Abstract: A headphone control method and a headphone are disclosed. By simultaneously turning on an active noise cancellation link and a first transparent transmission link, external audio signals may be suppressed by generating anti-noise signals by the active noise cancellation link and playing the anti-noise signals by the speaker. Also, a non-target-type audio signal may be removed or filtered by performing noise reduction processing on the non-target-type audio signal in the external audio signals by the first transparent transmission link to obtain the noise-reduced audio signal in which the target-type audio signal in the external audio signals is retained. The speaker plays the noise-reduced audio signal, so that the target-type audio signal can be transparently transmitted to a user's ears, and the user can focus on the audio signals of the target type that they desire to perceive.

Abstract: A semiconductor device includes a first wafer, and a second wafer bonded with the first wafer and comprising a substrate and a device layer over the substrate. The first wafer is over the second wafer and includes memory arrays, array-base regions over the memory arrays, an isolation structure surrounding and insulating the array-base regions from one another, and bonding pads over the isolation structure. An array-base region of the array-base regions is connected with a memory array of the memory arrays. A bonding pad of the bonding pads is exposed.

Abstract: Embodiments of three-dimensional (3D) memory devices formed by bonded semiconductor devices and methods for forming the same are disclosed. In an example, a method for forming a semiconductor device is disclosed. The method includes the following operations. First, an insulating material layer can be formed over a substrate. In an example, single-crystalline silicon is not essential to the substrate. The insulating material layer can be patterned to form an isolation structure and a plurality of trenches in the isolation structure. A semiconductor material can be deposited to fill up the plurality of trenches to form a plurality of array-base regions in the isolation structure, the isolation structure insulating the plurality of array-base regions from one another. Further, a plurality of memory arrays can be formed over the plurality of array-base regions, and an insulating structure can be formed to cover the plurality of memory arrays and the plurality of array-base regions.

Abstract: An ionizable lipid based on endogenous dicarboxylic acid as well as a preparation method and use thereof. The ionizable lipid based on endogenous dicarboxylic acid is a compound represented by Formula (I), or a stereoisomer, tautomer, pharmaceutically acceptable salt or solvate thereof; wherein, X is selected from — Y is selected from —O— and —NH—; R is selected from C6-C20 alkyl, C6-C20 alkyl substituted by a substituent group, C6-C20 alkenyl, C6-C20 alkenyl substituted by a substituent group, C6-C20 alkynyl, and C6-C20 alkynyl substituted by a substituent group; n is an integer of 1-8.

Abstract: The motion estimation of an anatomical structure may be performed using a machine-learned (ML) model trained based on medical training images of the anatomical structure and corresponding segmentation masks for the anatomical structure. During the training of the ML model, the model may be used to predict a motion field that may indicate a change between a first training image and a second training image, and to transform the first training image and a corresponding first segmentation mask based on the motion field. The parameters of the ML model may then be adjusted to maintain a correspondence between the transformed first training image and the second training image and between the transformed first segmentation mask or a second segmentation mask associated with the second training image. The correspondence may be assessed based on at least a boundary region shared by the anatomical structure and one or more other anatomical structures.

Abstract: The present disclosure includes a medical monitoring hub as the center of monitoring for a monitored patient. The hub is configured to receive and process a plurality of physiological parameters associated with the patient. The hub includes advanced analytical presentation views configured to provide timely, clinically-relevant, actionable information to care providers. In certain embodiments, the monitoring hub stores and is able to replay previously presented data reflective of the patient's condition.

Abstract: Embodiments of the disclosure provide a multi-class classification system. An exemplary system includes at least one processor and at least one non-transitory memory storing instructions that, when executed by the at least one processor, cause the system to perform operations. The operation includes applying a multi-class classifier to classify a set of objects into multiple classes and applying a plurality of binary classifiers to the set of objects, wherein the plurality of binary classifiers are decomposed from the multi-class classifier, each binary classifier classifying the set of the objects into a first group consisting of one or more classes selected from the multiple classes and a second group consisting of one or more remaining classes of the multiple classes. The operation also includes jointly classifying the set of objects using the multi-class classifier and the plurality of binary classifiers.

Abstract: The present disclosure includes a medical monitoring hub as the center of monitoring for a monitored patient. The hub is configured to receive and process a plurality of physiological parameters associated with the patient. The hub includes advanced analytical presentation views configured to provide timely, clinically-relevant, actionable information to care providers. In certain embodiments, the monitoring hub stores and is able to replay previously presented data reflective of the patient's condition.

Abstract: A semiconductor device includes a substrate, a gate dielectric layer, a gate electrode, a field plate, a source electrode and a drain electrode. The gate dielectric layer is disposed on the substrate and includes a first portion having a first thickness, a second portion having a second thickness, and a third portion having a third thickness. The first, second and third thicknesses are different from each other, and the first thickness is smaller than the second and third thicknesses. The gate electrode is disposed on the first portion of the gate dielectric layer. The field plate is separated from and electrically coupled to the gate electrode, and is disposed on the second and third portions of the gate dielectric layer. The source and drain electrodes are disposed on the sides of the gate electrode and the field plate, respectively.

