Abstract: Methods, computer-readable media, systems, and/or apparatuses for providing offer and insight generation functions are provided. For instance, user input may be received requesting generation of an offer. In response to receiving the request, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the application may be executed by the device and may facilitate establishing a communication session with a third party system, identifying and extracting data from the third party system, and transmitting the extracted data to an entity for evaluation. In some examples, evaluation by the entity may include generating one or more insights, outputs and the like. In some arrangements, the evaluation may be performed using machine learning and, in some examples, may be performed in real-time or near real-time.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises ingesting tabular data from at least one modality of a plurality of modalities; simultaneously extracting data and generating a prediction model for a task of a computing device from the extracted data from at least two modalities in the plurality of modalities; generating a data signature based on the generated prediction model from the at least two modalities by leveraging the generated prediction model for ingested tabular data and extracted data; comparing the generated data signature to identified data signatures stored in at least one modality in the plurality of modalities; and performing a task based on the generated data signature and a validation of the comparison of identified data signatures.

Abstract: A method includes receiving, at an artificial intelligence (AI) accelerator of a computing system, at least one of: manufacturer data, third-party data, sensor data, or primary usage data of a consumable in a primary device and performing an AI operation on at least one of: the manufacturer data, the third-party data, the sensor data, or the primary usage data at the AI accelerator of the computing system using an AI model. The method further includes determining a primary life expectancy of the consumable in the primary device at the AI accelerator in response to performing the AI operation.

Abstract: Functionalized particles comprising a shell and a core and a payload that is embedded or entrapped, wherein the shell matrix is obtained by interfacial polymerisation of vinyltriethoxy silane and at least one other ethylenically unsaturated monomer copolymerizable with vinyltriethoxy silane, said functionalized particles being capable to chemically bind to a substrate, are suitable as controlled release systems for textile applications to impart durable softness and excellent water retention even after multiple laundries.

Abstract: Described herein is an intronic recognition element for splicing modifier (iREMS) that can be recognized by a small molecule splicing modifier compound of Formula (I) provided herein or a form thereof, wherein W, X, A and B are as defined herein. In one aspect, methods for modifying RNA splicing to modulate the amount of a product of a gene, wherein a precursor RNA transcript transcribed from the gene that contains an intronic REMS is modified utilizing a splicing modifier compound of Formula (I), are described herein. In another aspect, methods for modifying RNA splicing to modulate the amount of an RNA transcript or protein product encoded by a gene, wherein a precursor RNA transcript transcribed from the gene is modified to comprise an intronic REMS utilizing a splicing modifier compound of Formula (I), are described herein.

Abstract: Embodiments of the present disclosure relate to an electronic identification system of a logic board for use in variable speed drives. Specifically, the present disclosure relates to a logic board for a variable speed drive having a configuration block that includes a plurality of resistors, a control system communicatively coupled to and configured to receive a signal from the configuration block, where the control system is configured to decode the signal to generate data indicative of an identity of the logic board, and a communication interface coupled to the control system, where the communication interface is configured to provide the data indicative of the identity of the logic board to an operator.

Abstract: A system and method are described herein for estimating power usage of various components of a CPU and controlling voltage regulators based on the estimated power usage. The power estimates may be based on digital power meter readings at each component, on voltage information from a voltage regulator, and on other power information. This power information is transmitted over a mesh interconnect disposed throughout the CPU such that power estimation can be accurately calculated and used to control voltage regulators without being limited by external bus speeds. More of the power management processes and components may be disposed on the CPU and connected to the mesh interconnect. These power management processes include various calibrations, adjustments, and limits so as efficiently manage and use the more rapidly processed power estimations.

Abstract: A system and method for accelerating modernization of user interfaces in a computing environment is disclosed. The method includes receiving request for transforming a current graphical user interface (GUI) corresponding to current programming language and associated software framework to a target GUI corresponding to target programming language and associated software framework. The method includes capturing run time application attributes during an active interactive session of the user interface with user devices. Further, the method includes determining static application attributes from the source code of the current application. The method includes generating application attribute model representing relationships between static application attributes and run time application attributes. The method further includes automatically generating a target application attribute model corresponding to the target programming language and associated software framework based on the application attribute model.

Abstract: A layer of amorphous Ge is formed on a substrate using electron-beam evaporation. The evaporation is performed at room temperature. The layer of amorphous Ge has a thickness of at least 50 nm and a purity of at least 90% Ge. The substrate is complementary metal-oxide-semiconductor (CMOS) compatible and is transparent at Long-Wave Infrared (LWIR) wavelengths. The layer of amorphous Ge can be used as a waveguide in chemical sensing and data communication applications. The amorphous Ge waveguide has a transmission loss in the LWIR of 11 dB/cm or less at 8 ?m.

Abstract: Temporal and spatially integrated forecast modeling includes generating a plurality of forecast models for a plurality of short-term to long-term time periods for a plurality of locations. Temporally integrating the plurality of forecast models sequentially over the plurality of time periods for the plurality of locations and spatially integrating the temporally integrated plurality of forecast models for each location hierarchically over the geographic areas. The forecast models are autoregressive distributed lag models with different explanatory variables for the short-term and long-term forecast models. The temporally integrating includes recursively integrating the plurality of forecast models over the time periods from the short-term to the long-term time periods and the spatially integrating includes recursively integrating the temporally integrated plurality of forecast models hierarchically from larger size geographic areas to smaller size geographic areas.

