Bridge condition assessment from long-term monitoring by means of Bayesian hypothesis test

Fifth International Symposium on Life-Cycle Civil Engineering (IALCCE 2016), 16-19 October 2016, Delft, The Netherlands.This study presents an approach to reduce effects of environmental and operational factors on long-term monitoring data of bridges. The Bayesian approach comprising both Bayesian regression and Bayesian hypothesis test is applied to investigate monitoring data of an in-service seven-span plate-Gerber bridge. This study considers time-varying temperature and vehicle weights as environmental and operational factors respectively. Vehicle weights were measured utilizing a bridge weigh-in-motion (BWIM) system installed on the bridge. All data was taken from a healthy bridge, since no damage and deterioration was reported during the monitoring period. Observations through the study demonstrated that considering both temperature and vehicle weight as environmental and operational factors in Bayesian regression led to improved regression results than that considering only temperature. It also showed that monitoring the data observed at a specific time could reduce influence of traffic in long-term monitoring. In the Bayesian hypothesis testing utilizing data from the healthy bridge, the bridge was judged as healthy

Investigation of the thermal expansion and heat capacity of the CaCu3Ti4O12 ceramics

The thermal expansion of the CaCu3Ti4O12 ceramics has been measured over a wide temperature range 120–1200 K. The high quality of the samples under study has been confirmed by good agreement of the results of measurements of the heat capacity in the range 2–300 K and in the vicinity of the phase transition of magnetic nature at 25 K with the data for the single crystal. No anomalies in the thermal expansion that can be associated with the phase transition at 726–732 K assumed by other investigators have been found. The influence exerted on the thermal expansion by the heat treatment of the sample in a helium atmosphere and in air has been investigated

Evaluation of the Quasi‐Biennial Oscillation in global climate models for the SPARC QBO‐initiative

The Quasi‐Biennial Oscillation initiative (QBOi) is a model intercomparison programme that specifically targets simulation of the QBO in current global climate models. Eleven of the models or model versions that participated in a QBOi intercomparison study have upper boundaries in or above the mesosphere and therefore simulate the region where the stratopause semiannual oscillation (SAO) is the dominant mode of variability of zonal winds in the tropical upper stratosphere. Comparisons of the SAO simulations in these models are presented here. These show that the model simulations of the amplitudes and phases of the SAO in zonal‐mean zonal wind near the stratopause agree well with the information derived from available observations. However, most of the models simulate time‐average zonal winds that are more westward than determined from observations, in some cases by several tens of m·s$^{–1}$. Validation of wave activity in the models is hampered by the limited observations of tropical waves in the upper stratosphere but suggests a deficit of eastward forcing either by large‐scale waves, such as Kelvin waves, or by gravity waves

Increased Level of Myeloid-Derived Suppressor Cells, Programmed Death Receptor Ligand 1/Programmed Death Receptor 1, and Soluble CD25 in Sokal High Risk Chronic Myeloid Leukemia

Peer reviewe

No interaction between serotonin transporter gene (5-HTTLPR) polymorphism and adversity on depression among Japanese children and adolescents

Background: Identification of gene × environment interactions (G × E) for depression is a crucial step in ascertaining the mechanisms underpinning the disorder. Earlier studies have indicated strong genetic influences and numerous environmental risk factors. In relation to childhood and adolescent depression, evidence is accumulating that the quality of the parental environment is associated with serotonin biology in children. We hypothesized that maternal depression is a crucial environmental risk factor associated with serotonin-regulating genes.Methods: This study was designed to ascertain the G × E interaction for diagnosis of depression in a Japanese pediatric sample. DNA samples from 55 pediatric patients with depression and 58 healthy schoolchildren were genotyped for the 5-HTT (2 short (S) alleles at the 5-HTT locus) promoter serotonin-transporter-linked polymorphic region (5-HTTLPR) polymorphism. We examined whether an adverse parental environment, operationalized as the mother\u27s history of recurrent major depressive disorder, interacts with 5-HTTLPR polymorphism to predict patients\u27 depression symptoms.Results: Binary logistic regression analyses revealed that maternal depression (adversity), gender, and FSIQ significantly affect the diagnosis of depression among children and adolescents. However, no main effect was found for adversity or genotype. Results of multivariable logistic regression analyses using stepwise procedure have elicited some models with a good fit index, which also suggests no interaction between 5-HTTLPR and adversity on depression.Conclusions: To assess G × E interaction, data obtained from children and adolescents who had been carefully diagnosed categorically and data from age-matched controls were analyzed using logistic regression. Despite an equivocal interaction effect, adversity and gender showed significant main effects

DYNAMIC RESPONSE EVALUATION ON CURVED TWIN I-GIRDER BRIDGE USING VEHICLE-BRIDGE COUPLED VIBRATION ANALYSIS

The Thirteenth East Asia-Pacific Conference on Structural Engineering and Construction (EASEC-13), September 11-13, 2013, Sapporo, Japan