scholarly journals An improved method of Newmark analysis for mapping hazards of coseismic landslides

2019 ◽  
Author(s):  
Mingdong Zang ◽  
Shengwen Qi ◽  
Yu Zou ◽  
Zhuping Sheng ◽  
Blanca S. Zamora
Keyword(s):  
Factor Model ◽  
Area Under The Curve ◽  
Infrastructure Development ◽  
Improved Method ◽  
Permanent Displacement ◽  
Coseismic Landslides ◽  
Ludian Earthquake ◽  
Slide Surface ◽  
Improved Performance ◽  
Using Data

Abstract. Coseismic landslides have been responsible for destroyed buildings and structures, dislocated roads and bridges, cut off of pipelines and lifelines, and tens of thousands of deaths. Accurately mapping the hazards of coseismic landslides is an important and challenge work. Newmark's method is widely applied to assess the permanent displacement along a potential slide surface to determine the coseismic responses of the slope. This paper considers the roughness and size effect of the potential slide surface-unloading joint, and then presents an improved method of Newmark analysis for mapping hazard of coseismic landslides. The improved method is verified using data from a case study of the 2014 Mw 6.1 (USGS) Ludian earthquake in Yunnan Province, China. The permanent displacement yielded from this method range from 0 to 122 cm. Comparisons are made between the predicted displacements and a comprehensive inventory of landslides triggered by the Ludian earthquake to map the spatial variability using certainty factor model (CFM). Confidence levels of coseismic landslides indicated by certainty factors range from −1 to 0.95. A coseismic landslide hazard map is then produced based on the spatial distribution of the values of certainty factors. Area under the curve analysis is used to draw a comparison between the improved and conventional method of Newmark analysis, revealing the improved performance of the method presented in this paper. Such method can be applied to predict the hazard zone of the region and provide guidelines for making decisions regarding infrastructure development and post-earthquake reconstruction.

scholarly journals An improved method of Newmark analysis for mapping hazards of coseismic landslides

2020 ◽  
Vol 20 (3) ◽  
pp. 713-726
Author(s):  
Mingdong Zang ◽  
Shengwen Qi ◽  
Yu Zou ◽  
Zhuping Sheng ◽  
Blanca S. Zamora
Keyword(s):  
Factor Model ◽  
Area Under The Curve ◽  
The United States ◽  
United States Geological Survey ◽  
Certainty Factor ◽  
Permanent Displacement ◽  
Mapping Procedure ◽  
Coseismic Landslides ◽  
Ludian Earthquake ◽  
Improved Performance

Abstract. Coseismic landslides can destroy buildings, dislocate roads, sever pipelines, and cause heavy casualties. It is thus important but challenging to accurately map the hazards posed by coseismic landslides. Newmark's method is widely applied to assess the permanent displacement along a potential slide surface and model the coseismic response of slopes. This paper proposes an improved Newmark analysis for mapping the hazards of coseismic landslides by considering the roughness and effect of the size of the potential slide surfaces. This method is verified by data from a case study on the 2014 Mw 6.1 (the United States Geological Survey) Ludian earthquake in Yunnan Province, China. Permanent displacements due to the earthquake ranged from 0 to 122 cm. The predicted displacements were compared with a comprehensive inventory of landslides triggered by the Ludian earthquake to map the spatial variation in the hazards of coseismic landslides using the certainty factor model. The confidence levels of coseismic landslides indicated by the certainty factors ranged from −1 to 0.95. A hazard map of the coseismic landslide was generated based on the spatial distribution of values of the certainty factor. A regression curve relating the predicted displacement and the certainty factor was drawn, and can be applied to predict the hazards of coseismic landslides for any seismic scenario of interest. The area under the curve was used to compare the improved and the conventional Newmark analyses, and revealed the improved performance of the former. This mapping procedure can be used to predict the hazards posed by coseismic landslides, and provide guidelines for decisions regarding the development of infrastructure and post-earthquake reconstruction.

scholarly journals A probabilistic method for mapping earth fissure hazards

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingdong Zang ◽  
Jianbing Peng ◽  
Nengxiong Xu ◽  
Zhijie Jia
Keyword(s):  
Factor Model ◽  
Probabilistic Method ◽  
Active Faults ◽  
Area Under The Curve ◽  
Susceptibility Map ◽  
Infrastructure Development ◽  
Mapping Procedure ◽  
Earth Fissure ◽  
Earth Fissures ◽  
Taiyuan Basin

