Reproducibility of quantitative susceptibility mapping in the brain at two field strengths from two vendors.

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Deh, Kofi; Nguyen, Thanh D; Eskreis-Winkler, Sarah; Prince, Martin R; Spincemaille, Pascal; Gauthier, Susan; Kovanlikaya, Ilhami; Zhang, Yan; Wang, Yi

2015-12-01

To assess the reproducibility of brain quantitative susceptibility mapping (QSM) in healthy subjects and in patients with multiple sclerosis (MS) on 1.5 and 3T scanners from two vendors. Ten healthy volunteers and 10 patients were scanned twice on a 3T scanner from one vendor. The healthy volunteers were also scanned on a 1.5T scanner from the same vendor and on a 3T scanner from a second vendor. Similar imaging parameters were used for all scans. QSM images were reconstructed using a recently developed nonlinear morphology-enabled dipole inversion (MEDI) algorithm with L1 regularization. Region-of-interest (ROI) measurements were obtained for 20 major brain structures. Reproducibility was evaluated with voxel-wise and ROI-based Bland-Altman plots and linear correlation analysis. ROI-based QSM measurements showed excellent correlation between all repeated scans (correlation coefficient R ≥ 0.97), with a mean difference of less than 1.24 ppb (healthy subjects) and 4.15 ppb (patients), and 95% limits of agreements of within -25.5 to 25.0 ppb (healthy subjects) and -35.8 to 27.6 ppb (patients). Voxel-based QSM measurements had a good correlation (0.64 ≤ R ≤ 0.88) and limits of agreements of -60 to 60 ppb or less. Brain QSM measurements have good interscanner and same-scanner reproducibility for healthy and MS subjects, respectively, on the systems evaluated in this study. © 2015 Wiley Periodicals, Inc.

Quantitative Susceptibility Mapping Indicates a Disturbed Brain Iron Homeostasis in Neuromyelitis Optica ? A Pilot Study

OpenAIRE

Doring, Thomas Martin; Granado, Vanessa; Rueda, Fernanda; Deistung, Andreas; Reichenbach, Juergen R.; Tukamoto, Gustavo; Gasparetto, Emerson Leandro; Schweser, Ferdinand

2016-01-01

Dysregulation of brain iron homeostasis is a hallmark of many neurodegenerative diseases and can be associated with oxidative stress. The objective of this study was to investigate brain iron in patients with Neuromyelitis Optica (NMO) using quantitative susceptibility mapping (QSM), a quantitative iron-sensitive MRI technique. 12 clinically confirmed NMO patients (6 female and 6 male; age 35.4y±14.2y) and 12 age- and sex-matched healthy controls (7 female and 5 male; age 33.9±11.3y) underwen...

Reduced deep regional cerebral venous oxygen saturation in hemodialysis patients using quantitative susceptibility mapping.

Science.gov (United States)

Chai, Chao; Liu, Saifeng; Fan, Linlin; Liu, Lei; Li, Jinping; Zuo, Chao; Qian, Tianyi; Haacke, E Mark; Shen, Wen; Xia, Shuang

2018-02-01

Cerebral venous oxygen saturation (SvO 2 ) is an important indicator of brain function. There was debate about lower cerebral oxygen metabolism in hemodialysis patients and there were no reports about the changes of deep regional cerebral SvO 2 in hemodialysis patients. In this study, we aim to explore the deep regional cerebral SvO 2 from straight sinus using quantitative susceptibility mapping (QSM) and the correlation with clinical risk factors and neuropsychiatric testing . 52 hemodialysis patients and 54 age-and gender-matched healthy controls were enrolled. QSM reconstructed from original phase data of 3.0 T susceptibility-weighted imaging was used to measure the susceptibility of straight sinus. The susceptibility was used to calculate the deep regional cerebral SvO 2 and compare with healthy individuals. Correlation analysis was performed to investigate the correlation between deep regional cerebral SvO 2 , clinical risk factors and neuropsychiatric testing. The deep regional cerebral SvO 2 of hemodialysis patients (72.5 ± 3.7%) was significantly lower than healthy controls (76.0 ± 2.1%) (P deep regional cerebral SvO 2 in patients. The Mini-Mental State Examination (MMSE) scores of hemodialysis patients were significantly lower than healthy controls (P deep regional cerebral SvO 2 did not correlate with MMSE scores (P = 0.630). In summary, the decreased deep regional cerebral SvO 2 occurred in hemodialysis patients and dialysis duration, parathyroid hormone, hematocrit, hemoglobin and red blood cell may be clinical risk factors.

Quantitative Susceptibility Mapping as a Possible Tool to Radiographically Diagnose Sentinel Headache Associated with Intracranial Aneurysm: Case Report.

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Nakagawa, Daichi; Cushing, Cameron; Nagahama, Yasunori; Allan, Lauren; Hasan, David

2017-07-01

Sentinel headache (SH) occurs before aneurysm rupture in an estimated 15%-60% of cases of aneurysmal subarachnoid hemorrhage (aSAH). By definition, noncontrast computed tomography (CT) scan of the brain and lumbar puncture are both negative in patients presenting with SH. One of the theories explaining this phenomenon is that microhemorrhage (MH) from the aneurysm wall contribute to iron deposition in the interface between the aneurysm wall and brain parenchyma. Quantitative susceptibility mapping (QSM) is a recently introduced magnetic resonance imaging (MRI) technique that has proven capable of localizing the deposition of paramagnetic metals, particularly ferric iron. Thus, the QSM sequence may be able to detect iron deposition secondary to MH. A 76-year-old male presented with the "worst headache of my life." Noncontrast head CT scan and lumbar puncture were negative. Magnetic resonance angiography (MRA) of the brain revealed an anterior communicating artery (A-com) aneurysm measuring 7 mm with a large bleb. T1-weighted imaging (WI), T2-WI, MRA, T2 star-weighted angiography (SWAN), and QSM sequences were obtained. T2-WI, SWAN, and QSM revealed isointense, hypointense, and hyperintense signals, respectively, at the interface of the aneurysm wall and brain tissue. These findings were consistent with deposition of ferric iron at this interface. The A-com aneurysm was treated with coil embolization, and the patient exhibited no postoperative deficits. The MRI QSM sequence can localize iron deposition resulting from MH within an aneurysmal wall. This sequence may be a promising imaging tool for screening patients presenting with SH. Copyright © 2017 Elsevier Inc. All rights reserved.

Changes of deep gray matter magnetic susceptibility over 2years in multiple sclerosis and healthy control brain

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Jesper Hagemeier

Full Text Available In multiple sclerosis, pathological changes of both tissue iron and myelin occur, yet these factors have not been characterized in a longitudinal fashion using the novel iron- and myelin-sensitive quantitative susceptibility mapping (QSM MRI technique. We investigated disease-relevant tissue changes associated with myelin loss and iron accumulation in multiple sclerosis deep gray matter (DGM over two years. One-hundred twenty (120 multiple sclerosis patients and 40 age- and sex-matched healthy controls were included in this prospective study. Written informed consent and local IRB approval were obtained from all participants. Clinical testing and QSM were performed both at baseline and at follow-up. Brain magnetic susceptibility was measured in major DGM structures. Temporal (baseline vs. follow-up and cross-sectional (multiple sclerosis vs. controls differences were studied using mixed factorial ANOVA analysis and appropriate t-tests. At either time-point, multiple sclerosis patients had significantly higher susceptibility in the caudate and globus pallidus and lower susceptibility in the thalamus. Over two years, susceptibility increased significantly in the caudate of both controls and multiple sclerosis patients. Inverse thalamic findings among MS patients suggest a multi-phase pathology explained by simultaneous myelin loss and/or iron accumulation followed by iron depletion and/or calcium deposition at later stages. Keywords: Quantitative susceptibility mapping, QSM, Iron, Multiple sclerosis, Longitudinal study

Non-Motor Symptom Burdens Are Not Associated with Iron Accumulation in Early Parkinson's Disease: a Quantitative Susceptibility Mapping Study.

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Shin, Chaewon; Lee, Seon; Lee, Jee Young; Rhim, Jung Hyo; Park, Sun Won

2018-03-26

Quantitative susceptibility mapping (QSM) has been used to measure iron accumulation in the deep nuclei of patients with Parkinson's disease (PD). This study examined the relationship between non-motor symptoms (NMSs) and iron accumulation in the deep nuclei of patients with PD. The QSM data were acquired from 3-Tesla magnetic resonance imaging (MRI) in 29 patients with early PD and 19 normal controls. The Korean version of the NMS scale (K-NMSS) was used for evaluation of NMSs in patients. The patients were divided into high NMS and low NMS groups. The region-of-interest analyses were performed in the following deep nuclei: red nucleus, substantia nigra pars compacta, substantia nigra pars reticulata, dentate nucleus, globus pallidus, putamen, and head of the caudate nucleus. Thirteen patients had high NMS scores (total K-NMSS score, mean = 32.1), and 16 had low NMS scores (10.6). The QSM values in the deep were not different among the patients with high NMS scores, low NMS scores, and controls. The QSM values were not correlated linearly with K-NMSS total score after adjusting the age at acquisition of brain MRI. The study demonstrated that the NMS burdens are not associated with iron accumulation in the deep nuclei of patients with PD. These results suggest that future neuroimaging studies on the pathology of NMSs in PD should use more specific and detailed clinical tools and recruit PD patients with severe NMSs. © 2018 The Korean Academy of Medical Sciences.

Combining Quantitative Susceptibility Mapping with Automatic Zero Reference (QSM0) and Myelin Water Fraction Imaging to Quantify Iron-Related Myelin Damage in Chronic Active MS Lesions.

Science.gov (United States)

Yao, Y; Nguyen, T D; Pandya, S; Zhang, Y; Hurtado Rúa, S; Kovanlikaya, I; Kuceyeski, A; Liu, Z; Wang, Y; Gauthier, S A

2018-02-01

A hyperintense rim on susceptibility in chronic MS lesions is consistent with iron deposition, and the purpose of this study was to quantify iron-related myelin damage within these lesions as compared with those without rim. Forty-six patients had 2 longitudinal quantitative susceptibility mapping with automatic zero reference scans with a mean interval of 28.9 ± 11.4 months. Myelin water fraction mapping by using fast acquisition with spiral trajectory and T2 prep was obtained at the second time point to measure myelin damage. Mixed-effects models were used to assess lesion quantitative susceptibility mapping and myelin water fraction values. Quantitative susceptibility mapping scans were on average 6.8 parts per billion higher in 116 rim-positive lesions compared with 441 rim-negative lesions ( P quantitative susceptibility mapping values of both the rim and core regions ( P Quantitative susceptibility mapping scans and myelin water fraction in rim-positive lesions decreased from rim to core, which is consistent with rim iron deposition. Whole lesion myelin water fractions for rim-positive and rim-negative lesions were 0.055 ± 0.07 and 0.066 ± 0.04, respectively. In the mixed-effects model, rim-positive lesions had on average 0.01 lower myelin water fraction compared with rim-negative lesions ( P quantitative susceptibility mapping scan was negatively associated with follow-up myelin water fraction ( P Quantitative susceptibility mapping rim-positive lesions maintained a hyperintense rim, increased in susceptibility, and had more myelin damage compared with rim-negative lesions. Our results are consistent with the identification of chronic active MS lesions and may provide a target for therapeutic interventions to reduce myelin damage. © 2018 by American Journal of Neuroradiology.

Mapping Magnetic Susceptibility Anisotropies of White Matter in vivo in the Human Brain at 7 Tesla

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Li, Xu; Vikram, Deepti S; Lim, Issel Anne L; Jones, Craig K; Farrell, Jonathan A.D.; van Zijl, Peter C. M.

2012-01-01

High-resolution magnetic resonance phase- or frequency- shift images acquired at high field show contrast related to magnetic susceptibility differences between tissues. Such contrast varies with the orientation of the organ in the field, but the development of quantitative susceptibility mapping (QSM) has made it possible to reproducibly image the intrinsic tissue susceptibility contrast. However, recent studies indicate that magnetic susceptibility is anisotropic in brain white matter and, as such, needs to be described by a symmetric second-rank tensor (χ¯¯). To fully determine the elements of this tensor, it would be necessary to acquire frequency data at six or more orientations. Assuming cylindrical symmetry of the susceptibility tensor in myelinated white matter fibers, we propose a simplified method to reconstruct the susceptibility tensor in terms of a mean magnetic susceptibility, MMS = (χ∥ + 2χ⊥)/3 and a magnetic susceptibility anisotropy, MSA = χ∥ − χ⊥, where χ∥ and χ⊥ are susceptibility parallel and perpendicular to the white matter fiber direction, respectively. Computer simulations show that with a practical head rotation angle of around 20°–30°, four head orientations suffice to reproducibly reconstruct the tensor with good accuracy. We tested this approach on whole brain 1×1×1 mm3 frequency data acquired from five healthy subjects at 7 T. The frequency information from phase images collected at four head orientations was combined with the fiber direction information extracted from diffusion tensor imaging (DTI) to map the white matter susceptibility tensor. The MMS and MSA were quantified for regions in several large white matter fiber structures, including the corona radiata, posterior thalamic radiation and corpus callosum. MMS ranged from −0.037 to −0.053 ppm (referenced to CSF being about zero). MSA values could be quantified without the need for a reference and ranged between 0.004 and 0.029 ppm, in line with

Quantitative Susceptibility Mapping Indicates a Disturbed Brain Iron Homeostasis in Neuromyelitis Optica - A Pilot Study.

Directory of Open Access Journals (Sweden)

Thomas Martin Doring

Full Text Available Dysregulation of brain iron homeostasis is a hallmark of many neurodegenerative diseases and can be associated with oxidative stress. The objective of this study was to investigate brain iron in patients with Neuromyelitis Optica (NMO using quantitative susceptibility mapping (QSM, a quantitative iron-sensitive MRI technique. 12 clinically confirmed NMO patients (6 female and 6 male; age 35.4y±14.2y and 12 age- and sex-matched healthy controls (7 female and 5 male; age 33.9±11.3y underwent MRI of the brain at 3 Tesla. Quantitative maps of the effective transverse relaxation rate (R2* and magnetic susceptibility were calculated and a blinded ROI-based group comparison analysis was performed. Normality of the data and differences between patients and controls were tested by Kolmogorov-Smirnov and t-test, respectively. Correlation with age was studied using Spearman's rank correlation and an ANCOVA-like analysis. Magnetic susceptibility values were decreased in the red nucleus (p0.95; between -15 and -22 ppb depending on reference region with a trend toward increasing differences with age. R2* revealed significantly decreased relaxation in the optic radiations of five of the 12 patients (p<0.0001; -3.136±0.567 s-1. Decreased relaxation in the optic radiation is indicative for demyelination, which is in line with previous findings. Decreased magnetic susceptibility in the red nucleus is indicative for a lower brain iron concentration, a chemical redistribution of iron into less magnetic forms, or both. Further investigations are necessary to elucidate the pathological cause or consequence of this finding.

Susceptibility Tensor Imaging (STI) of the Brain

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Li, Wei; Liu, Chunlei; Duong, Timothy Q.; van Zijl, Peter C.M.; Li, Xu

2016-01-01

Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility (MMS) and magnetic susceptibility anisotropy (MSA) can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping (QSM) to remove such dependence. Similar to diffusion tensor imaging (DTI), STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of susceptibility anisotropy in brain white matter is myelin. Another unique feature of susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. PMID:27120169

Magnetic susceptibility in the deep layers of the primary motor cortex in Amyotrophic Lateral Sclerosis

Directory of Open Access Journals (Sweden)

M. Costagli

2016-01-01

Full Text Available Amyotrophic Lateral Sclerosis (ALS is a progressive neurological disorder that entails degeneration of both upper and lower motor neurons. The primary motor cortex (M1 in patients with upper motor neuron (UMN impairment is pronouncedly hypointense in Magnetic Resonance (MR T2* contrast. In the present study, 3D gradient-recalled multi-echo sequences were used on a 7 Tesla MR system to acquire T2*-weighted images targeting M1 at high spatial resolution. MR raw data were used for Quantitative Susceptibility Mapping (QSM. Measures of magnetic susceptibility correlated with the expected concentration of non-heme iron in different regions of the cerebral cortex in healthy subjects. In ALS patients, significant increases in magnetic susceptibility co-localized with the T2* hypointensity observed in the middle and deep layers of M1. The magnetic susceptibility, hence iron concentration, of the deep cortical layers of patients' M1 subregions corresponding to Penfield's areas of the hand and foot in both hemispheres significantly correlated with the clinical scores of UMN impairment of the corresponding limbs. QSM therefore reflects the presence of iron deposits related to neuroinflammatory reaction and cortical microgliosis, and might prove useful in estimating M1 iron concentration, as a possible radiological sign of severe UMN burden in ALS patients.

In Vivo MRI Mapping of Brain Iron Deposition across the Adult Lifespan.

Science.gov (United States)

Acosta-Cabronero, Julio; Betts, Matthew J; Cardenas-Blanco, Arturo; Yang, Shan; Nestor, Peter J

2016-01-13

Disruption of iron homeostasis as a consequence of aging is thought to cause iron levels to increase, potentially promoting oxidative cellular damage. Therefore, understanding how this process evolves through the lifespan could offer insights into both the aging process and the development of aging-related neurodegenerative brain diseases. This work aimed to map, in vivo for the first time with an unbiased whole-brain approach, age-related iron changes using quantitative susceptibility mapping (QSM)--a new postprocessed MRI contrast mechanism. To this end, a full QSM standardization routine was devised and a cohort of N = 116 healthy adults (20-79 years of age) was studied. The whole-brain and ROI analyses confirmed that the propensity of brain cells to accumulate excessive iron as a function of aging largely depends on their exact anatomical location. Whereas only patchy signs of iron scavenging were observed in white matter, strong, bilateral, and confluent QSM-age associations were identified in several deep-brain nuclei--chiefly the striatum and midbrain-and across motor, premotor, posterior insular, superior prefrontal, and cerebellar cortices. The validity of QSM as a suitable in vivo imaging technique with which to monitor iron dysregulation in the human brain was demonstrated by confirming age-related increases in several subcortical nuclei that are known to accumulate iron with age. The study indicated that, in addition to these structures, there is a predilection for iron accumulation in the frontal lobes, which when combined with the subcortical findings, suggests that iron accumulation with age predominantly affects brain regions concerned with motor/output functions. This study used a whole--brain imaging approach known as quantitative susceptibility mapping (QSM) to provide a novel insight into iron accumulation in the brain across the adult lifespan. Validity of the method was demonstrated by showing concordance with ROI analysis and prior knowledge

Principles and applications of susceptibility weighted imaging; Grundlagen und Anwendungen der suszeptibilitaetsgewichteten Bildgebung

Energy Technology Data Exchange (ETDEWEB)

Kurz, F.T.; Ziener, C.H. [Deutsches Krebsforschungszentrum, Radiologie E010, INF 280, Heidelberg (Germany); Universitaetsklinikum Heidelberg, Abteilung fuer Neuroradiologie, INF 400, Heidelberg (Germany); Freitag, M.; Schlemmer, H.P. [Deutsches Krebsforschungszentrum, Radiologie E010, INF 280, Heidelberg (Germany); Bendszus, M. [Universitaetsklinikum Heidelberg, Abteilung fuer Neuroradiologie, INF 400, Heidelberg (Germany)

2016-02-15

Susceptibility-weighted imaging (SWI), initially developed to provide an improved method for cerebral magnetic resonance (MR) venography, is now an integral part of neuroradiological diagnostics and is steadily gaining importance in non-cerebral imaging. Tissue-inherent susceptibility differences generate a local magnetic field in which the dephasing of signal-producing protons occurs. This leads to a characteristic phase shift that can be used as a means to enhance contrast in the well-known T2*-weighted imaging. Many medically relevant pathologies induce tissue alterations that also influence the magnetic properties of tissue. Thus, the detection of blood residues and calcifications in SWI is superior to conventional MR sequences. New techniques, such as quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) allow improved differentiation between blood residues and calcifications and provide an alternative imaging method for fiber tractography with respect to diffusion tensor imaging. (orig.) [German] Die suszeptibilitaetsgewichtete Bildgebung (SWI), urspruenglich entwickelt als verbessertes Verfahren fuer die zerebrale MR-Venographie, ist inzwischen ein fester Bestandteil der neuroradiologischen Diagnostik und gewinnt zunehmend an Bedeutung in der nichtzerebralen Bildgebung. Gewebespezifische Suszeptibilitaetsunterschiede erzeugen ein lokales Magnetfeld, in dem die Dephasierung der signalgebenden Protonen stattfindet. Dabei kommt es zu einer charakteristischen Phasenverschiebung, die als Kontrastverstaerkung in der bekannten T2*-Bildgebung genutzt werden kann. Viele medizinisch relevante Pathologien erzeugen Veraenderungen im Gewebe, die auch die magnetischen Eigenschaften beeinflussen. So koennen Blutungen und Verkalkungen in der SWI besser identifiziert werden als mit konventionellen MR-Sequenzen. Neuere Techniken wie die quantitative Suszeptibilitaetskartierung (QSM) bzw. die Suszeptibilitaets-Tensor-Bildgebung (STI) ermoeglichen

Landslide susceptibility map: from research to application

Science.gov (United States)

Fiorucci, Federica; Reichenbach, Paola; Ardizzone, Francesca; Rossi, Mauro; Felicioni, Giulia; Antonini, Guendalina

2014-05-01

Susceptibility map is an important and essential tool in environmental planning, to evaluate landslide hazard and risk and for a correct and responsible management of the territory. Landslide susceptibility is the likelihood of a landslide occurring in an area on the basis of local terrain conditions. Can be expressed as the probability that any given region will be affected by landslides, i.e. an estimate of "where" landslides are likely to occur. In this work we present two examples of landslide susceptibility map prepared for the Umbria Region and for the Perugia Municipality. These two maps were realized following official request from the Regional and Municipal government to the Research Institute for the Hydrogeological Protection (CNR-IRPI). The susceptibility map prepared for the Umbria Region represents the development of previous agreements focused to prepare: i) a landslide inventory map that was included in the Urban Territorial Planning (PUT) and ii) a series of maps for the Regional Plan for Multi-risk Prevention. The activities carried out for the Umbria Region were focused to define and apply methods and techniques for landslide susceptibility zonation. Susceptibility maps were prepared exploiting a multivariate statistical model (linear discriminant analysis) for the five Civil Protection Alert Zones defined in the regional territory. The five resulting maps were tested and validated using the spatial distribution of recent landslide events that occurred in the region. The susceptibility map for the Perugia Municipality was prepared to be integrated as one of the cartographic product in the Municipal development plan (PRG - Piano Regolatore Generale) as required by the existing legislation. At strategic level, one of the main objectives of the PRG, is to establish a framework of knowledge and legal aspects for the management of geo-hydrological risk. At national level most of the susceptibility maps prepared for the PRG, were and still are obtained

Storm-Induced Slope Failure Susceptibility Mapping

Science.gov (United States)

2018-01-01

A pilot study was conducted to characterize and map the areas susceptible to slope failure using state-wide available data. The objective was to determine whether it would be possible to provide slope-failure susceptibility mapping that could be used...

Landslides susceptibility mapping at Gunung Ciremai National Park

Science.gov (United States)

Faizin; Nur, Bambang Azis

2018-02-01

In addition to agriculture, tourism became one of primary economic income for communities around Mount Ciremai, West, Java. Unfortunately, the landscape of West Java has many potential causes to disasters, mainly landslides. Mapping of disaster susceptibility area is needed as a consideration of tourism planning. The study was conducted in Gunung Ciremai National Park, West Java. This paper propose a methodology to map landslides susceptibilities based on spatial data. Using Geographic Information System tools, several environmental parameters such as slope, land use, elevation, and lithology are scored to build a landslide susceptibility map. Then, susceptibility map is overlaid with Utilization Zone.

SU-F-I-24: Feasibility of Magnetic Susceptibility to Relative Electron Density Conversion Method for Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Ito, K; Kadoya, N; Chiba, M; Matsushita, H; Jingu, K [Tohoku University Graduate School of Medicine, Sendai, Miyagi (Japan); Sato, K; Nagasaka, T; Yamanaka, K [Tohoku University Hospital, Sendai, Miyagi (Japan); Dobashi, S; Takeda, K [Tohoku University, Sendai, Miyagi (Japan)

2016-06-15

Purpose: The aim of this study is to develop radiation treatment planning using magnetic susceptibility obtained from quantitative susceptibility mapping (QSM) via MR imaging. This study demonstrates the feasibility of a method for generating a substitute for a CT image from an MRI. Methods: The head of a healthy volunteer was scanned using a CT scanner and a 3.0 T MRI scanner. The CT imaging was performed with a slice thickness of 2.5 mm at 80 and 120 kV (dual-energy scan). These CT images were converted to relative electron density (rED) using the CT-rED conversion table generated by a previous dual-energy CT scan. The CT-rED conversion table was generated using the conversion of the energy-subtracted CT number to rED via a single linear relationship. One T2 star-weighted 3D gradient echo-based sequence with four different echo times images was acquired using the MRI scanner. These T2 star-weighted images were used to estimate the phase data. To estimate the local field map, a Laplacian unwrapping of the phase and background field removal algorithm were implemented to process phase data. To generate a magnetic susceptibility map from the local field map, we used morphology enabled dipole inversion method. The rED map was resampled to the same resolution as magnetic susceptibility, and the magnetic susceptibility-rED conversion table was obtained via voxel-by-voxel mapping between the magnetic susceptibility and rED maps. Results: A correlation between magnetic susceptibility and rED is not observed through our method. Conclusion: Our results show that the correlation between magnetic susceptibility and rED is not observed. As the next step, we assume that the voxel of the magnetic susceptibility map comprises two materials, such as water (0 ppm) and bone (-2.2 ppm) or water and marrow (0.81ppm). The elements of each voxel were estimated from the ratio of the two materials.

Preliminary soil-slip susceptibility maps, southwestern California

Science.gov (United States)

Morton, Douglas M.; Alvarez, Rachel M.; Campbell, Russell H.; Digital preparation by Bovard, Kelly R.; Brown, D.T.; Corriea, K.M.; Lesser, J.N.

2003-01-01

This group of maps shows relative susceptibility of hill slopes to the initiation sites of rainfall-triggered soil slip-debris flows in southwestern California. As such, the maps offer a partial answer to one part of the three parts necessary to predict the soil-slip/debris-flow process. A complete prediction of the process would include assessments of “where”, “when”, and “how big”. These maps empirically show part of the “where” of prediction (i.e., relative susceptibility to sites of initiation of the soil slips) but do not attempt to show the extent of run out of the resultant debris flows. Some information pertinent to “when” the process might begin is developed. “When” is determined mostly by dynamic factors such as rainfall rate and duration, for which local variations are not amenable to long-term prediction. “When” information is not provided on the maps but is described later in this narrative. The prediction of “how big” is addressed indirectly by restricting the maps to a single type of landslide process—soil slip-debris flows. The susceptibility maps were created through an iterative process from two kinds of information. First, locations of sites of past soil slips were obtained from inventory maps of past events. Aerial photographs, taken during six rainy seasons that produced abundant soil slips, were used as the basis for soil slip-debris flow inventory. Second, digital elevation models (DEM) of the areas that were inventoried were used to analyze the spatial characteristics of soil slip locations. These data were supplemented by observations made on the ground. Certain physical attributes of the locations of the soil-slip debris flows were found to be important and others were not. The most important attribute was the mapped bedrock formation at the site of initiation of the soil slip. However, because the soil slips occur in surficial materials overlying the bedrocks units, the bedrock formation can only serve as

A landslide susceptibility map of Africa

Science.gov (United States)

Broeckx, Jente; Vanmaercke, Matthias; Duchateau, Rica; Poesen, Jean

2017-04-01

Studies on landslide risks and fatalities indicate that landslides are a global threat to humans, infrastructure and the environment, certainly in Africa. Nonetheless our understanding of the spatial patterns of landslides and rockfalls on this continent is very limited. Also in global landslide susceptibility maps, Africa is mostly underrepresented in the inventories used to construct these maps. As a result, predicted landslide susceptibilities remain subject to very large uncertainties. This research aims to produce a first continent-wide landslide susceptibility map for Africa, calibrated with a well-distributed landslide dataset. As a first step, we compiled all available landslide inventories for Africa. This data was supplemented by additional landslide mapping with Google Earth in underrepresented regions. This way, we compiled 60 landslide inventories from the literature (ca. 11000 landslides) and an additional 6500 landslides through mapping in Google Earth (including 1500 rockfalls). Various environmental variables such as slope, lithology, soil characteristics, land use, precipitation and seismic activity, were investigated for their significance in explaining the observed spatial patterns of landslides. To account for potential mapping biases in our dataset, we used Monte Carlo simulations that selected different subsets of mapped landslides, tested the significance of the considered environmental variables and evaluated the performance of the fitted multiple logistic regression model against another subset of mapped landslides. Based on these analyses, we constructed two landslide susceptibility maps for Africa: one for all landslide types and one excluding rockfalls. In both maps, topography, lithology and seismic activity were the most significant variables. The latter factor may be surprising, given the overall limited degree of seismicity in Africa. However, its significance indicates that frequent seismic events may serve as in important

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

Science.gov (United States)

Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y

2018-04-01

Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping

An improved FSL-FIRST pipeline for subcortical gray matter segmentation to study abnormal brain anatomy using quantitative susceptibility mapping (QSM).

Science.gov (United States)

Feng, Xiang; Deistung, Andreas; Dwyer, Michael G; Hagemeier, Jesper; Polak, Paul; Lebenberg, Jessica; Frouin, Frédérique; Zivadinov, Robert; Reichenbach, Jürgen R; Schweser, Ferdinand

2017-06-01

Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool (FIRST) is one of the most popular software tools for automated subcortical segmentation based on T 1 -weighted (T1w) images. In this work, we demonstrate that FIRST tends to produce inaccurate SGM segmentation results in the case of abnormal brain anatomy, such as present in atrophied brains, due to a poor spatial match of the subcortical structures with the training data in the MNI space as well as due to insufficient contrast of SGM structures on T1w images. Consequently, such deviations from the average brain anatomy may introduce analysis bias in clinical studies, which may not always be obvious and potentially remain unidentified. To improve the segmentation of subcortical nuclei, we propose to use FIRST in combination with a special Hybrid image Contrast (HC) and Non-Linear (nl) registration module (HC-nlFIRST), where the hybrid image contrast is derived from T1w images and magnetic susceptibility maps to create subcortical contrast that is similar to that in the Montreal Neurological Institute (MNI) template. In our approach, a nonlinear registration replaces FIRST's default linear registration, yielding a more accurate alignment of the input data to the MNI template. We evaluated our method on 82 subjects with particularly abnormal brain anatomy, selected from a database of >2000 clinical cases. Qualitative and quantitative analyses revealed that HC-nlFIRST provides improved segmentation compared to the default FIRST method. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative susceptibility mapping of human brain at 3T: a multisite reproducibility study.

Science.gov (United States)

Lin, P-Y; Chao, T-C; Wu, M-L

2015-03-01

Quantitative susceptibility mapping of the human brain has demonstrated strong potential in examining iron deposition, which may help in investigating possible brain pathology. This study assesses the reproducibility of quantitative susceptibility mapping across different imaging sites. In this study, the susceptibility values of 5 regions of interest in the human brain were measured on 9 healthy subjects following calibration by using phantom experiments. Each of the subjects was imaged 5 times on 1 scanner with the same procedure repeated on 3 different 3T systems so that both within-site and cross-site quantitative susceptibility mapping precision levels could be assessed. Two quantitative susceptibility mapping algorithms, similar in principle, one by using iterative regularization (iterative quantitative susceptibility mapping) and the other with analytic optimal solutions (deterministic quantitative susceptibility mapping), were implemented, and their performances were compared. Results show that while deterministic quantitative susceptibility mapping had nearly 700 times faster computation speed, residual streaking artifacts seem to be more prominent compared with iterative quantitative susceptibility mapping. With quantitative susceptibility mapping, the putamen, globus pallidus, and caudate nucleus showed smaller imprecision on the order of 0.005 ppm, whereas the red nucleus and substantia nigra, closer to the skull base, had a somewhat larger imprecision of approximately 0.01 ppm. Cross-site errors were not significantly larger than within-site errors. Possible sources of estimation errors are discussed. The reproducibility of quantitative susceptibility mapping in the human brain in vivo is regionally dependent, and the precision levels achieved with quantitative susceptibility mapping should allow longitudinal and multisite studies such as aging-related changes in brain tissue magnetic susceptibility. © 2015 by American Journal of Neuroradiology.

Earthquake-induced landslide-susceptibility mapping using an artificial neural network

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S. Lee

2006-01-01

Full Text Available The purpose of this study was to apply and verify landslide-susceptibility analysis techniques using an artificial neural network and a Geographic Information System (GIS applied to Baguio City, Philippines. The 16 July 1990 earthquake-induced landslides were studied. Landslide locations were identified from interpretation of aerial photographs and field survey, and a spatial database was constructed from topographic maps, geology, land cover and terrain mapping units. Factors that influence landslide occurrence, such as slope, aspect, curvature and distance from drainage were calculated from the topographic database. Lithology and distance from faults were derived from the geology database. Land cover was identified from the topographic database. Terrain map units were interpreted from aerial photographs. These factors were used with an artificial neural network to analyze landslide susceptibility. Each factor weight was determined by a back-propagation exercise. Landslide-susceptibility indices were calculated using the back-propagation weights, and susceptibility maps were constructed from GIS data. The susceptibility map was compared with known landslide locations and verified. The demonstrated prediction accuracy was 93.20%.

Landslide susceptibility mapping using a neuro-fuzzy

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Lee, S.; Choi, J.; Oh, H.

2009-12-01

This paper develops and applied an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment using landslide-related factors and location for landslide susceptibility mapping. A neuro-fuzzy system is based on a fuzzy system that is trained by a learning algorithm derived from the neural network theory. The learning procedure operates on local information, and causes only local modifications in the underlying fuzzy system. The study area, Boun, suffered much damage following heavy rain in 1998 and was selected as a suitable site for the evaluation of the frequency and distribution of landslides. Boun is located in the central part of Korea. Landslide-related factors such as slope, soil texture, wood type, lithology, and density of lineament were extracted from topographic, soil, forest, and lineament maps. Landslide locations were identified from interpretation of aerial photographs and field surveys. Landslide-susceptible areas were analyzed by the ANFIS method and mapped using occurrence factors. In particular, we applied various membership functions (MFs) and analysis results were verified using the landslide location data. The predictive maps using triangular, trapezoidal, and polynomial MFs were the best individual MFs for modeling landslide susceptibility maps (84.96% accuracy), proving that ANFIS could be very effective in modeling landslide susceptibility mapping. Various MFs were used in this study, and after verification, the difference in accuracy according to the MFs was small, between 84.81% and 84.96%. The difference was just 0.15% and therefore the choice of MFs was not important in the study. Also, compared with the likelihood ratio model, which showed 84.94%, the accuracy was similar. Thus, the ANFIS could be applied to other study areas with different data and other study methods such as cross-validation. The developed ANFIS learns the if-then rules between landslide-related factors and landslide

Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition

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Li, Wei; Wu, Bing; Liu, Chunlei

2011-01-01

Image phase from gradient echo MRI provides a unique contrast that reflects brain tissue composition variations, such as iron and myelin distribution. Phase imaging is emerging as a powerful tool for the investigation of functional brain anatomy and disease diagnosis. However, the quantitative value of phase is compromised by its nonlocal and orientation dependent properties. There is an increasing need for reliable quantification of magnetic susceptibility, the intrinsic property of tissue. In this study, we developed a novel and accurate susceptibility mapping method that is also phase-wrap insensitive. The proposed susceptibility mapping method utilized two complementary equations: (1) the Fourier relationship of phase and magnetic susceptibility; and (2) the first-order partial derivative of the first equation in the spatial frequency domain. In numerical simulation, this method reconstructed the susceptibility map almost free of streaking artifact. Further, the iterative implementation of this method allowed for high quality reconstruction of susceptibility maps of human brain in vivo. The reconstructed susceptibility map provided excellent contrast of iron-rich deep nuclei and white matter bundles from surrounding tissues. Further, it also revealed anisotropic magnetic susceptibility in brain white matter. Hence, the proposed susceptibility mapping method may provide a powerful tool for the study of brain physiology and pathophysiology. Further elucidation of anisotropic magnetic susceptibility in vivo may allow us to gain more insight into the white matter microarchitectures. PMID:21224002

Mapping Landslides Susceptibility in a Traditional Northern Nigerian City

Science.gov (United States)

Oluwafemi, Olawale A.; Yakubu, Tahir A.; Muhammad, Mahmud U.; Shitta, Nyofo; Akinwumiju, Akinola S.

2018-05-01

As a result of dearth of relevant information about Landslides Susceptibility in Nigeria, the monitoring and assessment appears intractable. Hence, the study developed a Remote Sensing approach to mapping landslides susceptibility, landuse and landcover analysis in Jos South LGA, Plateau State, Nigeria. Field Observation, SPOT 5 2009 and 2012, ASTER DEM 2009, Geological Map 2006, Topographical Map 1966 were used to map Landslide Susceptibility and Landuse /Lancover Analysis in the study area. Geospatial Analytical Operations employed using ArcGIS 10.3 and Erdas Imagine 2014 include Spatial Modeling, Vectorization, Pre-lineament Extraction, Image Processing among others. Result showed that 72.38 % of the study area is underlain by granitic rocks. The landuse/cover types delineated for the study area include floodplain (29.27 %), farmland (23.96 %), sparsely vegetated land (15.43 %), built up area (13.65 %), vegetated outcrop (8.48 %), light vegetation (5.37 %), thick vegetation (2.39 %), water body (0.58 %), plantation (0.50 %) and mining pond (0.37 %). Landslide Susceptibility Analysis also revealed that 87 % of the study area is relatively at low to very low risk of landslide event. While only 13 % of the study area is at high to very high risk of landslide event. The study revealed that the susceptibility of landslide event is very low in the study area. However, possible landslide event in the hot spots could be pronounced and could destabilize the natural and man-made environmental systems of the study area.

Implementation of landslide susceptibility maps in Lower Austria as part of risk governance

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Bell, Rainer; Petschko, Helene; Bauer, Christian; Glade, Thomas; Granica, Klaus; Heiss, Gerhard; Leopold, Philip; Pomaroli, Gilbert; Proske, Herwig; Schweigl, Joachim

2013-04-01

Landslides frequently cause damage to agricultural land and infrastructure in Lower Austria - a province of Austria. Also settlements and people are threatened by landslides. To reduce landslide risks and to prevent the establishment of new settlements in highly landslide prone areas, the project "MoNOE" (Method development for landslide susceptibility modeling in Lower Austria) was set up by the provincial government. The main aim of the project is the development of methods to model rock fall and slide susceptibility for an area of approx. 15,900 km2 and to implement the resulting susceptibility maps into the spatial planning strategies of the state. Right from the beginning of the project a close cooperation between the involved scientists and the stakeholders from the Geological Survey of Lower Austria and the Department of Spatial Planning and Regional Policy of Lower Austria was established to ensure that method development and final susceptibility maps meet exactly the needs and demands of the stakeholders. This posed huge challenges, together with its realization in the large study area and a (heterogeneous) complex geological situation,. Limitations were given by restricted data availability (e.g. for geology or landslide inventories) in such a large study area. Rock fall susceptibility was modeled by a combined approach of determining rock fall release areas by empirical slope thresholds (dependent on geology) followed by empirical run-out modeling. Slide susceptibility was modeled based on the statistical approaches of weights of evidence (WofE) and generalized additive models (GAM) by two different research groups. Huge efforts were spent on the validation of all susceptibility models. In a later stage of the project we found that the best scientific maps are not necessarily the best maps to be implemented in spatial planning strategies. Thus, in close cooperation with the stakeholders, decisions had to be taken to find the best resolution of the maps

Manifestation of a neuro-fuzzy model to produce landslide susceptibility map using remote sensing data derived parameters

Science.gov (United States)

Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred

Landslides are the most common natural hazards in Malaysia. Preparation of landslide suscep-tibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. In this study, a new attempt is tried to produce landslide susceptibility map of a part of Cameron Valley of Malaysia. This paper develops an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment for landslide susceptibility mapping. To ob-tain the neuro-fuzzy relations for producing the landslide susceptibility map, landslide locations were identified from interpretation of aerial photographs and high resolution satellite images, field surveys and historical inventory reports. Landslide conditioning factors such as slope, plan curvature, distance to drainage lines, soil texture, lithology, and distance to lineament were extracted from topographic, soil, and lineament maps. Landslide susceptible areas were analyzed by the ANFIS model and mapped using the conditioning factors. Furthermore, we applied various membership functions (MFs) and fuzzy relations to produce landslide suscep-tibility maps. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. Results show that, triangular, trapezoidal, and polynomial MFs were the best individual MFs for modelling landslide susceptibility maps (86

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

Science.gov (United States)

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

Spatially explicit shallow landslide susceptibility mapping over large areas

Science.gov (United States)

Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping

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Suhua Zhou

2016-04-01

Full Text Available The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS platform. The analytical hierarchy process (AHP, which is subjective, was employed to weight predictive factors’ contribution to landslide occurrence. The frequency ratio (FR method, which is objective, was used to derive subclasses’ frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI, lithology, land cover and mean annual precipitation (MAP. The landslide susceptibility index (LSI was calculated using the weighted linear combination of factors’ weights and subclasses’ weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI. The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.

Effects of tissue susceptibility on brain temperature mapping.

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Maudsley, Andrew A; Goryawala, Mohammed Z; Sheriff, Sulaiman

2017-02-01

A method for mapping of temperature over a large volume of the brain using volumetric proton MR spectroscopic imaging has been implemented and applied to 150 normal subjects. Magnetic susceptibility-induced frequency shifts in gray- and white-matter regions were measured and included as a correction in the temperature mapping calculation. Additional sources of magnetic susceptibility variations of the individual metabolite resonance frequencies were also observed that reflect the cellular-level organization of the brain metabolites, with the most notable differences being attributed to changes of the N-Acetylaspartate resonance frequency that reflect the intra-axonal distribution and orientation of the white-matter tracts with respect to the applied magnetic field. These metabolite-specific susceptibility effects are also shown to change with age. Results indicate no change of apparent brain temperature with age from 18 to 84 years old, with a trend for increased brain temperature throughout the cerebrum in females relative for males on the order of 0.1°C; slightly increased temperatures in the left hemisphere relative to the right; and a lower temperature of 0.3°C in the cerebellum relative to that of cerebral white-matter. This study presents a novel acquisition method for noninvasive measurement of brain temperature that is of potential value for diagnostic purposes and treatment monitoring, while also demonstrating limitations of the measurement due to the confounding effects of tissue susceptibility variations. Copyright © 2016 Elsevier Inc. All rights reserved.

A comparative study on the landslide susceptibility mapping using ...

Indian Academy of Sciences (India)

from faults, lithology, normalized difference vegetation index (NDVI), sediment transport index (STI), stream power ... economic losses and creating high maintenance costs, are ..... evidence method to landslide susceptibility map- ping using ...

Comparing two models for post-wildfire debris flow susceptibility mapping

Science.gov (United States)

Cramer, J.; Bursik, M. I.; Legorreta Paulin, G.

2017-12-01

Traditionally, probabilistic post-fire debris flow susceptibility mapping has been performed based on the typical method of failure for debris flows/landslides, where slip occurs along a basal shear zone as a result of rainfall infiltration. Recent studies have argued that post-fire debris flows are fundamentally different in their method of initiation, which is not infiltration-driven, but surface runoff-driven. We test these competing models by comparing the accuracy of the susceptibility maps produced by each initiation method. Debris flow susceptibility maps are generated according to each initiation method for a mountainous region of Southern California that recently experienced wildfire and subsequent debris flows. A multiple logistic regression (MLR), which uses the occurrence of past debris flows and the values of environmental parameters, was used to determine the probability of future debris flow occurrence. The independent variables used in the MLR are dependent on the initiation method; for example, depth to slip plane, and shear strength of soil are relevant to the infiltration initiation, but not surface runoff. A post-fire debris flow inventory serves as the standard to compare the two susceptibility maps, and was generated by LiDAR analysis and field based ground-truthing. The amount of overlap between the true locations where debris flow erosion can be documented, and where the MLR predicts high probability of debris flow initiation was statistically quantified. The Figure of Merit in Space (FMS) was used to compare the two models, and the results of the FMS comparison suggest that surface runoff-driven initiation better explains debris flow occurrence. Wildfire can breed conditions that induce debris flows in areas that normally would not be prone to them. Because of this, nearby communities at risk may not be equipped to protect themselves against debris flows. In California, there are just a few months between wildland fire season and the wet

Mapping debris flow susceptibility using analytical network process ...

Indian Academy of Sciences (India)

Evangelin Ramani Sujatha

2017-11-23

Nov 23, 2017 ... methods known as the analytical network process (ANP) is used to map the ..... ciated in any prospective way, through feedbacks ..... slide susceptibility by means of multivariate statistical .... and bivariate statistics: A case study in southern Italy;. Nat. ... combination applied to Tevankarai Stream Watershed,.

Fuzzy rule-based landslide susceptibility mapping in Yığılca Forest District (Northwest of Turkey

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Abdurrahim Aydın

2016-07-01

Full Text Available Landslide susceptibility map of Yığılca Forest District was formed based on developed fuzzy rules using GIS-based FuzzyCell software. An inventory of 315 landslides was updated through fieldworks after inventory map previously generated by the authors. Based on the landslide susceptibility mapping study previously made in the same area, for the comparison of two maps, same 8 landslide conditioning parameters were selected and then fuzzified for the landslide susceptibility mapping: land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature. Mamdani model was selected as fuzzy inference system. After fuzzy rules definition, Center of Area (COA was selected as defuzzification method in model. The output of developed model was normalized between 0 and 1, and then divided five classes such as very low, low, moderate, high, and very high. According to developed model based 8 conditioning parameters, landslide susceptibility in Yığılca Forest District varies between 32 and 67 (in range of 0-100 with 0.703 Area Under the Curve (AUC value. According to classified landslide susceptibility map, in Yığılca Forest District, 32.89% of the total area has high and very high susceptibility while 29.59% of the area has low and very low susceptibility and the rest located in moderate susceptibility. The result of developed fuzzy rule based model compared with previously generated landslide map with logistic regression (LR. According to comparison of the results of two studies, higher differences exist in terms of AUC value and dispersion of susceptibility classes. This is because fuzzy rule based model completely depends on how parameters are classified and fuzzified and also depends on how truly the expert composed the rules. Even so, GIS-based fuzzy applications provide very valuable facilities for reasoning, which makes it possible to take into account inaccuracies and uncertainties.

Mapping of murine radiation-induced acute myeloid leukaemia susceptibility loci

International Nuclear Information System (INIS)

Darakhshan, F.

2001-01-01

Studies on radiation-induced AML have shown characteristic phenotypic variation in susceptibility amongst inbred mouse strains, suggesting the involvement of genetic factors in determining the development of AML post-irradiation exposure. The main objective of the present study therefore was to identify and map markers in linkage disequilibrium with gene variants associated with influencing susceptibility to radiation induced AML in mice. Given Chr 2 abnormalities are characteristic of AML in mice, this feature was exploited in an effort to overcome the long latency for AML development. Analysis of Chr 2 aberrations at 24 and 48 h following irradiation established a positive correlation between Chr 2 radiosensitivity and radiation-AML susceptibility thus validating the choice of substitute assay. The analysis also resulted in the identification of a further trait, additional to Chr 2 radiosensitivity, termed overall chromosome radiosensitivity. Genetic mapping of Chr 2 radiosensitivity using public domain microsatellite database information resulted in the definition of cluster regions on 7 different chromosomes. Further genotyping reduced the candidate regions to 3 specific regions of interest. A test of allelic association could not ascertain a conclusive link between markers at these regions and the Chr 2 radiosensitivity/radiation-AML susceptibility phenotype. However, a region on Chr 4 around D4Mit221 appears to be most strongly associated. Similar studies identified three chromosomal regions of interest (on Chrs 4, 8 and 16) associated with overall chromosome radiosensitivity trait. An independent mapping strategy using F3 RCS confirmed the likely involvement of two of the candidate Chr 2 radiosensitivity regions identified by the inbred analysis including that on Chr 4 and also highlighted phenotypic heterogeneity amongst resistant RC strains, suggesting the influence of multiple alleles in specific phenotypes. RFLP analysis of candidate genes, localised on

An Improved Information Value Model Based on Gray Clustering for Landslide Susceptibility Mapping

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Qianqian Ba

2017-01-01

Full Text Available Landslides, as geological hazards, cause significant casualties and economic losses. Therefore, it is necessary to identify areas prone to landslides for prevention work. This paper proposes an improved information value model based on gray clustering (IVM-GC for landslide susceptibility mapping. This method uses the information value derived from an information value model to achieve susceptibility classification and weight determination of landslide predisposing factors and, hence, obtain the landslide susceptibility of each study unit based on the clustering analysis. Using a landslide inventory of Chongqing, China, which contains 8435 landslides, three landslide susceptibility maps were generated based on the common information value model (IVM, an information value model improved by an analytic hierarchy process (IVM-AHP and our new improved model. Approximately 70% (5905 of the inventory landslides were used to generate the susceptibility maps, while the remaining 30% (2530 were used to validate the results. The training accuracies of the IVM, IVM-AHP and IVM-GC were 81.8%, 78.7% and 85.2%, respectively, and the prediction accuracies were 82.0%, 78.7% and 85.4%, respectively. The results demonstrate that all three methods perform well in evaluating landslide susceptibility. Among them, IVM-GC has the best performance.

Comprehensive Clinical Phenotyping and Genetic Mapping for the Discovery of Autism Susceptibility Genes

Science.gov (United States)

2013-03-14

behavioral teaching strategies and best practice for teaching students with autism spectrum disorders 4.52 Learn strategies for incorporating IEP goals...AFRL-SA-WP-TR-2013-0013 Comprehensive Clinical Phenotyping and Genetic Mapping for the Discovery of Autism Susceptibility Genes...Genetic Mapping for the Discovery of Autism Susceptibility Genes 5a. CONTRACT NUMBER N/A 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER N/A 6

Weights of Evidence Method for Landslide Susceptibility Mapping in Takengon, Central Aceh, Indonesia

Science.gov (United States)

Pamela; Sadisun, Imam A.; Arifianti, Yukni

2018-02-01

Takengon is an area prone to earthquake disaster and landslide. On July 2, 2013, Central Aceh earthquake induced large numbers of landslides in Takengon area, which resulted in casualties of 39 people. This location was chosen to assess the landslide susceptibility of Takengon, using a statistical method, referred to as the weight of evidence (WoE). This WoE model was applied to indicate the main factors influencing the landslide susceptible area and to derive landslide susceptibility map of Takengon. The 251 landslides randomly divided into two groups of modeling/training data (70%) and validation/test data sets (30%). Twelve thematic maps of evidence are slope degree, slope aspect, lithology, land cover, elevation, rainfall, lineament, peak ground acceleration, curvature, flow direction, distance to river and roads used as landslide causative factors. According to the AUC, the significant factor controlling the landslide is the slope, the slope aspect, peak ground acceleration, elevation, lithology, flow direction, lineament, and rainfall respectively. Analytical result verified by using test data of landslide shows AUC prediction rate is 0.819 and AUC success rate with all landslide data included is 0.879. This result showed the selective factors and WoE method as good models for assessing landslide susceptibility. The landslide susceptibility map of Takengon shows the probabilities, which represent relative degrees of susceptibility for landslide proneness in Takengon area.

Desertification Susceptibility Mapping Using Logistic Regression Analysis in the Djelfa Area, Algeria

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Farid Djeddaoui

2017-10-01

Full Text Available The main goal of this work was to identify the areas that are most susceptible to desertification in a part of the Algerian steppe, and to quantitatively assess the key factors that contribute to this desertification. In total, 139 desertified zones were mapped using field surveys and photo-interpretation. We selected 16 spectral and geomorphic predictive factors, which a priori play a significant role in desertification. They were mainly derived from Landsat 8 imagery and Shuttle Radar Topographic Mission digital elevation model (SRTM DEM. Some factors, such as the topographic position index (TPI and curvature, were used for the first time in this kind of study. For this purpose, we adapted the logistic regression algorithm for desertification susceptibility mapping, which has been widely used for landslide susceptibility mapping. The logistic model was evaluated using the area under the receiver operating characteristic (ROC curve. The model accuracy was 87.8%. We estimated the model uncertainties using a bootstrap method. Our analysis suggests that the predictive model is robust and stable. Our results indicate that land cover factors, including normalized difference vegetation index (NDVI and rangeland classes, play a major role in determining desertification occurrence, while geomorphological factors have a limited impact. The predictive map shows that 44.57% of the area is classified as highly to very highly susceptible to desertification. The developed approach can be used to assess desertification in areas with similar characteristics and to guide possible actions to combat desertification.

Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study

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Rubini Mahalingam

2016-11-01

Full Text Available Landslides are a significant geohazard, which frequently result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping using GIS and remote sensing can help communities prepare for these damaging events. Current mapping efforts utilize a wide variety of techniques and consider multiple factors. Unfortunately, each study is relatively independent of others in the applied technique and factors considered, resulting in inconsistencies. Further, input data quality often varies in terms of source, data collection, and generation, leading to uncertainty. This paper investigates if lidar-derived data-sets (slope, slope roughness, terrain roughness, stream power index, and compound topographic index can be used for predictive mapping without other landslide conditioning factors. This paper also assesses the differences in landslide susceptibility mapping using several, widely used statistical techniques. Landslide susceptibility maps were produced from the aforementioned lidar-derived data-sets for a small study area in Oregon using six representative statistical techniques. Most notably, results show that only a few factors were necessary to produce satisfactory maps with high predictive capability (area under the curve >0.7. The sole use of lidar digital elevation models and their derivatives can be used for landslide mapping using most statistical techniques without requiring additional detailed data-sets that are often difficult to obtain or of lower quality.

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

Science.gov (United States)

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy

Science.gov (United States)

Mancini, F.; Ceppi, C.; Ritrovato, G.

2010-09-01

This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.

Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India

Science.gov (United States)

Kumar, Deepak; Thakur, Manoj; Dubey, Chandra S.; Shukla, Dericks P.

2017-10-01

In recent years, various machine learning techniques have been applied for landslide susceptibility mapping. In this study, three different variants of support vector machine viz., SVM, Proximal Support Vector Machine (PSVM) and L2-Support Vector Machine - Modified Finite Newton (L2-SVM-MFN) have been applied on the Mandakini River Basin in Uttarakhand, India to carry out the landslide susceptibility mapping. Eight thematic layers such as elevation, slope, aspect, drainages, geology/lithology, buffer of thrusts/faults, buffer of streams and soil along with the past landslide data were mapped in GIS environment and used for landslide susceptibility mapping in MATLAB. The study area covering 1625 km2 has merely 0.11% of area under landslides. There are 2009 pixels for past landslides out of which 50% (1000) landslides were considered as training set while remaining 50% as testing set. The performance of these techniques has been evaluated and the computational results show that L2-SVM-MFN obtains higher prediction values (0.829) of receiver operating characteristic curve (AUC-area under the curve) as compared to 0.807 for PSVM model and 0.79 for SVM. The results obtained from L2-SVM-MFN model are found to be superior than other SVM prediction models and suggest the usefulness of this technique to problem of landslide susceptibility mapping where training data is very less. However, these techniques can be used for satisfactory determination of susceptible zones with these inputs.

Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area

Science.gov (United States)

Oh, Hyun-Joo; Pradhan, Biswajeet

2011-09-01

This paper presents landslide-susceptibility mapping using an adaptive neuro-fuzzy inference system (ANFIS) using a geographic information system (GIS) environment. In the first stage, landslide locations from the study area were identified by interpreting aerial photographs and supported by an extensive field survey. In the second stage, landslide-related conditioning factors such as altitude, slope angle, plan curvature, distance to drainage, distance to road, soil texture and stream power index (SPI) were extracted from the topographic and soil maps. Then, landslide-susceptible areas were analyzed by the ANFIS approach and mapped using landslide-conditioning factors. In particular, various membership functions (MFs) were applied for the landslide-susceptibility mapping and their results were compared with the field-verified landslide locations. Additionally, the receiver operating characteristics (ROC) curve for all landslide susceptibility maps were drawn and the areas under curve values were calculated. The ROC curve technique is based on the plotting of model sensitivity — true positive fraction values calculated for different threshold values, versus model specificity — true negative fraction values, on a graph. Landslide test locations that were not used during the ANFIS modeling purpose were used to validate the landslide susceptibility maps. The validation results revealed that the susceptibility maps constructed by the ANFIS predictive models using triangular, trapezoidal, generalized bell and polynomial MFs produced reasonable results (84.39%), which can be used for preliminary land-use planning. Finally, the authors concluded that ANFIS is a very useful and an effective tool in regional landslide susceptibility assessment.

Land subsidence susceptibility and hazard mapping: the case of Amyntaio Basin, Greece

Science.gov (United States)

Tzampoglou, P.; Loupasakis, C.

2017-09-01

Landslide susceptibility and hazard mapping has been applying for more than 20 years succeeding the assessment of the landslide risk and the mitigation the phenomena. On the contrary, equivalent maps aiming to study and mitigate land subsidence phenomena caused by the overexploitation of the aquifers are absent from the international literature. The current study focuses at the Amyntaio basin, located in West Macedonia at Florina prefecture. As proved by numerous studies the wider area has been severely affected by the overexploitation of the aquifers, caused by the mining and the agricultural activities. The intensive ground water level drop has triggered extensive land subsidence phenomena, especially at the perimeter of the open pit coal mine operating at the site, causing damages to settlements and infrastructure. The land subsidence susceptibility and risk maps were produced by applying the semi-quantitative WLC (Weighted Linear Combination) method, especially calibrated for this particular catastrophic event. The results were evaluated by using detailed field mapping data referring to the spatial distribution of the surface ruptures caused by the subsidence. The high correlation between the produced maps and the field mapping data, have proved the great value of the maps and of the applied technique on the management and the mitigation of the phenomena. Obviously, these maps can be safely used by decision-making authorities for the future urban safety development.

Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

Science.gov (United States)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2007-01-01

Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

Debris flows susceptibility mapping under tropical rain conditions in Rwanda.

Science.gov (United States)

Nduwayezu, Emmanuel; Nsengiyumva, Jean-Baptiste; BUgnon, Pierre-Charles; Jaboyedoff, Michel; Derron, Marc-Henri

2017-04-01

Rwanda is a densely populated country. It means that all the space is exploited, including sometimes areas with very steep slopes. This has as for consequences that during the rainy season slopes with human activities are affected by gravitational processes, mostly debris and mud flows and shallow landslides. The events of early May 2016 (May 8 and 9), with more than 50 deaths, are an illustration of these frequents landslides and inundations. The goal of this work is to produce a susceptibility map for debris/mud flows at regional/national scale. Main available pieces of data are a national digital terrain model at 10m resolution, bedrock and soil maps, and information collected during field visits on some specific localities. The first step is the characterization of the slope angle distribution for the different types of bedrock or soils (decomposition in Gaussian populations). Then, the combination of this information with other geomorphic and hydrologic parameters is used to define potential source areas of debris flows. Finally, propagation maps of debris flows are produced using FLOW-R (Horton et al. 2013). Horton, P., Jaboyedoff, M., Rudaz, B., and Zimmermann, M.: Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale, Nat. Hazards Earth Syst. Sci., 13, 869-885, doi:10.5194/nhess-13-869-2013, 2013. The paper is in open access.

An application of adaptive neuro-fuzzy inference system to landslide susceptibility mapping (Klang valley, Malaysia)

Science.gov (United States)

Sezer, Ebru; Pradhan, Biswajeet; Gokceoglu, Candan

2010-05-01

Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. Recently, the Klang Valley area of Selangor state has faced numerous landslide and mudflow events and much damage occurred in these areas. However, only little effort has been made to assess or predict these events which resulted in serious damages. Through scientific analyses of these landslides, one can assess and predict landslide-susceptible areas and even the events as such, and thus reduce landslide damages through proper preparation and/or mitigation. For this reason , the purpose of the present paper is to produce landslide susceptibility maps of a part of the Klang Valley areas in Malaysia by employing the results of the adaptive neuro-fuzzy inference system (ANFIS) analyses. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments and NDVI were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, plan curvature, distance from drainage, soil type, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to construct the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were obtained by using ANFIS results. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values was calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 98% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient

Weights of evidence method for landslide susceptibility mapping in Tangier, Morocco

Directory of Open Access Journals (Sweden)

Bousta Mahfoud

2018-01-01

Full Text Available Tangier region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Tangier using the Weight of Evidence method (WofE. The method is founded on the principle that an event (landslide is more likely to occur based on the relationship between the presence or absence of a predictive variable (predisposing factors and the occurrence of this event. The inventory, description and analysis of mass movements were prepared. Then the main factors governing their occurrence (lithology, fault, slope, elevation, exposure, drainage and land use were mapped before applying WofE. Finally, the ROC curves were established and the areas under curves (AUC were calculated to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. The prediction accuracy was found to be 70%. Obtained susceptibility map shows that 60% of inventoried landslides are in the high to very high susceptibility zones, which is very satisfactory for the validation of the adopted model and the obtained results. These zones are mainly located in the N-E and E part of the Tangier region in the soft and fragile facies of the marls and clays of the Tangier unit, where landuse is characterized by dominance of arable and agricultural land (lack of forest cover. From a purely spatial point of view, the localization of these two classes of susceptibility is completely corresponding to the ground truth data, that is to say that all the environmental and anthropogenic conditions are in place for making this area prone to landslide hazards. The obtained map is a decision-making tool for presenting, comparing and discussing development and urban scenarios in Tangier. These results fall within the context of sustainable development and will help to mitigate the socio-economic impacts usually observed when landslides are triggered.

