RdgB2 is required for dim-light input into intrinsically photosensitive retinal ganglion cells.

A subset of retinal ganglion cells is intrinsically photosensitive (ipRGCs) and contributes directly to the pupillary light reflex and circadian photoentrainment under bright-light conditions. ipRGCs are also indirectly activated by light through cellular circuits initiated in rods and cones. A mammalian homologue (RdgB2) of a phosphoinositide transfer/exchange protein that functions in Drosophila phototransduction is expressed in the retinal ganglion cell layer. This raised the possibility that RdgB2 might function in the intrinsic light response in ipRGCs, which depends on a cascade reminiscent of Drosophila phototransduction. Here we found that under high light intensities, RdgB2(-/-) mutant mice showed normal pupillary light responses and circadian photoentrainment. Consistent with this behavioral phenotype, the intrinsic light responses of ipRGCs in RdgB2(-/-) were indistinguishable from wild-type. In contrast, under low-light conditions, RdgB2(-/-) mutants displayed defects in both circadian photoentrainment and the pupillary light response. The RdgB2 protein was not expressed in ipRGCs but was in GABAergic amacrine cells, which provided inhibitory feedback onto bipolar cells. We propose that RdgB2 is required in a cellular circuit that transduces light input from rods to bipolar cells that are coupled to GABAergic amacrine cells and ultimately to ipRGCs, thereby enabling ipRGCs to respond to dim light

A multi-function integrated circuit breaker for DC grid applications

The protection and current flow regulation of highvoltage direct-current (HVDC) grids requires the deployment of additional semiconductor-based equipment including dc circuit breakers (DCCBs) and current flow controllers (CFCs). However, the inclusion of multiple devices could significantly increase the total cost of an HVDC system. To potentially reduce costs, this paper presents an innovative multi-function integrated DCCB (MF-ICB). The proposed device exhibits a reduced number of semiconductor switches and can fully block dc faults at different locations while regulating dc currents. The configuration of the integrated solution and its operating principle are assessed, with its performance being examined in PSCAD/EMTDC using a three-terminal HVDC grid. Simulation results demonstrate the capability and effectiveness of the MF-ICB to regulate grid current and isolate dc faults

A multi-function integrated circuit breaker for DC grid applications

The protection and current flow regulation of highvoltage direct-current (HVDC) grids requires the deployment of additional semiconductor-based equipment including dc circuit breakers (DCCBs) and current flow controllers (CFCs). However, the inclusion of multiple devices could significantly increase the total cost of an HVDC system. To potentially reduce costs, this paper presents an innovative multi-function integrated DCCB (MF-ICB). The proposed device exhibits a reduced number of semiconductor switches and can fully block dc faults at different locations while regulating dc currents. The configuration of the integrated solution and its operating principle are assessed, with its performance being examined in PSCAD/EMTDC using a three-terminal HVDC grid. Simulation results demonstrate the capability and effectiveness of the MF-ICB to regulate grid current and isolate dc faults

Multi-objective design of single-phase differential buck inverters with active power decoupling

The design of single-phase differential buck inverters has two important considerations, including reducing seconder ripple power using decoupling capacitors and increasing inverter performances. Using larger capacitors will improve the performance of ripple power reduction while reducing the efficiency and power density. Such trade-off has not been fully modelled and investigated, leading to the sub-optimal design of inverters. To address that, in this paper, the trade-off between decoupling capacitances, inverter efficiency and power density are investigated through detailed mathematical modeling and sensitivity study. The trade-off of the volume and power loss of other essential components, including power switches, inductors and heatsinks, are also studied to facilitate the inverter design. A fast multi-objective design optimization method based on geometric programming is presented to optimize the inverters total efficiency and power density. A 1kW prototype of a Gallium Nitride (GaN) based inverter has been designed based on the presented method, aiming at an efficiency of 98.4% and power density 4.6kW/dm^3. The prototype has been tested to have an efficiency of 98.02% and power density 4.54kW/dm^3: This validates the accuracy and effectiveness of the presented design approach considering detailed trade-off analysis