AbstractEarth fissures caused by tectonic forces, human activities, or both seriously threaten the safety of people’s lives and properties. The Taiyuan Basin, a Cenozoic downfaulted basin located in the centre of the Fen-Wei Basin tectonic belt, in northwestern China, presents the ideal study area for a hazard assessment of earth fissures. A total of 104 earth fissures have been observed in the Taiyuan Basin, with a total length of approximately 128 km. In this paper, we proposed a probabilistic method for mapping earth fissure hazards by integrating the analytic hierarchy process (AHP), the area under the curve (AUC), and the certainty factor model (CFM). Geomorphic units, geologic formations, active faults and land subsidence zones of the Taiyuan Basin were mapped in detail. Correlations between these factors and earth fissures were evaluated through spatial modelling in ArcGIS. The AUC was introduced into the AHP to weight each factor and thus, to derive an earth fissure susceptibility map. Finally, the modelled earth fissure susceptibility was compared with a digital inventory of earth fissures to develop a probability function and map the spatial variability in failure probability through the CFM. The study indicates that active faults have the greatest contribution to the generation of earth fissures. Earth fissures are prone to develop in the piedmont alluvial-diluvial clinoplain and the transitional zone near the geomorphic boundary. This mapping procedure can assist in making rational decisions regarding urban planning and infrastructure development in areas susceptible to earth fissures.

scholarly journals An improved method of Newmark analysis for mapping hazards of coseismic landslides

2019 ◽  
Author(s):  
Mingdong Zang ◽  
Shengwen Qi ◽  
Zhuping Sheng ◽  
Blanca S. Zamora ◽  
Yu Zou
Keyword(s):  
Permanent Deformation ◽  
Regional Analysis ◽  
Deformation Analysis ◽  
Data Sets ◽  
Infrastructure Development ◽  
Permanent Displacement ◽  
Ground Shaking ◽  
Coseismic Landslides ◽  
Stability Of Slopes ◽  
Inexact Reasoning

Abstract. Coseismic landslides have been responsible for destroyed buildings and structures, dislocated roads and bridges, cut off of pipelines and lifelines, and tens of thousands of deaths. Newmark's method is widely applied to assess the permanent displacement along a potential slide surface to determine the coseismic responses of the slope. The Mw 6.1 (USGS) earthquake in Ludian, Yunnan Province, China in 2014 has caused widespread landslides and provided the ideal data sets to conduct a regional analysis of coseismic stability of slopes. The data sets include the topography, shear strength, and ground shaking of the study area. All of these data sets are digitized and rasterized at 30 m grid spacing using ArcGIS and combined in a dynamic slope model based on Newmark permanent-deformation analysis. The application of Barton model was then applied in the permanent-deformation analysis. According to a method of inexact reasoning, comparisons are made between the predicted displacements and a comprehensive inventory of landslides triggered by the Ludian earthquake to map the spatial variability in certainty factors. A coseismic landslide hazard map is then produced based on the spatial distribution of the values of certainty factors. Such map can be applied to predict the hazard zone of the region and provide guidelines for making decisions regarding infrastructure development and post-earthquake reconstruction.

From Bi-Dimensionality to Uni-Dimensionality in Self-Report Questionnaires

2020 ◽  
pp. 1-14 ◽  
Author(s):  
Bjarne Schmalbach ◽  
Markus Zenger ◽  
Michalis P. Michaelides ◽  
Karin Schermelleh-Engel ◽  
Andreas Hinz ◽  
...  
Keyword(s):  
Factor Model ◽  
Common Factor ◽  
Self Regulation ◽  
Model Fit ◽  
Self Report ◽  
External Criterion ◽  
Common Factor Model ◽  
Random Intercept ◽  
Using Data ◽  
Core Self

Abstract. The common factor model – by far the most widely used model for factor analysis – assumes equal item intercepts across respondents. Due to idiosyncratic ways of understanding and answering items of a questionnaire, this assumption is often violated, leading to an underestimation of model fit. Maydeu-Olivares and Coffman (2006) suggested the introduction of a random intercept into the model to address this concern. The present study applies this method to six established instruments (measuring depression, procrastination, optimism, self-esteem, core self-evaluations, and self-regulation) with ambiguous factor structures, using data from representative general population samples. In testing and comparing three alternative factor models (one-factor model, two-factor model, and one-factor model with a random intercept) and analyzing differential correlational patterns with an external criterion, we empirically demonstrate the random intercept model’s merit, and clarify the factor structure for the above-mentioned questionnaires. In sum, we recommend the random intercept model for cases in which acquiescence is suspected to affect response behavior.

