Green Economy as a New Pathway to Development (and Cohesion)? Place Evidence Analysis in the North-Eastern Italy: First Findings of an Ongoing Research Project

This paper shows the first findings of an ongoing research project on \u201cTerritorial Impact Assessment of the Italian regions territorial cohesion. Place based evidence model for the policy evaluation towards the development of green economy in inner and metropolitan peripheries\u201d, coordinated by Maria Prezioso (Tor Vergata University, Rome) as Principal Investigator. We hereby present the results of the first two years of investigation carried out by the Research Unit number 8, located in Trieste

Smart cities and communities, borghi e aree interne, innovazione a rete

Smart cities and communities, smart regions, smart villages sono i concetti, legati a tipologie territoriali diverse, che dominano la narrazione sulle città, e non solo, negli ultimi anni, a seguito dello sviluppo e della pervasività senza eguali delle ICT (le tecnologie dell’informazione e della comunicazione). Si nota la contrapposizione, tipicamente urbana, fra centro e periferie, con l’aumento dei divari fra queste realtà, evidenziabile, nella fattispecie, nell’osservazione del fatto che nelle periferie ci si ammala di più, così come sono più deboli e meno presenti le connessioni Internet ad alta velocità, e risulta più importante il fenomeno dell’abbandono scolastico

A smart and sustainable future for viticulture is rooted in soil: How to face cu toxicity

In recent decades, agriculture has faced the fundamental challenge of needing to increase food production and quality in order to meet the requirements of a growing global population. Similarly, viticulture has also been undergoing change. Several countries are reducing their vineyard areas, and several others are increasing them. In addition, viticulture is moving towards higher altitudes and latitudes due to climate change. Furthermore, global warming is also exacerbating the incidence of fungal diseases in vineyards, forcing farmers to apply agrochemicals to preserve production yields and quality. The repeated application of copper (Cu)-based fungicides in con-ventional and organic farming has caused a stepwise accumulation of Cu in vineyard soils, posing environmental and toxicological threats. High Cu concentrations in soils can have multiple impacts on agricultural systems. In fact, it can (i) alter the chemical-physical properties of soils, thus com-promising their fertility; (ii) induce toxicity phenomena in plants, producing detrimental effects on growth and productivity; and (iii) affect the microbial biodiversity of soils, thereby influencing some microbial-driven soil processes. However, several indirect (e.g., management of rhizosphere processes through intercropping and/or fertilization strategies) and direct (e.g., exploitation of vine resistant genotypes) strategies have been proposed to restrain Cu accumulation in soils. Furthermore, the application of precision and smart viticulture paradigms and their related technologies could allow a timely, localized and balanced distribution of agrochemicals to achieve the required goals. The present review highlights the necessity of applying multidisciplinary approaches to meet the requisites of sustainability demanded of modern viticulture

Investigating the microbial community of Cacopsylla spp. as potential factor in vector competence of phytoplasma

Phytoplasmas are obligatory intracellular bacteria that colonize the phloem of many plant species and cause hundreds of plant diseases worldwide. In nature, phytoplasmas are primarily transmitted by hemipteran vectors. While all phloem-feeding insects could in principle transmit phytoplasmas, only a limited number of species have been confirmed as vectors. Knowledge about factors that might determine the vector capacity is currently scarce. Here, we characterized the microbiomes of vector and non-vector species of apple proliferation (AP) phytoplasma ‘Candidatus Phytoplasma mali’ to investigate their potential role in the vector capacity of the host. We performed high-throughput 16S rRNA metabarcoding of the two principal AP-vectors Cacopsylla picta and Cacopsylla melanoneura and eight Cacopsylla species, which are not AP-vectors but co-occur in apple orchards. The microbiomes of all species are dominated by Carsonella, the primary endosymbiont of psyllids and a second uncharacterized Enterobacteriaceae endosymbiont. Each Cacopsylla species harboured a speciesspecific phylotype of both symbionts. Moreover, we investigated differences between the microbiomes of AP-vector versus non-vector species and identified the predominant endosymbionts but also Wolbachia and several minor taxa as potential indicator species. Our study highlights the importance of considering the microbiome in future investigations of potential factors influencing host vector competence. We investigated the potential role of symbiotic bacteria in the acquisition and transmission of phytoplasma. By comparing the two main psyillid vector species of Apple proliferation (AP) phytoplasma and eight co-occurring species, which are not able to vector AP-phytoplasma, we found differences in the microbial communities of AP-vector and non-vector species, which appear to be driven by the predominant symbionts in both vector species and Wolbachia and several minor taxa in the non-vector species. In contrast, infection with APphytoplasma did not affect microbiome composition in both vector species. Our study provides new insights into the endosymbiont diversity of Cacopsylla spp. and highlights the importance of considering the microbiome when investigating potential factors influencing host vector competenc