A low-loss integrated circuit breaker for HVDC applications

Hybrid dc circuit breakers (HCBs) are recognized as suitable devices for protecting high-voltage direct-current (HVDC) systems, along with other dc circuit breakers (DCCB). However, compared to mechanical circuit breakers, HCBs exhibit higher conduction losses. Such losses are inevitable under no-fault conditions as current may flow through some of the semiconductor switches. An integrated circuit breaker (ICB) minimizing these losses is presented in this paper, and this is achieved by replacing semiconductor switches by mechanical components in the current path. For completeness, the topology design, operating sequence and a mathematical analysis for component sizing of the device are provided. In addition, an estimation of the conduction losses is quantified. It is estimated that the power losses of an ICB are 2 to 30% of an HCB only. The ICB has been implemented in PSCAD/EMTDC to demonstrate its effectiveness for isolating dc faults, with simulations conducted on a three-terminal HVDC grid

Decentralized control for multi-terminal cascaded medium-voltage converters considering multiple crossovers

Decentralized control with multiple droop characteristics can significantly improve the accuracy of power flow in medium-voltage direct-current (MVdc) networks. However, multiple crossovers caused by different control characteristics can lead to the drifts of power and voltage and instability issues. When this type of control is implemented in the cascaded three-level neutral-point-clamped (C3L-NPC) converters, on one hand, the mechanism of such the power and voltage drifts was not investigated. On the other hand, power control accuracy, dc voltage balancing across submodules (SMs) and multiple crossovers should all be considered, which requires suitable control methods. To address the challenges, firstly, the mechanism behind the power and dc voltage drifts is analyzed. Secondly, a control scheme is presented to improve the power control accuracy and dc voltage balancing and concurrently, to avoid the multiple crossovers. This is achieved by suitable droop gain design and adding a secondary power compensator. The presented control scheme is verified in MATLAB/Simulink simulation and experimentally validated in a three-terminal MVdc testbed. Results show that the accuracy of steady-state power flow is improved by 15% due to the elimination of multiple crossovers, while the power accuracy at dynamics improved by 13% with the secondary power compensato

SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs

Anomaly detection aims to distinguish abnormal instances that deviate significantly from the majority of benign ones. As instances that appear in the real world are naturally connected and can be represented with graphs, graph neural networks become increasingly popular in tackling the anomaly detection problem. Despite the promising results, research on anomaly detection has almost exclusively focused on static graphs while the mining of anomalous patterns from dynamic graphs is rarely studied but has significant application value. In addition, anomaly detection is typically tackled from semi-supervised perspectives due to the lack of sufficient labeled data. However, most proposed methods are limited to merely exploiting labeled data, leaving a large number of unlabeled samples unexplored. In this work, we present semi-supervised anomaly detection (SAD), an end-to-end framework for anomaly detection on dynamic graphs. By a combination of a time-equipped memory bank and a pseudo-label contrastive learning module, SAD is able to fully exploit the potential of large unlabeled samples and uncover underlying anomalies on evolving graph streams. Extensive experiments on four real-world datasets demonstrate that SAD efficiently discovers anomalies from dynamic graphs and outperforms existing advanced methods even when provided with only little labeled data.Comment: Accepted to IJCAI'23. Code will be available at https://github.com/D10Andy/SA

Artificial neural networks-based multi-objective design methodology for wide-bandgap power electronics converters

Design methodology of power electronics converters is critical to fully explore the potential of wide-bandgap power semiconductors at the converter level. However, existing design methods largely rely on complex mathematical models which significantly increases the computational time, complexity and further leads to problems including poor constraint handling capabilities, inaccurate design, difficult parameter tuning and inadequate problem dimension. These all could generate sub-optimal designs that make the whole design process meaningless. To overcome the aforementioned problems, in this paper, an artificial neural network (ANN)-based multi-objective design approach is proposed, which offers significant advantages in reducing the repetitive usage of complex mathematical models and hence the computational time of design. The computational time was reduced by up to around 78% and 67% compared to the numerical modeling and geometric program (GP) methods as validated through a hardware design process. The proposed method was implemented in MATLAB/Simulink to design a 1 kW single-phase inverter, resulting in a design with an optimized efficiency (98.4%) and power density (4.57kW/dm3) . The accuracy of the design is verified through experimental prototyping and the measured efficiency and power density are 98.02% and 4.54kW/dm3 , respectively, so the errors of efficiency and power density are both less than 1%