Abstract: Methods of treating a metabolic disorder in a subject are provided. Aspects of the method include administering an effective amount of an N-lactoyl-amino acid to the subject. Also provided are pharmaceutical formulations including an amount of an N-lactoyl-amino acid effective to treat a metabolic disorder. Any suitable N-lactoyl-amino acid or combination of N-lactoyl-amino acids may be administered in the subject methods.

Abstract: The present disclosure provides diacylglycerol kinase modulating compounds, and pharmaceutical compositions thereof, for treating cancer, including solid tumors, and viral infections, such as HIV or hepatitis B virus infection. The compounds can be used alone or in combination with other agents.

Abstract: Provided herein are compounds (e.g., compounds of Formulae (A-I), (B-I), (C-I)), and pharmaceutically acceptable salts, stereoisomers, tautomers, isotopically labeled derivatives, solvates, hydrates, polymorphs, co-crystals, and prodrugs thereof, pharmaceutical compositions thereof, and kits comprising the same. The compounds provided herein are degraders of GRK2 proteins and are therefore useful for, e.g., treating and/or preventing diseases (e.g., cancer) in a subject, for inhibiting tumor growth in a subject, for inhibiting the activity of GRK2 and/or degrading a GRK2 protein in vitro or in vivo, etc. In certain embodiments, the compounds provided herein are selective for GRK2. Also provided herein are methods and synthetic intermediates useful in the preparation of compounds described herein.

Abstract: Techniques and configurations for data management are described. Features may be extracted from backup data stored in a data management system for a target object, where the backup data may reflect the target object at a point-in-time. An anomaly associated with the target object may be detected based on the features extracted from the backup data. Based on detecting the anomaly, a malware identity associated with the anomaly may be identified based on the features extracted from the backup data. The identified malware identity may be indicated via a user interface.

Abstract: The present invention discloses compounds of Formula (I), or pharmaceutically acceptable salts, thereof: which inhibit the cellular entry of hepatitis B virus (HBV) and/or hepatitis D virus (HDV) or interfere with the function of the life cycle of HBV and/or HDV and are also useful as antiviral agents. The present invention further relates to pharmaceutical compositions comprising the aforementioned compounds for administration to a subject suffering from HBV and/or HDV infection. The invention also relates to methods of treating an HBV and/or HDV infection in a subject by administering a pharmaceutical composition comprising the compounds of the present invention.

Abstract: A catalyst structure includes: (1) a substrate; (2) a catalyst layer on the substrate; and (3) an adhesion layer disposed between the substrate and the catalyst layer. In some implementations, an average thickness of the adhesion layer is about 1 nm or less. In some implementations, a material of the catalyst layer at least partially extends into a region of the adhesion layer. In some implementations, the catalyst layer is characterized by a lattice strain imparted by the adhesion layer.

Abstract: Methods and apparatus for predicting an association between input data in a first modality and data in a second modality using a statistical model trained to represent interactions between data having a plurality of modalities including the first modality and the second modality, the statistical model comprising a plurality of encoders and decoders, each of which is trained to process data for one of the plurality of modalities, and a joint-modality representation coupling the plurality of encoders and decoders. The method comprises selecting, based on the first modality and the second modality, an encoder/decoder pair or a pair of encoders, from among the plurality of encoders and decoders, and processing the input data with the joint-modality representation and the selected encoder/decoder pair or pair of encoders to predict the association between the input data and the data in the second modality.

Abstract: A machine learning system is provided to enhance various aspects of machine learning models. In some aspects. a substantially photorealistic three-dimensional (3D) graphical model of an object is accessed and a set of training images of the 3D graphical mode are generated, the set of training images generated to add imperfections and degrade photorealistic quality of the training images. The set of training images are provided as training data to train an artificial neural network.

Abstract: A crosslinker composition is prepared from a reaction mixture including: (a) a prepolymer including a reaction product of a prepolymer mixture including: (i) a polyfunctional isocyanate; and (ii) a first compound comprising two or more active hydrogen groups, where the polyfunctional isocyanate and/or the first compound comprising two or more active hydrogen groups includes a greater than two functional isocyanate and/or active hydrogen groups, respectively; and (b) a polyfunctional hydrazide. The crosslinker composition is not self-crosslinkable. The crosslinker composition has an acid value of at least 15 based on total resin solids of the crosslinker composition.

Abstract: Lossy or lossless compression and transmission, comprising the steps of: (i) receiving an input image; (ii) encoding it to produce a y latent representation; (iii) encoding the y latent representation to produce a z hyperlatent representation; (iv) quantizing the z hyperlatent representation to produce a quantized z hyperlatent representation; (v) entropy encoding the quantized z hyperlatent representation into a first bitstream, (vi) processing the quantized z hyperlatent representation to obtain a location entropy parameter ?y, an entropy scale parameter ?y, and a context matrix Ay of the y latent representation; (vii) processing the y latent representation, the location entropy parameter py and the context matrix Ay, to obtain quantized latent residuals; (viii) entropy encoding the quantized latent residuals into a second bitstream; and (ix) transmitting the bitstreams.

Abstract: Apparatuses, systems, and techniques to generate a prompt for one or more machine learning processes. In at least one embodiment, the machine learning process(es) generate(s) a plan to perform a task (identified in the prompt) that is to be performed by an agent (real world or virtual).

Abstract: A catalyst structure includes: (1) a substrate; (2) a catalyst layer on the substrate; and (3) an adhesion layer disposed between the substrate and the catalyst layer. In some implementations, an average thickness of the adhesion layer is about 1 nm or less. In some implementations, a material of the catalyst layer at least partially extends into a region of the adhesion layer. In some implementations, the catalyst layer is characterized by a lattice strain imparted by the adhesion layer.

Abstract: The present disclosure provides diacylglycerol kinase modulating compounds, and pharmaceutical compositions thereof, for treating cancer, including solid tumors, and viral infections, such as HIV or hepatitis B virus infection. The compounds can be used alone or in combination with other agents.

Abstract: A self-cleaning CO2 reduction strategy is proposed herein including alternating operation and regeneration of the CO2 electrolysis system. The strategy includes application of short and periodic reductions in applied voltage, thereby avoiding saturation and prevention of carbonate salt formation.

Abstract: A method of training one or more neural networks, the one or more neural networks being for use in lossy image or video encoding, transmission and decoding, the method comprising steps including: receiving an input image at a first computer system; encoding the input image using a first neural network and decoding the latent representation using a second neural network to produce an output image; at least one of the plurality of layers of the first or second neural network comprises a transformation; and the method further comprises the steps of: evaluating a difference between the output image and the input image and evaluating a function based on an output of the transformation; updating the parameters of the first neural network and the second neural network based on the evaluated difference and the evaluated function; and repeating the above steps.

Abstract: Subject matter related to data management is disclosed. A request to restore target objects of a computing system may be received, where a data management system may store multiple snapshots for the target objects and metadata for the snapshots. The snapshots may be filtered using metadata for the snapshots to obtain a set of snapshots that are available for restoring respective target objects. From among the set of snapshots, suggested snapshots that are available for restoring respective target objects may be identified. The suggested snapshots may be indicated.