Low Climate Stabilisation under Diverse Growth and Convergence Scenarios

4 p.

The Role of the Demand for Environmental Quality in Driving Transitions to Low-Polluting Energy Sources

4 p.

Low Climate Stabilisation under Diverse Growth and Convergence Scenarios

9 p.

The Demand for Environmental Quality in Driving Transitions to Low Polluting Energy Sources

38 p.

New climate scenario framework implementation in the GCAM integrated assessment model

48 p.

Is inbreeding avoidance driving female mate choice in Verreaux's sifaka lemurs?

Females of different species might exert female mate choice for different reasons, one of them the aim of avoiding inbreeding. In this study I examine the implication of inbreeding avoidance as a mechanism driving female mate choice in Verreaux’s sifaka lemurs (Propithecus verreauxi). In fact, in this species females are dominant and appear to be able to choose certain males to mate with, while observations indicate that rank, body size, canine size and proportions of fights won are not factors influencing female mate choice. So I hypothesized that females mate choice is driven by inbreeding avoidance in Verreaux’s sifaka lemurs. Tissue and fecal samples were collected in the Kirindy Mitea National Park in western Madagascar as a source of DNA. Parentage was assigned for a sample of the population and relatedness coefficients between dams and sires were estimated and compared to those of between random female and male pairs, dams and other candidate sires within the population and within the groups were the offspring were conceived. I found that there were no significant differences in none of the comparisons which means that Verreaux’s sifaka females do not mate more with males that are more distantly related to them. I concluded that inbreeding avoidance does not appear to be the main force driving female mate choice in Verreaux’s sifaka lemurs and I addressed explanations for these findings. With this study I contribute to our knowledge of female mate choice in lemurs.

Analysis of multivariate stochastic signals sampled by on-line particle analyzers: Application to the quantitative assessment of occupational exposure to NOAA in multisource industrial scenarios (MSIS)

In multisource industrial scenarios (MSIS) coexist NOAA generating activities with other productive sources of airborne particles, such as parallel processes of manufacturing or electrical and diesel machinery. A distinctive characteristic of MSIS is the spatially complex distribution of aerosol sources, as well as their potential differences in dynamics, due to the feasibility of multi-task configuration at a given time. Thus, the background signal is expected to challenge the aerosol analyzers at a probably wide range of concentrations and size distributions, depending of the multisource configuration at a given time. Monitoring and prediction by using statistical analysis of time series captured by on-line particle analyzers in industrial scenarios, have been proven to be feasible in predicting PNC evolution provided a given quality of net signals (difference between signal at source and background). However the analysis and modelling of non-consistent time series, influenced by low levels of SNR (Signal-Noise Ratio) could build a misleading basis for decision making. In this context, this work explores the use of stochastic models based on ARIMA methodology to monitor and predict exposure values (PNC). The study was carried out in a MSIS where an case study focused on the manufacture of perforated tablets of nano-TiO2 by cold pressing was performed

System architecture and deployment scenarios for SESAME: Small cEllS coordinAtion for Multi-tenancy and Edge services

The surge of the Internet traffic with exabytes of data flowing over operators mobile networks has created the need to rethink the paradigms behind the design of the mobile network architecture. The inadequacy of the 4G UMTS Long term Evolution (LTE) and even of its advanced version LTE-A is evident, considering that the traffic will be extremely heterogeneous in the near future and ranging from 4K resolution TV to machine-type communications. To keep up with these changes, academia, industries and EU institutions have now engaged in the quest for new 5G technology. In this paper we present the innovative system design, concepts and visions developed by the 5G PPP H2020 project SESAME (Small cEllS coordinAtion for Multi-tenancy and Edge services). The innovation of SESAME is manifold: i) combine the key 5G small cells with cloud technology, ii) promote and develop the concept of Small Cellsas- a-Service (SCaaS), iii) bring computing and storage power at the mobile network edge through the development of nonx86 ARM technology enabled micro-servers, and iv) address a large number of scenarios and use cases applying mobile edge computing. Topics: