Abstract: A positive electrode slurry contains polyether polyol, where the polyether polyol has the following constitutional formula: where R1, R2, R3, R4, R5, R6, R7, R8, R9, R10, and Y are as defined in the specification.

Abstract: A method, an apparatus, a device, a storage medium and a program product of performing a text matching are provided, which relate to a field of a computer technology, and in particular to natural language processing and deep learning technologies. The method includes: determining a word set and a plurality of semantic units from a text set, the word set is associated with a first predetermined attribute, and the text set contains a plurality of first texts indicating an object information and a plurality of second texts indicating an object demand information; generating a graph; and generating a final feature representation associated with the text set and the word set based on the graph and a graph convolution model, so as to perform the text matching.

Abstract: Methods and apparatuses for feature-driven communications are described. A set of features describing an observed subject is transmitted by a transmitting electronic device (ED) to a base station (BS). The BS translates the received features to another set of transmission features to be transmitted to a receiving ED. The receiving ED recovers information about the subject from the features received from the BS.

Abstract: Embodiments described herein may be useful in the detection of analytes. The systems and methods may allow for a relatively simple and rapid way for detecting analytes such as chemical and/or biological analytes and may be useful in numerous applications including sensing, food manufacturing, medical diagnostics, performance materials, dynamic lenses, water monitoring, environmental monitoring, detection of proteins, detection of DNA, among other applications. For example, the systems and methods described herein may be used for determining the presence of a contaminant such as bacteria (e.g., detecting pathogenic bacteria in food and water samples which helps to prevent widespread infection, illness, and even death). Advantageously, the systems and methods described herein may not have the drawbacks in current detection technologies including, for example, relatively high costs, long enrichment steps and analysis times, and/or the need for extensive user training.

Abstract: Embodiments described herein may be useful in the detection of analytes. The systems and methods may allow for a relatively simple and rapid way for detecting analytes such as chemical and/or biological analytes and may be useful in numerous applications including sensing, food manufacturing, medical diagnostics, performance materials, dynamic lenses, water monitoring, environmental monitoring, detection of proteins, detection of DNA, among other applications. For example, the systems and methods described herein may be used for determining the presence of a contaminant such as bacteria (e.g., detecting pathogenic bacteria in food and water samples which helps to prevent widespread infection, illness, and even death). Advantageously, the systems and methods described herein may not have the drawbacks in current detection technologies including, for example, relatively high costs, long enrichment steps and analysis times, and/or the need for extensive user training.

Abstract: Methods and apparatuses for feature-driven communications are described. A set of features describing an observed subject is transmitted by a transmitting electronic device (ED) to a base station (BS). The BS translates the received features to another set of transmission features to be transmitted to a receiving ED. The receiving ED recovers information about the subject from the features received from the BS.

Abstract: Methods and apparatuses for feature-driven machine-to-machine communications are described. At a feature encoder, features are extracted from sensed raw information, to generate features that compress the raw information by a compression ratio. The feature encoder implements a probabilistic encoder to generate the features, each feature providing information about a respective probability distribution that each represents one or more aspects of the subject. The probabilistic encoder is designed to provide a compression ratio that satisfies a predetermined physical channel capacity limit for a transmission channel. The features are transmitted over the transmission channel.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes polar encoding, with an encoder of the device, information bits and at least one parity bit using the polar code to obtain encoded data, and transmitting the encoded data to another device. The polar code comprises a plurality of sub-channels. The at least one parity bit being placed in at least one of the plurality of sub-channels. The at least one sub-channel is selected from the plurality of sub-channels based on a weight parameter.

Abstract: Embodiments described herein may be useful in the detection of analytes. The systems and methods may allow for a relatively simple and rapid way for detecting analytes such as chemical and/or biological analytes and may be useful in numerous applications including sensing, food manufacturing, medical diagnostics, performance materials, dynamic lenses, water monitoring, environmental monitoring, detection of proteins, detection of DNA, among other applications.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. The row weight for a sub-channel may be viewed as the number of “ones” in the corresponding row of the Kronecker matrix or as a power of 2 with the exponent (i.e. the hamming weight) being the number of “ones” in the binary representation of the sub-channel index (further described below). In one embodiment, candidate sub-channels that have certain row weight values are reserved for parity bit(s). Thereafter, K information bits may be mapped to the K most reliable remaining sub-channels, and a number of frozen bits (e.g. N?K) may be mapped to the least reliable remaining sub-channels. Parity bits may then mapped to the candidate sub-channels, and parity bit values are determined based on a function of the information bits.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. The row weight for a sub-channel may be viewed as the number of “ones” in the corresponding row of the Kronecker matrix or as a power of 2 with the exponent (i.e. the hamming weight) being the number of “ones” in the binary representation of the sub-channel index (further described below). In one embodiment, candidate sub-channels that have certain row weight values are reserved for parity bit(s). Thereafter, K information bits may be mapped to the K most reliable remaining sub-channels, and a number of frozen bits (e.g. N?K) may be mapped to the least reliable remaining sub-channels. Parity bits may then mapped to the candidate sub-channels, and parity bit values are determined based on a function of the information bits.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes allocating, from a set of sub-channels, one or more sub-channels for one or more parity bits based on row weights for sub-channels in a subset of sub-channels within the set of sub-channels, mapping information bits to remaining sub-channels in the set of sub-channels based on a reliability of the remaining sub-channels without mapping any of the information bits to the one or more sub-channels allocated for the one or more parity bits, polar encoding the information bits and the one or more parity bits based on at least the mapping of the information bits to the remaining sub-channels to obtain encoded bits, and transmitting the encoded bits to another device.

Abstract: Embodiments described herein may be useful in the detection of analytes. The systems and methods may allow for a relatively simple and rapid way for detecting analytes such as chemical and/or biological analytes and may be useful in numerous applications including sensing, food manufacturing, medical diagnostics, performance materials, dynamic lenses, water monitoring, environmental monitoring, detection of proteins, detection of DNA, among other applications. For example, the systems and methods described herein may be used for determining the presence of a contaminant such as bacteria (e.g., detecting pathogenic bacteria in food and water samples which helps to prevent widespread infection, illness, and even death). Advantageously, the systems and methods described herein may not have the drawbacks in current detection technologies including, for example, relatively high costs, long enrichment steps and analysis times, and/or the need for extensive user training.

Abstract: Embodiments are provided for an asynchronous processor with pipelined arithmetic and logic unit. The asynchronous processor includes a non-transitory memory for storing instructions and a plurality of instruction execution units (XUs) arranged in a ring architecture for passing tokens. Each one of the XUs comprises a logic circuit configured to fetch a first instruction from the non-transitory memory, and execute the first instruction. The logic circuit is also configured to fetch a second instruction from the non-transitory memory, and execute the second instruction, regardless whether the one of the XUs holds a token for writing the first instruction. The logic circuit is further configured to write the first instruction to the non-transitory memory after fetching the second instruction.