A self-paced learning algorithm for change detection in synthetic aperture radar images

Detecting changed regions between two given synthetic aperture radar images is very important to monitor the change of landscapes, change of ecosystem and so on. This can be formulated as a classification problem and addressed by learning a classifier, traditional machine learning classification methods very easily stick to local optima which can be caused by noises of data. Hence, we propose an unsupervised algorithm aiming at constructing a classifier based on self-paced learning. Self-paced learning is a recently developed supervised learning approach and has been proven to be capable to overcome effectively this shortcoming. After applying a pre-classification to the difference image, we uniformly select samples using the initial result. Then, self-paced learning is utilized to train a classifier. Finally, a filter is used based on spatial contextual information to further smooth the classification result. In order to demonstrate the efficiency of the proposed algorithm, we apply our proposed algorithm on five real synthetic aperture radar images datasets. The results obtained by our algorithm are compared with five other state-of-the-art algorithms, which demonstrates that our algorithm outperforms those state-of-the-art algorithms in terms of accuracy and robustness

Phase-Field Modelling of Microstructure Evolution in Solid Oxide Cells

The performance degradation of Solid Oxide Cells (SOC) caused by microstructure evolution limits the SOC's lifetime. Long-term testing combined with post-mortem characterization is one common approach to clarify degradation mechanisms and develop counter-acting measures, but this is associated with extensive amount of experimental work and long research time. Instead, many researchers have devoted their efforts to investigating degradation using computational methods. The phase-field model has been utilized in the SOC research to illustrate the microstructure evolution during long-term operation from micron to millimeter scale, with the possibility of taking into account the mechanical properties as well. In this article, the principle of the phase-field method and different models are introduced first, followed by examples published in literature on phase-field modeling of various degradation phenomena in SOCs. Finally, possible strategies coupling modelling and experimental research in optimizing SOC performance and microstructure are discussed

Associations between anxiety, depression, and personal mastery in community-dwelling older adults: a network-based analysis

Abstract Background In China, about 18.70% of the population aged 60 years and older are at risk of low personal mastery as well as anxiety and depression for a variety of reasons. The purpose of this study was to construct a symptom network model of the relationship between anxiety, depression, and personal mastery in community-dwelling older adults and to identify central and bridge symptoms in this network. Methods Depression, anxiety, and personal mastery were measured using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and Personal Mastery Scale (PMS), respectively. A total of 501 older adults in 16 communities in Changzhou and Zhenjiang, Jiangsu Province, China, were surveyed by using a combination of stratified sampling and convenience sampling methods. The R language was used to construct the network. Results (1) The network structure of anxiety–depression–personal mastery was stable, with “Nervousness” (node GAD1, strength = 1.38), “Sad mood” (node PHQ2, strength = 1.22), " Inability to change” (node PMS2, strength = 1.01) and “Involuntarily” (node PMS3, strength = 0.95) as the central symptoms. (2) “Irritability” (node GAD6, bridge strength = 0.743), “Sad mood” (node PHQ2, bridge strength = 0.655), and “Trouble relaxing” (node GAD4, bridge strength = 0.550) were the bridge symptoms connecting anxiety, depressive symptoms, and personal mastery. (3) In the network comparison test (NCT), residence, somatic chronic comorbidity and gender had no significant effect on network structure. Conclusions The construction of the anxiety–depression–personal mastery network structure opens up new possibilities for mechanisms of action and intervention formulation for psychological disorders in community-dwelling older adults. The identification of central symptoms (e.g., nervousness, sad mood, inability to change, involuntarily) and bridge symptoms (e.g., irritability, sad mood, trouble relaxing) in community-dwelling older adults with anxiety, depression, and low sense of mastery can provide a scientific basis for the development of precise interventions

Integrated 3D modeling unravels the measures to mitigate nickel migration in solid oxide fuel/electrolysis cells

Numerical modeling plays an important role in understanding the multi-physics coupling in solid oxide fuel/electrolysis cells (SOFCs/SOECs) operated at elevated temperatures. During long-term operation of SOFCs and SOECs, cell durability is limited by nickel (Ni) morphological changes and migration. To reveal the mechanisms behind these phenomena, a unified numerical model utilizing the phase-field (PF) method is integrated with a finite element (FE) multi-physics coupled heterogeneous single-cell model to quantitatively investigate the microstructure evolution of hydrogen electrodes operated in different modes. Based on the 3D microstructures of single-cell components reconstructed using the focused ion beam-scanning electron microscopy (FIB-SEM) technique, the performances of different cells and the corresponding microstructure evolutions caused by Ni coarsening and migration can be simulated under an identical framework in the FC and EC modes, taking into account the complex multi-physics coupling effects. It is shown that, in addition to conventional interfacial energies, the Ni migration driven by the electrochemical potential gradient induced by current also plays an important role in the microstructure evolution. The integrated model is also applied to the simulation of the microstructure evolution of the Ni-YSZ hydrogen electrode infiltrated with GDC nanoparticles to interpret their positive effect on the improvement of the electrode durability.Numerical modeling plays an important role in understanding the multi-physics coupling in solid oxide fuel/electrolysis cells (SOFCs/SOECs) operated at elevated temperatures

