Abstract: Various aspects involve a lagged prediction model trained for risk assessment or other purposes. For instance, a risk assessment computing system receives a risk assessment query for a target entity and provides an input predictor record for the target entity to a lagged prediction model. The input predictor record includes a first group of lagged values from a first time-series attribute associated with the target entity. The lagged prediction model is trained by implementing a group feature selection technique configured to select the first time-series attribute as input and to deselect a second time-series attribute associated with the target entity. The risk assessment computing system computes an output risk indicator from the input predictor record and transmits the output risk indicator to a remote computing system. The output risk indicator can be used to control access by the target entity to one or more interactive computing environments.

Abstract: Provided in the present invention is an antibody or an antigen binding protein thereof. The antibody or the antigen binding protein thereof can specifically bind to human CD3 or human GPRC5D protein or MUC16, or specifically bind to human CD3 and a second antigen. Further provided in the present invention are a nucleic acid molecule encoding the antibody, an expression vector for expressing the antibody, a host cell and a preparation method therefor. Also provided in the present invention is a diagnosis and treatment method using the antibody of the invention.

Abstract: A high-voltage energy storage quick connector including a socket and a plug. The socket includes a hanging platform with a convex ring located on the outer circumference of the socket. An annular slot is defined on the plug. The socket and the hanging platform are inserted in the annular slot of the plug. The plug includes an elastic hook configured in a cantilever structure on the side wall of the annular slot. The cantilever structure of the elastic hook extends axially along the plug in a free state. A hook of the elastic hook is engaged with a stepped surface of the hanging platform facing away from the plug. The plug includes an operating handle disposed along an elastic deformation direction of the elastic hook, and the operating handle is connected to the plug in a locking manner along the elastic deformation direction of the elastic hook.

Abstract: Systems and methods for automated historical risk assessment for risk mitigation in online access control are provided. An entity assessment server can receive a request to assess a risk indicator change from a first risk indicator to a second risk indicator. For each attribute used to generate the first risk indicator and second risk indicator, a first impact can be determined for changing from the first risk indicator to a third risk indicator between the first risk indicator and the second risk indicator. A second impact similarly can be determined for changing from the third risk indicator to the second risk indicator. Aggregating the first impact and the second impact can determine a total impact of each attribute. Assessment results can be generated to include a list of attributes ordered according to the respective total impact and transmitted to a remote computing device for use in improving the risk indicator.

Abstract: A video shooting method includes: enabling a camera application on a terminal and in a slow-motion video recording mode of the camera application, when a motion detection function of the camera application is enabled, starting to capture video frames after a video recording instruction input by a user is detected, recording a second video frame set at a first frame rate automatically when a motion of a human body in a captured first video frame set is a preset motion, and generating a target video, wherein the target video includes a slow-motion video clip, and wherein the slow-motion video clip includes video frames in the second video frame set.

Abstract: A control method includes obtaining distribution information of a point cloud obtained by a detection device. The detection device includes a light source, and a first reflection assembly and a second reflection assembly configured to cause a light beam emitted by the light source to scan in a first direction and a second direction, respectively, to obtain the point cloud in a detection range. The method further includes, in response to a point cloud line distribution of the point cloud deviating from the second direction, controlling the first reflection assembly to adjust from a current attitude to a target attitude, to correct the point cloud line distribution to the second direction.

Abstract: A face image clustering method and system based on a localized simple multiple kernel k-means is provided. The face image clustering method based on localized simple multiple kernel k-means includes the following steps: S1, acquiring face images, and preprocessing the acquired face images to obtain an average kernel matrix for each view; S2, calculating n (?×n)-nearest neighbor matrices according to the obtained average kernel matrices; S3, calculating a localized kernel matrix for each view according to the nearest neighbor matrices; S4, constructing a localized simple multiple kernel k-means clustering objective function according to the calculated localized kernel matrix for each view; S5, solving a minimum of the constructed objective function by adopting a reduced gradient descent method to obtain an optimal clustering partition matrix; and S6, performing k-means clustering on the obtained clustering partition matrix to achieve clustering.

Abstract: A method for the manufacture of agar or agarose beads, the method comprising the steps of: i) providing a water phase comprising an aqueous solution of agar or agarose at a temperature above the gelling temperature of said aqueous solution; ii) providing an oil phase comprising a natural or vegetable oil at a temperature above the gelling temperature of the aqueous solution provided in step i); iii) combining the water phase provided in step i) with the oil phase provided in step ii) in a reactor, and adding an emulsifier; iv) emulsifying the mixture obtained in step iii), preferably by agitating the mixture, thereby creating an emulsion; v) performing a stepwise cooling comprising a first cooling step for cooling the emulsion obtained in step iv) to a temperature 0.1-30 degrees C.

Abstract: Embodiments of the present disclosure relate to devices, methods, apparatus, and medium for recurrent spiking neural network based equalization and demapping. A first communication device is configured to: obtain at least one parameter for a recurrent spiking neural network at the first communication device, wherein the at least one parameter is generated based on channel condition information between the first communication device and a second communication device; configure the recurrent spiking neural network based on the at least one parameter; and perform equalization and demapping on a signal received from the second communication device based on the recurrent spiking neural network. In this way, embodiments of the present disclosure provide a method for recurrent spiking neural network based equalization and demapping, thereby implementing a solution of a low power consumption joint equalization and demapping.

Abstract: A directly-connected high-voltage battery energy storage system (BESS) and a control method thereof are provided. The directly-connected high-voltage BESS includes a battery module, a direct current (DC)/DC converter, a DC bus capacitor, a DC/alternating current (AC) converter, and a grid-side filter inductor. A plurality of battery modules is connected in series to form a battery cluster. The battery cluster is connected in series to the DC/DC converter to form a battery branch, and a plurality of battery branches is connected in parallel to form a battery stack. The battery stack is connected in parallel to the DC bus capacitor and then connected to a DC port of the DC/AC converter to form a battery energy storage submodule. AC ports of a plurality of battery energy storage submodules are connected in series to form a chain-type phase converter.

