Abstract: Provided are molecular feedback circuits employing caged-degrons. Aspects of such circuits include the use of a caged-degron to modulate the output of a signaling pathway in a feedback-controlled manner. Also provided are nucleic acids encoding molecular circuits and cells containing such nucleic acids. Methods of using caged-degron-based molecular feedback circuits are also provided, including e.g., methods of modulating a signaling pathway of a cell that include genetically modifying the cell with a caged-degron-based molecular feedback circuit.

Abstract: A risk management server may apply a trained risk model to a plurality of user accounts maintained by a service provider to identify a plurality of suspicious user accounts. The risk management server may suspend each of the identified suspicious user accounts from using one or more features provided by the service provider. The risk management server may cure one or more of the suspended user accounts responsive to a successful response to a challenge presented to a user associated with each of the suspended accounts. The risk management server may confirm that each of the uncured suspended user accounts is fraudulent after a period of time without being cured. The risk management server may create training data including the cured user accounts labeled as not fraudulent and the confirmed user accounts labeled as fraudulent. The risk management server may re-train the risk model using the training data.

Abstract: A method of repairing oxidatively-treated hair, the methods comprising the sequential steps of: (i) soaking hair in an aqueous treatment composition, (ii) rinsing the hair of step (i); characterised in that the aqueous treatment composition comprises 0.1 to 6 wt % N-acetyl amino acid, based on the total weight of the composition, wherein the N-acetyl amino acid is selected from the group consisting of N-acetyl glycine, N-acetyl alanine, N-acetyl proline, N-acetyl leucine, N-acetyl isoleucine, N-acetyl valine, N-acetyl tyrosine, N-acetyl phenylalanine, N-acetyl tryptophan, N-acetyl serine, N-acetyl glutamine, N-acetyl threonine, N-acetyl asparagine, N-acetyl methionine, N-acetyl lysine, N-acetyl histidine and mixtures thereof, gives damage repair benefits.

Abstract: Embodiments of a production-quality text-to-speech (TTS) system constructed from deep neural networks are described. System embodiments comprise five major building blocks: a segmentation model for locating phoneme boundaries, a grapheme-to-phoneme conversion model, a phoneme duration prediction model, a fundamental frequency prediction model, and an audio synthesis model. For embodiments of the segmentation model, phoneme boundary detection was performed with deep neural networks using Connectionist Temporal Classification (CTC) loss. For embodiments of the audio synthesis model, a variant of WaveNet was created that requires fewer parameters and trains faster than the original. By using a neural network for each component, system embodiments are simpler and more flexible than traditional TTS systems, where each component requires laborious feature engineering and extensive domain expertise. Inference with system embodiments may be performed faster than real time.

Abstract: Presented herein are embodiments of state-of-the-art speech recognition systems developed using end-to-end deep learning. In embodiments, the model architecture is significantly simpler than traditional speech systems, which rely on laboriously engineered processing pipelines; these traditional systems also tend to perform poorly when used in noisy environments. In contrast, embodiments of the system do not need hand-designed components to model background noise, reverberation, or speaker variation, but instead directly learn a function that is robust to such effects. Neither a phoneme dictionary, nor even the concept of a “phoneme,” is needed. Embodiments include a well-optimized recurrent neural network (RNN) training system that can use multiple GPUs, as well as a set of novel data synthesis techniques that allows for a large amount of varied data for training to be efficiently obtained.

Abstract: Provided are molecular feedback circuits employing caged-degrons. Aspects of such circuits include the use of a caged-degron to modulate the output of a signaling pathway in a feedback-controlled manner. Also provided are nucleic acids encoding molecular circuits and cells containing such nucleic acids. Methods of using caged-degron-based molecular feedback circuits are also provided, including e.g., methods of modulating a signaling pathway of a cell that include genetically modifying the cell with a caged-degron-based molecular feedback circuit.

Abstract: Provided are molecular feedback circuits as well as nucleic acids encoding such molecular feedback circuits and cells genetically modified with the subject molecular feedback circuits. Methods of modulating signaling of a signaling pathway of a cell using molecular feedback circuits and methods of treating a subject for a condition by administering a cell containing a nucleic acid that encodes a molecular feedback circuit are also provided. Aspects of the molecular feedback circuits of the present disclosure include a signaling protein, of a signaling pathway, that includes a latent deactivation domain. Such circuits may include a regulatory sequence that is responsive to an output of the signaling pathway and is operably linked to a nucleic acid encoding a switch polypeptide that, when expressed, triggers the deactivation domain to deactivate the signaling molecule.

Abstract: Disclosed herein are non-naturally occurring cage polypeptides, kits and degron LOCKRs including the cage polypep-tides, and uses thereof, wherein the cage polypeptides include (a) a helical bundle, comprising between 2 and 7 alpha-helices, wherein the helical bundle includes: (i) a structural region; and (ii) a latch region, wherein the latch region composes a degron located within the latch region, wherein the structural region interacts with the latch region to prevent activity of the degron; and (b) amino acid linkers connecting each alpha helix

Abstract: A method of repairing oxidatively-treated hair, the methods comprising the sequential steps of: (i) soaking hair in an aqueous treatment composition, (ii) rinsing the hair of step (i); characterised in that the aqueous treatment composition comprises 0.1 to 6 wt % N-acetyl amino acid, based on the total weight of the composition, wherein the N-acetyl amino acid is selected from the group consisting of N-acetyl glycine, N-acetyl alanine, N-acetyl proline, N-acetyl leucine, N-acetyl isoleucine, N-acetyl valine, N-acetyl tyrosine, N-acetyl phenylalanine, N-acetyl tryptophan, N-acetyl serine, N-acetyl glutamine, N-acetyl threonine, N-acetyl asparagine, N-acetyl methionine, N-acetyl lysine, N-acetyl histidine and mixtures thereof, gives damage repair benefits.

