Abstract: In an example method, a first device determines a first Zadoff-Chu sequence having a first root value, and a second Zadoff-Chu sequence having a second root value, where the first second root value is an inverse modulus of the first root value. Further, the first device generates a wireless signal including (i) a first preamble generated based, at least in part, on the first Zadoff-Chu sequence, (ii) a second preamble generated based, at least in part, on the second Zadoff-Chu sequence, and (iii) a payload. Further, the first device transmits the wireless signal from the first device to a second device.

Abstract: The present disclosure discloses a method, apparatus, device, and storage medium for training a model, relates to the technical fields of knowledge graph, natural language processing, and deep learning. The method may include: acquiring a first annotation data set, the first annotation data set including sample data and a annotation classification result corresponding to the sample data; training a preset initial classification model based on the first annotation data set to obtain an intermediate model; performing prediction on the sample data in the first annotation data set using the intermediate model to obtain a prediction classification result corresponding to the sample data; generating a second annotation data set based on the sample data, the corresponding annotation classification result, and the corresponding prediction classification result; and training the intermediate model based on the second annotation data set to obtain a classification model.

Abstract: The present disclosure provides compounds of Formula I?, compositions comprising the compound of Formula I?, and methods of using the same, in treating diseases, disorders, or conditions mediated by the inhibition of certain kinases, such as hematopoietic progenitor kinase 1 (HPK1) and/or Fms related receptor tyrosine kinases (FLTs), such as FLT3.

Abstract: Provided compounds of Formula I and I?, pharmaceutical compositions comprising the compounds, and methods of using the same, in treating, for example, the diseases, disorders, or conditions mediated by the degradation of a protein kinase, such as Hematopoietic progenitor kinase 1 (HPK1).

Abstract: A text recognition method includes scaling a to-be-recognized image based on a first scale ratio, determining first coordinate information corresponding to a text line area in the scaled to-be-recognized image, determining, based on the first scale ratio, second coordinate information corresponding to the first coordinate information, where the second coordinate information is coordinate information of the text line area in the to-be-recognized image, performing character recognition on text line images corresponding to the second coordinate information by using a recognition model, and determining text line content corresponding to the text line images, where the to-be-recognized image includes the text line images.

Abstract: A network system dynamically determines a route, including start and end points, for vehicles in a transportation network. The transportation network receives a service request from a user of the transportation network including an origin location for the trip and a destination location for the trip. The transportation network then generates a waypoint plan for one or more vehicles, which includes the requested origin and destination in addition to any previously requested origins and destinations included in the vehicles current route. The network system then determines a directionality for each of the waypoints in the waypoint plan and retrieves candidate start and end points that have an associated directionality within a threshold angle of the directionality of each waypoint and are proximate to the waypoint. The network system evaluates each combination of retrieved candidate points to select a route for the vehicle.

Abstract: In an example method, a first device determines a first Zadoff-Chu sequence having a first root value, and a second Zadoff-Chu sequence having a second root value, where the second root value is an inverse modulus of the first root value. Further, the first device generates a wireless signal including (i) a first preamble generated based, at least in part, on the first Zadoff-Chu sequence, (ii) a second preamble generated based, at least in part, on the second Zadoff-Chu sequence, and (iii) a payload. Further, the first device transmits the wireless signal from the first device to a second device.

Abstract: The present invention provides methods and kits for determining which microRNAs bind to a target mRNA where the methods comprise the steps of (a) creating a bait sequence from the target mRNA, where the bait sequence comprises a label that binds to a binding agent; (b) adding a mixture of microRNAs to the bait sequence; (c) separating the microRNAs that bind to the bait sequence from those microRNAs that do not bind; and (d) identifying the microRNAs that bind to the bait sequence, wherein the microRNAs identified are those that bind to the target mRNA.

Abstract: Selective gas-reducing methods for making shape-defined metal-based nanoparticles. By avoiding the use of solid or liquid reducing reagents, the gas reducing reagent can be used to make shape well-defined metal- and metal alloy-based nanoparticles without producing contaminates in solution. Therefore, the post-synthesis process including surface treatment become simple or unnecessary. Weak capping reagents can be used for preventing nanoparticles from aggregation, which makes the further removing the capping reagents easier. The selective gas-reducing technique represents a new concept for shape control of nanoparticles, which is based on the concepts of tuning the reducing rate of the different facets. This technique can be used to produce morphology-controlled nanoparticles from nanometer- to submicron- to micron-sized scale. The Pt-based nanoparticles show improved catalytic properties (e.g., activity and durability).

Abstract: The present invention provides methods and kits for determining which microRNAs bind to a target mRNA where the methods comprise the steps of (a) creating a bait sequence from the target mRNA, where the bait sequence comprises a label that binds to a binding agent; (b) adding a mixture of microRNAs to the bait sequence; (c) separating the microRNAs that bind to the bait sequence from those microRNAs that do not bind; and (d) identifying the microRNAs that bind to the bait sequence, wherein the microRNAs identified are those that bind to the target mRNA.

Abstract: A permuted sequences combination uses a frame structure in which two sync words, each comprising M complex symbols, are appended at the frame start. One benefit is the reduction of the large variance of the timing estimation error in the conventional correlation method. In at least one embodiment, the first sync word, {right arrow over (s)}1, is a predetermined constant amplitude zero autocorrelation (CAZAC) sequence. The second sync word, {right arrow over (s)}2, is a permutation of the first such that the combination of the two received sync signal vectors perform sliding window processing where the peak occurs at the correct frame start. The permuted sequences combination can be used in both AWGN channel and multi-path environments.

Abstract: A permuted sequences combination uses a frame structure in which two sync words, each comprising M complex symbols, are appended at the frame start. One benefit is the reduction of the large variance of the timing estimation error in the conventional correlation method. In at least one embodiment, the first sync word, s1, is a predetermined constant amplitude zero autocorrelation (CAZAC) sequence. The second sync word, s2, is a permutation of the first such that the combination of the two received sync signal vectors perform sliding window processing where the peak occurs at the correct frame start. The permuted sequences combination can be used in both AWGN channel and multi-path environments.