GIS-based landslide susceptibility modeling using data mining techniques

Introduction: Landslide is one of the most widespread geohazards around the world. Therefore, it is necessary and meaningful to map regional landslide susceptibility for landslide mitigation. In this research, landslide susceptibility maps were produced by four models, namely, certainty factors (CF), naive Bayes (NB), J48 decision tree (J48), and multilayer perceptron (MLP) models.Methods: In the first step, 328 landslides were identified via historical data, interpretation of remote sensing images, and field investigation, and they were divided into two subsets that were assigned different uses: 70% subset for training and 30% subset for validating. Then, twelve conditioning factors were employed, namely, altitude, slope angle, slope aspect, plan curvature, profile curvature, TWI, NDVI, distance to rivers, distance to roads, land use, soil, and lithology. Later, the importance of each conditioning factor was analyzed by average merit (AM) values, and the relationship between landslide occurrence and various factors was evaluated using the certainty factor (CF) approach. In the next step, the landslide susceptibility maps were produced based on four models, and the effect of the four models were quantitatively compared by receiver operating characteristic (ROC) curves, area under curve (AUC) values, and non-parametric tests.Results: The results demonstrated that all the four models can reasonably assess landslide susceptibility. Of these four models, the CF model has the best predictive performance for the training (AUC=0.901) and validating data (AUC=0.892).Discussion: The proposed approach is an innovative method that may also help other scientists to develop landslide susceptibility maps in other areas and that could be used for geo-environmental problems besides natural hazard assessments

piRNAs mediate posttranscriptional retroelement silencing and localization to pi-bodies in the Drosophila germline

Nuage, a well-conserved perinuclear organelle found in germline cells, is thought to mediate retroelement repression in Drosophila melanogaster by regulating the production of Piwi-interacting RNAs (piRNAs). In this study, we present evidence that the nuage–piRNA pathway components can be found in cytoplasmic foci that also contain retroelement transcripts, antisense piRNAs, and proteins involved in messenger RNA (mRNA) degradation. These mRNA degradation proteins, decapping protein 1/2 (DCP1/2), Me31B (maternal expression at 31B), and pacman (PCM), are normally thought of as components of processing bodies. In spindle-E (spn-E) and aubergine (aub) mutants that lack piRNA production, piRNA pathway proteins no longer overlap the mRNA degradation proteins. Concomitantly, spn-E and aub mutant ovaries show an accumulation of full-length retroelement transcripts and prolonged stabilization of HeT-A mRNA, supporting the role of piRNAs in mediating posttranscriptional retroelement silencing. HeT-A mRNA is derepressed in mRNA degradation mutants twin, dcp1, and ski3, indicating that these enzymes also aid in removing full-length transcripts and/or decay intermediates

Research Overview on Wireless Power Transmission Technology

According to the latest researches, this paper outlines the development of wireless power transmission and introduces the latest applications of wireless power transmission in life. To describe the wireless power transmission technologies in detail, the paper presents the short-range, medium-range and remote wireless power transmission, respectively. In addition, the paper also depicts some unique properties of wireless power transmission system to make readers understand WPT system better. At last, the existing problems and developing trends are presented

Research Overview on Wireless Power Transmission Technology

According to the latest researches, this paper outlines the development of wireless power transmission and introduces the latest applications of wireless power transmission in life. To describe the wireless power transmission technologies in detail, the paper presents the short-range, medium-range and remote wireless power transmission, respectively. In addition, the paper also depicts some unique properties of wireless power transmission system to make readers understand WPT system better. At last, the existing problems and developing trends are presented

Flood Risk Evaluation in the Middle Reaches of the Yangtze River Based on Eigenvector Spatial Filtering Poisson Regression

A Poisson regression based on eigenvector spatial filtering (ESF) is proposed to evaluate the flood risk in the middle reaches of the Yangtze River in China. Regression analysis is employed to model the relationship between the frequency of flood alarming events observed by hydrological stations and hazard-causing factors from 2005 to 2012. Eight factors, including elevation (ELE), slope (SLO), elevation standard deviation (ESD), river density (DEN), distance to mainstream (DIST), NDVI, annual mean rainfall (RAIN), mean annual maximum of three-day accumulated precipitation (ACC) and frequency of extreme rainfall (EXE) are selected and integrated into a GIS environment for the identification of flood-prone basins. ESF-based Poisson regression (ESFPS) can filter out the spatial autocorrelation. The methodology includes construction of a spatial weight matrix, testing of spatial autocorrelation, decomposition of eigenvectors, stepwise selection of eigenvectors and calculation of regression coefficients. Compared with the pseudo R squared obtained by PS (0.56), ESFPS exhibits better fitness with a value of 0.78, which increases by approximately 39.3%. ESFPS identifies six significant factors including ELE, DEN, EXE, DIST, ACC and NDVI, in which ACC and NDVI are the first two main factors. The method can provide decision support for flood risk relief and hydrologic station planning

Giant excitonic upconverted emission from two-dimensional semiconductor in doubly resonant plasmonic nanocavity

Phonon-assisted upconverted emission is the heart of energy harvesting, bioimaging, optical cryptography, and optical refrigeration. It has been demonstrated that emerging two-dimensional (2D) semiconductors can provide an excellent platform for efficient phonon-assisted upconversion due to the enhanced optical transition strength and phonon-exciton interaction of 2D excitons. However, there is little research on the further enhancement of excitonic upconverted emission in 2D semiconductors. Here, we report the enhanced multiphoton upconverted emission of 2D excitons in doubly resonant plasmonic nanocavities. Owing to the enhanced light collection, enhanced excitation rate, and quantum efficiency enhancement arising from the Purcell effect, an upconverted emission amplification of >1000-fold and a decrease of 2~3 orders of magnitude in the saturated excitation power are achieved. These findings pave the way for the development of excitonic upconversion lasing, nanoscopic thermometry, and sensing, revealing the possibility of optical refrigeration in future 2D electronic or excitonic devices.Published versionThis work is supported by National Key Research and Development Program of China (grant no. 2017YFA0206000), Beijing Natural Science Foundation (grant nos. Z180011), National Key Research Program (2017YFA0205700, 2019YFA0210203, 2020YFA0211300), National Science Foundation of China (grant nos. 12027807, 21790364, 12104241), and High-performance Computing Platform of Peking University