The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35◦ AGCM

The South Asian monsoon is one of the most significant manifestations of the seasonal cycle. It directly impacts nearly one third of the world’s population and also has substantial global influence. Using 27-year integrations of a high-resolution atmospheric general circulation model (Met Office Unified Model), we study changes in South Asian monsoon precipitation and circulation when horizontal resolution is increased from approximately 200 to 40 km at the equator (N96 to N512, 1.9 to 0.35◦). The high resolution, integration length and ensemble size of the dataset make this the most extensive dataset used to evaluate the resolution sensitivity of the South Asian monsoon to date. We find a consistent pattern of JJAS precipitation and circulation changes as resolution increases, which include a slight increase in precipitation over peninsular India, changes in Indian and Indochinese orographic rain bands, increasing wind speeds in the Somali Jet, increasing precipitation over the Maritime Continent islands and decreasing precipitation over the northern Maritime Continent seas. To diagnose which resolution related processes cause these changes we compare them to published sensitivity experiments that change regional orography and coastlines. Our analysis indicates that improved resolution of the East African Highlands results in the improved representation of the Somali Jet and further suggests that improved resolution of orography over Indochina and the Maritime Continent results in more precipitation over the Maritime Continent islands at the expense of reduced precipitation further north. We also evaluate the resolution sensitivity of monsoon depressions and lows, which contribute more precipitation over northeast India at higher resolution. We conclude that while increasing resolution at these scales does not solve the many monsoon biases that exist in GCMs, it has a number of small, beneficial impacts.

Cyanobacteria in biological soil crusts, Earth´s Most Extensive Biofilms: adaptation and sensitivity to global warming

School of Life Sciences, Arizona State University, Tempe AZ, USA

The impact of financial development and market conditions on investment-cash flow sensitivity: global evidence

In this study, we analyze the impact of financial development and market conditions on investment-cash flow sensitivity during the 2006-2014 for 76 countries. First, the results show a relationship between investment-cash flow sensitivity and an index of financial development and its components. Second, 68 countries are affected by the 2008-2009 financial crisis, but only 16 countries exhibit a higher investment-cash flow sensitivity during the crisis. Third, investment-cash flow sensitivity is lower in countries with a larger primary debt market, while the size of the primary equity market has no impact. Finally, analyzing investment-cash flow sensitivity over time, we find lower sensitivity during years associated with higher primary debt market activity.

Solar sensitivity experiments for the pre-industrial time period using the comprehensive global climate model CCSM3 (Community Climate System Model 3)

The Southern Hemisphere Westerly Winds (SWW) constitute an important zonal circulation that influences large-scale precipitation patterns and ocean circulation. Variations in their intensity and latitudinal position have been suggested to exert a strong influence on the CO2 budget in the Southern Ocean, thus making them a potential factor affecting the global climate. The possible influence of solar forcing on SWW variability during the Holocene is addressed. Solar sensitivity experiments with a comprehensive global climate model (CCSM3) are carried out to study the response of SWW to solar variability. In addition, It is shown that a high-resolution iron record from the Chilean continental slope (41° S), which is interpreted to reflect changes in the position of the SWW, is significantly correlated with reconstructed solar activity during the past 3000 years. Taken together, the proxy and model results suggest that centennial-scale periods of lower (higher) solar activity caused equatorward (southward) shifts of the annual mean SWW.

Optic flow in human vision: MEG reveals a foveo-fugal bias in V1, specialization for spiral space in hMSTs, and global motion sensitivity in the IPS

Abstract We recorded MEG responses from 17 participants viewing random-dot patterns simulating global optic flow components (expansion, contraction, rotation, deformation, and translation) and a random motion control condition. Theta-band (3–7 Hz), MEG signal power was greater for expansion than the other optic flow components in a region concentrated along the calcarine sulcus, indicating an ecologically valid, foveo-fugal bias for unidirectional motion sensors in V1. When the responses to the optic flow components were combined, a decrease in MEG beta-band (17–23 Hz) power was found in regions extending beyond the calcarine sulcus to the posterior parietal lobe (inferior to IPS), indicating the importance of structured motion in this region. However, only one cortical area, within or near the V5/hMT+ complex, responded to all three spiral-space components (expansion, contraction, and rotation) and showed no selectivity for global translation or deformation: we term this area hMSTs. This is the first demonstration of an exclusive region for spiral space in the human brain and suggests a functional role better suited to preliminary analysis of ego-motion than surface pose, which would involve deformation. We also observed that the rotation condition activated the cerebellum, suggesting its involvement in visually mediated control of postural adjustment.

Low cost 3D global instability analysis and flow sensitivity based on dynamic mode decomposition and high-order numerical tools

We explore the recently developed snapshot-based dynamic mode decomposition (DMD) technique, a matrix-free Arnoldi type method, to predict 3D linear global flow instabilities. We apply the DMD technique to flows confined in an L-shaped cavity and compare the resulting modes to their counterparts issued from classic, matrix forming, linear instability analysis (i.e. BiGlobal approach) and direct numerical simulations. Results show that the DMD technique, which uses snapshots generated by a 3D non-linear incompressible discontinuous Galerkin Navier?Stokes solver, provides very similar results to classical linear instability analysis techniques. In addition, we compare DMD results issued from non-linear and linearised Navier?Stokes solvers, showing that linearisation is not necessary (i.e. base flow not required) to obtain linear modes, as long as the analysis is restricted to the exponential growth regime, that is, flow regime governed by the linearised Navier?Stokes equations, and showing the potential of this type of analysis based on snapshots to general purpose CFD codes, without need of modifications. Finally, this work shows that the DMD technique can provide three-dimensional direct and adjoint modes through snapshots provided by the linearised and adjoint linearised Navier?Stokes equations advanced in time. Subsequently, these modes are used to provide structural sensitivity maps and sensitivity to base flow modification information for 3D flows and complex geometries, at an affordable computational cost. The information provided by the sensitivity study is used to modify the L-shaped geometry and control the most unstable 3D mode.

