Lifetime Prediction of DC-link Capacitors in Multiple Drives System Based on Simplified Analytical Modeling

Lifetime prediction of dc-link capacitors in a single drive has been discussed before, which indicates that the capacitor in a standard drive meets serious reliability challenges and in a slim drive does not. However, in most of the applications, drives are connected in parallel with the power grid. The large amount of harmonic distortion produced by nonlinearity drives may transmit and couple between grid and drives, which changes the stresses of devices as well as the dc-link filters. Therefore, the estimated results in a single drive cannot be extended to multiple drives any more. This article investigates the lifetime of dc-link capacitors in multiple drives system. First, by decoupling the interactions among grid-connected drives, a simplified equivalent circuit model and its analytical model to obtain the dc-link continuous current in multiple drives is proposed, which releases the designers from configuring the large simulation for multiple drives. Then, applying the lifetime prediction method, the lifetime of dc-link capacitors in multiple drives is investigated, in terms of types of drives, numbers of drives, and grid conditions. The results show that the lifetime of the standard drives extends in the multidrive systems and the lifetime of the slim drives decreases in the multidrive systems, which break the previous mind. Finally, based on the proposed analytical model and lifetime estimation method, the capacitor sizing from reliability aspect for multiple slim drives is given. The outcomes of the lifetime investigation could be a guideline for the design of the capacitive dc link in multidrive systems

Deep high-temperature hydrothermal circulation in a detachment faulting system on the ultra-slow spreading ridge

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Tao, C., Seyfried, W. E., Jr., Lowell, R. P., Liu, Y., Liang, J., Guo, Z., Ding, K., Zhang, H., Liu, J., Qiu, L., Egorov, I., Liao, S., Zhao, M., Zhou, J., Deng, X., Li, H., Wang, H., Cai, W., Zhang, G., Zhou, H., Lin, J., & Li, W. Deep high-temperature hydrothermal circulation in a detachment faulting system on the ultra-slow spreading ridge. Nature Communications, 11(1), (2020): 1300, doi:10.1038/s41467-020-15062-w.Coupled magmatic and tectonic activity plays an important role in high-temperature hydrothermal circulation at mid-ocean ridges. The circulation patterns for such systems have been elucidated by microearthquakes and geochemical data over a broad spectrum of spreading rates, but such data have not been generally available for ultra-slow spreading ridges. Here we report new geophysical and fluid geochemical data for high-temperature active hydrothermal venting at Dragon Horn area (49.7°E) on the Southwest Indian Ridge. Twin detachment faults penetrating to the depth of 13 ± 2 km below the seafloor were identified based on the microearthquakes. The geochemical composition of the hydrothermal fluids suggests a long reaction path involving both mafic and ultramafic lithologies. Combined with numerical simulations, our results demonstrate that these hydrothermal fluids could circulate ~ 6 km deeper than the Moho boundary and to much greater depths than those at Trans-Atlantic Geotraverse and Logachev-1 hydrothermal fields on the Mid-Atlantic Ridge.This work was supported by National Key R&D Program of China under contract no. 2018YFC0309901, 2017YFC0306603, 2017YFC0306803, and 2017YFC0306203, COMRA Major Project under contract No. DY135-S1-01-01 and No. DY135-S1-01-06

Spatial and Temporal Patterns of Ecological Connectivity in the Ethnic Areas, Sichuan Province, China

With ongoing economic and social development, natural habitats are becoming increasingly fragmented, blocking habitat connections and reducing landscape connectivity. The study of changes in ecological connectivity can provide valuable information for habitat and landscape restoration, which are necessary for sustainable regional development. Despite the growing interest in this issue, studies that reveal the change in ecological connectivity in the compounded areas of ecological vulnerability and deep poverty are still lacking. In this paper, one of the most underdeveloped and ecologically fragile southwestern ethnic regions of China, the Sanzhou region of Sichuan Province, was the study area. Based on a vector map of current land-use status and vector data on ecosystem factors and nature reserves in 2010 and 2015, the change in ecological connectivity was analyzed using the minimum cumulative resistance model using GIS spatial analysis method. Firstly, ecological sources were identified based on the distribution of ecological functional areas. Secondly, the ecological resistance surface based on ecosystem service value is revised by integrating the three dimensions of topography and hydrology, ecological environment and development, and utilization intensity. Finally, the ecological connectivity of ethnic areas in southwest China in 2010 and 2015 was compared and analyzed through the perspective of ecological resistance. The results show that: (1) From 2010 to 2015, the overall ecological connectivity decreased. (2) There were six areas of high ecological resistance featuring human activity and ecological degradation: the Anning River Valley in Liangshan Prefecture, Ganzi, Dege and Luho counties in Ganzi Prefecture, and Ruoergai and Hongyuan counties in Aba Prefecture. (3) Low ecological resistance areas were more numerous and widely distributed, forming an ecological protection barrier for the three autonomous prefectures, and regulating and protecting their natural environments. It is necessary to maintain and strengthen this protection; accordingly, measures are proposed to improve ecological connectivity. This study provides a reference for achieving ecological security and harmonious coexistence between humans and nature in this region

