Engineering Geology for Society and Territory: volume 2: landslide processes

This book is one out of 8 IAEG XII Congress volumes, and deals with Landslide processes, including: field data and monitoring techniques, prediction and forecasting of landslide occurrence, regional landslide inventories and dating studies, modeling of slope instabilities and secondary hazards (e.g. impulse waves and landslide-induced tsunamis, landslide dam failures and breaching), hazard and risk assessment, earthquake and rainfall induced landslides, instabilities of volcanic edifices, remedial works and mitigation measures, development of innovative stabilization techniques and applicability to specific engineering geological conditions, use of geophysical techniques for landslide characterization and investigation of triggering mechanisms. Focuses is given to innovative techniques, well documented case studies in different environments, critical components of engineering geological and geotechnical investigations, hydrological and hydrogeological investigations, remote sensing and geophysical techniques, modeling of triggering, collapse, runout and landslide reactivation, geotechnical design and construction procedures in landslide zones, interaction of landslides with structures and infrastructures and possibility of domino effects. The Engineering Geology for Society and Territory volumes of the IAEG XII Congress held in Torino from September 15-19, 2014, analyze the dynamic role of engineering geology in our changing world and build on the four main themes of the congress: environment, processes, issues, and approaches.

Prediction of the economic cost of individual long-term care in the Spanish population

Pensions together with savings and investments during active life are key elements of retirement planning. Motivation for personal choices about the standard of living, bequest and the replacement ratio of pension with respect to last salary income must be considered. This research contributes to the financial planning by helping to quantify long-term care economic needs. We estimate life expectancy from retirement age onwards. The economic cost of care per unit of service is linked to the expected time of needed care and the intensity of required services. The expected individual cost of long-term care from an onset of dependence is estimated separately for men and women. Assumptions on the mortality of the dependent people compared to the general population are introduced. Parameters defining eligibility for various forms of coverage by the universal public social care of the welfare system are addressed. The impact of the intensity of social services on individual predictions is assessed, and a partial coverage by standard private insurance products is also explored. Data were collected by the Spanish Institute of Statistics in two surveys conducted on the general Spanish population in 1999 and in 2008. Official mortality records and life table trends were used to create realistic scenarios for longevity. We find empirical evidence that the public long-term care system in Spain effectively mitigates the risk of incurring huge lifetime costs. We also find that the most vulnerable categories are citizens with moderate disabilities that do not qualify to obtain public social care support. In the Spanish case, the trends between 1999 and 2008 need to be further explored.

Association between parental history and genetic risk scores for coronary heart disease prediction: The population-based CoLaus study.

BACKGROUND AND AIMS: Parental history (PH) and genetic risk scores (GRSs) are separately associated with coronary heart disease (CHD), but evidence regarding their combined effects is lacking. We aimed to evaluate the joint associations and predictive ability of PH and GRSs for incident CHD. METHODS: Data for 4283 Caucasians were obtained from the population-based CoLaus Study, over median follow-up time of 5.6 years. CHD was defined as incident myocardial infarction, angina, percutaneous coronary revascularization or bypass grafting. Single nucleotide polymorphisms for CHD identified by genome-wide association studies were used to construct unweighted and weighted versions of three GRSs, comprising of 38, 53 and 153 SNPs respectively. RESULTS: PH was associated with higher values of all weighted GRSs. After adjustment for age, sex, smoking, diabetes, systolic blood pressure, low and high density lipoprotein cholesterol, PH was significantly associated with CHD [HR 2.61, 95% CI (1.47-4.66)] and further adjustment for GRSs did not change this estimate. Similarly, one standard deviation change of the weighted 153-SNPs GRS was significantly associated with CHD [HR 1.50, 95% CI (1.26-1.80)] and remained so, after further adjustment for PH. The weighted, 153-SNPs GRS, but not PH, modestly improved discrimination [(C-index improvement, 0.016), p = 0.048] and reclassification [(NRI improvement, 8.6%), p = 0.027] beyond cardiovascular risk factors. After including both the GRS and PH, model performance improved further [(C-index improvement, 0.022), p = 0.006]. CONCLUSION: After adjustment for cardiovascular risk factors, PH and a weighted, polygenic GRS were jointly associated with CHD and provided additive information for coronary events prediction.

