105 research outputs found

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

    Get PDF
    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

    Modelling and optimal design of a multifunctional single-stage buck-boost differential inverter

    Get PDF
    In this paper, a single-stage buck-boost differential inverter is optimally designed for applications with varying input DC voltage (e.g. photovoltaics and fuel cell systems). The designed inverter has multiple functionalities, including power decoupling and AC output filtering, and it can operate with a wide DC voltage range without adding extra power conversion stages or filters. Hence, it is naturally compact and highly efficient. To fully exploit its benefits, the proposed inverter operating principle and mathematical model were first developed to form the foundation of an optimal design. The criteria for selecting the inverter's key components have been presented. This ensures that the developed inverter meets the aforementioned functional requirements without being overly sized. A digital design procedure based on artificial neural networks is followed for further multiple objective optimization, targeting high efficiency, high power density and low cost. A 1.8kW prototype of the inverter was fabricated through the digital design. The inverter's operating functionality with varying DC voltage, power decoupling, and filtering was demonstrated by both simulation studies and experimental tests on the prototype. The accuracy of the optimal design was also validated

    A multi-function integrated circuit breaker for DC grid applications

    Get PDF
    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

    Get PDF
    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

    Get PDF
    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

    Get PDF
    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

    Get PDF
    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

    Full text link
    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
    corecore