Abstract: The present invention discloses a ZmWAK-RLK protein related to gray leaf spot resistance, and an encoding gene and application thereof. The present invention sets forth a protein obtained from a maize inbred line Y32, named ZmWAK-RLK, and being the protein shown in sequence 1 of the sequence listing. A nucleic acid molecule for encoding the ZmWAK-RLK protein is likewise considered to be within the scope of protection of the present invention. The present invention likewise sets forth a method for preparing a transgenic plant, comprising the following step: introducing said nucleic acid molecule into a starting plant, thus obtaining a transgenic plant having enhanced resistance to gray leaf spot. The present invention additionally sets forth a plant breeding method, comprising the following step: increasing the content and/or activity of the ZmWAK-RLK protein in a plant of interest, thus increasing the gray leaf spot resistance of the plant of interest.

Abstract: A NVMe™ or NVMe-over-fabrics enabled device with video codec functionality may be seen to overcome scalability problem of known hardware assisted video codec solutions. The device of aspects of the present application may or may not have storage media. A host computer communicates with the device through NVMe™ commands. The device may be in one of many SSD form factors, such as U.2 or AIC. The device may be provided as a component in NVMe-enabled computers or NVMe-over-fabrics-enabled systems.

Abstract: Methods and apparatus to adaptively manage data collection devices in distributed computing systems are disclosed. Example disclosed methods involve instructing a first data collection device to operate according to a first rule. The example first rule specifies a first operating mode and defining a first event of interest. Example disclosed methods also involve obtaining first data from the first data collection device while operating according to the first rule. Example disclosed methods also involve, in response to determining that the first event of interest has occurred based on the first data, providing a second rule based on the first data to the first data collection device, and providing a third rule to a second data collection device. The example second rule specifies a second operating mode and defines a second event of interest, and the examples third rule specifies a third operating mode.

Abstract: The present invention discloses a ZmWAK-RLK protein related to gray leaf spot resistance, and an encoding gene and application thereof. The present invention sets forth a protein obtained from a maize inbred line Y32, named ZmWAK-RLK, and being the protein shown in sequence 1 of the sequence listing. A nucleic acid molecule for encoding the ZmWAK-RLK protein is likewise considered to be within the scope of protection of the present invention. The present invention likewise sets forth a method for preparing a transgenic plant, comprising the following step: introducing said nucleic acid molecule into a starting plant, thus obtaining a transgenic plant having enhanced resistance to gray leaf spot. The present invention additionally sets forth a plant breeding method, comprising the following step: increasing the content and/or activity of the ZmWAK-RLK protein in a plant of interest, thus increasing the gray leaf spot resistance of the plant of interest.

Abstract: A NVMe™ or NVMe-over-fabrics enabled device with video codec functionality may be seen to overcome scalability problem of known hardware assisted video codec solutions. The device of aspects of the present application may or may not have storage media. A host computer communicates with the device through NVMe™ commands. The device may be in one of many SSD form factors, such as U.2 or AIC. The device may be provided as a component in NVMe-enabled computers or NVMe-over-fabrics-enabled systems.

Abstract: The present disclosure provides a method and system for large-capacity image steganography and recovery based on an invertible neural networks. The method is intended to embed one or more hidden images into a single host image, and recover all the hidden images from a stego image. The method designs an image steganography model that supports bidirectional mapping. The model includes cascaded invertible modules containing a host branch and a hidden branch. A hidden image is embedded into a host image through forward mapping to form a stego image, and the host image and the hidden image are separated and recovered from the single stego image through reverse mapping.

Abstract: A method has the steps of obtaining a set of training samples from one or more domains, using the set of training samples to query a plurality of artificial-intelligence (AI) models, combining the outputs of the queried AI models, and adapting a target AI model via knowledge distillation using the combined outputs.

Abstract: A NVMe™ or NVMe-over-fabrics enabled device with video codec functionality may be seen to overcome scalability problem of known hardware assisted video codec solutions. The device of aspects of the present application may or may not have storage media. A host computer communicates with the device through NVMe™ commands. The device may be in one of many SSD form factors, such as U.2 or AIC. The device may be provided as a component in NVMe-enabled computers or NVMe-over-fabrics-enabled systems.

