Abstract: In integrating multiple priors into media mix modeling, a processing device receives multiple priors that each includes contribution share for one or more marketing channels, a time period, and a geographical region. A machine-learning model generates a transferred model for each prior by performing hyperparameter tuning of a base model based on the corresponding contribution share. The processing device uses the transferred models to generate a combined prior that includes a proportional contribution of the multiple priors. The machine-learning model then generates a combined model by performing hyperparameter tuning of the base model using the combined prior. Marketers can utilize the combined model to assess the contribution of different marketing efforts and perform budget planning.

Abstract: Disclosed is a use of G007-LK in promoting osteogenic differentiation of dental mesenchymal stem cells and bone tissue regeneration. In vitro experiments of the present application show that G007-LK has the ability to induce SHED to form mineralized nodules and promote osteogenic differentiation; in vivo experiments show that G007-LK pretreatment of SHED for 7 days combined with Geistlich Bio-Oss® collagen bone scaffold can enhance the in vivo osteogenic effect of SHED and promote the subcutaneous ectopic osteogenesis of nude mice, indicating that G007-LK has good osteoinductivity and is a potential osteogenic drug. Therefore, G007-LK can promote osteogenic differentiation of dental mesenchymal stem cells and be applied to bone tissue regeneration.

Abstract: Some aspects relate to technologies providing a framework for integrating two machine learning models to determine an attribution of a content campaign to conversions. In accordance with some aspects, a first machine learning model (such as a media mix modeling model) generates a first attribution of a content campaign to intermediate events. A second machine learning model (such as a multi-touch attribution model) generates a second attribution of the intermediate events to conversions. An attribution of the content campaign to the conversions is determined as a function of the first attribution and the second attribution.

Abstract: Disclosed is a use of G007-LK in promoting osteogenic differentiation of dental mesenchymal stem cells and bone tissue regeneration. In vitro experiments of the present application show that G007-LK has the ability to induce SHED to form mineralized nodules and promote osteogenic differentiation; in vivo experiments show that G007-LK pretreatment of SHED for 7 days combined with Geistlich Bio-Oss® collagen bone scaffold can enhance the in vivo osteogenic effect of SHED and promote the subcutaneous ectopic osteogenesis of nude mice, indicating that G007-LK has good osteoinductivity and is a potential osteogenic drug. Therefore, G007-LK can promote osteogenic differentiation of dental mesenchymal stem cells and be applied to bone tissue regeneration.

Abstract: The present invention precisely concerns the calculation method for the optimum two-component synchronous rejuvenator dosage for aged SBS-modified asphalt, including the following steps: (1) calculating the characteristic peak area ratio of unaged SBS molecular chain IB0 and unaged pure asphalt IB, aI0 and ARI0; (2) selecting four types of SBS-modified asphalt with different aging degrees and calculating their IBA, IB, aIA and ARIA; (3) adding the rejuvenator to above asphalts and calculating their post-rejuvenation BR, IB, aIR and ARIR; (4) establishing the regression equation between optimum rejuvenator dosage and characteristic peak area ratio requiring restoration due to aging; (5) as the given aged SBS-modified asphalt, substituting the characteristic peak area ratio requiring restoration into the equation to calculate the required optimum rejuvenator dosage.

Abstract: A method, non-transitory computer readable medium, apparatus, and system for data processing include obtaining, by a multi-touch attribution model, individual-level user interaction data from a digital content channel, and computing, using the multi-touch attribution model, channel contribution data based on the individual-level user interaction data. Some embodiments include training, using a training component, an aggregate attribution model based on the channel contribution data. Some embodiments include generating, using a calibration component, an individual channel contribution value for the digital content channel based on the channel contribution data and the aggregate attribution model.

Abstract: The present invention precisely concerns the calculation method for the optimum two-component synchronous rejuvenator dosage for aged SBS-modified asphalt, including the following steps: (1) calculating the characteristic peak area ratio of unaged SBS molecular chain IB0 and unaged pure asphalt IB, aI0 and ARI0; (2) selecting four types of SBS-modified asphalt with different aging degrees and calculating their IBA, IB, aIA and ARIA; (3) adding the rejuvenator to above asphalts and calculating their post-rejuvenation IBR, IB, aIR and ARIR; (4) establishing the regression equation between optimum rejuvenator dosage and characteristic peak area ratio requiring restoration due to aging; (5) as the given aged SBS-modified asphalt, substituting the characteristic peak area ratio requiring restoration into the equation to calculate the required optimum rejuvenator dosage.