Differential response of soil respiration to nitrogen and phosphorus addition in a highly phosphorus-limited subtropical forest, China

Hosseini Bai, S ORCiD: 0000-0001-8646-6423Understanding feedback between terrestrial carbon (C) cycle and climate change is linked to the effects of nitrogen (N) and phosphorus (P) on soil respiration (Rs). However, the individual and interactive effects of N and P additions on soil respiration and its components (autotrophic [Ra] and heterotrophic respiration [Rh]) are not fully understood, especially in highly P limited subtropical forests. In this study, both field experiment and laboratory incubation (at 15 °C and 25 °C temperatures) were undertaken to examine the effects of N, P and N + P additions on Rs and Rh. Our results showed that N addition significantly increased Rs by 21.09%, but P and N + P additions exhibited no effects on Rs under field conditions. Under laboratory condition, N addition significantly suppressed Rh whereas P and N + P additions increased Rh compared with control. Meanwhile, N and P additions exhibited an antagonistic interaction on Rs, but N and P additions synergistically affected Rh under laboratory incubations at both incubation temperatures of 15 °C and 25 °C. Cumulative Rh was negatively correlated with fine root biomass, but was positively correlated with microbial biomass carbon regardless of incubation temperatures. Our findings indicated that both individual and interactive effects of N and P additions on Rs and Rh were required to be considered to improve prediction of N and P effects on forest C dynamics in the highly P limited subtropical forests. © 2019 Elsevier B.V

Interprovincial Joint Prevention and Control of Open Straw Burning in Northeast China: Implications for Atmospheric Environment Management

Large-scale open burning of straw residues causes seasonal and severe atmospheric pollution in Northeast China. Previous studies focused on the causes or assessment of atmospheric pollution in a single city. However, studies conducted on the interaction range, degree and policy control of pollutant transport on a large scale are still to be performed. In this study, we propose combined control of straw burning by dividing region the straw burning in Northeast China in recent 20 years, determining the transport routes between main cities, and analyzing the interaction characteristics of straw burning under different scenarios. The fire point data suggest that the most intense straw burning years in Northeast China in the past 20 years occurred in the range from 2014 to 2017, mainly after the autumn harvest (October–November) and before spring cultivation (March–April). The burning areas were concentrated in the belt of Shenyang-Changchun-Harbin, the border of the three provinces and Eastern-Inner Mongolia, and the surrounding area of Hegang and Jiamusi City. The lower number of fire points before 2013 indicates that high-intensity burning has not always been the case, while the sharp decline after 2018 is mainly due to scientific control of straw burning and increased comprehensive utilization of straw. Compared with S2, the PM2.5 concentrations increased by 6.2% in S3 and 18.7% in S4, indicating that burning in three or four provinces at the same time will significantly increase air pollution and exert a regional transmission effect. Straw burning in Northeast China is divided into six main regions based on correlation analysis and satellite fire monitoring. Under typical S3, the case analysis results indicate that there is regional transmission interaction between different cities and provinces, focusing on multi-province border cities, and it is affected by Northwest long airflow, and Southeast and Northeast short airflow. These results provide scientific and technological support for implementing the joint prevention and control plan for straw incineration in Northeast China

Understanding the Ni migration in solid oxide cell: a coupled experimental and modeling approach

International audienceA long-term test of 2000 h has been carried out on a typical solid oxide cell in electrolysis mode at −1 A.cm$^{−2}$ and 750 °C. The 3D reconstructions of the pristine and aged cermet have revealed a strong Ni depletion at the electrolyte interface. To explain this result, an electrochemical and phase-field model has been developed to simulate the Ni migration in Ni/YSZ electrode. For this purpose, a mechanism has been proposed that takes into account the impact of polarization on the Ni/YSZ wettability. In this approach, it assumes that the Ni/YSZ interfacial energy is changed by the concentration of oxygen vacancies in the electrochemical double layer. Thanks to the model, the Ni migration has been computed in the same condition than the experiment and complemented by a simulation in reverse condition in SOFC mode. In good agreement with the experiment, the simulations have revealed a strong Ni depletion at the electrolyte interface after operation under electrolysis current. On the contrary, a negligible Ni redistribution with a very slight Ni enrichment has been predicted at the electrolyte interface after SOFC operation. These results tend to prove the relevance of the mechanism