The modern pollen-vegetation relationship of a tropical forest-savannah mosaic landscape, Ghana, West Africa

Transitions between forest and savannah vegetation types in fossil pollen records are often poorly understood due to over-production by taxa such as Poaceae and a lack of modern pollen-vegetation studies. Here, modern pollen assemblages from within a forest-savannah transition in West Africa are presented and compared, their characteristic taxa discussed, and implications for the fossil record considered. Fifteen artificial pollen traps were deployed for 1 year, to collect pollen rain from three vegetation plots within the forest-savannah transition in Ghana. High percentages of Poaceae and Melastomataceae/Combretaceae were recorded in all three plots. Erythrophleum suaveolens characterised the forest plot, Manilkara obovata the transition plot and Terminalia the savannah plot. The results indicate that Poaceae pollen influx rates provide the best representation of the forest-savannah gradient, and that a Poaceae abundance of >40% should be considered as indicative of savannah-type vegetation in the fossil record

Genetic Determination and Linkage Mapping of Plasmodium falciparum Malaria Related Traits in Senegal

Plasmodium falciparum malaria episodes may vary considerably in their severity and clinical manifestations. There is good evidence that host genetic factors contribute to this variability. To date, most genetic studies aiming at the identification of these genes have used a case/control study design for severe malaria, exploring specific candidate genes. Here, we performed a family-based genetic study of falciparum malaria related phenotypes in two independent longitudinal survey cohorts, as a first step towards the identification of genes and mechanisms involved in the outcome of infection. We studied two Senegalese villages, Dielmo and Ndiop that differ in ethnicity, malaria transmission and endemicity. We performed genome-scan linkage analysis of several malaria-related phenotypes both during clinical attacks and asymptomatic infection. We show evidence for a strong genetic contribution to both the number of clinical falciparum malaria attacks and the asymptomatic parasite density. The asymptomatic parasite density showed linkage to chromosome 5q31 (LOD = 2.26, empirical p = 0.0014, Dielmo), confirming previous findings in other studies. Suggestive linkage values were also obtained at three additional chromosome regions: the number of clinical malaria attacks on chromosome 5p15 (LOD = 2.57, empirical p = 0.001, Dielmo) and 13q13 (LOD = 2.37, empirical p = 0.0014 Dielmo), and the maximum parasite density during asymptomatic infection on chromosome 12q21 (LOD = 3.1, empirical p<10−4, Ndiop). While regions of linkage show little overlap with genes known to be involved in severe malaria, the four regions appear to overlap with regions linked to asthma or atopy related traits, suggesting that common immune related pathways may be involved

Vision-Based, Terrain-Aided Navigation with Decentralized Fusion and Finite Set Statistics

Terrain-related information, in the form of features extracted from images, presents a rich data source that can be harvested to facilitate drastic improvements in navigation when conventional data sources, such as GPS, are not available. Conventional implementation of such data types requires image correlation techniques that interrupt streamlined transmission of statistics through a navigation filter, oftentimes leading to time-wise correlations that are erroneously ignored. This paper proposes leveraging finite set statistics to recast the terrain feature data into a simultaneous localization and mapping problem. Decentralized data fusion is employed to augment a standard extended Kalman filter-based navigation with the terrain data. Theoretical results are supported with a simulated descent to landing navigation scenario that demonstrates the improvements offered by augmenting standard navigation with terrain aiding

Exploring students eating habits through individual profiling and clustering analysis

Individual well-being strongly depends on food habits, therefore it is important to educate the general population, and especially young people, to the importance of a healthy and balanced diet. To this end, understanding the real eating habits of people becomes fundamental for a better and more effective intervention to improve the students’ diet. In this paper we present two exploratory analyses based on centroid-based clustering that have the goal of understanding the food habits of university students. The first clustering analysis simply exploits the information about the students’ food consumption of specific food categories, while the second exploratory analysis includes the temporal dimension in order to capture the information about when the students consume specific foods. The second approach enables the study of the impact of the time of consumption on the choice of the food