Abstract: The GmLMM1 gene, which is involved in the regulation of PTI immune responses, Phytophthora resistance, bacterial blight of soybean disease, soybean halo disease, etc., is cloned in soybeans. The PTI immune response and pathogen resistance of plants can be negatively regulated via the GmLMM1 gene. By reducing the expression of GmLMM1, the PTI immune response of plants can be effectively enhanced, and the pathogen resistance of plants can be increased. Cloning and functional discovery of the GmLMM1 gene provide important foundations and theoretical support for research on the related mechanisms of soybean disease resistance and provide valuable genetic resources for advancing the research and application of plant defense systems. Additionally, cloning and functional delivery of the GmLMM1 gene allows for breeding new soybean varieties with high disease resistance.

Abstract: In general, techniques are described that enable voice activation for computing devices. A computing device configured to support an audible interface that comprises a memory and one or more processors may be configured to perform the techniques. The memory may store a first audio signal representative of an environment external to a user associated with the computing device and a second audio signal sensed by a microphone coupled to a housing of the computing device. The one or more processors may verify, based on the first audio signal and the second audio signal, that the user activated the audible interface of the computing device, and obtain, based on the verification, additional audio signals representative of one or more audible commands.

Abstract: A wearable device may include a processor configured to detect a self-voice signal, based on one or more transducers. The processor may be configured to separate the self-voice signal from a background signal in an external audio signal based on using a multi-microphone speech generative network. The processor may also be configured to apply a first filter to an external audio signal, detected by at least one external microphone on the wearable device, during a listen through operation based on an activation of the audio zoom feature to generate a first listen-through signal that includes the external audio signal. The processor may be configured to produce an output audio signal that is based on at least the first listen-through signal that includes the external signal, and is based on the detected self-voice signal.

Abstract: An application of CRMP2 and/or anti-CRMP2 antibodies as markers of a nervous system autoimmune disease, and an application of a reagent for detecting anti-CRMP2 antibodies in preparing a reagent for the detection. diagnosis, treatment or prognosis evaluation of a nervous system autoimmune disease. CRMP2 is a new encephalitis/encephalomyelitis-related autoantibody targeted molecular marker, which can be used for clear diagnosis of the disease and provide the basis for an immunotherapy solution. In addition, the treatment effect can be monitored and the prognosis and recurrence can be determined by detecting a titer change in CRMP2 autoantibodies.

Abstract: A method for aging and storage of Jiang-flavor raw liquor involves “growing, nourishing and storing.” The Jiang-flavor new liquors of different rounds are subjected to outdoor storage in jars for not more than 1 year, then the Jiang-flavor raw liquors of different rounds having experienced the outdoor storage in jars for not more than 1 year are blended and put into stainless steel tank for blending and aging for a period of 1 to 2 years, and finally the Jiang-flavor raw liquor having experiencing the blending and ageing in the stainless steel tank for 1 to 2 years undergoes indoor storage in jars for 2 to 10 years. The method combines different storage containers with different storage years, improving the aging and storage effect and the quality of the Jiang-flavor raw liquor in a targeted manner.

Abstract: A wearable device may include a processor configured to detect a self-voice signal, based on one or more transducers. The processor may be configured to separate the self-voice signal from a background signal in an external audio signal based on using a multi-microphone speech generative network. The processor may also be configured to apply a first filter to an external audio signal, detected by at least one external microphone on the wearable device, during a listen through operation based on an activation of the audio zoom feature to generate a first listen-through signal that includes the external audio signal. The processor may be configured to produce an output audio signal that is based on at least the first listen-through signal that includes the external signal, and is based on the detected self-voice signal.

Abstract: A device includes one or more processors configured to perform signal processing including a linear transformation and a non-linear transformation of an input signal to generate a reference target signal. The reference target signal has a linear component associated with the linear transformation and a non-linear component associated with the non-linear transformation. The one or more processors are also configured to perform linear filtering of the input signal by controlling adaptation of the linear filtering to generate an output signal that substantially matches the linear component of the reference target signal.

Abstract: A wearable device may include a processor configured to perform active noise cancelation (ANC) applied to an input audio signal received by at least one microphone, and detect a self-voice signal, based on one or more transducers. The processor may also be configured to apply a first filter to an external audio signal, detected by at least one external microphone on the wearable device, during a listen through operation based on an activation of the audio zoom feature to generate a first listen-through signal that includes the external audio signal. The processor may also be configured to after the activation of the audio zoom feature terminate a second filter that provides low frequency compensation. The processor may be configured to produce an output audio signal that is based on at least the first listen-through signal that includes the external signal, and is based on the detected self-voice signal.