Abstract: Provided is a catching device for surface rescue based on an aircraft platform, and a surface rescue method. The catching device for surface rescue based on the aircraft platform includes a throwing mechanism, a flying mechanism, a recovery mechanism, an automatic control module, and a catching net. Both the throwing mechanism and the recovery mechanism are disposed on the flying mechanism, and the automatic control module automatically controls the throwing mechanism and the recovery mechanism. After the flying mechanism flies above a drowning person, the throwing mechanism is configured to throw the catching net towards the drowning person. After the catching net nets the drowning person, the recovery mechanism can drive a bottom of the catching net to close and lift the catching net upwards to approach the flying mechanism, and the flying mechanism is configured to drag the drowning person to a safe location.

Abstract: This application relates to the field of audio noise reduction, and provides a method and system for noise reduction in aircraft simulator sounds, a device, and a medium. The method includes: acquiring sound data from an aircraft simulator sound system; classifying the sound data to obtain classified audio data; performing Short-Time Fourier Transform (STFT) processing on the classified audio data to obtain spectral frames; performing noise reduction processing on the spectral frames by using a neural network, to obtain processed spectral frames, where the neural network includes a recurrent neural network and a Deep Q-network (DQN); and performing inverse STFT on the processed spectral frames to obtain denoised audio. This application can achieve low-cost and efficient noise reduction for sounds.

Abstract: In some embodiments, a computing system extrapolates aggregated interaction data associated with users of an online platform by applying a mixed granularity model to generate extrapolated interaction data for each user in the users. The aggregated interaction data includes a total number of occurrences of a target action performed by the users with respect to the online platform. The extrapolated data includes a series of actions leading to the target action for each user. The computing system identifies an impact of each action in the series of actions for each user on leading to the target action based, at least in part, upon the extrapolating a series of actions associated with the user. User interfaces presented on the online platform can be modified based on at least the identified impacts to improve customization of the user interfaces to the users or enhance an experience of the users.

Abstract: A magnetic material used in the magnetic SF-based composite aerogel is a ferroferric oxide nanocubic particle, which is a magnetic nanomaterial with both excellent magnetocaloric performance and excellent photothermal performance. The magnetic SF-based composite aerogel prepared by the present disclosure exhibits excellent responsiveness to both alternating current (AC) magnetic fields and sunlight. Under an action of an AC magnetic field, the magnetic SF-based composite aerogel exhibits excellent temperature rise performance, which can inhibit the generation of biofouling in pores and channels inside a three-dimensional (3D) porous evaporation material. The magnetic SF-based composite aerogel exhibits excellent water evaporation performance under a sunlight irradiation, with a water evaporation rate of 2.03 kg m?2·h?1.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a modified analytics prediction machine learning model using an iterative transfer learning approach. For example, the disclosed systems generate an initial version of an analytics prediction machine learning model for predicting an analytics metric according to learned parameters. In some embodiments, the disclosed systems determine expected data channel contributions for the analytics metric according to prior data. Additionally, in some cases, the disclosed systems generate a modified analytics prediction machine learning model by iteratively updating model parameters such that predicted data channel contributions are within a threshold similarity of expected data channel contributions.

Abstract: A magnetic material used in the magnetic SF-based composite aerogel is a ferroferric oxide nanocubic particle, which is a magnetic nanomaterial with both excellent magnetocaloric performance and excellent photothermal performance. The magnetic SF-based composite aerogel prepared by the present disclosure exhibits excellent responsiveness to both alternating current (AC) magnetic fields and sunlight. Under an action of an AC magnetic field, the magnetic SF-based composite aerogel exhibits excellent temperature rise performance, which can inhibit the generation of biofouling in pores and channels inside a three-dimensional (3D) porous evaporation material. The magnetic SF-based composite aerogel exhibits excellent water evaporation performance under a sunlight irradiation, with a water evaporation rate of 2.03 kg m?2·h?1.

Abstract: Example implementations described herein involve systems and methods for generating an ensemble of deep learning or neural network models, which can involve, for a training set of data, generating a plurality of model samples for the training set of data, the plurality of model samples generated from deep learning or neural network methods; and aggregating output of the model samples to generate an output of the ensemble models.

Abstract: Example implementations described herein involve systems and methods for generating an ensemble of deep learning or neural network models, which can involve, for a training set of data, generating a plurality of model samples for the training set of data, the plurality of model samples generated from deep learning or neural network methods; and aggregating output of the model samples to generate an output of the ensemble models.