Abstract: A method, computer program product, and computer system are provided for container cross-cluster capacity scaling. The method includes broadcasting local capacity information of capacity availability or capacity requirement for the local cluster and receiving broadcasts from each of one or more other clusters providing capacity information including capacity availability or capacity requirements. The method may map the received capacity information with the local capacity information and may determine a suitable cross-cluster capacity sharing when a capacity requirement of the local cluster maps to a capacity availability of another cluster or when a capacity availability of the local cluster maps to a capacity requirement of another cluster. The method may coordinate the deallocation of a node from the cluster having the capacity availability and reallocation of the node to the cluster having the capacity requirement.

Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: Systems and methods are provided for monitoring the effects of therapeutics on the brain. Brains of first and second sets of patients are imaged and a gene expression is measured at a first time to provide a first set of images and a first set of gene expression transcripts. A therapeutic is administered to the first set of patients after the first time. The brains of the patients are imaged and the gene expression of the patients is measured at a second time, after the therapeutic is administered, to provide a second set of images and a second set of gene expression transcripts. A change in the brain is determined for the patients from the sets of images. A set of changes in the gene expression that are correlated with the changes in the brain are determined from the change in the brain and the sets of gene expression transcripts.

Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: A method of anesthetizing a subject that includes administering a therapeutically effective amount of an NMDA antagonist to the subject is described. The method also includes administering an effective amount of a presynaptic glutamate release inhibitor to the subject to decrease the neurotoxic and/or psychomimetic side effects of the NMDA antagonist. Pharmaceutical compositions including an NMDA antagonist and a presynaptic glutamate release inhibitor are also described.

Abstract: Systems and methods are provided for correlating functional magnetic resonance imaging (fMRI) with gene expression. Brains of first and second sets of patients are imaged at first and second times to provide first and second sets of fMRI images. Blood is drawn from each of the first and second sets of patients at the first and second times to provide first and second sets of gene expression transcripts. A therapeutic is administered to the first set of patients between the first and second times. A change in the connectivity of the brain for each patient is determined from the first and second sets of fMRI images. A set of changes in the peripheral lymphocyte gene expression that are correlated with changes in the connectivity of the brain are determined from the change in the connectivity of the brain for each patient and the collected imaging and gene expression data.

Abstract: Systems and methods are provided for monitoring the effects of therapeutics on the brain. Brains of first and second sets of patients are imaged and a gene expression is measured at a first time to provide a first set of images and a first set of gene expression transcripts. A therapeutic is administered to the first set of patients after the first time. The brains of the patients are imaged and the gene expression of the patients is measured at a second time, after the therapeutic is administered, to provide a second set of images and a second set of gene expression transcripts. A change in the brain is determined for the patients from the sets of images. A set of changes in the gene expression that are correlated with the changes in the brain are determined from the change in the brain and the sets of gene expression transcripts.

Abstract: Systems and methods are provided for correlating functional magnetic resonance imaging (fMRI) with gene expression. Brains of first and second sets of patients are imaged at first and second times to provide first and second sets of fMRI images. Blood is drawn from each of the first and second sets of patients at the first and second times to provide first and second sets of gene expression transcripts. A therapeutic is administered to the first set of patients between the first and second times. A change in the connectivity of the brain for each patient is determined from the first and second sets of fMRI images. A set of changes in the peripheral lymphocyte gene expression that are correlated with changes in the connectivity of the brain are determined from the change in the connectivity of the brain for each patient and the collected imaging and gene expression data.

Abstract: A system for monitoring and tracking of personnel in a closed operational network is provided. The system includes a database to store and retrieve profiles of the personnel. The system also includes a plurality of Bluetooth Low Energy (BLE) based identification tags linked to the profiles of each of the personnel, and one or more BLE based receivers positioned at one or more strategic locations in the closed operational network to generate first signals in response to a detection of the one or more identification tags. The system further includes a processing unit to receive the one or more first signals from the one or more receivers. The processing unit further records, in the database, one or more first entries indicative of a presence of the one or more personnel with respect to the one or more strategic locations, based on the one or more first signals.

