Abstract: Methods, systems, and devices for wireless communications are described. A distributed unit (DU) component/function of a base station may determine, for one or more radio units associated with the distributed unit, one or more sampling metrics associated with signal combining operations at the radio units. The DU may select, based at least in part on the one or more sampling metrics, a combining scheme to use for the signal combining operations. The DU may provide an indication of the selected combining scheme to at least one radio unit of the one or more radio units.

Abstract: First images that are screenshots from a first version of a software component are obtained. Second images that are screenshots from a second version are obtained. A collection of image deviations that includes pair-wise image deviations between pairs of images are identified. A pair of images includes a first image from the first images and a corresponding second image from the second images. An image deviation indicates a portion of the second image identified as differing from a spatially corresponding portion of the first image. The image deviations are grouped into deviation groups. At least some of the second images are associated with at least some of the deviation groups. A subset of the second images corresponding to a deviation group is output responsive to a selection of an indication of the deviation group.

Abstract: A machine learning model trained with a triplet loss function classifies input strings into one of multiple hierarchical categories. The machine learning model is pre-trained using masking language modeling on a corpus of unlabeled strings. The machine learning module includes an attention-based bi-directional transformer layer. Following initial training, the machine learning model is refined by additional training with a loss function that includes cross-entropy loss and triplet loss. This provides a deep learning solution to classify input strings into one or more hierarchical categories. Embeddings generated from inputs to the machine learning model capture language similarities that can be visualized in a cartesian plane where strings with similar meanings are grouped together.

Abstract: Systems, methods, and computer program products are provided herein for hyperspectral imaging based authentication. An example method includes receiving check data associated with at least a first user and extracting one or more field details from the check data. By leveraging a hyperspectral imaging module, the method further includes generating hyperspectral image data associated with the one or more extracted field details and determining one or more spectral characteristics associated with the one or more extracted field details based on the hyperspectral image data. The method further includes determining a tampering indication for the check data based on the one or more spectral characteristics. The spectral characteristics may include one or more reflectance values associated with extracted field details across a plurality of spectral bands.

Abstract: The present invention relates to a cost effective and single step process for rapid manufacturing of paper-based SERS substrates (100), wherein chitosan is used for direct in situ reduction of the metallic precursor solutions for production of metallic nanoparticles on the substrates. The crucial step in the process involves the incubation of the paper-based substrates under humidifying conditions at an elevated temperature for a predetermined duration. The metal nanoparticles thus produced are homogenously deposited over the paper-based substrate making the paper-based substrate suitable for SERS analysis. The paper-based substrate thus developed is cost-effective, flexible, easy to load and is demonstrated to have exceptional sensitivity with detection limits of up to 1 pM.

Abstract: A temperature sensor includes a sensing element and a load. Multiple different currents pass through the sensing element in a sequential manner. Based on each current that passes through the sensing element, the sensing element outputs a complementary-to-absolute-temperature (CTAT) voltage and another current. Further, the currents that pass through the sensing element and the currents that the sensing element output separately pass through the load and result in the generation of multiple load voltages across the load. A current density ratio of the temperature sensor is determined based on the load voltages generated across the load. Further, a temperature value indicative of a temperature sensed by the temperature sensor is generated based on the current density ratio and the CTAT voltages outputted by the sensing element based on the different currents that pass therethrough.

Abstract: A technique is described herein for assisting a user in editing a file. The technique involves producing current context information that includes an input message and selected file content. The input message describes a user's editing objective, while the selected file content describes a portion of the file to which the editing objective is to be applied. The technique then requests a pattern-completion engine to generate edit information based on the current context information. The edit information describes one or more changes to the selected file content that satisfy the objective of the user. The pattern-completion engine uses a machine-trained autoregressive text-completion model that is trained on revision history information. The model can be trained in a process that incorporates various tests to ensure that the edit information that is generated works as expected, satisfies various performance metrics, and fulfills the editing objectives of the user.

Abstract: A method for identifying a dynamic resolution for an application (150) of an electronic device (100) is provided. The method includes identifying, by the electronic device, a base resolution for a window of the application (150), wherein the window includes a plurality of views; identifying, by the electronic device, a plurality of resolutions respectively corresponding to the plurality of views based on the base resolution and at least one characteristic of each of the plurality of views; applying, by the electronic device, the plurality of resolutions to the plurality of views, respectively; and displaying, by the electronic device, the plurality of views in the plurality of resolutions, respectively.

Abstract: Arrangements for providing API stability functions are provided. In some aspects, call logs may be received and analyzed to identify a provider associated with each API call. Based on the provider, the call logs may be split into one or more provider-specific sub-logs. The provider-specific sub-logs may be analyzed to identify failed API calls and the sub-logs having failed API calls may be encrypted using a provider-specific encryption key. The encrypted data may be written to a blockchain where the provider may decrypt the data using the provider-specific key and identify and execute one or more corrective actions. Once a cause of the API call failure has been addressed, an indication of the correction may be received and displayed.

