Relative increases in CH4 and CO2 emissions from wetlands under global warming dependent on soil carbon substrates

15 páginas.- 3 figuras.- 57 referencias.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41561-023-01345-6Compelling evidence has shown that wetland methane emissions are more temperature dependent than carbon dioxide emissions across diverse hydrologic conditions. However, the availability of carbon substrates, which ultimately determines microbial carbon metabolism, has not been adequately accounted for. By combining a global database and a continental-scale experimental study, we showed that differences in the temperature dependence of global wetland methane and carbon dioxide emissions (EM/C) were dependent on soil carbon-to-nitrogen stoichiometry. This can be explained mainly by the positive relationship between soil organic matter decomposability and EM/C. Our study indicates that only 23% of global wetlands will decrease methane relative to carbon dioxide emissions under future warming scenarios when soil organic matter decomposability is considered. Our findings highlight the importance of incorporating soil organic matter biodegradability into model predictions of wetland carbon–climate feedback.The authors received funding from Strategic Priority Research Program of the Chinese Academy of Sciences (XDA28030102 to Y.L.), National Natural Scientific Foundation of China (92251305 to M.N., 41622104 to Y.L.), Innovation Program of the Institute of Soil Science (ISSASIP2201 to Y.L.) and Youth Innovation Promotion Association of the Chinese Academy of Sciences (2016284 to Y.L.).Peer reviewe

The Local Origin of the Tibetan Pig and Additional Insights into the Origin of Asian Pigs

BACKGROUND: The domestic pig currently indigenous to the Tibetan highlands is supposed to have been introduced during a continuous period of colonization by the ancestors of modern Tibetans. However, there is no direct genetic evidence of either the local origin or exotic migration of the Tibetan pig. METHODS AND FINDINGS: We analyzed mtDNA hypervariable segment I (HVI) variation of 218 individuals from seven Tibetan pig populations and 1,737 reported mtDNA sequences from domestic pigs and wild boars across Asia. The Bayesian consensus tree revealed a main haplogroup M and twelve minor haplogroups, which suggested a large number of small scale in situ domestication episodes. In particular, haplogroups D1 and D6 represented two highly divergent lineages in the Tibetan highlands and Island Southeastern Asia, respectively. Network analysis of haplogroup M further revealed one main subhaplogroup M1 and two minor subhaplogroups M2 and M3. Intriguingly, M2 was mainly distributed in Southeastern Asia, suggesting for a local origin. Similar with haplogroup D6, M3 was mainly restricted in Island Southeastern Asia. This pattern suggested that Island Southeastern Asia, but not Southeastern Asia, might be the center of domestication of the so-called Pacific clade (M3 and D6 here) described in previous studies. Diversity gradient analysis of major subhaplogroup M1 suggested three local origins in Southeastern Asia, the middle and downstream regions of the Yangtze River, and the Tibetan highlands, respectively. CONCLUSIONS: We identified two new origin centers for domestic pigs in the Tibetan highlands and in the Island Southeastern Asian region

Simulation of Arc Plasma Gasification Based on Experimental Conditions

An EPJ process simulation model was set up and verified to simulate the plasma gasification process of the medical wastes. The influence of ER value and SAMR value was simulated based on experimental conditions including material feeding rate, furnace temperature and medical waste properties. Results shows that ER=0.3 is a turning point for medical waste plasma gasification. The required input plasma power and volume flow of combustible constituents in syngas reach the maximum at ER=0.3. The balance of syngas composition and required input plasma power should be overall considered. Results shows that the SAMR value mainly influences the amount of H element and N element in the system at a fixed ER value, thus influencing the proportions of H2 and N2 in monotonous ways. Input plasma power needed and combustible syngas flow increase with the increasing SAMR

R/S analysis of gas emission in coal mine underground tunnel

In order to grasp changes of the danger of coal and gas outburst, factors of coal seam gas emission were analyzed, R/S analysis method was used to study gas emission of coal mine tunnel, and the following conclusion was obtained: gas emission time series have fractal characteristics, when it is detected that Hurst index is decreasing and has great volatility, it indicates abnormal gas emission will occur, so certain safety precautions should be taken in advance

AMIO-Net: An Attention-Based Multiscale Input–Output Network for Building Change Detection in High-Resolution Remote Sensing Images

Building change detection (CD) from remote sensing images (RSI) has great significance in exploring the utilization of land resources and determining the building damage after a disaster. This article proposed an attention-based multiscale input–output network, named AMIO-Net, for building CD in high-resolution RSI. It is able to overcome partial drawbacks of existing CD methods, such as insufficient utilization of information (details of building edges) of original images and poor detection effect of small targets (small-scale buildings or small-area changed buildings that are disturbed by other buildings). In AMIO-Net, the input image is scaled down to different sizes, and performed the convolution to extract features. Then, the feature maps are fed into the encoding stage so that the network can fully utilize the feature information (FI) of the original image. More importantly, we design two attention mechanism modules: the pyramid pooling attention module (PPAM) and the Siamese attention mechanism module (SAMM). PPAM combines a pyramid pooling module and an attention mechanism to fully consider the global information and focus on the FI of changed pixels in the image. The input of SAMM is the parallel multiscale output diagram of the decoding portion and deep feature maps of the network so that AMIO-Net can utilize the global contextual semantic FI and strengthen detection ability for small targets. Experiments on three datasets show that the proposed method achieves higher detection accuracy and F1 score compared with the state-of-the-art methods

