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

Comparison between non‐orographic gravity‐wave parameterizations used in QBOi models and Strateole 2 constant‐level balloons

Gravity‐wave (GW) parameterizations from 12 general circulation models (GCMs) participating in the Quasi‐Biennial Oscillation initiative (QBOi) are compared with Strateole 2 balloon observations made in the tropical lower stratosphere from November 2019–February 2020 (phase 1) and from October 2021–January 2022 (phase 2). The parameterizations employ the three standard techniques used in GCMs to represent subgrid‐scale non‐orographic GWs, namely the two globally spectral techniques developed by Warner and McIntyre (1999) and Hines (1997), as well as the “multiwaves” approaches following the work of Lindzen (1981). The input meteorological fields necessary to run the parameterizations offline are extracted from the ERA5 reanalysis and correspond to the meteorological conditions found underneath the balloons. In general, there is fair agreement between amplitudes derived from measurements for waves with periods less than 1 $$1$$ h and parameterizations. The correlation between the daily observations and the corresponding results of the parameterization can be around 0.4, which is 99 % $$99\%$$ significant, since 1200 days of observations are used. Given that the parameterizations have only been tuned to produce a quasi‐biennial oscillation (QBO) in the models, the 0.4 correlation coefficient of the GW momentum fluxes is surprisingly good. These correlations nevertheless vary between schemes and depend little on their formulation (globally spectral versus multiwaves for instance). We therefore attribute these correlations to dynamical filtering, which all schemes take into account, whereas only a few relate the gravity waves to their sources. Statistically significant correlations are mostly found for eastward‐propagating waves, which may be due to the fact that during both Strateole 2 phases the QBO is easterly at the altitude of the balloon flights. We also found that the probability density functions (pdfs) of the momentum fluxes are represented better in spectral schemes with constant sources than in schemes (“spectral” or “multiwaves”) that relate GWs only to their convective sources

A prospective compound screening contest identified broader inhibitors for Sirtuin 1

Potential inhibitors of a target biomolecule, NAD-dependent deacetylase Sirtuin 1, were identified by a contest-based approach, in which participants were asked to propose a prioritized list of 400 compounds from a designated compound library containing 2.5 million compounds using in silico methods and scoring. Our aim was to identify target enzyme inhibitors and to benchmark computer-aided drug discovery methods under the same experimental conditions. Collecting compound lists derived from various methods is advantageous for aggregating compounds with structurally diversified properties compared with the use of a single method. The inhibitory action on Sirtuin 1 of approximately half of the proposed compounds was experimentally accessed. Ultimately, seven structurally diverse compounds were identified

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