Abstract: Provided are an interaction method and apparatus in a live streaming room, and a device and a storage medium. The method comprises: in response to a trigger operation for a preset duet entry on a live streaming room page, jumping from the live streaming room page to a camera capture page, wherein a host portrait cutout corresponding to the live streaming room page is displayed on the camera capture page and a capture control is provided on the camera capture page acquiring multimedia information captured by a camera, in response to a trigger operation for the capture control on the camera capture page, wherein the multimedia information comprises an image or a video; and synthesizing the multimedia information with the host portrait cutout to obtain a duet multimedia product.

Abstract: Provided are an interaction method and apparatus in a live streaming room, a device, and a storage medium. The method comprises: in response to a trigger operation for a preset drawing entry on a live streaming room page, jumping to a graphic drawing page from the live streaming room page, a drawing trajectory set for a preset object being displayed on the graphical drawing page; when a drawing stroke on the graphic drawing page is received, matching the drawing stroke with the drawing trajectory; and if it is determined that the drawing stroke is successfully matched with the drawing trajectory, displaying prompt information about successful participation in a preset activity, the preset activity and the preset drawing entry having a correspondence.

Abstract: Provided are a beveled light-emitting lamp bead, a beveled light-emitting lamp bead holder, a manufacturing method therefor, and a display device. The beveled light-emitting lamp bead holder includes a holder body and a metal holder embedded in the holder body, where the holder body is divided by the metal holder into a cup shield located on a top side and a support structure located on a bottom side, a cup bottom in the cup shield is provided with a chip mounting surface parallel to a cup rim top surface, a bottom portion of the support structure is provided with a soldering plane, the soldering plane is electrically connected to the chip mounting surface through the metal holder, and an inclination angle is formed between the chip mounting surface and the soldering plane.

Abstract: Exemplary semiconductor structures may include a plurality of LED structures and a backplane layer. Exemplary semiconductor structures may also include a light barrier region positioned between the LED structures and the backplane layer. The light barrier region may be operable to absorb light at wavelengths shorter than or about 300 nm and transmit light at wavelengths greater than or about 350.

Abstract: A conversion power supply and an autonomous electric energy replenishment method for an energy storage system are provided. An output terminal of the power supply module is connected to a second side of a first DC-DC converter through an energy storage element. A first side of the first DC-DC converter is connected to battery clusters of the energy storage system through a DC interface of the conversion power supply, so that under control by a conversion power supply controller, in a case that a voltage of a battery cluster is lower than a preset threshold, the first DC-DC converter receives the electric energy on the second side, and transmit the electric energy to the first side of the first DC-DC converter, to realize a electric energy replenishment function for at least one of the battery clusters and prevent battery failure due to over-discharge.

Abstract: A device and method for monitoring freezing-thawing damage of an underwater concrete member in situ. A main structure includes an upper link, concrete member, transverse sealed box, longitudinal sealed box, movable guide rod, probe launching box, multichannel data collector, frequency modulation transmitter, computer, auxiliary wheels, lower link, and a wireless temperature sensor. A process includes four steps: launching of a probe, collection of data, calculation of an elastic modulus, and evaluation of freezing-thawing damage.

Abstract: Systems and methods are provided for automatically allocating test protocols to a plurality of test locations. Once such method includes a computing device executing a first stage machine learning prediction model (MLPM) based on protocol data for multiple test protocols for a test experiment to generate a first stage output. The first stage MLPM is trained based on historical allocation data for one or more prior test experiments. Multiple test sets are associated with the test protocols, and the first stage output includes, for multiple test locations, allocation prediction scores for the test protocols. Based on the first stage output, the computing device executes a second stage optimization model to generate a second stage output. The second stage output includes an allocation plan for the test protocols. The allocation plan identifies one or more of the test locations for each of the test protocols.

Abstract: The disclosure relates to a packaging structure for a power module, a packaging method and an electric vehicle. The packaging structure includes: a circuit board; at least one power chip, where each power chip is fastened on the circuit board, and each power chip is integrated with a sensor that is capable of detecting a working state of the power chip; and a signal chip, where the signal chip is fastened on the circuit board and separated from the power chip, a compiling program is preset in the signal chip, the signal chip is in a communication connection with each sensor, and the signal chip is configured to be capable of being in a communication connection with a predetermined device, so as to output working state data of each power chip to the predetermined device. By detecting the working state of each power chip, the power chip can be protected precisely in real time.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a robotic control policy to perform a particular task. One of the methods includes performing a meta reinforcement learning phase including using training data collected for a plurality of different robotic control tasks and updating a robotic control policy according to the training data, wherein the robotic control policy is conditioned on an encoder network that is trained to predict which task is being performed from a context of a robotic operating environment; and performing an adaptation phase using a plurality of demonstrations for the particular task, including iteratively updating the encoder network after processing each demonstration of the plurality of demonstrations, thereby training the encoder network to learn environmental features of successful task runs.

Abstract: The present disclosure is applicable to the technical field of metering and distributing of an adhesive dispensing machine, and provides a machine learning-based flexible intelligent adhesive dispensing method.

Abstract: The present invention relates to the fields of medicinal chemistry and pharmacotherapeutics, and in particular to a 2-cyano-3,12-dioxoolean-1,9(11)-dien-17-phenylacrylamide derivative and a preparation method thereof; and the present invention further relates to use of the novel compound in the preparation of an anticancer medicament.

Abstract: A method of quantization evaluation, including, receiving a floating point data set, determining a floating point neural network model output utilizing the floating point data set, quantizing the floating point data set utilizing a quantization model yielding a quantized data set, determining a quantized neural network model output utilizing the quantized data set, determining whether an accuracy error between the floating point neural network model output and the quantized neural network model output exceeds an predetermined error tolerance, determining a floating point neural network tensor output utilizing the floating point data set if the predetermined error tolerance is exceeded, determining a quantized neural network tensor output utilizing the quantized data set if the predetermined error tolerance is exceeded, determining a per-tensor error based on the floating point neural network tensor output and the quantized neural network tensor output and updating the quantization model based on the per-tenso

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Systems and methods for use in identifying weights to be employed in a selection algorithm associated with plant advancement are disclosed. One example method includes identifying a start set of weights for a selection algorithm associated with a breeding program, and for each scale parameter value in a schedule, and for each of N iterations, modifying the start set of weights based on the scale parameter value, identifying a set of germplasm based on at least the modified set of weights, advancing the modified set of weights to a next iteration as the start set of weights when certain criteria are satisfied, and identifying the modified set of weights as an output when the iteration is equal to N.

Abstract: The disclosure relates to a display device including: an organic light-emitting diode display panel, a fingerprint recognition layer located below the organic light-emitting diode display panel, and a light filtering layer located between the organic light-emitting diode display panel and the fingerprint recognition layer, where the light filtering layer is configured to filter out light rays with an incidence angle greater than a filter angle among light rays carrying fingerprint line information, and to transmit light rays with an incidence angle smaller than or equal to the filter angle, where the incidence angle is the angle between the light rays carrying fingerprint line information, and the direction perpendicular to the fingerprint recognition layer.

Abstract: A prism sheet, a backlight module, a display and a preparation method of the prism sheet are provided. The prism sheet includes a base layer and a prism layer located on a surface of a first side of the base layer, holes are provided inside the base layer, so that light received from a second side of the base layer reaches the prism layer through the holes, and the first side of the base layer and the second side of the base layer are opposite to each other.