Abstract: A computing device includes a processor and a storage device. A wafer asset modeling module is stored in the storage device and is executed by the processor to configure the computing device to perform acts identifying and clustering a plurality of assets based on static properties of a wafer asset using a first module of the wafer asset modeling module. The clustered plurality of assets is determined based on dynamic properties of the wafer asset using a second module of the wafer asset modeling module. Event prediction is performed by converting a numeric data of the clustered plurality of assets to a natural language processing (NLP) domain by a third module of the wafer asset modeling module. One or more sequence-to-sequence methods are performed to predict a malfunction of a component of the wafer asset and/or an event based on past patterns. Prediction information is stored in the storage device.

Abstract: A method (1100) of fabricating a personalised orthopaedic cast (900) is disclosed. The method (1100) includes 3D scanning of a body part of a user, generating a Computer Aided Design (CAD) of an orthopaedic cast (900) for the scanned body part, and simulating real-life conditions to determine mechanical stability of the modelled cast. The mechanical stability is determined through Finite Element Analysis (FEA). The method (1100) includes determining whether the mechanical stability of the modelled cast is acceptable. The method (1100) includes finalising the CAD model when the mechanical stability of the modelled cast is found to be acceptable. The method (1100) includes 3D printing the finalised CAD model to fabricate the personalised orthopaedic cast (900).

Abstract: Methods and systems to provide a form of probabilistic labeling to associate an outage with a disturbance, which could itself be either known based on the available data or unknown. In the latter case, labeling is especially challenging, as it necessitates the discovery of the disturbance. One approach incorporates a statistical change-point analysis to time-series events that correspond to service tickets in the relevant geographic sub-regions. The method is calibrated to separate the regular periods from the environmental disturbance periods, under the assumption that disturbances significantly increase the rate of loss-causing events. To obtain the probability that a given loss-causing event is related to an environmental disturbance, the method leverages the difference between the rate of events expected in the absence of any disturbances (baseline) and the rate of actually observed events. In the analysis, the local disturbances are identified and estimators of their duration and magnitude are provided.

Abstract: Various methods and systems are provided for longitudinal presentation of patient information. In one example, a computing device comprises a display screen, the computing device being configured to display on the screen a timeline of patient medical information including a plurality of symbols representing the patient medical information, wherein a symbol of the plurality of symbols is selectable to launch a details panel and enable a report that references the displayed patient medical information to be seen within the timeline, and wherein the symbol is displayed while the details panel is in an un-launched state.

Abstract: Various methods and systems are provided for display of recommended treatment based on a patient's medical history and standardized guidelines. In one example, a computing system includes a display screen configured to display a patient medical path listing one or more of treatment guidelines and patient medical history, and to display abbreviated representations of at least one of the treatment guidelines and the patient medical history that can be reached directly from the displayed patient medical path. The abbreviated representations each display a limited list of data that is selectable to launch the treatment guidelines and/or the patient medical history and enable the selected data to be seen.

Abstract: Systems and methods in accordance with aspects of this disclosure may be provided to determine and calculate an overall driving risk index value corresponding to a driver and scene configuration. The overall driving risk index value may provide driving risk modeling and estimation at a personalized driving level. In some cases, the overall driving risk index value may be determined using a risk-predictive modeling system with weighting and machine learning and may include one or more of: a driver score system, a driver-contextual risk score system, and a conflict index system.

Abstract: A method for managing a boost time required for an application launch in an electronic device is provided. The method includes detecting, by the electronic device, a user input to launch the application. Further, the method includes measuring, by the electronic device, real-time system health parameters of the electronic device. Further, the method includes predicting, by the electronic device, an application launch time by inputting the real-time system health parameters to an AI-based application prediction model. Further, the method includes boosting, by the electronic device, at least one hardware of the electronic device based on the predicted application launch time.

Abstract: A method, a system, and a computer program product for generating name recommendations in a core data services computing environment. A dataset for training a name data model is received. The name data model is configured for determination of a recommendation for one or more names in a plurality of names associated with one or more artifacts in a plurality of artifacts of a database management system. The name data model is trained using the received dataset and applied to generate one or more names associated with the one or more artifacts.

Abstract: A concept associated with a feature used in machine learning model can be determined, the feature extracted from a first data source. A second data source containing the concept can be identified. An additional feature can be generated by performing a natural language processing on the second data source. The feature and the additional feature can be merged. A second machine learning model can be generated, which use the merged feature. A prediction result of the first machine learning model can be compared with a prediction result of the second machine learning model relative to ground truth data, to evaluate effective of the merged feature. Based on the evaluated effectiveness, the feature can be augmented with the merged feature in machine learning.

Abstract: The present disclosure relates to vectors for cloning and expressing genetic material including but not limiting to antibody gene or parts thereof and methods of generating said vectors. Said vectors express the antibody genes in different formats such as Fab or scFv as a part of intertransfer system, intratransfer system or direct cloning and expression in individual display systems. In particular, phage display technology is used to clone and screen potential antibody genes in phagemid which is followed by the transfer of said genes to yeast vector for further screening and identification of lead molecules against antigens. The present vectors have numerous advantages including uniquely designed inserts/expression cassettes resulting in efficient and smooth transfer of clonal population from phage to yeast vectors resulting in efficient library preparation and identification of lead molecules.