Abstract: Systems and methods for deploying emergency roadside signaling devices are disclosed. In one aspect, a control system for an object placing device of an autonomous vehicle includes a processor, and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to: receive a signal comprising instructions to activate the object placing device; and provide instructions to the object placing device to place a plurality of signaling devices in accordance with predetermined criteria.

Abstract: The disclosure provides compositions and methods related to activating alpha-kinase 1 (ALPK1) for modulating an immune response and treating or preventing cancer, infection, inflammation and related diseases and disorders as well as potentiating an immune response to a target antigen. The disclosure also provides heterocyclic compounds of formula (I) as agonists of alpha protein kinase 1 (ALPK1) and their use in activating ALPK1, modulating an immune response and treating diseases such as cancer, wherein A1, A2, L1, L2, L3, Z1, Z2, W1, W2, R1, R2, R3, R4, R5, R6 and R7 are defined herein.

Abstract: Provided are compounds of Formula (I) or (II) and related compositions and methods for their use as inhibitors of alpha-kinase 1 (ALPK1).

Abstract: Systems and methods for deploying emergency roadside signaling devices are disclosed. In one aspect, system for an autonomous vehicle includes one or more signaling devices configured to visually notify other vehicles when placed on or near a roadway, and an object placing device configured to place the one or more signaling devices. The system further includes a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to: determine that the autonomous vehicle has experienced a malfunction, and provide instructions to the object placing device to place the one or more signaling devices on or near the roadway.

Abstract: Provided are compounds of Formula I, compositions and methods for their use as inhibitors of alpha-kinase 1 (ALPK1).

Abstract: Systems and methods for deploying emergency roadside signaling devices are disclosed. In one aspect, a control system for an object placing device of an autonomous vehicle includes a processor, and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to: receive a signal comprising instructions to activate the object placing device; and provide instructions to the object placing device to place a plurality of signaling devices in accordance with predetermined criteria.

Abstract: Described herein are compositions and methods of forming a dielectric film comprising silicon and carbon onto at least a surface of a substrate, the method comprising introducing into a reactor at least one silacycloalkane precursor selected from the group consisting of compounds represented by the structure of Formula IA and compounds represented by the structure of Formula IB: as defined herein.

Abstract: A glass substrate comprises: a first surface with surface features having an average width, an average height, a ratio of the average height to the average width of from about 0.04 to about 0.24, and the first surface has a haze value of 3% to 40%. The glass substrate can be transparent to electromagnetic radiation in the visible spectrum. The glass substrate can have a composition of: 61-75 mol. % SiO2; 7-15 mol. % Al2O3; 0-12 mol. % B2O3; 9-21 mol. % Na2O; 0-4 mol. % K2O; 0-7 mol. % MgO; and 0-3 mol. % CaO. The first surface can have an average surface roughness Ra of from 10 nm to 1,000 nm. The first surface can have an average characteristic largest feature size of from 200 nm to 50 ?m. The ratio of the average height to the average width can be from 0.06 to about 0.08.

Abstract: In one aspect, a method of speech signal processing using artificial intelligence, includes receiving, with at least one processor, a digital speech signal, converting, with the at least one processor, the digital speech signal to text, performing self-alignment pre-training of an encoder on entities and their synonyms, label attention training the pretrained encoder by aligning label-text joint representation to that of label synonym-text joint representations, and identifying, with the trained encoder, entities in a span in the text.

Abstract: The disclosure provides compositions and methods related to activating alpha-kinase 1 (ALPK1) for modulating an immune response and treating or preventing cancer, infection, inflammation and related diseases and disorders as well as potentiating an immune response to a target antigen. The disclosure also provides heterocyclic compounds of formula (I) as agonists of alpha protein kinase 1 (ALPK1) and their use in activating ALPK1, modulating an immune response and treating diseases such as cancer, wherein A1, A2, L1, L2, L3, Z1, Z2, W1, W2, R1, R2, R3, R4, R5, R6 and R7 are defined herein.

Abstract: There is provided a non-transitory storage medium and a system for generating an abstractive summary of a document using an abstractive machine learning algorithm (MLA). A document including a plurality of text sequences is received. An extractive summary of the document is generated, the extractive summary including a set of summary text sequences which is a subset of the plurality of text sequences. The abstractive MLA generates, based on the set of summary text sequences and at least a portion of the plurality of text sequences, an abstractive summary of the document including a set of abstractive text sequences, at least one abstractive text sequence not being included in the plurality of text sequences.

Abstract: The disclosure provides compositions and methods related to activating alpha-kinase 1 (ALPK1) for modulating an immune response and treating or preventing cancer, infection, inflammation and related diseases and disorders as well as potentiating an immune response to a target antigen. The disclosure also provides heterocyclic compounds of formula (I) as agonists of alpha protein kinase 1 (ALPK1) and their use in activating ALPK1, modulating an immune response and treating diseases such as cancer, wherein A1, A2, L1, L2, L3, Z1, Z2, W1, W2, R1, R2, R3, R4, R5, R6 and R7 are defined herein.

