Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data-model fusion

Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion together with their different transport rates and vulnerability to oxidation determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways have not been well characterized by experiments or modeling approaches. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: 1) the Ebullition Bubble Growth volume threshold approach (EBG) and 2) the modified Ebullition Concentration Threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model-data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization.

How do human capital and R&D structure facilitate FDI knowledge spillovers to local firm innovation? a panel threshold approach

This paper examines how local firms’ structure of human capital and R&D strategies influence their absorption of FDI knowledge spillovers. Using a unique dataset of Chinese firms in Beijing Zhongguancun Science Park from 2009 to 2015, our panel endogenous threshold models confirm two thresholds for human capital diversity and one threshold for R&D diversity in facilitating FDI spillovers. When human capital diversity is below its second threshold, FDI presence positively influences local firms’ innovation performance; while above the second threshold, the FDI turns to an insignificant impact. Besides, when R&D diversity is below its single threshold, FDI spillovers are positively associated with local firms’ innovation; otherwise, the effect of FDI is insignificantly negative. Our findings highlight the importance of human capital and R&D structures in local firms’ absorptive capacity. Local organizations need to keep diversifying their human capital and R&D strategies to learn from FDI knowledge but avoid allocating their efforts evenly upon sub-categories within the two resources.

Enhanced (t, n) threshold d-level quantum secret sharing

The quantum secret sharing is an essential and fundamental technique for sharing a secret with the all participants in quantum cryptography. It can be used to design many complex protocols such as secure multiparty summation, multiplication, sorting, voting, etc. Recently, Song et al. have discussed a quantum protocol for secret sharing, which has (t, n) threshold approach and modulo d, where t and n denote the threshold number of participants and total number of participants, respectively. Kao et al. point out that the secret in the Song et al.’s protocol cannot be reconstructed without other participants’ information. In this paper, we discuss a protocol that overcomes this problem.

Trade Openness and Economic Growth: A Study on Asean-6

This paper focuses on examining the nonlinear impact of trade openness (TO) on economic growth (EG) in the Asean-6 countries (Indonesia, Malaysia, Thailand, Singapore, Philippines, and Vietnam). In order to achieve the set research objectives, the authors estimate the research model through the fixed-effect panel threshold approach. Unlike previous studies, this paper finds that there is a nonlinear impact of TO on EG, whereby TO has two threshold values. Specifically, before the first threshold value, TO plays an important role in boosting EG. However, this impact level decreases gradually when TO exceeds this threshold value. In particular, when exceeding the second threshold value, the impact of TO on EG is still positive but has a relatively low value. The research results show that if TO increases to a high level (beyond the threshold value) without combining with other complementary policies, this does not encourage high-efficiency EG. In addition, this study also shows that EG is positively affected by domestic investment and negatively affected by financial crisis. The findings in this paper are of great importance for the Asean-6 countries as well as researchers.