Geographic Information Systems and geomorphological mapping applied to landslide inventory and susceptibility mapping in El Estado river, Pico de Orizaba, Mexico

Directory of Open Access Journals (Sweden)

José Fernando Aceves Quesada

2016-11-01

Full Text Available With the aim of raising awareness on the prevention of landslide disasters, this work develops a methodology that incorporates geomorphological mapping into the mapping of landslide susceptibility using Geographic Information Systems (GIS and Multiple Logistic Regression (MLR. In Mexico, some studies have evaluated the stability of hillsides using GIS. However, these studies set a general framework and guidance (that includes basic concepts and explanations of landslide classification, triggering mechanisms, criteria, considerations, and analysis for landslide hazard reconnaissance, etc. for preparing a landslide atlas at state and city levels. So far, these have not developed a practical and standardized approach incorporating geomorphological maps into the landslide inventory using GIS. This paper describes the analysis conducted to develop an analytical technique and morphometric analysis for a multi-temporal landslide inventory. Three data management levels are used to create GIS thematic layers. For the first level, analogue topographic, geological, land-use, and climate paper are converted to raster format, georeferenced, and incorporated as GIS thematic layers. For the second level, five layers are derived from topographic elevation data: slope angles, slope curvature, contributing area, flow direction, and saturation. For the third level, thematic maps are derived from the previous two levels of data: a hypsometric map (heuristically classified to highlight altimetric levels, a reclassified slope map (allowing to highlight differences in relief , and a morphographic map (derived from a heuristic reclassification of the slope map to highlight volcanic landforms. The theoretical aspects of geomorphological mapping contribute to set the conceptual basis to support landslide mapping. The GIS thematic layers provide context and establish an overall characterization of landslide processes within the watershed. Through the retrieval and on

Suitability aero-geophysical methods for generating conceptual soil maps and their use in the modeling of process-related susceptibility maps

Science.gov (United States)

Tilch, Nils; Römer, Alexander; Jochum, Birgit; Schattauer, Ingrid

2014-05-01

In the past years, several times large-scale disasters occurred in Austria, which were characterized not only by flooding, but also by numerous shallow landslides and debris flows. Therefore, for the purpose of risk prevention, national and regional authorities also require more objective and realistic maps with information about spatially variable susceptibility of the geosphere for hazard-relevant gravitational mass movements. There are many and various proven methods and models (e.g. neural networks, logistic regression, heuristic methods) available to create such process-related (e.g. flat gravitational mass movements in soil) suszeptibility maps. But numerous national and international studies show a dependence of the suitability of a method on the quality of process data and parameter maps (f.e. Tilch & Schwarz 2011, Schwarz & Tilch 2011). In this case, it is important that also maps with detailed and process-oriented information on the process-relevant geosphere will be considered. One major disadvantage is that only occasionally area-wide process-relevant information exists. Similarly, in Austria often only soil maps for treeless areas are available. However, in almost all previous studies, randomly existing geological and geotechnical maps were used, which often have been specially adapted to the issues and objectives. This is one reason why very often conceptual soil maps must be derived from geological maps with only hard rock information, which often have a rather low quality. Based on these maps, for example, adjacent areas of different geological composition and process-relevant physical properties are razor sharp delineated, which in nature appears quite rarly. In order to obtain more realistic information about the spatial variability of the process-relevant geosphere (soil cover) and its physical properties, aerogeophysical measurements (electromagnetic, radiometric), carried out by helicopter, from different regions of Austria were interpreted

Method of magnetic susceptibility mapping of drilled cores. Experimental measurements for geologic structures determination

International Nuclear Information System (INIS)

Delrive, C.

1993-01-01

The evaluation of the safety of a deep geologic repository for dangerous materials requires the knowledge of the interstitial system of the surrounding host rock. A method is proposed for the determination of geologic structures (in particular fractures) from the magnetic susceptibility mapping of drilled cores. The feasibility of the method has been demonstrated using a SQUID magneto-gradient meter. A measurement tool using a new magnetic susceptibility captor and a testing bench have been developed. This tool allows the measurement of rocks with a magnetic susceptibility greater than 10 -5 SI units and can generate magnetic susceptibility maps with 4 x 4 mm 2 pixels. A magnetic visibility criterion has been defined which allows to foresee if a structure is visible or not. According to the measurements done, it is shown that any centimeter-scale structure with a sufficient magnetic contrast (20%) with respect to the matrix is visible. Therefore, the dip and the orientation of such structure can be determined with a 3 degree and a 5 degree precision, respectively. The position of the structure along the core axis is known with a 4 mm precision. On the other hand, about half of the magnetic contrasts observed do not correspond to the visual analyses and can be explained by very small variations of the mineralogic composition. This last point offers some interesting ways for future research using magnetic susceptibility mapping. (J.S.). 31 refs., 90 figs., 18 tabs., 2 photos., 6 appends

Landslide susceptibility mapping for a part of North Anatolian Fault Zone (Northeast Turkey) using logistic regression model

Science.gov (United States)

Demir, Gökhan; aytekin, mustafa; banu ikizler, sabriye; angın, zekai

2013-04-01

The North Anatolian Fault is know as one of the most active and destructive fault zone which produced many earthquakes with high magnitudes. Along this fault zone, the morphology and the lithological features are prone to landsliding. However, many earthquake induced landslides were recorded by several studies along this fault zone, and these landslides caused both injuiries and live losts. Therefore, a detailed landslide susceptibility assessment for this area is indispancable. In this context, a landslide susceptibility assessment for the 1445 km2 area in the Kelkit River valley a part of North Anatolian Fault zone (Eastern Black Sea region of Turkey) was intended with this study, and the results of this study are summarized here. For this purpose, geographical information system (GIS) and a bivariate statistical model were used. Initially, Landslide inventory maps are prepared by using landslide data determined by field surveys and landslide data taken from General Directorate of Mineral Research and Exploration. The landslide conditioning factors are considered to be lithology, slope gradient, slope aspect, topographical elevation, distance to streams, distance to roads and distance to faults, drainage density and fault density. ArcGIS package was used to manipulate and analyze all the collected data Logistic regression method was applied to create a landslide susceptibility map. Landslide susceptibility maps were divided into five susceptibility regions such as very low, low, moderate, high and very high. The result of the analysis was verified using the inventoried landslide locations and compared with the produced probability model. For this purpose, Area Under Curvature (AUC) approach was applied, and a AUC value was obtained. Based on this AUC value, the obtained landslide susceptibility map was concluded as satisfactory. Keywords: North Anatolian Fault Zone, Landslide susceptibility map, Geographical Information Systems, Logistic Regression Analysis.

Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

Science.gov (United States)

Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

2010-05-01

This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

A Support Vector Machine for Landslide Susceptibility Mapping in Gangwon Province, Korea

Directory of Open Access Journals (Sweden)

Saro Lee

2017-01-01

Full Text Available In this study, the support vector machine (SVM was applied and validated by using the geographic information system (GIS in order to map landslide susceptibility. In order to test the usefulness and effectiveness of the SVM, two study areas were carefully selected: the PyeongChang and Inje areas of Gangwon Province, Korea. This is because, not only did many landslides (2098 in PyeongChang and 2580 in Inje occur in 2006 as a result of heavy rainfall, but the 2018 Winter Olympics will be held in these areas. A variety of spatial data, including landslides, geology, topography, forest, soil, and land cover, were identified and collected in the study areas. Following this, the spatial data were compiled in a GIS-based database through the use of aerial photographs. Using this database, 18 factors relating to topography, geology, soil, forest and land use, were extracted and applied to the SVM. Next, the detected landslide data were randomly divided into two sets; one for training and the other for validation of the model. Furthermore, a SVM, specifically a type of data-mining classification model, was applied by using radial basis function kernels. Finally, the estimated landslide susceptibility maps were validated. In order to validate the maps, sensitivity analyses were carried out through area-under-the-curve analysis. The achieved accuracies from the SVM were approximately 81.36% and 77.49% in the PyeongChang and Inje areas, respectively. Moreover, a sensitivity assessment of the factors was performed. It was found that all of the factors, except for soil topography, soil drainage, soil material, soil texture, timber diameter, timber age, and timber density for the PyeongChang area, and timber diameter, timber age, and timber density for the Inje area, had relatively positive effects on the landslide susceptibility maps. These results indicate that SVMs can be useful and effective for landslide susceptibility analysis.

Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

DEFF Research Database (Denmark)

Orr, Nick; Dudbridge, Frank; Dryden, Nicola

2015-01-01

We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further...

Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

NARCIS (Netherlands)

N. Orr (Nick); F. Dudbridge (Frank); N. Dryden (Nicola); S. Maguire (Sarah); D. Novo (Daniela); E. Perrakis (Eleni); N. Johnson (Nichola); M. Ghoussaini (Maya); J. Hopper (John); M.C. Southey (Melissa); C. Apicella (Carmel); J. Stone (Jennifer); M.K. Schmidt (Marjanka); A. Broeks (Annegien); L.J. van 't Veer (Laura); F.B.L. Hogervorst (Frans); P.A. Fasching (Peter); L. Haeberle (Lothar); A.B. Ekici (Arif); M.W. Beckmann (Matthias); L.J. Gibson (Lorna); A. Aitken; H. Warren (Helen); E.J. Sawyer (Elinor); I.P. Tomlinson (Ian); M. Kerin (Michael); N. Miller (Nicola); B. Burwinkel (Barbara); F. Marme (Federick); A. Schneeweiss (Andreas); C. Sohn (Chistof); P. Guénel (Pascal); T. Truong (Thérèse); E. Cordina-Duverger (Emilie); M. Sanchez (Marie); S.E. Bojesen (Stig); B.G. Nordestgaard (Børge); S.F. Nielsen (Sune); H. Flyger (Henrik); J. Benítez (Javier); M.P. Zamora (Pilar); J.I.A. Perez (Jose Ignacio Arias); P. Menéndez (Primitiva); H. Anton-Culver (Hoda); S.L. Neuhausen (Susan); H. Brenner (Hermann); A.K. Dieffenbach (Aida Karina); V. Arndt (Volker); C. Stegmaier (Christa); U. Hamann (Ute); H. Brauch (Hiltrud); C. Justenhoven (Christina); T. Brüning (Thomas); Y.-D. Ko (Yon-Dschun); H. Nevanlinna (Heli); K. Aittomäki (Kristiina); C. Blomqvist (Carl); S. Khan (Sofia); N.V. Bogdanova (Natalia); T. Dörk (Thilo); A. Lindblom (Annika); S. Margolin (Sara); A. Mannermaa (Arto); V. Kataja (Vesa); V-M. Kosma (Veli-Matti); J.M. Hartikainen (J.); G. Chenevix-Trench (Georgia); J. Beesley (Jonathan); D. Lambrechts (Diether); M. Moisse (Matthieu); O.A.M. Floris; B. Beuselinck (B.); J. Chang-Claude (Jenny); A. Rudolph (Anja); P. Seibold (Petra); D. Flesch-Janys (Dieter); P. Radice (Paolo); P. Peterlongo (Paolo); B. Peissel (Bernard); V. Pensotti (Valeria); F.J. Couch (Fergus); J.E. Olson (Janet); S. Slettedahl (Seth); C. Vachon (Celine); G.G. Giles (Graham G.); R.L. Milne (Roger L.); C.A. McLean (Catriona Ann); C.A. Haiman (Christopher); B.E. Henderson (Brian); F.R. Schumacher (Fredrick); L. Le Marchand (Loic); J. Simard (Jacques); M.S. Goldberg (Mark); F. Labrèche (France); M. Dumont (Martine); V. Kristensen (Vessela); G.G. Alnæs (Grethe); S. Nord (Silje); A.-L. Borresen-Dale (Anne-Lise); W. Zheng (Wei); S.L. Deming-Halverson (Sandra); M. Shrubsole (Martha); J. Long (Jirong); R. Winqvist (Robert); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); M. Grip (Mervi); I.L. Andrulis (Irene); J.A. Knight (Julia); G. Glendon (Gord); S. Tchatchou (Sandrine); P. Devilee (Peter); R.A.E.M. Tollenaar (Robertus A. E. M.); C.M. Seynaeve (Caroline); C.J. van Asperen (Christi); M. García-Closas (Montserrat); J.D. Figueroa (Jonine); S.J. Chanock (Stephen); J. Lissowska (Jolanta); K. Czene (Kamila); H. Darabi (Hatef); M. Eriksson (Mikael); D. Klevebring (Daniel); M.J. Hooning (Maartje); A. Hollestelle (Antoinette); C.H.M. van Deurzen (Carolien); M. Kriege (Mieke); P. Hall (Per); J. Li (Jingmei); J. Liu (Jianjun); M.K. Humphreys (Manjeet); A. Cox (Angela); S.S. Cross (Simon); M.W.R. Reed (Malcolm); P.D.P. Pharoah (Paul); A.M. Dunning (Alison); M. Shah (Mitul); B. Perkins (Barbara); A. Jakubowska (Anna); J. Lubinski (Jan); K. Jaworska-Bieniek (Katarzyna); K. Durda (Katarzyna); A. Ashworth (Alan); A.J. Swerdlow (Anthony ); M. Jones (Michael); M. Schoemaker (Minouk); A. Meindl (Alfons); R.K. Schmutzler (Rita); C. Olswold (Curtis); S. Slager (Susan); A.E. Toland (Amanda); D. Yannoukakos (Drakoulis); K.R. Muir (K.); A. Lophatananon (Artitaya); S. Stewart-Brown (Sarah); P. Siriwanarangsan (Pornthep); K. Matsuo (Keitaro); H. Ito (Hidema); H. Iwata (Hisato); J. Ishiguro (Junko); A.H. Wu (Anna H.); C.-C. Tseng (Chiu-chen); D. Van Den Berg (David); D.O. Stram (Daniel O.); S.-H. Teo (Soo-Hwang); C.H. Yip (Cheng Har); P. Kang (Peter); M.K. Ikram (Kamran); X.-O. Shu (Xiao-Ou); W. Lu (Wei); Y. Gao; H. Cai (Hui); D. Kang (Daehee); J.-Y. Choi (J.); S.K. Park (Sue); D-Y. Noh (Dong-Young); J.M. Hartman (Joost); X. Miao; W.-Y. Lim (Wei-Yen); S.C. Lee (Soo Chin); S. Sangrajrang (Suleeporn); V. Gaborieau (Valerie); P. Brennan (Paul); J.D. McKay (James); P.-E. Wu (Pei-Ei); M.-F. Hou (Ming-Feng); J-C. Yu (Jyh-Cherng); C-Y. Shen (Chen-Yang); W.J. Blot (William); Q. Cai (Qiuyin); L.B. Signorello (Lisa B.); C. Luccarini (Craig); C. Bayes (Caroline); S. Ahmed (Shahana); M. Maranian (Melanie); S. Healey (Sue); A. González-Neira (Anna); G. Pita (Guillermo); M. Rosario Alonso; N. Álvarez (Nuria); D. Herrero (Daniel); D.C. Tessier (Daniel C.); D. Vincent (Daniel); F. Bacot (Francois); D. Hunter (David); S. Lindstrom (Stephen); J. Dennis (Joe); K. Michailidou (Kyriaki); M.K. Bolla (Manjeet); D.F. Easton (Douglas); I. dos Santos Silva (Isabel); O. Fletcher (Olivia); J. Peto (Julian)

2015-01-01

textabstractWe recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and

Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS

Science.gov (United States)

Tien Bui, Dieu; Pradhan, Biswajeet; Lofman, Owe; Revhaug, Inge; Dick, Oystein B.

2012-08-01

The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the landslide inventory was randomly split into a testing dataset 70% (82 landslide locations) for training the models and the remaining 30% (36 landslides locations) was used for validation purpose. Ten landslide conditioning factors such as slope, aspect, curvature, lithology, land use, soil type, rainfall, distance to roads, distance to rivers, and distance to faults were considered in the analysis. The hybrid learning algorithm and six different membership functions (Gaussmf, Gauss2mf, Gbellmf, Sigmf, Dsigmf, Psigmf) were applied to generate the landslide susceptibility maps. The validation dataset, which was not considered in the ANFIS modeling process, was used to validate the landslide susceptibility maps using the prediction rate method. The validation results showed that the area under the curve (AUC) for six ANFIS models vary from 0.739 to 0.848. It indicates that the prediction capability depends on the membership functions used in the ANFIS. The models with Sigmf (0.848) and Gaussmf (0.825) have shown the highest prediction capability. The results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable. As far as the performance of the ANFIS approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.

Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method

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Majid Shadman Roodposhti

2016-09-01

Full Text Available Assessing Landslide Susceptibility Mapping (LSM contributes to reducing the risk of living with landslides. Handling the vagueness associated with LSM is a challenging task. Here we show the application of hybrid GIS-based LSM. The hybrid approach embraces fuzzy membership functions (FMFs in combination with Shannon entropy, a well-known information theory-based method. Nine landslide-related criteria, along with an inventory of landslides containing 108 recent and historic landslide points, are used to prepare a susceptibility map. A random split into training (≈70% and testing (≈30% samples are used for training and validation of the LSM model. The study area—Izeh—is located in the Khuzestan province of Iran, a highly susceptible landslide zone. The performance of the hybrid method is evaluated using receiver operating characteristics (ROC curves in combination with area under the curve (AUC. The performance of the proposed hybrid method with AUC of 0.934 is superior to multi-criteria evaluation approaches using a subjective scheme in this research in comparison with a previous study using the same dataset through extended fuzzy multi-criteria evaluation with AUC value of 0.894, and was built on the basis of decision makers’ evaluation in the same study area.

MULTI-CRITERIA ANALYSIS APPLIED TO LANDSLIDE SUSCEPTIBILITY MAPPING

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Mariana Madruga de Brito

2017-10-01

Full Text Available This paper presents the application of a multi-criteria analysis (MCA tool for landslide susceptibility assessment in Porto Alegre municipality, southern Brazil. A knowledge driven approach was used, aiming to ensure an optimal use of the available information. The landslide conditioning factors considered were slope, lithology, flow accumulation and distance from lineaments. Standardization of these factors was done through fuzzy membership functions, and evaluation of their relative importance for landslide predisposition was supported by the analytic hierarchy process (AHP, based on local expert knowledge. Finally, factors were integrated in a GIS environment using the weighted linear combination (WLC method. For validation, an inventory, including 107 landslide points recorded between 2007 and 2013 was used. Results indicated that 8.2% (39.40 km² of the study area are highly and very highly susceptible to landslides. An overall accuracy of 95% was found, with an area under the receiver operating characteristic (ROC curve of 0.960. Therefore, the resulting map can be regarded as useful for monitoring landslide-prone areas. Based on the findings, it is concluded that the proposed method is effective for susceptibility assessment since it yielded meaningful results and does not require extensive input data.

GEOSTATISTICAL BASED SUSCEPTIBILITY MAPPING OF SOIL EROSION AND OPTIMIZATION OF ITS CAUSATIVE FACTORS: A CONCEPTUAL FRAMEWORK

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ABDULKADIR T. SHOLAGBERU

2017-11-01

Full Text Available Soil erosion hazard is the second biggest environmental challenges after population growth causing land degradation, desertification and water deterioration. Its impacts on watersheds include loss of soil nutrients, reduced reservoir capacity through siltation which may lead to flood risk, landslide, high water turbidity, etc. These problems become more pronounced in human altered mountainous areas through intensive agricultural activities, deforestation and increased urbanization among others. However, due to challenging nature of soil erosion management, there is great interest in assessing its spatial distribution and susceptibility levels. This study is thus intend to review the recent literatures and develop a novel framework for soil erosion susceptibility mapping using geostatistical based support vector machine (SVM, remote sensing and GIS techniques. The conceptual framework is to bridge the identified knowledge gaps in the area of causative factors’ (CFs selection. In this research, RUSLE model, field studies and the existing soil erosion maps for the study area will be integrated for the development of inventory map. Spatial data such as Landsat 8, digital soil and geological maps, digital elevation model and hydrological data shall be processed for the extraction of erosion CFs. GISbased SVM techniques will be adopted for the establishment of spatial relationships between soil erosion and its CFs, and subsequently for the development of erosion susceptibility maps. The results of this study include evaluation of predictive capability of GIS-based SVM in soil erosion mapping and identification of the most influential CFs for erosion susceptibility assessment. This study will serve as a guide to watershed planners and to alleviate soil erosion challenges and its related hazards.

Landslide susceptibility mapping using logistic statistical regression in Babaheydar Watershed, Chaharmahal Va Bakhtiari Province, Iran

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Ebrahim Karimi Sangchini

2015-01-01

Full Text Available Landslides are amongst the most damaging natural hazards in mountainous regions. Every year, hundreds of people all over the world lose their lives in landslides; furthermore, there are large impacts on the local and global economy from these events. In this study, landslide hazard zonation in Babaheydar watershed using logistic regression was conducted to determine landslide hazard areas. At first, the landslide inventory map was prepared using aerial photograph interpretations and field surveys. The next step, ten landslide conditioning factors such as altitude, slope percentage, slope aspect, lithology, distance from faults, rivers, settlement and roads, land use, and precipitation were chosen as effective factors on landsliding in the study area. Subsequently, landslide susceptibility map was constructed using the logistic regression model in Geographic Information System (GIS. The ROC and Pseudo-R2 indexes were used for model assessment. Results showed that the logistic regression model provided slightly high prediction accuracy of landslide susceptibility maps in the Babaheydar Watershed with ROC equal to 0.876. Furthermore, the results revealed that about 44% of the watershed areas were located in high and very high hazard classes. The resultant landslide susceptibility maps can be useful in appropriate watershed management practices and for sustainable development in the region.

Susceptibility mapping in the Río El Estado watershed, Pico de Orizaba volcano, Mexico

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Legorreta Paulin, G.; Bursik, M. I.; Lugo Hubp, J.; Paredes Mejía, L.; Aceves Quesada, F.

2013-12-01

In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. This poster provides an overview of the on-going research project (Grant SEP-CONACYT no 167495) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using Geographic Information Systems (GIS). The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 5.2 km2 with elevations ranging from 2676.79 to 4248.2 m a.s.l. and hillslopes between 5° and 56°. The stream system of Río El Estado catchment erodes Tertiary and Quaternary lavas, pyroclastic flows, and fall deposits. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. The first level builds a historic landslide inventory. In the study area, an inventory of more than 100 landslides was mapped from interpretation of multi-temporal aerial orthophotographs and local field surveys to assess and describe landslide distribution. All landslides were digitized into a GIS, and the spatial geo-database of landslides was constructed from standardized GIS datasets. The second level calculates the susceptibility for the watershed. Multiple Logistic Regression (MLR) was used to examine the relationship between landsliding and several independent variables (elevation, slope, terrain curvature, flow direction, saturation, contributing area, land use, and geology

Rainfall thresholds and susceptibility mapping for shallow landslides and debris flows in Scotland

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Postance, Benjamin; Hillier, John; Dijkstra, Tom; Dixon, Neil

2017-04-01

Shallow translational slides and debris flows (hereafter 'landslides') pose a significant threat to life and cause significant annual economic impacts (e.g. by damage and disruption of infrastructure). The focus of this research is on the definition of objective rainfall thresholds using a weather radar system and landslide susceptibility mapping. In the study area Scotland, an inventory of 75 known landslides was used for the period 2003 to 2016. First, the effect of using different rain records (i.e. time series length) on two threshold selection techniques in receiver operating characteristic (ROC) analysis was evaluated. The results show that thresholds selected by 'Threat Score' (minimising false alarms) are sensitive to rain record length and which is not routinely considered, whereas thresholds selected using 'Optimal Point' (minimising failed alarms) are not; therefore these may be suited to establishing lower limit thresholds and be of interest to those developing early warning systems. Robust thresholds are found for combinations of normalised rain duration and accumulation at 1 and 12 day's antecedence respectively; these are normalised using the rainy-day normal and an equivalent measure for rain intensity. This research indicates that, in Scotland, rain accumulation provides a better indicator than rain intensity and that landslides may be generated by threshold conditions lower than previously thought. Second, a landslide susceptibility map is constructed using a cross-validated logistic regression model. A novel element of the approach is that landslide susceptibility is calculated for individual hillslope sections. The developed thresholds and susceptibility map are combined to assess potential hazards and impacts posed to the national highway network in Scotland.

Variable-Weighted Linear Combination Model for Landslide Susceptibility Mapping: Case Study in the Shennongjia Forestry District, China

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Wei Chen

2017-11-01

Full Text Available A landslide susceptibility map plays an essential role in urban and rural planning. The main purpose of this study is to establish a variable-weighted linear combination model (VWLC and assess its potential for landslide susceptibility mapping. Firstly, different objective methods are employed for data processing rather than the frequently-used subjective judgments: K-means clustering is used for classification; binarization is introduced to determine buffer length thresholds for locational elements (road, river, and fault; landslide area density is adopted as the contribution index; and a correlation analysis is conducted for suitable factor selection. Secondly, considering the dimension changes of the preference matrix varying with the different locations of the mapping cells, the variable weights of each optimal factor are determined based on the improved analytic hierarchy process (AHP. On this basis, the VWLC model is established and applied to regional landslide susceptibility mapping for the Shennongjia Forestry District, China, where shallow landslides frequently occur. The obtained map is then compared with a map using the traditional WLC, and the results of the comparison show that VWLC is more reasonable, with a higher accuracy, and can be used anywhere that has the same or similar geological and topographical conditions.

Progress in national-scale landslide susceptibility mapping in Romania using a combined statistical-heuristical approach

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Bălteanu, Dan; Micu, Mihai; Malet, Jean-Philippe; Jurchescu, Marta; Sima, Mihaela; Kucsicsa, Gheorghe; Dumitrică, Cristina; Petrea, Dănuţ; Mărgărint, Ciprian; Bilaşco, Ştefan; Văcăreanu, Radu; Georgescu, Sever; Senzaconi, Francisc

2017-04-01

Landslide processes represent a very widespread geohazard in Romania, affecting mainly the hilly and plateau regions as well as the mountain sectors developed on flysch formations. Two main projects provided the framework for improving the existing national landslide susceptibility map (Bălteanu et al. 2010): the ELSUS (Pan-European and nation-wide landslide susceptibility assessment, EC-CERG) and the RO-RISK (Disaster Risk Evaluation at National Level, ESF-POCA) projects. The latter one, a flagship project aiming at strengthening risk prevention and management in Romania, focused on a national-level evaluation of the main risks in the country including landslides. The strategy for modeling landslide susceptibility was designed based on the experience gained from continental and national level assessments conducted in the frame of the International Programme on Landslides (IPL) project IPL-162, the European Landslides Expert Group - JRC and the ELSUS project. The newly proposed landslide susceptibility model used as input a reduced set of landslide conditioning factor maps available at scales of 1:100,000 - 1:200,000 and consisting of lithology, slope angle and land cover. The input data was further differentiated for specific natural environments, defined here as morpho-structural units in order to incorporate differences induced by elevation (vertical climatic zonation), morpho-structure as well as neotectonic features. In order to best discern the specific landslide conditioning elements, the analysis has been carried out for one single process category, namely slides. The existence of a landslide inventory covering the whole country's territory ( 30,000 records, Micu et al. 2014), although affected by incompleteness and lack of homogeneity, allowed for the application of a semi-quantitative, mixed statistical-heuristical approach having the advantage of combining the objectivity of statistics with expert-knowledge in calibrating class and factor weights. The

Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

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E. Tazik

2014-10-01

Full Text Available Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

Maps of Quaternary Deposits and Liquefaction Susceptibility in the Central San Francisco Bay Region, California

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Witter, Robert C.; Knudsen, Keith L.; Sowers, Janet M.; Wentworth, Carl M.; Koehler, Richard D.; Randolph, Carolyn E.; Brooks, Suzanna K.; Gans, Kathleen D.

2006-01-01

This report presents a map and database of Quaternary deposits and liquefaction susceptibility for the urban core of the San Francisco Bay region. It supercedes the equivalent area of U.S. Geological Survey Open-File Report 00-444 (Knudsen and others, 2000), which covers the larger 9-county San Francisco Bay region. The report consists of (1) a spatial database, (2) two small-scale colored maps (Quaternary deposits and liquefaction susceptibility), (3) a text describing the Quaternary map and liquefaction interpretation (part 3), and (4) a text introducing the report and describing the database (part 1). All parts of the report are digital; part 1 describes the database and digital files and how to obtain them by downloading across the internet. The nine counties surrounding San Francisco Bay straddle the San Andreas fault system, which exposes the region to serious earthquake hazard (Working Group on California Earthquake Probabilities, 1999). Much of the land adjacent to the Bay and the major rivers and streams is underlain by unconsolidated deposits that are particularly vulnerable to earthquake shaking and liquefaction of water-saturated granular sediment. This new map provides a consistent detailed treatment of the central part of the 9-county region in which much of the mapping of Open-File Report 00-444 was either at smaller (less detailed) scale or represented only preliminary revision of earlier work. Like Open-File Report 00-444, the current mapping uses geomorphic expression, pedogenic soils, inferred depositional environments, and geologic age to define and distinguish the map units. Further scrutiny of the factors controlling liquefaction susceptibility has led to some changes relative to Open-File Report 00-444: particularly the reclassification of San Francisco Bay mud (Qhbm) to have only MODERATE susceptibility and the rating of artificial fills according to the Quaternary map units inferred to underlie them (other than dams - adf). The two colored

Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms

NARCIS (Netherlands)

Razavi Termeh, Seyed Vahid; Kornejady, Aiding; Pourghasemi, Hamid Reza; Keesstra, Saskia

2018-01-01

Flood is one of the most destructive natural disasters which cause great financial and life losses per year. Therefore, producing susceptibility maps for flood management are necessary in order to reduce its harmful effects. The aim of the present study is to map flood hazard over the Jahrom

GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

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Bathrellos, G. D.; Kalivas, D. P.; Skilodimou, H. D.

2009-07-01

Landslide susceptibility mapping is a practical tool in natural and urban planning; it can be applied for determining land use zones, in construction design and planning of a variety of projects. In this study, two different GIS based landslide susceptibility maps were generated in the mountainous part of the Trikala Prefecture in Thessaly, Central Greece. This was accomplished by using different methods for correlating factors, which have an effect on landslide occurrences. The instability factors taken into account were: lithology, tectonic features, slope gradients, road network, drainage network, land use and rainfall. A frequency distribution of the half number of the landslide events of the study area in each class of the instability factors was performed in order to rate the classes. Two models have been used to combine the instability factors and assess the overall landslide susceptibility, namely: the Weight Factor Model (WeF), which is a statistical method, and the Multiple Factor Model (MuF) that is a logical method. The produced maps were classified into four zones: Low, Moderate, High and Very High susceptible zones and validated using the other half number of the landslide events of the area. Evaluation of the results is optimized through a Landslide Models Indicator (La.M.I.). (Author) 36 refs.

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

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Feizizadeh, Bakhtiar; Blaschke, Thomas

2014-01-01

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC

Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms.

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Razavi Termeh, Seyed Vahid; Kornejady, Aiding; Pourghasemi, Hamid Reza; Keesstra, Saskia

2018-02-15

Flood is one of the most destructive natural disasters which cause great financial and life losses per year. Therefore, producing susceptibility maps for flood management are necessary in order to reduce its harmful effects. The aim of the present study is to map flood hazard over the Jahrom Township in Fars Province using a combination of adaptive neuro-fuzzy inference systems (ANFIS) with different metaheuristics algorithms such as ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO) and comparing their accuracy. A total number of 53 flood locations areas were identified, 35 locations of which were randomly selected in order to model flood susceptibility and the remaining 16 locations were used to validate the models. Learning vector quantization (LVQ), as one of the supervised neural network methods, was employed in order to estimate factors' importance. Nine flood conditioning factors namely: slope degree, plan curvature, altitude, topographic wetness index (TWI), stream power index (SPI), distance from river, land use/land cover, rainfall, and lithology were selected and the corresponding maps were prepared in ArcGIS. The frequency ratio (FR) model was used to assign weights to each class within particular controlling factor, then the weights was transferred into MATLAB software for further analyses and to combine with metaheuristic models. The ANFIS-PSO was found to be the most practical model in term of producing the highly focused flood susceptibility map with lesser spatial distribution related to highly susceptible classes. The chi-square result attests the same, where the ANFIS-PSO had the highest spatial differentiation within flood susceptibility classes over the study area. The area under the curve (AUC) obtained from ROC curve indicated the accuracy of 91.4%, 91.8%, 92.6% and 94.5% for the respective models of FR, ANFIS-ACO, ANFIS-GA, and ANFIS-PSO ensembles. So, the ensemble of ANFIS-PSO was introduced as the

Landslide susceptibility mapping by comparing weight of evidence, fuzzy logic, and frequency ratio methods

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V. Vakhshoori

2016-09-01

Full Text Available A regional scale basin susceptible to landslide located in Qaemshahr area in northern Iran was chosen for comparing the reliability of weight of evidence (WofE, fuzzy logic, and frequency ratio (FR methods for landslide susceptibility mapping. The locations of 157 landslides were identified using Google Earth® or extracted from archived data, from which, 22 rockslides were eliminated from the data-set due to their different conditions. The 135 remaining landslides were randomly divided into two groups of modelling (70% and validation (30% data-sets. Elevation, slope degree, slope aspect, lithology, land use/cover, normalized difference vegetation index, rainfall, distance to drainage network, roads, and faults were considered as landslide causative factors. The landslide susceptibility maps were prepared using the three mentioned methods. The validation process was measured by the success and prediction rates calculated by area under receiver operating characteristic curve. The ‘OR’, ‘AND’, ‘SUM’, and ‘PRODUCT’ operators of the fuzzy logic method were unacceptable because these operators classify the target area into either very high or very low susceptible zones that are inconsistent with the physical conditions of the study area. The results of fuzzy ‘GAMMA’ operators were relatively reliable while, FR and WofE methods showed results that are more reliable.

Landslide susceptibility mapping using AHP method and GIS in the peninsula of Tangier (Rif-northern morocco

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Ait Brahim L

2018-01-01

Full Text Available The peninsula of Tangier (Northern Morocco is submitted to a significant number of landslides each year due to its lithological, structural and morphological complexity; which cause a lot of damage to the road network and other related infrastructure. The main objective of this study is to create a landslide indexed susceptibility map of Tangier peninsula, by using AHP (Analytical Hierarchical Processes model to calculate each factor’s weight. The work is made via GIS by using an ArcGIS AHP extension. In the current research, First of all, the four main types of landslides were identified and mapped from existing documents, works and new data which came from either remote sensing or fieldwork. Lithology, land use, slope, hypsometry, exposure, fault density and drainage network density were used as main parameters controlling the occurrence of the selected landslides. Then, afterward, each parameter is classified into a number of significant classes based on their relative influence on gravitational movement genesis. The validity of the susceptibility zoning map which is obtained through linear summation of indexed maps was tested and cross-checked by inventoried and studied landslides. The obtained landslide susceptibility map constitutes a powerful decision-making tool in land-use planning, i.e. New highways, secondary highways, railways, etc. within the national development program in the Northern provinces. It is a necessary step for the landslides hazard assessment in the Tangier peninsula in northern Morocco.

Mapping erosion susceptibility by a multivariate statistical method: A case study from the Ayvalık region, NW Turkey

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Akgün, Aykut; Türk, Necdet

2011-09-01

Erosion is one of the most important natural hazard phenomena in the world, and it poses a significant threat to Turkey in terms of land degredation and desertification. To cope with this problem, we must determine which areas are erosion-prone. Many studies have been carried out and different models and methods have been used to this end. In this study, we used a logistic regression to prepare an erosion susceptibility map for the Ayvalık region in Balıkesir (NW Turkey). The following were our assessment parameters: weathering grades of rocks, slope gradient, structural lineament density, drainage density, land cover, stream power index (SPI) and profile curvature. These were processed by Idrisi Kilimanjaro GIS software. We used logistic regression analysis to relate predictor variables to the occurrence or non-occurrence of gully erosion sites within geographic cells, and then we used this relationship to produce a probability map for future erosion sites. The results indicate that lineament density, weathering grades of rocks and drainage density are the most important variables governing erosion susceptibility. Other variables, such as land cover and slope gradient, were revealed as secondary important variables. Highly weathered basalt, andesite, basaltic andesite and lacustrine sediments were the units most susceptible to erosion. In order to calculate the prediction accuracy of the erosion susceptibility map generated, we compared it with the map showing the gully erosion areas. On the basis of this comparison, the area under curvature (AUC) value was found to be 0.81. This result suggests that the erosion susceptibility map we generated is accurate.

Comparative Assessment of Three Nonlinear Approaches for Landslide Susceptibility Mapping in a Coal Mine Area

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Qiaomei Su

2017-07-01

Full Text Available Landslide susceptibility mapping is the first and most important step involved in landslide hazard assessment. The purpose of the present study is to compare three nonlinear approaches for landslide susceptibility mapping and test whether coal mining has a significant impact on landslide occurrence in coal mine areas. Landslide data collected by the Bureau of Land and Resources are represented by the X, Y coordinates of its central point; causative factors were calculated from topographic and geologic maps, as well as satellite imagery. The five-fold cross-validation method was adopted and the landslide/non-landslide datasets were randomly split into a ratio of 80:20. From this, five subsets for 20 times were acquired for training and validating models by GIS Geostatistical analysis methods, and all of the subsets were employed in a spatially balanced sample design. Three landslide models were built using support vector machine (SVM, logistic regression (LR, and artificial neural network (ANN models by selecting the median of the performance measures. Then, the three fitted models were compared using the area under the receiver operating characteristics (ROC curves (AUC and the performance measures. The results show that the prediction accuracies are between 73.43% and 87.45% in the training stage, and 67.16% to 73.13% in the validating stage for the three models. AUCs vary from 0.807 to 0.906 and 0.753 to 0.944 in the two stages, respectively. Additionally, three landslide susceptibility maps were obtained by classifying the range of landslide probabilities into four classes representing low (0–0.02, medium (0.02–0.1, high (0.1–0.85, and very high (0.85–1 probabilities of landslides. For the distributions of landslide and area percentages under different susceptibility standards, the SVM model has more relative balance in the four classes compared to the LR and the ANN models. The result reveals that the SVM model possesses better

Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium

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M. Van Den Eeckhaut

2009-03-01

Full Text Available For a 277 km² study area in the Flemish Ardennes, Belgium, a landslide inventory and two landslide susceptibility zonations were combined to obtain an optimal landslide susceptibility assessment, in five classes. For the experiment, a regional landslide inventory, a 10 m × 10 m digital representation of topography, and lithological and soil hydrological information obtained from 1:50 000 scale maps, were exploited. In the study area, the regional inventory shows 192 landslides of the slide type, including 158 slope failures occurred before 1992 (model calibration set, and 34 failures occurred after 1992 (model validation set. The study area was partitioned in 2.78×10⁶ grid cells and in 1927 topographic units. The latter are hydro-morphological units obtained by subdividing slope units based on terrain gradient. Independent models were prepared for the two terrain subdivisions using discriminant analysis. For grid cells, a single pixel was identified as representative of the landslide depletion area, and geo-environmental information for the pixel was obtained from the thematic maps. The landslide and geo-environmental information was used to model the propensity of the terrain to host landslide source areas. For topographic units, morphologic and hydrologic information and the proportion of lithologic and soil hydrological types in each unit, were used to evaluate landslide susceptibility, including the depletion and depositional areas. Uncertainty associated with the two susceptibility models was evaluated, and the model performance was tested using the independent landslide validation set. An heuristic procedure was adopted to combine the landslide inventory and the susceptibility zonations. The procedure makes optimal use of the available landslide and susceptibility information, minimizing the limitations inherent in the inventory and the susceptibility maps. For the established susceptibility classes, regulations to

Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium

Science.gov (United States)

van den Eeckhaut, M.; Reichenbach, P.; Guzzetti, F.; Rossi, M.; Poesen, J.

2009-03-01

For a 277 km2 study area in the Flemish Ardennes, Belgium, a landslide inventory and two landslide susceptibility zonations were combined to obtain an optimal landslide susceptibility assessment, in five classes. For the experiment, a regional landslide inventory, a 10 m × 10 m digital representation of topography, and lithological and soil hydrological information obtained from 1:50 000 scale maps, were exploited. In the study area, the regional inventory shows 192 landslides of the slide type, including 158 slope failures occurred before 1992 (model calibration set), and 34 failures occurred after 1992 (model validation set). The study area was partitioned in 2.78×106 grid cells and in 1927 topographic units. The latter are hydro-morphological units obtained by subdividing slope units based on terrain gradient. Independent models were prepared for the two terrain subdivisions using discriminant analysis. For grid cells, a single pixel was identified as representative of the landslide depletion area, and geo-environmental information for the pixel was obtained from the thematic maps. The landslide and geo-environmental information was used to model the propensity of the terrain to host landslide source areas. For topographic units, morphologic and hydrologic information and the proportion of lithologic and soil hydrological types in each unit, were used to evaluate landslide susceptibility, including the depletion and depositional areas. Uncertainty associated with the two susceptibility models was evaluated, and the model performance was tested using the independent landslide validation set. An heuristic procedure was adopted to combine the landslide inventory and the susceptibility zonations. The procedure makes optimal use of the available landslide and susceptibility information, minimizing the limitations inherent in the inventory and the susceptibility maps. For the established susceptibility classes, regulations to link terrain domains to appropriate land

Comprehensive Clinical Phenotyping & Genetic Mapping for the Discovery of Autism Susceptibility Genes

Science.gov (United States)

2012-12-05

teaching students with autism spectrum disorders 4.52 Learn strategies for incorporating IEP goals and district standard into daily teaching...W403 Columbus, OH 43205 Final Report Comprehensive Clinical Phenotyping & Genetic Mapping for the Discovery of Autism Susceptibility Genes...QFOXGHDUHDFRGH 1.0 Summary In 2006, the Central Ohio Registry for Autism (CORA) was initiated as a collaboration between Wright-Patterson Air

Landslide susceptibility mapping in the coastal region in the State of São Paulo, Brazil

Science.gov (United States)

Alvala, R. C.; Camarinha, P. I.; Canavesi, V.

2013-05-01

, land use and pedology. As a result, we obtain 5 susceptibility classes: very low, low, medium, high and very high. To validate the methodology, there was overlapped the Landslides Susceptibility Map with real risk areas previously mapped, provided by the National Centre for Monitoring and Alert of Natural Disasters. This step is important especially to assess the methodology adherence to evaluate the classes that was mapped with high and very high susceptibility. The preliminary results indicate that over 70% of the the mapped risks areas are located into the classes more susceptible. We observed small inconsistencies that are related with spatial displacement of the various databases considered, which has different resolutions and scales. Therefore, the results indicated that the methodology is robust and showed the high vulnerability of the counties analyzed, which further highlights that the landslides susceptibility should be monitored carefully by the decision makers in order to prevent and minimize the natural disasters impact, so that provide better territorial planning.

Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

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Yilmaz, Işık

2009-06-01

The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

Mass movement susceptibility mapping - A comparison of logistic regression and Weight of evidence methods in Taounate-Ain Aicha region (Central Rif, Morocco

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JEMMAH A I

2018-01-01

Full Text Available Taounate region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Taounate using the Weight of Evidence method (WofE and the Logistic Regression method (LR. Seven conditioning factors were used in this study: lithology, fault, drainage, slope, elevation, exposure and land use. Over the years, this site and its surroundings have experienced repeated landslides. For this reason, landslide susceptibility mapping is mandatory for risk prevention and land-use management. In this study, we have focused on recent large-scale mass movements. Finally, the ROC curves were established to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. A total mass movements location were detected; 50% were randomly selected as input data for the entire process using the Spatial Data Model (SDM and the remaining locations were used for validation purposes. The obtained WofE’s landslide susceptibility map shows that high to very high susceptibility zones contain 62% of the total of inventoried landslides, while the same zones contain only 47% of landslides in the map obtained by the LR method. This landslide susceptibility map obtained is a major contribution to various urban and regional development plans under the Taounate Region National Development Program.

Structural and Functional Magnetic Resonance Imaging of the Cerebellum: Considerations for Assessing Cerebellar Ataxias.

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Deistung, Andreas; Stefanescu, Maria R; Ernst, Thomas M; Schlamann, Marc; Ladd, Mark E; Reichenbach, Jürgen R; Timmann, Dagmar

2016-02-01

Magnetic resonance imaging (MRI) of the brain is of high interest for diagnosing and understanding degenerative ataxias. Here, we present state-of-the-art MRI methods to characterize structural alterations of the cerebellum and introduce initial experiments to show abnormalities in the cerebellar nuclei. Clinically, T1-weighted MR images are used to assess atrophy of the cerebellar cortex, the brainstem, and the spinal cord, whereas T2-weighted and PD-weighted images are typically employed to depict potential white matter lesions that may be associated with certain types of ataxias. More recently, attention has also focused on the characterization of the cerebellar nuclei, which are discernible on spatially highly resolved iron-sensitive MR images due to their relatively high iron content, including T2 (*)-weighted images, susceptibility-weighted images (SWI), effective transverse relaxation rate (R2 (*)) maps, and quantitative susceptibility maps (QSM). Among these iron-sensitive techniques, QSM reveals the best contrast between cerebellar nuclei and their surroundings. In particular, the gyrification of the dentate nuclei is prominently depicted, even at the clinically widely available field strength of 3 T. The linear relationship between magnetic susceptibility and local iron content allows for determination of iron deposition in cerebellar nuclei non-invasively. The increased signal-to-noise ratio of ultrahigh-field MRI (B0 ≥ 7 T) and advances in spatial normalization methods enable functional MRI (fMRI) at the level of the cerebellar cortex and cerebellar nuclei. Data from initial fMRI studies are presented in three common forms of hereditary ataxias (Friedreich's ataxia, spinocerebellar ataxia type 3, and spinocerebellar ataxia type 6). Characteristic changes in the fMRI signal are discussed in the light of histopathological data and current knowledge of the underlying physiology of the fMRI signal in the cerebellum.

Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China

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Yao, X.; Tham, L. G.; Dai, F. C.

2008-11-01

The Support Vector Machine (SVM) is an increasingly popular learning procedure based on statistical learning theory, and involves a training phase in which the model is trained by a training dataset of associated input and target output values. The trained model is then used to evaluate a separate set of testing data. There are two main ideas underlying the SVM for discriminant-type problems. The first is an optimum linear separating hyperplane that separates the data patterns. The second is the use of kernel functions to convert the original non-linear data patterns into the format that is linearly separable in a high-dimensional feature space. In this paper, an overview of the SVM, both one-class and two-class SVM methods, is first presented followed by its use in landslide susceptibility mapping. A study area was selected from the natural terrain of Hong Kong, and slope angle, slope aspect, elevation, profile curvature of slope, lithology, vegetation cover and topographic wetness index (TWI) were used as environmental parameters which influence the occurrence of landslides. One-class and two-class SVM models were trained and then used to map landslide susceptibility respectively. The resulting susceptibility maps obtained by the methods were compared to that obtained by the logistic regression (LR) method. It is concluded that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, which only requires failed cases, has an advantage over the other two methods as only "failed" case information is usually available in landslide susceptibility mapping.

A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey

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Ozdemir, Adnan; Altural, Tolga

2013-03-01

This study evaluated and compared landslide susceptibility maps produced with three different methods, frequency ratio, weights of evidence, and logistic regression, by using validation datasets. The field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the Sultan Mountains of south-western Turkey. The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps. The relationships between landslide distributions and these parameters were analysed using the three methods, and the results of these methods were then used to calculate the landslide susceptibility of the entire study area. The accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork, and the accuracy of the models was evaluated by calculating each model's relative operating characteristic curve. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio, logistic regression, and weights of evidence methods are 0.976, 0.952, and 0.937, respectively. These results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area. Specifically, the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results, and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0.771 and 0.727, respectively. The frequency ratio model is simple, and its input, calculation and output processes are

Utilizing NASA Earth Observations to Assess Landslide Characteristics and Devlelop Susceptibility and Exposure Maps in Malawi

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Klug, M.; Cissell, J.; Grossman, M.

2017-12-01

Malawi has become increasingly prone to landslides in the past few decades. This can be attributed to the terrain, types of soil and vegetation, increased human interference, and heavy flooding after long periods of drought. In addition to the floods and droughts, landslides cause extra stress to farmlands, thus exacerbating the current food security crisis in the country. It can be difficult to pinpoint just how many people are affected by landslides in Malawi because landslides often occur in rural areas or are grouped with other disasters, such as floods or earthquakes. This project created a Landslide Susceptibility Map to assess landslide-prone areas in Malawi using variables such as slope, distance to roads, distance to streams, soil type, and precipitation. These variables were derived using imagery from Landsat 8 Operational Land Imager (OLI), Shuttle Radar Topography Mission Version 3 (SRTM-v3), Global Precipitation Measurement (GPM), and Tropical Rainfall Measuring Mission (TRMM) satellites. Furthermore, this project created a Landslide Exposure Map to estimate how much of the local population lives in susceptible areas by intersecting population data with the Landslide Susceptibility Map. Additionally, an assessment of GPM and TRMM precipitation measurements was generated to better understand the reliability of both measurements for landslide monitoring. Finally, this project updated NASA SERVIR's Global Landslide Catalog (GLC) for Malawi by using WorldView data from Google Earth and Landsat 8 OLI. These end products were used by NASA SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for aiding in disaster management throughout Malawi.

Fracturing mapping and rockfall susceptibility assessment in Yosemite Valley (California, USA)

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Matasci, B.; Carrea, D.; Jaboyedoff, M.; Stock, G. M.; Collins, B. D.; Putnam, R.

2013-12-01

In Yosemite Valley rockfall hazard and risk are high due to the presence of tall, steep granitic cliffs and to the large number of visitors. The main information needed to assess rockfall hazard is the location of the most probable rockfall source areas and the establishment of the frequency of activity from these areas. Terrestrial Laser Scanning (TLS) has been widely deployed to collect very accurate point clouds of vertical and overhanging rock faces. This provided the necessary data to identify the main joint sets, perform spacing and trace length measurements, identify the failure mechanisms and calculate rockfalls volumes. The presence of surface parallel sheeting or exfoliation joints is widespread in the granitic faces of Yosemite Valley, contributing significantly to the occurrence of rockfalls. Thus, through TLS, sheeting joints have been mapped and characterized in 3D. Rock type is another important parameter that must be constrained to identify potential rockfall sources. Therefore, we have focused on the precise mapping of the vertical geologic limits in the field, on high resolution photographs and on the basis of the intensity value associated to TLS point clouds. A methodology has been developed to carry out kinematic tests on full 3D TLS point clouds, taking into account for each joint set the orientation, spacing and persistence measured on the TLS data. The areas of a cliff with the highest density of potential failure mechanisms are shown to be the most susceptible to rockfalls. These advances in remote sensing methods provide new tools to locate the most probable future rockfall sources and provide key elements needed to evaluate the potential rockfall hazard of the cliffs in Yosemite Valley and elsewhere. 3D rockfall susceptibility mapping.

Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment

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Qianqian Wang

2015-12-01

Full Text Available Landslides are usually initiated under complex geological conditions. It is of great significance to find out the optimal combination of predisposing factors and create an accurate landslide susceptibility map based on them. In this paper, the Information Value Model was modified to make the Modified Information Value (MIV Model, and together with GIS (Geographical Information System and AUC (Area Under Receiver Operating Characteristic Curve test, 32 factor combinations were evaluated separately, and factor combination group with members Slope, Lithology, Drainage network, Annual precipitation, Faults, Road and Vegetation was selected as the optimal combination group with an accuracy of 95.0%. Based on this group, a landslide susceptibility zonation map was drawn, where the study area was reclassified into five classes, presenting an accurate description of different levels of landslide susceptibility, with 79.41% and 13.67% of the validating field survey landslides falling in the Very High and High zones, respectively, mainly distributed in the south and southeast of the catchment. It showed that MIV model can tackle the problem of “no data in subclass” well, generate the true information value and show real running trend, which performs well in showing the relationship between predisposing factors and landslide occurrence and can be used for preliminary landslide susceptibility assessment in the study area.

GIS-based soil liquefaction susceptibility map of Mumbai city for earthquake events

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Mhaske, Sumedh Yamaji; Choudhury, Deepankar

2010-03-01

The problem of liquefaction of soil during seismic event is one of the important topics in the field of Geotechnical Earthquake Engineering. Liquefaction of soil is generally occurs in loose cohesionless saturated soil when pore water pressure increases suddenly due to induced ground motion and shear strength of soil decreases to zero and leading the structure situated above to undergo a large settlement, or failure. The failures took place due to liquefaction induced soil movement spread over few square km area continuously. Hence this is a problem where spatial variation involves and to represent this spatial variation Geographic Information System (GIS) is very useful in decision making about the area subjected to liquefaction. In this paper, GIS software GRAM++ is used to prepare soil liquefaction susceptibility map for entire Mumbai city in India by marking three zones viz. critically liquefiable soil, moderately liquefiable soil and non liquefiable soil. Extensive field borehole test data for groundwater depth, standard penetration test (SPT) blow counts, dry density, wet density and specific gravity, etc. have been collected from different parts of Mumbai. Simplified procedure of Youd et al. (2001) is used for calculation of factor of safety against soil liquefaction potential. Mumbai city and suburban area are formed by reclaiming lands around seven islands since 1865 till current date and still it is progressing in the area such as Navi Mumbai and beyond Borivali to Mira road suburban area. The factors of safety against soil liquefaction were determined for earthquake moment magnitude ranging from Mw = 5.0 to 7.5. It is found that the areas like Borivali, Malad, Dahisar, Bhandup may prone to liquefaction for earthquake moment magnitude ranging from Mw = 5.0 to 7.5. The liquefaction susceptibility maps were created by using GRAM++ by showing the areas where the factor of safety against the soil liquefaction is less than one. Proposed liquefaction

TRIGRS Application for landslide susceptibility mapping

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Sugiarti, K.; Sukristiyanti, S.

2018-02-01

Research on landslide susceptibility has been carried out using several different methods. TRIGRS is a modeling program for landslide susceptibility by considering pore water pressure changes due to infiltration of rainfall. This paper aims to present a current state-of-the-art science on the development and application of TRIGRS. Some limitations of TRIGRS, some developments of it to improve its modeling capability, and some examples of the applications of some versions of it to model the effect of rainfall variation on landslide susceptibility are reviewed and discussed.

Belgium's burning coal tips. Coupling thermographic ASTER imagery with topography to map debris slide susceptibility

Energy Technology Data Exchange (ETDEWEB)

Nyssen, Jan; Diependaele, Stijn; Goossens, Rudi [Ghent Univ. (Belgium). Dept. of Geography

2012-03-15

Burning coal tips and the debris slides induced by this combustion are a potential danger for local residents and visitors, and a method is required to identify areas of susceptibility. The relatively easy circulation of air, enhanced by the poor compaction of the spoil heaps, and the exothermic reaction of pyrite with oxygen may ignite coal tips. Rainwater infiltration and subsequent evaporation inside burning coal tips may create steam pressure, which, combined with humidity and slope steepness can then trigger landsliding. Based on mapping of debris slides and susceptibility factors such as burning (represented by positive surface temperature anomalies on thermographic imagery) and slope gradient, this study aims to define thresholds for debris slide susceptibility on coal tips and to map potential debris slide source areas on spoil heaps. The Belgian coal tips were used as study area. A DTM as well as ASTER Kinetic Surface Temperature products were used to measure slope gradients and temperature anomaly. Locations with typical characteristics of combustion (heat, red soil colour, steam and gases), and debris slides were recorded in the field, and were used to identify thresholds beyond which debris sliding is generally observed: a temperature anomaly of > 0.5 K, when comparing the debris slide areas to the average temperature of the coal tip, and a slope gradient {>=} 28 . The susceptibility zones for debris slide detachment were mapped by considering the imagery pixels that exceeded the thresholds for temperature and slope gradient; the results fitted well when compared with the observed debris slides. The method can be improved by using more coal tips for calibration, and by taking into account rain depth and slope aspect. (orig.)

Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China.

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Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Chen, Wei

2018-06-01

In China, floods are considered as the most frequent natural disaster responsible for severe economic losses and serious damages recorded in agriculture and urban infrastructure. Based on the international experience prevention of flood events may not be completely possible, however identifying susceptible and vulnerable areas through prediction models is considered as a more visible task with flood susceptibility mapping being an essential tool for flood mitigation strategies and disaster preparedness. In this context, the present study proposes a novel approach to construct a flood susceptibility map in the Poyang County, JiangXi Province, China by implementing fuzzy weight of evidence (fuzzy-WofE) and data mining methods. The novelty of the presented approach is the usage of fuzzy-WofE that had a twofold purpose. Firstly, to create an initial flood susceptibility map in order to identify non-flood areas and secondly to weight the importance of flood related variables which influence flooding. Logistic Regression (LR), Random Forest (RF) and Support Vector Machines (SVM) were implemented considering eleven flood related variables, namely: lithology, soil cover, elevation, slope angle, aspect, topographic wetness index, stream power index, sediment transport index, plan curvature, profile curvature and distance from river network. The efficiency of this new approach was evaluated using area under curve (AUC) which measured the prediction and success rates. According to the outcomes of the performed analysis, the fuzzy WofE-SVM model was the model with the highest predictive performance (AUC value, 0.9865) which also appeared to be statistical significant different from the other predictive models, fuzzy WofE-RF (AUC value, 0.9756) and fuzzy WofE-LR (AUC value, 0.9652). The proposed methodology and the produced flood susceptibility map could assist researchers and local governments in flood mitigation strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment.

Science.gov (United States)

Shahabi, Himan; Hashim, Mazlan

2015-04-22

This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning.

A method of mapping sinkhole susceptibility using a geographic information system : a case study for interstates in the karst counties of Virginia.

Science.gov (United States)

2015-02-01

This study proposes the use of a geographic information system (GIS) to create a susceptibility map, pinpointing : regions in the karst counties of Virginia, in particular, along interstates, most susceptible to future sinkhole : development, determi...

Landslide Susceptibility Mapping Using GIS-based Vector Grid File (VGF Validating with InSAR Techniques: Three Gorges, Yangtze River (China

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Cem Kıncal

2017-04-01

Full Text Available A landslide susceptibility assessment for the Three Gorges (TG region (China was performed in a Geographical Information System (GIS environment and Persistent Scatterer (PS InSAR derived displacements were used for validation purposes. Badong County of TG was chosen as case study field. Landslide parameters were derived from two datasets. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER Global Digital Elevation Map (GDEM was used to calculate slope geometry parameters (slope, aspect, drainage, and lineament, while geology and vegetation cover were obtained from Landsat and ASTER data. The majority of historical landslides occurred in the sandstone-shale-claystone intercalations. It appears that slope gradients are more critical than other parameters such as aspect and drainage. The susceptibility assessment was based on a summation of assigned susceptibility scores (points for each 30×30 m unit in a database of a Vector Grid File (VGF composed of ‘vector pixels’. A landslide susceptibility map (LSM was generated using VGF and classified with low, moderate and high landslide susceptibility zones. The comparison between the LSM and PS InSAR derived displacements suggests that landslides only account for parts of the observed surface movements.

Intrinsic functional brain mapping in reconstructed 4D magnetic susceptibility (χ) data space.

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Chen, Zikuan; Calhoun, Vince

2015-02-15

By solving an inverse problem of T2*-weighted magnetic resonance imaging for a dynamic fMRI study, we reconstruct a 4D magnetic susceptibility source (χ) data space for intrinsic functional mapping. A 4D phase dataset is calculated from a 4D complex fMRI dataset. The background field and phase wrapping effect are removed by a Laplacian technique. A 3D χ source map is reconstructed from a 3D phase image by a computed inverse MRI (CIMRI) scheme. A 4D χ data space is reconstructed by repeating the 3D χ source reconstruction for each time point. A functional map is calculated by a temporal correlation between voxel signals in the 4D χ space and the timecourse of the task paradigm. With a finger-tapping experiment, we obtain two 3D functional mappings in the 4D magnitude data space and in the reconstructed 4D χ data space. We find that the χ-based functional mapping reveals co-occurrence of bidirectional responses in a 3D activation map that is different from the conventional magnitude-based mapping. The χ-based functional mapping can also be achieved by a 3D deconvolution of a phase activation map. Based on a subject experimental comparison, we show that the 4D χ tomography method could produce a similar χ activation map as obtained by the 3D deconvolution method. By removing the dipole effect and other fMRI technological contaminations, 4D χ tomography provides a 4D χ data space that allows a more direct and truthful functional mapping of a brain activity. Published by Elsevier B.V.

LANDSLIDE SUSCEPTIBILITY ASSESSMENT THROUGH FUZZY LOGIC INFERENCE SYSTEM (FLIS

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T. Bibi

2016-09-01

Full Text Available Landslide is among one of the most important natural hazards that lead to modification of the environment. It is a regular feature of a rapidly growing district Mansehra, Pakistan. This caused extensive loss of life and property in the district located at the foothills of Himalaya. Keeping in view the situation it is concluded that besides structural approaches the non-structural approaches such as hazard and risk assessment maps are effective tools to reduce the intensity of damage. A landslide susceptibility map is base for engineering geologists and geomorphologists. However, it is not easy to produce a reliable susceptibility map due to complex nature of landslides. Since 1980s, several mathematical models have been developed to map landslide susceptibility and hazard. Among various models this paper is discussing the effectiveness of fuzzy logic approach for landslide susceptibility mapping in District Mansehra, Pakistan. The factor maps were modified as landslide susceptibility and fuzzy membership functions were assessed for each class. Likelihood ratios are obtained for each class of contributing factors by considering the expert opinion. The fuzzy operators are applied to generate landslide susceptibility maps. According to this map, 17% of the study area is classified as high susceptibility, 32% as moderate susceptibility, 51% as low susceptibility and areas. From the results it is found that the fuzzy model can integrate effectively with various spatial data for landslide hazard mapping, suggestions in this study are hope to be helpful to improve the applications including interpretation, and integration phases in order to obtain an accurate decision supporting layer.

Cutaneous leishmaniasis susceptibility mapping using multi-criteria decision-making techniques, analytic hierarchy process (AHP and analytic network process (ANP

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SEYED VAHID RAZAVI TERMEH

2018-02-01

Full Text Available Background & objective:Cutaneous leech is one of the six major diseases and an example of epidemic diseases in tropical regions. Prevalence and spread of this disease is affected by environmental factors and climatic conditions as well as economic, social and cultural issues. In this research, Analytic Hierarchy Process and network analyzes are used to prepare susceptible cutaneous leeches map. Considering high incidence of cutaneous leech in Khuzestan province, Izeh city was selected as a case study.   Materials & Methods: For this purpose, the number of patients affected by this disease in Izeh was obtained from the Provincial Health Center from 2009 to 2014. Information layers of elevation, rainfall, temperature, humidity, distance from river, distance from rural areas and land use were identified as effective parameter and their maps were prepared in GIS environment. Parameters were compared in pairs by using AHP and ANP and weight of each factors determining their impacts was calculated in Expert Choice and Super Decision software. Then these parameters were combined based on their obtained weights in ArcGIS software and the final cutaneous leech map was prepared. Evaluation of these methods was performed using relative operation curve (ROC and 16 points related to leech disease. Result: The results of weighting effective parameters using AHP and ANP showed that the highest weight is related to elevation, temperature and rainfall parameters, respectively. The results of ROC assessment showed that in preparing the map, ANP had an accuracy of 87.8% and AHP had an accuracy of 68.9%. Conclusion:The results of ANP showed that this model had suitable accuracy in preparing susceptible cutaneous leech map and AHP had moderate accuracy in preparing susceptible cutaneous leech map.

Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA).

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Chen, Zikuan; Calhoun, Vince D

2016-03-01

Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.