Study on Livelihood Vulnerability and Adaptation Strategies of Farmers in Areas Threatened by Different Disaster Types under Climate Change

The intensification of global climate change leads to frequent mountain torrents, landslides, debris flows and other disasters, which seriously threaten the safety of residents’ lives and property. However, few studies have compared and analyzed the livelihood vulnerability and adaptation strategies of farmers in different disaster-threatened areas under the background of climate change. Based on survey data of 327 households in the areas threatened by mountain floods, landslides and debris flow in Sichuan Province, this study analyzed the characteristics of livelihood vulnerability and adaptation strategies of households in the areas threatened by different disaster types and constructed multinomial logistic regression models to explore their correlations. The findings show that: (1) The livelihood vulnerability indices of farmers in different hazard types showed different characteristics. Among them, the livelihood vulnerability index of farmers in landslide-threatened zones is the highest, followed by the livelihood vulnerability index of farmers in debris-flow-threatened zones, and finally the livelihood vulnerability index of farmers in flash flood threat zones. At the same time, all three natural hazards show a trend of higher vulnerability in the sensitivity dimension than in the exposure and livelihood resilience dimensions. (2) The nonfarming livelihood strategy is the main livelihood strategy for farmers in different disaster-type-threatened areas. At the same time, the vulnerability of farmers choosing the nonfarming livelihood strategy is much higher than that of farmers choosing the part-time livelihood strategy and pure farming livelihood strategy, and the vulnerability of sensitivity dimension is higher than that of the exposure dimension and livelihood resilience dimension. (3) For farmers in landslide- and debris-flow-threatened areas, livelihood resilience is an important factor affecting their livelihood strategy. There was a positive correlation between livelihood resilience and farmers’ choice of pure agricultural livelihood strategies in these two natural-disaster-threatened areas. This study deepens our understanding of the characteristics and relationships of farmers’ livelihood vulnerability and adaptation strategies under different disaster types in the context of climate change, and then provides the reference basis for the formulation of livelihood-adaptive capacity promotion-related policy

Sparse Inverse Covariance Estimation with L0 Penalty for Network Construction with Omics Data.

Constructing coexpression and association networks with omics data is crucial for studying gene-gene interactions and underlying biological mechanisms. In recent years, learning the structure of a Gaussian graphical model from high-dimensional data using L1 penalty has been well-studied and many applications in bioinformatics and computational biology have been found. However, besides the problem of biased estimators with LASSO, L1 does not always choose the true model consistently. Based on our previous work with L0 regularized regression (Liu and Li, 2014), we propose an L0 regularized sparse inverse covariance estimation (L0RICE) for structure learning with the efficient alternating direction (AD) method. The proposed method is robust and has the oracle property. The proposed method is applied to omics data including data, from next-generation sequencing technologies. Novel procedures for network construction and high-order gene-gene interaction detection with omics data are developed. Results from simulation and real omics data analysis indicate that L0 regularized structure learning can identify high-order correlation structure with lower false positive rate and outperform graphical lasso by a large margin

Sparse Inverse Covariance Estimation with L0 Penalty for Network Construction with Omics Data.