Predicting recurrence after unprovoked venous thromboembolism: prospective validation of the updated Vienna Prediction Model.

The updated Vienna Prediction Model for estimating recurrence risk after an unprovoked venous thromboembolism (VTE) has been developed to identify individuals at low risk for VTE recurrence in whom anticoagulation (AC) therapy may be stopped after 3 months. We externally validated the accuracy of the model to predict recurrent VTE in a prospective multicenter cohort of 156 patients aged ≥65 years with acute symptomatic unprovoked VTE who had received 3 to 12 months of AC. Patients with a predicted 12-month risk within the lowest quartile based on the updated Vienna Prediction Model were classified as low risk. The risk of recurrent VTE did not differ between low- vs higher-risk patients at 12 months (13% vs 10%; P = .77) and 24 months (15% vs 17%; P = 1.0). The area under the receiver operating characteristic curve for predicting VTE recurrence was 0.39 (95% confidence interval [CI], 0.25-0.52) at 12 months and 0.43 (95% CI, 0.31-0.54) at 24 months. In conclusion, in elderly patients with unprovoked VTE who have stopped AC, the updated Vienna Prediction Model does not discriminate between patients who develop recurrent VTE and those who do not. This study was registered at www.clinicaltrials.gov as #NCT00973596.

Evaluation of a snow avalanche possibly triggered by a local earthquake at Vallée de la Sionne, Switzerland

Snow avalanches are moving sources of infrasonic and seismic energy. They can be triggered by many different mechanisms that include the shaking produced by earthquakes. The forces induced by an earthquake can cause an increase in the load down the slope and can also decrease the shear strength and both effects can cause the release of an avalanche. This phenomenon represents an important hazard associated with earthquakes in snow-covered mountain areas with high seismicity.

Prediction of preeclampsia by means of Doppler flowmetry of uterine artery and flow-mediated dilation of brachial artery

Objective To evaluate the association of Doppler of uterine artery and flow-mediated dilation of brachial artery (FMD) in the assessment of placental perfusion and endothelial function to predict preeclampsia. Materials and Methods A total of 91 patients considered as at risk for developing preeclampsia were recruited at the prenatal unit of the authors' institution. All the patients underwent FMD and Doppler of uterine arteries between their 24th and 28th gestational weeks. Calculations of sensitivity and specificity for both isolated and associated methods were performed. Results Nineteen out of the 91 patients developed preeclampsia, while the rest remained normotensive. Doppler flowmetry of uterine arteries with presence of bilateral protodiastolic notch had sensitivity of 63.1% and specificity of 87.5% for the prediction of preeclampsia. Considering a cutoff value of 6.5%, FMD showed sensitivity of 84.2% and specificity of 73.6%. In a parallel analysis, as the two methods were associated, sensitivity was 94.2% and specificity, 64.4%. Conclusion The association of Doppler study of uterine arteries and FMD has proved to be an interesting clinical strategy for the prediction of preeclampsia, which may represent a positive impact on prenatal care of patients considered as at high-risk for developing such a condition.

A Meta-Analysis of Trabecular Bone Score in Fracture Risk Prediction and Its Relationship to FRAX.