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: In one embodiment, a method includes configuring a first application probe class and a second application probe class. The first application probe class may be associated with a first Differentiated Services Code Point (DSCP), and the second application probe class may be associated with a second DSCP. The method also includes determining an adaptive Forward Error Correction (FEC) data policy for the first application probe class and the second application probe class, calculating a first loss value associated with the first application probe class for a link between a first network node and a second network node, and comparing the first loss value to a first loss threshold. The method further includes determining whether to activate FEC processing for the first application probe class in response to comparing the first loss value to the first loss threshold.

Abstract: The disclosure may include an exemplary method comprising receiving risk metric data from a plurality of data sources; determining if the risk metric data passes quality control requirements; factoring the risk metric data; weighting the risk metric data by multiplying the weights at a sub-metric level; standardizing the risk metric data by scaling each risk value in the risk metric data to a range of values for each advisor to obtain standardized risk values; prioritizing the risk metric data by assigning a metric weight to the standardized risk values; further prioritizing the risk metric data by assigning a category weight to the standardized risk values; aggregating the risk metric data for an advisor to create advisor risk metric data; scoring a risk associated with the advisor based on the advisor risk metric data; and transferring the advisor risk data to a dashboard.

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: An evaporative cooling module may include a cooling media formed from a vapor permeable membrane in which is formed a plurality of pores at a first side and a second side of the vapor permeable membrane. Individual pores of the plurality of pores may be sized to prevent liquid water from passing there through, and enable water vapor to pass there through. The cooling media may be configured to hold liquid water while an air stream is passed through the cooling media. The evaporative cooling module may also include a module inlet to direct liquid water into the cooling media, a module outlet to direct liquid water out of the cooling media, and a frame configured to support the evaporative cooling module.

Abstract: A thermo-structural spacer is provided. The spacer includes a cylindrical center portion, a first flange connected to a first end of the cylindrical center portion, a second flange connected to a second end of the cylindrical center portion. The second end is distal from the first end. The spacer further includes an annular inner wall configured for providing a through hole extending through a longitudinal axis of the thermo-structural spacer. The cylindrical center portion is narrower than the first flange. The cylindrical center portion is narrower than the second flange. The thermo-structural spacer is configured for restricting heat transfer between the first flange and the second flange.

Abstract: Provided is a method, performed by an electronic device, of performing an operation based on bending, the method including: sensing bending that deforms a shape of the electronic device; determining a first region, from which the bending is sensed, from among regions of the electronic device; selecting an object indicated by the first region from at least one object displayed on the electronic device; and performing an operation on the selected object.

Abstract: The present invention relates to the beneficial effect of Chebulinic acid (CA) and its enriched standardized fraction (CAEF) isolated/prepared from the fruits of Terminalia chebula for the management of Benign Prostatic Hyperplasia respectively. Further, it relates to a novel, convenient and economically viable method for the isolation of chebulinic acid (CA) and ellagic acid (EA) from the dried and powdered fruits of T. chebula without using any expensive and tedious chromatographic techniques such as HPLC, column chromatography, resins etc.

Abstract: The present disclosure relates to an internally plasticized polyvinyl chloride resin and a process for preparation thereof. The internally plasticized polyvinyl chloride resin comprises a polyvinyl chloride (PVC) resin covalently bonded to at least one plasticizer. The process is simple and economical and provides internally plasticized PVC with enhanced flexibility, and improved characteristics than conventional PVC resin.

Abstract: In one embodiment, a method includes configuring a first application probe class and a second application probe class. The first application probe class may be associated with a first Differentiated Services Code Point (DSCP), and the second application probe class may be associated with a second DSCP. The method also includes determining an adaptive Forward Error Correction (FEC) data policy for the first application probe class and the second application probe class, calculating a first loss value associated with the first application probe class for a link between a first network node and a second network node, and comparing the first loss value to a first loss threshold. The method further includes determining whether to activate FEC processing for the first application probe class in response to comparing the first loss value to the first loss threshold.

Abstract: A computer-implemented technique is described herein for providing assistance to a user in performing various computer-related tasks. The technique relies on a state machine system that transitions among plural modes based on mode-specific cues provided by a pattern-completion engine. The pattern-completion engine, in turn, is induced to generate these cues based on initial context information provided to a context store of the state machine system. Among other information, the initial context information provides example dialogues that are annotated with mode-specific cues. Throughout its operation, the technique updates context information provided in the context store. The plural modes can include at least a user mode, an answer mode, and a command mode. The technique also provides various mechanisms to ensure the privacy of sensitive-information items and to reduce the risk that commands will damage execution platforms.