Abstract: Pharmaceutical compositions comprising an immediate release component comprising 4-((L-valyl)oxy)butanoic acid and a modified release component comprising 4-((L-valyl)oxy)butanoic acid and the pharmacokinetics of 4-((L-valyl)oxy)butanoic acid and ?-hydroxybutyrate following oral administration of the pharmaceutical compositions is disclosed.

Abstract: The present invention is directed to methods of identifying and treating a human subject harboring a tumor or other disease comprising assessing HRG gene expression at a protein level in the human subject and administering a treatment comprising an anti-HER3 antibody to the human subject whose HRG gene expression at a protein level is assessed as high. The present invention is also directed to methods of identifying a human subject harboring a tumor or other disease comprising assessing HRG gene expression at a protein level in the human subject and withholding a treatment comprising an anti-HER3 antibody to the human subject whose HRG gene expression at a protein level is assessed as low.

Abstract: In one general embodiment, a computer-implemented method includes performing a firmware update on a hardware component of a computer system. A hash value associated with the update of the firmware is collected, and added to Platform Control Registers (PCRs) of multiple Trusted Platform Module (TPMs) of the computer system. The hash value is logged in a log file. At a predetermined time, PCR values are received from the TPMs. The PCR values are compared to determine whether all PCR values match. In response to one of the PCR values not matching, a warning is issued.

Abstract: A computer-implemented method of generating a security language query from a user input query includes receiving, at a computer system, an input security hunting user query indicating a user intention; selecting, using a trained machine learning model and based on the input security hunting query, an example user security hunting query and corresponding example security language query; generating, using the trained machine learning model, query metadata from the input security hunting query; generating a prompt, the prompt comprising: the input security hunting user query; the selected example user security hunting query and the corresponding example security language query; and the generated query metadata; inputting the prompt to a large language model; receiving a security language query from the large language model corresponding to the input security hunting query reflective of the user intention.

Abstract: Request flow log retrieval can include extracting one or more keywords from a natural language description of an action, the action being a system response to a user request submitted to a resource-provisioning system during a user session. Request flow log retrieval can also include determining a classification of the action based on a correlation value generated by a classifier model trained using machine learning to classify actions performed by the resource-provisioning system, the classification based on the one or more keywords. Additionally, request flow log retrieval can include automatically identifying a request flow associated with the action based on the classification of the action and returning at least one system log entry corresponding to the request flow.

Abstract: The invention relates to a method for preventing search fraud in a content management system. For an update of a content item of a search index of a search service provided by the content management system ranking metrics are calculated using a set of one or more search queries from a collection of search queries previously received by the search service. At least one statistic is computed using the calculated ranking metrics and compared with at least one statistic provided by a statistics history database. Depending on the result of the comparing, the update of the content item is flagged as fraudulent or as non-fraudulent.

Abstract: A computer-implemented method for consolidating log file entries may be provided. The method comprises receiving a first log file and a second log file, determining a first characterizing feature set of a first log file entry of the first log file and a second characterizing feature set of a second log file entry of the second log file, and determining a correlation factor value of a correlation between the first log file entry and the second log file entry by classifying a relationship of the first log file entry and the second log file entry using the characterizing feature sets. The method further comprises upon determining that the correlation factor value is above a predetermined correlation factor threshold value, determining that the first log file entry and the second log file entry relate to each other and belong to a same action flow.

Abstract: A computer-implemented method for consolidating log file entries may be provided. The method comprises receiving a first log file and a second log file, determining a first characterizing feature set of a first log file entry of the first log file and a second characterizing feature set of a second log file entry of the second log file, and determining a correlation factor value of a correlation between the first log file entry and the second log file entry by classifying a relationship of the first log file entry and the second log file entry using the characterizing feature sets. The method further comprises upon determining that the correlation factor value is above a predetermined correlation factor threshold value, determining that the first log file entry and the second log file entry relate to each other and belong to a same action flow.

Abstract: The invention relates to a method for preventing search fraud in a content management system. For an update of a content item of a search index of a search service provided by the content management system ranking metrics are calculated using a set of one or more search queries from a collection of search queries previously received by the search service. At least one statistic is computed using the calculated ranking metrics and compared with at least one statistic provided by a statistics history database. Depending on the result of the comparing, the update of the content item is flagged as fraudulent or as non-fraudulent.

Abstract: Providing software-as-a-service to a plurality of clients includes: visually rendering a first virtual portal and a set of portal resources according to a portal-resource association specified in a resource association matrix; identifying a set of server resources accessible from a portal server, the set of server resources excluding the set of portal resources; determining a score for a first resource of the set of server resources; visually rendering the first resource; and associating the first resource with the first virtual portal in the resource association matrix by adding an identifier of the scored resource.