Abstract: In one embodiment, a method includes, by one or more computing systems, receiving, from a client system via an assistant xbot, a first audio input from a user, parsing the first audio input to identify a request for a content digest from an online social network, retrieving a plurality of content objects from the online social network, each of the content objects being accessible by the user, generating a customized newsfeed summary based on a determined semantical meaning of each of the plurality of content objects, and sending, to the client system via the assistant xbot, instructions for presenting an audio clip to the user responsive to the request for the content digest, wherein the audio clip comprises the customized newsfeed summary.

Abstract: The present disclosure is related to systems and methods for processing speech dialogue. The method includes obtaining target speech dialogue data. The method includes obtaining a text vector representation sequence, a phonetic symbol vector representation sequence, and a role vector representation sequence by performing a vector transformation on the target speech dialogue data based on a text embedding model, a phonetic symbol embedding model, and a role embedding model, respectively. The method includes determining a representation vector corresponding to the target speech dialogue data by inputting the text vector representation sequence, the phonetic symbol vector representation sequence, and the role vector representation sequence into a trained speech dialogue coding model. The method includes determining a summary of the target speech dialogue data by inputting the representation vector into a classification model.

Abstract: A circuit board for semiconductor test includes first and second sub-circuit boards, and an insulating dielectric layer therebetween. Each sub-circuit board includes a substrate and circuits including upper and lower contacts. The insulating dielectric layer includes through holes, and connecting conductors disposed therein and electrically connected with the upper and lower contacts of two sub-circuit boards. The circuit board is defined with central and peripheral regions. The lower contacts of the first sub-circuit board in the central region are electrically connected with a probe head. The upper contacts of the second sub-circuit board in the peripheral region are electrically connected with a tester, larger in pitch than the lower contacts of the first sub-circuit board in the central region, and larger in amount than the lower contacts of the first sub-circuit board in the peripheral region. The circuit board has great power test uniformity.

Abstract: A method and an electronic device of updating a neural network model are provided. The method includes the following steps. The neural network model is received. The neural network model includes a first neuron and a second neuron. The training data is input to the first neuron to output a first estimated value from the second neuron. A first weight of the first neuron is quantized to generate a third neuron, and a second weight of the second neuron is quantized to generate a fourth neuron. The training data is input to the third neuron to output a second estimated value from the fourth neuron. A first activation function of the first neuron and a second activation function of the second neuron are updated according to the first estimated value and the second estimated value, thereby generating the updated neural network model. The updated neural network model is output.

Abstract: The present disclosure includes a medical monitoring hub as the center of monitoring for a monitored patient. The hub is configured to receive and process a plurality of physiological parameters associated with the patient. The hub includes advanced analytical presentation views configured to provide timely, clinically-relevant, actionable information to care providers. In certain embodiments, the monitoring hub stores and is able to replay previously presented data reflective of the patient's condition.

Abstract: An ignition method of a plasma chamber includes steps of: (a) starting softly an ignition voltage to a first voltage, (b) decreasing the magnitude of the ignition voltage to a second voltage after a first ignition time, (c) increasing the magnitude of the ignition voltage to the first voltage after a second ignition time, and (d) repeating the step (b) and the step (c) until the ignition is successful.

Abstract: In one embodiment, a method includes receiving an indication of a trigger action by a first user at a client system, wherein the trigger action is associated with a priming content object, identifying related content objects associated with the priming content object, selecting recommended content objects based on the priming content object, the related content objects, and profile information of the first user, wherein each of the selected recommended content objects comprises entity information of entities associated with the priming content object, and presenting content suggestions at the client system, wherein each content suggestion comprises one of the selected recommended content objects.

Abstract: Various aspects of the disclosed technology relate to machine learning-based chain diagnosis. Faults are injected into scan chains in a circuit design. Simulations are performed on the fault-injected circuit design to determine test response patterns in response to the test patterns which are captured by the scan chains. Observed failing bit patterns are determined by comparing the unloaded test response patterns with corresponding good-machine test response patterns. Bit-reduction is performed on the observed failing bit patterns to construct training samples. Using the training samples, machine-learning models for faulty scan cell identification are trained. The bit reduction comprises pattern-based bit compression for good scan chains or cycle-based bit compression for the good scan chains. The bit reduction may further comprise bit-filtering. The bit-filtering may comprises keeping only sensitive bits on faulty scan chains for the training samples construction.

Abstract: A self-adaptive heavy-duty gear transmission walking device includes a guide track. A carrying seat is slidably installed on the guide track. A loading platform is arranged on the carrying seat, and matching frames are arranged at the bottom of the carrying seat and positioned opposite from each other. A first driving mechanism, a walking mechanism, a first support bracket, a stop mechanism, and a second support bracket are arranged on the carrying seat. A vertical support mechanism and a horizontal support mechanism are arranged in the matching frame. The first driving mechanism is connected to one end of the walking mechanism. The walking mechanism penetrates through the carrying seat and is magnetically connected to the guide track. The other end of the walking mechanism is connected to a first transmission shaft. The first transmission shaft penetrates through the first support bracket and is fixedly installed with a brake disc.