A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

Science.gov (United States)

Pradhan, Biswajeet

2013-02-01

The purpose of the present study is to compare the prediction performances of three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) for landslide susceptibility mapping at Penang Hill area, Malaysia. The necessary input parameters for the landslide susceptibility assessments were obtained from various sources. At first, landslide locations were identified by aerial photographs and field surveys and a total of 113 landslide locations were constructed. The study area contains 340,608 pixels while total 8403 pixels include landslides. The landslide inventory was randomly partitioned into two subsets: (1) part 1 that contains 50% (4000 landslide grid cells) was used in the training phase of the models; (2) part 2 is a validation dataset 50% (4000 landslide grid cells) for validation of three models and to confirm its accuracy. The digitally processed images of input parameters were combined in GIS. Finally, landslide susceptibility maps were produced, and the performances were assessed and discussed. Total fifteen landslide susceptibility maps were produced using DT, SVM and ANFIS based models, and the resultant maps were validated using the landslide locations. Prediction performances of these maps were checked by receiver operating characteristics (ROC) by using both success rate curve and prediction rate curve. The validation results showed that, area under the ROC curve for the fifteen models produced using DT, SVM and ANFIS varied from 0.8204 to 0.9421 for success rate curve and 0.7580 to 0.8307 for prediction rate curves, respectively. Moreover, the prediction curves revealed that model 5 of DT has slightly higher prediction performance (83.07), whereas the success rate showed that model 5 of ANFIS has better prediction (94.21) capability among all models. The results of this study showed that landslide susceptibility mapping in the Penang Hill area using the three approaches (e

Susceptibility of ternary aluminum alloys to cracking during solidification

International Nuclear Information System (INIS)

Liu, Jiangwei; Kou, Sindo

2017-01-01

The crack susceptibility map of a ternary Al alloy system provides useful information about which alloy compositions are most susceptible to cracking and thus should be avoided by using a filler metal with a significantly different composition. In the present study the crack susceptibility maps of ternary Al alloy systems were calculated based on the maximum |dT/d(f S ) 1/2 | as an index for the crack susceptibility, where T is temperature and f S fraction solid. Due to the complexity associated with ternary alloy solidification, commercial thermodynamic software Pandat and Al database PanAluminum, instead of analytical equations, were used to calculate f S as a function of T and hence the maximum |dT/d(f S ) 1/2 | for ternary Al-Mg-Si, Al-Cu-Mg and Al-Cu-Si alloy systems. A crack susceptibility map covering 121 alloy compositions was constructed for each of the three ternary alloy systems at each of the following three levels of back diffusion: no back diffusion, back diffusion under a 100 °C/s cooling rate, and back diffusion under 20° C/s. The location of the region of high crack susceptibility, which is the most important part of the map, was shown in each of the nine calculated maps. These locations were compared with those observed in crack susceptibility tests by previous investigators. With back diffusion considered, either under 20 or 100 °C/s, the agreement between the calculated and observed maps was good especially for Al-Mg-Si and Al-Cu-Mg. Thus, the maximum |dT/d(f S ) 1/2 | can be used as a crack susceptibility index to construct crack susceptibility maps for ternary Al alloys and to evaluate the effect of back diffusion on their crack susceptibility. - Graphical abstract: The crack susceptibility map of a ternary alloy system indicates the composition range most susceptible to cracking, which should be avoided in welding or casting. The crack susceptibility maps of ternary Al alloy systems Al-Mg-Si, Al-Cu-Mg and Al-Cu-Si were calculated based

Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

International Nuclear Information System (INIS)

Althuwaynee, Omar F; Pradhan, Biswajeet; Ahmad, Noordin

2014-01-01

This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies

Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

Science.gov (United States)

Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

2014-06-01

This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

Raster-based derivation of a flood runoff susceptibility map using the revised runoff curve number (CN) for the Kuantan watershed, Malaysia

DEFF Research Database (Denmark)

Akbari, Abolghasem; Samah, Azizan Abu; Daryabor, Farshid

2016-01-01

This study aims to develop a methodology for generating a flood runoff susceptibility (FRS) map using a revised curve number (CN) method. The study area is in the Kuantan watershed (KW), Malaysia, which was seriously affected by floods in December 2013 and December 2014. A revised runoff CN map w......, the finding of this research provides a road map for government agencies to effectively implement flood mitigation projects in the study area.......This study aims to develop a methodology for generating a flood runoff susceptibility (FRS) map using a revised curve number (CN) method. The study area is in the Kuantan watershed (KW), Malaysia, which was seriously affected by floods in December 2013 and December 2014. A revised runoff CN map....... Approximately 5% of the study area was identified as a very high-risk zone and 13% as high-risk zone. However, the spatial extent of a high-risk zone in the downstream end and lowland areas of the KW could be considered to be the main cause of flood damage in recent years. From practical point of view...

APPLICATION OF LiDAR DATE TO ASSESS THE LANDSLIDE SUSCEPTIBILITY MAP USING WEIGHTS OF EVIDENCE METHOD – AN EXAMPLE FROM PODHALE REGION (SOUTHERN POLAND

Directory of Open Access Journals (Sweden)

M. Kamiński

2016-06-01

Full Text Available Podhale is a region in southern Poland, which is the northernmost part of the Central Carpathian Mountains. It is characterized by the presence of a large number of landslides that threaten the local infrastructure. In an article presents application of LiDAR data and geostatistical methods to assess landslides susceptibility map. Landslide inventory map were performed using LiDAR data and field work. The Weights of Evidence method was applied to assess landslides susceptibility map. Used factors for modeling: slope gradient, slope aspect, elevation, drainage density, faults density, lithology and curvature. All maps were subdivided into different classes. Then were converted to grid format in the ArcGIS 10.0. The conditional independence test was carried out to determine factors that are conditionally independent of each other with landslides. As a result, chi-square test for further GIS analysis used only five factors: slope gradient, slope aspect, elevation, drainage density and lithology. The final prediction results, it is concluded that the susceptibility map gives useful information both on present instability of the area and its possible future evolution in agreement with the morphological evolution of the area.

Object-based Classification for Detecting Landslides and Stochastic Procedure to landslide susceptibility maps - A Case at Baolai Village, SW Taiwan

Science.gov (United States)

Lin, Ying-Tong; Chang, Kuo-Chen; Yang, Ci-Jian

2017-04-01

As the result of global warming in the past decades, Taiwan has experienced more and more extreme typhoons with hazardous massive landslides. In this study, we use object-oriented analysis method to classify landslide area at Baolai village by using Formosat-2 satellite images. We used for multiresolution segmented to generate the blocks, and used hierarchical logic to classified 5 different kinds of features. After that, classification the landslide into different type of landslide. Beside, we use stochastic procedure to integrate landslide susceptibility maps. This study assumed that in the extreme event, 2009 Typhoon Morakot, which precipitation goes to 1991.5mm in 5 days, and the highest landslide susceptible area. The results show that study area's landslide area was greatly changes, most of landslide was erosion by gully and made dip slope slide, or erosion by the stream, especially at undercut bank. From the landslide susceptibility maps, we know that the old landslide area have high potential to occur landslides in the extreme event. This study demonstrates the changing of landslide area and the landslide susceptible area. Keywords: Formosat-2, object-oriented, segmentation, classification, landslide, Baolai Village, SW Taiwan, FS

Water erosion susceptibility mapping by applying Stochastic Gradient Treeboost to the Imera Meridionale River Basin (Sicily, Italy)

Science.gov (United States)

Angileri, Silvia Eleonora; Conoscenti, Christian; Hochschild, Volker; Märker, Michael; Rotigliano, Edoardo; Agnesi, Valerio

2016-06-01

Soil erosion by water constitutes a serious problem affecting various countries. In the last few years, a number of studies have adopted statistical approaches for erosion susceptibility zonation. In this study, the Stochastic Gradient Treeboost (SGT) was tested as a multivariate statistical tool for exploring, analyzing and predicting the spatial occurrence of rill-interrill erosion and gully erosion. This technique implements the stochastic gradient boosting algorithm with a tree-based method. The study area is a 9.5 km2 river catchment located in central-northern Sicily (Italy), where water erosion processes are prevalent, and affect the agricultural productivity of local communities. In order to model soil erosion by water, the spatial distribution of landforms due to rill-interrill and gully erosion was mapped and 12 environmental variables were selected as predictors. Four calibration and four validation subsets were obtained by randomly extracting sets of negative cases, both for rill-interrill erosion and gully erosion models. The results of validation, based on receiving operating characteristic (ROC) curves, showed excellent to outstanding accuracies of the models, and thus a high prediction skill. Moreover, SGT allowed us to explore the relationships between erosion landforms and predictors. A different suite of predictor variables was found to be important for the two models. Elevation, aspect, landform classification and land-use are the main controlling factors for rill-interrill erosion, whilst the stream power index, plan curvature and the topographic wetness index were the most important independent variables for gullies. Finally, an ROC plot analysis made it possible to define a threshold value to classify cells according to the presence/absence of the two erosion processes. Hence, by heuristically combining the resulting rill-interrill erosion and gully erosion susceptibility maps, an integrated water erosion susceptibility map was created. The

Multi-Collinearity Based Model Selection for Landslide Susceptibility Mapping: A Case Study from Ulus District of Karabuk, Turkey

Science.gov (United States)

Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.

2017-12-01

Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

Science.gov (United States)

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Producing landslide susceptibility maps by utilizing machine learning methods. The case of Finikas catchment basin, North Peloponnese, Greece.

Science.gov (United States)

Tsangaratos, Paraskevas; Ilia, Ioanna; Loupasakis, Constantinos; Papadakis, Michalis; Karimalis, Antonios

2017-04-01

The main objective of the present study was to apply two machine learning methods for the production of a landslide susceptibility map in the Finikas catchment basin, located in North Peloponnese, Greece and to compare their results. Specifically, Logistic Regression and Random Forest were utilized, based on a database of 40 sites classified into two categories, non-landslide and landslide areas that were separated into a training dataset (70% of the total data) and a validation dataset (remaining 30%). The identification of the areas was established by analyzing airborne imagery, extensive field investigation and the examination of previous research studies. Six landslide related variables were analyzed, namely: lithology, elevation, slope, aspect, distance to rivers and distance to faults. Within the Finikas catchment basin most of the reported landslides were located along the road network and within the residential complexes, classified as rotational and translational slides, and rockfalls, mainly caused due to the physical conditions and the general geotechnical behavior of the geological formation that cover the area. Each landslide susceptibility map was reclassified by applying the Geometric Interval classification technique into five classes, namely: very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The comparison and validation of the outcomes of each model were achieved using statistical evaluation measures, the receiving operating characteristic and the area under the success and predictive rate curves. The computation process was carried out using RStudio an integrated development environment for R language and ArcGIS 10.1 for compiling the data and producing the landslide susceptibility maps. From the outcomes of the Logistic Regression analysis it was induced that the highest b coefficient is allocated to lithology and slope, which was 2.8423 and 1.5841, respectively. From the

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

Directory of Open Access Journals (Sweden)

Xianyu Yu

2016-05-01

Full Text Available In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Preliminary maps of Quaternary deposits and liquefaction susceptibility, nine-county San Francisco Bay region, California: a digital database

Science.gov (United States)

Knudsen, Keith L.; Sowers, Janet M.; Witter, Robert C.; Wentworth, Carl M.; Helley, Edward J.; Nicholson, Robert S.; Wright, Heather M.; Brown, Katherine H.

2000-01-01

This report presents a preliminary map and database of Quaternary deposits and liquefaction susceptibility for the nine-county San Francisco Bay region, together with a digital compendium of ground effects associated with past earthquakes in the region. The report consists of (1) a spatial database of fivedata layers (Quaternary deposits, quadrangle index, and three ground effects layers) and two text layers (a labels and leaders layer for Quaternary deposits and for ground effects), (2) two small-scale colored maps (Quaternary deposits and liquefaction susceptibility), (3) a text describing the Quaternary map, liquefaction interpretation, and the ground effects compendium, and (4) the databse description pamphlet. The nine counties surrounding San Francisco Bay straddle the San Andreas fault system, which exposes the region to serious earthquake hazard (Working Group on California Earthquake Probabilities, 1999). Much of the land adjacent to the Bay and the major rivers and streams is underlain by unconsolidated deposits that are particularly vulnerable to earthquake shaking and liquefaction of water-saturated granular sediment. This new map provides a modern and regionally consistent treatment of Quaternary surficial deposits that builds on the pioneering mapping of Helley and Lajoie (Helley and others, 1979) and such intervening work as Atwater (1982), Helley and others (1994), and Helley and Graymer (1997a and b). Like these earlier studies, the current mapping uses geomorphic expression, pedogenic soils, and inferred depositional environments to define and distinguish the map units. In contrast to the twelve map units of Helley and Lajoie, however, this new map uses a complex stratigraphy of some forty units, which permits a more realistic portrayal of the Quaternary depositional system. The two colored maps provide a regional summary of the new mapping at a scale of 1:275,000, a scale that is sufficient to show the general distribution and relationships of

Mapping debris flow susceptibility using analytical network process in Kodaikkanal Hills, Tamil Nadu (India)

Science.gov (United States)

Sujatha, Evangelin Ramani; Sridhar, Venkataramana

2017-12-01

Rapid debris flows, a mixture of unconsolidated sediments and water travelling at speeds > 10 m/s are the most destructive water related mass movements that affect hill and mountain regions. The predisposing factors setting the stage for the event are the availability of materials, type of materials, stream power, slope gradient, aspect and curvature, lithology, land use and land cover, lineament density, and drainage. Rainfall is the most common triggering factor that causes debris flow in the Palar subwatershed and seismicity is not considered as it is a stable continental region and moderate seismic zone. Also, there are no records of major seismic activities in the past. In this study, one of the less explored heuristic methods known as the analytical network process (ANP) is used to map the spatial propensity of debris flow. This method is based on top-down decision model and is a multi-criteria, decision-making tool that translates subjective assessment of relative importance to weights or scores and is implemented in the Palar subwatershed which is part of the Western Ghats in southern India. The results suggest that the factors influencing debris flow susceptibility in this region are the availability of material on the slope, peak flow, gradient of the slope, land use and land cover, and proximity to streams. Among all, peak discharge is identified as the chief factor causing debris flow. The use of micro-scale watersheds demonstrated in this study to develop the susceptibility map can be very effective for local level planning and land management.

Amplified fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the yellow fever mosquito Aedes aegypti.

Science.gov (United States)

Zhong, Daibin; Menge, David M; Temu, Emmanuel A; Chen, Hong; Yan, Guiyun

2006-07-01

The yellow fever mosquito Aedes aegypti has been the subject of extensive genetic research due to its medical importance and the ease with which it can be manipulated in the laboratory. A molecular genetic linkage map was constructed using 148 amplified fragment length polymorphism (AFLP) and six single-strand conformation polymorphism (SSCP) markers. Eighteen AFLP primer combinations were used to genotype two reciprocal F2 segregating populations. Each primer combination generated an average of 8.2 AFLP markers eligible for linkage mapping. The length of the integrated map was 180.9 cM, giving an average marker resolution of 1.2 cM. Composite interval mapping revealed a total of six QTL significantly affecting Plasmodium susceptibility in the two reciprocal crosses of Ae. aegypti. Two common QTL on linkage group 2 were identified in both crosses that had similar effects on the phenotype, and four QTL were unique to each cross. In one cross, the four main QTL accounted for 64% of the total phenotypic variance, and digenic epistasis explained 11.8% of the variance. In the second cross, the four main QTL explained 66% of the variance, and digenic epistasis accounted for 16% of the variance. The actions of these QTL were either dominance or underdominance. Our results indicated that at least three new QTL were mapped on chromosomes 1 and 3. The polygenic nature of susceptibility to P. gallinaceum and epistasis are important factors for significant variation within or among mosquito strains. The new map provides additional information useful for further genetic investigation, such as identification of new genes and positional cloning.

Landslide susceptibility mapping on a global scale using the method of logistic regression

Directory of Open Access Journals (Sweden)

L. Lin

2017-08-01

Full Text Available This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

Susceptibility and triggering scenarios at a regional scale for shallow landslides

Science.gov (United States)

Gullà, G.; Antronico, L.; Iaquinta, P.; Terranova, O.

2008-07-01

The work aims at identifying susceptible areas and pluviometric triggering scenarios at a regional scale in Calabria (Italy), with reference to shallow landsliding events. The proposed methodology follows a statistical approach and uses a database linked to a GIS that has been created to support the various steps of spatial data management and manipulation. The shallow landslide predisposing factors taken into account are derived from (i) the 40-m digital terrain model of the region, an ˜ 15,075 km 2 extension; (ii) outcropping lithology; (iii) soils; and (iv) land use. More precisely, a map of the slopes has been drawn from the digital terrain model. Two kinds of covers [prevalently coarse-grained (CG cover) or fine-grained (FG cover)] were identified, referring to the geotechnical characteristics of geomaterial covers and to the lithology map; soilscapes were drawn from soil maps; and finally, the land use map was employed without any prior processing. Subsequently, the inventory maps of some shallow landsliding events, totaling more than 30,000 instabilities of the past and detected by field surveys and photo aerial restitution, were employed to calibrate the relative importance of these predisposing factors. The use of single factors (first level analysis) therefore provides three different susceptibility maps. Second level analysis, however, enables better location of areas susceptible to shallow landsliding events by crossing the single susceptibility maps. On the basis of the susceptibility map obtained by the second level analysis, five different classes of susceptibility to shallow landsliding events have been outlined over the regional territory: 8.9% of the regional territory shows very high susceptibility, 14.3% high susceptibility, 15% moderate susceptibility, 3.6% low susceptibility, and finally, about 58% very low susceptibility. Finally, the maps of two significant shallow landsliding events of the past and their related rainfalls have been

Landslide susceptibility mapping in Mawat area, Kurdistan Region, NE Iraq: a comparison of different statistical models

Science.gov (United States)

Othman, A. A.; Gloaguen, R.; Andreani, L.; Rahnama, M.

2015-03-01

During the last decades, expansion of settlements into areas prone to landslides in Iraq has increased the importance of accurate hazard assessment. Susceptibility mapping provides information about hazardous locations and thus helps to potentially prevent infrastructure damage due to mass wasting. The aim of this study is to evaluate and compare frequency ratio (FR), weight of evidence (WOE), logistic regression (LR) and probit regression (PR) approaches in combination with new geomorphological indices to determine the landslide susceptibility index (LSI). We tested these four methods in Mawat area, Kurdistan Region, NE Iraq, where landslides occur frequently. For this purpose, we evaluated 16 geomorphological, geological and environmental predicting factors mainly derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite. The available reference inventory includes 351 landslides representing a cumulative surface of 3.127 km2. This reference inventory was mapped from QuickBird data by manual delineation and partly verified by field survey. The areas under curve (AUC) of the receiver operating characteristic (ROC), and relative landslide density (R index) show that all models perform similarly and that focus should be put on the careful selection of proxies. The results indicate that the lithology and the slope aspects play major roles for landslide occurrences. Furthermore, this paper demonstrates that using hypsometric integral as a prediction factor instead of slope curvature gives better results and increases the accuracy of the LSI.

Landslide Susceptibility Mapping of Tegucigalpa, Honduras Using Artificial Neural Network, Bayesian Network and Decision Trees

Science.gov (United States)

Garcia Urquia, E. L.; Braun, A.; Yamagishi, H.

2016-12-01

Tegucigalpa, the capital city of Honduras, experiences rainfall-induced landslides on a yearly basis. The high precipitation regime and the rugged topography the city has been built in couple with the lack of a proper urban expansion plan to contribute to the occurrence of landslides during the rainy season. Thousands of inhabitants live at risk of losing their belongings due to the construction of precarious shelters in landslide-prone areas on mountainous terrains and next to the riverbanks. Therefore, the city is in the need for landslide susceptibility and hazard maps to aid in the regulation of future development. Major challenges in the context of highly dynamic urbanizing areas are the overlap of natural and anthropogenic slope destabilizing factors, as well as the availability and accuracy of data. Data-driven multivariate techniques have proven to be powerful in discovering interrelations between factors, identifying important factors in large datasets, capturing non-linear problems and coping with noisy and incomplete data. This analysis focuses on the creation of a landslide susceptibility map using different methods from the field of data mining, Artificial Neural Networks (ANN), Bayesian Networks (BN) and Decision Trees (DT). The input dataset of the study contains geomorphological and hydrological factors derived from a digital elevation model with a 10 m resolution, lithological factors derived from a geological map, and anthropogenic factors, such as information on the development stage of the neighborhoods in Tegucigalpa and road density. Moreover, a landslide inventory map that was developed in 2014 through aerial photo interpretation was used as target variable in the analysis. The analysis covers an area of roughly 100 km2, while 8.95 km2 are occupied by landslides. In a first step, the dataset was explored by assessing and improving the data quality, identifying unimportant variables and finding interrelations. Then, based on a training

School dropout susceptibility mapping with fuzzy logic – a study in the District of Purulia, India

Directory of Open Access Journals (Sweden)

Mukunda Mishra

2017-05-01

Full Text Available Multi-input prediction models are gradually finding their places in the arena of social and economic sciences to assess, locate and address the complicated socio-economic issues arising around the globe. These models treat the problems as the output aroused from a complex interaction between a range of variables linked with physical, socio-cultural, economic as well as ambient political systems. The discussion on dropout from the education system belongs to the core of the educational researchers. The researchers within this domain are attempting to develop the ‘tools and techniques’ for efficiently demarcating the space with a given degree of susceptibility. The scope is to drop out and examine the internal functions of the interactive variables associated with the process. In the present study, we try to apply the fuzzy logic in mapping the spatial variation of the susceptibility of school dropout in the district of Purulia, a backwards district in India regarding achieved level of human development. The training datasets for building the fuzzy model based on the available secondary data from different reports published by the Government and a range of primary data collected through a socio-economic survey. The model output is an index, namely the Index of Susceptibility of School Drop Out (ISDO which reflects the levels of susceptibility to school dropout at different parts of the study area. The proposed model should allow the success within the larger social and economic system.

Landslide Susceptibility Mapping Based on Particle Swarm Optimization of Multiple Kernel Relevance Vector Machines: Case of a Low Hill Area in Sichuan Province, China

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Yongliang Lin

2016-10-01

Full Text Available In this paper, we propose a multiple kernel relevance vector machine (RVM method based on the adaptive cloud particle swarm optimization (PSO algorithm to map landslide susceptibility in the low hill area of Sichuan Province, China. In the multi-kernel structure, the kernel selection problem can be solved by adjusting the kernel weight, which determines the single kernel contribution of the final kernel mapping. The weights and parameters of the multi-kernel function were optimized using the PSO algorithm. In addition, the convergence speed of the PSO algorithm was increased using cloud theory. To ensure the stability of the prediction model, the result of a five-fold cross-validation method was used as the fitness of the PSO algorithm. To verify the results, receiver operating characteristic curves (ROC and landslide dot density (LDD were used. The results show that the model that used a heterogeneous kernel (a combination of two different kernel functions had a larger area under the ROC curve (0.7616 and a lower prediction error ratio (0.28% than did the other types of kernel models employed in this study. In addition, both the sum of two high susceptibility zone LDDs (6.71/100 km2 and the sum of two low susceptibility zone LDDs (0.82/100 km2 demonstrated that the landslide susceptibility map based on the heterogeneous kernel model was closest to the historical landslide distribution. In conclusion, the results obtained in this study can provide very useful information for disaster prevention and land-use planning in the study area.

Susceptibility tensor imaging (STI) of the brain.

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Li, Wei; Liu, Chunlei; Duong, Timothy Q; van Zijl, Peter C M; Li, Xu

2017-04-01

Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility and magnetic susceptibility anisotropy can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping to remove such dependence. Similar to diffusion tensor imaging, STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of the susceptibility anisotropy in brain white matter is myelin. Another unique feature of the susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in the myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Mapping flood and flooding potential indices: a methodological approach to identifying areas susceptible to flood and flooding risk. Case study: the Prahova catchment (Romania)

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Zaharia, Liliana; Costache, Romulus; Prăvălie, Remus; Ioana-Toroimac, Gabriela

2017-04-01

Given that floods continue to cause yearly significant worldwide human and material damages, flood risk mitigation is a key issue and a permanent challenge in developing policies and strategies at various spatial scales. Therefore, a basic phase is elaborating hazard and flood risk maps, documents which are an essential support for flood risk management. The aim of this paper is to develop an approach that allows for the identification of flash-flood and flood-prone susceptible areas based on computing and mapping of two indices: FFPI (Flash-Flood Potential Index) and FPI (Flooding Potential Index). These indices are obtained by integrating in a GIS environment several geographical variables which control runoff (in the case of the FFPI) and favour flooding (in the case of the FPI). The methodology was applied in the upper (mountainous) and middle (hilly) catchment of the Prahova River, a densely populated and socioeconomically well-developed area which has been affected repeatedly by water-related hazards over the past decades. The resulting maps showing the spatialization of the FFPI and FPI allow for the identification of areas with high susceptibility to flashfloods and flooding. This approach can provide useful mapped information, especially for areas (generally large) where there are no flood/hazard risk maps. Moreover, the FFPI and FPI maps can constitute a preliminary step for flood risk and vulnerability assessment.

Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion

Science.gov (United States)

Rahmati, Omid; Tahmasebipour, Nasser; Haghizadeh, Ali; Pourghasemi, Hamid Reza; Feizizadeh, Bakhtiar

2017-12-01

Gully erosion constitutes a serious problem for land degradation in a wide range of environments. The main objective of this research was to compare the performance of seven state-of-the-art machine learning models (SVM with four kernel types, BP-ANN, RF, and BRT) to model the occurrence of gully erosion in the Kashkan-Poldokhtar Watershed, Iran. In the first step, a gully inventory map consisting of 65 gully polygons was prepared through field surveys. Three different sample data sets (S1, S2, and S3), including both positive and negative cells (70% for training and 30% for validation), were randomly prepared to evaluate the robustness of the models. To model the gully erosion susceptibility, 12 geo-environmental factors were selected as predictors. Finally, the goodness-of-fit and prediction skill of the models were evaluated by different criteria, including efficiency percent, kappa coefficient, and the area under the ROC curves (AUC). In terms of accuracy, the RF, RBF-SVM, BRT, and P-SVM models performed excellently both in the degree of fitting and in predictive performance (AUC values well above 0.9), which resulted in accurate predictions. Therefore, these models can be used in other gully erosion studies, as they are capable of rapidly producing accurate and robust gully erosion susceptibility maps (GESMs) for decision-making and soil and water management practices. Furthermore, it was found that performance of RF and RBF-SVM for modelling gully erosion occurrence is quite stable when the learning and validation samples are changed.

Integration of landslide susceptibility products in the environmental plans

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Fiorucci, Federica; Reichenbach, Paola; Rossi, Mauro; Cardinali, Mauro; Guzzetti, Fausto

2015-04-01

Landslides are one of the most destructive natural hazard that causes damages to urban area worldwide. The knowledge of where a landslide could occur is essential for the strategic management of the territory and for a good urban planning . In this contest landslide susceptibility zoning (LSZ) is crucial to provide information on the degree to which an area can be affected by future slope movements. Despite landslide susceptibility maps have been prepared extensively during the last decades, there are few examples of application is in the environmental plans (EP). In this work we present a proposal for the integration of the landslide inventory map with the following landslide susceptibility products: (i) landslide susceptibility zonation , (ii) the associated error map and (iii) the susceptibility uncertainty map. Moreover we proposed to incorporate detailed morphological studies for the evaluation of landslide risk associated to local parceling plan. The integration of all this information is crucial for the management of landslide risk in urban expansions forecasts. Municipality, province and regional administration are often not able to support the costs of landslide risk evaluation for extensive areas but should concentrate their financial resources to specific hazardous and unsafe situations defined by the result of the integration of landslide susceptibility products. Zonation and detail morphological analysis should be performed taking into account the existing laws and regulations, and could become a starting point to discuss new regulations for the landslide risk management.

Landslide Hazard Assessment and Mapping in the Guil Catchment (Queyras, Southern French Alps): From Landslide Inventory to Susceptibility Modelling

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Roulleau, Louise; Bétard, François; Carlier, Benoît; Lissak, Candide; Fort, Monique

2016-04-01

Landslides are common natural hazards in the Southern French Alps, where they may affect human lives and cause severe damages to infrastructures. As a part of the SAMCO research project dedicated to risk evaluation in mountain areas, this study focuses on the Guil river catchment (317 km2), Queyras, to assess landslide hazard poorly studied until now. In that area, landslides are mainly occasional, low amplitude phenomena, with limited direct impacts when compared to other hazards such as floods or snow avalanches. However, when interacting with floods during extreme rainfall events, landslides may have indirect consequences of greater importance because of strong hillslope-channel connectivity along the Guil River and its tributaries (i.e. positive feedbacks). This specific morphodynamic functioning reinforces the need to have a better understanding of landslide hazards and their spatial distribution at the catchment scale to prevent local population from disasters with multi-hazard origin. The aim of this study is to produce a landslide susceptibility mapping at 1:50 000 scale as a first step towards global estimation of landslide hazard and risk. The three main methodologies used for assessing landslide susceptibility are qualitative (i.e. expert opinion), deterministic (i.e. physics-based models) and statistical methods (i.e. probabilistic models). Due to the rapid development of geographical information systems (GIS) during the last two decades, statistical methods are today widely used because they offer a greater objectivity and reproducibility at large scales. Among them, multivariate analyses are considered as the most robust techniques, especially the logistic regression method commonly used in landslide susceptibility mapping. However, this method like others is strongly dependent on the accuracy of the input data to avoid significant errors in the final results. In particular, a complete and accurate landslide inventory is required before the modelling

Application of a GIS-Based Slope Unit Method for Landslide Susceptibility Mapping along the Longzi River, Southeastern Tibetan Plateau, China

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Fei Wang

2017-06-01

Full Text Available The Longzi River Basin in Tibet is located along the edge of the Himalaya Mountains and is characterized by complex geological conditions and numerous landslides. To evaluate the susceptibility of landslide disasters in this area, eight basic factors were analyzed comprehensively in order to obtain a final susceptibility map. The eight factors are the slope angle, slope aspect, plan curvature, distance-to-fault, distance-to-river, topographic relief, annual precipitation, and lithology. Except for the rainfall factor, which was extracted from the grid cell, all the factors were extracted and classified by the slope unit, which is the basic unit in geological disaster development. The eight factors were superimposed using the information content method (ICM, and the weight of each factor was acquired through an analytic hierarchy process (AHP. The sensitivities of the landslides were divided into four categories: low, moderate, high, and very high, respectively, accounting for 22.76%, 38.64%, 27.51%, and 11.09% of the study area. The accuracies of the area under AUC using slope units and grid cells are 82.6% and 84.2%, respectively, and it means that the two methods are accurate in predicting landslide occurrence. The results show that the high and very high susceptibility areas are distributed throughout the vicinity of the river, with a large component in the north as well as a small portion in the middle and the south. Therefore, it is necessary to conduct landslide warnings in these areas, where the rivers are vast and the population is dense. The susceptibility map can reflect the comprehensive risk of each slope unit, which provides an important reference for later detailed investigations, including research and warning studies.

Slope, Scarp and Sea Cliff Instability Susceptibility Mapping for Planning Regulations in Almada County, Portugal

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Marques, Fernando; Queiroz, Sónia; Gouveia, Luís; Vasconcelos, Manuel

2017-12-01

In Portugal, the modifications introduced in 2008 and 2012 in the National Ecological Reserve law (REN) included the mandatory study of slope instability, including slopes, natural scarps, and sea cliffs, at municipal or regional scale, with the purpose of avoiding the use of hazardous zones with buildings and other structures. The law also indicates specific methods to perform these studies, with different approaches for slope instability, natural scarps and sea cliffs. The methods used to produce the maps required by REN law, with modifications and improvements to the law specified methods, were applied to the 71 km2 territory of Almada County, and included: 1) Slope instability mapping using the statistically based Information Value method validated with the landslide inventory using ROC curves, which provided an AAC=0.964, with the higher susceptibility zones which cover at least 80% of the landslides of the inventory to be included in REN map. The map was object of a generalization process to overcome the inconveniences of the use of a pixel based approach. 2) Natural scarp mapping including setback areas near the top, defined according to the law and setback areas near the toe defined by the application of the shadow angle calibrated with the major rockfalls which occurred in the study area; 3) Sea cliffs mapping including two levels of setback zones near the top, and one setback zone at the cliffs toe, which were based on systematic inventories of cliff failures occurred between 1947 and 2010 in a large scale regional littoral monitoring project. In the paper are described the methods used and the results obtained in this study, which correspond to the final maps of areas to include in REN. The results obtained in this study may be considered as an example of good practice of the municipal authorities in terms of solid, technical and scientifically supported regulation definitions, hazard prevention and safe and sustainable land use management.

Accuracy of magnetic resonance based susceptibility measurements

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Erdevig, Hannah E.; Russek, Stephen E.; Carnicka, Slavka; Stupic, Karl F.; Keenan, Kathryn E.

2017-05-01

Magnetic Resonance Imaging (MRI) is increasingly used to map the magnetic susceptibility of tissue to identify cerebral microbleeds associated with traumatic brain injury and pathological iron deposits associated with neurodegenerative diseases such as Parkinson's and Alzheimer's disease. Accurate measurements of susceptibility are important for determining oxygen and iron content in blood vessels and brain tissue for use in noninvasive clinical diagnosis and treatment assessments. Induced magnetic fields with amplitude on the order of 100 nT, can be detected using MRI phase images. The induced field distributions can then be inverted to obtain quantitative susceptibility maps. The focus of this research was to determine the accuracy of MRI-based susceptibility measurements using simple phantom geometries and to compare the susceptibility measurements with magnetometry measurements where SI-traceable standards are available. The susceptibilities of paramagnetic salt solutions in cylindrical containers were measured as a function of orientation relative to the static MRI field. The observed induced fields as a function of orientation of the cylinder were in good agreement with simple models. The MRI susceptibility measurements were compared with SQUID magnetometry using NIST-traceable standards. MRI can accurately measure relative magnetic susceptibilities while SQUID magnetometry measures absolute magnetic susceptibility. Given the accuracy of moment measurements of tissue mimicking samples, and the need to look at small differences in tissue properties, the use of existing NIST standard reference materials to calibrate MRI reference structures is problematic and better reference materials are required.

Evaluation of Renal Oxygenation Level Changes after Water Loading Using Susceptibility-Weighted Imaging and T2* Mapping.

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Ding, Jiule; Xing, Wei; Wu, Dongmei; Chen, Jie; Pan, Liang; Sun, Jun; Xing, Shijun; Dai, Yongming

2015-01-01

To assess the feasibility of susceptibility-weighted imaging (SWI) while monitoring changes in renal oxygenation level after water loading. Thirty-two volunteers (age, 28.0 ± 2.2 years) were enrolled in this study. SWI and multi-echo gradient echo sequence-based T2(*) mapping were used to cover the kidney before and after water loading. Cortical and medullary parameters were measured using small regions of interest, and their relative changes due to water loading were calculated based on baseline and post-water loading data. An intraclass correlation coefficient analysis was used to assess inter-observer reliability of each parameter. A receiver operating characteristic curve analysis was conducted to compare the performance of the two methods for detecting renal oxygenation changes due to water loading. Both medullary phase and medullary T2(*) values increased after water loading (p T2(*) changes (p > 0.05). Interobserver reliability was excellent for the T2(*) values, good for SWI cortical phase values, and moderate for the SWI medullary phase values. The area under receiver operating characteristic curve of the SWI medullary phase values was 0.85 and was not different from the medullary T2(*) value (0.84). Susceptibility-weighted imaging enabled monitoring changes in the oxygenation level in the medulla after water loading, and may allow comparable feasibility to detect renal oxygenation level changes due to water loading compared with that of T2(*) mapping.

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus

DEFF Research Database (Denmark)

Horne, Hisani N; Chung, Charles C; Zhang, Han

2016-01-01

rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120......The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking......,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry...

Data Mining Approaches for Landslide Susceptibility Mapping in Umyeonsan, Seoul, South Korea

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Sunmin Lee

2017-07-01

Full Text Available The application of data mining models has become increasingly popular in recent years in assessments of a variety of natural hazards such as landslides and floods. Data mining techniques are useful for understanding the relationships between events and their influencing variables. Because landslides are influenced by a combination of factors including geomorphological and meteorological factors, data mining techniques are helpful in elucidating the mechanisms by which these complex factors affect landslide events. In this study, spatial data mining approaches based on data on landslide locations in the geographic information system environment were investigated. The topographical factors of slope, aspect, curvature, topographic wetness index, stream power index, slope length factor, standardized height, valley depth, and downslope distance gradient were determined using topographical maps. Additional soil and forest variables using information obtained from national soil and forest maps were also investigated. A total of 17 variables affecting the frequency of landslide occurrence were selected to construct a spatial database, and support vector machine (SVM and artificial neural network (ANN models were applied to predict landslide susceptibility from the selected factors. In the SVM model, linear, polynomial, radial base function, and sigmoid kernels were applied in sequence; the model yielded 72.41%, 72.83%, 77.17% and 72.79% accuracy, respectively. The ANN model yielded a validity accuracy of 78.41%. The results of this study are useful in guiding effective strategies for the prevention and management of landslides in urban areas.

Multidisciplinary approach to evaluate landslide susceptibility along highway in northern Calabria, Italy

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Muto, Francesco; Conforti, Massimo; Critelli, Salvatore; Fabbricatore, Davide; Filomena, Luciana; Rago, Valeria; Robustelli, Gaetano; Scarciglia, Fabio; Versace, Pasquale

2014-05-01

The interaction of landslides with linear infrastructures is often the cause of disasters. In Italy landslide impact on roads, railways and buildings cause millions of Euro per year in damage and restoration as well. The proposed study is aimed to the landslide susceptibility evaluation using a multidisciplinary approach: geological and geomorphological survey, statistical analysis and GIS technique, along a section of highway "A3 (Salerno-Reggio Calabria)" between Cosenza Sud and Altilia, northern Calabria. This study is included in a wider research project, named: PON01-01503, Landslides Early Warning-Sistemi integrati per il monitoraggio e la mitigazione del rischio idrogeologico lungo le grandi vie di comunicazione - aimed at the hydrogeological risk mitigation and at the early warning along the highways. The work was first based on air-photo interpretations and field investigations, in order to realize the geological map, geomorphological map and landslide inventory map. In the study area the geomorphology is strongly controlled by its bedrock geology and tectonics. The bedrock geology consists of Neogene sedimentary rocks that cover a thick stack of allochthonous nappes. These nappes consist of crystalline rocks mainly gneiss, phyllite and schist. A total of 835 landslides were mapped and the type of movement are represented mainly by slides and complex and subordinately flow. In order to estimate and validate landslide susceptibility the landslides were divided in two group. One group (training set) was used to prepare susceptibility map and the second group (validation set) to validate the map. Then, the selection of predisposing factors was performed, according with the geological and geomorphological settings of the study area: lithology, distance from tectonic elements, land use, slope, aspect, stream power index (SPI) and plan curvature. In order to evaluate landslide susceptibility Conditional Analysis was applied to Unique Conditions Units (UCUs

GIS Supported Landslide Susceptibility Modeling at Regional Scale: An Expert-Based Fuzzy Weighting Method

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Christos Chalkias

2014-04-01

Full Text Available The main aim of this paper is landslide susceptibility assessment using fuzzy expert-based modeling. Factors that influence landslide occurrence, such as elevation, slope, aspect, lithology, land cover, precipitation and seismicity were considered. Expert-based fuzzy weighting (EFW approach was used to combine these factors for landslide susceptibility mapping (Peloponnese, Greece. This method produced a landslide susceptibility map of the investigated area. The landslides under investigation have more or less same characteristics: lateral based and downslope shallow movement of soils or rocks. The validation of the model reveals, that predicted susceptibility levels are found to be in good agreement with the past landslide occurrences. Hence, the obtained landslide susceptibility map could be acceptable, for landslide hazard prevention and mitigation at regional scale.

Landslide Susceptibility Assessment Using Frequency Ratio Technique with Iterative Random Sampling

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Hyun-Joo Oh

2017-01-01

Full Text Available This paper assesses the performance of the landslide susceptibility analysis using frequency ratio (FR with an iterative random sampling. A pair of before-and-after digital aerial photographs with 50 cm spatial resolution was used to detect landslide occurrences in Yongin area, Korea. Iterative random sampling was run ten times in total and each time it was applied to the training and validation datasets. Thirteen landslide causative factors were derived from the topographic, soil, forest, and geological maps. The FR scores were calculated from the causative factors and training occurrences repeatedly ten times. The ten landslide susceptibility maps were obtained from the integration of causative factors that assigned FR scores. The landslide susceptibility maps were validated by using each validation dataset. The FR method achieved susceptibility accuracies from 89.48% to 93.21%. And the landslide susceptibility accuracy of the FR method is higher than 89%. Moreover, the ten times iterative FR modeling may contribute to a better understanding of a regularized relationship between the causative factors and landslide susceptibility. This makes it possible to incorporate knowledge-driven considerations of the causative factors into the landslide susceptibility analysis and also be extensively used to other areas.

A GIS-based susceptibility map for landslides at the Franconian Alb, Germany

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Jaeger, Daniel; Wilde, Martina; Lorenz, Michael; Terhorst, Birgit; Neuhäuser, Bettina; Damm, Bodo; Bemm, Stefan

2014-05-01

In general, slopes of cuesta scarps like the Franconian Alb are highly prone to slide activity due to susceptible geological and geomorphological conditions. The geological setting with alternating permeable and non-permeable bedrock results in the characteristic cuesta landforms of almost flat backslopes and steeper front slopes. Furthermore, this bipartite structure leads to a strong disposition for mass movements. The slopes of the study area near the town of Ebermannstadt are affected by different types of mass movements, such as topples, slides, lateral spreads and flows, either in single or in combined occurrence. In the years 1625, 1957, 1961 and 1979, four large landslides took place in the area of Ebermannstadt, reaching close to the town limits and causing major destructions to traffic facilities. In the study area, slopes are covered by debris and slide masses, thus they are prone to remobilization and further mass movements. In order to assess hazardous areas, a GIS-based susceptibility modelling was generated for the study area. The susceptibtibility modeling was processed with the slope stability model SINMAP (Stability Index Mapping), developed by TARBOTON (1997) and PACK et al. (1999). As SINMAP was particularly designed to model shallow translational slides, it should be well designed for describing the conditions of the study area in a sufficient way. SINMAP is based on the "infinite slope stability model" by HAMMONT et al. (1992) and MONTGOMERY & DIETRICH (1994), which focuses on the relation of stabilizing (cohesiveness, friction angle) and destabilizing (gravitation) factors on a plain surface. By adding a slope gradient, as well as soil mechanical and climatical data, indices of slope stabilities are calculated. For a more detailed modeling of the slope conditions, SINMAP computes different "calibration regions", which merge similar parameters of soil, land-use, vegetation, and geology. Due to the fact that vegetation, land-use, and soils only

GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

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Skilodimou, H. D.

2009-06-01

Full Text Available Landslide susceptibility mapping is a practical tool in natural and urban planning; it can be applied for determining land use zones, in construction design and planning of a variety of projects. In this study, two different GIS based landslide susceptibility maps were generated in the mountainous part of the Trikala Prefecture in Thessaly, Central Greece. This was accomplished by using different methods for correlating factors, which have an effect on landslide occurrences. The instability factors taken into account were: lithology, tectonic features, slope gradients, road network, drainage network, land use and rainfall. A frequency distribution of the half number of the landslide events of the study area in each class of the instability factors was performed in order to rate the classes. Two models have been used to combine the instability factors and assess the overall landslide susceptibility, namely: the Weight Factor Model (WeF, which is a statistical method, and the Multiple Factor Model (MuF that is a logical method. The produced maps were classified into four zones: Low, Moderate, High and Very High susceptible zones and validated using the other half number of the landslide events of the area. Evaluation of the results is optimized through a Landslide Models Indicator (La.M.I..Los mapas de susceptibilidad de deslizamientos representan una práctica herramienta en la planificación urbana y de espacios naturales. Así, puede aplicarse a la determinación de los usos de terrenos, en el diseño de construcción civil y para la planificación de gran variedad de actividades. En este estudio se generaron dos tipos diferentes de mapas de susceptibilidad basados en GIS para la parte montañosa de la prefectura de Trikala en Tesalia (Grecia Central. Estos se llevaron a cabo usando dos métodos de correlación de los factores que pueden tener un efecto en la generación de deslizamientos. Los factores de desestabilización tenidos en cuenta

Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression

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Dieu Tien Bui

2016-04-01

Full Text Available The Cat Ba National Park area (Vietnam with its tropical forest is recognized as being part of the world biodiversity conservation by the United Nations Educational, Scientific and Cultural Organization (UNESCO and is a well-known destination for tourists, with around 500,000 travelers per year. This area has been the site for many research projects; however, no project has been carried out for forest fire susceptibility assessment. Thus, protection of the forest including fire prevention is one of the main concerns of the local authorities. This work aims to produce a tropical forest fire susceptibility map for the Cat Ba National Park area, which may be helpful for the local authorities in forest fire protection management. To obtain this purpose, first, historical forest fires and related factors were collected from various sources to construct a GIS database. Then, a forest fire susceptibility model was developed using Kernel logistic regression. The quality of the model was assessed using the Receiver Operating Characteristic (ROC curve, area under the ROC curve (AUC, and five statistical evaluation measures. The usability of the resulting model is further compared with a benchmark model, the support vector machine (SVM. The results show that the Kernel logistic regression model has a high level of performance in both the training and validation dataset, with a prediction capability of 92.2%. Since the Kernel logistic regression model outperforms the benchmark model, we conclude that the proposed model is a promising alternative tool that should also be considered for forest fire susceptibility mapping in other areas. The results of this study are useful for the local authorities in forest planning and management.

Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

Science.gov (United States)

Yusof, Norbazlan M.; Pradhan, Biswajeet

2014-06-01

PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for data

Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

International Nuclear Information System (INIS)

Yusof, Norbazlan M; Pradhan, Biswajeet

2014-01-01

PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for

Soil magnetic susceptibility mapping as a pollution and provenance tool: an example from southern New Zealand

Science.gov (United States)

Martin, A. P.; Ohneiser, C.; Turnbull, R. E.; Strong, D. T.; Demler, S.

2018-02-01

The presence or absence, degree and variation of heavy metal contamination in New Zealand soils is a matter of ongoing debate as it affects soil quality, agriculture and human health. In many instances, however, the soil heavy metal concentration data do not exist to answer these questions and the debate is ongoing. To address this, magnetic susceptibility (a common proxy for heavy metal contamination) values were measured in topsoil (0-30 cm) and subsoil (50-70 cm) at grid sites spaced at 8 km intervals across ca. 20 000 km2 of southern New Zealand. Samples were measured for both mass- and volume-specific magnetic susceptibility, with results being strongly, positively correlated. Three different methods of determining anomalies were applied to the data including the topsoil-subsoil difference method, Tukey boxplot method and geoaccumulation index method, with each method filtering out progressively more anomalies. Additional soil magnetic (hysteresis, isothermal remanence and thermomagnetic) measurements were made on a select subset of samples from anomalous sites. Magnetite is the dominant remanence carrying mineral, and magnetic susceptibility is governed by that minerals concentration in soils, rather than mineral type. All except two anomalous sites have a dominant geogenic source (cf. anthropogenic). By proxy, heavy metal contamination in southern New Zealand soils is minimal, making them relatively pristine. The provenance of the magnetic minerals in the anomalous sites can be traced back to likely sources in outcrops of igneous rocks within the same catchment, terrane or rock type: a distance of Soil provenance is a key step when mapping element or isotopic distribution, vectoring to mineralization or studying soil for agricultural suitability, water quality or environmental regulation. Measuring soil magnetic susceptibility is a useful, quick and inexpensive tool that usefully supplements soil geochemical data.

The magnetic susceptibility of soils in Krakow, southern Poland

Science.gov (United States)

Wojas, Anna

2017-06-01

Studies into the magnetic susceptibility have been used to assess the soils contamination in the Krakow area. The results of topsoil (over a 2 × 2 km grid), subsoil (37 shallow holes) and soil samples (112) measurements were presented as maps of soil magnetic susceptibility (both volume and mass) illustrating the distribution of parameters in topsoil horizon (0-10 cm) and differential magnetic susceptibility maps between topsoil horizon and subsoil (40-60 cm). All evidence leads to the finding that the highest values of magnetic susceptibility of soil are found exclusively in industrial areas. Taking into consideration the type of land use, the high median value (89.8 × 10-8 m3kg-1) was obtained for samples of cultivated soils and is likely to be connected with occurrence of fertile soil (chernozem). Moreover, enrichment of soils with Pb and Zn accompanies magnetic susceptibility anomalies in the vicinity of the high roads and in the steelworks area, respectively.

Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers.

Science.gov (United States)

Zheng, Yonglan; Ogundiran, Temidayo O; Falusi, Adeyinka G; Nathanson, Katherine L; John, Esther M; Hennis, Anselm J M; Ambs, Stefan; Domchek, Susan M; Rebbeck, Timothy R; Simon, Michael S; Nemesure, Barbara; Wu, Suh-Yuh; Leske, Maria Cristina; Odetunde, Abayomi; Niu, Qun; Zhang, Jing; Afolabi, Chibuzor; Gamazon, Eric R; Cox, Nancy J; Olopade, Christopher O; Olopade, Olufunmilayo I; Huo, Dezheng

2013-07-01

Numerous single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified by genome-wide association studies (GWAS). However, these SNPs were primarily discovered and validated in women of European and Asian ancestry. Because linkage disequilibrium is ancestry-dependent and heterogeneous among racial/ethnic populations, we evaluated common genetic variants at 22 GWAS-identified breast cancer susceptibility loci in a pooled sample of 1502 breast cancer cases and 1378 controls of African ancestry. None of the 22 GWAS index SNPs could be validated, challenging the direct generalizability of breast cancer risk variants identified in Caucasians or Asians to other populations. Novel breast cancer risk variants for women of African ancestry were identified in regions including 5p12 (odds ratio [OR] = 1.40, 95% confidence interval [CI] = 1.11-1.76; P = 0.004), 5q11.2 (OR = 1.22, 95% CI = 1.09-1.36; P = 0.00053) and 10p15.1 (OR = 1.22, 95% CI = 1.08-1.38; P = 0.0015). We also found positive association signals in three regions (6q25.1, 10q26.13 and 16q12.1-q12.2) previously confirmed by fine mapping in women of African ancestry. In addition, polygenic model indicated that eight best markers in this study, compared with 22 GWAS-identified SNPs, could better predict breast cancer risk in women of African ancestry (per-allele OR = 1.21, 95% CI = 1.16-1.27; P = 9.7 × 10(-16)). Our results demonstrate that fine mapping is a powerful approach to better characterize the breast cancer risk alleles in diverse populations. Future studies and new GWAS in women of African ancestry hold promise to discover additional variants for breast cancer susceptibility with clinical implications throughout the African diaspora.

Landslide inventory and susceptibility modelling using geospatial tools, in Hunza-Nagar valley, northern Pakistan

NARCIS (Netherlands)

Bacha, Alam Sher; Shafique, Muhammad; van der Werff, H.M.A.

2018-01-01

A comprehensive landslide inventory and susceptibility maps are prerequisite for developing and implementing landslide mitigation strategies. Landslide susceptibility maps for the landslides prone regions in northern Pakistan are rarely available. The Hunza-Nagar valley in northern Pakistan is known

Integrating Expert Knowledge with Statistical Analysis for Landslide Susceptibility Assessment at Regional Scale

Directory of Open Access Journals (Sweden)

Christos Chalkias

2016-03-01

Full Text Available In this paper, an integration landslide susceptibility model by combining expert-based and bivariate statistical analysis (Landslide Susceptibility Index—LSI approaches is presented. Factors related with the occurrence of landslides—such as elevation, slope angle, slope aspect, lithology, land cover, Mean Annual Precipitation (MAP and Peak Ground Acceleration (PGA—were analyzed within a GIS environment. This integrated model produced a landslide susceptibility map which categorized the study area according to the probability level of landslide occurrence. The accuracy of the final map was evaluated by Receiver Operating Characteristics (ROC analysis depending on an independent (validation dataset of landslide events. The prediction ability was found to be 76% revealing that the integration of statistical analysis with human expertise can provide an acceptable landslide susceptibility assessment at regional scale.

Method of magnetic susceptibility mapping of drilled cores. Experimental measurements for geologic structures determination; Methode de cartographie de susceptibilite magnetique sur carottes de forage. Mesures experimentales pour la determination de structures geologiques

Energy Technology Data Exchange (ETDEWEB)

Delrive, C

1993-11-08

The evaluation of the safety of a deep geologic repository for dangerous materials requires the knowledge of the interstitial system of the surrounding host rock. A method is proposed for the determination of geologic structures (in particular fractures) from the magnetic susceptibility mapping of drilled cores. The feasibility of the method has been demonstrated using a SQUID magneto-gradient meter. A measurement tool using a new magnetic susceptibility captor and a testing bench have been developed. This tool allows the measurement of rocks with a magnetic susceptibility greater than 10{sup -5} SI units and can generate magnetic susceptibility maps with 4 x 4 mm{sup 2} pixels. A magnetic visibility criterion has been defined which allows to foresee if a structure is visible or not. According to the measurements done, it is shown that any centimeter-scale structure with a sufficient magnetic contrast (20%) with respect to the matrix is visible. Therefore, the dip and the orientation of such structure can be determined with a 3 degree and a 5 degree precision, respectively. The position of the structure along the core axis is known with a 4 mm precision. On the other hand, about half of the magnetic contrasts observed do not correspond to the visual analyses and can be explained by very small variations of the mineralogic composition. This last point offers some interesting ways for future research using magnetic susceptibility mapping. (J.S.). 31 refs., 90 figs., 18 tabs., 2 photos., 6 appends.

Quantitative measurements of brain iron deposition in cirrhotic patients using susceptibility mapping.

Science.gov (United States)

Xia, Shuang; Zheng, Gang; Shen, Wen; Liu, Saifeng; Zhang, Long Jiang; Haacke, E Mark; Lu, Guang Ming

2015-03-01

Susceptibility-weighted imaging (SWI) has been used to detect micro-bleeds and iron deposits in the brain. However, no reports have been published on the application of SWI in studying iron changes in the brain of cirrhotic patients. To compare the susceptibility of different brain structures in cirrhotic patients with that in healthy controls and to evaluate susceptibility as a potential biomarker and correlate the measured susceptibility and cadaveric brain iron concentration for a variety of brain structures. Forty-three cirrhotic patients (27 men, 16 women; mean age, 50 ± 9 years) and 34 age- and sex-matched healthy controls (22 men, 12 women; mean age, 47 ± 7 years) were included in this retrospective study. Susceptibility was measured in the frontal white matter, basal ganglia, midbrain, and dentate nucleus and compared with results gathered from two postmortem brain studies. Correlation between susceptibility and clinical biomarkers and neuropsychiatric tests scores was calculated. In cirrhotic patients, the susceptibility of left frontal white matter, bilateral caudate head, and right substantia nigra was higher than that in healthy controls (P brain study (r = 0.835, P = 0.01) in eight deep grey matter structures and another in five brain structures (r = 0.900, P = 0.03). The susceptibility of right caudate head (r = 0.402) and left caudate head (r = 0.408) correlated with neuropsychological test scores (both P brain regions appears to reflect neurocognitive changes. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Evaluation of renal oxygenation level changes after water loading using susceptibility-weighted imaging and T2{sup *} mapping

Energy Technology Data Exchange (ETDEWEB)

Ding, Jiule; Xing, Wei; Chen, Jie; Pan, Liang; Sun, Jun; Xing, Shi Jun [Dept. of Radiology, Third Affiliated Hospital of Suzhou University, Changzhou (China); Wu, Dong Mei [Shanghai Key Laboratory of Magnetic Resonance Imaging, East China Normal University, Shanghai (China); Dai, Yong Ming [Philips Healthcare, Shanghai (China)

2015-08-15

To assess the feasibility of susceptibility-weighted imaging (SWI) while monitoring changes in renal oxygenation level after water loading. Thirty-two volunteers (age, 28.0 ± 2.2 years) were enrolled in this study. SWI and multi-echo gradient echo sequence-based T2{sup *} mapping were used to cover the kidney before and after water loading. Cortical and medullary parameters were measured using small regions of interest, and their relative changes due to water loading were calculated based on baseline and post-water loading data. An intraclass correlation coefficient analysis was used to assess inter-observer reliability of each parameter. A receiver operating characteristic curve analysis was conducted to compare the performance of the two methods for detecting renal oxygenation changes due to water loading. Both medullary phase and medullary T2{sup *} values increased after water loading (p < 0.001), although poor correlations were found between the phase changes and the T2{sup *} changes (p > 0.05). Interobserver reliability was excellent for the T2{sup *} values, good for SWI cortical phase values, and moderate for the SWI medullary phase values. The area under receiver operating characteristic curve of the SWI medullary phase values was 0.85 and was not different from the medullary T2{sup *} value (0.84). Susceptibility-weighted imaging enabled monitoring changes in the oxygenation level in the medulla after water loading, and may allow comparable feasibility to detect renal oxygenation level changes due to water loading compared with that of T2{sup *} mapping.

Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda

Directory of Open Access Journals (Sweden)

Jean Baptiste Nsengiyumva

2018-01-01

Full Text Available Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively. Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8% with no very high susceptibility (0%. Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management.

Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda

Science.gov (United States)

Nsengiyumva, Jean Baptiste; Luo, Geping; Nahayo, Lamek; Huang, Xiaotao; Cai, Peng

2018-01-01

Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management. PMID:29385096

1 Mapping Debris Flow Susceptibility using Analytical Network ...

Indian Academy of Sciences (India)

54

activities in the past. In this study, one of the less explored heuristic methods known. 10 ...... can be associated in any prospective way, through feedbacks and inter-relationships. 25 ..... means of multivariate statistical techniques. .... susceptibility assessment using GIS and bivariate statistics: a case study in southern. 9. Italy.

Complex geohazard susceptibility zoning for effective landuse planning and catastroph prevention in developing countries

Science.gov (United States)

Hradecky, P.; Baron, I.

2012-04-01

The Czech Geological Survey conducted projects of geological mapping and complex geohazard susceptibility zoning in Nicaragua in the years 1997-2009. For selected areas in vicinity of major cities and towns basic geological maps at a scalle 1:50,000, maps of geomorphic features (Geomorphic Inventory Maps), Morphostructural Maps of estimated fault zones, and derived Geohazard Susceptibility maps were done. These maps were prepared during field campaigns by direct field mapping, analysis of remote-sensing data, communicating the local authorities, interwieving the local inhabitants and with very close cooperation with the local partner of the projects - the Instituto Nicaragüense de Estudios Territoriales (INETER). The resulting maps and explanatory reports presented the dangerous natural processes that occurred in each respective area in the past and proposed preventive measures in detail. Zones evaluated as highly susceptible, e.g., to (i) mass movements, (ii) large inundations, (iii) torrential flooding, (iv) seismogenic liquefaction, etc., were presented in bold colours on the maps. Such maps and reports were presented to local authorities and inhabitants of respective cities during public breefings at the end of each mapping campaign. In such a way, areas of Pacific volcanic ridge (1997-2003), Jinotega (2004), Somoto (2005), Estelí (2006), Boaco and Santa Lucia (2007, 2008), Sebaco (2008) and Jalapa (2009) were elaborated. The maps then served to the INETER for implementation into the landuse plans, evacuation routes and other preventive measures to protect and save human lives and inftrastructure. This approach could serve as a muster for a simple, cost effective and relatively fast geohazards susceptibility evaluation of any area in any developing country. The projects also paid attention to capacity building of our Nicaraguan partners. These projects of the Czech Geological Survey were conducted as the international aid of the Czech Republic to Nicaragua

A Spatially Explicit Approach for Sensitivity and Uncertainty Analysis of GIS-Multicriteria Landslide Susceptibility Mapping. GI_Forum 2013 – Creating the GISociety|

OpenAIRE

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2016-01-01

GIS multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping for the prediction of future hazards, decision making, as well as hazard mitigation plans. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are prone to multiple types of uncertainty. In this paper, the spatiality explicitly method is employed to assess the uncertainty associated with two methods of GIS-MCDA namely, Analytical Hierarchi...

Susceptible-infected-recovered and susceptible-exposed-infected models

International Nuclear Information System (INIS)

Tome, Tania; De Oliveira, Mario J

2011-01-01

Two stochastic epidemic lattice models, the susceptible-infected-recovered and the susceptible-exposed-infected models, are studied on a Cayley tree of coordination number k. The spreading of the disease in the former is found to occur when the infection probability b is larger than b c = k/2(k - 1). In the latter, which is equivalent to a dynamic site percolation model, the spreading occurs when the infection probability p is greater than p c = 1/(k - 1). We set up and solve the time evolution equations for both models and determine the final and time-dependent properties, including the epidemic curve. We show that the two models are closely related by revealing that their relevant properties are exactly mapped into each other when p = b/[k - (k - 1)b]. These include the cluster size distribution and the density of individuals of each type, quantities that have been determined in closed forms.

Mapping Forest Fire Susceptibility in Temperate Mountain Areas with Expert Knowledge. A Case Study from Iezer Mountains, Romanian Carpathians

Science.gov (United States)

Mihai, Bogdan; Savulescu, Ionut

2014-05-01

Forest fires in Romanian Carpathians became a frequent phenomenon during the last decade, although local climate and other environmental features did not create typical conditions. From 2004, forest fires affect in Romania more than 100 hectares/year of different forest types (deciduous and coniferous). Their magnitude and frequency are not known, since a historical forest fire inventory does not exist (only press papers and local witness for some selected events). Forest fires features the summer dry periods but there are dry autumns and early winter periods with events of different magnitudes. The application we propose is based on an empirical modeling of forest fire susceptibility in a typical mountain area from the Southern Carpathians, the Iezer Mountains (2462 m). The study area features almost all the altitudinal vegetation zones of the European temperate mountains, from the beech zone, to the coniferous zone, the subalpine and the alpine zones (Mihai et al., 2007). The analysis combines GIS and remote sensing models (Chuvieco et al., 2012), starting from the ideas that forest fires are featured by the ignition zones and then by the fire propagation zones. The first data layer (ignition zones) is the result of the crossing between the ignition factors: lightning - points of multitemporal occurence and anthropogenic activities (grazing, tourism and traffic) and the ignition zones (forest fuel zonation - forest stands, soil cover and topoclimatic factor zonation). This data is modelled from different sources: the MODIS imagery fire product (Hantson et al., 2012), detailed topographic maps, multitemporal orthophotos at 0.5 m resolution, Landsat multispectral imagery, forestry cadastre maps, detailed soil maps, meteorological data (the WorldClim digital database) as well as the field survey (mapping using GPS and local observation). The second data layer (fire propagation zones) is the result of the crossing between the forest fuel zonation, obtained with the

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

Science.gov (United States)

Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel

2017-07-01

Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

ANFIS modeling for the assessment of landslide susceptibility for the Cameron Highland (Malaysia)

Science.gov (United States)

Pradhan, Biswajeet; Sezer, Ebru; Gokceoglu, Candan; Buchroithner, Manfred F.