Constructing coexpression and association networks with omics data is crucial for studying gene-gene interactions and underlying biological mechanisms. In recent years, learning the structure of a Gaussian graphical model from high-dimensional data using L1 penalty has been well-studied and many applications in bioinformatics and computational biology have been found. However, besides the problem of biased estimators with LASSO, L1 does not always choose the true model consistently. Based on our previous work with L0 regularized regression (Liu and Li, 2014), we propose an L0 regularized sparse inverse covariance estimation (L0RICE) for structure learning with the efficient alternating direction (AD) method. The proposed method is robust and has the oracle property. The proposed method is applied to omics data including data, from next-generation sequencing technologies. Novel procedures for network construction and high-order gene-gene interaction detection with omics data are developed. Results from simulation and real omics data analysis indicate that L0 regularized structure learning can identify high-order correlation structure with lower false positive rate and outperform graphical lasso by a large margin

Stay in Risk Area: Place Attachment, Efficacy Beliefs and Risk Coping

For residents living in earthquake-threatened areas, choosing suitable risk coping behaviors can effectively reduce the loss of family life and property. However, some residents still choose to continue to live within areas at risk of earthquake disaster. Place attachment may play an important role. Based on place attachment theory and the Protective Action Decision Model (PADM), this study explores the possible relationships among place attachment, efficacy beliefs, and evacuation/relocation intention. Furthermore, it examines the mediating role of efficacy beliefs. The study also used the partial least squares method (PLS-SEM) to test samples of 327 rural households in Wenchuan and Lushan earthquake-hit areas. The results show that: (1) Place attachment has a significant effect on response efficacy (RE), but not on self-efficacy (SE); (2) Place dependence (PD) has a negative and significant effect on relocation intention (RI) but has no significant effect on evacuation intention (EI). However, place identity (PI) can indirectly affect EI by influencing RE; (3) Efficacy beliefs have a significant positive effect on EI and RI. These results help us understand the complex relationships among place attachment, efficacy beliefs, and residents’ risk coping behavior, thus providing decision-making references for the formulation and improvement of regional disaster risk management policies

Why “Say One Thing and Do Another” a Study on the Contradiction between Farmers’ Intention and Behavior of Garbage Classification

How to protect the ecological environment is an important international issue for achieving the sustainable development goals. Using survey data of 2628 farmers in 52 administrative villages in 13 prefecture-level cities of the China Land Economic Survey in 2020, probit and multinomial logistic regression models were used to explore the influence of social capital on farmers’ willingness, behavior and the transformation between willingness and behavior. The results show that: (1) The consistency between farmers’ willingness and behavior is low; 90.25% of farmers had the willingness to separate waste, but only 48.49% of farmers had actually classified waste, and only 48.22% of farmers had transformed willingness into behavior. (2) Among the three dimensions of social capital, social network, social norm and social trust, all had positive and significant effects on farmers’ willingness and behavior to separate waste. (3) Social network and social norm had a positive and significant impact on the transformation of farmers’ willingness to separate waste into behavior, but social trust was not significant. The research results confirm that the contradiction between farmers’ intention and behavior of waste separation were generally inconsistent in rural areas. At the same time, the results showed that social capital can promote farmers’ willingness and behavior of waste separation and the transformation from a willingness to behavior, which can provide decision-making reference for how to improve farmers’ high willingness and behavior

Labor Off-Farm Employment and Farmers’ Cooking Clean Energy Use: Evidence from Rural China

(Motivation) With the transfer of labor force and the continuous improvement of household income, the household energy consumption structure is also changing. (Gaps) However, few studies have explored the correlations between labor off-farm employment (LOE) and farmers’ cooking clean energy (CCE) consumption. (Methodologies) Using survey data of 8198 farmers in 27 provinces from China’s labor dynamic survey in 2016, the IV-Probit model was used to analyze the impact of LOE on CCE use, and the mediation effect model was used to examine the specific mechanism of action between them. (Results) The results found that: (1) LOE accounted for about 39%, and farmers’ utilization rate of CCE accounted for 40%. (2) LOE has significantly promoted the use of CCE by farmers, and this action mechanism is mainly realized through three paths, that is, per capita annual cash income, social relationship network, and family population structure. (3) The heterogeneity analysis results showed that the head of the household having a university education or above, the family being located in rural areas and mountainous areas, and LOE will have a greater positive impact on the farmers’ CCE use. (Policy) From the micro perspective of LOE, this study can deepen our understanding of LOE and CCE use decisions, and then provide a reference for the rational allocation of labor resources and farmers’ CCE-related policy formulation