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Archaeologists are increasingly interested in networks constructed from site assemblage data, in which weighted network ties reflect sites’ assemblage similarity. Equivalent networks would arise in other scientific fields where actors’ similarity is assessed by comparing distributions of observed counts, so the assemblages studied here can represent other kinds of distributions in other domains. One concern with such work is that sampling variability in the assemblage network and, in turn, sampling variability in measures calculated from the network must be recognized in any comprehensive analysis. In this study, we investigated the use of the bootstrap as a means of estimating sampling variability in measures of assemblage networks. We evaluated the performance of the bootstrap in simulated assemblage networks, using a probability structure based on the actual distribution of sherds of ceramic wares in a region with 25 archaeological sites. Results indicated that the bootstrap was successful in estimating the true sampling variability of eigenvector centrality for the 25 sites. This held both for centrality scores and for centrality ranks, as well as the ratio of first to second eigenvalues of the network (similarity) matrix. Findings encourage the use of the bootstrap as a tool in analyses of network data derived from counts. 

Emerging applications of compact high-voltage SiC modules pose strong challenges in the module package insulation design. Such SiC module insulations are subjected to both high voltage DC and PWM excitations between different terminals during different switching intervals. High dV/dt strongly interferes with partial discharge (PD) testing as it is hard to distinguish PD pulses and PWM excitation induced interferences. This paper covers both the testing and modeling of PD phenomena in high-voltage power modules. A high dV/dt PD testing platform is proposed, which involves a Super-High-Frequency (SHF, >3GHz) down-mixing PD detection receiver and a high-voltage scalable square wave generator. The proposed method captures SHF PD signatures and determines PDIV for packaging insulation. Using this platform, this paper provides a group of PDIV comparisons of packaging insulation under DC and PWM waveforms and discloses discrepancies in these PDIV results with respect to their excitations. Based on these PD testing results, the paper further provides a model using space charge accumulation to explain the PD difference under DC and PWM waveforms. Both simulation and sample testing results are included in this paper to support this hypothesis. With this new model, the paper includes an updated insulation design procedure for high-voltage power modules. 

Boreal‐Arctic regions are key stores of organic carbon (C) and play a major role in the greenhouse gas balance of high‐latitude ecosystems. The carbon‐climate (C‐climate) feedback potential of northern high‐latitude ecosystems remains poorly understood due to uncertainty in temperature and precipitation controls on carbon dioxide (CO₂) uptake and the decomposition of soil C into CO₂and methane (CH₄) fluxes. While CH₄fluxes account for a smaller component of the C balance, the climatic impact of CH₄outweighs CO₂(28–34 times larger global warming potential on a 100‐year scale), highlighting the need to jointly resolve the climatic sensitivities of both CO₂and CH₄. Here, we jointly constrain a terrestrial biosphere model with in situ CO₂and CH₄flux observations at seven eddy covariance sites using a data‐model integration approach to resolve the integrated environmental controls on land‐atmosphere CO₂and CH₄exchanges in Alaska. Based on the combined CO₂and CH₄flux responses to climate variables, we find that 1970‐present climate trends will induce positive C‐climate feedback at all tundra sites, and negative C‐climate feedback at the boreal and shrub fen sites. The positive C‐climate feedback at the tundra sites is predominantly driven by increased CH₄emissions while the negative C‐climate feedback at the boreal site is predominantly driven by increased CO₂uptake (80% from decreased heterotrophic respiration, and 20% from increased photosynthesis). Our study demonstrates the need for joint observational constraints on CO₂and CH₄biogeochemical processes—and their associated climatic sensitivities—for resolving the sign and magnitude of high‐latitude ecosystem C‐climate feedback in the coming decades.

 

The coupled chemistry of methane, carbon monoxide (CO), and hydroxyl radical (OH) can modulate methane's 9‐year lifetime. This is often ignored in methane flux inversions, and the impacts of neglecting interactive chemistry have not been quantified. Using a coupled‐chemistry box model, we show that neglecting the effect of methane source perturbation on [OH] can lead to a 25% bias in estimating abrupt changes in methane sources after only 10 years. Further, large CO emissions, such as from biomass burning, can increase methane concentrations by extending the methane lifetime through impacts on [OH]. Finally, we quantify the biases of including (or excluding) coupled chemistry in the context of recent methane and CO trends. Decreasing CO concentrations, beginning in the 2000's, have notable impacts on methane flux inversions. Given these nonnegligible errors, decadal methane emissions inversions should incorporate chemical feedbacks for more robust methane trend analyses and source attributions.