2010-05-01

Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. In landslide literature, there are several approaches such as probabilistic, bivariate and multivariate statistical models, fuzzy and artificial neural network models etc. However, a neuro-fuzzy application on the landslide susceptibility assessment has not been encountered in the literature. For this reason, this study presents the results of an adaptive neuro-fuzzy inference system (ANFIS) using remote sensing data and GIS for landslide susceptibility analysis in a part of the Cameron Highland areas in Malaysia. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments, NDVI and land cover were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, curvature, distance from drainage, lithology, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to produce the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were constructed. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values were calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 97% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient agreement between the obtained susceptibility map and the existing data on landslide areas. Qualitatively, the model yields reasonable results which can be used for preliminary land

Anti-decuplet pentaquarks in the chiral quark-soliton model

International Nuclear Information System (INIS)

Ledwig, T.

2007-01-01

This thesis is an investigation of the anti-decuplet pentaquarks, especially the Θ + (udd anti s), within the framework of the χQSM. All baryon properties in this work are calculated by diagonalizing the χQSM Hamiltonian numerically and using these eigenvalues. Using the explicit dynamics of the χQSMenables us to investigate systematically properties of the octet, decuplet and anti-decuplet baryons, all of them within the same set of parameters. The χQSM is in good agreement with octet experimental data and since the new pentaquark discussion was triggered by the rotational picture of the χQSM, it is natural to extend this formalism to the anti-decuplet. At first we extract the mass of the Θ + in the χQSM. Among the results in this work, there are two of greater interest. In the light of the unsettled experimental situation the production/ formation of the Θ + plays an outstanding role. These processes are characterized by the coupling constants of the vector kaon and pseudo-scalar kaon coupling to the Θ-N system. In order to be compatible with experiments these coupling constants should be small. The vector kaon coupling strength can be extracted out of the vector-current via the vector-meson dominance. The vector-current will be subject of the third chapter. The pseudo-scalar kaon coupling is discussed in the fourth chapter along with the axial-vector current. By mapping the axial-vector constant to the strong coupling via the Goldberger-Treiman relation we are able to determine the Θ + decay width. Further aspects in case of the vector-current are the spatial sizes of the Θ + . We will determine the electric radii of the anti-decuplet baryons in order to distinguish whether the Θ + , minimal Fockcomponent of a five-quark state, is some kind of N-K molecule or a compact object like normal baryons. Magnetic anti-decuplet form factors are presented. Magnetic moments are also calculated for decuplet baryons. We consider the symmetry conserving

Application of Physically based landslide susceptibility models in Brazil

Science.gov (United States)

Carvalho Vieira, Bianca; Martins, Tiago D.

2017-04-01

Shallow landslides and floods are the processes responsible for most material and environmental damages in Brazil. In the last decades, some landslides events induce a high number of deaths (e.g. Over 1000 deaths in one event) and incalculable social and economic losses. Therefore, the prediction of those processes is considered an important tool for land use planning tools. Among different methods the physically based landslide susceptibility models having been widely used in many countries, but in Brazil it is still incipient when compared to other ones, like statistical tools and frequency analyses. Thus, the main objective of this research was to assess the application of some Physically based landslide susceptibility models in Brazil, identifying their main results, the efficiency of susceptibility mapping, parameters used and limitations of the tropical humid environment. In order to achieve that, it was evaluated SHALSTAB, SINMAP and TRIGRS models in some studies in Brazil along with the Geotechnical values, scales, DEM grid resolution and the results based on the analysis of the agreement between predicted susceptibility and the landslide scar's map. Most of the studies in Brazil applied SHALSTAB, SINMAP and to a lesser extent the TRIGRS model. The majority researches are concentrated in the Serra do Mar mountain range, that is a system of escarpments and rugged mountains that extends more than 1,500 km along the southern and southeastern Brazilian coast, and regularly affected by heavy rainfall that generates widespread mass movements. Most part of these studies used conventional topographic maps with scales ranging from 1:2000 to 1:50000 and DEM-grid resolution between 2 and 20m. Regarding the Geotechnical and hydrological values, a few studies use field collected data which could produce more efficient results, as indicated by international literature. Therefore, even though they have enormous potential in the susceptibility mapping, even for comparison

Urbanization and climate change implications in flood risk management: Developing an efficient decision support system for flood susceptibility mapping.

Science.gov (United States)

Mahmoud, Shereif H; Gan, Thian Yew

2018-04-26

The effects of urbanization and climate change impact to the flood risk of two governorates in Egypt were analyzed. Non-parametric change point and trend detection algorithms were applied to the annual rainfall, rainfall anomaly, and temperature anomaly of both study sites. Next, change points and trends of the annual and monthly surface runoff data generated by the Curve Number method over 1948-2014 were also analyzed to detect the effects of urbanization on the surface runoff. Lastly, a GIS decision support system was developed to delineate flood susceptibility zones for the two governorates. The significant decline in annual rainfall and rainfall anomaly after 1994 at 8.96 and 15.3 mm/decade respectively was likely due to climate change impact, especially significant warming trend since 1976 at 0.16 °C/decade, though that could partly be attributed to rapid urbanization. Since 1970, effects of urbanization to flood risk are clear, because despite a decline in rainfall, the annual surface runoff and runoff anomaly show positive trends of 12.7 and of 14.39 mm/decade, respectively. Eleven flood contributing factors have been identified and used in mapping flood susceptibility zones of both sites. In the El-Beheira governorate, 9.2%, 17.9%, 32.3%, 28.3% and 12.3% of its area are categorized as very high, high, moderate, low and very low susceptibility to flooding, respectively. Similarly, in Alexandria governorate, 15.9%, 33.5%, 41%, 8.8% and 0.8% of its area are categorized as very high, high, moderate, low and very low susceptibility to flooding, respectively. Very high and high susceptible zones are located in the northern, northwestern and northeastern parts of the Beheira governorates, and in the northeastern and northwestern parts of Alexandria. The flood related information obtained in this study will be useful to assist mitigating potential flood damages and future land use planning of both governorates of Egypt. Copyright © 2018 Elsevier B.V. All

A GIS-based statistical model for rapid landslide susceptibility mapping in the Beichuan-Pingwu area, Sichuan, China

International Nuclear Information System (INIS)

Chen, Y; Wang, Q J

2014-01-01

The 2008 Wenchuan earthquake, with a magnitude of Mw 8.0, induced numerous landslides. Remote sensing planes were sent out to take high resolution aerial photographs, from which the geologic hazards could be instantly interpreted. However, aerial images covering all of the study area could not be obtained in a short time because of the limitations of the planes and the influence of weather conditions. This studyestablishes a statistical model based on the landslide interpretation results of one photographic strip inside the Beichuan-Pingwu area. It has strong applicability and can be applied to other places without such data. Finally, we produced a landslide susceptibility map, which providesscientific support for the instant evaluation of disaster information and post-disaster reconstruction

Comparison of the landslide susceptibility models in Taipei Water Source Domain, Taiwan

Science.gov (United States)

WU, C. Y.; Yeh, Y. C.; Chou, T. H.

2017-12-01

Taipei Water Source Domain, locating at the southeast of Taipei Metropolis, is the main source of water resource in this region. Recently, the downstream turbidity often soared significantly during the typhoon period because of the upstream landslides. The landslide susceptibilities should be analysed to assess the influence zones caused by different rainfall events, and to ensure the abilities of this domain to serve enough and quality water resource. Generally, the landslide susceptibility models can be established based on either a long-term landslide inventory or a specified landslide event. Sometimes, there is no long-term landslide inventory in some areas. Thus, the event-based landslide susceptibility models are established widely. However, the inventory-based and event-based landslide susceptibility models may result in dissimilar susceptibility maps in the same area. So the purposes of this study were to compare the landslide susceptibility maps derived from the inventory-based and event-based models, and to interpret how to select a representative event to be included in the susceptibility model. The landslide inventory from Typhoon Tim in July, 1994 and Typhoon Soudelor in August, 2015 was collected, and used to establish the inventory-based landslide susceptibility model. The landslides caused by Typhoon Nari and rainfall data were used to establish the event-based model. The results indicated the high susceptibility slope-units were located at middle upstream Nan-Shih Stream basin.

Probing white-matter microstructure with higher-order diffusion tensors and susceptibility tensor MRI

Science.gov (United States)

Liu, Chunlei; Murphy, Nicole E.; Li, Wei

2012-01-01

Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging (STI) has provided another unique tool for assessing the structure of white matter. In the highly ordered white matter structure, diffusion MRI measures hindered water mobility induced by various tissue and cell membranes, while susceptibility sensitizes to the molecular composition and axonal arrangement. Integrating these two methods may produce new insights into the complex physiology of white matter. In this study, we investigated the relationship between diffusion and magnetic susceptibility in the white matter. Experiments were conducted on phantoms and human brains in vivo. Diffusion properties were quantified with the diffusion tensor model and also with the higher order tensor model based on the cumulant expansion. Frequency shift and susceptibility tensor were measured with quantitative susceptibility mapping and susceptibility tensor imaging. These diffusion and susceptibility quantities were compared and correlated in regions of single fiber bundles and regions of multiple fiber orientations. Relationships were established with similarities and differences identified. It is believed that diffusion MRI and susceptibility MRI provide complementary information of the microstructure of white matter. Together, they allow a more complete assessment of healthy and diseased brains. PMID:23507987

Collaborative GIS for flood susceptibility mapping: An example from Mekong river basin of Viet Nam

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Thanh, B.

2016-12-01

Flooding is one of the most dangerous natural disasters in Vietnam. Floods have caused serious damages to people and made adverse impact on social economic development across the country, especially in lower river basin where there is high risk of flooding as consequences of the climate change and social activities. This paper presents a collaborative platform of a combination of an interactive web-GIS framework and a multi-criteria evaluation (MCE) tool. MCE is carried out in server side through web interface, in which parameters used for evaluation are groups into three major categories, including (1) climatic factor: precipitation, typhoon frequency, temperature, humidity (2) physiographic data: DEM, topographic wetness index, NDVI, stream power index, soil texture, distance to river (3) social factor: NDBI, land use pattern. Web-based GIS is based on open-source technology that includes an information page, a page for MCE tool that users can interactively alter parameters in flood susceptible mapping, and a discussion page. The system is designed for local participation in prediction of the flood risk magnitude under impacts of natural processes and human intervention. The proposed flood susceptibility assessment prototype was implemented in the Mekong river basin, Viet Nam. Index images were calculated using Landsat data, and other were collected from authorized agencies. This study shows the potential to combine web-GIS and spatial analysis tool to flood hazard risk assessment. The combination can be a supportive solution that potentially assists the interaction between stakeholders in information exchange and in disaster management, thus provides for better analysis, control and decision-making.

Admixture mapping of end stage kidney disease genetic susceptibility using estimated mutual information ancestry informative markers

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Geiger Dan

2010-10-01

Full Text Available Abstract Background The question of a genetic contribution to the higher prevalence and incidence of end stage kidney disease (ESKD among African Americans (AA remained unresolved, until recent findings using admixture mapping pointed to the association of a genomic locus on chromosome 22 with this disease phenotype. In the current study we utilize this example to demonstrate the utility of applying a multi-step admixture mapping approach. Methods A multi-step case only admixture mapping study, consisted of the following steps was designed: 1 Assembly of the sample dataset (ESKD AA; 2 Design of the estimated mutual information ancestry informative markers (n = 2016 screening panel 3; Genotyping the sample set whose size was determined by a power analysis (n = 576 appropriate for the initial screening panel; 4 Inference of local ancestry for each individual and identification of regions with increased AA ancestry using two different ancestry inference statistical approaches; 5 Enrichment of the initial screening panel; 6 Power analysis of the enriched panel 7 Genotyping of additional samples. 8 Re-analysis of the genotyping results to identify a genetic risk locus. Results The initial screening phase yielded a significant peak using the ADMIXMAP ancestry inference program applying case only statistics. Subgroup analysis of 299 ESKD patients with no history of diabetes yielded peaks using both the ANCESTRYMAP and ADMIXMAP ancestry inference programs. The significant peak was found on chromosome 22. Genotyping of additional ancestry informative markers on chromosome 22 that took into account linkage disequilibrium in the ancestral populations, and the addition of samples increased the statistical significance of the finding. Conclusions A multi-step admixture mapping analysis of AA ESKD patients replicated the finding of a candidate risk locus on chromosome 22, contributing to the heightened susceptibility of African Americans to develop non

Low signal-to-noise FDEM in-phase data: Practical potential for magnetic susceptibility modelling

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Delefortrie, Samuël; Hanssens, Daan; De Smedt, Philippe

2018-05-01

In this paper, we consider the use of land-based frequency-domain electromagnetics (FDEM) for magnetic susceptibility modelling. FDEM data comprises both out-of-phase and in-phase components, which can be related to the electrical conductivity and magnetic susceptibility of the subsurface. Though applying the FDEM method to obtain information on the subsurface conductivity is well established in various domains (e.g. through the low induction number approximation of subsurface apparent conductivity), the potential for susceptibility mapping is often overlooked. Especially given a subsurface with a low magnetite and maghemite content (e.g. most sedimentary environments), it is generally assumed that susceptibility is negligible. Nonetheless, the heterogeneity of the near surface and the impact of anthropogenic disturbances on the soil can cause sufficient variation in susceptibility for it to be detectable in a repeatable way. Unfortunately, it can be challenging to study the potential for susceptibility mapping due to systematic errors, an often poor low signal-to-noise ratio, and the intricacy of correlating in-phase responses with subsurface susceptibility and conductivity. Alongside use of an accurate forward model - accounting for out-of-phase/in-phase coupling - any attempt at relating the in-phase response with subsurface susceptibility requires overcoming instrument-specific limitations that burden the real-world application of FDEM susceptibility mapping. Firstly, the often erratic and drift-sensitive nature of in-phase responses calls for relative data levelling. In addition, a correction for absolute levelling offsets may be equally necessary: ancillary (subsurface) susceptibility data can be used to assess the importance of absolute in-phase calibration though hereby accurate in-situ data is required. To allow assessing the (importance of) in-phase calibration alongside the potential of FDEM data for susceptibility modelling, we consider an experimental

Assessment of Groundwater Susceptibility to Non-Point Source Contaminants Using Three-Dimensional Transient Indexes.

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Zhang, Yong; Weissmann, Gary S; Fogg, Graham E; Lu, Bingqing; Sun, HongGuang; Zheng, Chunmiao

2018-06-05

Groundwater susceptibility to non-point source contamination is typically quantified by stable indexes, while groundwater quality evolution (or deterioration globally) can be a long-term process that may last for decades and exhibit strong temporal variations. This study proposes a three-dimensional (3- d ), transient index map built upon physical models to characterize the complete temporal evolution of deep aquifer susceptibility. For illustration purposes, the previous travel time probability density (BTTPD) approach is extended to assess the 3- d deep groundwater susceptibility to non-point source contamination within a sequence stratigraphic framework observed in the Kings River fluvial fan (KRFF) aquifer. The BTTPD, which represents complete age distributions underlying a single groundwater sample in a regional-scale aquifer, is used as a quantitative, transient measure of aquifer susceptibility. The resultant 3- d imaging of susceptibility using the simulated BTTPDs in KRFF reveals the strong influence of regional-scale heterogeneity on susceptibility. The regional-scale incised-valley fill deposits increase the susceptibility of aquifers by enhancing rapid downward solute movement and displaying relatively narrow and young age distributions. In contrast, the regional-scale sequence-boundary paleosols within the open-fan deposits "protect" deep aquifers by slowing downward solute movement and displaying a relatively broad and old age distribution. Further comparison of the simulated susceptibility index maps to known contaminant distributions shows that these maps are generally consistent with the high concentration and quick evolution of 1,2-dibromo-3-chloropropane (DBCP) in groundwater around the incised-valley fill since the 1970s'. This application demonstrates that the BTTPDs can be used as quantitative and transient measures of deep aquifer susceptibility to non-point source contamination.

Blood pressure modifies retinal susceptibility to intraocular pressure elevation.

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Zheng He

Full Text Available Primary open angle glaucoma affects more than 67 million people. Elevated intraocular pressure (IOP is a risk factor for glaucoma and may reduce nutrient availability by decreasing ocular perfusion pressure (OPP. An interaction between arterial blood pressure and IOP determines OPP; but the exact contribution that these factors have for retinal function is not fully understood. Here we sought to determine how acute modifications of arterial pressure will affect the susceptibility of neuronal function and blood flow to IOP challenge. Anaesthetized (ketamine:xylazine Long-Evan rats with low (∼60 mmHg, sodium nitroprusside infusion, moderate (∼100 mmHg, saline, or high levels (∼160 mmHg, angiotensin II of mean arterial pressure (MAP, n = 5-10 per group were subjected to IOP challenge (10-120 mmHg, 5 mmHg steps every 3 minutes. Electroretinograms were measured at each IOP step to assess bipolar cell (b-wave and inner retinal function (scotopic threshold response or STR. Ocular blood flow was measured using laser-Doppler flowmetry in groups with similar MAP level and the same IOP challenge protocol. Both b-wave and STR amplitudes decreased with IOP elevation. Retinal function was less susceptible to IOP challenge when MAP was high, whereas the converse was true for low MAP. Consistent with the effects on retinal function, higher IOP was needed to attenuated ocular blood flow in animals with higher MAP. The susceptibility of retinal function to IOP challenge can be ameliorated by acute high BP, and exacerbated by low BP. This is partially mediated by modifications in ocular blood flow.

Genome-wide mapping of susceptibility to coronary artery disease identifies a novel replicated locus on chromosome 17.

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Martin Farrall

2006-05-01

Full Text Available Coronary artery disease (CAD is a leading cause of death world-wide, and most cases have a complex, multifactorial aetiology that includes a substantial heritable component. Identification of new genes involved in CAD may inform pathogenesis and provide new therapeutic targets. The PROCARDIS study recruited 2,658 affected sibling pairs (ASPs with onset of CAD before age 66 y from four European countries to map susceptibility loci for CAD. ASPs were defined as having CAD phenotype if both had CAD, or myocardial infarction (MI phenotype if both had a MI. In a first study, involving a genome-wide linkage screen, tentative loci were mapped to Chromosomes 3 and 11 with the CAD phenotype (1,464 ASPs, and to Chromosome 17 with the MI phenotype (739 ASPs. In a second study, these loci were examined with a dense panel of grid-tightening markers in an independent set of families (1,194 CAD and 344 MI ASPs. This replication study showed a significant result on Chromosome 17 (MI phenotype; p = 0.009 after adjustment for three independent replication tests. An exclusion analysis suggests that further genes of effect size lambda(sib > 1.24 are unlikely to exist in these populations of European ancestry. To our knowledge, this is the first genome-wide linkage analysis to map, and replicate, a CAD locus. The region on Chromosome 17 provides a compelling target within which to identify novel genes underlying CAD. Understanding the genetic aetiology of CAD may lead to novel preventative and/or therapeutic strategies.

Background field removal technique using regularization enabled sophisticated harmonic artifact reduction for phase data with varying kernel sizes.

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Kan, Hirohito; Kasai, Harumasa; Arai, Nobuyuki; Kunitomo, Hiroshi; Hirose, Yasujiro; Shibamoto, Yuta

2016-09-01

An effective background field removal technique is desired for more accurate quantitative susceptibility mapping (QSM) prior to dipole inversion. The aim of this study was to evaluate the accuracy of regularization enabled sophisticated harmonic artifact reduction for phase data with varying spherical kernel sizes (REV-SHARP) method using a three-dimensional head phantom and human brain data. The proposed REV-SHARP method used the spherical mean value operation and Tikhonov regularization in the deconvolution process, with varying 2-14mm kernel sizes. The kernel sizes were gradually reduced, similar to the SHARP with varying spherical kernel (VSHARP) method. We determined the relative errors and relationships between the true local field and estimated local field in REV-SHARP, VSHARP, projection onto dipole fields (PDF), and regularization enabled SHARP (RESHARP). Human experiment was also conducted using REV-SHARP, VSHARP, PDF, and RESHARP. The relative errors in the numerical phantom study were 0.386, 0.448, 0.838, and 0.452 for REV-SHARP, VSHARP, PDF, and RESHARP. REV-SHARP result exhibited the highest correlation between the true local field and estimated local field. The linear regression slopes were 1.005, 1.124, 0.988, and 0.536 for REV-SHARP, VSHARP, PDF, and RESHARP in regions of interest on the three-dimensional head phantom. In human experiments, no obvious errors due to artifacts were present in REV-SHARP. The proposed REV-SHARP is a new method combined with variable spherical kernel size and Tikhonov regularization. This technique might make it possible to be more accurate backgroud field removal and help to achive better accuracy of QSM. Copyright © 2016 Elsevier Inc. All rights reserved.

Spatially explicit shallow landslide susceptibility mapping over large areas

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Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region

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Kamp, Ulrich; Growley, Benjamin J.; Khattak, Ghazanfar A.; Owen, Lewis A.

2008-11-01

The Mw 7.6 October 8, 2005 Kashmir earthquake triggered several thousand landslides throughout the Himalaya of northern Pakistan and India. These were concentrated in six different geomorphic-geologic-anthropogenic settings. A spatial database, which included 2252 landslides, was developed and analyzed using ASTER satellite imagery and geographical information system (GIS) technology. A multi-criterion evaluation was applied to determine the significance of event-controlling parameters in triggering the landslides. The parameters included lithology, faults, slope gradient, slope aspect, elevation, land cover, rivers and roads. The results showed four classes of landslide susceptibility. Furthermore, they indicated that lithology had the strongest influence on landsliding, particularly when the rock is highly fractured, such as in shale, slate, clastic sediments, and limestone and dolomite. Moreover, the proximity of the landslides to faults, rivers, and roads was also an important factor in helping to initiate failures. In addition, landslides occurred particularly in moderate elevations on south facing slopes. Shrub land, grassland, and also agricultural land were highly susceptible to failures, while forested slopes had few landslides. One-third of the study area was highly or very highly susceptible to future landsliding and requires immediate mitigation action. The rest of the region had a low or moderate susceptibility to landsliding and remains relatively stable. This study supports the view that (1) earthquake-triggered landslides are concentrated in specific zones associated with event-controlling parameters; and (2) in the western Himalaya deforestation and road construction contributed significantly to landsliding during and shortly after earthquakes.

Effects of Inventory Bias on Landslide Susceptibility Calculations

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Stanley, T. A.; Kirschbaum, D. B.

2017-01-01

Many landslide inventories are known to be biased, especially inventories for large regions such as Oregon's SLIDO or NASA's Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modeling landslide susceptibility with heavily biased inventories.

MAPPING OF FLOOD SUSCEPTIBILITY IN CAMPINA GRANDE COUNTY - PB: A SPATIAL MULTICRITERIA APPROACH

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Priscila Barros Ramalho Alves

Full Text Available Abstract: The social and economic impacts caused by floods in urban areas are diverse and increase as the land becomes gradually impervious. Due to the increasing urbanization of cities, it is necessary to implement a better planning process and optimize the urban spaces management and occupation. Thus, the government needs to gather reliable and useful data for the decision-making process. Therefore, the GIS plays an important role among urban planning instruments. Given the current situation in Campina Grande County, Paraiba State, Brazil - an area continually facing disturbances caused by occasional and concentrated rainfalls - the current study aims to map the areas seen as the most susceptible to floods, by using a MCDA GIS-based model (Multi-Criteria Decision Analysis. There are five quantitative criteria considered in the analysis: slope, altitude, roads with drainage infrastructure, distance from water bodies and land use. It is a pixel by pixel analysis based on predetermined assumptions. Fuzzy functions were developed and overlay operations were performed. The results were consistent with historical records and with previous studies about the county, thus adding reliability to the model, which can be considered a potential management instrument for the case study area, as well as for cities facing similar issues.

An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ

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Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin

2013-04-01

The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.

Assessing the impact of waterborne and dietborne cadmium toxicity on susceptibility risk for rainbow trout

International Nuclear Information System (INIS)

Liao, Chung-Min; Ju, Yun-Ru; Chen, Wei-Yu; Chen, Bo-Ching

2011-01-01

The purpose of this study was to use a risk-based integrated-scale toxicological model to examine the impact of waterborne and dietborne cadmium (Cd) toxicity on rainbow trout (Oncorhynchus mykiss) susceptibility appraised with recent published data. A probabilistic assessment model was performed to estimate Cd susceptibility risk. The dose-response models were constructed based on two endpoints of % Cd in metabolically active pool (MAP) and susceptibility time that causes 50% effect (ST50). We further constructed an elimination-detoxification-recovery scheme to enhance the model predictive ability. We found a 95% probability of % Cd in gill and liver MAP exceeding 47-49% and it was likely (70% probability) to have exceeded 52-55%, but it was unlikely (30% probability) to have exceeded 56-60%. In contrast to gill and liver, gut had a relative lower Cd susceptibility risk (15-17% Cd in MAP) with a longer ST50. We suggested that the proposed probabilistic risk assessment framework can incorporate the elimination-detoxification-recovery scheme to help government based biomonitoring and bioassessment programs to prevent potential aquatic ecosystems and human health consequences. - Research Highlights: → An integrated-scale toxicological model was used to examine the impact of Cd on rainbow trout. → A probabilistic assessment model was performed to estimate Cd susceptibility risk. → An elimination-detoxification-recovery scheme was constructed to enhance the model predictive ability. → Gut had a relative lower Cd susceptibility risk than that in gill and liver.

Assessing the impact of waterborne and dietborne cadmium toxicity on susceptibility risk for rainbow trout

Energy Technology Data Exchange (ETDEWEB)

Liao, Chung-Min, E-mail: cmliao@ntu.edu.tw [Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 10617, Taiwan (China); Ju, Yun-Ru; Chen, Wei-Yu [Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 10617, Taiwan (China); Chen, Bo-Ching [Department of Post-Modern Agriculture, Mingdao University, Changhua, 52345, Taiwan (China)

2011-01-01

The purpose of this study was to use a risk-based integrated-scale toxicological model to examine the impact of waterborne and dietborne cadmium (Cd) toxicity on rainbow trout (Oncorhynchus mykiss) susceptibility appraised with recent published data. A probabilistic assessment model was performed to estimate Cd susceptibility risk. The dose-response models were constructed based on two endpoints of % Cd in metabolically active pool (MAP) and susceptibility time that causes 50% effect (ST50). We further constructed an elimination-detoxification-recovery scheme to enhance the model predictive ability. We found a 95% probability of % Cd in gill and liver MAP exceeding 47-49% and it was likely (70% probability) to have exceeded 52-55%, but it was unlikely (30% probability) to have exceeded 56-60%. In contrast to gill and liver, gut had a relative lower Cd susceptibility risk (15-17% Cd in MAP) with a longer ST50. We suggested that the proposed probabilistic risk assessment framework can incorporate the elimination-detoxification-recovery scheme to help government based biomonitoring and bioassessment programs to prevent potential aquatic ecosystems and human health consequences. - Research Highlights: {yields} An integrated-scale toxicological model was used to examine the impact of Cd on rainbow trout. {yields} A probabilistic assessment model was performed to estimate Cd susceptibility risk. {yields} An elimination-detoxification-recovery scheme was constructed to enhance the model predictive ability. {yields} Gut had a relative lower Cd susceptibility risk than that in gill and liver.

Landslide susceptibility assessment of SE Bartin (West Black Sea region, Turkey by artificial neural networks

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M. Ercanoglu

2005-01-01

Full Text Available Landslides are significant natural hazards in Turkey, second only to earthquakes with respect to economic losses and casualties. The West Black Sea region of Turkey is known as one of the most landslide-prone regions in the country. The work presented in this paper is aimed at evaluating landslide susceptibility in a selected area in the West Black Sea region using Artificial Neural Network (ANN method. A total of 317 landslides were identified and mapped in the area by extensive field work and by use of air photo interpretations to build a landslide inventory map. A landslide database was then derived automatically from the landslide inventory map. To evaluate landslide susceptibility, six input parameters (slope angle, slope aspect, topographical elevation, topographical shape, wetness index, and vegetation index were used. To obtain maps of these parameters, Digital Elevation Model (DEM and ASTER satellite imagery of the study area were used. At the first stage, all data were normalized in [0, 1] interval, and parameter effects on landslide occurrence were expressed using Statistical Index values (Wi. Then, landslide susceptibility analyses were performed using an ANN. Finally, performance of the resulting map and the applied methodology is discussed relative to performance indicators, such as predicted areal extent of landslides and the strength of relation (rij value. Much of the areal extents of the landslides (87.2% were classified as susceptible to landsliding, and rij value of 0.85 showed a high degree of similarity. In addition to these, at the final stage, an independent validation strategy was followed by dividing the landslide data set into two parts and 82.5% of the validation data set was found to be correctly classified as landslide susceptible areas. According to these results, it is concluded that the map produced by the ANN is reliable and methodology applied in the study produced high performance, and satisfactory results.

Introduction: Hazard mapping

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Baum, Rex L.; Miyagi, Toyohiko; Lee, Saro; Trofymchuk, Oleksandr M

2014-01-01

Twenty papers were accepted into the session on landslide hazard mapping for oral presentation. The papers presented susceptibility and hazard analysis based on approaches ranging from field-based assessments to statistically based models to assessments that combined hydromechanical and probabilistic components. Many of the studies have taken advantage of increasing availability of remotely sensed data and nearly all relied on Geographic Information Systems to organize and analyze spatial data. The studies used a range of methods for assessing performance and validating hazard and susceptibility models. A few of the studies presented in this session also included some element of landslide risk assessment. This collection of papers clearly demonstrates that a wide range of approaches can lead to useful assessments of landslide susceptibility and hazard.

Landslide Susceptibility Statistical Methods: A Critical and Systematic Literature Review

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Mihir, Monika; Malamud, Bruce; Rossi, Mauro; Reichenbach, Paola; Ardizzone, Francesca

2014-05-01

Landslide susceptibility assessment, the subject of this systematic review, is aimed at understanding the spatial probability of slope failures under a set of geomorphological and environmental conditions. It is estimated that about 375 landslides that occur globally each year are fatal, with around 4600 people killed per year. Past studies have brought out the increasing cost of landslide damages which primarily can be attributed to human occupation and increased human activities in the vulnerable environments. Many scientists, to evaluate and reduce landslide risk, have made an effort to efficiently map landslide susceptibility using different statistical methods. In this paper, we do a critical and systematic landslide susceptibility literature review, in terms of the different statistical methods used. For each of a broad set of studies reviewed we note: (i) study geography region and areal extent, (ii) landslide types, (iii) inventory type and temporal period covered, (iv) mapping technique (v) thematic variables used (vi) statistical models, (vii) assessment of model skill, (viii) uncertainty assessment methods, (ix) validation methods. We then pulled out broad trends within our review of landslide susceptibility, particularly regarding the statistical methods. We found that the most common statistical methods used in the study of landslide susceptibility include logistic regression, artificial neural network, discriminant analysis and weight of evidence. Although most of the studies we reviewed assessed the model skill, very few assessed model uncertainty. In terms of geographic extent, the largest number of landslide susceptibility zonations were in Turkey, Korea, Spain, Italy and Malaysia. However, there are also many landslides and fatalities in other localities, particularly India, China, Philippines, Nepal and Indonesia, Guatemala, and Pakistan, where there are much fewer landslide susceptibility studies available in the peer-review literature. This

Developing a scientific procedure for community based hazard mapping and risk mitigation

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Verrier, M.

2011-12-01

As an international exchange student from the Geological Sciences Department at San Diego State University (SDSU), I joined the KKN-PPM program at Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia, in July 2011 for 12 days (July 4th to July 16th) of its two month duration (July 4th to August 25th). The KKN-PPM group I was attached was designated 154 and was focused in Plosorejo Village, Karanganyar, Kerjo, Central Java, Indonesia. The mission of KKN-PPM 154 was to survey Plosorejo village for existing landslides, to generate a simple hazard susceptibility map that can be understood by local villagers, and then to begin dissemination of that map into the community. To generate our susceptibility map we first conducted a geological survey of the existing landslides in the field study area, with a focus on determining landslide triggers and gauging areas for susceptibility for future landslides. The methods for gauging susceptibility included lithological observation, the presence of linear cracking, visible loss of structural integrity in structures such as villager homes, as well as collaboration with local residents and with the local rescue and response team. There were three color distinctions used in representing susceptibility which were green, where there is no immediate danger of landslide damage; orange, where transportation routes are at risk of being disrupted by landslides; and red, where imminent landslide potential puts a home in direct danger. The landslide inventory and susceptibility data was compiled into digital mediums such as CorelDraw, ArcGIS and Google Earth. Once a technical map was generated, we presented it to the village leadership for confirmation and modification based on their experience. Finally, we began to use the technical susceptibility map to draft evacuation routes and meeting points in the event of landslides, as well as simple susceptibility maps that can be understood and utilized by local villagers. Landslide mitigation

Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan.

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Jie Dou

Full Text Available This paper assesses the potentiality of certainty factor models (CF for the best suitable causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata Prefecture, Japan. To test the applicability of CF, a landslide inventory map provided by National Research Institute for Earth Science and Disaster Prevention (NIED was split into two subsets: (i 70% of the landslides in the inventory to be used for building the CF based model; (ii 30% of the landslides to be used for the validation purpose. A spatial database with fifteen landslide causative factors was then constructed by processing ALOS satellite images, aerial photos, topographical and geological maps. CF model was then applied to select the best subset from the fifteen factors. Using all fifteen factors and the best subset factors, landslide susceptibility maps were produced using statistical index (SI and logistic regression (LR models. The susceptibility maps were validated and compared using landslide locations in the validation data. The prediction performance of two susceptibility maps was estimated using the Receiver Operating Characteristics (ROC. The result shows that the area under the ROC curve (AUC for the LR model (AUC = 0.817 is slightly higher than those obtained from the SI model (AUC = 0.801. Further, it is noted that the SI and LR models using the best subset outperform the models using the fifteen original factors. Therefore, we conclude that the optimized factor model using CF is more accurate in predicting landslide susceptibility and obtaining a more homogeneous classification map. Our findings acknowledge that in the mountainous regions suffering from data scarcity, it is possible to select key factors related to landslide occurrence based on the CF models in a GIS platform. Hence, the development of a scenario for future planning of risk mitigation is achieved in an efficient manner.

Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan.

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Dou, Jie; Tien Bui, Dieu; Yunus, Ali P; Jia, Kun; Song, Xuan; Revhaug, Inge; Xia, Huan; Zhu, Zhongfan

2015-01-01

This paper assesses the potentiality of certainty factor models (CF) for the best suitable causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata Prefecture, Japan. To test the applicability of CF, a landslide inventory map provided by National Research Institute for Earth Science and Disaster Prevention (NIED) was split into two subsets: (i) 70% of the landslides in the inventory to be used for building the CF based model; (ii) 30% of the landslides to be used for the validation purpose. A spatial database with fifteen landslide causative factors was then constructed by processing ALOS satellite images, aerial photos, topographical and geological maps. CF model was then applied to select the best subset from the fifteen factors. Using all fifteen factors and the best subset factors, landslide susceptibility maps were produced using statistical index (SI) and logistic regression (LR) models. The susceptibility maps were validated and compared using landslide locations in the validation data. The prediction performance of two susceptibility maps was estimated using the Receiver Operating Characteristics (ROC). The result shows that the area under the ROC curve (AUC) for the LR model (AUC = 0.817) is slightly higher than those obtained from the SI model (AUC = 0.801). Further, it is noted that the SI and LR models using the best subset outperform the models using the fifteen original factors. Therefore, we conclude that the optimized factor model using CF is more accurate in predicting landslide susceptibility and obtaining a more homogeneous classification map. Our findings acknowledge that in the mountainous regions suffering from data scarcity, it is possible to select key factors related to landslide occurrence based on the CF models in a GIS platform. Hence, the development of a scenario for future planning of risk mitigation is achieved in an efficient manner.

Landslide susceptibility assessment by using a neuro-fuzzy model: a case study in the Rupestrian heritage rich area of Matera

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Sdao, F.; Lioi, D. S.; Pascale, S.; Caniani, D.; Mancini, I. M.

2013-02-01

The complete assessment of landslide susceptibility needs uniformly distributed detailed information on the territory. This information, which is related to the temporal occurrence of landslide phenomena and their causes, is often fragmented and heterogeneous. The present study evaluates the landslide susceptibility map of the Natural Archaeological Park of Matera (Southern Italy) (Sassi and area Rupestrian Churches sites). The assessment of the degree of "spatial hazard" or "susceptibility" was carried out by the spatial prediction regardless of the return time of the events. The evaluation model for the susceptibility presented in this paper is very focused on the use of innovative techniques of artificial intelligence such as Neural Network, Fuzzy Logic and Neuro-fuzzy Network. The method described in this paper is a novel technique based on a neuro-fuzzy system. It is able to train data like neural network and it is able to shape and control uncertain and complex systems like a fuzzy system. This methodology allows us to derive susceptibility maps of the study area. These data are obtained from thematic maps representing the parameters responsible for the instability of the slopes. The parameters used in the analysis are: plan curvature, elevation (DEM), angle and aspect of the slope, lithology, fracture density, kinematic hazard index of planar and wedge sliding and toppling. Moreover, this method is characterized by the network training which uses a training matrix, consisting of input and output training data, which determine the landslide susceptibility. The neuro-fuzzy method was integrated to a sensitivity analysis in order to overcome the uncertainty linked to the used membership functions. The method was compared to the landslide inventory map and was validated by applying three methods: a ROC (Receiver Operating Characteristic) analysis, a confusion matrix and a SCAI method. The developed neuro-fuzzy method showed a good performance in the

Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

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Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

2018-02-01

As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

Assessments on landslide susceptibility in the Tseng-wen reservoir watershed, Taiwan

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Chen, Yu-Chin; Chen, Yung-Chau; Chen, Wen-Fu

2014-05-01

Typhoon Morakot under the strong influence of southwestern monsoon wind struck Taiwan on 8 August 2009, and dumped record-breaking rains in southern Taiwan. It triggered enormous landslides in mountains and severe flooding in low-lying areas. In addition, it destroyed or damaged houses, agricultural fields, roads, bridges, and other infrastructure facilities, causing massive economic loss and, more tragically, human casualties. In order to evaluate landslide hazard and risk assessment, it is important to understand the potential sites of landslide and their spatial distribution. Multi-temporal satellite images and geo-spatial data are used to build landslide susceptibility map for the post-disaster in the Tseng-wen reservoir watershed in this research. Elevation, slope, aspect, NDVI (normalized differential vegetation index), relief, roughness, distance to river, and distance to road are the considered factors for estimating landslide susceptibility. Maximum hourly rainfall and total rainfall, accompanied with typhoon event, are selected as the trigger factors of landslide events. Logistic regression analysis is adopted as the statistical method to model landslide susceptibility. The assessed susceptibility is represented in 4 levels which are high, high-intermediate, intermediate, and low level, respectively. Landslide spatial distribution can be depicted as a landslide susceptibility map with respect to each considered influence factors for a specified susceptible level. The landslide areas are about 358 ha and 1,485 ha before and after typhoon Morakot. The new landslide area, induced by typhoon Morakot, is as almost 4 times as the landslide area before typhoon Morakot. In addition, there is about 44.56% landslide area elevation ranging from 500m to 1000m and about 57.22% average slope ranging from 30° to 45° of landslide area. Furthermore, the devastating landslides were happened at those sites close to rivers, exposed area, and area with big land cover change

FLOOD SUSCEPTIBILITY ASSESSMENT IN THE NIRAJ BASIN

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SANDA ROŞCA

2012-03-01

Full Text Available Flood susceptibility assessment in the Niraj basin. In the context of global warming and the increasing frequency of extreme weather events, it becomes evident that we have to face natural hazards, such as floods. In the area of Niraj basin this phenomenon is specific both in the spring, because of the snow melting and of the precipitations which come along with the season, and then in the summer because of the torrential precipitations but rarely in autumn and winter. The aim of this paper is to determinate the susceptibility of the zone and obtain a map which will take into consideration the possibility of a flooding. Defining vulnerability can help us understand this type of natural disasters and find the best ways to reduce it. For this purpose we use thematic layers, morphological characteristics (slope and depth fragmentation, hydrological characteristics, geology, pedology (permeability and soil texture, landuse, precipitation data, and human interventions because in this way we have the possibility to use data mining for this purpose. Data mining will allow us to extract new information based on the existing sets of data.The final result will be a thematic map that highlights the areas which are exposed to the flood. Therefore, this map can be used as a support decision for local government or business purposes.

Evaluation of Landslide Mapping Techniques and LiDAR-based Conditioning Factors

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Mahalingam, R.; Olsen, M. J.

2014-12-01

Landslides are a major geohazard, which result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping can help communities to plan and prepare for these damaging events. Mapping landslide susceptible locations using GIS and remote sensing techniques is gaining popularity in the past three decades. These efforts use a wide variety of procedures and consider a wide range of factors. Unfortunately, each study is often completed differently and independently of others. Further, the quality of the datasets used varies in terms of source, data collection, and generation, which can propagate errors or inconsistencies into the resulting output maps. Light detection and ranging (LiDAR) has proved to have higher accuracy in representing the continuous topographic surface, which can help minimize this uncertainty. The primary objectives of this paper are to investigate the applicability and performance of terrain factors in landslide hazard mapping, determine if LiDAR-derived datasets (slope, slope roughness, terrain roughness, stream power index and compound topographic index) can be used for predictive mapping without data representing other common landslide conditioning factors, and evaluate the differences in landslide susceptibility mapping using widely-used statistical approaches. The aforementioned factors were used to produce landslide susceptibility maps for a 140 km2 study area in northwest Oregon using six representative techniques: frequency ratio, weights of evidence, logistic regression, discriminant analysis, artificial neural network, and support vector machine. Most notably, the research showed an advantage in selecting fewer critical conditioning factors. The most reliable factors all could be derived from a single LiDAR DEM, reducing the need for laborious and costly data gathering. Most of the six techniques showed similar statistical results; however, ANN showed less accuracy for predictive mapping. Keywords : Li

Evaluation of landslide susceptibility of Sete Cidades Volcano (S. Miguel Island, Azores

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A. Gomes

2005-01-01

Full Text Available Sete Cidades is an active central volcano with a summit caldera located in the westernmost part of S. Miguel Island (Azores. Since the settlement of the Island, in the 15th century, many landslide events occurred in this volcano, causing extensive damages in buildings and infrastructures. The study of historical records and the observation of new occurrences showed that landslides in the region have been triggered by heavy rainfall periods, earthquakes and erosion. In order to assess landslide susceptibility at Sete Cidades Volcano, landslide scars and associated deposits were mapped through aerial photographs and field surveys. The obtained data were inserted in a GIS to produce a landslide distribution map. It was concluded that the high density landslide areas are related with (1 major scarp faults, (2 the margin of fluvial channels, (3 the sea cliffs and (4 volcanic landforms, namely the caldera wall. About 73% of the mapped events took place in areas where pyroclastic deposits are the dominant lithology and more than 77% occurred where slopes are equal or higher than 20°. These two parameters were integrated and used to generate a preliminary susceptibility map. The incorporation of vulnerability data into the GIS allowed concluding that 30% of dwellings and most of the roads on Sete Cidades Volcano are located in areas where landslide susceptibility is high to very high. Such conclusion should be taken into account for emergency and land use planning.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

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P. Horton

2013-04-01

Full Text Available The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by process-based modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM. The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under http://www.flow-r.org and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws. We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10 m DEM resolution as a good compromise between processing time

The use of magnetic susceptibility measurements to determine ...

African Journals Online (AJOL)

This research work presents a study on the application of magnetic susceptibility measurements and geochemical analysis for mapping or assessing heavy metal pollution in the agricultural soil in road proximity. The research work was also done to check any runoff of heavy metals pollution to the Owabi dam which serves ...

A variational image-based approach to the correction of susceptibility artifacts in the alignment of diffusion weighted and structural MRI.

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Tao, Ran; Fletcher, P Thomas; Gerber, Samuel; Whitaker, Ross T

2009-01-01

This paper presents a method for correcting the geometric and greyscale distortions in diffusion-weighted MRI that result from inhomogeneities in the static magnetic field. These inhomogeneities may due to imperfections in the magnet or to spatial variations in the magnetic susceptibility of the object being imaged--so called susceptibility artifacts. Echo-planar imaging (EPI), used in virtually all diffusion weighted acquisition protocols, assumes a homogeneous static field, which generally does not hold for head MRI. The resulting distortions are significant, sometimes more than ten millimeters. These artifacts impede accurate alignment of diffusion images with structural MRI, and are generally considered an obstacle to the joint analysis of connectivity and structure in head MRI. In principle, susceptibility artifacts can be corrected by acquiring (and applying) a field map. However, as shown in the literature and demonstrated in this paper, field map corrections of susceptibility artifacts are not entirely accurate and reliable, and thus field maps do not produce reliable alignment of EPIs with corresponding structural images. This paper presents a new, image-based method for correcting susceptibility artifacts. The method relies on a variational formulation of the match between an EPI baseline image and a corresponding T2-weighted structural image but also specifically accounts for the physics of susceptibility artifacts. We derive a set of partial differential equations associated with the optimization, describe the numerical methods for solving these equations, and present results that demonstrate the effectiveness of the proposed method compared with field-map correction.

GIS-based debris flow source and runout susceptibility assessment from DEM data – a case study in NW Nicaragua

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J. M. Vilaplana

2007-11-01

Full Text Available In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk

Sinkhole Susceptibility Analysis for Karapinar/konya via Multi Criteria Decision

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Sarı, F.

2017-11-01

Sinkholes are being a natural hazard which threads economic and human life. Sudden occurrence characteristic of sinkholes make it unable to escape. There are a lot of factor that activate sinkholes such as geology, irrigation, land use and human related factors. In Karapınar, Konya, there are over 200 sinkholes and this count is getting increased in recent years. Especially active agricultural lands, decreasing ground water level, extreme irrigation by 55267 water wells increase the risk factor of Karapınar. Nowadays, considering the economic contribution of Karapınar to Turkey economy in the field of agriculture, solar energy fields and thermal reactor which will be planned in next few years, prediction of sinkholes and searching for preventation ways are being more important issue. In this study, sinkhole susceptibility map via AHP was carried out for Karapınar in Konya. Slope, land use, elevation, geology, water wells, distance to roads and settlements criteria are included to determine susceptibility. The weights are calculated with AHP for each criterion and generated susceptibility map is overlapped with existing sinkholes. Suggestions and results are shared for this study.

SINKHOLE SUSCEPTIBILITY ANALYSIS FOR KARAPINAR/KONYA VIA MULTI CRITERIA DECISION

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F. Sarı

2017-11-01

Full Text Available Sinkholes are being a natural hazard which threads economic and human life. Sudden occurrence characteristic of sinkholes make it unable to escape. There are a lot of factor that activate sinkholes such as geology, irrigation, land use and human related factors. In Karapınar, Konya, there are over 200 sinkholes and this count is getting increased in recent years. Especially active agricultural lands, decreasing ground water level, extreme irrigation by 55267 water wells increase the risk factor of Karapınar. Nowadays, considering the economic contribution of Karapınar to Turkey economy in the field of agriculture, solar energy fields and thermal reactor which will be planned in next few years, prediction of sinkholes and searching for preventation ways are being more important issue. In this study, sinkhole susceptibility map via AHP was carried out for Karapınar in Konya. Slope, land use, elevation, geology, water wells, distance to roads and settlements criteria are included to determine susceptibility. The weights are calculated with AHP for each criterion and generated susceptibility map is overlapped with existing sinkholes. Suggestions and results are shared for this study.

Mapping of Mcs30, a new mammary carcinoma susceptibility quantitative trait locus (QTL30 on rat chromosome 12: identification of fry as a candidate Mcs gene.

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Xuefeng Ren

Full Text Available Rat strains differ dramatically in their susceptibility to mammary carcinogenesis. On the assumption that susceptibility genes are conserved across mammalian species and hence inform human carcinogenesis, numerous investigators have used genetic linkage studies in rats to identify genes responsible for differential susceptibility to carcinogenesis. Using a genetic backcross between the resistant Copenhagen (Cop and susceptible Fischer 344 (F344 strains, we mapped a novel mammary carcinoma susceptibility (Mcs30 locus to the centromeric region on chromosome 12 (LOD score of ∼8.6 at the D12Rat59 marker. The Mcs30 locus comprises approximately 12 Mbp on the long arm of rat RNO12 whose synteny is conserved on human chromosome 13q12 to 13q13. After analyzing numerous genes comprising this locus, we identified Fry, the rat ortholog of the furry gene of Drosophila melanogaster, as a candidate Mcs gene. We cloned and determined the complete nucleotide sequence of the 13 kbp Fry mRNA. Sequence analysis indicated that the Fry gene was highly conserved across evolution, with 90% similarity of the predicted amino acid sequence among eutherian mammals. Comparison of the Fry sequence in the Cop and F344 strains identified two non-synonymous single nucleotide polymorphisms (SNPs, one of which creates a putative, de novo phosphorylation site. Further analysis showed that the expression of the Fry gene is reduced in a majority of rat mammary tumors. Our results also suggested that FRY activity was reduced in human breast carcinoma cell lines as a result of reduced levels or mutation. This study is the first to identify the Fry gene as a candidate Mcs gene. Our data suggest that the SNPs within the Fry gene contribute to the genetic susceptibility of the F344 rat strain to mammary carcinogenesis. These results provide the foundation for analyzing the role of the human FRY gene in cancer susceptibility and progression.

Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas

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Chen Cao

2016-09-01

Full Text Available This study focused on producing flash flood hazard susceptibility maps (FFHSM using frequency ratio (FR and statistical index (SI models in the Xiqu Gully (XQG of Beijing, China. First, a total of 85 flash flood hazard locations (n = 85 were surveyed in the field and plotted using geographic information system (GIS software. Based on the flash flood hazard locations, a flood hazard inventory map was built. Seventy percent (n = 60 of the flooding hazard locations were randomly selected for building the models. The remaining 30% (n = 25 of the flooded hazard locations were used for validation. Considering that the XQG used to be a coal mining area, coalmine caves and subsidence caused by coal mining exist in this catchment, as well as many ground fissures. Thus, this study took the subsidence risk level into consideration for FFHSM. The ten conditioning parameters were elevation, slope, curvature, land use, geology, soil texture, subsidence risk area, stream power index (SPI, topographic wetness index (TWI, and short-term heavy rain. This study also tested different classification schemes for the values for each conditional parameter and checked their impacts on the results. The accuracy of the FFHSM was validated using area under the curve (AUC analysis. Classification accuracies were 86.61%, 83.35%, and 78.52% using frequency ratio (FR-natural breaks, statistical index (SI-natural breaks and FR-manual classification schemes, respectively. Associated prediction accuracies were 83.69%, 81.22%, and 74.23%, respectively. It was found that FR modeling using a natural breaks classification method was more appropriate for generating FFHSM for the Xiqu Gully.

Migraine aura: retracting particle-like waves in weakly susceptible cortex.

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Markus A Dahlem

Full Text Available Cortical spreading depression (SD has been suggested to underlie migraine aura. Despite a precise match in speed, the spatio-temporal patterns of SD observed in animal cortex and aura symptoms mapped to the cortical surface ordinarily differ in aspects of size and shape. We show that this mismatch is reconciled by utilizing that both pattern types bifurcate from an instability point of generic reaction-diffusion models. To classify these spatio-temporal pattern we suggest a susceptibility scale having the value sigma = 1 at the instability point. We predict that human cortex is only weakly susceptible to SD (sigma1, and potentially silent aura occurring below a second bifurcation point at sigma = 0 on the susceptible scale.

Genotyping-by-Sequencing derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat

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Hard red winter wheat parents ‘Harry’ (drought tolerant) and ‘Wesley’ (drought susceptible) was used to develop a recombinant inbred population to identify genomic regions associated with drought and adaptation. To precisely map genomic regions high-density linkage maps are a prerequisite. In this s...

The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

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Saro, Lee; Woo, Jeon Seong; Kwan-Young, Oh; Moung-Jin, Lee

2016-02-01

The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs) followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS). These factors were analysed using artificial neural network (ANN) and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50%) and a test set (50%). A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10%) was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%). Of the weights used in the artificial neural network model, `slope' yielded the highest weight value (1.330), and `aspect' yielded the lowest value (1.000). This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

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Saro Lee

2016-02-01

Full Text Available The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS. These factors were analysed using artificial neural network (ANN and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50% and a test set (50%. A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10% was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%. Of the weights used in the artificial neural network model, ‘slope’ yielded the highest weight value (1.330, and ‘aspect’ yielded the lowest value (1.000. This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

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Bartolini, S.; Cappello, A.; Martí, J.; Del Negro, C.

2013-11-01

One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps (i.e., the spatial probability of a future vent opening given the past eruptive activity of a volcano). This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source geographic information system Quantum GIS, which is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows the selection of an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input data sets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

Joint eigenvector estimation from mutually anisotropic tensors improves susceptibility tensor imaging of the brain, kidney, and heart.

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Dibb, Russell; Liu, Chunlei

2017-06-01

To develop a susceptibility-based MRI technique for probing microstructure and fiber architecture of magnetically anisotropic tissues-such as central nervous system white matter, renal tubules, and myocardial fibers-in three dimensions using susceptibility tensor imaging (STI) tools. STI can probe tissue microstructure, but is limited by reconstruction artifacts because of absent phase information outside the tissue and noise. STI accuracy may be improved by estimating a joint eigenvector from mutually anisotropic susceptibility and relaxation tensors. Gradient-recalled echo image data were simulated using a numerical phantom and acquired from the ex vivo mouse brain, kidney, and heart. Susceptibility tensor data were reconstructed using STI, regularized STI, and the proposed algorithm of mutually anisotropic and joint eigenvector STI (MAJESTI). Fiber map and tractography results from each technique were compared with diffusion tensor data. MAJESTI reduced the estimated susceptibility tensor orientation error by 30% in the phantom, 36% in brain white matter, 40% in the inner medulla of the kidney, and 45% in myocardium. This improved the continuity and consistency of susceptibility-based fiber tractography in each tissue. MAJESTI estimation of the susceptibility tensors yields lower orientation errors for susceptibility-based fiber mapping and tractography in the intact brain, kidney, and heart. Magn Reson Med 77:2331-2346, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Combined rock slope stability and shallow landslide susceptibility assessment of the Jasmund cliff area (Rügen Island, Germany

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A. Günther

2009-05-01

Full Text Available In this contribution we evaluated both the structurally-controlled failure susceptibility of the fractured Cretaceous chalk rocks and the topographically-controlled shallow landslide susceptibility of the overlying glacial sediments for the Jasmund cliff area on Rügen Island, Germany. We employed a combined methodology involving spatially distributed kinematical rock slope failure testing with tectonic fabric data, and both physically- and inventory-based shallow landslide susceptibility analysis. The rock slope failure susceptibility model identifies areas of recent cliff collapses, confirming its value in predicting the locations of future failures. The model reveals that toppling is the most important failure type in the Cretaceous chalk rocks of the area. The shallow landslide susceptibility analysis involves a physically-based slope stability evaluation which utilizes material strength and hydraulic conductivity data, and a bivariate landslide susceptibility analysis exploiting landslide inventory data and thematic information on ground conditioning factors. Both models show reasonable success rates when evaluated with the available inventory data, and an attempt was made to combine the individual models to prepare a map displaying both terrain instability and landslide susceptibility. This combination highlights unstable cliff portions lacking discrete landslide areas as well as cliff sections highly affected by past landslide events. Through a spatial integration of the rock slope failure susceptibility model with the combined shallow landslide assessment we produced a comprehensive landslide susceptibility map for the Jasmund cliff area.

Application of an advanced fuzzy logic model for landslide susceptibility analysis

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Biswajeet Pradhan

2010-09-01

Full Text Available The aim of this study is to evaluate the susceptibility of landslides at Klang valley area, Malaysia, using a Geographic Information System (GIS and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. A data derived model (frequency ratio and a knowledge-derived model (fuzzy operator were combined for landslide susceptibility analysis. The nine factors that influence landslide occurrence were extracted from the database and the frequency ratio coefficient for each factor was computed. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide susceptibility mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (l = 0.8 showed the best accuracy (91% while the case in which the fuzzy algebraic product was applied showed the worst accuracy (79%.

Mapping basin-wide subaquatic slope failure susceptibility as a tool to assess regional seismic and tsunami hazards

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Strasser, Michael; Hilbe, Michael; Anselmetti, Flavio S.

2010-05-01

occurred. Comparison of reconstructed critical stability conditions with the known distribution of landslide deposits reveals minimum and maximum threshold conditions for slopes that failed or remained stable, respectively. The resulting correlations reveal good agreements and suggest that the slope stability model generally succeeds in reproducing past events. The basin-wide mapping of subaquatic slope failure susceptibility through time thus can also be considered as a promising paleoseismologic tool that allows quantification of past earthquake ground shaking intensities. Furthermore, it can be used to assess the present-day slope failure susceptibility allowing for identification of location and estimation of size of future, potentially tsunamigenic subaquatic landslides. The new approach presented in our comprehensive lake study and resulting conceptual ideas can be vital to improve our understanding of larger marine slope instabilities and related seismic and oceanic geohazards along formerly glaciated ocean margins and closed basins worldwide.

Gene expression profiling in susceptible interaction of grapevine with its fungal pathogen Eutypa lata: Extending MapMan ontology for grapevine

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Usadel Björn

2009-08-01

experiments performed with Affymetrix or Operon microarrays. MapMan was first validated on an already published dataset and later used to obtain an overview of transcriptional changes in a susceptible grapevine – Eutypa lata interaction at the time of symptoms development, where we showed that the responsive genes belong to families known to be involved in the plant defence towards fungal infection (PR-proteins, enzymes of the phenylpropanoid pathway.

Positional mapping and candidate gene analysis of the mouse Ccs3 locus that regulates differential susceptibility to carcinogen-induced colorectal cancer.

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Charles Meunier

Full Text Available The Ccs3 locus on mouse chromosome 3 regulates differential susceptibility of A/J (A, susceptible and C57BL/6J (B6, resistant mouse strains to chemically-induced colorectal cancer (CRC. Here, we report the high-resolution positional mapping of the gene underlying the Ccs3 effect. Using phenotype/genotype correlation in a series of 33 AcB/BcA recombinant congenic mouse strains, as well as in groups of backcross populations bearing unique recombinant chromosomes for the interval, and in subcongenic strains, we have delineated the maximum size of the Ccs3 physical interval to a ∼2.15 Mb segment. This interval contains 12 annotated transcripts. Sequencing of positional candidates in A and B6 identified many either low-priority coding changes or non-protein coding variants. We found a unique copy number variant (CNV in intron 15 of the Nfkb1 gene. The CNV consists of two copies of a 54 bp sequence immediately adjacent to the exon 15 splice site, while only one copy is found in CRC-susceptible A. The Nfkb1 protein (p105/p50 expression is much reduced in A tumors compared to normal A colonic epithelium as analyzed by immunohistochemistry. Studies in primary macrophages from A and B6 mice demonstrate a marked differential activation of the NfκB pathway by lipopolysaccharide (kinetics of stimulation and maximum levels of phosphorylated IκBα, with a more robust activation being associated with resistance to CRC. NfκB has been previously implicated in regulating homeostasis and inflammatory response in the intestinal mucosa. The interval contains another positional candidate Slc39a8 that is differentially expressed in A vs B6 colons, and that has recently been associated in CRC tumor aggressiveness in humans.

Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility

Science.gov (United States)

Wang, H. B.; Li, J. W.; Zhou, B.; Yuan, Z. Q.; Chen, Y. P.

2013-03-01

In the last few decades, the development of Geographical Information Systems (GIS) technology has provided a method for the evaluation of landslide susceptibility and hazard. Slope units were found to be appropriate for the fundamental morphological elements in landslide susceptibility evaluation. Following the DEM construction in a loess area susceptible to landslides, the direct-reverse DEM technology was employed to generate 216 slope units in the studied area. After a detailed investigation, the landslide inventory was mapped in which 39 landslides, including paleo-landslides, old landslides and recent landslides, were present. Of the 216 slope units, 123 involved landslides. To analyze the mechanism of these landslides, six environmental factors were selected to evaluate landslide occurrence: slope angle, aspect, the height and shape of the slope, distance to river and human activities. These factors were extracted in terms of the slope unit within the ArcGIS software. The spatial analysis demonstrates that most of the landslides are located on convex slopes at an elevation of 100-150 m with slope angles from 135°-225° and 40°-60°. Landslide occurrence was then checked according to these environmental factors using an artificial neural network with back propagation, optimized by genetic algorithms. A dataset of 120 slope units was chosen for training the neural network model, i.e., 80 units with landslide presence and 40 units without landslide presence. The parameters of genetic algorithms and neural networks were then set: population size of 100, crossover probability of 0.65, mutation probability of 0.01, momentum factor of 0.60, learning rate of 0.7, max learning number of 10 000, and target error of 0.000001. After training on the datasets, the susceptibility of landslides was mapped for the land-use plan and hazard mitigation. Comparing the susceptibility map with landslide inventory, it was noted that the prediction accuracy of landslide occurrence

Mapping of gene expression reveals CYP27A1 as a susceptibility gene for sporadic ALS.

