How do multilateral institutions influence individual perceptions of international affairs? Evidence from Europe and Asia

To date there has been no systematic study of the relationship between individuals’ opinions of different institutions and their perceptions of world affairs. This article tries to fill this gap by using a large cross-country data set comprising nine EU members and seven Asian nations and instrumental variable bivariate probit regression analysis. Controlling for a host of factors, the article shows that individuals’ confidence in multilateral institutions affects their perceptions of whether or not their country is being treated fairly in international affairs. This finding expands upon both theoretical work on multilateral institutions that has focused on state actors’ rationale for engaging in multilateral cooperation and empirical work that has treated confidence in multilateral institutions as a dependent variable. The article also shows that individuals’ confidence in different international organizations has undifferentiated effects on their perceptions of whether or not their country is being treated fairly in international affairs, though individuals more knowledgeable about international affairs exhibit slightly different attitudes. Finally, the article demonstrates significant differences in opinion across Europe and Asia.

Interaction among non-toxic phytoplankton, toxic phytoplankton and zooplankton: inferences from field observations

We explore the mutual dependencies and interactions among different groups of species of the plankton population, based on an analysis of the long-term field observations carried out by our group in the North–West coast of the Bay of Bengal. The plankton community is structured into three groups of species, namely, non-toxic phytoplankton (NTP), toxic phytoplankton (TPP) and zooplankton. To find the pair-wise dependencies among the three groups of plankton, Pearson and partial correlation coefficients are calculated. To explore the simultaneous interaction among all the three groups, a time series analysis is performed. Following an Expectation Maximization (E-M) algorithm, those data points which are missing due to irregularities in sampling are estimated, and with the completed data set a Vector Auto-Regressive (VAR) model is analyzed. The overall analysis demonstrates that toxin-producing phytoplankton play two distinct roles: the inhibition on consumption of toxic substances reduces the abundance of zooplankton, and the toxic materials released by TPP significantly compensate for the competitive disadvantages among phytoplankton species. Our study suggests that the presence of TPP might be a possible cause for the generation of a complex interaction among the large number of phytoplankton and zooplankton species that might be responsible for the prolonged coexistence of the plankton species in a fluctuating biomass.

Elastic net orthogonal forward regression

An efficient two-level model identification method aiming at maximising a model׳s generalisation capability is proposed for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularisation parameters in the elastic net are optimised using a particle swarm optimisation (PSO) algorithm at the upper level by minimising the leave one out (LOO) mean square error (LOOMSE). There are two elements of original contributions. Firstly an elastic net cost function is defined and applied based on orthogonal decomposition, which facilitates the automatic model structure selection process with no need of using a predetermined error tolerance to terminate the forward selection process. Secondly it is shown that the LOOMSE based on the resultant ENOFR models can be analytically computed without actually splitting the data set, and the associate computation cost is small due to the ENOFR procedure. Consequently a fully automated procedure is achieved without resort to any other validation data set for iterative model evaluation. Illustrative examples are included to demonstrate the effectiveness of the new approaches.

Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)

In addition to CO2, the climate impact of aviation is strongly influenced by non-CO2 emissions, such as nitrogen oxides, influencing ozone and methane, and water vapour, which can lead to the formation of persistent contrails in ice-supersaturated regions. Because these non-CO2 emission effects are characterised by a short lifetime, their climate impact largely depends on emission location and time; that is to say, emissions in certain locations (or times) can lead to a greater climate impact (even on the global average) than the same emission in other locations (or times). Avoiding these climate-sensitive regions might thus be beneficial to climate. Here, we describe a modelling chain for investigating this climate impact mitigation option. This modelling chain forms a multi-step modelling approach, starting with the simulation of the fate of emissions released at a certain location and time (time-region grid points). This is performed with the chemistry–climate model EMAC, extended via the two submodels AIRTRAC (V1.0) and CONTRAIL (V1.0), which describe the contribution of emissions to the composition of the atmosphere and to contrail formation, respectively. The impact of emissions from the large number of time-region grid points is efficiently calculated by applying a Lagrangian scheme. EMAC also includes the calculation of radiative impacts, which are, in a second step, the input to climate metric formulas describing the global climate impact of the emission at each time-region grid point. The result of the modelling chain comprises a four-dimensional data set in space and time, which we call climate cost functions and which describes the global climate impact of an emission at each grid point and each point in time. In a third step, these climate cost functions are used in an air traffic simulator (SAAM) coupled to an emission tool (AEM) to optimise aircraft trajectories for the North Atlantic region. Here, we describe the details of this new modelling approach and show some example results. A number of sensitivity analyses are performed to motivate the settings of individual parameters. A stepwise sanity check of the results of the modelling chain is undertaken to demonstrate the plausibility of the climate cost functions.

