Integrating Agriculture in Greenways: a Methodology for Planning Connected Urban and Peri-Urban Farmlands in a Mediterranean City

Cities are often threatened by a loss of environmental quality due the rapid increase of urbanized areas that fragment natural landscapes. This is particularly true at the cities’ fringe where uncontrolled urbanization is often characterized by discontinuous patterns and consequent fragmentation of farmlands. These phenomena are particularly relevant in Mediterranean cities, where the high degree of land-use transitions, a consequence of urban growth with poor environmental regulations produce urban landscapes characterized by a lack of green areas and high levels of ecological fragmentation (EEA, 2006). Greenways are one of the most powerful and widespread tools used at urban, metropolitan and regional scales. Their aim is to counteract ecological fragmentation and to integrate urban development, nature conservation and public health promotion (Ahern, 1995; Fabos & Ryan, 2006). They facilitate linkages between rural and urban spaces along the rural-urban interface through linear systems (Walmsley, 2006). As networks of linear elements they are planned, designed and managed for multiple purposes, including the provision of ecosystem services such as purification of air and water, mitigation of floods, climate regulation, generation and renewal of soil fertility, accessibility to open spaces and intellectual stimulation. Urban contexts present particular challenges for greenways development due to the complex arrangement of urban landscape features. The large number and diversity of land-cover types often produce high degrees of fragmentation of open spaces and heterogeneity of their roles and functions. For this reason a number of different types of patches of Non Urbanized Areas (NUAs) are present in urban contexts: this calls for a characterization of these spaces in order to highlight their physical features and their ecological and social functions. Particularly, they could represent a big opportunity for planning policies oriented to support new forms of urban agriculture (La Greca et al., 2011a). When formulating planning approaches to greenways in urban contexts, new forms of agriculture have been the focus of very few studies and applications but they can significantly contribute to cities’ sustainability (Zasada, 2011). Proposing an agricultural greenway that integrates different NUAs into a network of farmlands and other green spaces (parks, playgrounds and so on) could significantly improve the overall accessibility of these areas, redefining the rural-urban interface and enhancing the provision of urban ecosystem services

Impact of information technology on future floras

Some important facilities offered by the information technology to innovate the development of traditional floras are illustrated and discussed. These include: random access interactive tools for the identification of species, low cost, easy updating, virtually unlimited space for high resolution images and texts, on-line utilities, strong synergy between authors and users. It is argued that the combination of printed books with integrated digital utilities and data-sources is the most desirable structure for future floras

“Flora Italiana Digitale”: an interactive identification tool for the Flora of Italy

The digital facilities of the second edition of Pignatti’s “Flora d’Italia” are presented. A software, called FID (i.e. “Flora Italiana Digitale”) will link together a random-access interactive identification tool, a thesaurus, synoptic tables and one template for each single species, including a distribution map (referred to the Italian regions), “ecograms”, a text-box and up to 24 highresolution colour images. The FID follows a “shareware phylosophy”. All contents and images can be integrated and/or replaced over time, in order to continuously improve the diagnostic and qualitative performance of the provided utilities. Ideally, the community of users should interact on the web, so that every user could easily become content provider

Evaluating The Potential Energy Savings Of An Urban Green Infrastructure Through Environmental Simulation

Green infrastructure is a very important aspect to be considered in designing and preparing cities to adapt and mitigate climate change impacts on the built environment. Green based solutions have a strong impact on many aspects, such as controlling storm-water, reducing urban heat island effect, stabilizing soils, facing earthquakes, etcetera. In this paper an environmental analysis is performed by simulation with TRNSYS Studio tool. The cooling potential that can be obtained by trees in residential compounds is assessed, considering shadowing effect, changes in air movement, sky view factor reduction and other simulation-parameter changes. Results show that a reduction of 30 to 50% in cooling demand can be obtained by using a raw of trees on South, East and especially West façades. Two types of trees are tested, showing different cooling performances depending on the height and form of the trees

Neutron Star Radius-to-mass Ratio from Partial Accretion Disc Occultation as Measured through Fe Kα\alpha Line Profiles

We present a new method to measure the radius-to-mass ratio (R/M) of weakly magnetic, disc-accreting neutron stars by exploiting the occultation of parts of the inner disc by the star itself. This occultation imprints characteristic features on the X-ray line profile that are unique and are expected to be present in low mass X-ray binary systems seen under inclinations higher than ~65 degrees. We analyse a NuSTAR observation of a good candidate system, 4U 1636-53, and find that X-ray spectra from current instrumentation are unlikely to single out the occultation features owing to insufficient signal-to-noise. Based on an extensive set of simulations we show that large-area X-ray detectors of the future generation could measure R/M to ~2{\div}3% precision over a range of inclinations. Such is the precision in radius determination required to derive tight constraints on the equation of state of ultradense matter and it represents the goal that other methods too aim to achieve in the future.Comment: 17 pages, 8 figures; this is a pre-print edition of an article that has been accepted for publication in the Astrophysical Journa

Green Infrastructure to reduce cooling loads and heat stress in Mediterranean Climates

Climate change impact on cities and urban warming due to anthropogenic effects are urgent problems to be solved. Among the most beneficious strategies to reduce those impacts we can account the development of green infrastructures in cities, a kind of intervention that assure both mitigation of global warming by reducing greenhouse gases emissions, and adaptation to warmer urban environments. This work presents a building simulation and machine learning methodology to estimate the energy and comfort-related benefits that can be obtained by using a green infrastructure to shadow buildings' façades and roofs. We used previously developed simulation models to test the energy savings provided by different types of trees planted to produce shadows on buildings. Then, we tested different algorithms to predict using a machine learning approach the saving that can be obtained in different buildings-trees contexts for the cities of Catania, Rome, Santiago de Chile and Viña del Mar. Results show that the saving obtained is in the range 5-60%, mainly depending on the number of façade shadowed and on the specie of trees; and the prediction accuracy of machine learning process is over 90% for a binary classification (energy saving > 15% or <15%

Amaurodon mustialaënsis (Basidiomycota, Thelephoraceae) new to Italy

Amaurodon mustialaënsis is reported for the first time from Italy. Based on Italian specimens, a brief description, microscopical and macroscopical photographs, ecological and distributional data of this rare taxon are presented.

Frailty trajectories in ICU survivors: A comparison between the clinical frailty scale and the Tilburg frailty Indicator and association with 1 year mortality

Purpose: To test the agreement of the Clinical Frailty Scale (CFS) and the Tilburg Frailty Indicator (TFI), their association with 3, 6 months and 1-year mortality and the trajectory of frailty in a mixed population of ICU survivors. Material and methods: This is a prospective, multicenter, longitudinal study on ICU survivors ≥18 years old with an ICU stay >72 h. For each patient, sociodemographic and clinical data were collected. Frailty was assessed during ICU stay and at 3, 6, 12 months after ICU discharge, through both CFS and TFI. Results: 124 patients with a mean age of 66 years old were enrolled. The baseline prevalence of frailty was 15.3% by CFS and 44.4% by TFI. Baseline CFS and TFI correlated but showed low agreement (Cohen's K = 0.23, p < 0.001). Baseline CFS score, but not TFI, was significantly associated to 1 year mortality. Moreover, CFS score during the follow-up was independently associated 1-year mortality (OR = 1.43; 95% CI: 1.18-1.73). Conclusions: CFS and TFI identify different populations of frail ICU survivors. Frail patients before ICU according to CFS have a significantly higher mortality after ICU discharge. The CFS during follow-up is an independent negative prognostic factor of long-term mortality in the ICU population

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets