Abstract: The disclosure relates to a system and method for image reconstruction. The method may include the steps of: obtaining raw data corresponding to radiation rays within a volume, determining a radiation ray passing a plurality of voxels, grouping the voxels into a plurality of subsets such that at least some subset of voxels are sequentially loaded into a memory, and performing a calculation relating to the sequentially loaded voxels. The radiation ray may be determined based on the raw data. The calculation may be performed by a plurality of processing threads in a parallel hardware architecture. A processing thread may correspond to a subset of voxels.

Abstract: In one embodiment, the disclosed apparatus is an in-situ, closed-loop bubble and foam detection and reduction system that includes a liquid-level sensor to determine a volume of a liquid in a fluid reservoir, a mass-detection device to determine a mass of the fluid reservoir and any liquid contained within the fluid reservoir, a processor electrically coupled to the liquid-level sensor and the mass-detection device to determine an actual volume of the liquid within the fluid reservoir, and a showerhead coupled to the processor and positioned above the fluid reservoir. The showerhead is activated by the processor when a volume of the liquid determined by the liquid-level sensor exceeds the actual volume of the liquid by a predetermined amount. Other apparatuses and methods are disclosed.

Abstract: The present disclosure may provide imaging methods, systems and storage media. The imaging methods may include: obtaining first imaging data acquired by an imaging device, wherein the first imaging data includes data corresponding to a plurality of cardiac cycles; and performing image reconstruction on data corresponding to the plurality of cardiac cycles in the first imaging data to acquire one or more cardiac cines. Each cardiac cine of the one or more cardiac cines may include cardiac images of a plurality of phases in at least one cardiac cycle.

Abstract: A power converter incorporating a synchronous rectifier implements adaptive gate voltage regulation for fast turn-off of the synchronous rectifier. In some embodiments, the adaptive gate voltage regulation circuit detects a voltage indicative of a drain current of the synchronous rectifier in each SR conduction cycle and monitors a slope of the detected voltage indicative of a rate of decrease of the drain current of the synchronous rectifier. The adaptive gate voltage regulation circuit further selects a gate discharge current as a function of the slope of the detected voltage to apply to the gate terminal of the synchronous rectifier.

Abstract: An object emotion analysis method and apparatus and an electronic device are provided. The method includes: extracting a static facial feature and a dynamic feature from multimedia data associated with a target object, wherein the dynamic feature includes one or more of an expression change feature, a sound feature and a language content feature: inputting the static facial feature and the dynamic feature into a pre-trained object emotion analysis model, fusing the static facial feature and the dynamic feature by the object emotion analysis model, and outputting an emotion analysis result.

Abstract: The present disclosure relates to the field of battery technologies, and more particularly, to a battery cell, a battery, an electric apparatus, a welding method, and a welding device. The battery cell includes: an end cover having an injection hole defined thereon; and a seal sealingly connected to the injection hole. A first weld segment and a second weld segment are formed between the seal and the end cover. An annular weld seam of the seal is formed by enclosing with at least a part of the first weld segment and at least a part of the second weld segment together. The first weld segment is formed by continuous laser light. The second weld segment is formed by pulsed laser light.

Abstract: For etching tools, a neural network model is trained to predict optimum scheduling parameter values. The model is trained using data collected from preventive maintenance operations, recipe times, and wafer-less auto clean times as inputs. The model is used to capture underlying relationships between scheduling parameter values and various wafer processing scenarios to make predictions. Additionally, in tools used for multiple parallel material deposition processes, a nested neural network based model is trained using machine learning. The model is initially designed and trained offline using simulated data and then trained online using real tool data for predicting wafer routing path and scheduling. The model improves accuracy of scheduler pacing and achieves highest tool/fleet utilization, shortest wait times, and fastest throughput.

Abstract: A power converter incorporating a synchronous rectifier implements adaptive gate voltage regulation for fast turn-off of the synchronous rectifier. In some embodiments, the adaptive gate voltage regulation circuit and method monitors the slope of the synchronous rectifier current during the on period of the synchronous rectifier. In response to detecting the synchronous rectifier current decreasing rapidly, a larger gate discharge current is applied to quickly discharge the synchronous rectifier gate voltage. In response to detecting the synchronous rectifier current decreasing more moderately, a smaller gate discharge current is applied to discharge the synchronous rectifier gate voltage in a moderate manner. When the synchronous rectifier can be turned off quickly, large reverse current and large drain voltage spike at the synchronous rectifier is avoided. The adaptive gate voltage regulation circuit and method is particularly useful when the power converter is operated in the discontinuous conduction mode.