Conversations on Twitter: structure, pace, balance

Twitter is both a micro-blogging service and a platform for public conversation. Direct conversation is facilitated in Twitter through the use of @’s (mentions) and replies. While the conversational element of Twitter is of particular interest to the marketing sector, relatively few data-mining studies have focused on this area. We analyse conversations associated with reciprocated mentions that take place in a data-set consisting of approximately 4 million tweets collected over a period of 28 days that contain at least one mention. We ignore tweet content and instead use the mention network structure and its dynamical properties to identify and characterise Twitter conversations between pairs of users and within larger groups. We consider conversational balance, meaning the fraction of content contributed by each party. The goal of this work is to draw out some of the mechanisms driving conversation in Twitter, with the potential aim of developing conversational models.

On the clustering of winter storm loss events over Germany

During the last decades, several windstorm series hit Europe leading to large aggregated losses. Such storm series are examples of serial clustering of extreme cyclones, presenting a considerable risk for the insurance industry. Clustering of events and return periods of storm series for Germany are quantified based on potential losses using empirical models. Two reanalysis data sets and observations from German weather stations are considered for 30 winters. Histograms of events exceeding selected return levels (1-, 2- and 5-year) are derived. Return periods of historical storm series are estimated based on the Poisson and the negative binomial distributions. Over 4000 years of general circulation model (GCM) simulations forced with current climate conditions are analysed to provide a better assessment of historical return periods. Estimations differ between distributions, for example 40 to 65 years for the 1990 series. For such less frequent series, estimates obtained with the Poisson distribution clearly deviate from empirical data. The negative binomial distribution provides better estimates, even though a sensitivity to return level and data set is identified. The consideration of GCM data permits a strong reduction of uncertainties. The present results support the importance of considering explicitly clustering of losses for an adequate risk assessment for economical applications.

The Solar Stormwatch CME catalogue: results from the first space weather citizen science project

Solar Stormwatch was the first space weather citizen science project, the aim of which was to identify and track coronal mass ejections (CMEs) observed by the Heliospheric Imagers aboard the STEREO satellites. The project has now been running for approximately 4 years, with input from >16000 citizen scientists, resulting in a dataset of >38000 time-elongation profiles of CME trajectories, observed over 18 pre-selected position angles. We present our method for reducing this data set into aCME catalogue. The resulting catalogue consists of 144 CMEs over the period January-2007 to February-2010, of which 110 were observed by STEREO-A and 77 were observed by STEREO-B. For each CME, the time-elongation profiles generated by the citizen scientists are averaged into a consensus profile along each position angle that the event was tracked. We consider this catalogue to be unique, being at present the only citizen science generated CME catalogue, tracking CMEs over an elongation range of 4 degrees out to a maximum of approximately 70 degrees. Using single spacecraft fitting techniques, we estimate the speed, direction, solar source region and latitudinal width of each CME. This shows that, at present, the Solar Stormwatch catalogue (which covers only solar minimum years) contains almost exclusively slow CMEs, with a mean speed of approximately 350 kms−1. The full catalogue is available for public access at www.met.reading.ac.uk/spate/stormwatch. This includes, for each event, the unprocessed time-elongation profiles generated by Solar Stormwatch, the consensus time-elongation profiles and a set of summary plots, as well as the estimated CME properties.