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Frank P Diekstra

Full Text Available Amyotrophic lateral sclerosis (ALS is a progressive, neurodegenerative disease characterized by loss of upper and lower motor neurons. ALS is considered to be a complex trait and genome-wide association studies (GWAS have implicated a few susceptibility loci. However, many more causal loci remain to be discovered. Since it has been shown that genetic variants associated with complex traits are more likely to be eQTLs than frequency-matched variants from GWAS platforms, we conducted a two-stage genome-wide screening for eQTLs associated with ALS. In addition, we applied an eQTL analysis to finemap association loci. Expression profiles using peripheral blood of 323 sporadic ALS patients and 413 controls were mapped to genome-wide genotyping data. Subsequently, data from a two-stage GWAS (3,568 patients and 10,163 controls were used to prioritize eQTLs identified in the first stage (162 ALS, 207 controls. These prioritized eQTLs were carried forward to the second sample with both gene-expression and genotyping data (161 ALS, 206 controls. Replicated eQTL SNPs were then tested for association in the second-stage GWAS data to find SNPs associated with disease, that survived correction for multiple testing. We thus identified twelve cis eQTLs with nominally significant associations in the second-stage GWAS data. Eight SNP-transcript pairs of highest significance (lowest p = 1.27 × 10(-51 withstood multiple-testing correction in the second stage and modulated CYP27A1 gene expression. Additionally, we show that C9orf72 appears to be the only gene in the 9p21.2 locus that is regulated in cis, showing the potential of this approach in identifying causative genes in association loci in ALS. This study has identified candidate genes for sporadic ALS, most notably CYP27A1. Mutations in CYP27A1 are causal to cerebrotendinous xanthomatosis which can present as a clinical mimic of ALS with progressive upper motor neuron loss, making it a plausible

Challenges to mapping the health risk of hepatitis A virus infection

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Wiersma Steven T

2011-10-01

Full Text Available Abstract Background World maps are among the most effective ways to convey public health messages such as recommended vaccinations, but creating a useful and valid map requires careful deliberation. The changing epidemiology of hepatitis A virus (HAV in many world regions heightens the need for up-to-date risk maps. HAV infection is usually asymptomatic in children, so low-income areas with high incidence rates usually have a low burden of disease. In higher-income areas, many adults remain susceptible to the virus and, if infected, often experience severe disease. Results Several challenges associated with presenting hepatitis A risk using maps were identified, including the need to decide whether prior infection or continued susceptibility more aptly indicates risk, whether to display incidence or prevalence, how to distinguish between different levels of risk, how to display changes in risk over time, how to present complex information to target audiences, and how to handle missing or obsolete data. Conclusion For future maps to be comparable across place and time, we propose the use of the age at midpoint of population susceptibility as a standard indicator for the level of hepatitis A endemicity within a world region. We also call for the creation of an accessible active database for population-based age-specific HAV seroprevalence and incidence studies. Health risk maps for other conditions with rapidly changing epidemiology would benefit from similar strategies.

Spatial agreement of predicted patterns in landslide susceptibility maps

Czech Academy of Sciences Publication Activity Database

Sterlacchini, S.; Ballabio, C.; Blahůt, Jan; Masetti, J.; Sorichetta, A.

2011-01-01

Roč. 125, č. 1 (2011), s. 51-61 ISSN 0169-555X Institutional research plan: CEZ:AV0Z30460519 Keywords : landslide susceptibility * weights of evidence * success rate Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 2.520, year: 2011 http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V93-511TN6P-3&_user=1407143&_coverDate=01%2F01%2F2011&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_acct=C000052620&_version=1&_urlVersion=0&_userid=1407143&md5=d4e3ac0e1295373f2203f99a1aa8e905&searchtype=a

Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

Science.gov (United States)

Hong, H.; Zhu, A. X.

2017-12-01

Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic

Iron-related gene variants and brain iron in multiple sclerosis and healthy individuals

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Jesper Hagemeier

2018-01-01

Full Text Available Brain iron homeostasis is known to be disturbed in multiple sclerosis (MS, yet little is known about the association of common gene variants linked to iron regulation and pathological tissue changes in the brain. In this study, we investigated the association of genetic determinants linked to iron regulation with deep gray matter (GM magnetic susceptibility in both healthy controls (HC and MS patients. Four hundred (400 patients with MS and 150 age- and sex-matched HCs were enrolled and obtained 3 T MRI examination. Three (3 single nucleotide polymorphisms (SNPs associated with iron regulation were genotyped: two SNPs in the human hereditary hemochromatosis protein gene HFE: rs1800562 (C282Y mutation and rs1799945 (H63D mutation, as well as the rs1049296 SNP in the transferrin gene (C2 mutation. The effects of disease and genetic status were studied using quantitative susceptibility mapping (QSM voxel-based analysis (VBA and region-of-interest (ROI analysis of the deep GM. The general linear model framework was used to compare groups. Analyses were corrected for age and sex, and adjusted for false discovery rate. We found moderate increases in susceptibility in the right putamen of participants with the C282Y (+6.1 ppb and H63D (+6.9 ppb gene variants vs. non-carriers, as well as a decrease in thalamic susceptibility of progressive MS patients with the C282Y mutation (left: −5.3 ppb, right: −6.7 ppb, p < 0.05. Female MS patients had lower susceptibility in the caudate (−6.0 ppb and putamen (left: −3.9 ppb, right: −4.6 ppb than men, but only when they had a wild-type allele (p < 0.05. Iron-gene linked increases in putamen susceptibility (in HC and relapsing remitting MS and decreases in thalamus susceptibility (in progressive MS, coupled with apparent sex interactions, indicate that brain iron in healthy and disease states may be influenced by genetic factors.

Increased brain iron deposition is a risk factor for brain atrophy in patients with haemodialysis: a combined study of quantitative susceptibility mapping and whole brain volume analysis.

Science.gov (United States)

Chai, Chao; Zhang, Mengjie; Long, Miaomiao; Chu, Zhiqiang; Wang, Tong; Wang, Lijun; Guo, Yu; Yan, Shuo; Haacke, E Mark; Shen, Wen; Xia, Shuang

2015-08-01

To explore the correlation between increased brain iron deposition and brain atrophy in patients with haemodialysis and their correlation with clinical biomarkers and neuropsychological test. Forty two patients with haemodialysis and forty one age- and gender-matched healthy controls were recruited in this prospective study. 3D whole brain high resolution T1WI and susceptibility weighted imaging were scanned on a 3 T MRI system. The brain volume was analyzed using voxel-based morphometry (VBM) in patients and to compare with that of healthy controls. Quantitative susceptibility mapping was used to measure and compare the susceptibility of different structures between patients and healthy controls. Correlation analysis was used to investigate the relationship between the brain volume, iron deposition and neuropsychological scores. Stepwise multiple regression analysis was used to explore the effect of clinical biomarkers on the brain volumes in patients. Compared with healthy controls, patients with haemodialysis showed decreased volume of bilateral putamen and left insular lobe (All P brain iron deposition is negatively correlated with the decreased volume of bilateral putamen (P brain iron deposition and dialysis duration was risk factors for brain atrophy in patients with haemodialysis. The decreased gray matter volume of the left insular lobe was correlated with neurocognitive impairment.

Evaluation of the influence of source and spatial resolution of DEMs on derivative products used in landslide mapping

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Rubini Mahalingam

2016-11-01

Full Text Available Landslides are a major geohazard, which result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping can help communities plan and prepare for these damaging events. Digital elevation models (DEMs are one of the most important data-sets used in landslide hazard assessment. Despite their frequent use, limited research has been completed to date on how the DEM source and spatial resolution can influence the accuracy of the produced landslide susceptibility maps. The aim of this paper is to analyse the influence of spatial resolutions and source of DEMs on landslide susceptibility mapping. For this purpose, Advanced Spaceborne Thermal Emission and Reflection (ASTER, National Elevation Dataset (NED, and Light Detection and Ranging (LiDAR DEMs were obtained for two study sections of approximately 140 km2 in north-west Oregon. Each DEM was resampled to 10, 30, and 50 m and slope and aspect grids were derived for each resolution. A set of nine spatial databases was constructed using geoinformation science (GIS for each of the spatial resolution and source. Additional factors such as distance to river and fault maps were included. An analytical hierarchical process (AHP, fuzzy logic model, and likelihood ratio-AHP representing qualitative, quantitative, and hybrid landslide mapping techniques were used for generating landslide susceptibility maps. The results from each of the techniques were verified with the Cohen's kappa index, confusion matrix, and a validation index based on agreement with detailed landslide inventory maps. The spatial resolution of 10 m, derived from the LiDAR data-set showed higher predictive accuracy in all the three techniques used for producing landslide susceptibility maps. At a resolution of 10 m, the output maps based on NED and ASTER had higher misclassification compared to the LiDAR-based outputs. Further, the 30-m LiDAR output showed improved results over the 10-m NED and 10-m

Quantum Statistical Mechanics, L-Series and Anabelian Geometry I: Partition Functions

NARCIS (Netherlands)

Marcolli, Matilde; Cornelissen, Gunther

2014-01-01

The zeta function of a number field can be interpreted as the partition function of an associated quantum statistical mechanical (QSM) system, built from abelian class field theory. We introduce a general notion of isomorphism of QSM-systems and prove that it preserves (extremal) KMS equilibrium

Assessing landslide susceptibility by applying fuzzy sets, possibility evidence-based theories

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Ibsen Chivatá Cárdenas

2008-01-01

Full Text Available A landslide susceptibility model was developed for the city of Manizales, Colombia; landslides have been the city’s main environmental problem. Fuzzy sets and possibility and evidence-based theories were used to construct the mo-del due to the set of circumstances and uncertainty involved in the modelling; uncertainty particularly concerned the lack of representative data and the need for systematically coordinating subjective information. Susceptibility and the uncertainty were estimated via data processing; the model contained data concerning mass vulnerability and uncer-tainty. Output data was expressed on a map defined by linguistic categories or uncertain labels as having low, me-dium, high and very high susceptibility; this was considered appropriate for representing susceptibility. A fuzzy spec-trum was developed for classifying susceptibility levels according to perception and expert opinion. The model sho-wed levels of susceptibility in the study area, ranging from low to high susceptibility (medium susceptibility being mo-re frequent. This article shows the details concerning systematic data processing by presenting theories and tools regarding uncertainty. The concept of fuzzy parameters is introduced; this is useful in modelling phenomena regar-ding uncertainty, complexity and nonlinear performance, showing that susceptibility modelling can be feasible. The paper also shows the great convenience of incorporating uncertainty into modelling and decision-making. However, quantifying susceptibility is not suitable when modelling identified uncertainty because incorporating model output information cannot be reduced into exact or real numerical quantities when the nature of the variables is particularly uncertain. The latter concept is applicable to risk assessment.

In vivo rapid field map measurement and shimming

International Nuclear Information System (INIS)

Kanayama, Shoichi; Kassai, Yoshimori; Kondo, Masafumi; Kuhara, Shigehide; Satoh, Kozo; Seo, Yasutsugu.

1992-01-01

MR imaging and MR spectroscopy need a homogeneous static magnetic field. The static field characteristics are determined by the magnet's homogeneity, the set-up conditions, and the magnetic suspectibility of the subject itself. The field inhomogeneity is usually minimized only once when the apparatus is installed. However, field distortions arising from the magnetic susceptibility differ with each subject and region. To overcome this problem, in vivo shimming can be carried out to improve the homogeneity. The procedures are too lengthy when applying the conventional shimming techniques in vivo. We have developed a new field map measurement technique using a double gradient-recalled echo phase mapping. The values of the currents for the 13-channel shim coils are derived by least squares fitting to the field map and automatically applied to the shim coils. The proposed technique can rapidly and accurately measure the field map in vivo and correct the field inhomogeneity. The results show that this technique improves the homogeneity, especially in regions having a simple field distribution. However, local sharp field distortions which can not be practically corrected by shimming occur near the eyes, ears, heart, etc. due to abrupt susceptibility changes. (author)

Mapping the genes for susceptibility and response to Leishmania tropica in mouse

Czech Academy of Sciences Publication Activity Database

Sohrabi, Yahya; Havelková, Helena; Kobets, Tetyana; Šíma, Matyáš; Volkova, Valeriya; Grekov, Igor; Jarošíková, T.; Kurey, Irina; Vojtíšková, Jarmila; Svobodová, M.; Demant, P.; Lipoldová, Marie

2013-01-01

Roč. 7, č. 7 (2013), s. 1-17 ISSN 1935-2735 R&D Projects: GA ČR GA310/08/1697; GA MŠk LH12049 Institutional support: RVO:68378050 Keywords : Leishmania tropica * gene controlling susceptibility * host-parasite interactions * leishmaniasis Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.489, year: 2013

Susceptibility analysis of landslide in Chittagong City Corporation Area, Bangladesh

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Sourav Das

2015-06-01

Full Text Available In Chittagong city, landslide phenomena is the most burning issue which causes great problems to the life and properties and it is increasing day by day and becoming one of the main problems of city life. On 11 June 2007, a massive landslide happened in Chittagong City Corporation (CCC area, a large number of foothill settlements and slums were demolished; more than 90 people died and huge resource destruction took place. It is therefore essential to analyze the landslide susceptibility for CCC area to prepare mitigation strategies as well as assessing the impacts of climate change. To assess community susceptibility of landslide hazard, a landslide susceptibility index map has been prepared using analytical hierarchy process (AHP model based on geographic information system (GIS and remote sensing (RS and its susceptibility is analyzed through community vulnerability assessment tool (CVAT. The major findings of the research are 27% of total CCC area which is susceptible to landslide hazard and whereas 6.5 sq.km areas are found very highly susceptible. The landslide susceptible areas of CCC have also been analyzed in respect of physical, social, economic, environmental and critical facilities and it is found that the overall CCC area is highly susceptible to landslide hazard. So the findings of the research can be utilized to prioritize risk mitigation investments, measures to strengthen the emergency preparedness and response mechanisms for reducing the losses and damages due to future landslide events. DOI: http://dx.doi.org/10.3126/ije.v4i2.12635 International Journal of Environment Vol.4(2 2015: 157-181

High Frequency of Interactions between Lung Cancer Susceptibility Genes in the Mouse : Mapping of Sluc5 to Sluc14

NARCIS (Netherlands)

Fijneman, Remond J.A.; Jansen, Ritsert C.; Valk, Martin A. van der; Demant, Peter

1998-01-01

Although several genes that cause monogenic familial cancer syndromes have been identified, susceptibility to sporadic cancer remains unresolved. Animal experiments have demonstrated multigenic control of tumor susceptibility. Recently, we described four mouse lung cancer susceptibility (Sluc) loci,

Ancestry-shift refinement mapping of the C6orf97-ESR1 breast cancer susceptibility locus.

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Simon N Stacey

2010-07-01

Full Text Available We used an approach that we term ancestry-shift refinement mapping to investigate an association, originally discovered in a GWAS of a Chinese population, between rs2046210[T] and breast cancer susceptibility. The locus is on 6q25.1 in proximity to the C6orf97 and estrogen receptor alpha (ESR1 genes. We identified a panel of SNPs that are correlated with rs2046210 in Chinese, but not necessarily so in other ancestral populations, and genotyped them in breast cancer case:control samples of Asian, European, and African origin, a total of 10,176 cases and 13,286 controls. We found that rs2046210[T] does not confer substantial risk of breast cancer in Europeans and Africans (OR = 1.04, P = 0.099, and OR = 0.98, P = 0.77, respectively. Rather, in those ancestries, an association signal arises from a group of less common SNPs typified by rs9397435. The rs9397435[G] allele was found to confer risk of breast cancer in European (OR = 1.15, P = 1.2 x 10(-3, African (OR = 1.35, P = 0.014, and Asian (OR = 1.23, P = 2.9 x 10(-4 population samples. Combined over all ancestries, the OR was 1.19 (P = 3.9 x 10(-7, was without significant heterogeneity between ancestries (P(het = 0.36 and the SNP fully accounted for the association signal in each ancestry. Haplotypes bearing rs9397435[G] are well tagged by rs2046210[T] only in Asians. The rs9397435[G] allele showed associations with both estrogen receptor positive and estrogen receptor negative breast cancer. Using early-draft data from the 1,000 Genomes project, we found that the risk allele of a novel SNP (rs77275268, which is closely correlated with rs9397435, disrupts a partially methylated CpG sequence within a known CTCF binding site. These studies demonstrate that shifting the analysis among ancestral populations can provide valuable resolution in association mapping.

3D and 4D magnetic susceptibility tomography based on complex MR images

Science.gov (United States)

Chen, Zikuan; Calhoun, Vince D

2014-11-11

Magnetic susceptibility is the physical property for T2*-weighted magnetic resonance imaging (T2*MRI). The invention relates to methods for reconstructing an internal distribution (3D map) of magnetic susceptibility values, .chi. (x,y,z), of an object, from 3D T2*MRI phase images, by using Computed Inverse Magnetic Resonance Imaging (CIMRI) tomography. The CIMRI technique solves the inverse problem of the 3D convolution by executing a 3D Total Variation (TV) regularized iterative convolution scheme, using a split Bregman iteration algorithm. The reconstruction of .chi. (x,y,z) can be designed for low-pass, band-pass, and high-pass features by using a convolution kernel that is modified from the standard dipole kernel. Multiple reconstructions can be implemented in parallel, and averaging the reconstructions can suppress noise. 4D dynamic magnetic susceptibility tomography can be implemented by reconstructing a 3D susceptibility volume from a 3D phase volume by performing 3D CIMRI magnetic susceptibility tomography at each snapshot time.

Mapping the nonlinear optical susceptibility by noncollinear second-harmonic generation.

Science.gov (United States)

Larciprete, M C; Bovino, F A; Giardina, M; Belardini, A; Centini, M; Sibilia, C; Bertolotti, M; Passaseo, A; Tasco, V

2009-07-15

We present a method, based on noncollinear second-harmonic generation, to evaluate the nonzero elements of the nonlinear optical susceptibility. At a fixed incidence angle, the generated signal is investigated by varying the polarization state of both fundamental beams. The resulting polarization charts allows us to verify if Kleinman's symmetry rules can be applied to a given material or to retrieve the absolute value of the nonlinear optical tensor terms, from a reference measurement. Experimental measurements obtained from gallium nitride layers are reported. The proposed method does not require an angular scan and thus is useful when the generated signal is strongly affected by sample rotation.

Laboratory Accreditation Bureau (L-A-B)

Science.gov (United States)

2011-03-28

to all Technical Advisors. Must agree with code of conduct, confidentiality and our mission DoD ELAP Program  ISO / IEC 17025 :2005 and DoD QSM...Additional DoD QSM requirements fit well in current 17025 process … just much, much more. Sector Specific. Outcome (L-A-B case)  83

A Hybrid Physical and Maximum-Entropy Landslide Susceptibility Model

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Jerry Davis

2015-06-01

Full Text Available The clear need for accurate landslide susceptibility mapping has led to multiple approaches. Physical models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical methods can include other factors influencing slope stability such as distance to roads, but rely on good landslide inventories. The maximum entropy (MaxEnt model has been widely and successfully used in species distribution mapping, because data on absence are often uncertain. Similarly, knowledge about the absence of landslides is often limited due to mapping scale or methodology. In this paper a hybrid approach is described that combines the physically-based landslide susceptibility model “Stability INdex MAPping” (SINMAP with MaxEnt. This method is tested in a coastal watershed in Pacifica, CA, USA, with a well-documented landslide history including 3 inventories of 154 scars on 1941 imagery, 142 in 1975, and 253 in 1983. Results indicate that SINMAP alone overestimated susceptibility due to insufficient data on root cohesion. Models were compared using SINMAP stability index (SI or slope alone, and SI or slope in combination with other environmental factors: curvature, a 50-m trail buffer, vegetation, and geology. For 1941 and 1975, using slope alone was similar to using SI alone; however in 1983 SI alone creates an Areas Under the receiver operator Curve (AUC of 0.785, compared with 0.749 for slope alone. In maximum-entropy models created using all environmental factors, the stability index (SI from SINMAP represented the greatest contributions in all three years (1941: 48.1%; 1975: 35.3; and 1983: 48%, with AUC of 0.795, 0822, and 0.859, respectively; however; using slope instead of SI created similar overall AUC values, likely due to the combined effect with plan curvature indicating focused hydrologic inputs and vegetation identifying the effect of root cohesion

Rice Yellow Mottle Virus stress responsive genes from susceptible and tolerant rice genotypes

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Siré Christelle

2008-03-01

Full Text Available Abstract Background The effects of viral infection involve concomitant plant gene variations and cellular changes. A simple system is required to assess the complexity of host responses to viral infection. The genome of the Rice yellow mottle virus (RYMV is a single-stranded RNA with a simple organisation. It is the most well-known monocotyledon virus model. Several studies on its biology, structure and phylogeography have provided a suitable background for further genetic studies. 12 rice chromosome sequences are now available and provide strong support for genomic studies, particularly physical mapping and gene identification. Results The present data, obtained through the cDNA-AFLP technique, demonstrate differential responses to RYMV of two different rice cultivars, i.e. susceptible IR64 (Oryza sativa indica, and partially resistant Azucena (O. s. japonica. This RNA profiling provides a new original dataset that will enable us to gain greater insight into the RYMV/rice interaction and the specificity of the host response. Using the SIM4 subroutine, we took the intron/exon structure of the gene into account and mapped 281 RYMV stress responsive (RSR transcripts on 12 rice chromosomes corresponding to 234 RSR genes. We also mapped previously identified deregulated proteins and genes involved in partial resistance and thus constructed the first global physical map of the RYMV/rice interaction. RSR transcripts on rice chromosomes 4 and 10 were found to be not randomly distributed. Seven genes were identified in the susceptible and partially resistant cultivars, and transcripts were colocalized for these seven genes in both cultivars. During virus infection, many concomitant plant gene expression changes may be associated with host changes caused by the infection process, general stress or defence responses. We noted that some genes (e.g. ABC transporters were regulated throughout the kinetics of infection and differentiated susceptible and

Clay mineralogy and magnetic susceptibility of Oxisols in geomorphic surfaces

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Livia Arantes Camargo

2014-06-01

Full Text Available Studies analyzing the variability of clay minerals and magnetic susceptibility provide data for the delineation of site-specific management areas since many of their attributes are important to agronomy and the environment. This study aimed to evaluate the spatial variability of clay minerals, magnetic susceptibility, adsorbed phosphorus and physical attributes in Oxisols of sandstones in different geomorphic surfaces. For that purpose, soil samples were collected every 25 m along a transect located within the area where the geomorphic surfaces were identified and mapped. The transect occupied the central portion of 500 ha, where it was also sampled for density purposes with one sample per six hectares. Soil samples were collected at a depth of 0.0-0.2 m. The results of the physical, chemical, mineralogical and magnetic susceptibility analyses were subjected to statistical and geostatistical analyses. The nature of the clay minerals and magnetic susceptibility was dependent on the variation of the soil parent material. High values of magnetic susceptibility were associated with the presence of maghemite and magnetite of coarse size. The spatial variability of crystallinity and the content of Fe oxides, as well as magnetic susceptibility, were dependent on the age of the geomorphic surfaces. The youngest surface had greater spatial variability of these attributes. The iron (goethite and hematite and aluminum (gibbsite oxides in the youngest geomorphic surface influenced the low values of soil density and high values of total pore volume, micropores and P adsorption. The characterization of the spatial variability of Fe oxides and susceptibility allowed for the delineation of homogeneous areas.

Susceptibility assessment of landslides: A comparison of two GIS-based methods in the region of Al Hoceima (Eastern Rif, Morocco.

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El Fahchouch A. N.

2018-01-01

Full Text Available The evaluation of the degree of susceptibility to landslides has become a major concern in mountainous areas, it is a key component of manager policies efforts in disaster prevention, mitigate risk and manage the consequences. The region of Al Hoceima is one of most mountain regions in Morocco, and is highly exposed landslides events. For this reason, the area was selected in order to determine its susceptibility to landslides using two methods. The purpose of this study is to evaluate and to compare the results of multivariate (logical regression and bivariate (landslide susceptibility methods in Geographical Information System (GIS based landslide susceptibility assessment procedures. In order to achieve this goal, the selected methods were compared by the Seed Cell Area Indexes (SCAI and by the spatial locations of the resultant susceptibility pixels. We found that both of the methods converge in 80% of the area; however, the weighting algorithm in the bivariate technique (landslide susceptibility method had some severe deficiencies, as the resultant hazard classes in overweighed areas did not converge with the factual landslide inventory map. The result of the multivariate technique (logical regression was more sensitive to the different local features of the test zone and it resulted in more accurate and homogeneous susceptibility maps. This information may have direct applications in landslides susceptibility research programs and can assist decision-makers in the implementation of preventive management strategies in the most sensitive areas.

Carcinogen susceptibility is regulated by genome architecture and predicts cancer mutagenesis.

Science.gov (United States)

García-Nieto, Pablo E; Schwartz, Erin K; King, Devin A; Paulsen, Jonas; Collas, Philippe; Herrera, Rafael E; Morrison, Ashby J

2017-10-02

The development of many sporadic cancers is directly initiated by carcinogen exposure. Carcinogens induce malignancies by creating DNA lesions (i.e., adducts) that can result in mutations if left unrepaired. Despite this knowledge, there has been remarkably little investigation into the regulation of susceptibility to acquire DNA lesions. In this study, we present the first quantitative human genome-wide map of DNA lesions induced by ultraviolet (UV) radiation, the ubiquitous carcinogen in sunlight that causes skin cancer. Remarkably, the pattern of carcinogen susceptibility across the genome of primary cells significantly reflects mutation frequency in malignant melanoma. Surprisingly, DNase-accessible euchromatin is protected from UV, while lamina-associated heterochromatin at the nuclear periphery is vulnerable. Many cancer driver genes have an intrinsic increase in carcinogen susceptibility, including the BRAF oncogene that has the highest mutation frequency in melanoma. These findings provide a genome-wide snapshot of DNA injuries at the earliest stage of carcinogenesis. Furthermore, they identify carcinogen susceptibility as an origin of genome instability that is regulated by nuclear architecture and mirrors mutagenesis in cancer. © 2017 The Authors.

Rainfall and earthquake-induced landslide susceptibility assessment using GIS and Artificial Neural Network

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Y. Li

2012-08-01

Full Text Available A GIS-based method for the assessment of landslide susceptibility in a selected area of Qingchuan County in China is proposed by using the back-propagation Artificial Neural Network model (ANN. Landslide inventory was derived from field investigation and aerial photo interpretation. 473 landslides occurred before the Wenchuan earthquake (which were thought as rainfall-induced landslides (RIL in this study, and 885 earthquake-induced landslides (EIL were recorded into the landslide inventory map. To understand the different impacts of rainfall and earthquake on landslide occurrence, we first compared the variations between landslide spatial distribution and conditioning factors. Then, we compared the weight variation of each conditioning factor derived by adjusting ANN structure and factors combination respectively. Last, the weight of each factor derived from the best prediction model was applied to the entire study area to produce landslide susceptibility maps.

Results show that slope gradient has the highest weight for landslide susceptibility mapping for both RIL and EIL. The RIL model built with four different factors (slope gradient, elevation, slope height and distance to the stream shows the best success rate of 93%; the EIL model built with five different factors (slope gradient, elevation, slope height, distance to the stream and distance to the fault has the best success rate of 98%. Furthermore, the EIL data was used to verify the RIL model and the success rate is 92%; the RIL data was used to verify the EIL model and the success rate is 53%.

Genome-wide association study identifies novel breast cancer susceptibility loci

Science.gov (United States)

Easton, Douglas F.; Pooley, Karen A.; Dunning, Alison M.; Pharoah, Paul D. P.; Thompson, Deborah; Ballinger, Dennis G.; Struewing, Jeffery P.; Morrison, Jonathan; Field, Helen; Luben, Robert; Wareham, Nicholas; Ahmed, Shahana; Healey, Catherine S.; Bowman, Richard; Meyer, Kerstin B.; Haiman, Christopher A.; Kolonel, Laurence K.; Henderson, Brian E.; Marchand, Loic Le; Brennan, Paul; Sangrajrang, Suleeporn; Gaborieau, Valerie; Odefrey, Fabrice; Shen, Chen-Yang; Wu, Pei-Ei; Wang, Hui-Chun; Eccles, Diana; Evans, D. Gareth; Peto, Julian; Fletcher, Olivia; Johnson, Nichola; Seal, Sheila; Stratton, Michael R.; Rahman, Nazneen; Chenevix-Trench, Georgia; Bojesen, Stig E.; Nordestgaard, Børge G.; Axelsson, Christen K.; Garcia-Closas, Montserrat; Brinton, Louise; Chanock, Stephen; Lissowska, Jolanta; Peplonska, Beata; Nevanlinna, Heli; Fagerholm, Rainer; Eerola, Hannaleena; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Ahn, Sei-Hyun; Hunter, David J.; Hankinson, Susan E.; Cox, David G.; Hall, Per; Wedren, Sara; Liu, Jianjun; Low, Yen-Ling; Bogdanova, Natalia; Schürmann, Peter; Dörk, Thilo; Tollenaar, Rob A. E. M.; Jacobi, Catharina E.; Devilee, Peter; Klijn, Jan G. M.; Sigurdson, Alice J.; Doody, Michele M.; Alexander, Bruce H.; Zhang, Jinghui; Cox, Angela; Brock, Ian W.; MacPherson, Gordon; Reed, Malcolm W. R.; Couch, Fergus J.; Goode, Ellen L.; Olson, Janet E.; Meijers-Heijboer, Hanne; van den Ouweland, Ans; Uitterlinden, André; Rivadeneira, Fernando; Milne, Roger L.; Ribas, Gloria; Gonzalez-Neira, Anna; Benitez, Javier; Hopper, John L.; McCredie, Margaret; Southey, Melissa; Giles, Graham G.; Schroen, Chris; Justenhoven, Christina; Brauch, Hiltrud; Hamann, Ute; Ko, Yon-Dschun; Spurdle, Amanda B.; Beesley, Jonathan; Chen, Xiaoqing; Mannermaa, Arto; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana; Day, Nicholas E.; Cox, David R.; Ponder, Bruce A. J.; Luccarini, Craig; Conroy, Don; Shah, Mitul; Munday, Hannah; Jordan, Clare; Perkins, Barbara; West, Judy; Redman, Karen; Driver, Kristy; Aghmesheh, Morteza; Amor, David; Andrews, Lesley; Antill, Yoland; Armes, Jane; Armitage, Shane; Arnold, Leanne; Balleine, Rosemary; Begley, Glenn; Beilby, John; Bennett, Ian; Bennett, Barbara; Berry, Geoffrey; Blackburn, Anneke; Brennan, Meagan; Brown, Melissa; Buckley, Michael; Burke, Jo; Butow, Phyllis; Byron, Keith; Callen, David; Campbell, Ian; Chenevix-Trench, Georgia; Clarke, Christine; Colley, Alison; Cotton, Dick; Cui, Jisheng; Culling, Bronwyn; Cummings, Margaret; Dawson, Sarah-Jane; Dixon, Joanne; Dobrovic, Alexander; Dudding, Tracy; Edkins, Ted; Eisenbruch, Maurice; Farshid, Gelareh; Fawcett, Susan; Field, Michael; Firgaira, Frank; Fleming, Jean; Forbes, John; Friedlander, Michael; Gaff, Clara; Gardner, Mac; Gattas, Mike; George, Peter; Giles, Graham; Gill, Grantley; Goldblatt, Jack; Greening, Sian; Grist, Scott; Haan, Eric; Harris, Marion; Hart, Stewart; Hayward, Nick; Hopper, John; Humphrey, Evelyn; Jenkins, Mark; Jones, Alison; Kefford, Rick; Kirk, Judy; Kollias, James; Kovalenko, Sergey; Lakhani, Sunil; Leary, Jennifer; Lim, Jacqueline; Lindeman, Geoff; Lipton, Lara; Lobb, Liz; Maclurcan, Mariette; Mann, Graham; Marsh, Deborah; McCredie, Margaret; McKay, Michael; McLachlan, Sue Anne; Meiser, Bettina; Milne, Roger; Mitchell, Gillian; Newman, Beth; O'Loughlin, Imelda; Osborne, Richard; Peters, Lester; Phillips, Kelly; Price, Melanie; Reeve, Jeanne; Reeve, Tony; Richards, Robert; Rinehart, Gina; Robinson, Bridget; Rudzki, Barney; Salisbury, Elizabeth; Sambrook, Joe; Saunders, Christobel; Scott, Clare; Scott, Elizabeth; Scott, Rodney; Seshadri, Ram; Shelling, Andrew; Southey, Melissa; Spurdle, Amanda; Suthers, Graeme; Taylor, Donna; Tennant, Christopher; Thorne, Heather; Townshend, Sharron; Tucker, Kathy; Tyler, Janet; Venter, Deon; Visvader, Jane; Walpole, Ian; Ward, Robin; Waring, Paul; Warner, Bev; Warren, Graham; Watson, Elizabeth; Williams, Rachael; Wilson, Judy; Winship, Ingrid; Young, Mary Ann; Bowtell, David; Green, Adele; deFazio, Anna; Chenevix-Trench, Georgia; Gertig, Dorota; Webb, Penny

2009-01-01

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2>0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P<10−7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P<0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach. PMID:17529967

Susceptibility tensor imaging and tractography of collagen fibrils in the articular cartilage.

Science.gov (United States)

Wei, Hongjiang; Gibbs, Eric; Zhao, Peida; Wang, Nian; Cofer, Gary P; Zhang, Yuyao; Johnson, G Allan; Liu, Chunlei

2017-11-01

To investigate the B 0 orientation-dependent magnetic susceptibility of collagen fibrils within the articular cartilage and to determine whether susceptibility tensor imaging (STI) can detect the 3D collagen network within cartilage. Multiecho gradient echo datasets (100-μm isotropic resolution) were acquired from fixed porcine articular cartilage specimens at 9.4 T. The susceptibility tensor was calculated using phase images acquired at 12 or 15 different orientations relative to B 0 . The susceptibility anisotropy of the collagen fibril was quantified and diffusion tensor imaging (DTI) was compared against STI. 3D tractography was performed to visualize and track the collagen fibrils with DTI and STI. STI experiments showed the distinct and significant anisotropic magnetic susceptibility of collagen fibrils within the articular cartilage. STI can be used to measure and quantify susceptibility anisotropy maps. Furthermore, STI provides orientation information of the underlying collagen network via 3D tractography. The findings of this study demonstrate that STI can characterize the orientation variation of collagen fibrils where diffusion anisotropy fails. We believe that STI could serve as a sensitive and noninvasive marker to study the collagen fibrils microstructure. Magn Reson Med 78:1683-1690, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Meta-analysis and genome-wide interpretation of genetic susceptibility to drug addiction

Science.gov (United States)

2011-01-01

Background Classical genetic studies provide strong evidence for heritable contributions to susceptibility to developing dependence on addictive substances. Candidate gene and genome-wide association studies (GWAS) have sought genes, chromosomal regions and allelic variants likely to contribute to susceptibility to drug addiction. Results Here, we performed a meta-analysis of addiction candidate gene association studies and GWAS to investigate possible functional mechanisms associated with addiction susceptibility. From meta-data retrieved from 212 publications on candidate gene association studies and 5 GWAS reports, we linked a total of 843 haplotypes to addiction susceptibility. We mapped the SNPs in these haplotypes to functional and regulatory elements in the genome and estimated the magnitude of the contributions of different molecular mechanisms to their effects on addiction susceptibility. In addition to SNPs in coding regions, these data suggest that haplotypes in gene regulatory regions may also contribute to addiction susceptibility. When we compared the lists of genes identified by association studies and those identified by molecular biological studies of drug-regulated genes, we observed significantly higher participation in the same gene interaction networks than expected by chance, despite little overlap between the two gene lists. Conclusions These results appear to offer new insights into the genetic factors underlying drug addiction. PMID:21999673

Landslide temporal analysis and susceptibility assessment as bases for landslide mitigation, Machu Picchu, Peru

Czech Academy of Sciences Publication Activity Database

Klimeš, Jan

2013-01-01

Roč. 70, č. 2 (2013), s. 913-925 ISSN 1866-6280 Institutional research plan: CEZ:AV0Z30460519 Keywords : landslide inventory * landslide frequency * susceptibility map Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 1.572, year: 2013

High-resolution physical map for chromosome 16q12.1-q13, the Blau syndrome locus

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Bonavita Gina

2002-08-01

Full Text Available Abstract Background The Blau syndrome (MIM 186580, an autosomal dominant granulomatous disease, was previously mapped to chromosome 16p12-q21. However, inconsistent physical maps of the region and consequently an unknown order of microsatellite markers, hampered us from further refining the genetic locus for the Blau syndrome. To address this problem, we constructed our own high-resolution physical map for the Blau susceptibility region. Results We generated a high-resolution physical map that provides more than 90% coverage of a refined Blau susceptibility region. The map consists of four contigs of sequence tagged site-based bacterial artificial chromosomes with a total of 124 bacterial artificial chromosomes, and spans approximately 7.5 Mbp; however, three gaps still exist in this map with sizes of 425, 530 and 375 kbp, respectively, estimated from radiation hybrid mapping. Conclusions Our high-resolution map will assist genetic studies of loci in the interval from D16S3080, near D16S409, and D16S408 (16q12.1 to 16q13.

Candidate hippocampal biomarkers of susceptibility and resilience to stress in a rat model of depression

DEFF Research Database (Denmark)

Henningsen, Kim; Palmfeldt, Johan; Christiansen, Sofie Friis

2012-01-01

-scale proteomics was used to map hippocampal protein alterations in different stress states. Membrane proteins were successfully captured by two-phase separation and peptide based proteomics. Using iTRAQ labeling coupled with mass spectrometry, more than 2000 proteins were quantified and 73 proteins were found......Susceptibility to stress plays a crucial role in the development of psychiatric disorders such as unipolar depression and post-traumatic stress disorder. In the present study the chronic mild stress rat model of depression was used to reveal stress-susceptible and stress-resilient rats. Large...... to be differentially expressed. Stress susceptibility was associated with increased expression of a sodium-channel protein (SCN9A) currently investigated as a potential antidepressant target. Differential protein profiling also indicated stress susceptibility to be associated with deficits in synaptic vesicle release...

Geological mapping using fractal technique | Lawal | Nigerian ...

African Journals Online (AJOL)

... in Nigeria) showed good correlation with the geological maps of the areas. The results also indicated that basement rocks can generally be represented by scaling exponents with values ranging between -3.0 and -2.0. Keywords: Fractal, dimension, susceptibility, spectra, scaling exponent. Nigerian Journal of Physics Vol.

An in-depth characterization of the major psoriasis susceptibility locus identifies candidate susceptibility alleles within an HLA-C enhancer element.

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Alex Clop

Full Text Available Psoriasis is an immune-mediated skin disorder that is inherited as a complex genetic trait. Although genome-wide association scans (GWAS have identified 36 disease susceptibility regions, more than 50% of the genetic variance can be attributed to a single Major Histocompatibility Complex (MHC locus, known as PSORS1. Genetic studies indicate that HLA-C is the strongest PSORS1 candidate gene, since markers tagging HLA-Cw*0602 consistently generate the most significant association signals in GWAS. However, it is unclear whether HLA-Cw*0602 is itself the causal PSORS1 allele, especially as the role of SNPs that may affect its expression has not been investigated. Here, we have undertaken an in-depth molecular characterization of the PSORS1 interval, with a view to identifying regulatory variants that may contribute to disease susceptibility. By analysing high-density SNP data, we refined PSORS1 to a 179 kb region encompassing HLA-C and the neighbouring HCG27 pseudogene. We compared multiple MHC sequences spanning this refined locus and identified 144 candidate susceptibility variants, which are unique to chromosomes bearing HLA-Cw*0602. In parallel, we investigated the epigenetic profile of the critical PSORS1 interval and uncovered three enhancer elements likely to be active in T lymphocytes. Finally we showed that nine candidate susceptibility SNPs map within a HLA-C enhancer and that three of these variants co-localise with binding sites for immune-related transcription factors. These data indicate that SNPs affecting HLA-Cw*0602 expression are likely to contribute to psoriasis susceptibility and highlight the importance of integrating multiple experimental approaches in the investigation of complex genomic regions such as the MHC.

A comparison between univariate probabilistic and multivariate (logistic regression) methods for landslide susceptibility analysis: the example of the Febbraro valley (Northern Alps, Italy)

Science.gov (United States)

Rossi, M.; Apuani, T.; Felletti, F.

2009-04-01

The aim of this paper is to compare the results of two statistical methods for landslide susceptibility analysis: 1) univariate probabilistic method based on landslide susceptibility index, 2) multivariate method (logistic regression). The study area is the Febbraro valley, located in the central Italian Alps, where different types of metamorphic rocks croup out. On the eastern part of the studied basin a quaternary cover represented by colluvial and secondarily, by glacial deposits, is dominant. In this study 110 earth flows, mainly located toward NE portion of the catchment, were analyzed. They involve only the colluvial deposits and their extension mainly ranges from 36 to 3173 m2. Both statistical methods require to establish a spatial database, in which each landslide is described by several parameters that can be assigned using a main scarp central point of landslide. The spatial database is constructed using a Geographical Information System (GIS). Each landslide is described by several parameters corresponding to the value of main scarp central point of the landslide. Based on bibliographic review a total of 15 predisposing factors were utilized. The width of the intervals, in which the maps of the predisposing factors have to be reclassified, has been defined assuming constant intervals to: elevation (100 m), slope (5 °), solar radiation (0.1 MJ/cm2/year), profile curvature (1.2 1/m), tangential curvature (2.2 1/m), drainage density (0.5), lineament density (0.00126). For the other parameters have been used the results of the probability-probability plots analysis and the statistical indexes of landslides site. In particular slope length (0 ÷ 2, 2 ÷ 5, 5 ÷ 10, 10 ÷ 20, 20 ÷ 35, 35 ÷ 260), accumulation flow (0 ÷ 1, 1 ÷ 2, 2 ÷ 5, 5 ÷ 12, 12 ÷ 60, 60 ÷27265), Topographic Wetness Index 0 ÷ 0.74, 0.74 ÷ 1.94, 1.94 ÷ 2.62, 2.62 ÷ 3.48, 3.48 ÷ 6,00, 6.00 ÷ 9.44), Stream Power Index (0 ÷ 0.64, 0.64 ÷ 1.28, 1.28 ÷ 1.81, 1.81 ÷ 4.20, 4.20 ÷ 9

Shallow Landslide Susceptibility Modeling Using the Data Mining Models Artificial Neural Network and Boosted Tree

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Hyun-Joo Oh

2017-09-01

Full Text Available The main purpose of this paper is to present some potential applications of sophisticated data mining techniques, such as artificial neural network (ANN and boosted tree (BT, for landslide susceptibility modeling in the Yongin area, Korea. Initially, landslide inventory was detected from visual interpretation using digital aerial photographic maps with a high resolution of 50 cm taken before and after the occurrence of landslides. The debris flows were randomly divided into two groups: training and validation sets with a 50:50 proportion. Additionally, 18 environmental factors related to landslide occurrence were derived from the topography, soil, and forest maps. Subsequently, the data mining techniques were applied to identify the influence of environmental factors on landslide occurrence of the training set and assess landslide susceptibility. Finally, the landslide susceptibility indexes from ANN and BT were compared with a validation set using a receiver operating characteristics curve. The slope gradient, topographic wetness index, and timber age appear to be important factors in landslide occurrence from both models. The validation result of ANN and BT showed 82.25% and 90.79%, which had reasonably good performance. The study shows the benefit of selecting optimal data mining techniques in landslide susceptibility modeling. This approach could be used as a guideline for choosing environmental factors on landslide occurrence and add influencing factors into landslide monitoring systems. Furthermore, this method can rank landslide susceptibility in urban areas, thus providing helpful information when selecting a landslide monitoring site and planning land-use.

Outlining precision boundaries among areas with different variability standards using magnetic susceptibility and geomorphic surfaces

OpenAIRE

Matias,Sammy S. R.; Marques Júnior,José; Siqueira,Diego S.; Pereira,Gener T.

2014-01-01

There is an increasing demand for detailed maps that represent in a simplified way the knowledge of the variability of a particular area or region maps. The objective was to outline precision boundaries among areas with different accuracy variability standards using magnetic susceptibility and geomorphic surfaces. The study was conducted in an area of 110 ha, which identified three compartment landscapes based on the geomorphic surfaces model. To determinate pH, organic matter, phosphorus, po...

Landslide susceptibility and risk assessment: specificities for road networks

Science.gov (United States)

Pellicani, Roberta; Argentiero, Ilenia; Parisi, Alessandro; Spilotro, Giuseppe

2017-04-01

A regional-scale assessment of landslide susceptibility and risk along the main road corridors crossing the provincial territory of Matera (Basilicata Region, Southern Italy) was carried out. The entire provincial road network extends for about 1,320 km through a territory, of which represents the main connection infrastructure among thirty-one municipalities due to the lack of an efficient integrated transportation system through the whole regional territory. For this reason, the strategic importance of these roads consists in their uniqueness in connecting every urban center with the socio-economic surrounding context. These roads and their vehicular traffic are continuously exposed to instability processes (about the 40% of the total length is disrupted by landslides), characterized both by high intensity and low frequency and by low intensity and high frequency. This last typology, consisting in small shallow landslides, is particularly hazardous for the roads since it is widespread along the road network, its occurrence is connected to rainfalls and determines high vulnerability conditions for the road in terms of interruption of vehicular traffic. A GIS-based heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area, by using a polynomial function of eight predisposing factors, weighted according to their influence on the landslide phenomena, recognized and collected in an inventory. Susceptibility associated to small shallow phenomena was assessed by using a polynomial function of specific factors, such as slope angle and aspect, lithological outcrops, rainfalls, etc. In absence of detailed input data, the spatial distribution of landslide risk along the road corridors was assessed and mapped using a qualitative hazard-consequence matrix approach, by which risk is obtained by combining hazard categories with consequence classes pairwise in a two-dimensional table or matrix. Landslide

Groundwater Vulnerability Map for South Africa | Musekiwa | South ...

African Journals Online (AJOL)

Vulnerability of groundwater is a relative, non-measurable and dimensionless property which is based on the concept that some land areas are more vulnerable to groundwater contamination than others. Maps showing groundwater vulnerability assist with the identification of areas more susceptible to contamination than ...

The calcitonin receptor gene is a candidate for regulation of susceptibility to herpes simplex type 1 neuronal infection leading to encephalitis in rat.

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Nada Abdelmagid

Full Text Available Herpes simplex encephalitis (HSE is a fatal infection of the central nervous system (CNS predominantly caused by Herpes simplex virus type 1. Factors regulating the susceptibility to HSE are still largely unknown. To identify host gene(s regulating HSE susceptibility we performed a genome-wide linkage scan in an intercross between the susceptible DA and the resistant PVG rat. We found one major quantitative trait locus (QTL, Hse1, on rat chromosome 4 (confidence interval 24.3-31 Mb; LOD score 29.5 governing disease susceptibility. Fine mapping of Hse1 using recombinants, haplotype mapping and sequencing, as well as expression analysis of all genes in the interval identified the calcitonin receptor gene (Calcr as the main candidate, which also is supported by functional studies. Thus, using unbiased genetic approach variability in Calcr was identified as potentially critical for infection and viral spread to the CNS and subsequent HSE development.

A conserved p38 MAP kinase pathway in Caenorhabditis elegans innate immunity.

Science.gov (United States)

Kim, Dennis H; Feinbaum, Rhonda; Alloing, Geneviève; Emerson, Fred E; Garsin, Danielle A; Inoue, Hideki; Tanaka-Hino, Miho; Hisamoto, Naoki; Matsumoto, Kunihiro; Tan, Man-Wah; Ausubel, Frederick M

2002-07-26

A genetic screen for Caenorhabditis elegans mutants with enhanced susceptibility to killing by Pseudomonas aeruginosa led to the identification of two genes required for pathogen resistance: sek-1, which encodes a mitogen-activated protein (MAP) kinase kinase, and nsy-1, which encodes a MAP kinase kinase kinase. RNA interference assays and biochemical analysis established that a p38 ortholog, pmk-1, functions as the downstream MAP kinase required for pathogen defense. These data suggest that this MAP kinase signaling cassette represents an ancient feature of innate immune responses in evolutionarily diverse species.

Landslide Susceptibility Index Determination Using Aritificial Neural Network

Science.gov (United States)

Kawabata, D.; Bandibas, J.; Urai, M.

2004-12-01

The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic features, rock types and geologic structure are especially important base factors of the landslide occurrence. Generating landslide susceptibility index by defining the relationship between landslide occurrence and that base factors using conventional mathematical and statistical methods is very difficult and inaccurate. This study focuses on generating landslide susceptibility index using artificial neural networks in Southern Japanese Alps. The training data are geomorphic (e.g. altitude, slope and aspect) and geologic parameters (e.g. rock type, distance from geologic boundary and geologic dip-strike angle) and landslides. Artificial neural network structure and training scheme are formulated to generate the index. Data from areas with and without landslide occurrences are used to train the network. The network is trained to output 1 when the input data are from areas with landslides and 0 when no landslide occurred. The trained network generates an output ranging from 0 to 1 reflecting the possibility of landslide occurrence based on the inputted data. Output values nearer to 1 means higher possibility of landslide occurrence. The artificial neural network model is incorporated into the GIS software to generate a landslide susceptibility map.

A major QTL controls susceptibility to spinal curvature in the curveback guppy

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Dreyer Christine

2011-01-01

Full Text Available Abstract Background Understanding the genetic basis of heritable spinal curvature would benefit medicine and aquaculture. Heritable spinal curvature among otherwise healthy children (i.e. Idiopathic Scoliosis and Scheuermann kyphosis accounts for more than 80% of all spinal curvatures and imposes a substantial healthcare cost through bracing, hospitalizations, surgery, and chronic back pain. In aquaculture, the prevalence of heritable spinal curvature can reach as high as 80% of a stock, and thus imposes a substantial cost through production losses. The genetic basis of heritable spinal curvature is unknown and so the objective of this work is to identify quantitative trait loci (QTL affecting heritable spinal curvature in the curveback guppy. Prior work with curveback has demonstrated phenotypic parallels to human idiopathic-type scoliosis, suggesting shared biological pathways for the deformity. Results A major effect QTL that acts in a recessive manner and accounts for curve susceptibility was detected in an initial mapping cross on LG 14. In a second cross, we confirmed this susceptibility locus and fine mapped it to a 5 cM region that explains 82.6% of the total phenotypic variance. Conclusions We identify a major QTL that controls susceptibility to curvature. This locus contains over 100 genes, including MTNR1B, a candidate gene for human idiopathic scoliosis. The identification of genes associated with heritable spinal curvature in the curveback guppy has the potential to elucidate the biological basis of spinal curvature among humans and economically important teleosts.

Comparative assessment of landslide susceptibility. Case study: the Niraj river basin (Transylvania depression, Romania

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RoŞca Sanda

2016-05-01

Full Text Available This study represents a comparison between two independent models used to evaluate landslide susceptibility in Romania: first, the model derived from the Romanian Governmental Decision no. 447/2003 (H.G. 447 and second, the bivariate statistical analysis. Considering the numerous objections to the first approach, which is also imposed by law, the accuracy of the results was analyzed using an alternative method which takes into consideration the reality from the field to a greater extent (the inventory of the existing landslides. The case study is focused on the Niraj catchment area (658 km2, a representative area for frequent landslide occurrence. The H.G. 447 model implies the estimation of the importance of eight factors involved in landslide occurrence: lithology, geomorphology, structure, hydro-climatic factors, hydrogeology, seismicity, forest cover and the anthropogenic factor. A thematic map was generated and analyzed for each one of the eight factors influencing slope instability and a specific coefficient was assigned. The statistical model, based on the bivariate probability analysis, was applied in order to predict the spatial distribution of the susceptibility classes. The probability of landslide occurrence was estimated based on the assumption that the prediction of the spatial distributions of landslides starts from the existing ones. In order to validate the model, the resulting maps were compared with the existing landslide maps: the relative landslide density index (R and the relative operation curve (ROC value were calculated, which indicate that the statistical model emphasizes a better correlation between the susceptibility classes and the active landslides (ROC value 0.972, the causative factors selected being relevant for the applied models.

Analyses of susceptibility to radiation-induced tumors: Prkdc, a candidate modifier of lymphomas

International Nuclear Information System (INIS)

Mori, Nobuko; Okumoto, Masaaki; Nakao, Ren

2003-01-01

BALB/cHeA (BALB/c) mice are susceptible to radiation-induced lymphomas, while STS/A (STS) mice are resistant. To analyze the difference in susceptibility between these two strains of mice, we have performed 3 independent studies: 1) mapping of apoptosis susceptibility gene Rapopl (chromosome 16) and identification of Prkdc as a candidate modifier of apoptosis as well as lymphomas, 2) analysis of congenic lines for Lyr, a gene responsible for the lymphoma resistance of STS mice on chromosome 4, 3) genetic analyses of lymphoma susceptibility using a backcross [(BALB/c x STS)F 1 x STS]. Analysis of Rapopl congenic lines indicated a minor contribution of the STS allele at the Rapopl (Prkdc) locus to the lymphoma resistance of STS mice. On the other hand, homozygous STS alleles at Lyr had a substantial, but less potent, effect on radiation lymphomagenesis. Furthermore, there was no single marker where the potent resistance of the STS mice was achieved with the homozygous STS alleles. These results suggest potential involvement of another loci in the resistance of STS mice. (author)

MAPEAMENTO DAS ÁREAS SUSCETÍVEIS À EROSÃO HÍDRICA NOS MUNICÍPIOS DE CALDAS NOVAS, NOVA AMÉRICA E RIO QUENTE (GO MAPPING THE EROSION SUSCEPTIBLE AREAS OF CALDAS NOVAS, NOVA AMÉRICA AND RIO QUENTE, GOIÁS - BRASIL

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Luiz Fernando Coutinho de Oliveira

2007-09-01

Full Text Available

A importância de mapear as áreas suscetíveis à erosão hídrica nos municípios de Caldas Novas, Nova América e Rio Quente deve-se ao fato de que eles apresentaram os maiores índices de precipitação pluviométrica e pelo potencial que os mesmos representam para o estado de Goiás, principalmente o turístico. Na elaboração desses mapas, estabeleceram-se preliminarmente os planos de informação referentes às classes de solo, à declividade e ao uso do solo através de digitalização, empregando o software SGI/INPE, e a espacialização da intensidade de precipitação com duração de 30 minutos sobre a base cartográfica dos municípios, obtendo assim os mapas temáticos. Através do cruzamento dos mapas temáticos, foram classificadas e mapeadas as áreas suscetíveis à erosão hídrica. A metodologia empregada mostrou-se satisfatória, permitindo gerar os mapas temáticos das áreas suscetíveis à erosão hídrica nos municípios estudados que servirão de orientação para os trabalhos de campo.

PALAVRAS-CHAVE: Erosão; sistema de informação geográfica; conservação do solo.

The importance of mapping the erosion susceptible areas of Caldas Novas, Nova América and Rio Quente is that these municipalities present high rainfall rates and the potential they represent for the Goiás state, mostly for tourism. As a preliminary to elaborate these maps the soil type, slope and use of classes information were planned through digitalization using the SGI/INPE software, and a spatialization of the 30 minutes rainfall intensity over the municipalities cartographic base, obtaining the thematic maps. Through thematic maps crossing, the erosion susceptible areas were classified and mapped. The methodology used was considered satisfactory and generated the thematic

Comparison and validation of shallow landslides susceptibility maps generated by bi-variate and multi-variate linear probabilistic GIS-based techniques. A case study from Ribeira Quente Valley (S. Miguel Island, Azores)

Science.gov (United States)

Marques, R.; Amaral, P.; Zêzere, J. L.; Queiroz, G.; Goulart, C.

2009-04-01

Slope instability research and susceptibility mapping is a fundamental component of hazard assessment and is of extreme importance for risk mitigation, land-use management and emergency planning. Landslide susceptibility zonation has been actively pursued during the last two decades and several methodologies are still being improved. Among all the methods presented in the literature, indirect quantitative probabilistic methods have been extensively used. In this work different linear probabilistic methods, both bi-variate and multi-variate (Informative Value, Fuzzy Logic, Weights of Evidence and Logistic Regression), were used for the computation of the spatial probability of landslide occurrence, using the pixel as mapping unit. The methods used are based on linear relationships between landslides and 9 considered conditioning factors (altimetry, slope angle, exposition, curvature, distance to streams, wetness index, contribution area, lithology and land-use). It was assumed that future landslides will be conditioned by the same factors as past landslides in the study area. The presented work was developed for Ribeira Quente Valley (S. Miguel Island, Azores), a study area of 9,5 km2, mainly composed of volcanic deposits (ash and pumice lapilli) produced by explosive eruptions in Furnas Volcano. This materials associated to the steepness of the slopes (38,9% of the area has slope angles higher than 35°, reaching a maximum of 87,5°), make the area very prone to landslide activity. A total of 1.495 shallow landslides were mapped (at 1:5.000 scale) and included in a GIS database. The total affected area is 401.744 m2 (4,5% of the study area). Most slope movements are translational slides frequently evolving into debris-flows. The landslides are elongated, with maximum length generally equivalent to the slope extent, and their width normally does not exceed 25 m. The failure depth rarely exceeds 1,5 m and the volume is usually smaller than 700 m3. For modelling

A Novel Phytophthora sojae Resistance Rps12 Gene Mapped to a Genomic Region That Contains Several Rps Genes.

Science.gov (United States)

Sahoo, Dipak K; Abeysekara, Nilwala S; Cianzio, Silvia R; Robertson, Alison E; Bhattacharyya, Madan K

2017-01-01

Phytophthora sojae Kaufmann and Gerdemann, which causes Phytophthora root rot, is a widespread pathogen that limits soybean production worldwide. Development of Phytophthora resistant cultivars carrying Phytophthora resistance Rps genes is a cost-effective approach in controlling this disease. For this mapping study of a novel Rps gene, 290 recombinant inbred lines (RILs) (F7 families) were developed by crossing the P. sojae resistant cultivar PI399036 with the P. sojae susceptible AR2 line, and were phenotyped for responses to a mixture of three P. sojae isolates that overcome most of the known Rps genes. Of these 290 RILs, 130 were homozygous resistant, 12 heterzygous and segregating for Phytophthora resistance, and 148 were recessive homozygous and susceptible. From this population, 59 RILs homozygous for Phytophthora sojae resistance and 61 susceptible to a mixture of P. sojae isolates R17 and Val12-11 or P7074 that overcome resistance encoded by known Rps genes mapped to Chromosome 18 were selected for mapping novel Rps gene. A single gene accounted for the 1:1 segregation of resistance and susceptibility among the RILs. The gene encoding the Phytophthora resistance mapped to a 5.8 cM interval between the SSR markers BARCSOYSSR_18_1840 and Sat_064 located in the lower arm of Chromosome 18. The gene is mapped 2.2 cM proximal to the NBSRps4/6-like sequence that was reported to co-segregate with the Phytophthora resistance genes Rps4 and Rps6. The gene is mapped to a highly recombinogenic, gene-rich genomic region carrying several nucleotide binding site-leucine rich repeat (NBS-LRR)-like genes. We named this novel gene as Rps12, which is expected to be an invaluable resource in breeding soybeans for Phytophthora resistance.

A Novel Phytophthora sojae Resistance Rps12 Gene Mapped to a Genomic Region That Contains Several Rps Genes.

Directory of Open Access Journals (Sweden)

Dipak K Sahoo

Full Text Available Phytophthora sojae Kaufmann and Gerdemann, which causes Phytophthora root rot, is a widespread pathogen that limits soybean production worldwide. Development of Phytophthora resistant cultivars carrying Phytophthora resistance Rps genes is a cost-effective approach in controlling this disease. For this mapping study of a novel Rps gene, 290 recombinant inbred lines (RILs (F7 families were developed by crossing the P. sojae resistant cultivar PI399036 with the P. sojae susceptible AR2 line, and were phenotyped for responses to a mixture of three P. sojae isolates that overcome most of the known Rps genes. Of these 290 RILs, 130 were homozygous resistant, 12 heterzygous and segregating for Phytophthora resistance, and 148 were recessive homozygous and susceptible. From this population, 59 RILs homozygous for Phytophthora sojae resistance and 61 susceptible to a mixture of P. sojae isolates R17 and Val12-11 or P7074 that overcome resistance encoded by known Rps genes mapped to Chromosome 18 were selected for mapping novel Rps gene. A single gene accounted for the 1:1 segregation of resistance and susceptibility among the RILs. The gene encoding the Phytophthora resistance mapped to a 5.8 cM interval between the SSR markers BARCSOYSSR_18_1840 and Sat_064 located in the lower arm of Chromosome 18. The gene is mapped 2.2 cM proximal to the NBSRps4/6-like sequence that was reported to co-segregate with the Phytophthora resistance genes Rps4 and Rps6. The gene is mapped to a highly recombinogenic, gene-rich genomic region carrying several nucleotide binding site-leucine rich repeat (NBS-LRR-like genes. We named this novel gene as Rps12, which is expected to be an invaluable resource in breeding soybeans for Phytophthora resistance.

Evaluating performance of simplified physically based models for shallow landslide susceptibility

Directory of Open Access Journals (Sweden)

G. Formetta

2016-11-01

Full Text Available Rainfall-induced shallow landslides can lead to loss of life and significant damage to private and public properties, transportation systems, etc. Predicting locations that might be susceptible to shallow landslides is a complex task and involves many disciplines: hydrology, geotechnical science, geology, hydrogeology, geomorphology, and statistics. Two main approaches are commonly used: statistical or physically based models. Reliable model applications involve automatic parameter calibration, objective quantification of the quality of susceptibility maps, and model sensitivity analyses. This paper presents a methodology to systemically and objectively calibrate, verify, and compare different models and model performance indicators in order to identify and select the models whose behavior is the most reliable for particular case studies.The procedure was implemented in a package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslide susceptibility analysis (M1, M2, and M3 and a component for model verification. It computes eight goodness-of-fit indices by comparing pixel-by-pixel model results and measurement data. The integration of the package in NewAge-JGrass uses other components, such as geographic information system tools, to manage input–output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy along the Salerno–Reggio Calabria highway, between Cosenza and Altilia. The area is extensively subject to rainfall-induced shallow landslides mainly because of its complex geology and climatology. The analysis was carried out considering all the combinations of the eight optimized indices and the three models. Parameter calibration, verification, and model performance assessment were performed by a comparison with a detailed landslide

Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed.

Science.gov (United States)

Altaf, Sadaff; Meraj, Gowhar; Romshoo, Shakil Ahmad

2014-12-01

Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area.

Climate change induced lanslide hazard mapping over Greece- A case study in Pelion Mountain (SE Thessaly, Central Greece)

Science.gov (United States)

Angelitsa, Varvara; Loupasakis, Constantinos; Anagnwstopoulou, Christina

2015-04-01

Landslides, as a major type of geological hazard, represent one of the natural events that occur most frequently worldwide after hydro-meteorological events. Landslides occur when the stability of a slope changes due to a number of factors, such as the steep terrain and prolonged precipitation. Identification of landslides and compilation of landslide susceptibility, hazard and risk maps are very important issues for the public authorities providing substantial information regarding, the strategic planning and management of the land-use. Although landslides cannot be predicted accurately, many attempts have been made to compile these maps. Important factors for the the compilation of reliable maps are the quality and the amount of available data and the selection of the best method for the analysis. Numerous studies and publications providing landslide susceptibility,hazard and risk maps, for different regions of Greece, have completed up to now. Their common characteristic is that they are static, taking into account parameters like geology, mean annual precipitaion, slope, aspect, distance from roads, faults and drainage network, soil capability, land use etc., without introducing the dimension of time. The current study focuses on the Pelion Mountain, which is located at the southeastern part of Thessaly in Central Greece; aiming to compile "dynamic" susceptibility and hazard maps depending on climate changes. For this purpose, past and future precipipation data from regional climate models (RCMs) datasets are introduced as input parameters for the compilation of "dynamic" landslide hazard maps. Moreover, land motion mapping data produced by Persistent Scatterer Interferometry (PSI) are used for the validation of the landslide occurrence during the period from June 1992 to December 2003 and as a result for the calibration of the mapping procedure. The PSI data can be applied at a regional scale as support for land motion mapping and at local scale for the

Simultaneous MR quantification of hepatic fat content, fatty acid composition, transverse relaxation time and magnetic susceptibility for the diagnosis of non-alcoholic steatohepatitis.