Abstract: A composite ceramic including: a lithium garnet major phase; and a grain growth inhibitor minor phase, as defined herein. Also disclosed is a method of making composite ceramic, pellets and tapes thereof, a solid electrolyte, and an electrochemical device including the solid electrolyte, as defined herein.

Abstract: A 4K high-resolution panoramic annular optical system includes a panoramic annular lens head unit, a subsequent lens group, and a 4K sensor (SE) that is coaxially installed. The panoramic annular lens head unit includes a first lens (PALIPAL1) and a second lens (PAL2). The subsequent lens group includes a third lens (RL1), a fourth lens (RL2), a fifth lens (RL3), a sixth lens (RL4), a seventh lens (RL5), an eighth lens (RL6), and a ninth lens (RL7) that are arranged in order from an object plane to an image plane. The first lens (PAL1) and the fifth lens (RL3) are meniscus glass lenses with positive refractive power. The six lens (RL4) and the ninth lens (RL7) are meniscus glass lenses with negative refractive power, and the second lens (PAL2), the fourth lens (RL2), the seventh lens (RL5), and the eighth lens (RL6) are biconvex lenses with positive refractive power.

Abstract: Various aspects involve a monotonic recurrent neural network (MRNN) trained for risk assessment or other purposes. For instance, the MRNN is trained to compute a risk indicator from a predictor variable. Training the MRNN includes adjusting weights of nodes of the MRNN subject to a set of monotonicity constraints, wherein the set of monotonicity constraints causes output risk indicators computed by the RNN to be a monotonic function of input predictor variables. The trained monotonic RNN can be used to generate an output risk indicator for a target entity.

Abstract: A method and system are disclosed for detecting microbial pathogens in a sample suspected of containing the pathogens. The method includes combining loop-mediated isothermal amplification (LAMP) reagents and a polymer gel, such as a hydrogel, together with the sample to form a mixture. The gel polymerizes over a short time to immobilize the viral particles within the mixture. If target DNA/RNA are present in the sample, amplicons are produced. The target microorganisms are detected by visually detecting the presence or absence of the amplicons. The target microorganism concentrations may be determined based on the number of fluorescent amplicon dots after the reaction using a smartphone or a fluorescent microscope. The method may be employed for rapidly and inexpensively quantifying microbial pathogens in environmental water samples with high sensitivity.

Abstract: A heterojunction cell and a processing method thereof, and a battery assembly are provided. The heterojunction cell includes a substrate, a TCO film layer is provided on both a front surface and a back surface of the substrate, and at least two columns of short main gates with the same number are disposed at intervals on the TCO film layer of both the front surface and the back surface of the substrate, the short main gates located on the front surface of the substrate are defined as first main gates; the short main gates located on the back surface of the substrate are defined as second main gates; and the substrate is capable of being cut to form battery slices, each of the battery slices is provided with one column of the first main gates and one column of the second main gates.

Abstract: Various aspects involve a lagged prediction model trained for risk assessment or other purposes. For instance, a risk assessment computing system receives a risk assessment query for a target entity and provides an input predictor record for the target entity to a lagged prediction model. The input predictor record includes a first group of lagged values from a first time-series attribute associated with the target entity. The lagged prediction model is trained by implementing a group feature selection technique configured to select the first time-series attribute as input and to deselect a second time-series attribute associated with the target entity. The risk assessment computing system computes an output risk indicator from the input predictor record and transmits the output risk indicator to a remote computing system. The output risk indicator can be used to control access by the target entity to one or more interactive computing environments.

Abstract: Systems and methods for automated historical risk assessment for risk mitigation in online access control are provided. An entity assessment server can receive a request to assess a risk indicator change from a first risk indicator to a second risk indicator. For each attribute used to generate the first risk indicator and second risk indicator, a first impact can be determined for changing from the first risk indicator to a third risk indicator between the first risk indicator and the second risk indicator. A second impact similarly can be determined for changing from the third risk indicator to the second risk indicator. Aggregating the first impact and the second impact can determine a total impact of each attribute. Assessment results can be generated to include a list of attributes ordered according to the respective total impact and transmitted to a remote computing device for use in improving the risk indicator.

Abstract: An optical network unit is configured to send a plurality of optical signals with different wavelengths to an optical line terminal. The optical signals in the plurality of optical signals carry indicating information. The indicating information is used to indicate the wavelength serial number of the optical signal and the temperature information of the laser chip when the optical signal is generated. The optical unit is further configured to receive temperature adjustment information from the optical line terminal; and adjust, based on the temperature adjustment information, the emission wavelength of the laser by adjusting the temperature of the laser chip.

Abstract: Various aspects involve a monotonic recurrent neural network (MRNN) trained for risk assessment or other purposes. For instance, the MRNN is trained to compute a risk indicator from a predictor variable. Training the MRNN includes adjusting weights of nodes of the MRNN subject to a set of monotonicity constraints, wherein the set of monotonicity constraints causes output risk indicators computed by the RNN to be a monotonic function of input predictor variables. The trained monotonic RNN can be used to generate an output risk indicator for a target entity.

Abstract: The present invention relates to a novel antibody and antibody fragment that specifically binds to TNFR2 and to a composition comprising said antibody or antibody fragment. In addition, the present invention relates to a nucleic acid encoding the antibody or an antibody fragment thereof and a host cell comprising the same, and to a related use thereof. Besides, the present invention relates to the use of the antibody and antibody fragment for treatment and diagnosis.