Methane in the atmosphere of the transiting hot Neptune GJ436b?

We present an analysis of seven primary transit observations of the hot Neptune GJ436b at 3.6, 4.5, and 8 μm obtained with the Infrared Array Camera on the Spitzer Space Telescope. After correcting for systematic effects, we fitted the light curves using the Markov Chain Monte Carlo technique. Combining these new data with the EPOXI, Hubble Space Telescope, and ground-based V, I, H, and Ks published observations, the range 0.5-10 μm can be covered. Due to the low level of activity of GJ436, the effect of starspots on the combination of transits at different epochs is negligible at the accuracy of the data set. Representative climate models were calculated by using a three-dimensional, pseudospectral general circulation model with idealized thermal forcing. Simulated transit spectra of GJ436b were generated using line-by-line radiative transfer models including the opacities of the molecular species expected to be present in such a planetary atmosphere. A new, ab-initio-calculated, line list for hot ammonia has been used for the first time. The photometric data observed at multiple wavelengths can be interpreted with methane being the dominant absorption after molecular hydrogen, possibly with minor contributions from ammonia, water, and other molecules. No clear evidence of carbon monoxide and carbon dioxide is found from transit photometry. We discuss this result in the light of a recent paper where photochemical disequilibrium is hypothesized to interpret secondary transit photometric data. We show that the emission photometric data are not incompatible with the presence of abundant methane, but further spectroscopic data are desirable to confirm this scenario.

Atmospheric electric field measurements in urban environment and the pollutant aerosol weekly dependence

The weekly dependence of pollutant aerosols in the urban environment of Lisbon (Portugal) is inferred from the records of atmospheric electric field at Portela meteorological station (38°47′N,9°08′W). Measurements were made with a Bendorf electrograph. The data set exists from 1955 to 1990, but due to the contaminating effect of the radioactive fallout during 1960 and 1970s, only the period between 1980 and 1990 is considered here. Using a relative difference method a weekly dependence of the atmospheric electric field is found in these records, which shows an increasing trend between 1980 and 1990. This is consistent with a growth of population in the Lisbon metropolitan area and consequently urban activity, mainly traffic. Complementarily, using a Lomb–Scargle periodogram technique the presence of a daily and weekly cycle is also found. Moreover, to follow the evolution of theses cycles, in the period considered, a simple representation in a colour surface plot representation of the annual periodograms is presented. Further, a noise analysis of the periodograms is made, which validates the results found. Two datasets were considered: all days in the period, and fair-weather days only.

Intercomparison and evaluation of global aerosol microphysical properties among AeroCom models of a range of complexity

Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

Comparisons between EISCAT observations and model calculations of the high latitude ionosphere

Calculations using a numerical model of the convection dominated high latitude ionosphere are compared with observations made by EISCAT as part of the UK-POLAR Special Programme. The data used were for 24–25 October 1984, which was characterized by an unusually steady IMF, with Bz < 0 and By > 0; in the calculations it was assumed that a steady IMF implies steady convection conditions. Using the electric field models of Heppner and Maynard (1983) appropriate to By > 0 and precipitation data taken from Spiroet al. (1982), we calculated the velocities and electron densities appropriate to the EISCAT observations. Many of the general features of the velocity data were reproduced by the model. In particular, the phasing of the change from eastward to westward flow in the vicinity of the Harang discontinuity, flows near the dayside throat and a region of slow flow at higher latitudes near dusk were well reproduced. In the afternoon sector modelled velocity values were significantly less than those observed. Electron density calculations showed good agreement with EISCAT observations near the F-peak, but compared poorly with observations near 211 km. In both cases, the greatest disagreement occurred in the early part of the observations, where the convection pattern was poorly known and showed some evidence of long term temporal change. Possible causes for the disagreement between observations and calculations are discussed and shown to raise interesting and, as yet, unresolved questions concerning the interpretation of the data. For the data set used, the late afternoon dip in electron density observed near the F-peak and interpreted as the signature of the mid-latitude trough is well reproduced by the calculations. Calculations indicate that it does not arise from long residence times of plasma on the nightside, but is the signature of a gap between two major ionization sources, viz. photoionization and particle precipitation.