Resample-smoothing of Voronoi intensity estimators

Voronoi estimators are non-parametric and adaptive estimators of the intensity of a point process. The intensity estimate at a given location is equal to the reciprocal of the size of the Voronoi/Dirichlet cell containing that location. Their major drawback is that they tend to paradoxically under-smooth the data in regions where the point density of the observed point pattern is high, and over-smooth where the point density is low. To remedy this behaviour, we propose to apply an additional smoothing operation to the Voronoi estimator, based on resampling the point pattern by independent random thinning. Through a simulation study we show that our resample-smoothing technique improves the estimation substantially. In addition, we study statistical properties such as unbiasedness and variance, and propose a rule-of-thumb and a data-driven cross-validation approach to choose the amount of smoothing to apply. Finally we apply our proposed intensity estimation scheme to two datasets: locations of pine saplings (planar point pattern) and motor vehicle traffic accidents (linear network point pattern)

The visualization and analysis of urban facility pois using network kernel density estimation constrained by multi-factors

The urban facility, one of the most important service providers is usually represented by sets of points in GIS applications using POI (Point of Interest) model associated with certain human social activities. The knowledge about distribution intensity and pattern of facility POIs is of great significance in spatial analysis, including urban planning, business location choosing and social recommendations. Kernel Density Estimation (KDE), an efficient spatial statistics tool for facilitating the processes above, plays an important role in spatial density evaluation, because KDE method considers the decay impact of services and allows the enrichment of the information from a very simple input scatter plot to a smooth output density surface. However, the traditional KDE is mainly based on the Euclidean distance, ignoring the fact that in urban street network the service function of POI is carried out over a network-constrained structure, rather than in a Euclidean continuous space. Aiming at this question, this study proposes a computational method of KDE on a network and adopts a new visualization method by using 3-D "wall" surface. Some real conditional factors are also taken into account in this study, such as traffic capacity, road direction and facility difference. In practical works the proposed method is implemented in real POI data in Shenzhen city, China to depict the distribution characteristic of services under impacts of multi-factors

Smart cities in a smart world

Very often the concept of smart city is strongly related to the flourishing of mobile applications, stressing the technological aspects and a top-down approach of high-tech centralized control systems capable of resolving all the urban issues, completely forgetting the essence of a city with its connected problems. The real challenge in future years will be a huge increase in the urban population and the changes this will produce in energy and resource consumption. It is fundamental to manage this phenomenon with clever approaches in order to guarantee a better management of resources and their sustainable access to present and future generations. This chapter develops some considerations on these aspects, trying to insert the technological issues within a framework closer to planning and with attention to the social impact

Statistical disclosure control when publishing on thematic maps

The spatial distribution of a variable, such as the energy consumption per company, is usually plotted by colouring regions of the study area according to an underlying table which is already protected from disclosing sensitive information. The result is often heavily influenced by the shape and size of the regions. In this paper, we are interested in producing a continuous plot of the variable directly from microdata and we protect it by adding random noise. We consider a simple attacker scenario and develop an appropriate sensitivity rule that can be used to determine the amount of noise needed to protect the plot from disclosing private information