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  1. Free, publicly-accessible full text available July 6, 2023
  2. Graph Convolutional Network (GCN) plays pivotal roles in many real-world applications. Despite the successes of GCN deployment, GCN often exhibits performance disparity with respect to node de- grees, resulting in worse predictive accuracy for low-degree nodes. We formulate the problem of mitigating the degree-related per- formance disparity in GCN from the perspective of the Rawlsian difference principle, which is originated from the theory of distribu- tive justice. Mathematically, we aim to balance the utility between low-degree nodes and high-degree nodes while minimizing the task- specific loss. Specifically, we reveal the root cause of this degree- related unfairness by analyzing the gradients of weight matrices in GCN. Guided by the gradients of weight matrices, we further propose a pre-processing method RawlsGCN-Graph and an in- processing method RawlsGCN-Grad that achieves fair predictive accuracy in low-degree nodes without modification on the GCN architecture or introduction of additional parameters. Extensive experiments on real-world graphs demonstrate the effectiveness of our proposed RawlsGCN methods in significantly reducing degree- related bias while retaining comparable overall performance.
    Free, publicly-accessible full text available April 25, 2023
  3. The three-level system in a diamond nitrogen vacancy center is used to engineer a tensor monopole.
    Free, publicly-accessible full text available March 4, 2023
  4. Abstract

    Warming due to climate change has profound impacts on regional crop yields, and this includes impacts from rising mean growing season temperature and heat stress events. Adapting to these two impacts could be substantially different, and the overall contribution of these two factors on the effects of climate warming and crop yield is not known. This study used the improved WheatGrow model, which can reproduce the effects of temperature change and heat stress, along with detailed information from 19 location-specific cultivars and local agronomic management practices at 129 research stations across the main wheat-producing region of China, to quantify the regional impacts of temperature increase and heat stress separately on wheat in China. Historical climate, plus two future low-warming scenarios (1.5 °C/2.0 °C warming above pre-industrial) and one future high-warming scenario (RCP8.5), were applied using the crop model, without considering elevated CO2effects. The results showed that heat stress and its yield impact were more severe in the cooler northern sub-regions than the warmer southern sub-regions with historical and future warming scenarios. Heat stress was estimated to reduce wheat yield in most of northern sub-regions by 2.0%–4.0% (up to 29% in extreme years) under the historical climate. Climate warming ismore »projected to increase heat stress events in frequency and extent, especially in northern sub-regions. Surprisingly, higher warming did not result in more yield-impacting heat stress compared to low-warming, due to advanced phenology with mean warming and finally avoiding heat stress events during grain filling in summer. Most negative impacts of climate warming are attributed to increasing mean growing-season temperature, while changes in heat stress are projected to reduce wheat yields by an additional 1.0%–1.5% in northern sub-regions. Adapting to climate change in China must consider the different regional and temperature impacts to be effective.

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  5. The two-way interaction between Madden–Julian oscillation (MJO) and higher-frequency waves (HFW) over the Maritime Continent (MC) during boreal winter of 1984–2005 is investigated. It is noted from observational analysis that strengthened (weakened) HFW activity appears to the west (east) of and under MJO convection during the MJO active phase and the opposite is seen during the MJO suppressed phase. Sensitivity model experiments indicate that the control of HFW activity by MJO is through change of the background vertical wind shear and specific humidity. The upscale feedbacks from HFW to MJO through nonlinear rectification of condensational heating and eddy momentum transport are also investigated with observational data. A significantly large amount (25%–40%) of positive heating anomaly ([Formula: see text]) at low levels to the east of MJO convection is contributed by nonlinear rectification of HFW. This nonlinear rectification is primarily attributed to eddy meridional moisture advection. A momentum budget diagnosis reveals that 60% of MJO zonal wind tendency at 850 hPa is attributed to the nonlinear interaction of HFW with other scale flows. Among them, the largest contribution arises from eddy zonal momentum flux divergence [Formula: see text]. Easterly (westerly) vertical shear to the west (east) of MJO convection during themore »MJO active phase causes the strengthening (weakening) of the HFW zonal wind anomaly. This leads to the increase (decrease) of eddy momentum flux activity to the east (west) of the MJO convection, which causes a positive (negative) eddy zonal momentum flux divergence in the zonal wind transitional region during the MJO active (suppressed) phase, favoring the eastward propagation of the MJO.« less