Understanding the implementation challenges of urban resilience policies : investigating the influence of urban geological risk in Thessaloniki, Greece

Urban Resilience has recently emerged as a systematic approach to urban sustainability. The malleable definition of resilience has rendered its operationalisation an intriguing task for contemporary cities trying to address their organisational problems and confront uncertainty in a holistic manner. In this article we investigate the implementation challenges emerging for Resilient Strategies by the inattention paid to urban geological risk. We conceptualise urban geological risk as the combination of urban geohazards, geological vulnerability and exposure of the built environment and focus on the case study of Thessaloniki, Greece, a city that joined the 100 Resilient Cities initiative in 2014 and published its “Resilience Strategy 2030” (RS) in 2017. After a review of the RS, historical records of natural hazard events and with evidence gathered through interviews with city officials, we emphasize on earthquakes and surface flooding as the most relevant geohazards for Thessaloniki to tackle in its journey towards urban resilience. First, we examine geological vulnerability to earthquakes in conjunction with exposure of the built environment, as an outcome of ageing building stock, high building densities and the urban configuration, in Acheiropoietos neighbourhood, within the historic centre of the city. Then, we explore geological risk to surface flooding in Perea, in Thermaikos Municipality, with a particular focus on flash floods, by demonstrating how limited consideration of local geomorphology as well as semi-regulated urban expansion and its limited connection with emergency planning increase exposure of the built environment to surface flooding. Finally, we come up with the major implementation challenges Thessaloniki’s RS faces with regard to urban geohazards

The ρ(1S,2S)\rho(1S,2S), ψ(1S,2S)\psi(1S,2S), Υ(1S,2S)\Upsilon(1S,2S) and ψt(1S,2S)\psi_t(1S,2S) mesons in a double pole QCD Sum Rule

We use the method of double pole QCD sum rule which is basically a fit with two exponentials of the correlation function, where we can extract the masses and decay constants of mesons as a function of the Borel mass. We apply this method to study the mesons: $\rho(1S,2S)$, $\psi(1S,2S)$, $\Upsilon(1S,2S)$ and $\psi_t(1S,2S)$. We also present predictions for the toponiuns masses $\psi_t(1S,2S)$ of m(1S)=357 GeV and m(2S)=374 GeV.Comment: 14 pages, 11 figures in Braz J Phys (2016

The use of phylogeny to interpret cross-cultural patterns in plant use and guide medicinal plant discovery: an example from Pterocarpus (Leguminosae)

The study of traditional knowledge of medicinal plants has led to discoveries that have helped combat diseases and improve healthcare. However, the development of quantitative measures that can assist our quest for new medicinal plants has not greatly advanced in recent years. Phylogenetic tools have entered many scientific fields in the last two decades to provide explanatory power, but have been overlooked in ethnomedicinal studies. Several studies show that medicinal properties are not randomly distributed in plant phylogenies, suggesting that phylogeny shapes ethnobotanical use. Nevertheless, empirical studies that explicitly combine ethnobotanical and phylogenetic information are scarce.In this study, we borrowed tools from community ecology phylogenetics to quantify significance of phylogenetic signal in medicinal properties in plants and identify nodes on phylogenies with high bioscreening potential. To do this, we produced an ethnomedicinal review from extensive literature research and a multi-locus phylogenetic hypothesis for the pantropical genus Pterocarpus (Leguminosae: Papilionoideae). We demonstrate that species used to treat a certain conditions, such as malaria, are significantly phylogenetically clumped and we highlight nodes in the phylogeny that are significantly overabundant in species used to treat certain conditions. These cross-cultural patterns in ethnomedicinal usage in Pterocarpus are interpreted in the light of phylogenetic relationships.This study provides techniques that enable the application of phylogenies in bioscreening, but also sheds light on the processes that shape cross-cultural ethnomedicinal patterns. This community phylogenetic approach demonstrates that similar ethnobotanical uses can arise in parallel in different areas where related plants are available. With a vast amount of ethnomedicinal and phylogenetic information available, we predict that this field, after further refinement of the techniques, will expand into similar research areas, such as pest management or the search for bioactive plant-based compounds

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits

The detection and location estimation of disasters using Twitter and the identification of Non-Governmental Organisations using crowdsourcing

status: publishe