Abstract: Write optimization for block-based storage performing snapshot operations may be implemented. Write requests for a particular data volume may be received for which a snapshot operation is in progress. A determination may be made as to whether a data chunk of the data volume modified as part of the write request has not yet been stored to a remote snapshot data store as part of the snapshot operation. For a data chunk that is to be modified and that has not yet been stored, the data chunk may be stored in a local in-memory volume snapshot buffer. Once the data chunk is stored in the in-memory volume snapshot buffer, the write request may be performed and acknowledged as complete. The data chunk may be sent to the remote snapshot data store asynchronously with regard to the acknowledgment of the write request.

Abstract: A system and method to determine health prognostics for selection and management of a tool for deployment in a downhole environment are described. The system includes a database to store life cycle information of the tool, the life cycle information including environmental and operational parameters associated with use of the tool. The system also includes a memory device to store statistical equations to determine the health prognostics of the tool, and a processor to calibrate the statistical equations and build a time-to-failure model of the tool based on a first portion of the life cycle information in the database.

Abstract: Write optimization for block-based storage performing snapshot operations may be implemented. Write requests for a particular data volume may be received for which a snapshot operation is in progress. A determination may be made as to whether a data chunk of the data volume modified as part of the write request has not yet been stored to a remote snapshot data store as part of the snapshot operation. For a data chunk that is to be modified and that has not yet been stored, the data chunk may be stored in a local in-memory volume snapshot buffer. Once the data chunk is stored in the in-memory volume snapshot buffer, the write request may be performed and acknowledged as complete. The data chunk may be sent to the remote snapshot data store asynchronously with regard to the acknowledgment of the write request.

Abstract: Write optimization for block-based storage performing snapshot operations may be implemented. Write requests for a particular data volume may be received for which a snapshot operation is in progress. A determination may be made as to whether a data chunk of the data volume modified as part of the write request has not yet been stored to a remote snapshot data store as part of the snapshot operation. For a data chunk that is to be modified and that has not yet been stored, the data chunk may be stored in a local in-memory volume snapshot buffer. Once the data chunk is stored in the in-memory volume snapshot buffer, the write request may be performed and acknowledged as complete. The data chunk may be sent to the remote snapshot data store asynchronously with regard to the acknowledgment of the write request.

Abstract: A system and method to determine health prognostics for selection and management of a tool for deployment in a downhole environment are described. The system includes a database to store life cycle information of the tool, the life cycle information including environmental and operational parameters associated with use of the tool. The system also includes a memory device to store statistical equations to determine the health prognostics of the tool, and a processor to calibrate the statistical equations and build a time-to-failure model of the tool based on a first portion of the life cycle information in the database.

Abstract: A method and apparatus for buffering an encoded signal having a plurality of codewords for a turbo decoder is provided. The method comprises de-interleaving each sub-block of the codeword received at the turbo-decoder; and storing LLRs of the de-interleaved codeword LLRs into an input buffer. Thereafter, each of punctured locations, if any, in the de-interleaved codeword is indicated to a read logic for enabling the latter to fill in each of those locations with a pre-determined LLR value as and when a read request corresponding to one of those locations arrives. This method obviates the need for storing the pre-determined LLRs at the punctured locations into the input buffer and thereby cuts down the input latency of turbo decoder significantly for higher code rates.

Abstract: A method and apparatus for buffering an encoded signal having a plurality of codewords for a turbo decoder is provided. The method comprises de-interleaving each sub-block of the codeword received at the turbo-decoder; and storing LLRs of the de-interleaved codeword LLRs into an input buffer. Thereafter, each of punctured locations, if any, in the de-interleaved codeword is indicated to a read logic for enabling the latter to fill in each of those locations with a pre-determined LLR value as and when a read request corresponding to one of those locations arrives. This method obviates the need for storing the pre-determined LLRs at the punctured locations into the input buffer and thereby cuts down the input latency of turbo decoder significantly for higher code rates.