Abstract: There is provided a method and a system for training an extractive machine learning algorithm (MLA) to generate extractive summaries of text documents. Reference documents and associated extractive summaries are received. The extractive MLA is then trained to generate an extractive summary, where the training includes, for a given reference document, encoding, using a sentence encoder, a plurality of reference sentences to obtain an associated plurality of sentence representations, encoding, using a document encoder, the associated plurality of sentence representations to obtain a document representation, extracting, using a decoder and based on the associated plurality of sentence representations and the document representation, a first reference sentence of the plurality of reference sentences to obtain a first extracted sentence. A given parameter is updated based on the first extracted sentence and the given reference document summary.

Abstract: There is provided a method and system for training and using a transformer language model (TLM) part of a recommendation engine. Natural language discussions about a category of items are received, the discussions comprising tags each indicative of a respective item belonging to the category of item. Information is received for each respective item. Based on the natural language discussions, the tags and the information about the respective item, the TLM is trained to: upon receipt of a user input, determine whether a given item should be recommended based on the user input, if the given item should be recommended, retrieving given information about the given item and generating a response to the user input, the response to the user input comprising the given item to be recommended and the given information, and output the response to the user input. The response is generated in natural language format.

Abstract: There is provided a method and a system for training an extractive machine learning algorithm (MLA) to generate extractive summaries of text documents. Reference documents and associated extractive summaries are received. The extractive MLA is then trained to generate an extractive summary, where the training includes, for a given reference document, encoding, using a sentence encoder, a plurality of reference sentences to obtain an associated plurality of sentence representations, encoding, using a document encoder, the associated plurality of sentence representations to obtain a document representation, extracting, using a decoder and based on the associated plurality of sentence representations and the document representation, a first reference sentence of the plurality of reference sentences to obtain a first extracted sentence. A given parameter is updated based on the first extracted sentence and the given reference document summary.

Abstract: A method and a system for generating an abstractive summary of a document using an abstractive machine learning algorithm (MLA) and a method and a system for training the abstractive MLA. A document including a plurality of text sequences is received. An extractive summary of the document is generated, the extractive summary including a set of summary text sequences which is a subset of the plurality of text sequences. The abstractive MLA generates, based on the set of summary text sequences and at least a portion of the plurality of text sequences, an abstractive summary of the document including a set of abstractive text sequences, at least one abstractive text sequence not being included in the plurality of text sequences. In some aspects, the extractive summary is generated by an extractive MLA having been trained to generate extractive summaries.

Abstract: The disclosure provides compositions and methods related to activating alpha-kinase 1 (ALPK1) for modulating an immune response and treating or preventing cancer, infection, inflammation and related diseases and disorders as well as potentiating an immune response to a target antigen. The disclosure also provides heterocyclic compounds of formula (I) as agonists of alpha protein kinase 1 (ALPK1) and their use in activating ALPK1, modulating an immune response and treating diseases such as cancer, wherein A1, A2, L1, L2, L3, Z1, Z2, W1, W2, R1, R2, R3, R4, R5, R6 and R7 are defined herein.

Abstract: The disclosure provides compositions and methods related to activating alpha-kinase 1 (ALPK1) for modulating an immune response and treating or preventing cancer, infection, inflammation and related diseases and disorders as well as potentiating an immune response to a target antigen. The disclosure also provides heterocyclic compounds of formula (I) as agonists of alpha protein kinase 1 (ALPK1) and their use in activating ALPK1, modulating an immune response and treating diseases such as cancer, wherein A1, A2, L1, L2, L3, Z1, Z2, W1, W2, R1, R2, R3, R4, R5, R6 and R7 are defined herein.

Abstract: The disclosure provides compositions and methods related to activating alpha-kinase 1 (ALPK1) for modulating an immune response and treating or preventing cancer, infection, inflammation and related diseases and disorders as well as potentiating an immune response to a target antigen. The disclosure also provides heterocyclic compounds of formula (I) as agonists of alpha protein kinase 1 (ALPK1) and their use in activating ALPK1, modulating an immune response and treating diseases such as cancer, wherein A1, A2, L1, L2, L3, Z1, Z2, W1, W2, R1, R2, R3, R4, R5, R6 and R7 are defined herein.

Abstract: A method and a system for generating an abstractive summary of a document using an abstractive machine learning algorithm (MLA) and a method and a system for training the abstractive MLA. A document including a plurality of text sequences is received. An extractive summary of the document is generated, the extractive summary including a set of summary text sequences which is a subset of the plurality of text sequences. The abstractive MLA generates, based on the set of summary text sequences and at least a portion of the plurality of text sequences, an abstractive summary of the document including a set of abstractive text sequences, at least one abstractive text sequence not being included in the plurality of text sequences. In some aspects, the extractive summary is generated by an extractive MLA having been trained to generate extractive summaries.