Abstract: An electronic device is provided. The electronic device includes: a first substrate, a first light-emitting unit, a wall structure, and a first optical film. The first light-emitting unit is disposed on the first substrate. The wall structure is disposed on the first substrate, and includes a first opening corresponding to the first light-emitting unit. At least a portion of the first optical film is disposed on the first light-emitting unit, and the at least a portion of the first optical film is disposed in the first opening.

Abstract: This disclosure discloses an information transmission method and a communications device. The method includes: obtaining a reference object group containing at least two reference objects, where the reference objects contained in the reference object group are quasi co-located; and performing information transmission based on the reference object group.

Abstract: In one embodiment, the disclosed apparatus is an in-situ, closed-loop bubble and foam detection and reduction system that includes a liquid-level sensor to determine a volume of a liquid in a fluid reservoir, a mass-detection device to determine a mass of the fluid reservoir and any liquid contained within the fluid reservoir, a processor electrically coupled to the liquid-level sensor and the mass-detection device to determine an actual volume of the liquid within the fluid reservoir, and a showerhead coupled to the processor and positioned above the fluid reservoir. The showerhead is activated by the processor when a volume of the liquid determined by the liquid-level sensor exceeds the actual volume of the liquid by a predetermined amount. Other apparatuses and methods are disclosed.

Abstract: The disclosure relates to a system and method for image reconstruction. The method may include the steps of: obtaining raw data corresponding to radiation rays within a volume, determining a radiation ray passing a plurality of voxels, grouping the voxels into a plurality of subsets such that at least some subset of voxels are sequentially loaded into a memory, and performing a calculation relating to the sequentially loaded voxels. The radiation ray may be determined based on the raw data. The calculation may be performed by a plurality of processing threads in a parallel hardware architecture. A processing thread may correspond to a subset of voxels.

Abstract: The present disclosure discloses a method and apparatus for processing load balancing of a Kubernetes cluster, and a storage medium, wherein the method comprises: acquiring traffic configuration rules for controllers in the Kubernetes cluster by a central control component of the Kubernetes cluster; sending the traffic configuration rules to a proxy container corresponding to each of the controllers; and controlling data interaction between an API server and the controllers through the proxy container based on the traffic configuration rules. According to the present disclosure, the technical problem that load balancing is difficult to achieve due to single-point operation of the controllers caused by a single master is solved.

Abstract: The present disclosure may provide imaging methods, systems and storage media. The imaging methods may include: obtaining first imaging data acquired by an imaging device, wherein the first imaging data includes data corresponding to a plurality of cardiac cycles; and performing image reconstruction on data corresponding to the plurality of cardiac cycles in the first imaging data to acquire one or more cardiac cines. Each cardiac cine of the one or more cardiac cines may include cardiac images of a plurality of phases in at least one cardiac cycle.

Abstract: Systems and techniques are provided for simulating LiDAR sensors. An example method includes generating, within a simulation environment, a first Light Detection and Ranging (LiDAR) measurement that corresponds to a first virtual beam transmission from a first channel of a first LiDAR sensor; generating, within the simulation environment, a second LiDAR measurement that corresponds to a second virtual beam transmission from a second channel of the first LiDAR sensor, wherein the first virtual beam transmission and the second virtual beam transmission are directed to a virtual object in the simulation environment; determining a channel measurement variance between the first channel and the second channel; and adjusting at least one of the first LiDAR measurement and the second LiDAR measurement based on the channel measurement variance.

Abstract: An embodiment of the present disclosure provides a measurement reporting method and device. The method includes: starting a timer according to a measurement configuration of a target cell transmitted by a network side; determining, before the timer expires, that identification information of the target cell cannot be obtained; and reporting, to the network side, that the identification information of the target cell cannot be obtained by the UE.

Abstract: A method for medical imaging may include obtaining a plurality of successive images of a region of interest (ROI) including at least a portion of an object's heart. The plurality of successive images may be based on imaging data acquired from the ROI by a scanner without electrocardiography (ECG) gating. The plurality of successive images may be related to one or more cardiac cycles of the object's heart. The method may also include automatically determining, in the plurality of successive images, target images that correspond to at least one of the one or more cardiac cycles of the object's heart.

Abstract: For etching tools, a neural network model is trained to predict optimum scheduling parameter values. The model is trained using data collected from preventive maintenance operations, recipe times, and wafer-less auto clean times as inputs. The model is used to capture underlying relationships between scheduling parameter values and various wafer processing scenarios to make predictions. Additionally, in tools used for multiple parallel material deposition processes, a nested neural network based model is trained using machine learning. The model is initially designed and trained offline using simulated data and then trained online using real tool data for predicting wafer routing path and scheduling. The model improves accuracy of scheduler pacing and achieves highest tool/fleet utilization, shortest wait times, and fastest throughput.