Abstract: The present disclosure provides a method and system for large-capacity image steganography and recovery based on an invertible neural networks. The method is intended to embed one or more hidden images into a single host image, and recover all the hidden images from a stego image. The method designs an image steganography model that supports bidirectional mapping. The model includes cascaded invertible modules containing a host branch and a hidden branch. A hidden image is embedded into a host image through forward mapping to form a stego image, and the host image and the hidden image are separated and recovered from the single stego image through reverse mapping.

Abstract: A system and method for managing sensors including determining health operation states of the sensors correlative with sensor accuracy, classifying the sensors by their respective health operation state, and teaming two sensors each having a health operation state that is intermediate to give a team having a health operation state that is healthy. The sampling frequency of the sensors to determine sensor accuracy may be dynamic.

Abstract: Methods and apparatus to adaptively manage data collection devices in distributed computing systems are disclosed. Example disclosed methods involve instructing a first data collection device to operate according to a first rule. The example first rule specifies a first operating mode and defining a first event of interest. Example disclosed methods also involve obtaining first data from the first data collection device while operating according to the first rule. Example disclosed methods also involve, in response to determining that the first event of interest has occurred based on the first data, providing a second rule based on the first data to the first data collection device, and providing a third rule to a second data collection device. The example second rule specifies a second operating mode and defines a second event of interest, and the examples third rule specifies a third operating mode.

Abstract: A system and method for managing sensors including determining health operation states of the sensors correlative with sensor accuracy, classifying the sensors by their respective health operation state, and teaming two sensors each having a health operation state that is intermediate to give a team having a health operation state that is healthy. The sampling frequency of the sensors to determine sensor accuracy may be dynamic.

Abstract: Methods and apparatus to adaptively manage data collection devices in distributed computing systems are disclosed. Example disclosed methods involve instructing a first data collection device to operate according to a first rule. The example first rule specifies a first operating mode and defining a first event of interest. Example disclosed methods also involve obtaining first data from the first data collection device while operating according to the first rule. Example disclosed methods also involve, in response to determining that the first event of interest has occurred based on the first data, providing a second rule based on the first data to the first data collection device, and providing a third rule to a second data collection device. The example second rule specifies a second operating mode and defines a second event of interest, and the examples third rule specifies a third operating mode.

Abstract: A NVMe™ or NVMe-over-fabrics enabled device with video codec functionality may be seen to overcome scalability problem of known hardware assisted video codec solutions. The device of aspects of the present application may or may not have storage media. A host computer communicates with the device through NVMe™ commands. The device may be in one of many SSD form factors, such as U.2 or AIC. The device may be provided as a component in NVMe-enabled computers or NVMe-over-fabrics-enabled systems.

Abstract: A NVMe™ or NVMe-over-fabrics enabled device with video codec functionality may be seen to overcome scalability problem of known hardware assisted video codec solutions. The device of aspects of the present application may or may not have storage media. A host computer communicates with the device through NVMe™ commands. The device may be in one of many SSD form factors, such as U.2 or AIC. The device may be provided as a component in NVMe-enabled computers or NVMe-over-fabrics-enabled systems.

Abstract: A system and method for managing sensors including determining health operation states of the sensors correlative with sensor accuracy, classifying the sensors by their respective health operation state, and teaming two sensors each having a health operation state that is intermediate to give a team having a health operation state that is healthy. The sampling frequency of the sensors to determine sensor accuracy may be dynamic.

Abstract: The present invention discloses a ZmWAK-RLK protein related to gray leaf spot resistance, and an encoding gene and application thereof. The present invention sets forth a protein obtained from a maize inbred line Y32, named ZmWAK-RLK, and being the protein shown in sequence 1 of the sequence listing. A nucleic acid molecule for encoding the ZmWAK-RLK protein is likewise considered to be within the scope of protection of the present invention. The present invention likewise sets forth a method for preparing a transgenic plant, comprising the following step: introducing said nucleic acid molecule into a starting plant, thus obtaining a transgenic plant having enhanced resistance to gray leaf spot. The present invention additionally sets forth a plant breeding method, comprising the following step: increasing the content and/or activity of the ZmWAK-RLK protein in a plant of interest, thus increasing the gray leaf spot resistance of the plant of interest.