A Superresolution Image Reconstruction Algorithm Based on Landweber in Electrical Capacitance Tomography

According to the image reconstruction accuracy influenced by the “soft field” nature and ill-conditioned problems in electrical capacitance tomography, a superresolution image reconstruction algorithm based on Landweber is proposed in the paper, which is based on the working principle of the electrical capacitance tomography system. The method uses the algorithm which is derived by regularization of solutions derived and derives closed solution by fast Fourier transform of the convolution kernel. So, it ensures the certainty of the solution and improves the stability and quality of image reconstruction results. Simulation results show that the imaging precision and real-time imaging of the algorithm are better than Landweber algorithm, and this algorithm proposes a new method for the electrical capacitance tomography image reconstruction algorithm

Design Synthesis of Nitrogen-Doped TiO2@Carbon Nanosheets toward Selective Nitroaromatics Reduction under Mild Conditions

The development of a facile, low-cost, and ecofriendly approach to the synthesis of aromatic amines remains a great scientific challenge. TiO2, as a low-cost and earth abundant metal oxide, is usually not active for thermo-catalyzed nitro reduction. Herein, we report a composite nanosheet catalyst, composed of nitrogen-doped TiO2 and carbon (N-TiO2@C), which exhibits highly efficient, thermo-catalytic performance for selective nitroaromatic reduction at room temperature. The NTiO2@C nanosheet catalyst is synthesized via a facile approach where C3N4 nanosheets are utilized not only as a structuredirecting agent to control the shape, size, and crystal phase of TiO2 but also as a source of nitrogen for doping into both TiO2 and carbon nanosheets. Furthermore, the origin of the superior performance of the N-TiO2@C nanosheet composite catalyst, along with a possible nitroaromatic reduction mechanism, has also been explored.This work was financially supported by the National Key Project on Basic Research (Grant No. 2013CB933203), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB20000000), the Natural Science Foundation of China (Grants No. 21607153, 21373224 and 21577143), the Natural Science Foundation of Fujian Province (Grant No. 2015J05044), and the Frontier Science Key Project of the Chinese Academy of Sciences (QYZDB-SSW-JSC027). The work at ORNL was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division (STEM-EELS), and through a user project supported by ORNL’s Center for Nanophase Materials Sciences, which is sponsored by the Scientific User Facilities Division of U.S. DOE

A Cross Comparison of Spatiotemporally Enhanced Springtime Phenological Measurements From Satellites and Ground in a Northern U.S. Mixed Forest

Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed deciduous and coniferous tree phenology using an upscaling approach. Results showed that daily MODIS-based LSP consistently estimated greenup onset dates at the study area (625 m × 625 m) level with 4.48 days of mean absolute error (MAE), slightly better than that of using 16-day standard VI (4.63 days MAE). For the observed study areas, the time series with increased number of observations confirmed that post-bud burst deciduous tree phenology contributes the most to vegetation reflectance change. Moreover, fused VI time series demonstrated closer correspondences with LP at the community level (0.1-20 ha) than using MODIS alone at the study area level (390 ha). The fused LSP captured greenup onset dates for respective forest communities of varied sizes and compositions with four days of the overall MAE. This study supports further use of spatiotemporally enhanced LSP for more precise phenological monitoring

Decomposition and Decoupling Analysis of Carbon Emissions in Xinjiang Energy Base, China

China faces a difficult choice of maintaining socioeconomic development and carbon emissions mitigation. Analyzing the decoupling relationship between economic development and carbon emissions and its driving factors from a regional perspective is the key for the Chinese government to achieve the 2030 emission reduction target. This study adopted the logarithmic mean Divisia index (LMDI) method and Tapio index, decomposed the driving forces of the decoupling, and measured the sector’s decoupling states from carbon emissions in Xinjiang province, China. The results found that: (1) Xinjiang’s carbon emissions increased from 93.34 Mt in 2000 to 468.12 Mt in 2017. Energy-intensive industries were the key body of carbon emissions in Xinjiang. (2) The economic activity effect played the decisive factor to carbon emissions increase, which account for 93.58%, 81.51%, and 58.62% in Xinjiang during 2000–2005, 2005–2010, and 2010–2017, respectively. The energy intensity effect proved the dominant influence for carbon emissions mitigation, which accounted for −22.39% of carbon emissions increase during 2000–2010. (3) Weak decoupling (WD), expansive coupling (EC), expansive negative decoupling (END) and strong negative decoupling (SND) were identified in Xinjiang during 2001 to 2017. Gross domestic product (GDP) per capita elasticity has a major inhibitory effect on the carbon emissions decoupling. Energy intensity elasticity played a major driver to the decoupling in Xinjiang. Most industries have not reached the decoupling state in Xinjiang. Fuel processing, power generation, chemicals, non-ferrous, iron and steel industries mainly shown states of END and EC. On this basis, it is suggested that local governments should adjust the industrial structure, optimize energy consumption structure, and promote energy conservation and emission reduction to tap the potential of carbon emissions mitigation in key sectors

Regulation of Two-Dimensional Lattice Deformation Recovery

The lattice directly determines the electronic structure, and it enables controllably tailoring the properties by deforming the lattices of two-dimensional (2D)materials. Owing to the unbalanced electrostatic equilibrium among the dislocated atoms, the deformed lattice is thermodynamically unstable and would recover to the initial state. Here, we demonstrate that the recovery of deformed 2D lattices could be directly regulated via doping metal donors to reconstruct electrostatic equilibrium. Compared with the methods that employed external force fields with intrinsic instability and nonuniformity, the stretched 2D molybdenum diselenide (MoSe2)could be uniformly retained and permanently preserved via doping metal atoms with more outermost electrons and smaller electronegativity than Mo. We believe that the proposed strategy could open up a new avenue in directly regulating the atomic-thickness lattice and promote its practical applications based on 2D crystals. © 2019 The Author(s

How do tree species with different successional stages affect soil organic nitrogen transformations?

Organic nitrogen (N) is the most important N component of soil organic matter.However, knowledge on how tree species with different successional stages affect its transformations in soils remains limited. To address this issue, we sampled mineral soils (0−10 cm) in monocultures composed by tree species of different successional stages, including early (black alder and silver birch), early to mid (sycamore and European ash), and late (sweet chestnut, pedunculate oak and European beech), and measured the potential protease activity, the microbial uptake and respiration of 14C-labeled organic N (L-alanine and L-trialanine), and the mineralization of L-alanine N. The activities of alanine aminopeptidase and leucine aminopeptidase (153.8−341.9 and 91.6−147.9 nmol/g/h, respectively), the half-life of the uptake of alanine and trialanine (26.7−39.6 and 60.8−78.6 min, respectively), the half-life of the mineraliztion of alanine and trialanine (1.98−2.45 and 2.98−4.13 h, respectively) by soil microbes were altered by tree species of different successional stages, systematically changing the transformation chain of soil organic N. From trees of early successional stage to that of late, the turnover rates of soil organic N appeared to decrease and the half-life appeared to increase significantly. The (carbon) C:N ratio of soil microbial biomass was positively related to the half-life of 14Clabeled alanine and trialanine mineralization, and was negatively related to the C use efficiency of alanine, suggesting that microbial demand for C could partially drive the assimilation of soil organic N. Our results suggest that the successional stage of tree species play an important role in regulating the soil organic N turnover. An improved understanding of how tree species with different successional stages influence microbial function and soil organic N cycling is beneficial to future afforestation and forest management, alleviating the impacts of global change on the ecosystem