Measurement invariance of the Center for Epidemiologic Studies Depression Scale in parents of individuals with disabilities

2019 ◽  
Vol 47 (10) ◽  
pp. 1-9
Author(s):  
Eun-Young Park ◽  
Joungmin Kim
Keyword(s):  
South Korea ◽  
Measurement Invariance ◽  
Factor Model ◽  
Panel Study ◽  
Depression Scale ◽  
Epidemiologic Studies ◽  
Fit Indices ◽  
Chi Square ◽  
Using Data ◽  
Invariance Model

We aimed to verify the factor model and measurement invariance of the abbreviated Center for Epidemiologic Studies Depression Scale by conducting a confirmatory factor analysis using data from 761 parents of individuals with intellectual disabilities who completed the scale as part of the 2011 Survey on the Actual Conditions of Individuals with Developmental Disabilities, South Korea, and 7,301 participants from the general population who completed the scale as part of the 2011 Welfare Panel Study and Survey by the Ministry of Health and Welfare, South Korea. We used fit indices to assess data reliability and Amos 22.0 for data analysis. According to the results, the 4-factor model had an appropriate fit to the data and the regression coefficients were significant. However, the chi-square difference test result was nonsignificant; therefore, the metric invariance model was the most appropriate measurement invariance model for the data. Implications of the findings are discussed.

scholarly journals Comorbidity index for predicting mortality at 6 months after reperfusion therapy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hyo Suk Nam ◽  
Young Dae Kim ◽  
Joonsang Yoo ◽  
Hyungjong Park ◽  
Byung Moon Kim ◽  
...  
Keyword(s):  
Prospective Cohort ◽  
Multivariate Logistic Regression Analysis ◽  
Area Under The Curve ◽  
Reperfusion Therapy ◽  
Good Prediction ◽  
Multivariate Logistic Regression ◽  
Stroke Patients ◽  
Number Of Patients ◽  
Comorbidity Index ◽  
Using Data

AbstractThe eligibility of reperfusion therapy has been expanded to increase the number of patients. However, it remains unclear the reperfusion therapy will be beneficial in stroke patients with various comorbidities. We developed a reperfusion comorbidity index for predicting 6-month mortality in patients with acute stroke receiving reperfusion therapy. The 19 comorbidities included in the Charlson comorbidity index were adopted and modified. We developed a statistical model and it was validated using data from a prospective cohort. Among 1026 patients in the retrospective nationwide reperfusion therapy registry, 845 (82.3%) had at least one comorbidity. As the number of comorbidities increased, the likelihood of mortality within 6 months also increased (p < 0.001). Six out of the 19 comorbidities were included for developing the reperfusion comorbidity index on the basis of the odds ratios in the multivariate logistic regression analysis. This index showed good prediction of 6-month mortality in the retrospective cohort (area under the curve [AUC], 0.747; 95% CI, 0.704–0.790) and in 333 patients in the prospective cohort (AUC, 0.784; 95% CI, 0.709–0.859). Consideration of comorbidities might be helpful for the prediction of the 6-month mortality in patients with acute ischemic stroke who receive reperfusion therapy.