Abstract: Request flow log retrieval can include extracting one or more keywords from a natural language description of an action, the action being a system response to a user request submitted to a resource-provisioning system during a user session. Request flow log retrieval can also include determining a classification of the action based on a correlation value generated by a classifier model trained using machine learning to classify actions performed by the resource-provisioning system, the classification based on the one or more keywords. Additionally, request flow log retrieval can include automatically identifying a request flow associated with the action based on the classification of the action and returning at least one system log entry corresponding to the request flow.

Abstract: Providing software-as-a-service to a plurality of clients includes: visually rendering a first virtual portal and a set of portal resources according to a portal-resource association specified in a resource association matrix; identifying a set of server resources accessible from a portal server, the set of server resources excluding the set of portal resources; determining a score for a first resource of the set of server resources; visually rendering the first resource; and associating the first resource with the first virtual portal in the resource association matrix by adding an identifier of the scored resource

Abstract: Providing software-as-a-service to a plurality of clients includes: selecting a first virtual portal, determining a score for a first resource to generate a first scored resource, determining a set of scored resources, visually rendering the first virtual portal and the set of portal resources, visually rendering the set of scored resources, and selecting a scored resource from the set of scored resources to be associated with the first virtual portal by updating the resource association matrix with an identifier of the scored resource. The score is selected to represent a usefulness factor of the first resource. Each scored resource of the set of scored resources is selected to be different than each portal resource of a set of portal resources associated with the first virtual portal by a resource association matrix.

Abstract: Providing software-as-a-service to a plurality of clients includes: selecting a first virtual portal, determining a score for a first resource to generate a first scored resource, determining a set of scored resources, visually rendering the first virtual portal and the set of portal resources, visually rendering the set of scored resources, and selecting a scored resource from the set of scored resources to be associated with the first virtual portal by updating the resource association matrix with an identifier of the scored resource. The score is selected to represent a usefulness factor of the first resource. Each scored resource of the set of scored resources is selected to be different than each portal resource of a set of portal resources associated with the first virtual portal by a resource association matrix.

Abstract: Providing software-as-a-service to a plurality of clients includes: selecting a first virtual portal, determining a score for a first resource to generate a first scored resource, determining a set of scored resources, visually rendering the first virtual portal and the set of portal resources, visually rendering the set of scored resources, and selecting a scored resource from the set of scored resources to be associated with the first virtual portal by updating the resource association matrix with an identifier of the scored resource. The score is selected to represent a usefulness factor of the first resource. Each scored resource of the set of scored resources is selected to be different than each portal resource of a set of portal resources associated with the first virtual portal by a resource association matrix.

Abstract: Providing software-as-a-service to a plurality of clients includes: selecting a first virtual portal, determining a score for a first resource to generate a first scored resource, determining a set of scored resources, visually rendering the first virtual portal and the set of portal resources, visually rendering the set of scored resources, and selecting a scored resource from the set of scored resources to be associated with the first virtual portal by updating the resource association matrix with an identifier of the scored resource. The score is selected to represent a usefulness factor of the first resource. Each scored resource of the set of scored resources is selected to be different than each portal resource of a set of portal resources associated with the first virtual portal by a resource association matrix.

Abstract: In a method of and system for enforcing authentication strength for remote portlets, a portlet is provided by a producer portal and consumed as remote portlet by a consumer portal. The producer portal defines an authentication strength level requirement for the portlet. A user requests the remote portlet from the consumer portal. The consumer portal authenticates the user with a particular authentication method that implies a particular authentication strength level. The producer portal authenticates the consumer portal with a particular authentication method that implies a particular authentication strength assertion level. The consumer portal requests the portlet from the producer portal with an assertion of the authentication strength level of the user. The producer portal rejects the request from the consumer portal if the authentication strength level of the user is less than the authentication strength level requirement for the portlet.

Abstract: Embodiments provide methods, apparatus, and systems for environmental lighting compensation in imaging devices. Environmental characteristics, including ambient light, may be accounted for in order to optimize an output.

Abstract: A method and corresponding apparatus are for compressing image data of an image. The method includes splitting the image data into regions, including a first region and a second region. The method further includes determining a first compression scheme to be used in encoding the image data of the first region and a different second compression scheme to be used in encoding the image data of the second region. The method further includes applying the first compression scheme to the image data of the first region and the second the compression scheme to the image data of the second region. For each region, the determining and the applying are iteratively performed to yield first resulting compressed region data for the first region and second resulting compressed region data for the second region.

Abstract: Embodiments provide methods, apparatus, and systems for environmental lighting compensation in imaging devices. Environmental characteristics, including ambient light, may be accounted for in order to optimize an output.