Abstract: A rain-resistant, drainless, heated air data probe assembly may comprise a probe having a central channel, one or more peripheral channels, and a heating element. In addition, inner surfaces of the channels may include hydrophilic surfaces, and the outer surface of the probe may include hydrophobic surfaces. The hydrophobic outer surface may reduce water ingress into the channels of the probe, and the hydrophilic inner surfaces may cause dispersion of water that has entered the channels. The heating element may further cause evaporation or running off of water on the outer surface, and may cause evaporation of dispersed water within the channels, which may further eliminate the need for a drain at a terminal end of the probe assembly.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: A multiplexed amplitude modulation photometer includes a microchannel; a first input light path that: receives a first modulated light at a first modulation frequency; and communicates the first modulated light to a first optical region that receives the first analyte that produces a first output light including the first modulation frequency communicated to a first detection light path; the first optical region; the first detection light path that receives the first output light; a second input light path that: receives a second modulated light with a second modulation frequency; and communicates second modulated light to a second optical region that receives the second analyte that produces a second output light with the second modulation frequency communicated to a second detection light path; the second optical region; and the second detection light path that receives the second output light from the second optical region.

Abstract: A multiplexed amplitude modulation photometer includes a microchannel; a first input light path that: receives a first modulated light at a first modulation frequency; and communicates the first modulated light to a first optical region that receives the first analyte that produces a first output light including the first modulation frequency communicated to a first detection light path; the first optical region; the first detection light path that receives the first output light; a second input light path that: receives a second modulated light with a second modulation frequency; and communicates second modulated light to a second optical region that receives the second analyte that produces a second output light with the second modulation frequency communicated to a second detection light path; the second optical region; and the second detection light path that receives the second output light from the second optical region.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: A spatio-temporal profilometer performs time-resolved spatial profilometry and includes a substrate, a tapered optical collimator waveguide, a fluid channel, and a light-fluid interaction volume. The tapered optical collimator waveguide receives diverging light, internally reflects it, and collimates it. The fluid channel receives a fluid comprising microparticles and communicates the microparticles into the fluid channel. The light-fluid interaction volume is disposed in the fluid channel and provided by an overlap within the fluid channel of the collimated light from the tapered optical collimator waveguide and the fluid. The spatio-temporal profilometer produces product light from the collimated light in response to the microparticles interacting with the collimated light in the light-fluid interaction volume from which is determined a spatial and temporal profile of microparticles in the fluid channel.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: The present concepts relate to a differentiable user-item co-clustering (“DUICC”) model for recommendation and co-clustering. Users' interaction with items (e.g., content) may be centered around information co-clusters—groups of items and users that exhibit common consumption behavior. The DUICC model may learn fine-grained co-cluster structures of items and users based on their interaction data. The DUICC model can then leverage the learned latent co-cluster structures to calculate preference stores of the items for a user. The top scoring items may be presented to the user as recommendations.

Abstract: Disclosed are techniques for extracting, identifying, and consuming imprecise temporal elements (“ITEs”). A user input may be received from a client device. A prediction may be generated of one or more time intervals to which the user input refers based upon an ITE model. The user input may be associated with the prediction, and provided to the client device.

Abstract: Disclosed are systems and methods for trusted and secure application deployment via collective signature verification of the application artifacts. The trusted and secure application deployment may include receiving multiple application artifacts, decoding verifications from at least one cryptographic signature associated with each received artifact, comparing the verifications to a first set of requirements specified in an admission control list, comparing the verifications from a first received artifact to a second set of requirements specified in the verifications of a second received artifact, halting the deployment of the artifacts in response to the decoded verifications not satisfying one or more requirements from the first set of requirements or the second set of requirements, and deploying the artifacts to a set of compute nodes in response to the verifications decoded from the received artifacts satisfying the first set of requirements and the second set of requirements.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.

Abstract: Disclosed are systems and methods for trusted and secure application deployment via collective signature verification of the application artifacts. The trusted and secure application deployment may include receiving multiple application artifacts, decoding verifications from at least one cryptographic signature associated with each received artifact, comparing the verifications to a first set of requirements specified in an admission control list, comparing the verifications from a first received artifact to a second set of requirements specified in the verifications of a second received artifact, halting the deployment of the artifacts in response to the decoded verifications not satisfying one or more requirements from the first set of requirements or the second set of requirements, and deploying the artifacts to a set of compute nodes in response to the verifications decoded from the received artifacts satisfying the first set of requirements and the second set of requirements.

Abstract: The present concepts relate to a differentiable user-item co-clustering (“DUICC”) model for recommendation and co-clustering. Users' interaction with items (e.g., content) may be centered around information co-clusters—groups of items and users that exhibit common consumption behavior. The DUICC model may learn fine-grained co-cluster structures of items and users based on their interaction data. The DUICC model can then leverage the learned latent co-cluster structures to calculate preference stores of the items for a user. The top scoring items may be presented to the user as recommendations.

Abstract: Embodiments of the present invention relate to a system and method for determining quantity of target nucleic acid sequence in a sample. During a PCR-based amplification reaction, fluorescence intensity signals are acquired that form an amplification profile from which an exponential amplification region is desirably identified. In determining the exponential region, embodiments of the present invention determine a fluorescence threshold by background subtraction, test the feasibility of matching a signal to a reference curve and, in the event the feasibility test is successful, determine the matching parameters that quantify the initial amplicon number, and signal detection that reduces systematic errors in the measurements and increase the sensitivity of the measurement by decreasing the apparent noise-floor.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: A computer-implemented technique receives an input expression that a user submits with an intent to accomplish some objective. The technique then uses a machine-trained intent encoder component to map the input expression into an input expression intent vector (IEIV). The IEIV corresponds to a distributed representation of the intent associated with the input expression, within a vector intent vector space. The technique then leverages the intent vector to facilitate some downstream application task, such as the retrieval of information. Some application tasks also use a neighbor search component to find expressions that express an intent similar to that of the input expression. A training system trains the intent encoder component based on the nexus between queries and user clicks, as recorded in a search engine's search log.

Abstract: Embodiments of the present invention described herein provide a device that can measure a single particle in flow several times along a microchannel with integrated waveguides that carry optical signals (e.g. excitation, emission, transmission, and scattered light) to and from measurement regions. Embodiments of the present invention used to perform multiple measurements of particles, such as microspheres or cells, traveling in a sample fluid through a microfluidic channel achieve lower uncertainties, discriminate complex samples, and account for sources of uncertainty that might be related to the shape, deformability, stability, or activity of objects in a liquid sample.