A Comparison of Two Five-Factor Model Operationalizations of the Triarchic Model of Psychopathy in a Clinical Sample

Assessment ◽  
2021 ◽  
pp. 107319112110061
Author(s):  
Jared R. Ruchensky ◽  
M. Brent Donnellan ◽  
Christopher J. Hopwood ◽  
John F. Edens ◽  
Andrew E. Skodol ◽  
...  
Keyword(s):  
Negative Affect ◽  
Personality Traits ◽  
Convergent Validity ◽  
Factor Model ◽  
Clinical Sample ◽  
Five Factor Model ◽  
Neo Personality Inventory ◽  
Neo Personality Inventory Revised ◽  
Using Data ◽  
Triarchic Model

Structural models of personality traits, particularly the five-factor model (FFM), continue to inform ongoing debates regarding what personality attributes and trait domains are central to psychopathy. A growing body of literature has linked the constructs of the triarchic model of psychopathy (boldness, meanness, disinhibition) to the FFM. Recently, researchers developed both item and regression-based measures of the triarchic model of psychopathy using the NEO Personality Inventory–Revised—a popular measure of the FFM. The current study examines the correlates of these two FFM-derived operationalizations of the triarchic model using data from the Collaborative Longitudinal Personality Disorders Study. The two approaches had strong convergent validity coefficients and similar patterns of criterion-related validity coefficients. Meanness related to greater personality pathology characterized by exploitation of others and poor attachment, whereas disinhibition related to indicators of greater negative affect and poor behavioral constraint. Boldness related to reduced negative affect and greater narcissistic personality traits. Although the item and regression-based approaches showed similar patterns of associations with criterion-variables, the item-based approach has some practical and psychometric advantages over the regression-based approach given strong correlations between the meanness and disinhibition scores from the regression approach.

scholarly journals Assisting scalable diagnosis automatically via CT images in the combat against COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bohan Liu ◽  
Pan Liu ◽  
Lutao Dai ◽  
Yanlin Yang ◽  
Peng Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Area Under The Curve ◽  
Independent Set ◽  
Reference Method ◽  
Ct Images ◽  
Loss Of Life ◽  
Case Identification ◽  
Reverse Transcription Pcr ◽  
Using Data

AbstractThe pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

scholarly journals Text Mining Drug-Protein Interactions using an Ensemble of BERT, Sentence BERT and T5 models

2021 ◽  
Author(s):  
Xin Sui ◽  
Wanjing Wang ◽  
Jinfeng Zhang
Keyword(s):  
Protein Interactions ◽  
Clustering Algorithm ◽  
Data Augmentation ◽  
Majority Vote ◽  
Classification Model ◽  
Ensemble Model ◽  
K Nearest Neighbors ◽  
Test Dataset ◽  
Improved Performance ◽  
Using Data

In this work, we trained an ensemble model for predicting drug-protein interactions within a sentence based on only its semantics. Our ensembled model was built using three separate models: 1) a classification model using a fine-tuned BERT model; 2) a fine-tuned sentence BERT model that embeds every sentence into a vector; and 3) another classification model using a fine-tuned T5 model. In all models, we further improved performance using data augmentation. For model 2, we predicted the label of a sentence using k-nearest neighbors with its embedded vector. We also explored ways to ensemble these 3 models: a) we used the majority vote method to ensemble these 3 models; and b) based on the HDBSCAN clustering algorithm, we trained another ensemble model using features from all the models to make decisions. Our best model achieved an F-1 score of 0.753 on the BioCreative VII Track 1 test dataset.

scholarly journals The Healthy Personality from a Basic Trait Perspective

2018 ◽  
Author(s):  
Wiebke Bleidorn ◽  
Christopher James Hopwood ◽  
Robert A. Ackerman ◽  
Edward A. Witt ◽  
Christian Kandler ◽  
...  
Keyword(s):  
Factor Model ◽  
Rank Order ◽  
Five Factor Model ◽  
Psychology Students ◽  
Healthy Person ◽  
Comprehensive Description ◽  
Expert Rating ◽  
Two Samples ◽  
Using Data ◽  
Healthy Personality

We adopted an expert-rating approach to generate a consensus Five Factor Model (FFM) profile of the psychologically healthy person. In addition, we collected ratings from scholars with expertise in positive psychology and two samples of undergraduate psychology students to examine the agreement within and between different groups of raters. We then examined the reliability, heritability, rank-order stability, external validity, and normativeness of this expert-generated FFM profile of the healthy personality using data from seven different samples (N &gt; 3,000). To do this, we computed a healthy FFM score for each participant by using intraclass q-correlation to match individual FFM profiles to the healthy personality prototype. Through these analyses, we aim to provide an initial but nonetheless comprehensive description of the nature and correlates of the healthy personality from a contemporary basic trait perspective.

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