Abstract: A radar signal processing system with a self-interference cancelling function includes an analog front end (AFE) processor, an analog to digital converter (ADC), an adaptive interference canceller (AIC), and a digital to analog converter (DAC). The AFE processor receives an original input signal and generates an analog input signal. The ADC converts the analog input signal to a digital input signal. The AIC generates a digital interference signal digital interference signal by performing an adaptive interference cancellation process according to the digital input signal. The DAC converts the digital interference signal to an analog interference signal. Finally, the analog interference signal is fed back to the AFE and cancelled from the original input signal in the AFE processor while performing the front end process, reducing the interference of the static interference from the leaking of a close-by transmitter during the front end process.

Abstract: A method of forming a semiconductor device includes providing a substrate including a circuit region and a well strap region, forming a mandrel extending from the circuit region to the well strap region, depositing mandrel spacers on sidewalls of the mandrel, removing the mandrel in the circuit region, while the mandrel in the well strap region remains intact, patterning the substrate with the mandrel spacers in the circuit region and the mandrel in the well strap region as an etch mask, thereby forming at least a first fin in the circuit region and a second fin in the well strap region, and epitaxially growing a first epitaxial feature over the first fin in the circuit region and a second epitaxial feature over the second fin in the well strap region. A width of the second fin is larger than a width of the first fin.

Abstract: A method and a system for identifying an operating status of an electrical appliance based on non-intrusive load monitoring are provided. The method includes the following steps. Total power consumption history data of a target field and appliance power consumption history data of target electrical appliances are obtained. The appliance power consumption history data of each target electrical appliance is converted into a binary data set. The total power consumption history data is clustered into cluster samples to obtain first feature data sets, which are then dimensionally reduced into second feature data sets, and a machine learning model is trained by using the second feature data sets and the binary data sets of the target electrical appliances to establish an operation identification model for the target electrical appliances. The operation identification model identifies an operating status of the target electrical appliances according to total power consumption data.

Abstract: An isolated antibody, comprising heavy chain complementary determining regions CDR1, CDR2, and CDR3 from a heavy chain variable region sequence having SEQ ID NO: 1 or 3; light chain complementary determining regions CDR1, CDR2, and CDR3 from a light chain variable region sequence having SEQ ID NO: 2 or 4; wherein the antibody binds specifically to both vascular endothelial growth factor receptor-2 (VEGFR2) and vascular endothelial growth factor receptor-3 (VEGFR3).

Abstract: An isolated antibody, comprising heavy chain complementary determining regions CDR1, CDR2, and CDR3 from a heavy chain variable region sequence having SEQ ID NO: 1 or 3; light chain complementary determining regions CDR1, CDR2, and CDR3 from a light chain variable region sequence having SEQ ID NO: 2 or 4; wherein the antibody binds specifically to both vascular endothelial growth factor receptor-2 (VEGFR2) and vascular endothelial growth factor receptor-3 (VEGFR3).

Abstract: Disclosed herein are novel sialyltransferase inhibitors, and compositions and methods for treating diseases and/or conditions associated with the activation of sialyltransferase, such as a cancer, an immune disease or an inflammatory disease.

Abstract: Disclosed herein are novel sialyltransferase inhibitors, and compositions and methods for treating diseases and/or conditions associated with the activation of sialyltransferase, such as a cancer, an immune disease or an inflammatory disease.