Abstract: Embodiments of a production-quality text-to-speech (TTS) system constructed from deep neural networks are described. System embodiments comprise five major building blocks: a segmentation model for locating phoneme boundaries, a grapheme-to-phoneme conversion model, a phoneme duration prediction model, a fundamental frequency prediction model, and an audio synthesis model. For embodiments of the segmentation model, phoneme boundary detection was performed with deep neural networks using Connectionist Temporal Classification (CTC) loss. For embodiments of the audio synthesis model, a variant of WaveNet was created that requires fewer parameters and trains faster than the original. By using a neural network for each component, system embodiments are simpler and more flexible than traditional TTS systems, where each component requires laborious feature engineering and extensive domain expertise. Inference with system embodiments may be performed faster than real time.

Abstract: Embodiments of a production-quality text-to-speech (TTS) system constructed from deep neural networks are described. System embodiments comprise five major building blocks: a segmentation model for locating phoneme boundaries, a grapheme-to-phoneme conversion model, a phoneme duration prediction model, a fundamental frequency prediction model, and an audio synthesis model. For embodiments of the segmentation model, phoneme boundary detection was performed with deep neural networks using Connectionist Temporal Classification (CTC) loss. For embodiments of the audio synthesis model, a variant of WaveNet was created that requires fewer parameters and trains faster than the original. By using a neural network for each component, system embodiments are simpler and more flexible than traditional TTS systems, where each component requires laborious feature engineering and extensive domain expertise. Inference with system embodiments may be performed faster than real time.

Abstract: Presented herein are embodiments of state-of-the-art speech recognition systems developed using end-to-end deep learning. In embodiments, the model architecture is significantly simpler than traditional speech systems, which rely on laboriously engineered processing pipelines; these traditional systems also tend to perform poorly when used in noisy environments. In contrast, embodiments of the system do not need hand-designed components to model background noise, reverberation, or speaker variation, but instead directly learn a function that is robust to such effects. A phoneme dictionary, nor even the concept of a “phoneme,” is needed. Embodiments include a well-optimized recurrent neural network (RNN) training system that can use multiple GPUs, as well as a set of novel data synthesis techniques that allows for a large amount of varied data for training to be efficiently obtained.

Abstract: Embodiments of a production-quality text-to-speech (TTS) system constructed from deep neural networks are described. System embodiments comprise five major building blocks: a segmentation model for locating phoneme boundaries, a grapheme-to-phoneme conversion model, a phoneme duration prediction model, a fundamental frequency prediction model, and an audio synthesis model. For embodiments of the segmentation model, phoneme boundary detection was performed with deep neural networks using Connectionist Temporal Classification (CTC) loss. For embodiments of the audio synthesis model, a variant of WaveNet was created that requires fewer parameters and trains faster than the original. By using a neural network for each component, system embodiments are simpler and more flexible than traditional TTS systems, where each component requires laborious feature engineering and extensive domain expertise. Inference with system embodiments may be performed faster than real time.

Abstract: A system for recording a compressed video-audio stream includes a decoder for decoding the video and audio packets of the stream, a multimedia recorder for recording the video and audio portions of the stream, and a video frame editor. In one embodiment the multimedia recorder receives and ignores initial delta frames of the video portion of the stream while buffering the audio portion of the stream received until a first key frame arrives and is buffered and decoded and wherein upon receiving a command to record, the system writes a copy of the key frame at a predefined interval the first interval corresponding with the start of the recording of the audio portions of the stream, the write interval repeated successively until a next key frame arrives whereby the video and audio is then recorded as received.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to a feed event, a feed event document, and/or a feed event type business object.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to a user feed administrator, a user feed event link and/or a user feed settings business object.

Abstract: A system for recording a compressed video-audio stream includes a decoder for decoding the video and audio packets of the stream, a multimedia recorder for recording the video and audio portions of the stream, and a video frame editor. In one embodiment the multimedia recorder receives and ignores initial delta frames of the video portion of the stream while buffering the audio portion of the stream received until a first key frame arrives and is buffered and decoded and wherein upon receiving a command to record, the system writes a copy of the key frame at a predefined interval the first interval corresponding with the start of the recording of the audio portions of the stream, the write interval repeated successively until a next key frame arrives whereby the video and audio is then recorded as received.

Abstract: A system for recording a compressed video-audio stream includes a decoder for decoding the video and audio packets of the stream, a multimedia recorder for recording the video and audio portions of the stream, and a video frame editor. In one embodiment the multimedia recorder receives and ignores initial delta frames of the video portion of the stream while buffering the audio portion of the stream received until a first key frame arrives and is buffered and decoded and wherein upon receiving a command to record, the system writes a copy of the key frame at a predefined interval the first interval corresponding with the start of the recording of the audio portions of the stream, the write interval repeated successively until a next key frame arrives whereby the video and audio is then recorded as received.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to a feed collaboration group and/or a feed event subscription business object.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to a feed event, a feed event document, and/or a feed event type business object.