Trabecular bone score (TBS) is a gray-level textural index of bone microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry (DXA) images. TBS is a bone mineral density (BMD)-independent predictor of fracture risk. The objective of this meta-analysis was to determine whether TBS predicted fracture risk independently of FRAX probability and to examine their combined performance by adjusting the FRAX probability for TBS. We utilized individual-level data from 17,809 men and women in 14 prospective population-based cohorts. Baseline evaluation included TBS and the FRAX risk variables, and outcomes during follow-up (mean 6.7 years) comprised major osteoporotic fractures. The association between TBS, FRAX probabilities, and the risk of fracture was examined using an extension of the Poisson regression model in each cohort and for each sex and expressed as the gradient of risk (GR; hazard ratio per 1 SD change in risk variable in direction of increased risk). FRAX probabilities were adjusted for TBS using an adjustment factor derived from an independent cohort (the Manitoba Bone Density Cohort). Overall, the GR of TBS for major osteoporotic fracture was 1.44 (95% confidence interval [CI] 1.35-1.53) when adjusted for age and time since baseline and was similar in men and women (p > 0.10). When additionally adjusted for FRAX 10-year probability of major osteoporotic fracture, TBS remained a significant, independent predictor for fracture (GR = 1.32, 95% CI 1.24-1.41). The adjustment of FRAX probability for TBS resulted in a small increase in the GR (1.76, 95% CI 1.65-1.87 versus 1.70, 95% CI 1.60-1.81). A smaller change in GR for hip fracture was observed (FRAX hip fracture probability GR 2.25 vs. 2.22). TBS is a significant predictor of fracture risk independently of FRAX. The findings support the use of TBS as a potential adjustment for FRAX probability, though the impact of the adjustment remains to be determined in the context of clinical assessment guidelines. © 2015 American Society for Bone and Mineral Research.

Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations

Reduced ceria nanofilms from structure prediction

Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth.

Prediction of individual automobile RBNS claim reserves in the context of Solvency II

Automobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported But Not Settled (RBNS) claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project (CEIOPS, 2007) a statistical model is here implemented for RBNS reserve estimation. Lognormality on empirical compensation cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The BI severity is predicted by means of a heteroscedastic multiple choice model, because empirical evidence has found that the variability in the latent severity of injured individuals travelling by car is not constant. It is shown that this methodology can improve the accuracy of RBNS reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners.

Present-day deformation of the Pyrenees revealed by GPS surveying and earthquake focal mechanisms until 2011

The Pyrenean mountain range is a slowly deforming belt with continuous and moderate seismic activity. To quantify its deformation field, we present the velocity field estimated from a GPS survey of the Pyrenees spanning 18 yr. The PotSis and ResPyr networks, including a total of 85 GPS sites, were installed and first measured in 1992 and 1995 1997, respectively, and remeasured in 2008 and 2010. We obtain a deformation field with velocities less than 1 mm yr−1 across the range. The estimated velocities for individual stations do not differ significantly from zero with 95 per cent confidence. Even so, we estimate a maximum extensional horizontal strain rate of 2.0 ± 1.7 nanostrain per year in a N S direction in the western part of the range. We do not interpret the vertical displacements due to their large uncertainties. In order to compare the horizontal strain rates with the seismic activity, we analyse a set of 194 focal mechanisms using three methods: (i) the 'r' factor relating their P and T axes, (ii) the stress tensors obtained by fault slip inversion and (iii) the strain-rate tensors. Stress and strain-rate tensors are estimated for: (i) the whole data set, (ii) the eastern and western parts of the range separately, and (iii) eight zones, which are defined based on the seismicity and the tectonic patterns of the Pyrenees. Each of these analyses reveals a lateral variation of the deformation style from compression and extension in the east to extension and strike-slip in the west of the range. Although the horizontal components of the strain-rate tensors estimated from the seismic data are slightly smaller in magnitude than those computed from the GPS velocity field, they are consistent within the 2σ uncertainties. Furthermore, the orientations of their principal axes agree with the mapped active faults.

Minimization of the experimental workload for the prediction of pollutants propagation in rivers. Mathematical modelling and knowledge re-use

The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.

Application of GA-PLS and GA-KPLS calculations for the prediction of the retention indices of essential oils

Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.