Science.gov (United States)

Leporq, B; Lambert, S A; Ronot, M; Vilgrain, V; Van Beers, B E

2017-10-01

Non-alcoholic steatohepatitis (NASH) is characterized at histology by steatosis, hepatocyte ballooning and inflammatory infiltrates, with or without fibrosis. Although diamagnetic material in fibrosis and inflammation can be detected with quantitative susceptibility imaging, fatty acid composition changes in NASH relative to simple steatosis have also been reported. Therefore, our aim was to develop a single magnetic resonance (MR) acquisition and post-processing scheme for the diagnosis of steatohepatitis by the simultaneous quantification of hepatic fat content, fatty acid composition, T 2 * transverse relaxation time and magnetic susceptibility in patients with non-alcoholic fatty liver disease. MR acquisition was performed at 3.0 T using a three-dimensional, multi-echo, spoiled gradient echo sequence. Phase images were unwrapped to compute the B 0 field inhomogeneity (ΔB 0 ) map. The ΔB 0 -demodulated real part images were used for fat-water separation, T 2 * and fatty acid composition quantification. The external and internal fields were separated with the projection onto dipole field method. Susceptibility maps were obtained after dipole inversion from the internal field map with single-orientation Bayesian regularization including spatial priors. Method validation was performed in 32 patients with biopsy-proven, non-alcoholic fatty liver disease from which 12 had simple steatosis and 20 NASH. Liver fat fraction and T 2 * did not change significantly between patients with simple steatosis and NASH. In contrast, the saturated fatty acid fraction increased in patients with NASH relative to patients with simple steatosis (48 ± 2% versus 44 ± 4%; p magnetic susceptibility decreased (-0.30 ± 0.27 ppm versus 0.10 ± 0.14 ppm; p magnetic susceptibility as NASH marker was 0.91 (95% CI: 0.79-1.0). Simultaneous MR quantification of fat content, fatty acid composition, T 2 * and magnetic susceptibility is feasible in the liver. Our preliminary results

Mapping genetic variants associated with beta-adrenergic responses in inbred mice.

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Micha Hersch

Full Text Available β-blockers and β-agonists are primarily used to treat cardiovascular diseases. Inter-individual variability in response to both drug classes is well recognized, yet the identity and relative contribution of the genetic players involved are poorly understood. This work is the first genome-wide association study (GWAS addressing the values and susceptibility of cardiovascular-related traits to a selective β(1-blocker, Atenolol (ate, and a β-agonist, Isoproterenol (iso. The phenotypic dataset consisted of 27 highly heritable traits, each measured across 22 inbred mouse strains and four pharmacological conditions. The genotypic panel comprised 79922 informative SNPs of the mouse HapMap resource. Associations were mapped by Efficient Mixed Model Association (EMMA, a method that corrects for the population structure and genetic relatedness of the various strains. A total of 205 separate genome-wide scans were analyzed. The most significant hits include three candidate loci related to cardiac and body weight, three loci for electrocardiographic (ECG values, two loci for the susceptibility of atrial weight index to iso, four loci for the susceptibility of systolic blood pressure (SBP to perturbations of the β-adrenergic system, and one locus for the responsiveness of QTc (p<10(-8. An additional 60 loci were suggestive for one or the other of the 27 traits, while 46 others were suggestive for one or the other drug effects (p<10(-6. Most hits tagged unexpected regions, yet at least two loci for the susceptibility of SBP to β-adrenergic drugs pointed at members of the hypothalamic-pituitary-thyroid axis. Loci for cardiac-related traits were preferentially enriched in genes expressed in the heart, while 23% of the testable loci were replicated with datasets of the Mouse Phenome Database (MPD. Altogether these data and validation tests indicate that the mapped loci are relevant to the traits and responses studied.

A multi-annual landslide inventory for the assessment of shallow landslide susceptibility - Two test cases in Vorarlberg, Austria

Science.gov (United States)

Zieher, Thomas; Perzl, Frank; Rössel, Monika; Rutzinger, Martin; Meißl, Gertraud; Markart, Gerhard; Geitner, Clemens

2016-04-01

Geomorphological landslide inventories provide crucial input data for any study on the assessment of landslide susceptibility, hazard or risk. Several approaches for assessing landslide susceptibility have been proposed to identify areas particularly vulnerable to this natural hazard. What they have in common is the need for data of observed landslides. Therefore the first step of any study on landslide susceptibility is usually the compilation of a geomorphological landslide inventory using a geographical information system. Recent research has proved the feasibility of orthophoto interpretation for the preparation of an inventory aimed at the delineation of landslides with the use of distinctive signs in the imagery data. In this study a multi-annual landslide inventory focusing on shallow landslides (i.e. translational soil slides of 0-2 m in depth) was compiled for two study areas in Vorarlberg (Austria) from the interpretation of nine orthophoto series. In addition, derivatives of two generations of airborne laser scanning data aided the mapping procedure. Landslide scar areas were delineated on the basis of a high-resolution differential digital terrain model. The derivation of landslide volumes, depths and depth-to-length ratios are discussed. Results show that most mapped landslides meet the definition of a shallow landslide. The inventory therefore provides the data basis for the assessment of shallow landslide susceptibility and allows for the application of various modelling techniques.

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation

Science.gov (United States)

Andlauer, Till F. M.; Buck, Dorothea; Antony, Gisela; Bayas, Antonios; Bechmann, Lukas; Berthele, Achim; Chan, Andrew; Gasperi, Christiane; Gold, Ralf; Graetz, Christiane; Haas, Jürgen; Hecker, Michael; Infante-Duarte, Carmen; Knop, Matthias; Kümpfel, Tania; Limmroth, Volker; Linker, Ralf A.; Loleit, Verena; Luessi, Felix; Meuth, Sven G.; Mühlau, Mark; Nischwitz, Sandra; Paul, Friedemann; Pütz, Michael; Ruck, Tobias; Salmen, Anke; Stangel, Martin; Stellmann, Jan-Patrick; Stürner, Klarissa H.; Tackenberg, Björn; Then Bergh, Florian; Tumani, Hayrettin; Warnke, Clemens; Weber, Frank; Wiendl, Heinz; Wildemann, Brigitte; Zettl, Uwe K.; Ziemann, Ulf; Zipp, Frauke; Arloth, Janine; Weber, Peter; Radivojkov-Blagojevic, Milena; Scheinhardt, Markus O.; Dankowski, Theresa; Bettecken, Thomas; Lichtner, Peter; Czamara, Darina; Carrillo-Roa, Tania; Binder, Elisabeth B.; Berger, Klaus; Bertram, Lars; Franke, Andre; Gieger, Christian; Herms, Stefan; Homuth, Georg; Ising, Marcus; Jöckel, Karl-Heinz; Kacprowski, Tim; Kloiber, Stefan; Laudes, Matthias; Lieb, Wolfgang; Lill, Christina M.; Lucae, Susanne; Meitinger, Thomas; Moebus, Susanne; Müller-Nurasyid, Martina; Nöthen, Markus M.; Petersmann, Astrid; Rawal, Rajesh; Schminke, Ulf; Strauch, Konstantin; Völzke, Henry; Waldenberger, Melanie; Wellmann, Jürgen; Porcu, Eleonora; Mulas, Antonella; Pitzalis, Maristella; Sidore, Carlo; Zara, Ilenia; Cucca, Francesco; Zoledziewska, Magdalena; Ziegler, Andreas; Hemmer, Bernhard; Müller-Myhsok, Bertram

2016-01-01

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis. PMID:27386562

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation.

Science.gov (United States)

Andlauer, Till F M; Buck, Dorothea; Antony, Gisela; Bayas, Antonios; Bechmann, Lukas; Berthele, Achim; Chan, Andrew; Gasperi, Christiane; Gold, Ralf; Graetz, Christiane; Haas, Jürgen; Hecker, Michael; Infante-Duarte, Carmen; Knop, Matthias; Kümpfel, Tania; Limmroth, Volker; Linker, Ralf A; Loleit, Verena; Luessi, Felix; Meuth, Sven G; Mühlau, Mark; Nischwitz, Sandra; Paul, Friedemann; Pütz, Michael; Ruck, Tobias; Salmen, Anke; Stangel, Martin; Stellmann, Jan-Patrick; Stürner, Klarissa H; Tackenberg, Björn; Then Bergh, Florian; Tumani, Hayrettin; Warnke, Clemens; Weber, Frank; Wiendl, Heinz; Wildemann, Brigitte; Zettl, Uwe K; Ziemann, Ulf; Zipp, Frauke; Arloth, Janine; Weber, Peter; Radivojkov-Blagojevic, Milena; Scheinhardt, Markus O; Dankowski, Theresa; Bettecken, Thomas; Lichtner, Peter; Czamara, Darina; Carrillo-Roa, Tania; Binder, Elisabeth B; Berger, Klaus; Bertram, Lars; Franke, Andre; Gieger, Christian; Herms, Stefan; Homuth, Georg; Ising, Marcus; Jöckel, Karl-Heinz; Kacprowski, Tim; Kloiber, Stefan; Laudes, Matthias; Lieb, Wolfgang; Lill, Christina M; Lucae, Susanne; Meitinger, Thomas; Moebus, Susanne; Müller-Nurasyid, Martina; Nöthen, Markus M; Petersmann, Astrid; Rawal, Rajesh; Schminke, Ulf; Strauch, Konstantin; Völzke, Henry; Waldenberger, Melanie; Wellmann, Jürgen; Porcu, Eleonora; Mulas, Antonella; Pitzalis, Maristella; Sidore, Carlo; Zara, Ilenia; Cucca, Francesco; Zoledziewska, Magdalena; Ziegler, Andreas; Hemmer, Bernhard; Müller-Myhsok, Bertram

2016-06-01

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis.

Environmental magnetic methods for detecting and mapping contaminated sediments in lakes

Science.gov (United States)

Boyce, J. I.

2009-05-01

The remediation of contaminated sediments is an urgent environmental priority in the Great Lakes and requires detailed mapping of impacted sediment layer thickness, areal distribution and pollutant levels. Magnetic property measurements of sediment cores from two heavily polluted basins in Lake Ontario (Hamilton Harbour, Frenchman's Bay) show that concentrations of hydrocarbons (PAH) and a number of heavy metals (Pb, As, Ni, Cu, Cr, Zn, Cd, Fe) are strongly correlated with magnetic susceptibility. The magnetic susceptibility contrast between the contaminated sediment and underlying 'pre-colonial' sediments is sufficient to generate a total field anomaly (ca. 2-20 nT) that can be measured with a magnetometer towed above the lake bed. Systematic magnetic surveying (550 line km) of Hamilton Harbour using a towed marine magnetometer clearly identifies a number of well-defined magnetic anomalies that coincide with known accumulations of contaminated lake sediment. When calibrated against in-situ magnetic property measurements, the modeled apparent susceptibility from magnetic survey results can be used to classify the relative contaminant impact levels. The results demonstrate the potential of magnetic property measurements for rapid reconnaissance mapping of large areas of bottom contamination prior to detailed coring and sediment remediation.

Detection and assessment of flood susceptible irrigation networks in Licab, Nueva Ecija, Philippines using LiDAR DTM

Science.gov (United States)

Alberto, R. T.; Hernando, P. J. C.; Tagaca, R. C.; Celestino, A. B.; Palado, G. C.; Camaso, E. E.; Damian, G. B.

2017-09-01

Climate change has wide-ranging effects on the environment and socio-economic and related sectors which includes water resources, agriculture and food security, human health, terrestrial ecosystems, coastal zones and biodiversity. Farmers are under pressure to the changing weather and increasing unpredictable water supply. Because of rainfall deficiencies, artificial application of water has been made through irrigation. Irrigation is a basic determinant of agriculture because its inadequacies are the most powerful constraints on the increase of agricultural production. Irrigation networks are permanent and temporary conduits that supply water to agricultural areas from an irrigation source. Detection of irrigation networks using LiDAR DTM, and flood susceptible assessment of irrigation networks could give baseline information on the development and management of sustainable agriculture. Map Gully Depth (MGD) in Whitebox GAT was used to generate the potential irrigation networks. The extracted MGD was overlaid in ArcGIS as guide in the digitization of potential irrigation networks. A flood hazard map was also used to identify the flood susceptible irrigation networks in the study area. The study was assessed through field validation of points which were generated using random sampling method. Results of the study showed that most of the detected irrigation networks have low to moderate susceptibility to flooding while the rest have high susceptibility to flooding which is due to shifting weather. These irrigation networks may cause flood when it overflows that could also bring huge damage to rice and other agricultural areas.

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

DEFF Research Database (Denmark)

Gaulton, Kyle J; Ferreira, Teresa; Lee, Yeji

2015-01-01

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct...... signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping...... implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele...

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

NARCIS (Netherlands)

K. Gaulton (Kyle); T. Ferreira (Teresa); Y. Lee (Yeji); A. Raimondo (Anne); R. Mägi (Reedik); M.E. Reschen (Michael E.); A. Mahajan (Anubha); A. Locke (Adam); N.W. Rayner (Nigel William); N.R. Robertson (Neil); R.A. Scott (Robert); I. Prokopenko (Inga); L.J. Scott (Laura); T. Green (Todd); T. Sparsø (Thomas); D. Thuillier (Dorothee); L. Yengo (Loic); H. Grallert (Harald); S. Wahl (Simone); M. Frånberg (Mattias); R.J. Strawbridge (Rona); H. Kestler (Hans); H. Chheda (Himanshu); L. Eisele (Lewin); S. Gustafsson (Stefan); V. Steinthorsdottir (Valgerdur); G. Thorleifsson (Gudmar); L. Qi (Lu); L.C. Karssen (Lennart); E.M. van Leeuwen (Elisa); S.M. Willems (Sara); M. Li (Man); H. Chen (Han); C. Fuchsberger (Christian); P. Kwan (Phoenix); C. Ma (Clement); M. Linderman (Michael); Y. Lu (Yingchang); S.K. Thomsen (Soren K.); J.K. Rundle (Jana K.); N.L. Beer (Nicola L.); M. van de Bunt (Martijn); A. Chalisey (Anil); H.M. Kang (Hyun Min); B.F. Voight (Benjamin); G.R. Abecasis (Gonçalo); P. Almgren (Peter); D. Baldassarre (Damiano); B. Balkau (Beverley); R. Benediktsson (Rafn); M. Blüher (Matthias); H. Boeing (Heiner); L.L. Bonnycastle (Lori); E.P. Bottinger (Erwin P.); N.P. Burtt (Noël); J. Carey (Jason); G. Charpentier (Guillaume); P.S. Chines (Peter); M. Cornelis (Marilyn); D.J. Couper (David J.); A. Crenshaw (Andrew); R.M. van Dam (Rob); A.S.F. Doney (Alex); M. Dorkhan (Mozhgan); T. Edkins (Ted); J.G. Eriksson (Johan G.); T. Esko (Tõnu); E. Eury (Elodie); J. Fadista (João); J. Flannick (Jason); P. Fontanillas (Pierre); C.S. Fox (Caroline); P.W. Franks (Paul W.); K. Gertow (Karl); C. Gieger (Christian); B. Gigante (Bruna); R.F. Gottesman (Rebecca); G.B. Grant (George); N. Grarup (Niels); C.J. Groves (Christopher J.); M. Hassinen (Maija); C.T. Have (Christian T.); C. Herder (Christian); O.L. Holmen (Oddgeir); A.B. Hreidarsson (Astradur); S.E. Humphries (Steve E.); D.J. Hunter (David J.); A.U. Jackson (Anne); A. Jonsson (Anna); M.E. Jørgensen (Marit E.); T. Jørgensen (Torben); W.H.L. Kao (Wen); N.D. Kerrison (Nicola D.); L. Kinnunen (Leena); N. Klopp (Norman); A. Kong (Augustine); P. Kovacs (Peter); P. Kraft (Peter); J. Kravic (Jasmina); C. Langford (Cordelia); K. Leander (Karin); L. Liang (Liming); P. Lichtner (Peter); C.M. Lindgren (Cecilia M.); B. Lindholm (Bengt); A. Linneberg (Allan); C.-T. Liu (Ching-Ti); S. Lobbens (Stéphane); J. Luan (Jian'fan); V. Lyssenko (Valeriya); S. Männistö (Satu); O. McLeod (Olga); J. Meyer (Jobst); E. Mihailov (Evelin); G. Mirza (Ghazala); T.W. Mühleisen (Thomas); M. Müller-Nurasyid (Martina); C. Navarro (Carmen); M.M. Nöthen (Markus); N.N. Oskolkov (Nikolay N.); K.R. Owen (Katharine); D. Palli (Domenico); S. Pechlivanis (Sonali); L. Peltonen (Leena Johanna); J.R.B. Perry (John); C.P. Platou (Carl); M. Roden (Michael); D. Ruderfer (Douglas); D. Rybin (Denis); Y.T. Van Der Schouw (Yvonne T.); B. Sennblad (Bengt); G. Sigurosson (Gunnar); A. Stancáková (Alena); D. Steinbach; P. Storm (Petter); K. Strauch (Konstantin); H.M. Stringham (Heather); Q. Sun; B. Thorand (Barbara); E. Tikkanen (Emmi); A. Tönjes (Anke); J. Trakalo (Joseph); E. Tremoli (Elena); T. Tuomi (Tiinamaija); R. Wennauer (Roman); S. Wiltshire (Steven); A.R. Wood (Andrew); E. Zeggini (Eleftheria); I. Dunham (Ian); E. Birney (Ewan); L. Pasquali (Lorenzo); J. Ferrer (Jorge); R.J.F. Loos (Ruth); J. Dupuis (Josée); J.C. Florez (Jose); E.A. Boerwinkle (Eric); J.S. Pankow (James); C.M. van Duijn (Cornelia); E.J.G. Sijbrands (Eric); J.B. Meigs (James B.); F.B. Hu (Frank B.); U. Thorsteinsdottir (Unnur); J-A. Zwart (John-Anker); T.A. Lakka (Timo); R. Rauramaa (Rainer); M. Stumvoll (Michael); N.L. Pedersen (Nancy L.); L. Lind (Lars); S. Keinanen-Kiukaanniemi (Sirkka); E. Korpi-Hyövälti (Eeva); T. Saaristo (Timo); J. Saltevo (Juha); J. Kuusisto (Johanna); M. Laakso (Markku); A. Metspalu (Andres); R. Erbel (Raimund); K.-H. Jöckel (Karl-Heinz); S. Moebus (Susanne); S. Ripatti (Samuli); V. Salomaa (Veikko); E. Ingelsson (Erik); B.O. Boehm (Bernhard); R.N. Bergman (Richard N.); F.S. Collins (Francis S.); K.L. Mohlke (Karen L.); H. Koistinen (Heikki); J. Tuomilehto (Jaakko); K. Hveem (Kristian); I. Njølstad (Inger); P. Deloukas (Panagiotis); P.J. Donnelly (Peter J.); T.M. Frayling (Timothy); A.T. Hattersley (Andrew); U. de Faire (Ulf); A. Hamsten (Anders); T. Illig (Thomas); A. Peters (Annette); S. Cauchi (Stephane); R. Sladek (Rob); P. Froguel (Philippe); T. Hansen (Torben); O. Pedersen (Oluf); A.D. Morris (Andrew); C.N.A. Palmer (Collin N. A.); S. Kathiresan (Sekar); O. Melander (Olle); P.M. Nilsson (Peter M.); L. Groop (Leif); I.E. Barroso (Inês); C. Langenberg (Claudia); N.J. Wareham (Nicholas J.); C.A. O'Callaghan (Christopher A.); A.L. Gloyn (Anna); D. Altshuler (David); M. Boehnke (Michael); T.M. Teslovich (Tanya M.); M.I. McCarthy (Mark); A.P. Morris (Andrew)

2015-01-01

textabstractWe performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

NARCIS (Netherlands)

Gaulton, Kyle J; Ferreira, Teresa; Lee, Yeji; Raimondo, Anne; Mägi, Reedik; Reschen, Michael E; Mahajan, Anubha; Locke, Adam; William Rayner, N; Robertson, Neil; Scott, Robert A; Prokopenko, Inga; Scott, Laura J; Green, Todd; Sparso, Thomas; Thuillier, Dorothee; Yengo, Loic; Grallert, Harald; Wahl, Simone; Frånberg, Mattias; Strawbridge, Rona J; Kestler, Hans; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Li, Man; Chen, Han; Fuchsberger, Christian; Kwan, Phoenix; Ma, Clement; Linderman, Michael; Lu, Yingchang; Thomsen, Soren K; Rundle, Jana K; Beer, Nicola L; van de Bunt, Martijn; Chalisey, Anil; Kang, Hyun Min; Voight, Benjamin F; Abecasis, Gonçalo R; Almgren, Peter; Baldassarre, Damiano; Balkau, Beverley; Benediktsson, Rafn; Blüher, Matthias; Boeing, Heiner; Bonnycastle, Lori L; Bottinger, Erwin P; Burtt, Noël P; Carey, Jason; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Doney, Alex S F; Dorkhan, Mozhgan; Edkins, Sarah; Eriksson, Johan G; Esko, Tonu; Eury, Elodie; Fadista, João; Flannick, Jason; Fontanillas, Pierre; Fox, Caroline; Franks, Paul W; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Gottesman, Omri; Grant, George B; Grarup, Niels; Groves, Christopher J; Hassinen, Maija; Have, Christian T; Herder, Christian; Holmen, Oddgeir L; Hreidarsson, Astradur B; Humphries, Steve E; Hunter, David J; Jackson, Anne U; Jonsson, Anna; Jørgensen, Marit E; Jørgensen, Torben; Kao, Wen-Hong L; Kerrison, Nicola D; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Kovacs, Peter; Kraft, Peter; Kravic, Jasmina; Langford, Cordelia; Leander, Karin; Liang, Liming; Lichtner, Peter; Lindgren, Cecilia M; Lindholm, Eero; Linneberg, Allan; Liu, Ching-Ti; Lobbens, Stéphane; Luan, Jian'an; Lyssenko, Valeriya; Männistö, Satu; McLeod, Olga; Meyer, Julia; Mihailov, Evelin; Mirza, Ghazala; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Navarro, Carmen; Nöthen, Markus M; Oskolkov, Nikolay N; Owen, Katharine R; Palli, Domenico; Pechlivanis, Sonali; Peltonen, Leena; Perry, John R B; Platou, Carl G P; Roden, Michael; Ruderfer, Douglas; Rybin, Denis; van der Schouw, Yvonne T; Sennblad, Bengt; Sigurðsson, Gunnar; Stančáková, Alena; Steinbach, Gerald; Storm, Petter; Strauch, Konstantin; Stringham, Heather M; Sun, Qi; Thorand, Barbara; Tikkanen, Emmi; Tonjes, Anke; Trakalo, Joseph; Tremoli, Elena; Tuomi, Tiinamaija; Wennauer, Roman; Wiltshire, Steven; Wood, Andrew R; Zeggini, Eleftheria; Dunham, Ian; Birney, Ewan; Pasquali, Lorenzo; Ferrer, Jorge; Loos, Ruth J F; Dupuis, Josée; Florez, Jose C; Boerwinkle, Eric; Pankow, James S; van Duijn, Cornelia; Sijbrands, Eric; Meigs, James B; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Lakka, Timo A; Rauramaa, Rainer; Stumvoll, Michael; Pedersen, Nancy L; Lind, Lars; Keinanen-Kiukaanniemi, Sirkka M; Korpi-Hyövälti, Eeva; Saaristo, Timo E; Saltevo, Juha; Kuusisto, Johanna; Laakso, Markku; Metspalu, Andres; Erbel, Raimund; Jöcke, Karl-Heinz; Moebus, Susanne; Ripatti, Samuli; Salomaa, Veikko; Ingelsson, Erik; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Koistinen, Heikki; Tuomilehto, Jaakko; Hveem, Kristian; Njølstad, Inger; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; de Faire, Ulf; Hamsten, Anders; Illig, Thomas; Peters, Annette; Cauchi, Stephane; Sladek, Rob; Froguel, Philippe; Hansen, Torben; Pedersen, Oluf; Morris, Andrew D; Palmer, Collin N A; Kathiresan, Sekar; Melander, Olle; Nilsson, Peter M; Groop, Leif C; Barroso, Inês; Langenberg, Claudia; Wareham, Nicholas J; O'Callaghan, Christopher A; Gloyn, Anna L; Altshuler, David; Boehnke, Michael; Teslovich, Tanya M; McCarthy, Mark I; Morris, Andrew P

2015-01-01

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct

Continuous Real-time Measurements of Vertical Distribution of Magnetic Susceptibility In Soils

Science.gov (United States)

Petrovsky, E.; Hulka, Z.; Kapicka, A.; Magprox Team

Measurements of top-soil magnetic susceptibility are used in approximative outlining polluted areas. However, one of the serious limitations of the method is discrimina- tion between top-soil layers enhanced by atmospherically deposited anthropogenic particles from those dominated by natural particles migrating from magnetically-rich basement rocks. For this purpose, measurements of vertical distribution of magnetic susceptibility along soil profiles is one of the most effective ways in estimating the effect of lithogenic contribution. Up to now, in most cases soil cores have to be mea- sured in laboratory. This method is quite time consuming and does not allow flexible decision about the suitability of the measured site for surface magnetic mapping. In our contribution we will present a new device enabling continuous real-time measure- ments of vertical distribution of magnetic susceptibility directly in field, performed in holes after soil coring. The method is fast, yielding smooth curves (6 data points per 1 mm dept), at least as sensitive as laboratory methods available until now, and at- tached notebook enables direct, on-line control of the lithogenic versus anthropogenic contributions.

Assessing Landslide Characteristics and Developing a Landslide Potential Hazard Map in Rwanda and Uganda Using NASA Earth Observations

Science.gov (United States)

Sinclair, L.; Conner, P.; le Roux, J.; Finley, T.

2015-12-01

The International Emergency Disasters Database indicates that a total of 482 people have been killed and another 27,530 have been affected by landslides in Rwanda and Uganda, although the actual numbers are thought to be much higher. Data for individual countries are poorly tracked, but hotspots for devastating landslides occur throughout Rwanda and Uganda due to the local topography and soil type, intense rainfall events, and deforestation. In spite of this, there has been little research in this region that utilizes satellite imagery to estimate areas susceptible to landslides. This project utilized Landsat 8 Operational Land Imager (OLI) data and Google Earth to identify landslides that occurred within the study area. These landslides were then added to SERVIR's Global Landslide Catalog (GLC). Next, Landsat 8 OLI, the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), and Shuttle Radar Topography Mission Version 2 (SRTM V2) data were used to create a Landslide Susceptibility Map. This was combined with population data from the Socioeconomic Data and Applications Center (SEDAC) to create a Landslide Hazard map. A preliminary assessment of the relative performance of GPM and TRMM in identifying landslide conditions was also performed. The additions to the GLC, the Landslide Susceptibility Map, the Landslide Hazard Map, and the preliminary assessment of satellite rainfall performance will be used by SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for disaster risk management, land use planning, and determining landslide conditions and moisture thresholds.

Reactivation hazard mapping for ancient landslides in West Belgium

Directory of Open Access Journals (Sweden)

O. Dewitte

2006-01-01

Full Text Available Several examples in western Europe have shown that, at least for deep-seated rotational slides, reactivation of formerly slipped masses is a more frequent phenomenon than the occurrence of new landslides, therefore representing a higher hazard. We selected a study area comprised of 13 landslides located in the Flemish Ardennes (West Belgium and predicted the hazard related to scarp retreat. The scarp reactivations were identified from the comparison of DTMs produced for 1952 and 1996. Robust results were obtained with the Gamma operator of a fuzzy set approach and a combination of geomorphic, topographic and land use data. We built first a prediction model from the relations linking the 1952–1996 retreat events to the conditioning parameters of 1952. The prediction rate of the resulting susceptibility map is estimated by a cross-validation procedure. We then applied the statistics of this model to the data of 1996 in order to produce a susceptibility map responding to the present-day conditions. Finally, we estimated the conditional probabilities of occurrence of future reactivations for the period 1996–2036.

A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping

Science.gov (United States)

Crozier, M. J.

2017-10-01

Multiple-occurrence regional landslide events (MORLEs) consist of hundreds to thousands of shallow landslides occurring more or less simultaneously within defined areas, ranging from tens to thousands of square kilometres. While MORLEs can be triggered by rainstorms and earthquakes, this paper is confined to those landslide events triggered by rainstorms. Globally, MORLEs occur in a range of geological settings in areas of moderate to steep slopes subject to intense rainstorms. Individual landslides in rainstorm-triggered events are dominantly small, shallow debris and earth flows, and debris and earth slides involving regolith or weathered bedrock. The model used to characterise these events assumes that energy distribution within the event area is represented on the land surface by a cell structure; with maximum energy expenditure within an identifiable core and rapid dissipation concentrically away from the centre. The version of the model presented here has been developed for rainfall-triggered landslide events. It proposes that rainfall intensity can be used to determine different critical landslide response zones within the cell (referred to as core, middle, and periphery zones). These zones are most readily distinguished by two conditions: the proportion of the slope that fails and the particular type of the slope stability factor that assumes dominance in determining specific sites of landslide occurrence. The latter condition means that the power of any slope stability factor to distinguish between stable and unstable sites varies throughout the affected area in accordance with the landslide response zones within the cell; certain factors critical for determining the location of landslide sites in one part of the event area have little influence in other parts of the event area. The implication is that landslide susceptibility maps (and subsequently derived mitigation measures) based on conventional slope stability factors may have only limited validity

Genetic fine-mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

Science.gov (United States)

Mahajan, Anubha; Locke, Adam; Rayner, N William; Robertson, Neil; Scott, Robert A; Prokopenko, Inga; Scott, Laura J; Green, Todd; Sparso, Thomas; Thuillier, Dorothee; Yengo, Loic; Grallert, Harald; Wahl, Simone; Frånberg, Mattias; Strawbridge, Rona J; Kestler, Hans; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Li, Man; Chen, Han; Fuchsberger, Christian; Kwan, Phoenix; Ma, Clement; Linderman, Michael; Lu, Yingchang; Thomsen, Soren K; Rundle, Jana K; Beer, Nicola L; van de Bunt, Martijn; Chalisey, Anil; Kang, Hyun Min; Voight, Benjamin F; Abecasis, Goncalo R; Almgren, Peter; Baldassarre, Damiano; Balkau, Beverley; Benediktsson, Rafn; Blüher, Matthias; Boeing, Heiner; Bonnycastle, Lori L; Borringer, Erwin P; Burtt, Noël P; Carey, Jason; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Doney, Alex SF; Dorkhan, Mozhgan; Edkins, Sarah; Eriksson, Johan G; Esko, Tonu; Eury, Elodie; Fadista, João; Flannick, Jason; Fontanillas, Pierre; Fox, Caroline; Franks, Paul W; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Gottesman, Omri; Grant, George B; Grarup, Niels; Groves, Christopher J; Hassinen, Maija; Have, Christian T; Herder, Christian; Holmen, Oddgeir L; Hreidarsson, Astradur B; Humphries, Steve E; Hunter, David J; Jackson, Anne U; Jonsson, Anna; Jørgensen, Marit E; Jørgensen, Torben; Kerrison, Nicola D; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Kovacs, Peter; Kraft, Peter; Kravic, Jasmina; Langford, Cordelia; Leander, Karin; Liang, Liming; Lichtner, Peter; Lindgren, Cecilia M; Lindholm, Eero; Linneberg, Allan; Liu, Ching-Ti; Lobbens, Stéphane; Luan, Jian’an; Lyssenko, Valeriya; Männistö, Satu; McLeod, Olga; Meyer, Julia; Mihailov, Evelin; Mirza, Ghazala; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Navarro, Carmen; Nöthen, Markus M; Oskolkov, Nikolay N; Owen, Katharine R; Palli, Domenico; Pechlivanis, Sonali; Perry, John RB; Platou, Carl GP; Roden, Michael; Ruderfer, Douglas; Rybin, Denis; van der Schouw, Yvonne T; Sennblad, Bengt; Sigurðsson, Gunnar; Stančáková, Alena; Steinbach, Gerald; Storm, Petter; Strauch, Konstantin; Stringham, Heather M; Sun, Qi; Thorand, Barbara; Tikkanen, Emmi; Tonjes, Anke; Trakalo, Joseph; Tremoli, Elena; Tuomi, Tiinamaija; Wennauer, Roman; Wood, Andrew R; Zeggini, Eleftheria; Dunham, Ian; Birney, Ewan; Pasquali, Lorenzo; Ferrer, Jorge; Loos, Ruth JF; Dupuis, Josée; Florez, Jose C; Boerwinkle, Eric; Pankow, James S; van Duijn, Cornelia; Sijbrands, Eric; Meigs, James B; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Lakka, Timo A; Rauramaa, Rainer; Stumvoll, Michael; Pedersen, Nancy L; Lind, Lars; Keinanen-Kiukaanniemi, Sirkka M; Korpi-Hyövälti, Eeva; Saaristo, Timo E; Saltevo, Juha; Kuusisto, Johanna; Laakso, Markku; Metspalu, Andres; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Ripatti, Samuli; Salomaa, Veikko; Ingelsson, Erik; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Koistinen, Heikki; Tuomilehto, Jaakko; Hveem, Kristian; Njølstad, Inger; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; de Faire, Ulf; Hamsten, Anders; Illig, Thomas; Peters, Annette; Cauchi, Stephane; Sladek, Rob; Froguel, Philippe; Hansen, Torben; Pedersen, Oluf; Morris, Andrew D; Palmer, Collin NA; Kathiresan, Sekar; Melander, Olle; Nilsson, Peter M; Groop, Leif C; Barroso, Inês; Langenberg, Claudia; Wareham, Nicholas J; O’Callaghan, Christopher A; Gloyn, Anna L; Altshuler, David; Boehnke, Michael; Teslovich, Tanya M; McCarthy, Mark I; Morris, Andrew P

2015-01-01

We performed fine-mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in/near KCNQ1. “Credible sets” of variants most likely to drive each distinct signal mapped predominantly to non-coding sequence, implying that T2D association is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine-mapping implicated rs10830963 as driving T2D association. We confirmed that this T2D-risk allele increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D-risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease. PMID:26551672

A Stream Erosion Susceptibility Identification Tool for use in Hydromodification Planning

Science.gov (United States)

Berntsen, E.; Bowles, C.

2008-12-01

A stream erosion susceptibility identification tool has been developed for use in hydromodification planning based on a three-tiered approach. Tier 1 involved development of a susceptibility map. This included conducting a watershed scale GIS- and remote sensing-based screening analysis of two methodologies to quantify stream susceptibility to hydromodification. Tier 2 will involve conducting rapid geomorphic assessments for selected areas that were screened to have high and low erosion potential in Tier 1. Tier 3 will identify key geomorphic thresholds (e.g., relationship between channel slope, median particle size, and drainage area for stable and unstable channels, critical bank heights in various channel materials, channel response to changes in flow and sediment supply, etc.) from comparison of stable and unstable channels. This poster will primarily cover the methodology and results in Tier 1 for a pilot project in the Laguna Creek Watershed in Sacramento County, California. We used two methodologies, relying on readily available topographic information (i.e., USGS 10-meter DEM), for producing the Tier 1 susceptibility map: Hack's relationship (Hack, 1957; Bledsoe and Watson, 2004) and specific stream power (Simons and Downs, 1995). Hack's relationship involved calculating the hydraulic stability number (Nh), which is the ratio of the existing channel slope to the corresponding equilibrium slope, whereby a value greater than 1 represents a relatively unstable channel. Specific stream power involved calculating the power expended per unit area of the streambed (in Watts/m2), whereby a value greater than 35 represents a relatively unstable channel. The results of the Tier 1 analysis indicated that the two methodologies compared favorably in their predictions of channel instability. Comparisons of the two methodologies were also made with existing channel conditions as observed by others in a recent study in the watershed and completed in 2007. As shown by this

Analysis of early events in the interaction between Fusarium graminearum and the susceptible barley (Hordeum vulgare) cultivar Scarlett

DEFF Research Database (Denmark)

Yang, Fen; Jensen, J.D.; Svensson, Birte

2010-01-01

A proteomic analysis was conducted to map the events during the initial stages of the interaction between the fungal pathogen Fusarium graminearum and the susceptible barley cultivar Scarlett. Quantification of fungal DNA demonstrated a sharp increase in fungal biomass in barley spikelets at 3 da...

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

Science.gov (United States)

Beecham, Ashley H; Patsopoulos, Nikolaos A; Xifara, Dionysia K; Davis, Mary F; Kemppinen, Anu; Cotsapas, Chris; Shahi, Tejas S; Spencer, Chris; Booth, David; Goris, An; Oturai, Annette; Saarela, Janna; Fontaine, Bertrand; Hemmer, Bernhard; Martin, Claes; Zipp, Frauke; D’alfonso, Sandra; Martinelli-Boneschi, Filippo; Taylor, Bruce; Harbo, Hanne F; Kockum, Ingrid; Hillert, Jan; Olsson, Tomas; Ban, Maria; Oksenberg, Jorge R; Hintzen, Rogier; Barcellos, Lisa F; Agliardi, Cristina; Alfredsson, Lars; Alizadeh, Mehdi; Anderson, Carl; Andrews, Robert; Søndergaard, Helle Bach; Baker, Amie; Band, Gavin; Baranzini, Sergio E; Barizzone, Nadia; Barrett, Jeffrey; Bellenguez, Céline; Bergamaschi, Laura; Bernardinelli, Luisa; Berthele, Achim; Biberacher, Viola; Binder, Thomas M C; Blackburn, Hannah; Bomfim, Izaura L; Brambilla, Paola; Broadley, Simon; Brochet, Bruno; Brundin, Lou; Buck, Dorothea; Butzkueven, Helmut; Caillier, Stacy J; Camu, William; Carpentier, Wassila; Cavalla, Paola; Celius, Elisabeth G; Coman, Irène; Comi, Giancarlo; Corrado, Lucia; Cosemans, Leentje; Cournu-Rebeix, Isabelle; Cree, Bruce A C; Cusi, Daniele; Damotte, Vincent; Defer, Gilles; Delgado, Silvia R; Deloukas, Panos; di Sapio, Alessia; Dilthey, Alexander T; Donnelly, Peter; Dubois, Bénédicte; Duddy, Martin; Edkins, Sarah; Elovaara, Irina; Esposito, Federica; Evangelou, Nikos; Fiddes, Barnaby; Field, Judith; Franke, Andre; Freeman, Colin; Frohlich, Irene Y; Galimberti, Daniela; Gieger, Christian; Gourraud, Pierre-Antoine; Graetz, Christiane; Graham, Andrew; Grummel, Verena; Guaschino, Clara; Hadjixenofontos, Athena; Hakonarson, Hakon; Halfpenny, Christopher; Hall, Gillian; Hall, Per; Hamsten, Anders; Harley, James; Harrower, Timothy; Hawkins, Clive; Hellenthal, Garrett; Hillier, Charles; Hobart, Jeremy; Hoshi, Muni; Hunt, Sarah E; Jagodic, Maja; Jelčić, Ilijas; Jochim, Angela; Kendall, Brian; Kermode, Allan; Kilpatrick, Trevor; Koivisto, Keijo; Konidari, Ioanna; Korn, Thomas; Kronsbein, Helena; Langford, Cordelia; Larsson, Malin; Lathrop, Mark; Lebrun-Frenay, Christine; Lechner-Scott, Jeannette; Lee, Michelle H; Leone, Maurizio A; Leppä, Virpi; Liberatore, Giuseppe; Lie, Benedicte A; Lill, Christina M; Lindén, Magdalena; Link, Jenny; Luessi, Felix; Lycke, Jan; Macciardi, Fabio; Männistö, Satu; Manrique, Clara P; Martin, Roland; Martinelli, Vittorio; Mason, Deborah; Mazibrada, Gordon; McCabe, Cristin; Mero, Inger-Lise; Mescheriakova, Julia; Moutsianas, Loukas; Myhr, Kjell-Morten; Nagels, Guy; Nicholas, Richard; Nilsson, Petra; Piehl, Fredrik; Pirinen, Matti; Price, Siân E; Quach, Hong; Reunanen, Mauri; Robberecht, Wim; Robertson, Neil P; Rodegher, Mariaemma; Rog, David; Salvetti, Marco; Schnetz-Boutaud, Nathalie C; Sellebjerg, Finn; Selter, Rebecca C; Schaefer, Catherine; Shaunak, Sandip; Shen, Ling; Shields, Simon; Siffrin, Volker; Slee, Mark; Sorensen, Per Soelberg; Sorosina, Melissa; Sospedra, Mireia; Spurkland, Anne; Strange, Amy; Sundqvist, Emilie; Thijs, Vincent; Thorpe, John; Ticca, Anna; Tienari, Pentti; van Duijn, Cornelia; Visser, Elizabeth M; Vucic, Steve; Westerlind, Helga; Wiley, James S; Wilkins, Alastair; Wilson, James F; Winkelmann, Juliane; Zajicek, John; Zindler, Eva; Haines, Jonathan L; Pericak-Vance, Margaret A; Ivinson, Adrian J; Stewart, Graeme; Hafler, David; Hauser, Stephen L; Compston, Alastair; McVean, Gil; De Jager, Philip; Sawcer, Stephen; McCauley, Jacob L

2013-01-01

Using the ImmunoChip custom genotyping array, we analysed 14,498 multiple sclerosis subjects and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (p-value multiple sclerosis subjects and 26,703 healthy controls. In these 80,094 individuals of European ancestry we identified 48 new susceptibility variants (p-value multiple sclerosis risk variants in 103 discrete loci outside of the Major Histocompatibility Complex. With high resolution Bayesian fine-mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalogue of multiple sclerosis risk variants and illustrates the value of fine-mapping in the resolution of GWAS signals. PMID:24076602

Mapping of gene expression reveals CYP27A1 as a susceptibility gene for sporadic ALS

NARCIS (Netherlands)

F.P. Diekstra (Frank); C.G.J. Saris (Christiaan); W. van Rheenen (Wouter); L. Franke (Lude); R.C. Jansen (Ritsert); M.A. van Es (Michael); K. Estrada Gil (Karol); P.W.J. van Vught (Paul); H.M. Blauw (Hylke); E.J.N. Groen (Ewout); S. Horvath (Steve); K. Estrada Gil (Karol); F. Rivadeneira Ramirez (Fernando); A. Hofman (Albert); A.G. Uitterlinden (André); W. Robberecht (Wim); P.M. Andersen (Peter); J. Melki (Judith); V. Meininger (Vincent); O. Hardiman (Orla); J.E. Landers (John); R.H. Brown (Robert); A. Shatunov (Aleksey); C.E. Shaw (Christopher); P.N. Leigh (Nigel); A. Al-Chalabi (Ammar); R.A. Ophoff (Roel); L.H. van den Berg (Leonard); J.H. Veldink (Jan)

2012-01-01

textabstractAmyotrophic lateral sclerosis (ALS) is a progressive, neurodegenerative disease characterized by loss of upper and lower motor neurons. ALS is considered to be a complex trait and genome-wide association studies (GWAS) have implicated a few susceptibility loci. However, many more causal

Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (lidar) in Densely Vegetated Areas of Tropics

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Bibi, T.; Azahari Razak, K.; Rahman, A. Abdul; Latif, A.

2017-10-01

Landslides are an inescapable natural disaster, resulting in massive social, environmental and economic impacts all over the world. The tropical, mountainous landscape in generally all over Malaysia especially in eastern peninsula (Borneo) is highly susceptible to landslides because of heavy rainfall and tectonic disturbances. The purpose of the Landslide hazard mapping is to identify the hazardous regions for the execution of mitigation plans which can reduce the loss of life and property from future landslide incidences. Currently, the Malaysian research bodies e.g. academic institutions and government agencies are trying to develop a landslide hazard and risk database for susceptible areas to backing the prevention, mitigation, and evacuation plan. However, there is a lack of devotion towards landslide inventory mapping as an elementary input of landslide susceptibility, hazard and risk mapping. The developing techniques based on remote sensing technologies (satellite, terrestrial and airborne) are promising techniques to accelerate the production of landslide maps, shrinking the time and resources essential for their compilation and orderly updates. The aim of the study is to provide a better perception regarding the use of virtual mapping of landslides with the help of LiDAR technology. The focus of the study is spatio temporal detection and virtual mapping of landslide inventory via visualization and interpretation of very high-resolution data (VHR) in forested terrain of Mesilau river, Kundasang. However, to cope with the challenges of virtual inventory mapping on in forested terrain high resolution LiDAR derivatives are used. This study specifies that the airborne LiDAR technology can be an effective tool for mapping landslide inventories in a complex climatic and geological conditions, and a quick way of mapping regional hazards in the tropics.

Genetic and genomic analysis modeling of germline c-MYC overexpression and cancer susceptibility

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Nunes Virginia

2008-01-01

Full Text Available Abstract Background Germline genetic variation is associated with the differential expression of many human genes. The phenotypic effects of this type of variation may be important when considering susceptibility to common genetic diseases. Three regions at 8q24 have recently been identified to independently confer risk of prostate cancer. Variation at 8q24 has also recently been associated with risk of breast and colorectal cancer. However, none of the risk variants map at or relatively close to known genes, with c-MYC mapping a few hundred kilobases distally. Results This study identifies cis-regulators of germline c-MYC expression in immortalized lymphocytes of HapMap individuals. Quantitative analysis of c-MYC expression in normal prostate tissues suggests an association between overexpression and variants in Region 1 of prostate cancer risk. Somatic c-MYC overexpression correlates with prostate cancer progression and more aggressive tumor forms, which was also a pathological variable associated with Region 1. Expression profiling analysis and modeling of transcriptional regulatory networks predicts a functional association between MYC and the prostate tumor suppressor KLF6. Analysis of MYC/Myc-driven cell transformation and tumorigenesis substantiates a model in which MYC overexpression promotes transformation by down-regulating KLF6. In this model, a feedback loop through E-cadherin down-regulation causes further transactivation of c-MYC. Conclusion This study proposes that variation at putative 8q24 cis-regulator(s of transcription can significantly alter germline c-MYC expression levels and, thus, contribute to prostate cancer susceptibility by down-regulating the prostate tumor suppressor KLF6 gene.

Spatial probabilistic approach on landslide susceptibility assessment from high resolution sensors derived parameters

International Nuclear Information System (INIS)

Aman, S N A; Latif, Z Abd; Pradhan, B

2014-01-01

Landslide occurrence depends on various interrelating factors which consequently initiate to massive mass of soil and rock debris that move downhill due to the gravity action. LiDAR has come with a progressive approach in mitigating landslide by permitting the formation of more accurate DEM compared to other active space borne and airborne remote sensing techniques. The objective of this research is to assess the susceptibility of landslide in Ulu Klang area by investigating the correlation between past landslide events with geo environmental factors. A high resolution LiDAR DEM was constructed to produce topographic attributes such as slope, curvature and aspect. These data were utilized to derive second deliverables of landslide parameters such as topographic wetness index (TWI), surface area ratio (SAR) and stream power index (SPI) as well as NDVI generated from IKONOS imagery. Subsequently, a probabilistic based frequency ratio model was applied to establish the spatial relationship between the landslide locations and each landslide related factor. Factor ratings were summed up to obtain Landslide Susceptibility Index (LSI) to construct the landslide susceptibility map

Mapping of Gene Expression Reveals CYP27A1 as a Susceptibility Gene for Sporadic ALS

NARCIS (Netherlands)

Diekstra, Frank P.; Saris, Christiaan G. J.; van Rheenen, Wouter; Franke, Lude; Jansen, Ritsert C.; van Es, Michael A.; van Vught, Paul W. J.; Blauw, Hylke M.; Groen, Ewout J. N.; Horvath, Steve; Estrada, Karol; Rivadeneira, Fernando; Hofman, Albert; Uitterlinden, Andre G.; Robberecht, Wim; Andersen, Peter M.; Melki, Judith; Meininger, Vincent; Hardiman, Orla; Landers, John E.; Brown, Robert H.; Shatunov, Aleksey; Shaw, Christopher E.; Leigh, P. Nigel; Al-Chalabi, Ammar; Ophoff, Roel A.; van den Berg, Leonard H.; Veldink, Jan H.; Brown Jr., Robert H.; Brug, Marcel P. van der

2012-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive, neurodegenerative disease characterized by loss of upper and lower motor neurons. ALS is considered to be a complex trait and genome-wide association studies (GWAS) have implicated a few susceptibility loci. However, many more causal loci remain

Analysis of significance of environmental factors in landslide susceptibility modeling: Case study Jemma drainage network, Ethiopia

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Vít Maca

2017-06-01

Full Text Available Aim of the paper is to describe methodology for calculating significance of environmental factors in landslide susceptibility modeling and present result of selected one. As a study area part of a Jemma basin in Ethiopian Highland is used. This locality is highly affected by mass movement processes. In the first part all major factors and their influence are described briefly. Majority of the work focuses on research of other methodologies used in susceptibility models and design of own methodology. This method is unlike most of the methods used completely objective, therefore it is not possible to intervene in the results. In article all inputs and outputs of the method are described as well as all stages of calculations. Results are illustrated on specific examples. In study area most important factor for landslide susceptibility is slope, on the other hand least important is land cover. At the end of article landslide susceptibility map is created. Part of the article is discussion of results and possible improvements of the methodology.

Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31

Science.gov (United States)

Permuth-Wey, Jennifer; Lawrenson, Kate; Shen, Howard C.; Velkova, Aneliya; Tyrer, Jonathan P.; Chen, Zhihua; Lin, Hui-Yi; Chen, Y. Ann; Tsai, Ya-Yu; Qu, Xiaotao; Ramus, Susan J.; Karevan, Rod; Lee, Janet; Lee, Nathan; Larson, Melissa C.; Aben, Katja K.; Anton-Culver, Hoda; Antonenkova, Natalia; Antoniou, Antonis; Armasu, Sebastian M.; Bacot, François; Baglietto, Laura; Bandera, Elisa V.; Barnholtz-Sloan, Jill; Beckmann, Matthias W.; Birrer, Michael J.; Bloom, Greg; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Brown, Robert; Butzow, Ralf; Cai, Qiuyin; Campbell, Ian; Chang-Claude, Jenny; Chanock, Stephen; Chenevix-Trench, Georgia; Cheng, Jin Q.; Cicek, Mine S.; Coetzee, Gerhard A.; Cook, Linda S.; Couch, Fergus J.; Cramer, Daniel W.; Cunningham, Julie M.; Dansonka-Mieszkowska, Agnieszka; Despierre, Evelyn; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Easton, Douglas F; Eccles, Diana; Edwards, Robert; Ekici, Arif B.; Fasching, Peter A.; Fenstermacher, David A.; Flanagan, James M.; Garcia-Closas, Montserrat; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind M.; Gonzalez-Bosquet, Jesus; Goodman, Marc T.; Gore, Martin; Górski, Bohdan; Gronwald, Jacek; Hall, Per; Halle, Mari K.; Harter, Philipp; Heitz, Florian; Hillemanns, Peter; Hoatlin, Maureen; Høgdall, Claus K.; Høgdall, Estrid; Hosono, Satoyo; Jakubowska, Anna; Jensen, Allan; Jim, Heather; Kalli, Kimberly R.; Karlan, Beth Y.; Kaye, Stanley B.; Kelemen, Linda E.; Kiemeney, Lambertus A.; Kikkawa, Fumitaka; Konecny, Gottfried E.; Krakstad, Camilla; Kjaer, Susanne Krüger; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Lancaster, Johnathan M.; Le, Nhu D.; Leminen, Arto; Levine, Douglas A.; Liang, Dong; Lim, Boon Kiong; Lin, Jie; Lissowska, Jolanta; Lu, Karen H.; Lubiński, Jan; Lurie, Galina; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Nakanishi, Toru; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Nickels, Stefan; Noushmehr, Houtan; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Paul, James; Pearce, Celeste L; Pejovic, Tanja; Pelttari, Liisa M.; Pike, Malcolm C.; Poole, Elizabeth M.; Raska, Paola; Renner, Stefan P.; Risch, Harvey A.; Rodriguez-Rodriguez, Lorna; Rossing, Mary Anne; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schwaab, Ira; Severi, Gianluca; Shridhar, Vijayalakshmi; Shu, Xiao-Ou; Shvetsov, Yurii B.; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Spiewankiewicz, Beata; Stram, Daniel; Sutphen, Rebecca; Teo, Soo-Hwang; Terry, Kathryn L.; Tessier, Daniel C.; Thompson, Pamela J.; Tworoger, Shelley S.; van Altena, Anne M.; Vergote, Ignace; Vierkant, Robert A.; Vincent, Daniel; Vitonis, Allison F.; Wang-Gohrke, Shan; Weber, Rachel Palmieri; Wentzensen, Nicolas; Whittemore, Alice S.; Wik, Elisabeth; Wilkens, Lynne R.; Winterhoff, Boris; Woo, Yin Ling; Wu, Anna H.; Xiang, Yong-Bing; Yang, Hannah P.; Zheng, Wei; Ziogas, Argyrios; Zulkifli, Famida; Phelan, Catherine M.; Iversen, Edwin; Schildkraut, Joellen M.; Berchuck, Andrew; Fridley, Brooke L.; Goode, Ellen L.; Pharoah, Paul D. P.; Monteiro, Alvaro N.A.; Sellers, Thomas A.; Gayther, Simon A.

2013-01-01

Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3′ untranslated region at putative microRNA (miRNA) binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA binding site single nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (OR=1.12, P=10−8) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10−10). Variation at 17q21.31 associates with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes. PMID:23535648

Radiation hybrid mapping of genes in the lithium-sensitive wnt signaling pathway.

Science.gov (United States)

Rhoads, A R; Karkera, J D; Detera-Wadleigh, S D

1999-09-01

Lithium, an effective drug in the treatment of bipolar disorder, has been proposed to disrupt the Wnt signaling pathway. To facilitate analysis of the possible involvement of elements of the Wnt pathway in human bipolar disorder, a high resolution radiation hybrid mapping (RHM) of these genes was performed. A fine physical location has been obtained for Wnt 7A, frizzled 3, 4 and 5, dishevelled 1, 2 and 3, GSK3beta, axin, alpha-catenin, the Armadillo repeat-containing genes (delta-catenin and ARVCF), and a frizzled-like protein (frpHE) using the Stanford Human Genome Center (SHGC) G3 panel. Most of these genes were previously mapped by fluorescence in situ hybridization (FISH). Frizzled 4, axin and frpHE did not have a previous chromosomal assignment and were linked by RHM to chromosome markers, SHGC-35131 at 11q22.1, NIB1488 at 16p13.3 and D7S2919 at 7p15.2, respectively. Interestingly, some of these genes were found to map within potential regions underlying susceptibility to bipolar disorder and schizophrenia as well as disorders of neurodevelopmental origin. This alternative approach of establishing the precise location of selected genetic components of a candidate pathway and determining if they map within previously defined susceptibility loci should help to identify plausible candidate genes that warrant further analysis through association and mutational scanning.

Sinkhole susceptibility mapping using the analytical hierarchy process (AHP) and magnitude-frequency relationships: A case study in Hamadan province, Iran

Science.gov (United States)

Taheri, Kamal; Gutiérrez, Francisco; Mohseni, Hassan; Raeisi, Ezzat; Taheri, Milad

2015-04-01

Since 1989, an increasing number of sinkhole occurrences have been reported in the Kabudar Ahang and Razan-Qahavand subcatchments (KRQ) of Hamadan province, western Iran. The sinkhole-related subsidence phenomenon poses a significant threat for people and human structures, including sensitive facilities like the Hamadan Power Plant. Groundwater over-exploitation from the thick alluvial cover and the underlying cavernous limestone has been identified as the main factor involved in sinkhole development. A sinkhole susceptibility model was produced in a GIS environment applying the analytical hierarchy process (AHP) approach and considering a selection of eight factors, each categorized into five classes: distance to faults (DF), water level decline (WLD), groundwater exploitation (GE), penetration of deep wells into karst bedrock (PKA), distance to deep wells (DDW), groundwater alkalinity (GA), bedrock lithology (BL), and alluvium thickness (AT). Relative weights were preliminarily assigned to each factor and to their different classes through systematic pairwise comparisons based on expert judgment. The resulting sinkhole susceptibility index (SSI) values were then classified into four susceptibility classes: low, moderate, high and very high susceptibility. Subsequently, the model was refined through a trial and error process involving changes in the relative weights and iterative evaluation of the prediction capability. Independent evaluation of the final model indicates that 55% and 45% of the subsidence events fall within the very high and high, susceptibility zones, respectively. The results of this study show that AHP can be a useful approach for susceptibility assessment if data on the main controlling factors have sufficient accuracy and spatial coverage. The limitations of the model are partly related to the difficulty of gathering data on some important geological factors, due to their hidden nature. The magnitude and frequency relationship constructed

Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India)

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Das, Iswar; Sahoo, Sashikant; van Westen, Cees; Stein, Alfred; Hack, Robert

2010-02-01

Landslide studies are commonly guided by ground knowledge and field measurements of rock strength and slope failure criteria. With increasing sophistication of GIS-based statistical methods, however, landslide susceptibility studies benefit from the integration of data collected from various sources and methods at different scales. This study presents a logistic regression method for landslide susceptibility mapping and verifies the result by comparing it with the geotechnical-based slope stability probability classification (SSPC) methodology. The study was carried out in a landslide-prone national highway road section in the northern Himalayas, India. Logistic regression model performance was assessed by the receiver operator characteristics (ROC) curve, showing an area under the curve equal to 0.83. Field validation of the SSPC results showed a correspondence of 72% between the high and very high susceptibility classes with present landslide occurrences. A spatial comparison of the two susceptibility maps revealed the significance of the geotechnical-based SSPC method as 90% of the area classified as high and very high susceptible zones by the logistic regression method corresponds to the high and very high class in the SSPC method. On the other hand, only 34% of the area classified as high and very high by the SSPC method falls in the high and very high classes of the logistic regression method. The underestimation by the logistic regression method can be attributed to the generalisation made by the statistical methods, so that a number of slopes existing in critical equilibrium condition might not be classified as high or very high susceptible zones.

A Genetic Linkage Map of Mycosphaerella Fijiensis, using SSR and DArT Markers

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Mycosphaerella fijiensis is the causal agent of black leaf streak or Black Sigatoka disease in bananas. This pathogen threatens global banana production as the main export Cavendish cultivars are highly susceptible. Previously a genetic linkage map was generated predominantly using anonymous AFLP ma...

Quantitative comparison between a multiecho sequence and a single-echo sequence for susceptibility-weighted phase imaging.

Science.gov (United States)

Gilbert, Guillaume; Savard, Geneviève; Bard, Céline; Beaudoin, Gilles

2012-06-01

The aim of this study was to investigate the benefits arising from the use of a multiecho sequence for susceptibility-weighted phase imaging using a quantitative comparison with a standard single-echo acquisition. Four healthy adult volunteers were imaged on a clinical 3-T system using a protocol comprising two different three-dimensional susceptibility-weighted gradient-echo sequences: a standard single-echo sequence and a multiecho sequence. Both sequences were repeated twice in order to evaluate the local noise contribution by a subtraction of the two acquisitions. For the multiecho sequence, the phase information from each echo was independently unwrapped, and the background field contribution was removed using either homodyne filtering or the projection onto dipole fields method. The phase information from all echoes was then combined using a weighted linear regression. R2 maps were also calculated from the multiecho acquisitions. The noise standard deviation in the reconstructed phase images was evaluated for six manually segmented regions of interest (frontal white matter, posterior white matter, globus pallidus, putamen, caudate nucleus and lateral ventricle). The use of the multiecho sequence for susceptibility-weighted phase imaging led to a reduction of the noise standard deviation for all subjects and all regions of interest investigated in comparison to the reference single-echo acquisition. On average, the noise reduction ranged from 18.4% for the globus pallidus to 47.9% for the lateral ventricle. In addition, the amount of noise reduction was found to be strongly inversely correlated to the estimated R2 value (R=-0.92). In conclusion, the use of a multiecho sequence is an effective way to decrease the noise contribution in susceptibility-weighted phase images, while preserving both contrast and acquisition time. The proposed approach additionally permits the calculation of R2 maps. Copyright © 2012 Elsevier Inc. All rights reserved.

As Queixas Subjetivas de Memória num Cuidado de Saúde Primário: Um Estudo Follow up

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Mónica Sousa

2017-08-01

Full Text Available ObjetivoAs queixas subjetivas de memória (QSM são um fator clínico relevante e uma das principais queixas feitas aos médicos de família por adultos e adultos idosos. Este estudo, realizado numa Unidade de Saúde Familiar da Região Centro de Portugal, teve como objetivo caracterizar as QSM em função de variáveis sociodemográficas, clínicas, cognitivas, emocionais e de qualidade de vida.MétodoEste estudo, de coorte prospetivo em dois momentos, procurou explorar a evolução das QSM durante 18 meses e quais os fatores que se associam. Foi levado a cabo numa amostra de 19 adultos e de adultos idosos com idades compreendidas entre os 55 e os 81 anos (79.2% do sexo feminino. Os dados foram recolhidos por entrevistas semiestruturadas e sempre que possível foram consultados os processos clínicos. Foram utilizados como instrumentos de medida o Mini Mental State Examination (MMSE, o Montreal Cognitive Assessment (MoCA, a Escala de Queixas de Memória (EQM, a Escala de Depressão Geriátrica (GDS, o Inventário de Ansiedade Geriátrica (GAI, a Avaliação de Qualidade de Vida da Organização Mundial de Saúde (WHOQOL-Bref e por um questionário sociodemográfico e clínico construído para o efeito.ResultadosNo segundo momento avaliativo, todos os participantes evidenciam QSM, sendo estas influenciadas significativamente pela idade. Houve ainda um aumento da sintomatologia depressiva e ansiógena, dos valores da Hemoglobina glicosilada (HbA1c e do número de medicamentos consumidos, com particular ênfase nos anti hipertensores.ConclusãoAs QSM deverão ser objeto de preocupação e vigilância do médico de família, uma vez que podem representar um sintoma relevante para a identificação precoce de um processo demencial.

