Age model and pollen analysis from site GIK16867 in the northern Angola Basin

Sporomorphs and dinoflagellate cysts from site GIK16867 in the northern Angola Basin record the vegetation history of the West African forest during the last 700 ka in relation to changes in salinity and productivity of the eastern Gulf of Guinea. During most cool and cold periods, the Afromontane forest, rather than the open grass-rich dry forest, expanded to lower altitudes partly replacing the lowland rain forest of the borderlands east of the Gulf of Guinea. Except in Stage 3, when oceanic productivity was high during a period of decreased atmospheric circulation, high oceanic productivity is correlated to strong winds. The response of marine productivity in the course of a climatic cycle, however, is earlier than that of wind vigour and makes wind-stress-induced oceanic upwelling in the area less likely. Monsoon variation is well illustrated by the pollen record of increased lowland rain forest that is paired to the dinoflagellate cyst record of decreased salinity forced by increased precipitation and run-off.

Holocene precipitation change in different monsoon sub-regions (time-slices and transient data) simulated by different global climate models, with links to model results

The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak, and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the Holocene rainfall optimum in the different sub-monsoon systems. They rather indicate locally inhomogeneous rainfall changes and show, that single palaeo-records should not be used to characterise the rainfall change and monsoon evolution for entire monsoon sub-systems.

Correlation between anxiety and academic self-concept in interpreter trainees

This paper focuses on two basic issues: the anxiety-generating nature of the interpreting task and the relevance of interpreter trainees’ academic self-concept. The first has already been acknowledged, although not extensively researched, in several papers, and the second has only been mentioned briefly in interpreting literature. This study seeks to examine the relationship between the anxiety and academic self-concept constructs among interpreter trainees. An adapted version of the Foreign Language Anxiety Scale (Horwitz et al., 1986), the Academic Autoconcept Scale (Schmidt, Messoulam & Molina, 2008) and a background information questionnaire were used to collect data. Students’ t-Test analysis results indicated that female students reported experiencing significantly higher levels of anxiety than male students. No significant gender difference in self-concept levels was found. Correlation analysis results suggested, on the one hand, that younger would-be interpreters suffered from higher anxiety levels and students with higher marks tended to have lower anxiety levels; and, on the other hand, that younger students had lower self-concept levels and higher-ability students held higher self-concept levels. In addition, the results revealed that students with higher anxiety levels tended to have lower self-concept levels. Based on these findings, recommendations for interpreting pedagogy are discussed.

New Method for the Estimation of Viscosity of Pure and Mixtures of Ionic Liquids Based on the UNIFAC–VISCO Model

A modified UNIFAC–VISCO group contribution method was developed for the correlation and prediction of viscosity of ionic liquids as a function of temperature at 0.1 MPa. In this original approach, cations and anions were regarded as peculiar molecular groups. The significance of this approach comes from the ability to calculate the viscosity of mixtures of ionic liquids as well as pure ionic liquids. Binary interaction parameters for selected cations and anions were determined by fitting the experimental viscosity data available in literature for selected ionic liquids. The temperature dependence on the viscosity of the cations and anions were fitted to a Vogel–Fulcher–Tamman behavior. Binary interaction parameters and VFT type fitting parameters were then used to determine the viscosity of pure and mixtures of ionic liquids with different combinations of cations and anions to ensure the validity of the prediction method. Consequently, the viscosities of binary ionic liquid mixtures were then calculated by using this prediction method. In this work, the viscosity data of pure ionic liquids and of binary mixtures of ionic liquids are successfully calculated from 293.15 K to 363.15 K at 0.1 MPa. All calculated viscosity data showed excellent agreement with experimental data with a relative absolute average deviation lower than 1.7%.

Use of Galleria mellonella as a model organism to study Legionella pneumophila infection.

Legionella pneumophila, the causative agent of a severe pneumonia named Legionnaires' disease, is an important human pathogen that infects and replicates within alveolar macrophages. Its virulence depends on the Dot/Icm type IV secretion system (T4SS), which is essential to establish a replication permissive vacuole known as the Legionella containing vacuole (LCV). L. pneumophila infection can be modeled in mice however most mouse strains are not permissive, leading to the search for novel infection models. We have recently shown that the larvae of the wax moth Galleria mellonella are suitable for investigation of L. pneumophila infection. G. mellonella is increasingly used as an infection model for human pathogens and a good correlation exists between virulence of several bacterial species in the insect and in mammalian models. A key component of the larvae's immune defenses are hemocytes, professional phagocytes, which take up and destroy invaders. L. pneumophila is able to infect, form a LCV and replicate within these cells. Here we demonstrate protocols for analyzing L. pneumophila virulence in the G. mellonella model, including how to grow infectious L. pneumophila, pretreat the larvae with inhibitors, infect the larvae and how to extract infected cells for quantification and immunofluorescence microscopy. We also describe how to quantify bacterial replication and fitness in competition assays. These approaches allow for the rapid screening of mutants to determine factors important in L. pneumophila virulence, describing a new tool to aid our understanding of this complex pathogen.

