Abstract: In some implementations, a first ultra-wideband (UWB) device may determine a respective time offset for each scrambled timestamp sequence (STS) in a series of STS used for ranging in a UWB ranging session between the first UWB device and the second UWB device, wherein the respective time offset for each STS in the series of STS is determined in accordance with time offset information shared between the first UWB device and the second UWB device. The first UWB device may transmit the series of STS via UWB radio frequency (RF) signals during the UWB ranging session, wherein each STS in the series of STS is transmitted with the respective time offset.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: The invention relates to salts of Compound 1, crystalline forms thereof, methods of their preparation, pharmaceutical compositions thereof and methods of their use

Abstract: A multi-label ranking method includes receiving, at a processor and from a first set of artificial neural networks (ANNs), multiple signals representing a first set of ANN output pairs for a first label. A signal representing a second set of ANN output pairs for a second label different from the first label is received at the processor from a second set of ANNs different from the first set of ANNs, substantially concurrently with the first set of ANN output pairs. A first activation function is solved based on the first set of ANN output pairs, and a second activation function is solved based on the second set of ANN output pairs. Loss values are calculated based on the solved activations, and a mask is generated based on at least one ground truth label. A signal, including a representation of the mask, is sent from the processor to each of the sets of ANNs.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: Examples can include (1) identifying, on a network, a source node and a destination node, the source node including at least one source node virtual machine (“VM”) to be replicated as a destination node VM on the destination node, (2) performing a full synchronization by copying disks used by the source node VM in a current operational state to the destination node VM, (3) scheduling start times for multiple update synchronizations of changed data between the source node VM and the destination node VM, the start times being scheduled at different time intervals, wherein a first time interval is greater than a second time interval, and (4) performing, at a switch-over time, a shutdown of the source node VM and transmitting data changes that are pending on the disk to the destination node. Various corresponding systems, methods, and non-transitory computer-readable media are also disclosed.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more maps are obtained by an agricultural work machine. The one or more maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: The present invention is directed to, in part, fused heteroaryl compounds and compositions useful for preventing and/or treating a disease or condition relating to aberrant function of a voltage-gated, sodium ion channel, for example, abnormal late/persistent sodium current. Methods of treating a disease or condition relating to aberrant function of a sodium ion channel including neurological disorders (e.g., Dravet syndrome, epilepsy), pain, and neuromuscular disorders are also provided herein.

Abstract: An agricultural harvesting system includes a control system that is configured to obtain a map that maps values of a speed characteristic of an agricultural harvester to different geographic locations in a worksite. The control system is further configured to generate a control signal to control a receiving machine based on the map.

Abstract: An agricultural harvesting system includes a harvesting logistics module that is configured to receive a map that maps values of a crop characteristic to different geographic locations in a field. The harvesting logistics module further configured to identify a crop characteristic threshold and to identify a mixture of crop material based on the map and based on the crop characteristic threshold. The harvesting logistics module configured to generate a route for a mobile machine, such as a receiving machine or a harvester, based on the identified mixture.

Abstract: An agricultural harvesting system obtains a yield map that maps yield values to different geographic locations in a worksite and a speed map that maps agricultural harvester speed values to different geographic locations in the worksite. The agricultural harvesting system identifies a geographic location in the worksite at which the agricultural harvester will be full, at least to a threshold level, based on the yield map; identifies a geographic location in the worksite at which a material transfer operation is to start based on the geographic location at which the agricultural harvester will be full, at least to the threshold level; and identifies a time at which the agricultural harvester will arrive at the material transfer location, based on the speed map. The agricultural harvesting system can control one or more of the agricultural harvester and a receiving machine.

Abstract: One or more maps are obtained by an agricultural system. The one or more maps map characteristic values at different geographic locations in a worksite. The agricultural system identifies one or more operational constraints. The agricultural system generates a control output to control operation of a mobile machine operating in an agricultural harvesting operation based on the one or more operational constraints.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: Methods, systems, and computer storage media for providing a multi-attribute cluster-identifier that supports identifying malicious activity in computing environments. An instance of an activity having an attribute set can be assessed. The attribute set of the instance of the activity is analyzed to determine whether the instance of the activity is a malicious activity. The attribute set of the instance of the activity is compared to a plurality of multi-attribute cluster-identifiers of previous instances of the activity, such that, a determination that the instance of the activity is a malicious activity is made when the attribute set of the instance of the activity corresponds to an identified multi-attribute cluster-identifier. The identified multi-attribute cluster-identifier has a risk score and an attribute set that indicate a likelihood that the instance of the activity is a malicious activity. A visualization that identifies the instance of the activity as a malicious activity is generated.