (22) is disposed adjacent to the upper surface (26) of the base portion (20). The lower surface (24) defines a non-working three dimensional Cartesian coordinate system (XS-YS-ZS). The upper surface (34) of the working portion (22) extends relative to the lower surface (24) of the base portion (20) at an angle (?22) for angularly-offsetting the working three dimensional Cartesian coordinate system (X-Y-Z) from the non-working three dimensional Cartesian coordinate system (XS-YS-ZS). Methods (200, 300) are also disclosed.

Abstract: Determination of high value customer journey sequences is performed by determining customer interactions that are most frequent as length N=1 sub-sequences, recursively determining most frequent length N+1 sub-sequences that start with the length N sub-sequences, determining a first count indicating how often one of the sub-sequences appears in the sequences, determining a second count indicating how often the one sub-sequence resulted in the goal, and using the counts to determine the most or least effective sub-sequences for achieving the goal.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing audience segments associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify audience segments associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors and segments that caused the particular anomaly and how those factors correlate with each other.

Abstract: Determination of high value customer journey sequences is performed by determining customer interactions that are most frequent as length N=1 sub-sequences, recursively determining most frequent length N+1 sub-sequences that start with the length N sub-sequences, determining a first count indicating how often one of the sub-sequences appears in the sequences, determining a second count indicating how often the one sub-sequence resulted in the goal, and using the counts to determine the most or least effective sub-sequences for achieving the goal.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing audience segments associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify audience segments associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors and segments that caused the particular anomaly and how those factors correlate with each other.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing factors associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify sub-factors associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors that caused the particular anomaly and how those factors correlate with each other.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing audience segments associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify audience segments associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors and segments that caused the particular anomaly and how those factors correlate with each other.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing factors associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify sub-factors associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors that caused the particular anomaly and how those factors correlate with each other.

Abstract: In some embodiments, a real-time and interactive preview of alerts is provided in a user interface. A computer system parses a set of rules that specifies an alert definition. Each rule identifies a set of observations and an alert trigger criterion based on user input in the user interface. For a rule, the computer system accesses historical data corresponding to the set of observations identified by the rule and determines, based on an analysis of the historical data, time points that trigger alerts over a time period according to the rule. The analysis is based on the alert trigger criterion identified by the rule. The computer system aggregates, based on the alert definition, the time points determined for the rule with time points determined for another rule from the set of rules. Further, the computer system generates an alert preview over the time period for presentation at the user interface.

Abstract: A business process management (BPM) system, a business event processing system, and a business visibility system are integrated into a responsive process management platform using standardized messages to permit communication and collaboration among the systems. The BPM system has the capability to model and execute at least one monitoring process including at least one monitoring workstep. This monitoring process makes visible in the BPM system processes of interest that are executing in external systems. The business event processing system and/or the business visibility system have tools to allow users to easily configure those systems to sense events and send appropriate standardized messages to the other systems, can extract and send data to the BPM system, and can send alerts to the BPM system.

Abstract: Systems and methods for collecting client-side application performance monitoring (APM) information in distributed computer systems. An example method may comprise: inserting a script code fragment into an electronic document to be transmitted to a client computing device, wherein the script code fragment is to issue a request for loading an object from a second computer system, the request comprising at least one of: a parameter of a client browser executed by the client computing device, a parameter of an application being executed within the client browser, or a parameter of a current session of the client browser; and transmitting the electronic document to at least one of: the second computer system or the client computing device.

Abstract: In some embodiments, a real-time and interactive preview of alerts is provided in a user interface. A computer system parses a set of rules that specifies an alert definition. Each rule identifies a set of observations and an alert trigger criterion based on user input in the user interface. For a rule, the computer system accesses historical data corresponding to the set of observations identified by the rule and determines, based on an analysis of the historical data, time points that trigger alerts over a time period according to the rule. The analysis is based on the alert trigger criterion identified by the rule. The computer system aggregates, based on the alert definition, the time points determined for the rule with time points determined for another rule from the set of rules. Further, the computer system generates an alert preview over the time period for presentation at the user interface.

Abstract: Systems and methods for visualization of performance parameters of distributed computer systems. An example method may comprise: receiving data representing a geographic location of a client computer system issuing a plurality of requests to a server computer system, the data further comprising a plurality of values representing one or more parameters of request processing by the server computer system; and generating a sequence of video frames, each video frame of the sequence of video frames comprising a visual element of a pre-defined shape overlaid over a geographic map in a position corresponding to the geographic location of the client computer system, wherein a pre-defined attribute of the visual element visually represents one or more values of the plurality of values.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing audience segments associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify audience segments associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors and segments that caused the particular anomaly and how those factors correlate with each other.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing factors associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify sub-factors associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors that caused the particular anomaly and how those factors correlate with each other.

Abstract: Methods and apparatus for ascertaining trends in network activity data are disclosed. A plurality of trend indicators is calculated for a plurality of values of a metric associated with network activity for a network content provider. The trend indicators include one or more moving averages of the plurality of values of the metric, and one or more standard deviation values of the plurality of values of the metric. A time-series graphical overlay representation of the plurality of values of the metric and the plurality of trend indicators demonstrating a relationship between the metric values and the trend indicators is displayed.

Abstract: Methods and apparatus for predicting network activity with forecasting model selection are disclosed. In one embodiment a network analytics forecasting model with a preferred model error measurement is selected from among a set of model error measurements for a set of network analytics forecasting models. The selecting includes, for each of a set of network analytics forecasting models, calculating a set of predicted network analytics metric values corresponding to individual ones of a set of actual network analytics metric values in a network analytics metrics data set, comparing individual ones of the set of predicted network analytics metric values to corresponding ones of the set of actual network analytics metric values, and generating a model error measurement reflecting the comparing. Future network analytics metric values are predicted using the network analytics forecasting model with the preferred model error measurement.

Abstract: Systems and methods for collecting client-side application performance monitoring (APM) information in distributed computer systems. An example method may comprise: inserting a script code fragment into an electronic document to be transmitted to a client computing device, wherein the script code fragment is to issue a request for loading an object from a second computer system, the request comprising at least one of: a parameter of a client browser executed by the client computing device, a parameter of an application being executed within the client browser, or a parameter of a current session of the client browser; and transmitting the electronic document to at least one of: the second computer system or the client computing device.