Simplified model for prediction of compressive strength of alkali-activated natural pozzolans

The assessment of pozzolanic activity is essential for estimating the reaction of a material as pozzolan. Natural pozzolans can be activated and condensed with sodium silicate in an alkaline environment to synthesize high performance cementitious construction materials with low environmental impact. In this paper, the pozzolanic activities of five natural pozzolans are studied. The correlation between type and chemical composition of natural pozzolan, which affects the formation of the geopolymer gel phase, both for the calcined and untreated natural pozzolans, have been reviewed. The improvement in pozzolanic properties was studied following heat treatment including calcinations and/or elevated curing temperature by using alkali solubility, and compressive strength tests. A model was developed to allow prediction of the alkali-activated pozzolan strength versus their chemical compositions, alkali solubility, and crystallinity.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.

A comparison of sound localisation techniques using cross-correlation and spiking neural networks for mobile robotics

This paper outlines the development of a crosscorrelation algorithm and a spiking neural network (SNN) for sound localisation based on real sound recorded in a noisy and dynamic environment by a mobile robot. The SNN architecture aims to simulate the sound localisation ability of the mammalian auditory pathways by exploiting the binaural cue of interaural time difference (ITD). The medial superior olive was the inspiration for the SNN architecture which required the integration of an encoding layer which produced biologically realistic spike trains, a model of the bushy cells found in the cochlear nucleus and a supervised learning algorithm. The experimental results demonstrate that biologically inspired sound localisation achieved using a SNN can compare favourably to the more classical technique of cross-correlation.

A simplified finite element model for assessing steel fibre reinforced concrete structural performance

The present numerical investigation offers evidence concerning the validity and objectivity of the predictions of a simple, yet practical, finite element model concerning the responses of steel fibre reinforced concrete structural elements under static monotonic and cyclic loading. Emphasis is focused on realistically describing the fully brittle tensile behaviour of plain concrete and the contribution of steel fibres on the post-cracking behaviour it exhibits. The good correlation exhibited between the numerical predictions and their experimental counterparts reveals that, despite its simplicity, the subject model is capable of providing realistic predictions concerning the response of steel fibre reinforced concrete structural configurations exhibiting both ductile and brittle modes of failure without requiring recalibration.

Data Reduction in Intrusion Alert Correlation

Network intrusion detection sensors are usually built around low level models of network traffic. This means that their output is of a similarly low level and as a consequence, is difficult to analyze. Intrusion alert correlation is the task of automating some of this analysis by grouping related alerts together. Attack graphs provide an intuitive model for such analysis. Unfortunately alert flooding attacks can still cause a loss of service on sensors, and when performing attack graph correlation, there can be a large number of extraneous alerts included in the output graph. This obscures the fine structure of genuine attacks and makes them more difficult for human operators to discern. This paper explores modified correlation algorithms which attempt to minimize the impact of this attack.

Dynamic model development of adiabatic compressed air energy storage

The share of variable renewable energy in electricity generation has seen exponential growth during the recent decades, and due to the heightened pursuit of environmental targets, the trend is to continue with increased pace. The two most important resources, wind and insolation both bear the burden of intermittency, creating a need for regulation and posing a threat to grid stability. One possibility to deal with the imbalance between demand and generation is to store electricity temporarily, which was addressed in this thesis by implementing a dynamic model of adiabatic compressed air energy storage (CAES) with Apros dynamic simulation software. Based on literature review, the existing models due to their simplifications were found insufficient for studying transient situations, and despite of its importance, the investigation of part load operation has not yet been possible with satisfactory precision. As a key result of the thesis, the cycle efficiency at design point was simulated to be 58.7%, which correlated well with literature information, and was validated through analytical calculations. The performance at part load was validated against models shown in literature, showing good correlation. By introducing wind resource and electricity demand data to the model, grid operation of CAES was studied. In order to enable the dynamic operation, start-up and shutdown sequences were approximated in dynamic environment, as far as is known, the first time, and a user component for compressor variable guide vanes (VGV) was implemented. Even in the current state, the modularly designed model offers a framework for numerous studies. The validity of the model is limited by the accuracy of VGV correlations at part load, and in addition the implementation of heat losses to the thermal energy storage is necessary to enable longer simulations. More extended use of forecasts is one of the important targets of development, if the system operation is to be optimised in future.

Savani: A variable resolution whole-mantle model of anisotropic shear velocity variations based on multiple data sets

International audience