Uso de perfis cromatográficos de voláteis de cafés arábicas torrados para a diferenciação das amostras segundo o sabor, o aroma e a qualidade global da bebida

In this work, the volatile chromatographic profiles of roasted Arabica coffees, previously analyzed for their sensorial attributes, were explored by principal component analysis. The volatile extraction technique used was the solid phase microextraction. The correlation optimized warping algorithm was used to align the gas chromatographic profiles. Fifty four compounds were found to be related to the sensorial attributes investigated. The volatiles pyrrole, 1-methyl-pyrrole, cyclopentanone, dihydro-2-methyl-3-furanone, furfural, 2-ethyl-5-methyl-pyrazine, 2-etenyl-n-methyl-pyrazine, 5-methyl-2-propionyl-furan compounds were important for the differentiation of coffee beverage according to the flavour, cleanliness and overall quality. Two figures of merit, sensitivity and specificity (or selectivity), were used to interpret the sensory attributes studied.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

A global marker database for Phytophthora infestans

A marker database was compiled for isolates of the potato and tomato late blight pathogen, Phytophthora infestans, originating from 41 locations which include 31 countries plus 10 regions within Mexico. Presently, the database contains information on 1,776 isolates for one or more of the following markers: restriction fragment length polymorphism (RFLP) fingerprint consisting of 23 bands; mating type; dilocus allozyme genotype; mitochondrial DNA haplotype; sensitivity to the fungicide metalaxyl; and virulence. In the database, 305 entries have unique RFLP fingerprints and 258 entries have unique multilocus genotypes based on RFLP fingerprint, dilocus allozyme genotype, and mating type. A nomenclature is described for naming multilocus genotypes based on the International Organization for Standardization (ISO) two-letter country code and a unique number, Forty-two previously published multilocus genotypes are represented in the database with references to publications. As a result of compilation of the database, seven new genotypes were identified and named. Cluster analysis of genotypes from clonally propagated populations worldwide generally confirmed a previously published classification of old and new genotypes. Genotypes from geographically distant countries were frequently clustered, and several old and new genotypes were found in two or more distant countries. The cluster analysis also demonstrated that A2 genotypes from Argentina differed from all others. The database is available via the Internet, and thus can serve as a resource for Phytophthora workers worldwide.

Serotonin and Sensitivity to Trauma-Related Exposure in Selective Serotonin Reuptake Inhibitors-Recovered Posttraumatic Stress Disorder

Background: Selective serotonin reuptake inhibitors (SSRIs) are first-line treatments for posttraumatic stress disorder (PTSD). Serotonergic (5HT) attenuation of stress sensitivity is postulated from SSRIs` effects in other anxiety disorders, and we studied this in PTSD. Methods: Ten patients with PTSD fully recovered on SSRIs (Clinical Global Impression Scale-I 1 and 2) were enrolled in the study. Patients were tested on two occasions I week apart; in each session, they received a drink containing large neutral amino acids (LNAAs) either with (sham tryptophan depletion [STD], control) or without (acute tryptophan depletion [ATD]) tryptophan. At 5.5 hours after the drink, subjects were exposed to a trauma-related exposure challenge. Self-reports of PTSD (visual analogue scales [VAS] and the Davidson Trauma Scale [DTSI), anxiety (Spielberger State Inventory [STAI] Form Y-1), and mood (Profile of Mood States [POMS]) were obtained. Heart rate (HR), systolic (SBP) and diastolic (DBP) blood pressure were also measured. Results: The trauma-related exposure challenge induced anxiety on both days, with more marked responses on the ATD day according to VAS, DTS, POMS, and DBP (p < .05). A trend of significance (.1 > p >.05) was observed for STAI Form Y-1, HR, and SBP. Conclusions: These data demonstrate that ATD accentuates responses to trauma-related stimuli in SSRI-recovered PTSD. They also suggest that SSRI-induced increases in serotonin function restrain PTSD symptoms, especially under provocation, supporting a role for serotonin in mediating stress resilience.

Sensitivity and uncertainty analyses for burden of disease and risk factor estimates

Epidemiological studies report confidence or uncertainty intervals around their estimates. Estimates of the burden of diseases and risk factors are subject to a broader range of uncertainty because of the combination of multiple data sources and value choices. Sensitivity analysis can be used to examine the effects of social values that have been incorporated into the design of the disability–adjusted life year (DALY). Age weight, where a year of healthy life lived at one age is valued differently from at another age, is the most controversial value built into the DALY. The discount rate, which addresses the difference in value of current versus future health benefits, also has been criticized. The distribution of the global disease burden and rankings of various conditions are largely insensitive to alternate assumptions about the discount rate and age weighting. The major effects of discounting and age weighting are to enhance the importance of neuropsychiatric conditions and sexually transmitted infections. The Global Burden of Disease study also has been criticized for estimating mortality and disease burden for regions using incomplete and uncertain data. Including uncertain results, with uncertainty quantified to the extent possible, is preferable, however, to leaving blank cells in tables intended to provide policy makers with an overall assessment of burden of disease. No estimate is generally interpreted as no problem. Greater investment in getting the descriptive epidemiology of diseases and injuries correct in poor countries will do vastly more to reduce uncertainty in disease burden assessments than a philosophical debate about the appropriateness of social value