Superthermal ion signatures of auroral acceleration processes

The retarding ion mass spectrometer on the Dynamics Explorer 1 spacecraft has generated a unique data set which documents, among other things, the occurrence of non-Maxwellian superthermal features in the auroral topside ionosphere distribution functions. In this paper, we provide a representative sampling of the observed features and their spatial morphology as observed at altitudes in the range from a few thousand kilometers to a few earth radii. At lower altitudes, these features appear at auroral latitudes separating regions of polar cap and subauroral light ion polar wind. The most common signature is the appearance of an upgoing energetic tail having conical lobes representing significant ion heat and number flux in all species, including O+. Transverse ion heating below the observation point at several thousand kilometers is clearly associated with O+ outflows. In some events observed, transverse acceleration apparently involves nearly the entire thermal plasma, the distribution function becomes highly anisotropic with T⊥ > T∥, and may actually develop a minimum at zero velocity, i.e., become a torus having as its axis the local magnetic field direction. At higher altitudes, the localized dayside source region appears as a field aligned flow which is dispersed tailward across the polar cap according to parallel velocity by antisunward convective flow, so that upflowing low energy O+ ions appear well within the polar cap region. While this flow can appear beamlike in a given location, the energy dispersion observed implies a very broad energy distribution at the source, extending from a few tenths of an eV to in excess of 50 eV. On the nightside, upgoing ion beams are found to be latitudinally bounded by regions of ion conics whose half angles increase with increasing separation from the beam region, indicating low altitude transverse acceleration in immediate proximity to, and below, the parallel acceleration region. These observations reveal a clear distinction between classical polar wind ion outflow and O+ enhanced superthermal flows, and confirm the importance of low altitude transverse acceleration in ionospheric plasma transport, as suggested by previous observations.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Infrared and millimetre-wave scintillometry in the suburban environment – Part 2: Large-area sensible and latent heat fluxes

A millimetre-wave scintillometer was paired with an infrared scintillometer, enabling estimation of large-area evapotranspiration across northern Swindon, a suburban area in the UK. Both sensible and latent heat fluxes can be obtained using this "two-wavelength" technique, as it is able to provide both temperature and humidity structure parameters, offering a major advantage over conventional single-wavelength scintillometry. The first paper of this two-part series presented the measurement theory and structure parameters. In this second paper, heat fluxes are obtained and analysed. These fluxes, estimated using two-wavelength scintillometry over an urban area, are the first of their kind. Source area modelling suggests the scintillometric fluxes are representative of 5–10 km2. For comparison, local-scale (0.05–0.5 km2) fluxes were measured by an eddy covariance station. Similar responses to seasonal changes are evident at the different scales but the energy partitioning varies between source areas. The response to moisture availability is explored using data from 2 consecutive years with contrasting rainfall patterns (2011–2012). This extensive data set offers insight into urban surface-atmosphere interactions and demonstrates the potential for two-wavelength scintillometry to deliver fluxes over mixed land cover, typically representative of an area 1–2 orders of magnitude greater than for eddy covariance measurements. Fluxes at this scale are extremely valuable for hydro-meteorological model evaluation and assessment of satellite data products

(How) Do research and administrative duties affect university professors’ teaching?

We analyze the interaction between university professors’ teaching quality and their research and administrative activities. Our sample is a high-quality individual panel data set from a medium size public Spanish university that allows us to avoid several types of biases frequently encountered in the literature. Although researchers teach roughly 20% more than non-researchers, their teaching quality is also 20% higher. Instructors with no research are 5 times more likely than the rest to be among the worst teachers. Over much of the relevant range, we find a nonlinear and positive relationship between research output and teaching quantity on teaching quality. Our conclusions may be useful for decision makers in universities and governments.