Abstract: A wearable device may include a processor configured to perform active noise cancelation (ANC) applied to an input audio signal received by at least one microphone, and detect a self-voice signal, based on one or more transducers. The processor may also be configured to apply a first filter to an external audio signal, detected by at least one external microphone on the wearable device, during a listen through operation based on an activation of the audio zoom feature to generate a first listen-through signal that includes the external audio signal. The processor may also be configured to after the activation of the audio zoom feature terminate a second filter that provides low frequency compensation. The processor may be configured to produce an output audio signal that is based on at least the first listen-through signal that includes the external signal, and is based on the detected self-voice signal.

Abstract: Methods, systems, and devices for signal processing are described. Generally, as provided for by the described techniques, a wearable device may receive an input audio signal (e.g., including both an external signal and a self-voice signal). The wearable device may detect the self-voice signal in the input audio signal based on a self-voice activity detection (SVAD) procedure, and may implement the described techniques based thereon. The wearable device may perform beamforming operations or other separation procedures to isolate the external signal and the self-voice signal from the input audio signal. The wearable device may apply a first filter to the external signal, and a second filter to the self-voice signal. The wearable device may then mix the filtered signals, and generate an output signal that sounds natural to the user.

Abstract: Aspects of the subject disclosure may include, for example, monitoring communication traffic in a communication network including a plurality of cell sites and a plurality of collector circuits over a time period, storing information about the communication traffic and information about available network resources in a database and predicting where additional capacity will be needed in the communication network at a future time, wherein the predicting is based on the information about the communication traffic. The subject disclosure may further include improving assignment of additional capacity in the communication network between the plurality of cell sites and the plurality of collector circuits based on the information about available network resources and communicating with network switches to assign the additional capacity within the communication network and initiate communication in the communication network. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, monitoring communication traffic in a communication network including a plurality of cell sites and a plurality of collector circuits over a time period, storing information about the communication traffic and information about available network resources in a database and predicting where additional capacity will be needed in the communication network at a future time, wherein the predicting is based on the information about the communication traffic. The subject disclosure may further include improving assignment of additional capacity in the communication network between the plurality of cell sites and the plurality of collector circuits based on the information about available network resources and communicating with network switches to assign the additional capacity within the communication network and initiate communication in the communication network. Other embodiments are disclosed.

Abstract: The GmLMM1 gene, which is involved in the regulation of PTI immune responses, Phytophthora resistance, bacterial blight of soybean disease, soybean halo disease, etc., is cloned in soybeans. The PTI immune response and pathogen resistance of plants can be negatively regulated via the GmLMM1 gene. By reducing the expression of GmLMM1, the PTI immune response of plants can be effectively enhanced, and the pathogen resistance of plants can be increased. Cloning and functional discovery of the GmLMM1 gene provide important foundations and theoretical support for research on the related mechanisms of soybean disease resistance and provide valuable genetic resources for advancing the research and application of plant defense systems. Additionally, cloning and functional delivery of the GmLMM1 gene allows for breeding new soybean varieties with high disease resistance.

Abstract: Aspects of the subject disclosure may include, for example, monitoring communication traffic in a communication network including a plurality of cell sites and a plurality of collector circuits over a time period, storing information about the communication traffic and information about available network resources in a database and predicting where additional capacity will be needed in the communication network at a future time, wherein the predicting is based on the information about the communication traffic. The subject disclosure may further include improving assignment of additional capacity in the communication network between the plurality of cell sites and the plurality of collector circuits based on the information about available network resources and communicating with network switches to assign the additional capacity within the communication network and initiate communication in the communication network. Other embodiments are disclosed.

Abstract: A machine automation system for controlling and operating an automated machine. The system includes a controller and sensor bus including a central processing core and a multi-medium transmission intranet for implementing a dynamic burst to broadcast transmission scheme where messages are burst from nodes to the central processing core and broadcast from the central processing core to all of the nodes.

Abstract: A machine automation system for controlling and operating an automated machine. The system includes a controller and sensor bus including a central processing core and a multi-medium transmission intranet for implementing a dynamic burst to broadcast transmission scheme where messages are burst from nodes to the central processing core and broadcast from the central processing core to all of the nodes.

Abstract: A machine automation system for controlling and operating an automated machine. The system includes a controller and sensor bus including a central processing core and a multi-medium transmission intranet for implementing a dynamic burst to broadcast transmission scheme where messages are burst from nodes to the central processing core and broadcast from the central processing core to all of the nodes.

Abstract: An apparatus includes a processor configured to receive one or more media signals associated with a scene. The processor is also configured to identify a spatial location in the scene for each source of the one or more media signals. The processor is further configured to identify audio content for each media signal of the one or more media signals. The processor is also configured to determine one or more candidate spatial locations in the scene based on the identified spatial locations. The processor is further configured to generate audio to playback as virtual sounds that originate from the one or more candidate spatial locations.