Modeling landslide susceptibility in data-scarce environments using optimized data mining and statistical methods

Science.gov (United States)

Lee, Jung-Hyun; Sameen, Maher Ibrahim; Pradhan, Biswajeet; Park, Hyuck-Jin

2018-02-01

This study evaluated the generalizability of five models to select a suitable approach for landslide susceptibility modeling in data-scarce environments. In total, 418 landslide inventories and 18 landslide conditioning factors were analyzed. Multicollinearity and factor optimization were investigated before data modeling, and two experiments were then conducted. In each experiment, five susceptibility maps were produced based on support vector machine (SVM), random forest (RF), weight-of-evidence (WoE), ridge regression (Rid_R), and robust regression (RR) models. The highest accuracy (AUC = 0.85) was achieved with the SVM model when either the full or limited landslide inventories were used. Furthermore, the RF and WoE models were severely affected when less landslide samples were used for training. The other models were affected slightly when the training samples were limited.

Exposure of young dairy cattle to Mycobacterium avium subsp. paratuberculosis (MAP) through intensive grazing of contaminated pastures in a herd positive for Johne's disease.

Science.gov (United States)

Fecteau, Marie-Eve; Whitlock, Robert H; Buergelt, Claus D; Sweeney, Raymond W

2010-02-01

This study investigated the susceptibility of 1- to 2-year-old cattle to Mycobacterium avium subsp. paratuberculosis (MAP) on pasture previously grazed by infected cattle. The exposure of yearling cattle to pastures contaminated with MAP resulted in infection with MAP, showing that age resistance to infection can be overcome by pressure of infection.

Inverse gene-for-gene interactions contribute additively to tan spot susceptibility in wheat.

Science.gov (United States)

Liu, Zhaohui; Zurn, Jason D; Kariyawasam, Gayan; Faris, Justin D; Shi, Gongjun; Hansen, Jana; Rasmussen, Jack B; Acevedo, Maricelis

2017-06-01

Tan spot susceptibility is conferred by multiple interactions of necrotrophic effector and host sensitivity genes. Tan spot of wheat, caused by Pyrenophora tritici-repentis, is an important disease in almost all wheat-growing areas of the world. The disease system is known to involve at least three fungal-produced necrotrophic effectors (NEs) that interact with the corresponding host sensitivity (S) genes in an inverse gene-for-gene manner to induce disease. However, it is unknown if the effects of these NE-S gene interactions contribute additively to the development of tan spot. In this work, we conducted disease evaluations using different races and quantitative trait loci (QTL) analysis in a wheat recombinant inbred line (RIL) population derived from a cross between two susceptible genotypes, LMPG-6 and PI 626573. The two parental lines each harbored a single known NE sensitivity gene with LMPG-6 having the Ptr ToxC sensitivity gene Tsc1 and PI 626573 having the Ptr ToxA sensitivity gene Tsn1. Transgressive segregation was observed in the population for all races. QTL mapping revealed that both loci (Tsn1 and Tsc1) were significantly associated with susceptibility to race 1 isolates, which produce both Ptr ToxA and Ptr ToxC, and the two genes contributed additively to tan spot susceptibility. For isolates of races 2 and 3, which produce only Ptr ToxA and Ptr ToxC, only Tsn1 and Tsc1 were associated with tan spot susceptibility, respectively. This work clearly demonstrates that tan spot susceptibility in this population is due primarily to two NE-S interactions. Breeders should remove both sensitivity genes from wheat lines to obtain high levels of tan spot resistance.

Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey

Science.gov (United States)

Duman, T. Y.; Can, T.; Gokceoglu, C.; Nefeslioglu, H. A.; Sonmez, H.

2006-11-01

As a result of industrialization, throughout the world, cities have been growing rapidly for the last century. One typical example of these growing cities is Istanbul, the population of which is over 10 million. Due to rapid urbanization, new areas suitable for settlement and engineering structures are necessary. The Cekmece area located west of the Istanbul metropolitan area is studied, because the landslide activity is extensive in this area. The purpose of this study is to develop a model that can be used to characterize landslide susceptibility in map form using logistic regression analysis of an extensive landslide database. A database of landslide activity was constructed using both aerial-photography and field studies. About 19.2% of the selected study area is covered by deep-seated landslides. The landslides that occur in the area are primarily located in sandstones with interbedded permeable and impermeable layers such as claystone, siltstone and mudstone. About 31.95% of the total landslide area is located at this unit. To apply logistic regression analyses, a data matrix including 37 variables was constructed. The variables used in the forwards stepwise analyses are different measures of slope, aspect, elevation, stream power index (SPI), plan curvature, profile curvature, geology, geomorphology and relative permeability of lithological units. A total of 25 variables were identified as exerting strong influence on landslide occurrence, and included by the logistic regression equation. Wald statistics values indicate that lithology, SPI and slope are more important than the other parameters in the equation. Beta coefficients of the 25 variables included the logistic regression equation provide a model for landslide susceptibility in the Cekmece area. This model is used to generate a landslide susceptibility map that correctly classified 83.8% of the landslide-prone areas.

Flood susceptibility analysis through remote sensing, GIS and frequency ratio model

Science.gov (United States)

Samanta, Sailesh; Pal, Dilip Kumar; Palsamanta, Babita

2018-05-01

Papua New Guinea (PNG) is saddled with frequent natural disasters like earthquake, volcanic eruption, landslide, drought, flood etc. Flood, as a hydrological disaster to humankind's niche brings about a powerful and often sudden, pernicious change in the surface distribution of water on land, while the benevolence of flood manifests in restoring the health of the thalweg from excessive siltation by redistributing the fertile sediments on the riverine floodplains. In respect to social, economic and environmental perspective, flood is one of the most devastating disasters in PNG. This research was conducted to investigate the usefulness of remote sensing, geographic information system and the frequency ratio (FR) for flood susceptibility mapping. FR model was used to handle different independent variables via weighted-based bivariate probability values to generate a plausible flood susceptibility map. This study was conducted in the Markham riverine precinct under Morobe province in PNG. A historical flood inventory database of PNG resource information system (PNGRIS) was used to generate 143 flood locations based on "create fishnet" analysis. 100 (70%) flood sample locations were selected randomly for model building. Ten independent variables, namely land use/land cover, elevation, slope, topographic wetness index, surface runoff, landform, lithology, distance from the main river, soil texture and soil drainage were used into the FR model for flood vulnerability analysis. Finally, the database was developed for areas vulnerable to flood. The result demonstrated a span of FR values ranging from 2.66 (least flood prone) to 19.02 (most flood prone) for the study area. The developed database was reclassified into five (5) flood vulnerability zones segmenting on the FR values, namely very low (less that 5.0), low (5.0-7.5), moderate (7.5-10.0), high (10.0-12.5) and very high susceptibility (more than 12.5). The result indicated that about 19.4% land area as `very high

The Rock Engineering System (RES) applied to landslide susceptibility zonation of the northeastern flank of Etna: methodological approach and results

Science.gov (United States)

Apuani, Tiziana; Corazzato, Claudia

2015-04-01

Ground deformations in the northeastern flank of Etna are well known. Despite only a few landslide events have been documented, these have significantly involved and damaged lifelines and buildings. These events are mainly related to the activity of the volcano-tectonic structures and associated seismicity, as in the case of the 2002 reactivation of the Presa landslide during an increased activity of the Pernicana fault system. In order to highlight the areal distribution of potentially unstable slopes based on a detailed, site-specific study of the factors responsible for landslide, and to ultimately contribute to risk management, a landslide susceptibility analysis of the northeastern flank of Etna in the Pernicana area was carried out, and a susceptibility map at 1:10.000 scale was produced, extending over an area of 168 km2. Different methods are proposed in the literature to obtain the regional distribution of potentially unstable slopes, depending on the problem scale, the slope dynamic evolution in the geological context, and the availability of data. Among semi-quantitative approaches, the present research combines the Rock Engineering System (RES) methodology with parameter zonation mapping in a GIS environment. The RES method represents a structured approach to manage a high number of interacting factors involved in the instability problem. A numerically coded, site-specific interaction matrix (IM) analyzes the cause-effect relationship in these factors, and calculates the degree of interactivity of each parameter, normalized by the overall interactivity of the system (weight factor). In the specific Etna case, the considered parameters are: slope attitude, lithotechnical properties (lithology, structural complexity, soil and rock mass quality), land use, tectonic structures, seismic activity (horizontal acceleration) and hydrogeological conditions (groundwater and drainage). Thematic maps are prepared at 1:10.000 scale for each of these parameters, and

Penicillin-susceptible Staphylococcus aureus: susceptibility testing, resistance rates and outcome of infection.

Science.gov (United States)

Hagstrand Aldman, Malin; Skovby, Annette; I Påhlman, Lisa

2017-06-01

Staphylococcus aureus (SA) is an important human pathogen that causes both superficial and invasive infections. Penicillin is now rarely used in the treatment of SA infections due to widespread resistance and a concern about the accuracy of existing methods for penicillin susceptibility testing. The aims of the present study were to determine the frequency of penicillin-susceptible SA isolates from blood and wound cultures in Lund, Sweden, and to evaluate methods for penicillin testing in SA. We also wanted to investigate if penicillin-susceptible isolates are associated with higher mortality. Hundred blood culture isolates collected 2008/2009, 140 blood culture isolates from 2014/2015, and 141 superficial wound culture strains from 2015 were examined. Penicillin susceptibility was tested with disk diffusion according to EUCAST guidelines, and results were confirmed with a cloverleaf assay and PCR amplification of the BlaZ gene. Patient data for all bacteraemia cases were extracted from medical records. The disk diffusion method with assessment of both zone size and zone edge appearance had high accuracy in our study. About 57% of bacteraemia isolates from 2008/2009 were sensitive to penicillin compared to 29% in 2014/2015 (p penicillin susceptible. There was no difference in co-morbidity or mortality rates between patients with penicillin resistant and penicillin sensitive SA bacteraemia. Disk-diffusion is a simple and reliable method to detect penicillin resistance in SA, and susceptibility rates are significant. Penicillin has many theoretical advantages and should be considered in the treatment of SA bacteraemia when susceptible.

Mapping of soil erosion and redistribution on two agricultural areas in Czech Republic by using of magnetic parameters.

Science.gov (United States)

Kapicka, Ales; Stejskalova, Sarka; Grison, Hana; Petrovsky, Eduard; Jaksik, Ondrej; Kodesova, Radka

2015-04-01

Soil erosion is one of the major concerns in sustainability of agricultural systems in different areas. Therefore there is a need to develop suitable innovative indirect methods of soil survey. One of this methods is based on well established differentiation in magnetic signature with depth in soil profile. Magnetic method can be applied in the field as well as in the laboratory on collected soil samples. The aim of this study is to evaluate suitability of magnetic method to assess soil degradation and construct maps of cumulative soil loss due to erosion at two morphologically diverse areas with different soil types. Dominant soil unit in the first locality (Brumovice) is chernozem, which is gradually degraded on slopes to regosols. In the second site (Vidim), the dominant soil unit is luvisol, gradualy transformed to regosol due to erosion. Field measurements of magnetic susceptibility were carried out on regular grid, resulting in 101 data points in Brumovice and 65 in Vidim locality. Mass specific magnetic susceptibility χ and its frequency dependence χFD was used to estimate the significance of SP ferrimagnetic particles of pedogenic origin in top soil horizons. Strong correlation was found between the volume magnetic susceptibility (field measurement) and mass- specific magnetic susceptibility measured in the laboratory (Kapicka et al 2013). Values of magnetic susceptibility are spatially distributed depending on terrain position. Higher values were measured at the flat parts (where the original topsoil horizon remained). The lowest values magnetic susceptibility were obtained on the steep valley sides. Here the original topsoil was eroded and mixed by tillage with the soil substrate (loess). Positive correlation between the organic carbon content and volume magnetic susceptibility (R2= 0.89) was found for chernozem area. The differences between the values of susceptibility in the undisturbed soil profile and the magnetic signal after uniform mixing of the

Nodal infection in Markovian susceptible-infected-susceptible and susceptible-infected-removed epidemics on networks are non-negatively correlated.

Science.gov (United States)

Cator, E; Van Mieghem, P

2014-05-01

By invoking the famous Fortuin, Kasteleyn, and Ginibre (FKG) inequality, we prove the conjecture that the correlation of infection at the same time between any pair of nodes in a network cannot be negative for (exact) Markovian susceptible-infected-susceptible (SIS) and susceptible-infected-removed (SIR) epidemics on networks. The truth of the conjecture establishes that the N-intertwined mean-field approximation (NIMFA) upper bounds the infection probability in any graph so that network design based on NIMFA always leads to safe protections against malware spread. However, when the infection or/and curing are not Poisson processes, the infection correlation between two nodes can be negative.

Nodal infection in Markovian susceptible-infected-susceptible and susceptible-infected-removed epidemics on networks are non-negatively correlated

Science.gov (United States)

Cator, E.; Van Mieghem, P.

2014-05-01

By invoking the famous Fortuin, Kasteleyn, and Ginibre (FKG) inequality, we prove the conjecture that the correlation of infection at the same time between any pair of nodes in a network cannot be negative for (exact) Markovian susceptible-infected-susceptible (SIS) and susceptible-infected-removed (SIR) epidemics on networks. The truth of the conjecture establishes that the N-intertwined mean-field approximation (NIMFA) upper bounds the infection probability in any graph so that network design based on NIMFA always leads to safe protections against malware spread. However, when the infection or/and curing are not Poisson processes, the infection correlation between two nodes can be negative.

Disease mapping based on stochastic SIR-SI model for Dengue and Chikungunya in Malaysia

Energy Technology Data Exchange (ETDEWEB)

Samat, N. A.; Ma' arof, S. H. Mohd Imam [Department of Mathematics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Perak (Malaysia)

2014-12-04

This paper describes and demonstrates a method for relative risk estimation which is based on the stochastic SIR-SI vector-borne infectious disease transmission model specifically for Dengue and Chikungunya diseases in Malaysia. Firstly, the common compartmental model for vector-borne infectious disease transmission called the SIR-SI model (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) is presented. This is followed by the explanations on the stochastic SIR-SI model which involve the Bayesian description. This stochastic model then is used in the relative risk formulation in order to obtain the posterior relative risk estimation. Then, this relative estimation model is demonstrated using Dengue and Chikungunya data of Malaysia. The viruses of these diseases are transmitted by the same type of female vector mosquito named Aedes Aegypti and Aedes Albopictus. Finally, the findings of the analysis of relative risk estimation for both Dengue and Chikungunya diseases are presented, compared and displayed in graphs and maps. The distribution from risk maps show the high and low risk area of Dengue and Chikungunya diseases occurrence. This map can be used as a tool for the prevention and control strategies for both diseases.

Disease mapping based on stochastic SIR-SI model for Dengue and Chikungunya in Malaysia

International Nuclear Information System (INIS)

Samat, N. A.; Ma'arof, S. H. Mohd Imam

2014-01-01

This paper describes and demonstrates a method for relative risk estimation which is based on the stochastic SIR-SI vector-borne infectious disease transmission model specifically for Dengue and Chikungunya diseases in Malaysia. Firstly, the common compartmental model for vector-borne infectious disease transmission called the SIR-SI model (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) is presented. This is followed by the explanations on the stochastic SIR-SI model which involve the Bayesian description. This stochastic model then is used in the relative risk formulation in order to obtain the posterior relative risk estimation. Then, this relative estimation model is demonstrated using Dengue and Chikungunya data of Malaysia. The viruses of these diseases are transmitted by the same type of female vector mosquito named Aedes Aegypti and Aedes Albopictus. Finally, the findings of the analysis of relative risk estimation for both Dengue and Chikungunya diseases are presented, compared and displayed in graphs and maps. The distribution from risk maps show the high and low risk area of Dengue and Chikungunya diseases occurrence. This map can be used as a tool for the prevention and control strategies for both diseases

Disease mapping based on stochastic SIR-SI model for Dengue and Chikungunya in Malaysia

Science.gov (United States)

Samat, N. A.; Ma'arof, S. H. Mohd Imam

2014-12-01

This paper describes and demonstrates a method for relative risk estimation which is based on the stochastic SIR-SI vector-borne infectious disease transmission model specifically for Dengue and Chikungunya diseases in Malaysia. Firstly, the common compartmental model for vector-borne infectious disease transmission called the SIR-SI model (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) is presented. This is followed by the explanations on the stochastic SIR-SI model which involve the Bayesian description. This stochastic model then is used in the relative risk formulation in order to obtain the posterior relative risk estimation. Then, this relative estimation model is demonstrated using Dengue and Chikungunya data of Malaysia. The viruses of these diseases are transmitted by the same type of female vector mosquito named Aedes Aegypti and Aedes Albopictus. Finally, the findings of the analysis of relative risk estimation for both Dengue and Chikungunya diseases are presented, compared and displayed in graphs and maps. The distribution from risk maps show the high and low risk area of Dengue and Chikungunya diseases occurrence. This map can be used as a tool for the prevention and control strategies for both diseases.

AFLP/SSR mapping of resistance genes to Alectra vogelii in cowpea ...

African Journals Online (AJOL)

To find and map the resistance gene to A. vogelii in cowpea, a F2 population from a cross involving a resistant parent IT81D-994 and a susceptible TVX3236 was screened. Amplified fragment length polymorphism (AFLP) in combination with Single Sequence Repeat (SSR) analysis was used to identify markers that may be ...

Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

Science.gov (United States)

Chen, Wei; Pourghasemi, Hamid Reza; Panahi, Mahdi; Kornejady, Aiding; Wang, Jiale; Xie, Xiaoshen; Cao, Shubo

2017-11-01

The spatial prediction of landslide susceptibility is an important prerequisite for the analysis of landslide hazards and risks in any area. This research uses three data mining techniques, such as an adaptive neuro-fuzzy inference system combined with frequency ratio (ANFIS-FR), a generalized additive model (GAM), and a support vector machine (SVM), for landslide susceptibility mapping in Hanyuan County, China. In the first step, in accordance with a review of the previous literature, twelve conditioning factors, including slope aspect, altitude, slope angle, topographic wetness index (TWI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, land use, normalized difference vegetation index (NDVI), and lithology, were selected. In the second step, a collinearity test and correlation analysis between the conditioning factors and landslides were applied. In the third step, we used three advanced methods, namely, ANFIS-FR, GAM, and SVM, for landslide susceptibility modeling. Subsequently, the results of their accuracy were validated using a receiver operating characteristic curve. The results showed that all three models have good prediction capabilities, while the SVM model has the highest prediction rate of 0.875, followed by the ANFIS-FR and GAM models with prediction rates of 0.851 and 0.846, respectively. Thus, the landslide susceptibility maps produced in the study area can be applied for management of hazards and risks in landslide-prone Hanyuan County.

New insights into susceptibility to glioma.

Science.gov (United States)

Liu, Yanhong; Shete, Sanjay; Hosking, Fay J; Robertson, Lindsay B; Bondy, Melissa L; Houlston, Richard S

2010-03-01

The study of inherited susceptibility to cancer has been one of the most informative areas of research in the past decade. Most of the cancer genetics studies have been focused on the common tumors such as breast and colorectal cancers. As the allelic architecture of these tumors is unraveled, research attention is turning to other rare cancers such as glioma, which are also likely to have a major genetic component as the basis of their development. In this brief review we discuss emerging data on glioma whole genome-association searches to identify risk loci. Two glioma genome-wide association studies have so far been reported. Our group identified 5 risk loci for glioma susceptibility (TERT rs2736100, CCDC26 rs4295627, CDKN2A/CDKN2B rs4977756, RTEL1 rs6010620, and PHLDB1 rs498872). Wrensch and colleagues provided further evidence to 2 risk loci (CDKN2B rs1412829 and RTEL1 rs6010620) for GBM and anaplastic astrocytoma. Although these data provide the strongest evidence to date for the role of common low-risk variants in the etiology of glioma, the single-nucleotide polymorphisms identified alone are unlikely to be candidates for causality. Identifying the causal variant at each specific locus and its biological impact now poses a significant challenge, contingent on a combination of fine mapping and functional analyses. Finally, we hope that a greater understanding of the biological basis of the disease will lead to the development of novel therapeutic interventions.

Extraction of the predisposition parameters for mapping the susceptibility of slides lands, in the region of EL Quola, province of Larache (Nothern Rif

Directory of Open Access Journals (Sweden)

El hamdouni Ikram

2018-01-01

Full Text Available Slide lands (Lands mass movements are among the natural risks that Morocco faces in the Rifaines regions in particular. They generally constitute small-scale, punctual phenomena. But their diversity and frequency are nevertheless responsible for significant and costly damages and injuries. To deal with this problem, the study of field instabilities must take into account that: ithe ground movements must be taken in a context of the overall dynamics of the watershed, ii-the choice of more objective methods, which is not based on the very subjective opinion of the expert; iii-the choice of an adapted approach to the scale of work. In this article, we used the evidence theory "WofE" to evaluate the sensibility of landslide in the El Quola area. This method is based on the analysis of the relationships between landslides that occurred in the past (the so-called modelable variable Vm and the spatial distribution of some predictive parameters of instability (Vp. The result obtained is a landslide susceptibility map that is the result of multi-disciplinary and multi-temporal data. This method has been described as one of the most performing by several authors; however, it requires a conditional independence between the different predictive factors. The quality of the performances was evaluated with success curves.

Nonlinear electromagnetic susceptibilities of unmagnetized plasmas

International Nuclear Information System (INIS)

Yoon, Peter H.

2005-01-01

Fully electromagnetic nonlinear susceptibilities of unmagnetized plasmas are analyzed in detail. Concrete expressions of the second-order nonlinear susceptibility are found in various forms in the literature, usually in connection with the discussions of various three-wave decay processes, but the third-order susceptibilities are rarely discussed. The second-order susceptibility is pertinent to nonlinear wave-wave interactions (i.e., the decay/coalescence), whereas the third-order susceptibilities affect nonlinear wave-particle interactions (i.e., the induced scattering). In the present article useful approximate analytical expressions of these nonlinear susceptibilities that can be readily utilized in various situations are derived

The Role of Abcb5 Alleles in Susceptibility to Haloperidol-Induced Toxicity in Mice and Humans

Science.gov (United States)

Zheng, Ming; Zhang, Haili; Dill, David L.; Clark, J. David; Tu, Susan; Yablonovitch, Arielle L.; Tan, Meng How; Zhang, Rui; Rujescu, Dan; Wu, Manhong; Tessarollo, Lino; Vieira, Wilfred; Gottesman, Michael M.; Deng, Suhua; Eberlin, Livia S.; Zare, Richard N.; Billard, Jean-Martin; Gillet, Jean-Pierre; Li, Jin Billy; Peltz, Gary

2015-01-01

Background We know very little about the genetic factors affecting susceptibility to drug-induced central nervous system (CNS) toxicities, and this has limited our ability to optimally utilize existing drugs or to develop new drugs for CNS disorders. For example, haloperidol is a potent dopamine antagonist that is used to treat psychotic disorders, but 50% of treated patients develop characteristic extrapyramidal symptoms caused by haloperidol-induced toxicity (HIT), which limits its clinical utility. We do not have any information about the genetic factors affecting this drug-induced toxicity. HIT in humans is directly mirrored in a murine genetic model, where inbred mouse strains are differentially susceptible to HIT. Therefore, we genetically analyzed this murine model and performed a translational human genetic association study. Methods and Findings A whole genome SNP database and computational genetic mapping were used to analyze the murine genetic model of HIT. Guided by the mouse genetic analysis, we demonstrate that genetic variation within an ABC-drug efflux transporter (Abcb5) affected susceptibility to HIT. In situ hybridization results reveal that Abcb5 is expressed in brain capillaries, and by cerebellar Purkinje cells. We also analyzed chromosome substitution strains, imaged haloperidol abundance in brain tissue sections and directly measured haloperidol (and its metabolite) levels in brain, and characterized Abcb5 knockout mice. Our results demonstrate that Abcb5 is part of the blood-brain barrier; it affects susceptibility to HIT by altering the brain concentration of haloperidol. Moreover, a genetic association study in a haloperidol-treated human cohort indicates that human ABCB5 alleles had a time-dependent effect on susceptibility to individual and combined measures of HIT. Abcb5 alleles are pharmacogenetic factors that affect susceptibility to HIT, but it is likely that additional pharmacogenetic susceptibility factors will be discovered

The role of Abcb5 alleles in susceptibility to haloperidol-induced toxicity in mice and humans.

KAUST Repository

Zheng, Ming

2015-02-03

We know very little about the genetic factors affecting susceptibility to drug-induced central nervous system (CNS) toxicities, and this has limited our ability to optimally utilize existing drugs or to develop new drugs for CNS disorders. For example, haloperidol is a potent dopamine antagonist that is used to treat psychotic disorders, but 50% of treated patients develop characteristic extrapyramidal symptoms caused by haloperidol-induced toxicity (HIT), which limits its clinical utility. We do not have any information about the genetic factors affecting this drug-induced toxicity. HIT in humans is directly mirrored in a murine genetic model, where inbred mouse strains are differentially susceptible to HIT. Therefore, we genetically analyzed this murine model and performed a translational human genetic association study.A whole genome SNP database and computational genetic mapping were used to analyze the murine genetic model of HIT. Guided by the mouse genetic analysis, we demonstrate that genetic variation within an ABC-drug efflux transporter (Abcb5) affected susceptibility to HIT. In situ hybridization results reveal that Abcb5 is expressed in brain capillaries, and by cerebellar Purkinje cells. We also analyzed chromosome substitution strains, imaged haloperidol abundance in brain tissue sections and directly measured haloperidol (and its metabolite) levels in brain, and characterized Abcb5 knockout mice. Our results demonstrate that Abcb5 is part of the blood-brain barrier; it affects susceptibility to HIT by altering the brain concentration of haloperidol. Moreover, a genetic association study in a haloperidol-treated human cohort indicates that human ABCB5 alleles had a time-dependent effect on susceptibility to individual and combined measures of HIT. Abcb5 alleles are pharmacogenetic factors that affect susceptibility to HIT, but it is likely that additional pharmacogenetic susceptibility factors will be discovered.ABCB5 alleles alter susceptibility to

Antibiotic susceptibility profiles for mastitis treatment.

Science.gov (United States)

Hinckley, L S; Benson, R H; Post, J E; DeCloux, J C

1985-10-01

Susceptibility tests were performed on milk samples representing prevalent mastitis infections in certain herds. Susceptibility patterns of the same bacterial species from several mastitis infections in the same herd were consistent. The herd antibiotic susceptibility profiles were used as a basis for selecting antibiotics for treatment of all such mastitis cases in that herd. A high degree of correlation was seen between the susceptibility test results and treatment results. Susceptibility patterns of the same bacterial species from mastitis infections in different herds varied greatly, which indicated that any one antibiotic would not work equally well against the same bacterial infection in every herd. Therefore, treatment should be selected on the basis of susceptibility test results. When both Streptococcus and Staphylococcus mastitis occurred in the same herd, the susceptibility patterns for the 2 bacterial species varied widely. Therefore, for herds that experienced both streptococcal and staphylococcal mastitis, antibiotics to which both bacterial species were susceptible were used for treatment.

An Ensemble Model for Co-Seismic Landslide Susceptibility Using GIS and Random Forest Method

Directory of Open Access Journals (Sweden)

Suchita Shrestha

2017-11-01

Full Text Available The Mw 7.8 Gorkha earthquake of 25 April 2015 triggered thousands of landslides in the central part of the Nepal Himalayas. The main goal of this study was to generate an ensemble-based map of co-seismic landslide susceptibility in Sindhupalchowk District using model comparison and combination strands. A total of 2194 co-seismic landslides were identified and were randomly split into 1536 (~70%, to train data for establishing the model, and the remaining 658 (~30% for the validation of the model. Frequency ratio, evidential belief function, and weight of evidence methods were applied and compared using 11 different causative factors (peak ground acceleration, epicenter proximity, fault proximity, geology, elevation, slope, plan curvature, internal relief, drainage proximity, stream power index, and topographic wetness index to prepare the landslide susceptibility map. An ensemble of random forest was then used to overcome the various prediction limitations of the individual models. The success rates and prediction capabilities were critically compared using the area under the curve (AUC of the receiver operating characteristic curve (ROC. By synthesizing the results of the various models into a single score, the ensemble model improved accuracy and provided considerably more realistic prediction capacities (91% than the frequency ratio (81.2%, evidential belief function (83.5% methods, and weight of evidence (80.1%.

Reprint of "A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping"

Science.gov (United States)

Crozier, M. J.

2018-04-01

Multiple-occurrence regional landslide events (MORLEs) consist of hundreds to thousands of shallow landslides occurring more or less simultaneously within defined areas, ranging from tens to thousands of square kilometres. While MORLEs can be triggered by rainstorms and earthquakes, this paper is confined to those landslide events triggered by rainstorms. Globally, MORLEs occur in a range of geological settings in areas of moderate to steep slopes subject to intense rainstorms. Individual landslides in rainstorm-triggered events are dominantly small, shallow debris and earth flows, and debris and earth slides involving regolith or weathered bedrock. The model used to characterise these events assumes that energy distribution within the event area is represented on the land surface by a cell structure; with maximum energy expenditure within an identifiable core and rapid dissipation concentrically away from the centre. The version of the model presented here has been developed for rainfall-triggered landslide events. It proposes that rainfall intensity can be used to determine different critical landslide response zones within the cell (referred to as core, middle, and periphery zones). These zones are most readily distinguished by two conditions: the proportion of the slope that fails and the particular type of the slope stability factor that assumes dominance in determining specific sites of landslide occurrence. The latter condition means that the power of any slope stability factor to distinguish between stable and unstable sites varies throughout the affected area in accordance with the landslide response zones within the cell; certain factors critical for determining the location of landslide sites in one part of the event area have little influence in other parts of the event area. The implication is that landslide susceptibility maps (and subsequently derived mitigation measures) based on conventional slope stability factors may have only limited validity

Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

NARCIS (Netherlands)

J. Shi (Jiajun); Zhang, Y. (Yanfeng); W. Zheng (Wei); K. Michailidou (Kyriaki); M. Ghoussaini (Maya); M.K. Bolla (Manjeet K.); Wang, Q. (Qin); J. Dennis (Joe); Lush, M. (Michael); R.L. Milne (Roger); X.-O. Shu (Xiao-Ou); J. Beesley (Jonathan); S. Kar (Siddhartha); I.L. Andrulis (Irene); H. Anton-Culver (Hoda); Arndt, V. (Volker); M.W. Beckmann (Matthias); Z. Zhao (Zhiguo); Guo, X. (Xingyi); J. Benítez (Javier); A. Beeghly-Fadiel (Alicia); W.J. Blot (William); N.V. Bogdanova (Natalia); S.E. Bojesen (Stig); H. Brauch (Hiltrud); H. Brenner (Hermann); L.A. Brinton (Louise); A. Broeks (Annegien); T. Brüning (Thomas); B. Burwinkel (Barbara); H. Cai (Hui); S. Canisius (Sander); J. Chang-Claude (Jenny); Choi, J.-Y. (Ji-Yeob); F.J. Couch (Fergus); A. Cox (Angela); S.S. Cross (Simon); K. Czene (Kamila); H. Darabi (Hatef); P. Devilee (Peter); A. Droit (Arnaud); T. Dörk (Thilo); P.A. Fasching (Peter); O. Fletcher (Olivia); H. Flyger (Henrik); F. Fostira (Florentia); Gaborieau, V. (Valerie); M. García-Closas (Montserrat); G.G. Giles (Graham); Grip, M. (Mervi); P. Guénel (Pascal); C.A. Haiman (Christopher A.); U. Hamann (Ute); J.M. Hartman (Joost); X. Miao; A. Hollestelle (Antoinette); J.L. Hopper (John); Hsiung, C.-N. (Chia-Ni); H. Ito (Hidemi); A. Jakubowska (Anna); Johnson, N. (Nichola); D. Torres (Diana); M. Kabisch (Maria); D. Kang (Daehee); S. Khan (Sofia); J.A. Knight (Julia); V-M. Kosma (Veli-Matti); Lambrechts, D. (Diether); J. Li (Jingmei); A. Lindblom (Annika); A. Lophatananon (Artitaya); J. Lubinski (Jan); A. Mannermaa (Arto); S. Manoukian (Siranoush); L. Le Marchand (Loic); S. Margolin (Sara); Marme, F. (Frederik); K. Matsuo (Keitaro); C.A. McLean (Catriona Ann); A. Meindl (Alfons); K.R. Muir (K.); S.L. Neuhausen (Susan); H. Nevanlinna (Heli); S. Nord (Silje); A.-L. Borresen-Dale (Anne-Lise); J.E. Olson (Janet); N. Orr (Nick); A.M.W. van den Ouweland (Ans); P. Peterlongo (Paolo); T.C. Putti (Thomas Choudary); Rudolph, A. (Anja); Sangrajrang, S. (Suleeporn); E.J. Sawyer (Elinor); M.K. Schmidt (Marjanka); R.K. Schmutzler (Rita); C.-Y. Shen (Chen-Yang); M.-F. Hou (Ming-Feng); M. Shrubsole (Martha); M.C. Southey (Melissa); A.J. Swerdlow (Anthony ); Hwang Teo, S. (Soo); B. Thienpont (Bernard); A.E. Toland (Amanda); R.A.E.M. Tollenaar (Rob); I.P. Tomlinson (Ian); T. Truong (Thérèse); C.-C. Tseng (Chiu-Chen); W. Wen (Wanqing); R. Winqvist (Robert); A.H. Wu (Anna); C. Har Yip (Cheng); P.M. Zamora (Pilar M.); Zheng, Y. (Ying); O.A.M. Floris; Cheng, C.-Y. (Ching-Yu); M.J. Hooning (Maartje); J.W.M. Martens (John); C.M. Seynaeve (Caroline); V. Kristensen (Vessela); P. Hall (Per); P.D.P. Pharoah (Paul); J. Simard (Jacques); G. Chenevix-Trench (Georgia); A.M. Dunning (Alison); A.C. Antoniou (Antonis C.); D.F. Easton (Douglas F.); Q. Cai (Qiuyin); J. Long (Jirong)

2016-01-01

textabstractPrevious genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb

Variants in linkage disequilibrium with the late cornified envelope gene cluster deletion are associated with susceptibility to psoriatic arthritis.

LENUS (Irish Health Repository)

Bowes, John

2010-12-01

A common deletion mapping to the psoriasis susceptibility locus 4 on chromosome 1q21, encompassing two genes of the late cornified envelope (LCE) gene cluster, has been associated with an increased risk of psoriasis vulgaris (PsV). One previous report found no association of the deletion with psoriatic arthritis (PsA), suggesting it may be a specific risk factor for PsV. Given the genetic overlap between PsA and PsV, a study was undertaken to investigate whether single nucleotide polymorphisms (SNPs) mapping to this locus are risk factors for PsA in a UK and Irish population.

Personality traits as potential susceptibility markers : Differential susceptibility to support among parents

NARCIS (Netherlands)

Slagt, M.; Dubas, J.S.; Denissen, J.J.A.; Deković, M.; van Aken, M.A.G.

2015-01-01

In this study, we examined whether parents are differentially susceptible to support from their spouse and adolescent child depending on their personality traits, and whether differences in susceptibility to support among parents, in turn, are linked to the quality of support parents give to their

Landscape susceptibility, hazard and risk assessments along pipeline corridors in Canada

Energy Technology Data Exchange (ETDEWEB)

Blais-Stevens, A.; Couture, R.; Page, A. [Natural Resources Canada, Ottawa, ON (Canada). Geological Survey of Canada; Koch, J.; Clague, J.J. [Simon Fraser Univ., Burnaby, BC (Canada); Lipovsky, P.S. [Yukon Geological Survey, Whitehorse, YT (Canada)

2010-07-01

This article discussed work that was carried out to inventory landslides and assess hazards along two proposed gas-pipeline routes in the North. Landslide inventories and hazard assessments are necessary to quantify and qualify the risk of environmental impacts from landslides on linear infrastructure. The Yukon Alaska Highway Pipeline and the Mackenzie Gas Project Pipeline, which will both be over 800 kilometres in length, will cross harsh landscapes characterized by permafrost terrain and will be at risk from geological hazards, including landslides with debris flows, earthquakes, subsidence, and permafrost degradation. The work involved inventorying and mapping landslides via aerial photography and field visits to identify the frequency-magnitude relationships for debris flow fans along the route and the creation of qualitative parametric landslide maps for both proposed pipeline corridors. A good correlation was found between actual landslide distribution and the landslide susceptibility maps. For the Mackenzie Valley Pipeline Corridor, most landslides have occurred in fine unconsolidated sediments and shallow slopes. Landslides in the Yukon Alaska Highway Corridor mostly happened in unconsolidated sediments, but a few took place in bedrock with high relief. The preliminary investigation revealed that a slope hazard exists in both corridors and must be taken into account during pipeline development. The results are intended to facilitate better decision-making for planning, constructing, and maintaining safe and economically viable pipeline routes in Northern Canada. The mapping methodology was outlined. 13 refs., 1 tab., 6 figs.

Modelling mass movement susceptibility for Alpine infrastructure in the Karavank Mountains (Austria/Slovenia)

Science.gov (United States)

Bauer, C.; Kern, K.; Lieb, G. K.

2012-12-01

The aim of this study is the generation of indicative susceptibility maps on a regional scale that can be used as a decision support tool for land use management (i.e. risk potential on alpine infrastructure). The study in particular focuses on geomorphological processes (rockfall and debris flows in unconsolidated rock) that reshape the land surface by erosion, transport and deposition. When interacting with human activity (e.g. road, alpine trails) such naturally occurring processes can quickly become natural hazards. The study area is located in the Karavank Mountains, a border region between Austria and Slovenia, and covers approx. 200 sq km with maximum altitudes above 2.000 m a.s.l. (Hochstuhl: 2.237 m a.s.l.). The Karavanks form an east-west striking mountain chain (approx. 120 km total length) of the southeastern Alps that consists mainly of thick Triassic carbonate sequences and, with less extent, Paleozoic carbonate rocks crystalline rocks. The mountain chain is separated into the Northern Karavanks and the Southern Karavanks by a structural boundary (Periadriatic Line). In addition, the area is known for extreme weather events due to Adriatic cyclones with daily accumulated precipitation of more than 200 mm that regularly trigger hazardous and torrential processes like rockfall events and debris flows. To assess the triggering factors and trajectories, two different disposition and process models (one for rockfall and one for debris flow, respectively) were developed. The information about potential source areas was obtained by combining various types of information (e.g. DTM derivatives, geotechnical units, vegetation). Threshold slope values for potential rockfall source areas were attributed to different lithological units according to field observations. The defined threshold slope angles cover values from 42° in Triassic carbonates up to 46° in massive crystalline rocks. For debris flows areas with a slope inclination model is based on the idea

The development of flood map in Malaysia

Science.gov (United States)

Zakaria, Siti Fairus; Zin, Rosli Mohamad; Mohamad, Ismail; Balubaid, Saeed; Mydin, Shaik Hussein; MDR, E. M. Roodienyanto

2017-11-01

In Malaysia, flash floods are common occurrences throughout the year in flood prone areas. In terms of flood extent, flash floods affect smaller areas but because of its tendency to occur in densely urbanized areas, the value of damaged property is high and disruption to traffic flow and businesses are substantial. However, in river floods especially the river floods of Kelantan and Pahang, the flood extent is widespread and can extend over 1,000 square kilometers. Although the value of property and density of affected population is lower, the damage inflicted by these floods can also be high because the area affected is large. In order to combat these floods, various flood mitigation measures have been carried out. Structural flood mitigation alone can only provide protection levels from 10 to 100 years Average Recurrence Intervals (ARI). One of the economically effective non-structural approaches in flood mitigation and flood management is using a geospatial technology which involves flood forecasting and warning services to the flood prone areas. This approach which involves the use of Geographical Information Flood Forecasting system also includes the generation of a series of flood maps. There are three types of flood maps namely Flood Hazard Map, Flood Risk Map and Flood Evacuation Map. Flood Hazard Map is used to determine areas susceptible to flooding when discharge from a stream exceeds the bank-full stage. Early warnings of incoming flood events will enable the flood victims to prepare themselves before flooding occurs. Properties and life's can be saved by keeping their movable properties above the flood levels and if necessary, an early evacuation from the area. With respect to flood fighting, an early warning with reference through a series of flood maps including flood hazard map, flood risk map and flood evacuation map of the approaching flood should be able to alert the organization in charge of the flood fighting actions and the authority to

Natural-focal diseases: mapping experience in Russia.

Science.gov (United States)

Malkhazova, Svetlana M; Mironova, Varvara A; Kotova, Tatiana V; Shartova, Natalia V; Orlov, Dmitry S

2014-06-14

. Taken in entirety, the maps that have been prepared for the Atlas will enable researchers to evaluate the stability of epidemic manifestation of individual diseases and the susceptibility of a given territory to disease transmission. The results can be used for sanitary monitoring and disease prevention.

Mapping soil total nitrogen of cultivated land at county scale by using hyperspectral image

Science.gov (United States)

Gu, Xiaohe; Zhang, Li Yan; Shu, Meiyan; Yang, Guijun

2018-02-01

Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agriculture. The study aimed to develop a universal method to map total nitrogen content in soil of cultivated land by HSI image at county scale. Several mathematical transformations were used to improve the expression ability of HSI image. The correlations between soil TNC and the reflectivity and its mathematical transformations were analyzed. Then the susceptible bands and its transformations were screened to develop the optimizing model of map soil TNC in the Anping County based on the method of multiple linear regression. Results showed that the bands of 14th, 16th, 19th, 37th and 60th with different mathematical transformations were screened as susceptible bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. The determination coefficient of the first order differential of logarithmic transformation was biggest (0.505), while the RMSE was lowest. The study confirmed the first order differential of logarithm transformation as the optimal inversion model for soil TNC, which was used to map soil TNC of cultivated land in the study area.

Spatial prediction of ground subsidence susceptibility using an artificial neural network.

Science.gov (United States)

Lee, Saro; Park, Inhye; Choi, Jong-Kuk

2012-02-01

Ground subsidence in abandoned underground coal mine areas can result in loss of life and property. We analyzed ground subsidence susceptibility (GSS) around abandoned coal mines in Jeong-am, Gangwon-do, South Korea, using artificial neural network (ANN) and geographic information system approaches. Spatial data of subsidence area, topography, and geology, as well as various ground-engineering data, were collected and used to create a raster database of relevant factors for a GSS map. Eight major factors causing ground subsidence were extracted from the existing ground subsidence area: slope, depth of coal mine, distance from pit, groundwater depth, rock-mass rating, distance from fault, geology, and land use. Areas of ground subsidence were randomly divided into a training set to analyze GSS using the ANN and a test set to validate the predicted GSS map. Weights of each factor's relative importance were determined by the back-propagation training algorithms and applied to the input factor. The GSS was then calculated using the weights, and GSS maps were created. The process was repeated ten times to check the stability of analysis model using a different training data set. The map was validated using area-under-the-curve analysis with the ground subsidence areas that had not been used to train the model. The validation showed prediction accuracies between 94.84 and 95.98%, representing overall satisfactory agreement. Among the input factors, "distance from fault" had the highest average weight (i.e., 1.5477), indicating that this factor was most important. The generated maps can be used to estimate hazards to people, property, and existing infrastructure, such as the transportation network, and as part of land-use and infrastructure planning.

Topographical mapping system for hazardous and radiological environments

International Nuclear Information System (INIS)

Armstrong, G.A.; Burks, B.L.; Bernacki, B.E.; Pardini, A.

1995-01-01

This report focuses on the results of the acceptance test of the Topographical Mapping System (TMS) delivered to the Hanford site. The TMS was tested for accuracy over the specified range of 45 feet. The TMS was also tested to ensure that the unit could be deployed through multiple risers and maintain accuracy and registration of the surface mapping data. In addition, the TMS was disassembled and reassembled and redeployed to test field replacement of modules that make up the sensor head that is deployed in the vapor space of Underground Storage Tanks such as those located at the Hanford site in southeastern Washington State. The results from these tests along with temperature testing on the complete system and radiation testing of selected susceptible components are covered in this report. The primary purpose of the TMS is to generate reliable and accurate three-dimensional maps of the internal surfaces of storage tank. One use for these mapping systems is in creating and maintaining a current map of the tank interior as input to a robotic ''world model'' that is used to test remediation strategies or plan robot trajectories. Another use is tracking the movement of the waste surface as it responds to expanding bubbles of trapped Gas. A third use of the TMS is to perform a volumetric analysis of the amount of waste removed from the tanks during remediation

Polarized Neutron Diffraction as a Tool for Mapping Molecular Magnetic Anisotropy: Local Susceptibility Tensors in Co(II) Complexes.

Science.gov (United States)

Ridier, Karl; Gillon, Béatrice; Gukasov, Arsen; Chaboussant, Grégory; Cousson, Alain; Luneau, Dominique; Borta, Ana; Jacquot, Jean-François; Checa, Ruben; Chiba, Yukako; Sakiyama, Hiroshi; Mikuriya, Masahiro

2016-01-11

Polarized neutron diffraction (PND) experiments were carried out at low temperature to characterize with high precision the local magnetic anisotropy in two paramagnetic high-spin cobalt(II) complexes, namely [Co(II) (dmf)6 ](BPh4 )2 (1) and [Co(II) 2 (sym-hmp)2 ](BPh4 )2 (2), in which dmf=N,N-dimethylformamide; sym-hmp=2,6-bis[(2-hydroxyethyl)methylaminomethyl]-4-methylphenolate, and BPh4 (-) =tetraphenylborate. This allowed a unique and direct determination of the local magnetic susceptibility tensor on each individual Co(II) site. In compound 1, this approach reveals the correlation between the single-ion easy magnetization direction and a trigonal elongation axis of the Co(II) coordination octahedron. In exchange-coupled dimer 2, the determination of the individual Co(II) magnetic susceptibility tensors provides a clear outlook of how the local magnetic properties on both Co(II) sites deviate from the single-ion behavior because of antiferromagnetic exchange coupling. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Drosophila model for toxicogenomics: Genetic variation in susceptibility to heavy metal exposure.

Directory of Open Access Journals (Sweden)

Shanshan Zhou

2017-07-01

Full Text Available The genetic factors that give rise to variation in susceptibility to environmental toxins remain largely unexplored. Studies on genetic variation in susceptibility to environmental toxins are challenging in human populations, due to the variety of clinical symptoms and difficulty in determining which symptoms causally result from toxic exposure; uncontrolled environments, often with exposure to multiple toxicants; and difficulty in relating phenotypic effect size to toxic dose, especially when symptoms become manifest with a substantial time lag. Drosophila melanogaster is a powerful model that enables genome-wide studies for the identification of allelic variants that contribute to variation in susceptibility to environmental toxins, since the genetic background, environmental rearing conditions and toxic exposure can be precisely controlled. Here, we used extreme QTL mapping in an outbred population derived from the D. melanogaster Genetic Reference Panel to identify alleles associated with resistance to lead and/or cadmium, two ubiquitous environmental toxins that present serious health risks. We identified single nucleotide polymorphisms (SNPs associated with variation in resistance to both heavy metals as well as SNPs associated with resistance specific to each of them. The effects of these SNPs were largely sex-specific. We applied mutational and RNAi analyses to 33 candidate genes and functionally validated 28 of them. We constructed networks of candidate genes as blueprints for orthologous networks of human genes. The latter not only provided functional contexts for known human targets of heavy metal toxicity, but also implicated novel candidate susceptibility genes. These studies validate Drosophila as a translational toxicogenomics gene discovery system.

Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: a comparison between GLM, GAM, MARS, and M-AHP methods

Science.gov (United States)

Pourghasemi, Hamid Reza; Rossi, Mauro

2017-10-01

Landslides are identified as one of the most important natural hazards in many areas throughout the world. The essential purpose of this study is to compare general linear model (GLM), general additive model (GAM), multivariate adaptive regression spline (MARS), and modified analytical hierarchy process (M-AHP) models and assessment of their performances for landslide susceptibility modeling in the west of Mazandaran Province, Iran. First, landslides were identified by interpreting aerial photographs, and extensive field works. In total, 153 landslides were identified in the study area. Among these, 105 landslides were randomly selected as training data (i.e. used in the models training) and the remaining 48 (30 %) cases were used for the validation (i.e. used in the models validation). Afterward, based on a deep literature review on 220 scientific papers (period between 2005 and 2012), eleven conditioning factors including lithology, land use, distance from rivers, distance from roads, distance from faults, slope angle, slope aspect, altitude, topographic wetness index (TWI), plan curvature, and profile curvature were selected. The Certainty Factor (CF) model was used for managing uncertainty in rule-based systems and evaluation of the correlation between the dependent (landslides) and independent variables. Finally, the landslide susceptibility zonation was produced using GLM, GAM, MARS, and M-AHP models. For evaluation of the models, the area under the curve (AUC) method was used and both success and prediction rate curves were calculated. The evaluation of models for GLM, GAM, and MARS showed 90.50, 88.90, and 82.10 % for training data and 77.52, 70.49, and 78.17 % for validation data, respectively. Furthermore, The AUC value of the produced landslide susceptibility map using M-AHP showed a training value of 77.82 % and validation value of 82.77 % accuracy. Based on the overall assessments, the proposed approaches showed reasonable results for landslide

Candidate chromosome 1 disease susceptibility genes for Sjogren’s syndrome xerostomia are narrowed by novel NOD.B10 congenic mice

Science.gov (United States)

Mongini, Patricia K. A.; Kramer, Jill M.; Ishikawa, Tomo-o; Herschman, Harvey; Esposito, Donna

2014-01-01

Sjogren’s syndrome (SS) is characterized by salivary gland leukocytic infiltrates and impaired salivation (xerostomia). Cox-2 (Ptgs2) is located on chromosome 1 within the span of the Aec2 region. In an attempt to demonstrate that COX-2 drives antibody-dependent hyposalivation, NOD.B10 congenic mice bearing a Cox-2flox gene were generated. A congenic line with non-NOD alleles in Cox-2-flanking genes failed manifest xerostomia. Further backcrossing yielded disease-susceptible NOD.B10 Cox-2flox lines; fine genetic mapping determined that critical Aec2 genes lie within a 1.56 to 2.17 Mb span of DNA downstream of Cox-2. Bioinformatics analysis revealed that susceptible and non-susceptible lines exhibit non-synonymous coding SNPs in 8 protein-encoding genes of this region, thereby better delineating candidate Aec2 alleles needed for SS xerostomia. PMID:24685748

Refined candidate region specified by haplotype sharing for Escherichia coli F4ab/F4ac susceptibility alleles in pigs

DEFF Research Database (Denmark)

Jacobsen, Mette Juul; Kracht, Steffen Skaarup; Esteso, G.

2009-01-01

Infection of the small intestine by enterotoxigenic Escherichia coli F4ab/ac is a major welfare problem and financial burden for the pig industry. Natural resistance to this infection is inherited as a Mendelian recessive trait, and a polymorphism in the MUC4 gene segregating for susceptibility....../resistance is presently used in a selection programme by the Danish pig breeding industry. To elucidate the genetic background involved in E. coli F4ab/ac susceptibility in pigs, a detailed haplotype map of the porcine candidate region was established. This region covers approximately 3.7 Mb. The material used...... for the study is a three generation family, where the founders are two Wild boars and eight Large White sows. All pigs have been phenotyped for susceptibility to F4ab/ac using an adhesion assay. Their haplotypes are known from segregation analysis using flanking markes. By a targeted approach, the candidate...

Fine-Mapping the HOXB Region Detects Common Variants Tagging a Rare Coding Allele

DEFF Research Database (Denmark)

Saunders, Edward J; Dadaev, Tokhir; Leongamornlert, Daniel A

2014-01-01

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs u...

Spatial correlation between the predictor variables and the weighting values calculated during the mapping of the environmental factors of mass movements in the Beni Idder region (northern Rif

Directory of Open Access Journals (Sweden)

Ait Brahim L.

2018-01-01

Full Text Available The Tleta of Beni Ider region located in the SW of Tetouan (Rif Septentrional knows many mass instabilities. The diagnostic via the inventory, the mapping and the characterization of mass movements was made by using satellite imagery, aerial photography and field data coupled with existing documents (geological, geomorphological,…. The understanding of both their spatial distribution and the mechanism generating them, is very complex because of the existence of an important number of natural factors (geological, geomorphological, hydrological in a relative mountainous landscape with deep valleys, steep slopes and significant elevation changes. Thus, a multidisciplinary approach was adopted to elaborate the landslide susceptibility map of the region taking into account interactions and causal relationships between the various natural parameters that tend to accentuate and aggravate the setting of landslides. The multidisciplinary database allowed us to evaluate the susceptibility thanks to a bivariate probabiliste model (Weight of Evidence. The obtained landslide susceptibility map is a major contribution to the development of urban development plans in the region.

Clinical high-resolution mapping of the proteoglycan-bound water fraction in articular cartilage of the human knee joint.

Science.gov (United States)

Bouhrara, Mustapha; Reiter, David A; Sexton, Kyle W; Bergeron, Christopher M; Zukley, Linda M; Spencer, Richard G

2017-11-01

We applied our recently introduced Bayesian analytic method to achieve clinically-feasible in-vivo mapping of the proteoglycan water fraction (PgWF) of human knee cartilage with improved spatial resolution and stability as compared to existing methods. Multicomponent driven equilibrium single-pulse observation of T 1 and T 2 (mcDESPOT) datasets were acquired from the knees of two healthy young subjects and one older subject with previous knee injury. Each dataset was processed using Bayesian Monte Carlo (BMC) analysis incorporating a two-component tissue model. We assessed the performance and reproducibility of BMC and of the conventional analysis of stochastic region contraction (SRC) in the estimation of PgWF. Stability of the BMC analysis of PgWF was tested by comparing independent high-resolution (HR) datasets from each of the two young subjects. Unlike SRC, the BMC-derived maps from the two HR datasets were essentially identical. Furthermore, SRC maps showed substantial random variation in estimated PgWF, and mean values that differed from those obtained using BMC. In addition, PgWF maps derived from conventional low-resolution (LR) datasets exhibited partial volume and magnetic susceptibility effects. These artifacts were absent in HR PgWF images. Finally, our analysis showed regional variation in PgWF estimates, and substantially higher values in the younger subjects as compared to the older subject. BMC-mcDESPOT permits HR in-vivo mapping of PgWF in human knee cartilage in a clinically-feasible acquisition time. HR mapping reduces the impact of partial volume and magnetic susceptibility artifacts compared to LR mapping. Finally, BMC-mcDESPOT demonstrated excellent reproducibility in the determination of PgWF. Published by Elsevier Inc.

Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba

Science.gov (United States)

Melchiorre, C.; Castellanos Abella, E. A.; van Westen, C. J.; Matteucci, M.

2011-04-01

This paper describes a procedure for landslide susceptibility assessment based on artificial neural networks, and focuses on the estimation of the prediction capability, robustness, and sensitivity of susceptibility models. The study is carried out in the Guantanamo Province of Cuba, where 186 landslides were mapped using photo-interpretation. Twelve conditioning factors were mapped including geomorphology, geology, soils, landuse, slope angle, slope direction, internal relief, drainage density, distance from roads and faults, rainfall intensity, and ground peak acceleration. A methodology was used that subdivided the database in 3 subsets. A training set was used for updating the weights. A validation set was used to stop the training procedure when the network started losing generalization capability, and a test set was used to calculate the performance of the network. A 10-fold cross-validation was performed in order to show that the results are repeatable. The prediction capability, the robustness analysis, and the sensitivity analysis were tested on 10 mutually exclusive datasets. The results show that by means of artificial neural networks it is possible to obtain models with high prediction capability and high robustness, and that an exploration of the effect of the individual variables is possible, even if they are considered as a black-box model.

Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

Science.gov (United States)

García-Rodríguez, M. J.; Malpica, J. A.

2010-06-01

This paper presents an approach for assessing earthquake-triggered landslide susceptibility using artificial neural networks (ANNs). The computational method used for the training process is a back-propagation learning algorithm. It is applied to El Salvador, one of the most seismically active regions in Central America, where the last severe destructive earthquakes occurred on 13 January 2001 (Mw 7.7) and 13 February 2001 (Mw 6.6). The first one triggered more than 600 landslides (including the most tragic, Las Colinas landslide) and killed at least 844 people. The ANN is designed and programmed to develop landslide susceptibility analysis techniques at a regional scale. This approach uses an inventory of landslides and different parameters of slope instability: slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness. The information obtained from ANN is then used by a Geographic Information System (GIS) to map the landslide susceptibility. In a previous work, a Logistic Regression (LR) was analysed with the same parameters considered in the ANN as independent variables and the occurrence or non-occurrence of landslides as dependent variables. As a result, the logistic approach determined the importance of terrain roughness and soil type as key factors within the model. The results of the landslide susceptibility analysis with ANN are checked using landslide location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone. Finally, a comparative analysis of the ANN and LR models are made. The advantages and disadvantages of both approaches are discussed using Receiver Operating Characteristic (ROC) curves.

SU-D-207A-04: Use of Gradient Echo Plural Contrast Imaging (GEPCI) in MR-Guided Radiation Therapy: A Feasibility Study Targeting Brain Treatment

International Nuclear Information System (INIS)

Cai, B; Rao, Y; Tsien, C; Huang, J; Green, O; Mutic, S; Gach, H; Wen, J; Yablonskiy, D

2016-01-01

Purpose: To implement the Gradient Echo Plural Contrast Imaging(GEPCI) technique in MRI-simulation for radiation therapy and assess the feasibility of using GEPCI images with advanced inhomogeneity correction in MRI-guided radiotherapy for brain treatment. Methods: An optimized multigradient-echo GRE sequence (TR=50ms;TE1=4ms;delta-TE=4ms;flip angle=300,11 Echoes) was developed to generate both structural (T1w and T2*w) and functional MRIs (field and susceptibility maps) from a single acquisition. One healthy subject (Subject1) and one post-surgical brain cancer patient (Subject2) were scanned on a Philips Ingenia 1.5T MRI used for radiation therapy simulation. Another healthy subject (Subject3) was scanned on a 0.35T MRI-guided radiotherapy (MR-IGRT) system (ViewRay). A voxel spread function (VSF) was used to correct the B0 inhomogeneities caused by surgical cavities and edema for Subject2. GEPCI images and standard radiotherapy planning MRIs for this patient were compared focusing the delineation of radiotherapy target region. Results: GEPCI brain images were successfully derived from all three subjects with scan times of <7 minutes. The images derived for Subjects1&2 demonstrated that GEPCI can be applied and combined into radiotherapy MRI simulation. Despite low field, T1-weighted and R2* images were successfully reconstructed for Subject3 and were satisfactory for contour and target delineation. The R2* distribution of grey matter (center=12,FWHM=4.5) and white matter (center=14.6, FWHM=2) demonstrated the feasibility for tissue segmentation and quantification. The voxel spread function(VSF) corrected surgical site related inhomogeneities for Subject2. R2* and quantitative susceptibility map(QSM) images for Subject2 can be used to quantitatively assess the brain structure response to radiation over the treatment course. Conclusion: We implemented the GEPCI technique in MRI-simulation and in MR-IGRT system for radiation therapy. The images demonstrated that it

Quantification of susceptibility change at high-concentrated SPIO-labeled target by characteristic phase gradient recognition.

Science.gov (United States)

Zhu, Haitao; Nie, Binbin; Liu, Hua; Guo, Hua; Demachi, Kazuyuki; Sekino, Masaki; Shan, Baoci

2016-05-01

Phase map cross-correlation detection and quantification may produce highlighted signal at superparamagnetic iron oxide nanoparticles, and distinguish them from other hypointensities. The method may quantify susceptibility change by performing least squares analysis between a theoretically generated magnetic field template and an experimentally scanned phase image. Because characteristic phase recognition requires the removal of phase wrap and phase background, additional steps of phase unwrapping and filtering may increase the chance of computing error and enlarge the inconsistence among algorithms. To solve problem, phase gradient cross-correlation and quantification method is developed by recognizing characteristic phase gradient pattern instead of phase image because phase gradient operation inherently includes unwrapping and filtering functions. However, few studies have mentioned the detectable limit of currently used phase gradient calculation algorithms. The limit may lead to an underestimation of large magnetic susceptibility change caused by high-concentrated iron accumulation. In this study, mathematical derivation points out the value of maximum detectable phase gradient calculated by differential chain algorithm in both spatial and Fourier domain. To break through the limit, a modified quantification method is proposed by using unwrapped forward differentiation for phase gradient generation. The method enlarges the detectable range of phase gradient measurement and avoids the underestimation of magnetic susceptibility. Simulation and phantom experiments were used to quantitatively compare different methods. In vivo application performs MRI scanning on nude mice implanted by iron-labeled human cancer cells. Results validate the limit of detectable phase gradient and the consequent susceptibility underestimation. Results also demonstrate the advantage of unwrapped forward differentiation compared with differential chain algorithms for susceptibility

High density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

Science.gov (United States)

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I.; Padyukov, Leonid; Toes, Rene E.M.; Huizinga, Tom W.J.; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I.W.; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A.; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-01-01

Summary Using the Immunochip custom single nucleotide polymorphism (SNP) array, designed for dense genotyping of 186 genome wide association study (GWAS) confirmed loci we analysed 11,475 rheumatoid arthritis cases of European ancestry and 15,870 controls for 129,464 markers. The data were combined in meta-analysis with GWAS data from additional independent cases (n=2,363) and controls (n=17,872). We identified fourteen novel loci; nine were associated with rheumatoid arthritis overall and 5 specifically in anti-citrillunated peptide antibody positive disease, bringing the number of confirmed European ancestry rheumatoid arthritis loci to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at six loci and association to low frequency variants (minor allele frequency <0.05) at 4 loci. Bioinformatic analysis of the data generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations. PMID:23143596

Groundwater vulnerability assessment using hydrogeologic and geoelectric layer susceptibility indexing at Igbara Oke, Southwestern Nigeria

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T.E. Oni

2017-12-01

Full Text Available Groundwater vulnerability assessment was carried out at Igbara Oke Southwestern Nigeria, with a view to classify the area into vulnerability zones, by applying the electrical resistivity method, using Schlumberger electrode arrays with maximum electrode separation (AB/2 of 65 m in (41 different locations for data acquisition. Geoelectric parameters (layer resistivity and thickness were determined from the interpreted data. The study area comprises four geoelectric layers (topsoil, lateritic layer, weathered/fractured layer and fresh basement. The geoelectric parameters of the overlying layers across the area were used to assess the vulnerability of the underlying aquifers to near-surface contaminants with the aid of vulnerability maps generated. Three models were compared by maps using geo-electrically derived models; longitudinal conductance, GOD (groundwater occurrence, overlying lithology and depth to the aquifer and GLSI (geoelectric layer susceptibility indexing. The total longitudinal conductance map shows the north central part of the study area as a weakly protected (0.1–0.19 area, while the northern and southern parts have poor protective capacity (<0.1; this is in agreement with the GOD method which shows the northern part of the study area as less vulnerable (0–0.1 while the southern part has low/moderate (0.1–0.3 vulnerability to contamination. The longitudinal conductance exaggerates the degree of susceptibility to contamination than the GOD and GLSI models. From the models, vulnerability to contamination can be considered higher at the southern part than the northern part and therefore, sources of contamination like septic tank, refuse dump should be cited far from groundwater development area. Keywords: Aquifer vulnerability, Longitudinal conductance, GOD and GLSI

Groundwater vulnerability assessment using hydrogeologic and geoelectric layer susceptibility indexing at Igbara Oke, Southwestern Nigeria

Science.gov (United States)

Oni, T. E.; Omosuyi, G. O.; Akinlalu, A. A.