Learning Dense Consistent Features for Aerial-to-Ground Structure-From-Motion

The integration of aerial and ground images is known to be effective for enhancing the quality of 3-D reconstruction in complex urban scenarios. However, directly applying the structure-from-motion (SfM) technique for unified 3-D reconstruction with aerial and ground images is particularly difficult, due to the large differences in viewpoint, scale, and appearance between those two types of images. Previous studies mainly rely on viewpoint rectification or view rendering/synthesis to improve the feature matching quality for aligning the aerial and ground models. Nevertheless, these approaches still fail to address the inherent information differences between aerial and ground images. In this article, we propose a learning-based matching framework for direct SfM with ground and aerial images. The key idea of our method is to learn the pixel-wise consistent features between aerial and ground images to handle the large heterogeneity of these two types of images. Specifically, we deploy a learning-based matching framework to robustly correspond the aerial and ground images. With the high-quality feature matching, learned feature maps are used for refining keypoint locations and fusing featuremetric error into bundle adjustment with the consideration of geometric error, both of which can further improve the accuracy and completeness of the recovered 3-D scene. Extensive experiments conducted on six datasets demonstrate that the proposed method can reconstruct high-fidelity 3-D models with direct aerial-to-ground SfM, which cannot be achieved by existing methods. In addition, our method also shows outstanding performance in subtasks of feature matching and point cloud recovery

Stabilization and strengthening of chromium(VI)-contaminated soil via magnesium ascorbyl phosphate (MAP) and phytase addition

Cr(VI) contamination of soil threatens the environment and reduces soil strength. Therefore, both Cr(VI) stabilization and soil reinforcement should be considered in site remediation for future construction. This study investigated a biochemical treatment process using magnesium ascorbyl phosphate (MAP) and phytase. MAP was hydrolyzed via phytase catalysis to produce ascorbic acid (AA) and MgHPO4·3H2O precipitation. The AA reduced Cr(VI) into low-toxic Cr(III), which precipitated as Cr(OH)3 and CrPO4. More than 90% of the 500 mg/kg Cr(VI) in soil was reduced by 5% MAP (wt% of soil) and 1% phytase (vol/vol of soil water) doses at the geotechnically optimal soil moisture content of 16.8%. The MgHPO4·3H2O precipitates filled soil pores and enhanced the unconfined compression strength of treated soil by more than two times. This research reports a novel and practical enzymatically induced phosphate precipitation process for the remediation of Cr(VI)-contaminated soil.This study is supported by the National Key Research and Development Programme (Grant No. 2019YFC1804002). Major Science and Technology Project of Inner Mongolia Autonomous Region (Grant No. 2021ZD0007-02-01). Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences (Grant No. Z020003). The first author (Lijun Han) would like to acknowledge China Scholarship Council (CSC) for funding her studies at Nanyang Technological University, Singapore (Grant No. 202104910310)

Decreased level of irisin, a skeletal muscle cell-derived myokine, is associated with post-stroke depression in the ischemic stroke population

Abstract Background Depression is a frequent mood disorder in stroke patient. Our aim was to determine irisin levels in serum and investigate their associations with post-stroke depression (PSD) in a 6-month follow-up study in Chinese patients with first-ever acute ischemic stroke (AIS). Methods The subjects were first-ever AIS patients who were hospitalized at three stroke centers during the period from January 2015 to December 2016. Neurological and neuropsychological evaluations were conducted at the 6-month follow-up. Serum irisin concentrations were measured by enzyme-linked immunosorbent assay (ELISA). Results During the study period, 1205 patients were included in the analysis. There were 370 patients (30.7%) classified as depression. The depression distribution across the irisin quartiles ranged between 49.8% (first quartile) and 9.9% (fourth quartile). In the patients with depression, serum irisin levels were lower compared with those in patients without depression (P < 0.001). In a multivariate model using the first (Q1) quartile of irisin vs. Q2–4 together with the clinical variables, the marker displayed predictive information and increased risk of PSD by 75% (odds ratio [OR] for Q1, 1.75 [95% confidence interval [CI], 1.15–2.65]). In addition, a model containing known risk factors plus irisin compared with a model containing known risk factors without irisin showed a greater discriminatory ability; the area under the curve (AUC) increased from 0.77 to 0.81 (95% CI, 0.76–0.86). Conclusions The data suggested that reduced serum levels of irisin were powerful biological markers of risk of developing PSD even after adjustment by variables. Further studies are necessary to confirm this association, which may open the way to the proposal of new therapeutic options. Trial registration ChiCTR-OPC-17013501. Retrospectively registered 23 September 201

Hydrothermal Synthesized of CoMoO4 Microspheres as Excellent Electrode Material for Supercapacitor

Abstract The single-phase CoMoO4 was prepared via a facile hydrothermal method coupled with calcination treatment at 400 °C. The structures, morphologies, and electrochemical properties of samples with different hydrothermal reaction times were investigated. The microsphere structure, which consisted of nanoflakes, was observed in samples. The specific capacitances at 1 A g−1 are 151, 182, 243, 384, and 186 F g−1 for samples with the hydrothermal times of 1, 4, 8, 12, and 24 h, respectively. In addition, the sample with the hydrothermal time of 12 h shows a good rate capability, and there is 45% retention of initial capacitance when the current density increases from 1 to 8 A g−1. The high retain capacitances of samples show the fine long-cycle stability after 1000 charge-discharge cycles at current density of 8 A g−1. The results indicate that CoMoO4 samples could be a choice of excellent electrode materials for supercapacitor