2017-12-01

Groundwater vulnerability assessment was carried out at Igbara Oke Southwestern Nigeria, with a view to classify the area into vulnerability zones, by applying the electrical resistivity method, using Schlumberger electrode arrays with maximum electrode separation (AB/2) of 65 m in (41) different locations for data acquisition. Geoelectric parameters (layer resistivity and thickness) were determined from the interpreted data. The study area comprises four geoelectric layers (topsoil, lateritic layer, weathered/fractured layer and fresh basement). The geoelectric parameters of the overlying layers across the area were used to assess the vulnerability of the underlying aquifers to near-surface contaminants with the aid of vulnerability maps generated. Three models were compared by maps using geo-electrically derived models; longitudinal conductance, GOD (groundwater occurrence, overlying lithology and depth to the aquifer) and GLSI (geoelectric layer susceptibility indexing). The total longitudinal conductance map shows the north central part of the study area as a weakly protected (0.1-0.19) area, while the northern and southern parts have poor protective capacity (septic tank, refuse dump should be cited far from groundwater development area.

Assessment of landslide distribution map reliability in Niigata prefecture - Japan using frequency ratio approach

Science.gov (United States)

Rahardianto, Trias; Saputra, Aditya; Gomez, Christopher

2017-07-01

Research on landslide susceptibility has evolved rapidly over the few last decades thanks to the availability of large databases. Landslide research used to be focused on discreet events but the usage of large inventory dataset has become a central pillar of landslide susceptibility, hazard, and risk assessment. Indeed, extracting meaningful information from the large database is now at the forth of geoscientific research, following the big-data research trend. Indeed, the more comprehensive information of the past landslide available in a particular area is, the better the produced map will be, in order to support the effective decision making, planning, and engineering practice. The landslide inventory data which is freely accessible online gives an opportunity for many researchers and decision makers to prevent casualties and economic loss caused by future landslides. This data is advantageous especially for areas with poor landslide historical data. Since the construction criteria of landslide inventory map and its quality evaluation remain poorly defined, the assessment of open source landslide inventory map reliability is required. The present contribution aims to assess the reliability of open-source landslide inventory data based on the particular topographical setting of the observed area in Niigata prefecture, Japan. Geographic Information System (GIS) platform and statistical approach are applied to analyze the data. Frequency ratio method is utilized to model and assess the landslide map. The outcomes of the generated model showed unsatisfactory results with AUC value of 0.603 indicate the low prediction accuracy and unreliability of the model.

Identification of highly susceptible individuals in complex networks

Science.gov (United States)

Tang, Shaoting; Teng, Xian; Pei, Sen; Yan, Shu; Zheng, Zhiming

2015-08-01

Identifying highly susceptible individuals in spreading processes is of great significance in controlling outbreaks. In this paper, we explore the susceptibility of people in susceptible-infectious-recovered (SIR) and rumor spreading dynamics. We first study the impact of community structure on people's susceptibility. Although the community structure can reduce the number of infected people for same infection rate, it will not significantly affect nodes' susceptibility. We find the susceptibility of individuals is sensitive to the choice of spreading dynamics. For SIR spreading, since the susceptibility is highly correlated to nodes' influence, the topological indicator k-shell can better identify highly susceptible individuals, outperforming degree, betweenness centrality and PageRank. In contrast, in rumor spreading model, where nodes' susceptibility and influence have no clear correlation, degree performs the best among considered topological measures. Our finding highlights the significance of both topological features and spreading mechanisms in identifying highly susceptible population.

Identification of rs671, a common variant of ALDH2, as a gout susceptibility locus

OpenAIRE

Sakiyama, Masayuki; Matsuo, Hirotaka; Nakaoka, Hirofumi; Yamamoto, Ken; Nakayama, Akiyoshi; Nakamura, Takahiro; Kawai, Sayo; Okada, Rieko; Ooyama, Hiroshi; Shimizu, Toru; Shinomiya, Nariyoshi

2016-01-01

Gout is a common disease resulting from hyperuricemia. Recently, a genome-wide association study identified an association between gout and a single nucleotide polymorphism (SNP) rs2188380, located on an intergenic region between MYL2 and CUX2 on chromosome 12. However, other genes around rs2188380 could possibly be gout susceptibility genes. Therefore, we performed a fine-mapping study of the MYL2-CUX2 region. From 8,595 SNPs in the MYL2-CUX2 region, 9 tag SNPs were selected, and genotyping ...

Doxorubicin-loaded QuadraSphere microspheres: plasma pharmacokinetics and intratumoral drug concentration in an animal model of liver cancer.

Science.gov (United States)

Lee, Kwang-Hun; Liapi, Eleni A; Cornell, Curt; Reb, Philippe; Buijs, Manon; Vossen, Josephina A; Ventura, Veronica Prieto; Geschwind, Jean-Francois H

2010-06-01

The purpose of this study was to evaluate, in vitro and in vivo, doxorubicin-loaded poly (vinyl alcohol-sodium acrylate) copolymer microspheres [QuadraSphere microspheres (QSMs)] for transcatheter arterial delivery in an animal model of liver cancer. Doxorubicin loading efficiency and release profile were first tested in vitro. In vivo, 15 rabbits, implanted with a Vx-2 tumor in the liver, were divided into three groups of five rabbits each, based on the time of euthanasia. Twenty-five milligrams of QSMs was diluted in 10 ml of a 10 mg/ml doxorubicin solution and 10 ml of nonionic contrast medium for a total volume of 20 ml. One milliliter of a drug-loaded QSM solution containing 5 mg of doxorubicin was injected into the tumor feeding artery. Plasma doxorubicin and doxorubicinol concentrations, and intratumoral and peritumoral doxorubicin tissue concentrations, were measured. Tumor specimens were pathologically evaluated to record tumor necrosis. As a control, one animal was blandly embolized with plain QSMs in each group. In vitro testing of QSM doxorubicin loadability and release over time showed 82-94% doxorubicin loadability within 2 h and 6% release within the first 6 h after loading, followed by a slow release pattern. In vivo, the doxorubicin plasma concentration declined at 40 min. The peak doxorubicin intratumoral concentration was observed at 3 days and remained detectable till the study's end point (7 days). Mean percentage tumor cell death in the doxorubicin QSM group was 90% at 7 days and 60% in the bland QSM embolization group. In conclusion, QSMs can be efficiently loaded with doxorubicin. Initial experiments with doxorubicin-loaded QSMs show a safe pharmacokinetic profile and effective tumor killing in an animal model of liver cancer.

Doxorubicin-Loaded QuadraSphere Microspheres: Plasma Pharmacokinetics and Intratumoral Drug Concentration in an Animal Model of Liver Cancer

International Nuclear Information System (INIS)

Lee, Kwang-Hun; Liapi, Eleni A.; Cornell, Curt; Reb, Philippe; Buijs, Manon; Vossen, Josephina A.; Ventura, Veronica Prieto; Geschwind, Jean-Francois H.

2010-01-01

The purpose of this study was to evaluate, in vitro and in vivo, doxorubicin-loaded poly (vinyl alcohol-sodium acrylate) copolymer microspheres [QuadraSphere microspheres (QSMs)] for transcatheter arterial delivery in an animal model of liver cancer. Doxorubicin loading efficiency and release profile were first tested in vitro. In vivo, 15 rabbits, implanted with a Vx-2 tumor in the liver, were divided into three groups of five rabbits each, based on the time of euthanasia. Twenty-five milligrams of QSMs was diluted in 10 ml of a 10 mg/ml doxorubicin solution and 10 ml of nonionic contrast medium for a total volume of 20 ml. One milliliter of a drug-loaded QSM solution containing 5 mg of doxorubicin was injected into the tumor feeding artery. Plasma doxorubicin and doxorubicinol concentrations, and intratumoral and peritumoral doxorubicin tissue concentrations, were measured. Tumor specimens were pathologically evaluated to record tumor necrosis. As a control, one animal was blandly embolized with plain QSMs in each group. In vitro testing of QSM doxorubicin loadability and release over time showed 82-94% doxorubicin loadability within 2 h and 6% release within the first 6 h after loading, followed by a slow release pattern. In vivo, the doxorubicin plasma concentration declined at 40 min. The peak doxorubicin intratumoral concentration was observed at 3 days and remained detectable till the study's end point (7 days). Mean percentage tumor cell death in the doxorubicin QSM group was 90% at 7 days and 60% in the bland QSM embolization group. In conclusion, QSMs can be efficiently loaded with doxorubicin. Initial experiments with doxorubicin-loaded QSMs show a safe pharmacokinetic profile and effective tumor killing in an animal model of liver cancer.

Complementation of a pKM101 derivative that decreases resistance to UV killing but increases susceptibility to mutagenesis

International Nuclear Information System (INIS)

Langer, P.J.; Perry, K.L.; Walker, G.C.

1985-01-01

The drug resistance plasmid pKM101 makes Escherichia coli resistant to the lethal effects of ultraviolet (UV) irradiation and more susceptible to mutagenesis by a variety of agents. The plasmid operon responsible for increasing mutagenesis has been termed mucAB (Mutagenesis, UV and chemical). The authors have isolated a derivative of pKM101 called pGW1975 which makes cells more sensitive to killing by UV but which retains the ability of pKM101 to increase susceptibility to methyl methanesulfonate (MMS) mutagenesis. pGW1975 increases UV mutagenesis less than pKM101 in a uvrA + strain but more than pKM101 in a uvrA - strain. muc - point and insertion mutants of pKM101 and pGW1975 complement to restore the plasmid-mediated: (i) ability to reactivate UV-irradiated phage, (ii) resistance to killing by UV, and (iii) level of susceptibility to UV mutagenesis. They have identified a 2.0 kb region of pKM101 which is responsible for the complementation and which maps counterclockwise of mucAB. (Auth)

Spatial vent opening probability map of El Hierro Island (Canary Islands, Spain)

Science.gov (United States)

Becerril, Laura; Cappello, Annalisa; Galindo, Inés; Neri, Marco; Del Negro, Ciro

2013-04-01

The assessment of the probable spatial distribution of new eruptions is useful to manage and reduce the volcanic risk. It can be achieved in different ways, but it becomes especially hard when dealing with volcanic areas less studied, poorly monitored and characterized by a low frequent activity, as El Hierro. Even though it is the youngest of the Canary Islands, before the 2011 eruption in the "Las Calmas Sea", El Hierro had been the least studied volcanic Island of the Canaries, with more historically devoted attention to La Palma, Tenerife and Lanzarote. We propose a probabilistic method to build the susceptibility map of El Hierro, i.e. the spatial distribution of vent opening for future eruptions, based on the mathematical analysis of the volcano-structural data collected mostly on the Island and, secondly, on the submerged part of the volcano, up to a distance of ~10-20 km from the coast. The volcano-structural data were collected through new fieldwork measurements, bathymetric information, and analysis of geological maps, orthophotos and aerial photographs. They have been divided in different datasets and converted into separate and weighted probability density functions, which were then included in a non-homogeneous Poisson process to produce the volcanic susceptibility map. Future eruptive events on El Hierro is mainly concentrated on the rifts zones, extending also beyond the shoreline. The major probabilities to host new eruptions are located on the distal parts of the South and West rifts, with the highest probability reached in the south-western area of the West rift. High probabilities are also observed in the Northeast and South rifts, and the submarine parts of the rifts. This map represents the first effort to deal with the volcanic hazard at El Hierro and can be a support tool for decision makers in land planning, emergency plans and civil defence actions.

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

Science.gov (United States)

Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu

2018-06-15

Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.

Dissection of a Complex Disease Susceptibility Region Using a Bayesian Stochastic Search Approach to Fine Mapping.

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Chris Wallace

2015-06-01

Full Text Available Identification of candidate causal variants in regions associated with risk of common diseases is complicated by linkage disequilibrium (LD and multiple association signals. Nonetheless, accurate maps of these variants are needed, both to fully exploit detailed cell specific chromatin annotation data to highlight disease causal mechanisms and cells, and for design of the functional studies that will ultimately be required to confirm causal mechanisms. We adapted a Bayesian evolutionary stochastic search algorithm to the fine mapping problem, and demonstrated its improved performance over conventional stepwise and regularised regression through simulation studies. We then applied it to fine map the established multiple sclerosis (MS and type 1 diabetes (T1D associations in the IL-2RA (CD25 gene region. For T1D, both stepwise and stochastic search approaches identified four T1D association signals, with the major effect tagged by the single nucleotide polymorphism, rs12722496. In contrast, for MS, the stochastic search found two distinct competing models: a single candidate causal variant, tagged by rs2104286 and reported previously using stepwise analysis; and a more complex model with two association signals, one of which was tagged by the major T1D associated rs12722496 and the other by rs56382813. There is low to moderate LD between rs2104286 and both rs12722496 and rs56382813 (r2 ≃ 0:3 and our two SNP model could not be recovered through a forward stepwise search after conditioning on rs2104286. Both signals in the two variant model for MS affect CD25 expression on distinct subpopulations of CD4+ T cells, which are key cells in the autoimmune process. The results support a shared causal variant for T1D and MS. Our study illustrates the benefit of using a purposely designed model search strategy for fine mapping and the advantage of combining disease and protein expression data.

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in EPI

Science.gov (United States)

Yeo, Desmond T. B.; Fessler, Jeffrey A.; Kim, Boklye

2014-01-01

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is “corrected” with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume (MSV) registration with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection. PMID:18280077

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in echo-planar imaging.

Science.gov (United States)

Yeo, Desmond T B; Fessler, Jeffrey A; Kim, Boklye

2008-06-01

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is "corrected" with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.

Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

Directory of Open Access Journals (Sweden)

M. J. García-Rodríguez

2010-06-01

Full Text Available This paper presents an approach for assessing earthquake-triggered landslide susceptibility using artificial neural networks (ANNs. The computational method used for the training process is a back-propagation learning algorithm. It is applied to El Salvador, one of the most seismically active regions in Central America, where the last severe destructive earthquakes occurred on 13 January 2001 (M_w 7.7 and 13 February 2001 (M_w 6.6. The first one triggered more than 600 landslides (including the most tragic, Las Colinas landslide and killed at least 844 people.

The ANN is designed and programmed to develop landslide susceptibility analysis techniques at a regional scale. This approach uses an inventory of landslides and different parameters of slope instability: slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness. The information obtained from ANN is then used by a Geographic Information System (GIS to map the landslide susceptibility. In a previous work, a Logistic Regression (LR was analysed with the same parameters considered in the ANN as independent variables and the occurrence or non-occurrence of landslides as dependent variables. As a result, the logistic approach determined the importance of terrain roughness and soil type as key factors within the model. The results of the landslide susceptibility analysis with ANN are checked using landslide location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone. Finally, a comparative analysis of the ANN and LR models are made. The advantages and disadvantages of both approaches are discussed using Receiver Operating Characteristic (ROC curves.

Magnetic susceptibility measurements on Bi - Sn alloys

International Nuclear Information System (INIS)

Mustaffa bin Haji Abdullah

1985-01-01

Magnetic susceptibility measurements on eight samples of tin-rich and three samples of bismuth-rich Bi-Sn alloys were made from 85K to 300K by Faraday's method. The susceptibilities of the eight tin-rich samples are positive and greater than the susceptibility of pure tin. The values are approximately constant at low temperatures but decreasing a little bit with increasing temperature. This result is interpreted as due to the predominant contribution of the Pauli spin paramagnetic susceptibility. A small decrease in susceptibility with temperature is interpreted as due to the effect of the second order term in the expression for spin paramagnetic susceptibility. The fluctuation of the susceptibility for alloys of different composition is interpreted as due to the effect of the density of states at the Fermi levels. The three samples of bismuth-rich alloys show a transition to diamagnetic property, where the diamagnetism is increased with temperature. This result is predominant and due to the diamagnetic contribution from the ions. The increase in susceptibility with temperature is interpreted as due to an increase in the effective radii of the ions due to thermal expansion. (author)

Susceptibility Genes in Thyroid Autoimmunity

Directory of Open Access Journals (Sweden)

Yoshiyuki Ban

2005-01-01

Full Text Available The autoimmune thyroid diseases (AITD are complex diseases which are caused by an interaction between susceptibility genes and environmental triggers. Genetic susceptibility in combination with external factors (e.g. dietary iodine is believed to initiate the autoimmune response to thyroid antigens. Abundant epidemiological data, including family and twin studies, point to a strong genetic influence on the development of AITD. Various techniques have been employed to identify the genes contributing to the etiology of AITD, including candidate gene analysis and whole genome screening. These studies have enabled the identification of several loci (genetic regions that are linked with AITD, and in some of these loci, putative AITD susceptibility genes have been identified. Some of these genes/loci are unique to Graves' disease (GD and Hashimoto's thyroiditis (HT and some are common to both the diseases, indicating that there is a shared genetic susceptibility to GD and HT. The putative GD and HT susceptibility genes include both immune modifying genes (e.g. HLA, CTLA-4 and thyroid specific genes (e.g. TSHR, Tg. Most likely, these loci interact and their interactions may influence disease phenotype and severity.

Integrated geophysical characterisation of Sunyani municipal solid waste disposal site using magnetic gradiometry, magnetic susceptibility survey and electrical resistivity tomography

Science.gov (United States)

Appiah, Isaac; Wemegah, David Dotse; Asare, Van-Dycke Sarpong; Danuor, Sylvester K.; Forson, Eric Dominic

2018-06-01

Non-invasive geophysical investigation using magnetic gradiometry, magnetic susceptibility survey and electrical resistivity tomography (ERT) was carried out on the Sunyani Municipal Assembly (SMA) solid waste disposal (SWD) site. The study was aimed at delineating the physical boundaries and the area extent of the waste deposit, mapping the distribution of the waste at the site, detecting and delineating zones of leachate contamination and its preferential migration pathways beneath the waste deposit and its surroundings. The results of both magnetic susceptibility and gradiometric methods displayed in anomaly maps clearly delineated the physical boundaries of the waste deposit with an approximate area extent of 82,650 m2 that are characterised by high magnetic susceptibilities between 426 × 10-5 SI and 9890 × 10-5 SI. They also revealed high magnetic anomalies erratically distributed within the waste deposit attributable to its heterogeneous and uncontrolled nature. The high magnetic anomalies outside the designated waste boundaries were also attributed to indiscriminate deposition of the waste. Similarly, the ERT sections delineated and characterised zones of leachate contamination beneath the waste body and its close surroundings as well as pathways for leachate migration with low resistivity signatures up to 43.9 Ωm. In spite of the successes reported herein using the ERT, this research also revealed that the ERT is less effective in estimating the thickness of the waste deposit in unlined SWD sites due to leachate infiltration into the ground beneath it that masks the resistivities of the top level ground and makes it indistinguishable from the waste body.

Landslide susceptibility assessment in the Upper Orcia Valley (Southern Tuscany, Italy through conditional analysis: a contribution to the unbiased selection of causal factors

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F. Vergari

2011-05-01

Full Text Available In this work the conditional multivariate analysis was applied to evaluate landslide susceptibility in the Upper Orcia River Basin (Tuscany, Italy, where widespread denudation processes and agricultural practices have a mutual impact. We introduced an unbiased procedure for causal factor selection based on some intuitive statistical indices. This procedure is aimed at detecting among different potential factors the most discriminant ones in a given study area. Moreover, this step avoids generating too small and statistically insignificant spatial units by intersecting the factor maps. Finally, a validation procedure was applied based on the partition of the landslide inventory from multi-temporal aerial photo interpretation.

Although encompassing some sources of uncertainties, the applied susceptibility assessment method provided a satisfactory and unbiased prediction for the Upper Orcia Valley. The results confirmed the efficiency of the selection procedure, as an unbiased step of the landslide susceptibility evaluation. Furthermore, we achieved the purpose of presenting a conceptually simple but, at the same time, effective statistical procedure for susceptibility analysis to be used as well by decision makers in land management.

An overview of a GIS method for mapping landslides and assessing landslide susceptibility in the Río La Carbonera watershed, on the SE flank of Pico de Orizaba Volcano, Mexico.

Science.gov (United States)

Legorreta Paulin, G.; Bursik, M. I.; Contreras, T.

2015-12-01

This poster provides an overview of the on-going research project (Grant PAPIIT # IN102115) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory, produce a landslide susceptibility map, and estimate sediment production by using Geographic Information Systems (GIS). The Río La Carbonera watershed on the southeastern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 71.9 km2 with elevations ranging from 1224 to 3643 m a.s.l. and hillslopes between landslides. The methodology encompasses three main stages of analysis to assess landslide hazards: Stage 1 builds a historic landslide inventory. In the study area, an inventory of more than 200 landslides is created from multi-temporal aerial-photo-interpretation and local field surveys to assess landslide distribution. All landslides were digitized into a geographic information system (GIS), and a spatial geo-database of landslides was constructed from standardized GIS datasets. Stage 2 calculates the susceptibility for the watershed. During this stage, (SINMAP using default values) is evaluated. Stage 3 Estimate the potential total material delivered to the main stream drainage channel by all landslides in the catchment. Detailed geometric measurements of individual landslides visited during the field work will be carried out to obtain the landslide area and volume. These measurements revealed an empirical relationship between area and volume that took the form of a power law. This relationship will be used to estimate the potential volume of material delivered to the catchment. The technique and its implementation of each stage in a GIS-based technology is presented and discussed.

Fine mapping of the rice bacterial blight resistance gene Xa-4 and its co-segregation marker

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

An F2 population developed from the Xa-4 near isogenic lines,IR24 and IRBB4,was used for fine mapping of the rice bacterial blight resistance gene,Xa-4.Some restriction fragment length polymorphism (RFLP) markers on the high-density map constructed by Harushima et al.and the amplified DNA fragments homologous to the conserved domains of plant disease resistance (R) genes were used to construct the genetic linkage map around the gene Xa-4 by scoring susceptible individuals in the population.Xa-4 was mapped between the RFLP marker G181 and the polymerase chain reaction (PCR) marker M55.The R gene homologous fragment marker RS13 was found co-segregating with Xa-4 by analyzing all the plants in the population.This result opened an approach to map-based cloning of this gene,and marker RS13 can be applied to molecular marker-assisted selection of Xa-4 in rice breeding programs.

Aquatic insect ecophysiological traits reveal phylogenetically based differences in dissolved cadmium susceptibility.

Science.gov (United States)

Buchwalter, David B; Cain, Daniel J; Martin, Caitrin A; Xie, Lingtian; Luoma, Samuel N; Garland, Theodore

2008-06-17

We used a phylogenetically based comparative approach to evaluate the potential for physiological studies to reveal patterns of diversity in traits related to susceptibility to an environmental stressor, the trace metal cadmium (Cd). Physiological traits related to Cd bioaccumulation, compartmentalization, and ultimately susceptibility were measured in 21 aquatic insect species representing the orders Ephemeroptera, Plecoptera, and Trichoptera. We mapped these experimentally derived physiological traits onto a phylogeny and quantified the tendency for related species to be similar (phylogenetic signal). All traits related to Cd bioaccumulation and susceptibility exhibited statistically significant phylogenetic signal, although the signal strength varied among traits. Conventional and phylogenetically based regression models were compared, revealing great variability within orders but consistent, strong differences among insect families. Uptake and elimination rate constants were positively correlated among species, but only when effects of body size and phylogeny were incorporated in the analysis. Together, uptake and elimination rates predicted dramatic Cd bioaccumulation differences among species that agreed with field-based measurements. We discovered a potential tradeoff between the ability to eliminate Cd and the ability to detoxify it across species, particularly mayflies. The best-fit regression models were driven by phylogenetic parameters (especially differences among families) rather than functional traits, suggesting that it may eventually be possible to predict a taxon's physiological performance based on its phylogenetic position, provided adequate physiological information is available for close relatives. There appears to be great potential for evolutionary physiological approaches to augment our understanding of insect responses to environmental stressors in nature.

Susceptibility Testing

Science.gov (United States)

... Marker Bicarbonate (Total CO2) Bilirubin Blood Culture Blood Gases Blood Ketones Blood Smear Blood Typing Blood Urea ... hours depending on the method used. There are commercial tests available that offer rapid susceptibility testing and ...

Impact of population structure, effective bottleneck time, and allele frequency on linkage disequilibrium maps.

Science.gov (United States)

Zhang, Weihua; Collins, Andrew; Gibson, Jane; Tapper, William J; Hunt, Sarah; Deloukas, Panos; Bentley, David R; Morton, Newton E

2004-12-28

Genetic maps in linkage disequilibrium (LD) units play the same role for association mapping as maps in centimorgans provide at much lower resolution for linkage mapping. Association mapping of genes determining disease susceptibility and other phenotypes is based on the theory of LD, here applied to relations with three phenomena. To test the theory, markers at high density along a 10-Mb continuous segment of chromosome 20q were studied in African-American, Asian, and Caucasian samples. Population structure, whether created by pooling samples from divergent populations or by the mating pattern in a mixed population, is accurately bioassayed from genotype frequencies. The effective bottleneck time for Eurasians is substantially less than for migration out of Africa, reflecting later bottlenecks. The classical dependence of allele frequency on mutation age does not hold for the generally shorter time span of inbreeding and LD. Limitation of the classical theory to mutation age justifies the assumption of constant time in a LD map, except for alleles that were rare at the effective bottleneck time or have arisen since. This assumption is derived from the Malecot model and verified in all samples. Tested measures of relative efficiency, support intervals, and localization error determine the operating characteristics of LD maps that are applicable to every sexually reproducing species, with implications for association mapping, high-resolution linkage maps, evolutionary inference, and identification of recombinogenic sequences.

Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction

DEFF Research Database (Denmark)

Antoniou, Antonis C; Beesley, Jonathan; McGuffog, Lesley

2010-01-01

The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs650495...

A comparative assessment of prediction capabilities of modified analytical hierarchy process (M-AHP and Mamdani fuzzy logic models using Netcad-GIS for forest fire susceptibility mapping

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Hamid reza Pourghasemi

2016-03-01

Full Text Available The main purpose of this study is to assess forest fire susceptibility maps (FFSMs and their performances comparison using modified analytical hierarchy process (M-AHP and Mamdani fuzzy logic (MFL models in a geographic information system (GIS environment. This study was carried out in the Minudasht Forests, Golestan Province, Iran, and was conducted in three main stages such as spatial data construction, forest fire modelling using M-AHP and MFL, and validation of constructed models using receiver operating characteristic (ROC curve. At first, seven conditioning factors, such as altitude, slope aspect, slope angle, annual temperature, wind effect, land use, and normalized different vegetation index, were extracted from the spatial database. In the next step, FFSMs were prepared using M-AHP and MFL modules in a Netcad-GIS Architect environment. Finally, the ROC curves and area under the curves (AUCs were estimated for validation purposes. The results showed that the AUCs for MFL and M-AHP are 88.20% and 77.72%, respectively. The results obtained in this study also showed that the MFL model performed better than the M-AHP model. These FFSMs can be applied for land use planning, management, and prevention of future fire hazards.

Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression

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García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.; Díaz, M.

2008-03-01

This work has evaluated the probability of earthquake-triggered landslide occurrence in the whole of El Salvador, with a Geographic Information System (GIS) and a logistic regression model. Slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness are the predictor variables used to determine the dependent variable of occurrence or non-occurrence of landslides within an individual grid cell. The results illustrate the importance of terrain roughness and soil type as key factors within the model — using only these two variables the analysis returned a significance level of 89.4%. The results obtained from the model within the GIS were then used to produce a map of relative landslide susceptibility.

High spatial resolution and temporally resolved T2* mapping of normal human myocardium at 7.0 Tesla: an ultrahigh field magnetic resonance feasibility study.

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Fabian Hezel

Full Text Available Myocardial tissue characterization using T(2(* relaxation mapping techniques is an emerging application of (preclinical cardiovascular magnetic resonance imaging. The increase in microscopic susceptibility at higher magnetic field strengths renders myocardial T(2(* mapping at ultrahigh magnetic fields conceptually appealing. This work demonstrates the feasibility of myocardial T(2(* imaging at 7.0 T and examines the applicability of temporally-resolved and high spatial resolution myocardial T(2(* mapping. In phantom experiments single cardiac phase and dynamic (CINE gradient echo imaging techniques provided similar T(2(* maps. In vivo studies showed that the peak-to-peak B(0 difference following volume selective shimming was reduced to approximately 80 Hz for the four chamber view and mid-ventricular short axis view of the heart and to 65 Hz for the left ventricle. No severe susceptibility artifacts were detected in the septum and in the lateral wall for T(2(* weighting ranging from TE = 2.04 ms to TE = 10.2 ms. For TE >7 ms, a susceptibility weighting induced signal void was observed within the anterior and inferior myocardial segments. The longest T(2(* values were found for anterior (T(2(* = 14.0 ms, anteroseptal (T(2(* = 17.2 ms and inferoseptal (T(2(* = 16.5 ms myocardial segments. Shorter T(2(* values were observed for inferior (T(2(* = 10.6 ms and inferolateral (T(2(* = 11.4 ms segments. A significant difference (p = 0.002 in T(2(* values was observed between end-diastole and end-systole with T(2(* changes of up to approximately 27% over the cardiac cycle which were pronounced in the septum. To conclude, these results underscore the challenges of myocardial T(2(* mapping at 7.0 T but demonstrate that these issues can be offset by using tailored shimming techniques and dedicated acquisition schemes.

Definition of a magnetic susceptibility of conglomerates with magnetite particles. Particularities of defining single particle susceptibility

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Sandulyak, A. A.; Sandulyak, A. V.; Ershova, V.; Pamme, N.; Ngmasom, B.; Iles, A.

2017-11-01

Data of a magnetic susceptibility of ferro-and the ferrimagnetic particles of many technogenic, natural, special media are especially demanded for the solution of various tasks connected with purposeful magnetic impact on these particles. One of productive approaches to definition of a magnetic susceptibility χ of these particles consists in receiving experimental data of a susceptibility of disperse samples 〈 χ 〉 with a disperse phase of these particles. The paper expounds and analyses the results of experiments on defining (by Faraday method in a magnetic field with intensity H = 90-730 kA/m) the magnetic susceptibility 〈 χ 〉 of disperse samples (conglomerates) with a given volume ratio γ of magnetite particles (γ = 0.0065-0.25). The corresponding families of concentration and field dependences are provided alongside with discussing the applicability of linear and exponential functions to describe these dependences. We consider the possibility of defining single particles susceptibility χ (with simultaneous obtaining field dependence of this susceptibility) by the commonly used relation χ = 〈 χ 〉 /γ both at relatively small (preferable for accuracy reasons) values γ - to γ = 0.02…0.025, as well as at increased values γ - up to γ = 0.25. The data χ are provided depending on H and correlating with known data at H matter magnetic susceptibility χm (for the case when the particles are traditionally likened to balls with the characteristic for them demagnetising factor equalling 1/3) complies with the anticipated inverse function χm ∼ 1/H in the studied area H (where magnetization M expressed as M = χH reaches saturation M = Const).

Scalar and pseudoscalar susceptibilities in nuclei

International Nuclear Information System (INIS)

Ericson, Magda; Chanfray, Guy; Chanfray, Guy

2003-01-01

We study the two QCD susceptibilities of the nuclear medium in the linear σ model. The magnitude of the scalar one increases due to the mixing with the softer modes of the nucleon-hole excitations. The pseudoscalar susceptibility, follows the density evolution of the quark condensate and thus decreases in magnitude. At normal nuclear matter density the two susceptibilities become much close than in the vacuum, a consequence of the partial chiral symmetry restoration. (author)

Differential Susceptibility Experiments: Going beyond Correlational Evidence--Comment on beyond Mental Health, Differential Susceptibility Articles

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van IJzendoorn, Marinus H.; Bakermans-Kranenburg, Marian J.

2012-01-01

Reviewing the studies on differential susceptibility presented in this section, we argue that the time is ripe to go beyond correlational designs to differential susceptibility experiments. In such experiments, randomization prevents hidden moderator effects on the environment and guarantees the independence of moderator and outcome, while the…

Flavor structure of the nucleon electromagnetic form factors and transverse charge densities in the chiral quark-soliton model

Science.gov (United States)

Silva, António; Urbano, Diana; Kim, Hyun-Chul

2018-02-01

We investigate the flavor decomposition of the electromagnetic form factors of the nucleon, based on the chiral quark-soliton model (χQSM) with symmetry-conserving quantization. We consider the rotational 1/N_c and linear strange-quark mass (ms) corrections. We discuss the results of the flavor-decomposed electromagnetic form factors in comparison with the recent experimental data. In order to see the effects of the strange quark, we compare the SU(3) results with those of SU(2). Finally, we discuss the transverse charge densities for both unpolarized and polarized nucleons. The transverse charge density inside a neutron turns out to be negative in the vicinity of the center within the SU(3) χQSM, which can be explained by the contribution of the strange quark.

[Antimicrobial susceptibility in Chile 2012].

Science.gov (United States)

Cifuentes-D, Marcela; Silva, Francisco; García, Patricia; Bello, Helia; Briceño, Isabel; Calvo-A, Mario; Labarca, Jaime

2014-04-01

Bacteria antimicrobial resistance is an uncontrolled public health problem that progressively increases its magnitude and complexity. The Grupo Colaborativo de Resistencia, formed by a join of experts that represent 39 Chilean health institutions has been concerned with bacteria antimicrobial susceptibility in our country since 2008. In this document we present in vitro bacterial susceptibility accumulated during year 2012 belonging to 28 national health institutions that represent about 36% of hospital discharges in Chile. We consider of major importance to report periodically bacteria susceptibility so to keep the medical community updated to achieve target the empirical antimicrobial therapies and the control measures and prevention of the dissemination of multiresistant strains.

Mapping out Map Libraries

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Ferjan Ormeling

2008-09-01

Full Text Available Discussing the requirements for map data quality, map users and their library/archives environment, the paper focuses on the metadata the user would need for a correct and efficient interpretation of the map data. For such a correct interpretation, knowledge of the rules and guidelines according to which the topographers/cartographers work (such as the kind of data categories to be collected, and the degree to which these rules and guidelines were indeed followed are essential. This is not only valid for the old maps stored in our libraries and archives, but perhaps even more so for the new digital files as the format in which we now have to access our geospatial data. As this would be too much to ask from map librarians/curators, some sort of web 2.0 environment is sought where comments about data quality, completeness and up-to-dateness from knowledgeable map users regarding the specific maps or map series studied can be collected and tagged to scanned versions of these maps on the web. In order not to be subject to the same disadvantages as Wikipedia, where the ‘communis opinio’ rather than scholarship, seems to be decisive, some checking by map curators of this tagged map use information would still be needed. Cooperation between map curators and the International Cartographic Association ( ICA map and spatial data use commission to this end is suggested.

St. Louis area earthquake hazards mapping project; seismic and liquefaction hazard maps

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Cramer, Chris H.; Bauer, Robert A.; Chung, Jae-won; Rogers, David; Pierce, Larry; Voigt, Vicki; Mitchell, Brad; Gaunt, David; Williams, Robert; Hoffman, David; Hempen, Gregory L.; Steckel, Phyllis; Boyd, Oliver; Watkins, Connor M.; Tucker, Kathleen; McCallister, Natasha

2016-01-01

We present probabilistic and deterministic seismic and liquefaction hazard maps for the densely populated St. Louis metropolitan area that account for the expected effects of surficial geology on earthquake ground shaking. Hazard calculations were based on a map grid of 0.005°, or about every 500 m, and are thus higher in resolution than any earlier studies. To estimate ground motions at the surface of the model (e.g., site amplification), we used a new detailed near‐surface shear‐wave velocity model in a 1D equivalent‐linear response analysis. When compared with the 2014 U.S. Geological Survey (USGS) National Seismic Hazard Model, which uses a uniform firm‐rock‐site condition, the new probabilistic seismic‐hazard estimates document much more variability. Hazard levels for upland sites (consisting of bedrock and weathered bedrock overlain by loess‐covered till and drift deposits), show up to twice the ground‐motion values for peak ground acceleration (PGA), and similar ground‐motion values for 1.0 s spectral acceleration (SA). Probabilistic ground‐motion levels for lowland alluvial floodplain sites (generally the 20–40‐m‐thick modern Mississippi and Missouri River floodplain deposits overlying bedrock) exhibit up to twice the ground‐motion levels for PGA, and up to three times the ground‐motion levels for 1.0 s SA. Liquefaction probability curves were developed from available standard penetration test data assuming typical lowland and upland water table levels. A simplified liquefaction hazard map was created from the 5%‐in‐50‐year probabilistic ground‐shaking model. The liquefaction hazard ranges from low (60% of area expected to liquefy) in the lowlands. Because many transportation routes, power and gas transmission lines, and population centers exist in or on the highly susceptible lowland alluvium, these areas in the St. Louis region are at significant potential risk from seismically induced liquefaction and associated

Presence-only approach to assess landslide triggering-thickness susceptibility. A test for the Mili catchment (North-Eastern Sicily, Italy)

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Lombardo, Luigi; Fubelli, Giandomenico; Amato, Gabriele; Bonasera, Mauro; Hochschild, Volker; Rotigliano, Edoardo

2015-04-01

This study aims at comparing the performances of a presence only approach, namely Maximum Entropy, in assessing landslide triggering-thickness susceptibility within the Mili catchment, located in the north-eastern Sicily, Italy. This catchment has been recently exposed to three main meteorological extreme events, resulting in the activation of multiple fast landslides, which occurred on the 1st October 2009, 10th March 2010 and 1st March 2011. Differently from the 2009 event, which only marginally hit the catchment, the 2010 and 2011 storms fully involved the area of the Mili catchment. Detailed field data was collected to associate the thickness of mobilised materials at the triggering zone to each mass movement within the catchment. This information has been used to model the landslide susceptibility for two classes of processes clustered into shallow failures for maximum depths of 0.5m and deep ones in case of values equal or greater than 0.5m. As the authors believed that the peculiar geomorphometry of this narrow and steep catchment played a fundamental role in generating two distinct patterns of landslide thicknesses during the initiation phase, a HRDEM was used to extract topographic attributes to express near-triggering geomorphological conditions. On the other hand, medium resolution vegetation indexes derived from ASTER scenes were used as explanatory variables pertaining to a wider spatial neighbourhood, whilst a revised geological map, the land use from CORINE and a tectonic map were used to convey an even wider area connected to the slope instability. The choice of a presence-only approach allowed to effectively discriminate between the two types of landslide thicknesses at the triggering zone, producing outstanding prediction skills associated with relatively low variances across a set of 20 randomly generated replicates. The validation phase produced indeed average AUC values of 0.91 with a standard deviation of 0.03 for both the modelled landslide

Debris flow susceptibility assessment based on an empirical approach in the central region of South Korea

Science.gov (United States)

Kang, Sinhang; Lee, Seung-Rae

2018-05-01

Many debris flow spreading analyses have been conducted during recent decades to prevent damage from debris flows. An empirical approach that has been used in various studies on debris flow spreading has advantages such as simple data acquisition and good applicability for large areas. In this study, a GIS-based empirical model that was developed at the University of Lausanne (Switzerland) is used to assess the debris flow susceptibility. Study sites are classified based on the types of soil texture or geological conditions, which can indirectly consider geotechnical or rheological properties, to supplement the weaknesses of Flow-R which neglects local controlling factors. The mean travel angle for each classification is calculated from a debris flow inventory map. The debris flow susceptibility is assessed based on changes in the flow-direction algorithm, an inertial function with a 5-m DEM resolution. A simplified friction-limited model was applied to the runout distance analysis by using the appropriate travel angle for the corresponding classification with a velocity limit of 28 m/s. The most appropriate algorithm combinations that derived the highest average of efficiency and sensitivity for each classification are finally determined by applying a confusion matrix with the efficiency and the sensitivity to the results of the susceptibility assessment. The proposed schemes can be useful for debris flow susceptibility assessment in both the study area and the central region of Korea, which has similar environmental factors such as geological conditions, topography and rainfall characteristics to the study area.

Methodology to develop maps of susceptibility to mass removal processes, case analysis south slope of Tuxtla Gutiérrez, Chiapas

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J. A. Paz Tenorio

2017-03-01

classified as Very High Threat are the more susceptible to the occurrence of these events. It is to be expected that in time, the incidence of this type of phenomena is manifested in the levels of High and Very High Threat. Applying the Analytic Hierarchy Process (AHP developed by Saaty (1988, which consists of matrix analysis and involves value judgments. In this way the matrix of preference over the selected criteria was generated, obtaining the weighting of the five chosen variables. It was important the knowledge of the study area, the documentation and local studies generated to date, where the criteria of the specialists are taken up. The process was done in an Excel spreadsheet (2007 version, applying the corresponding formulas. Because only five variables and the size of the area (250 km2 were handled, no specialized software was required. With the data obtained a table was created in which a column with the name of "Threat" was created, which corresponds to the sum of the parameters of the six criteria mentioned above. This is reflected in the Map of Threats by Mass Removal Processes. Thus, in the one the extreme values are included in a range from 0 to 1. The map of hazard by removing processes in mass or landslide (PRM, was developed from the heuristic combination of multi-criteria analysis method, and determined five levels of threat in the urban area, covering the following percentages: Very Low 5%, Low 27.1%, Middle 39.3%, High 15.3% and Very High 13.3%, the latter being distributed mostly in slope deposits around La Mesa of Copoya, confirming their status as maximum hazard. For Tuxtla Gutierrez is estimated a population exposed about 62,500 inhabitants (11.6% of the total (537.102 inhabitants in the urban area who reside both in the southern part of the city and 30 rural towns settled on the flanks of La Mesa of Copoya; estimates about 28,000 dwellings exposed grouped into 850 blocks. Current trends in the growth of the city, make evident the need to manage

Identification of a shared genetic susceptibility locus for coronary heart disease and periodontitis.

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Arne S Schaefer

2009-02-01

Full Text Available Recent studies indicate a mutual epidemiological relationship between coronary heart disease (CHD and periodontitis. Both diseases are associated with similar risk factors and are characterized by a chronic inflammatory process. In a candidate-gene association study, we identify an association of a genetic susceptibility locus shared by both diseases. We confirm the known association of two neighboring linkage disequilibrium regions on human chromosome 9p21.3 with CHD and show the additional strong association of these loci with the risk of aggressive periodontitis. For the lead SNP of the main associated linkage disequilibrium region, rs1333048, the odds ratio of the autosomal-recessive mode of inheritance is 1.99 (95% confidence interval 1.33-2.94; P = 6.9 x 10(-4 for generalized aggressive periodontitis, and 1.72 (1.06-2.76; P = 2.6 x 10(-2 for localized aggressive periodontitis. The two associated linkage disequilibrium regions map to the sequence of the large antisense noncoding RNA ANRIL, which partly overlaps regulatory and coding sequences of CDKN2A/CDKN2B. A closely located diabetes-associated variant was independent of the CHD and periodontitis risk haplotypes. Our study demonstrates that CHD and periodontitis are genetically related by at least one susceptibility locus, which is possibly involved in ANRIL activity and independent of diabetes associated risk variants within this region. Elucidation of the interplay of ANRIL transcript variants and their involvement in increased susceptibility to the interactive diseases CHD and periodontitis promises new insight into the underlying shared pathogenic mechanisms of these complex common diseases.

Candida Species From Eye Infections: Drug Susceptibility, Virulence Factors, and Molecular Characterization.

Science.gov (United States)

Ranjith, Konduri; Sontam, Bhavani; Sharma, Savitri; Joseph, Joveeta; Chathoth, Kanchana N; Sama, Kalyana C; Murthy, Somasheila I; Shivaji, Sisinthy

2017-08-01

To determine the type of Candida species in ocular infections and to investigate the relationship of antifungal susceptibility profile to virulence factors. Fifty isolates of yeast-like fungi from patients with keratitis, endophthalmitis, and orbital cellulitis were identified by Vitek-2 compact system and DNA sequencing of ITS1-5.8S-ITS2 regions of the rRNA gene, followed by phylogenetic analysis for phenotypic and genotypic identification, respectively. Minimum inhibitory concentration of six antifungal drugs was determined by E test/microbroth dilution methods. Phenotypic and genotypic methods were used to determine the virulence factors. Phylogenetic analysis showed the clustering of all isolates into eight distinct groups with a major cluster formed Candida parapsilosis (n = 21), which was the most common species by both Vitek 2 and DNA sequencing. Using χ2 test no significant difference was noted between the techniques except that Vitek 2 did not identify C. viswanathii, C. orthopsilosis, and two non-Candida genera. Of 43 tested Candida isolates high susceptibility to amphotericin B (39/43, 90.6%) and natamycin (43/43, 100%) was noted. While none of the isolates produced coagulase, all produced esterase and catalase. The potential to form biofilm was detected in 23/43 (53.4%) isolates. Distribution of virulence factors by heat map analysis showed difference in metabolic activity of biofilm producers from nonbiofilm producers. Identified by Vitek 2 and DNA sequencing methods C. parapsilosis was the most common species associated with eye infections. Irrespective of the virulence factors elaborated, the Candida isolates were susceptible to commonly used antifungal drugs such as amphotericin B and natamycin.

Landslides Mapped from LIDAR Imagery, Kitsap County, Washington

Science.gov (United States)

McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.

2008-01-01

Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser

Linkage disequilibrium mapping of a breast cancer susceptibility locus near RAI/PPPIRI3L/iASPP

DEFF Research Database (Denmark)

Nexø, Bjørn A.; Vogel, Ulla Birgitte; Olsen, Anja

2008-01-01

mapping. The study groups included 434 postmenopausal breast cancer cases and an identical number of individually matched controls. Methods and Results: Studying one marker at a time, we found a region spanning the gene RAI ( alias PPP1R13L or iASPP) and the 5' portion of XPD to be associated...

The combination of two Sle2 lupus-susceptibility loci and Cdkn2c deficiency leads to T cell-mediated pathology in B6.Faslpr mice

Science.gov (United States)

Xu, Zhiwei; Croker, Byron P.; Morel, Laurence

2013-01-01

The NZM2410 Sle2c1 lupus susceptibility locus is responsible for the expansion of the B1a cell compartment and for the induction of T-cell induced renal and skin pathology on a CD95 deficient (Faslpr)-background. We have previously shown that deficiency in cyclin-dependent kinase inhibitor p18INK4c (p18) was responsible for the B1a cell expansion but was not sufficient to account for the pathology in B6.lpr mice. This study was designed to map the additional Sle2c1 loci responsible for autoimmune pathology when co-expressed with CD95 deficiency. The production, fine-mapping and phenotypic characterization of five recombinant intervals indicated that three interacting sub-loci were responsive for inducting autoimmune pathogenesis in B6.lpr mice. One of these sub-loci corresponds most likely to p18-deficiency. Another major locus mapping to a 2 Mb region at the telomeric end of Sle2c1 is necessary to both renal and skin pathology. Finally, a third locus centromeric to p18 enhances the severity of lupus nephritis. These results provide new insights into the genetic interactions leading to SLE disease presentation, and represent a major step towards the identification of novel susceptibility genes involved in T-cell mediated organ damage. PMID:23698709

Quality Systems Manual (QSM) Version 5: Update

Science.gov (United States)

2012-03-01

Rei Mao; Charles Stoner  Air Force: John (Seb) Gillette  DOE: Joe Pardue; Todd Hardt  Contractor: Alyssa Wingard Questions ??? We have answers* Do...labs must be approved by appropriate DOE representative • Outsourced QS elements (such as data review) must comply with the standard and are subject to

7-Tesla Susceptibility-Weighted Imaging to Assess the Effects of Radiotherapy on Normal-Appearing Brain in Patients With Glioma

International Nuclear Information System (INIS)

Lupo, Janine M.; Chuang, Cynthia F.; Chang, Susan M.; Barani, Igor J.; Jimenez, Bert; Hess, Christopher P.; Nelson, Sarah J.

2012-01-01

Purpose: To evaluate the intermediate- and long-term imaging manifestations of radiotherapy on normal-appearing brain tissue in patients with treated gliomas using 7T susceptibility-weighted imaging (SWI). Methods and Materials: SWI was performed on 25 patients with stable gliomas on a 7 Tesla magnet. Microbleeds were identified as discrete foci of susceptibility that did not correspond to vessels. The number of microbleeds was counted within and outside of the T2-hyperintense lesion. For 3 patients, radiation dosimetry maps were reconstructed and fused with the 7T SWI data. Results: Multiple foci of susceptibility consistent with microhemorrhages were observed in patients 2 years after chemoradiation. These lesions were not present in patients who were not irradiated. The prevalence of microhemorrhages increased with the time since completion of radiotherapy, and these lesions often extended outside the boundaries of the initial high-dose volume and into the contralateral hemisphere. Conclusions: High-field SWI has potential for visualizing the appearance of microbleeds associated with long-term effects of radiotherapy on brain tissue. The ability to visualize these lesions in normal-appearing brain tissue may be important in further understanding the utility of this treatment in patients with longer survival.

Antianaerobic Antimicrobials: Spectrum and Susceptibility Testing

Science.gov (United States)

Wexler, Hannah M.; Goldstein, Ellie J. C.

2013-01-01

SUMMARY Susceptibility testing of anaerobic bacteria recovered from selected cases can influence the choice of antimicrobial therapy. The Clinical and Laboratory Standards Institute (CLSI) has standardized many laboratory procedures, including anaerobic susceptibility testing (AST), and has published documents for AST. The standardization of testing methods by the CLSI allows comparisons of resistance trends among various laboratories. Susceptibility testing should be performed on organisms recovered from sterile body sites, those that are isolated in pure culture, or those that are clinically important and have variable or unique susceptibility patterns. Organisms that should be considered for individual isolate testing include highly virulent pathogens for which susceptibility cannot be predicted, such as Bacteroides, Prevotella, Fusobacterium, and Clostridium spp.; Bilophila wadsworthia; and Sutterella wadsworthensis. This review describes the current methods for AST in research and reference laboratories. These methods include the use of agar dilution, broth microdilution, Etest, and the spiral gradient endpoint system. The antimicrobials potentially effective against anaerobic bacteria include beta-lactams, combinations of beta-lactams and beta-lactamase inhibitors, metronidazole, chloramphenicol, clindamycin, macrolides, tetracyclines, and fluoroquinolones. The spectrum of efficacy, antimicrobial resistance mechanisms, and resistance patterns against these agents are described. PMID:23824372

Epidemiology of Acute Q Fever, Scrub Typhus, and Murine Typhus, and Identification of Their Clinical Characteristics Compared to Patients with Acute Febrile Illness in Southern Taiwan

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Chung-Hsu Lai

2009-05-01

Conclusion: In southern Taiwan, acute Q fever is the most common rickettsiosis. QSM diseases should be suspected in febrile patients who present with relative bradycardia, hepatomegaly, and elevated serum aminotransferases, but without leukocytosis.

Measurements of temperature dependence of 'localized susceptibility'

CERN Document Server

Shiozawa, H; Ishii, H; Takayama, Y; Obu, K; Muro, T; Saitoh, Y; Matsuda, T D; Sugawara, H; Sato, H

2003-01-01

The magnetic susceptibility of some rare-earth compounds is estimated by measuring magnetic circular dichroism (MCD) of rare-earth 3d-4f absorption spectra. The temperature dependence of the magnetic susceptibility obtained by the MCD measurement is remarkably different from the bulk susceptibility in most samples, which is attributed to the strong site selectivity of the core MCD measurement.

Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

Science.gov (United States)

Jacobs, Liesbet; Dewitte, Olivier; Poesen, Jean; Sekajugo, John; Nobile, Adriano; Rossi, Mauro; Thiery, Wim; Kervyn, Matthieu

2018-01-01

landslides such as tangent curvature and total rainfall. Finally, the landslide susceptibility assessment is overlaid with a population density map in order to identify potential landslide risk hotspots, which could direct research and policy action towards reduced landslide risk in this under-researched, landslide-prone region.

Absolute method of measuring magnetic susceptibility

Science.gov (United States)

Thorpe, A.; Senftle, F.E.

1959-01-01

An absolute method of standardization and measurement of the magnetic susceptibility of small samples is presented which can be applied to most techniques based on the Faraday method. The fact that the susceptibility is a function of the area under the curve of sample displacement versus distance of the magnet from the sample, offers a simple method of measuring the susceptibility without recourse to a standard sample. Typical results on a few substances are compared with reported values, and an error of less than 2% can be achieved. ?? 1959 The American Institute of Physics.

Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping

Energy Technology Data Exchange (ETDEWEB)

Pekin, Thomas C. [Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, USA 94720 (United States); National Center for Electron Microscopy, Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, USA 94720 (United States); Gammer, Christoph [Erich Schmid Institute of Materials Science, Jahnstrasse 12, Leoben, Austria 8700 (Austria); Ciston, Jim [National Center for Electron Microscopy, Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, USA 94720 (United States); Minor, Andrew M. [Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, USA 94720 (United States); National Center for Electron Microscopy, Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, USA 94720 (United States); Ophus, Colin, E-mail: cophus@gmail.com [National Center for Electron Microscopy, Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, USA 94720 (United States)

2017-05-15

Scanning nanobeam electron diffraction strain mapping is a technique by which the positions of diffracted disks sampled at the nanoscale over a crystalline sample can be used to reconstruct a strain map over a large area. However, it is important that the disk positions are measured accurately, as their positions relative to a reference are directly used to calculate strain. In this study, we compare several correlation methods using both simulated and experimental data in order to directly probe susceptibility to measurement error due to non-uniform diffracted disk illumination structure. We found that prefiltering the diffraction patterns with a Sobel filter before performing cross correlation or performing a square-root magnitude weighted phase correlation returned the best results when inner disk structure was present. We have tested these methods both on simulated datasets, and experimental data from unstrained silicon as well as a twin grain boundary in 304 stainless steel.

Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

Science.gov (United States)

Zhou, Chao; Yin, Kunlong; Cao, Ying; Ahmed, Bayes; Li, Yuanyao; Catani, Filippo; Pourghasemi, Hamid Reza

2018-03-01

Landslide is a common natural hazard and responsible for extensive damage and losses in mountainous areas. In this study, Longju in the Three Gorges Reservoir area in China was taken as a case study for landslide susceptibility assessment in order to develop effective risk prevention and mitigation strategies. To begin, 202 landslides were identified, including 95 colluvial landslides and 107 rockfalls. Twelve landslide causal factor maps were prepared initially, and the relationship between these factors and each landslide type was analyzed using the information value model. Later, the unimportant factors were selected and eliminated using the information gain ratio technique. The landslide locations were randomly divided into two groups: 70% for training and 30% for verifying. Two machine learning models: the support vector machine (SVM) and artificial neural network (ANN), and a multivariate statistical model: the logistic regression (LR), were applied for landslide susceptibility modeling (LSM) for each type. The LSM index maps, obtained from combining the assessment results of the two landslide types, were classified into five levels. The performance of the LSMs was evaluated using the receiver operating characteristics curve and Friedman test. Results show that the elimination of noise-generating factors and the separated modeling of each landslide type have significantly increased the prediction accuracy. The machine learning models outperformed the multivariate statistical model and SVM model was found ideal for the case study area.

Susceptibility of Staphylococcus species and subspecies to teicoplanin.

Science.gov (United States)

Bannerman, T L; Wadiak, D L; Kloos, W E

1991-01-01

Twenty-four Staphylococcus species and their subspecies were examined for their susceptibilities to teicoplanin by disk diffusion (30-micrograms disk) and agar dilution for the determination of MICs. Moderately susceptible and resistant clinical strains were further tested for their susceptibilities to oxacillin and vancomycin. Teicoplanin resistance was not observed in the reference strains of the various Staphylococcus species isolated from healthy volunteers or animals. However, the novobiocin-resistant species Staphylococcus saprophyticus, Staphylococcus cohnii, Staphylococcus xylosus, Staphylococcus arlettae, Staphylococcus kloosii, and Staphylococcus gallinarum were less susceptible to teicoplanin (MIC, 2 to 8 micrograms/ml) than most of the novobiocin-susceptible species were (MIC, 0.5 to 4 micrograms/ml). Clinical isolates of coagulase-negative species were generally less susceptible to teicoplanin than were reference strains. Seven percent of the Staphylococcus epidermidis clinical strains were moderately susceptible (MIC, 16 micrograms/ml) to teicoplanin. Of these strains, 70% were oxacillin resistant. For Staphylococcus haemolyticus strains, 11% were resistant (MIC, greater than 16 micrograms/ml) and 21% were moderately susceptible to teicoplanin. Of these strains, 95% were oxacillin resistant, No strains of S. epidermidis or S. haemolyticus were intermediate or resistant to vancomycin. Teicoplanin appears to be less active in vitro against oxacillin-resistant S. haemolyticus. However, teicoplanin is an effective antimicrobial agent against many Staphylococcus species. PMID:1835340

Construction of 2 intraspecific linkage maps and identification of resistance QTLs for Phytophthora capsici root-rot and foliar-blight diseases of pepper (Capsicum annuum L.).

Science.gov (United States)

Ogundiwin, Ebenezer A; Berke, Terry F; Massoudi, Mark; Black, Lowell L; Huestis, Gordon; Choi, Doil; Lee, Sanghyeob; Prince, James P

2005-08-01

Two linkage maps of pepper were constructed and used to identify quantitative trait loci (QTLs) conferring resistance to Phytophthora capsici. Inoculations were done with 7 isolates: 3 from Taiwan, 3 from California, and 1 from New Mexico. The first map was constructed from a set of recombinant inbred lines (RILs) of the PSP-11 (susceptible) x PI201234 (resistant) cross; and the second map was from a set of F(2) lines of the Joe E. Parker' (susceptible) x 'Criollo de Morelos 334' (resistant) cross. The RIL map covered 1466.1 cM of the pepper genome, and it consisted of 144 markers -- 91 amplified fragment length polymorphisms (AFLPs), 34 random amplified polymorphic DNA (RAPDs), 15 simple sequence repeats (SSRs), 1 sequence characterized amplified region (SCAR), and 3 morphological markers -- distributed over 17 linkage groups. The morphological markers mapped on this population were erect fruit habit (up), elongated fruit shape (fs(e)), and fasciculate fruit clusters (fa). The F(2) map consisted of 113 markers (51 AFLPs, 45 RAPDs, 14 SSRs, and 3 SCARs) distributed in 16 linkage groups, covering a total of 1089.2 cM of the pepper genome. Resistance to both root rot and foliar blight were evaluated in the RIL population using the 3 Taiwan isolates; the remaining isolates were used for the root-rot test only. Sixteen chromosomal regions of the RIL map contained single QTLs or clusters of resistance QTLs that had an effect on root rot and (or) foliar blight, revealing a complex set of genetics involved in resistance to P. capsici. Five QTLs were detected in the F(2) map that had an effect on resistance to root rot.

High-frequency, transient magnetic susceptibility of ferroelectrics

Science.gov (United States)

Grimes, Craig A.

1996-10-01

A significant high-frequency magnetic susceptibility was measured both in weakly polarized and nonpolarized samples of barium titanate, lead zirconate titanate, and carnauba wax. Magnetic susceptibility measurements were made from 10 to 500 MHz using a thin film permeameter at room temperature; initial susceptibilities ranged from 0.1 to 2.5. These values are larger than expected for paramagnets and smaller than expected for ferromagnets. It was found that the magnetic susceptibility decreases rapidly with exposure to the exciting field. The origin of the magnetic susceptibility is thought to originate with the applied time varying electric field associated with the susceptibility measurements. An electric field acts to rotate an electric dipole, creating a magnetic quadrupole if the two moments are balanced, and a net magnetic dipole moment if imbalanced. It is thought that local electrostatic fields created at ferroelectric domain discontinuities associated with grain boundaries create an imbalance in the anion rotation that results in a net, measurable, magnetic moment. The origin of the magnetic aftereffect may be due to the local heating of the material through the moving charges associated with the magnetic moment.

Participatory three dimensional mapping for the preparation of landslide disaster risk reduction program

Science.gov (United States)

Kusratmoko, Eko; Wibowo, Adi; Cholid, Sofyan; Pin, Tjiong Giok

2017-07-01

This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng' village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of the village. Based on the results P3DM, the ability of the communities in understanding the village environment spatially well-tested and honed, so as to facilitate the preparation of the CBDRR programs. Furthermore, the P3DM method can be applied to another disaster areas, due to it becomes a medium of effective dialogue between all levels of involved communities.

SCC susceptibility evaluation of plastic deformed austenitic stainless steels

Energy Technology Data Exchange (ETDEWEB)

Kaneshima, Yoshiari; Totsuka, Nobuo; Arioka, Koji [Inst. of Nuclear Safety System Inc., Mihama, Fukui (Japan)

2002-09-01

Slow strain rate temperature (SSRT) tests were carried out to evaluate the SCC susceptibility of deformed SUS316 stainless steel in simulated primary water of pressurized water reactor (PWR). The influence of material hardness and temperature on SCC susceptibility was studied. From these tests following results were obtained. (1) Both of the total SCC and IGSCC susceptibilities increased as the hardness of deformed specimens increased. Especially over 250{approx}300HV area, this tendency remarkably increased. (2) The reduction ratio showed a plateau under 300HV area. However, over 300HV area, it decreased remarkably as the hardness increased, that is, the SCC susceptibility remarkably increased. (3) Based on the SSRT test results conducted at 320, 340 and 360degC, the total SCC susceptibility dependence on temperature was small and the IGSCC susceptibility was dependent on the temperature. From these results, the TGSCC susceptibility dependence on temperature was also small. The activation energy of total SCC and IGSCC susceptibility were calculated. (author)

Ancestral susceptibility to colorectal cancer

Czech Academy of Sciences Publication Activity Database

Huhn, S.; Pardini, Barbara; Naccarati, Alessio; Vodička, Pavel (ed.); Hemminki, K.; Försti, A.

2012-01-01

Roč. 27, č. 2 (2012), s. 197-204 ISSN 0267-8357 R&D Projects: GA ČR GA310/07/1430; GA ČR GAP304/10/1286 Grant - others:EU FP7(XE) HEALTH-F4-2007-200767 Institutional research plan: CEZ:AV0Z50390512 Keywords : cancer susceptibility * molecular epidemiology * genetic susceptibility Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.500, year: 2012

Soil geohazard mapping for improved asset management of UK local roads

Science.gov (United States)

Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

2015-09-01

Unclassified roads comprise 60 % of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink-swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any, structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.