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Xylella fastidiosa subsp. pauca is a plant pathogen that causes the Olive Quick Decline Syndrome, the spread of which is linked to insect vectors. Since these vectors can use and move across multiple managed and natural habitats, understanding their occurrence in different habitat types at the landscape scale is particularly challenging. Here, we applied a bipartite network approach to explore the spatio-temporal distribution of confirmed and potential vectors of X. fastidiosa in olive groves. We sampled sharpshooters and spittlebugs in 10 heterogeneous landscapes in southern Italy during spring, summer, and autumn. In each landscape, we sampled insects in the main habitat types, i.e., arable land, grassland, olive grove, vineyard, and woodland. We then built and analyzed the resulting bipartite species–habitat networks. The abundance of vectors in different habitat types throughout the seasons varied from species to species, with Philaenus spumarius, the main vector of X. fastidiosa, being mostly collected in olive groves. However, the analysis of habitat specialization showed that P. spumarius acted as a super-generalist species, occupying all the habitats. Insect vectors in olive grove patches were strongly influenced by other olive grove patches in the landscape and also by grasslands, particularly in spring, therefore highlighting the focal role of non-crop habitats on potential pathogen spread. Landscapes dominated by olive orchards and grasslands seemed to provide the most suitable conditions to support large vector populations. Network analyses helped untangle the complex interactions between vectors of X. fastidiosa and the landscapes and habitats they use. [ABSTRACT FROM AUTHOR]

Despite longstanding discussions and consequent improvements of gender representation in academia, the number of women working in academic research, their performance and their recognition still indicate the persistence of gender inequalities. Of the various mechanisms that may drive such inequality the one that relates the structure of research collaborative networks to the rewards that these networks facilitate is intriguing. If social networks play a role in academic performances and women are under-recognized compared to men, what are the mechanisms that relate networks to gender inequalities in academia? Do men and women obtain equal returns from similar network structure, or do women have to build different networks to obtain similar returns? This article contributes to the theoretical debate that aims to disentangle the mechanisms by which social networks may affect gendered success. We do so by looking at networks of collaborations to research projects in 10 years of public funding in Italy. We use a permutation t-test analysis to see if men and women, who are equally successful in getting funded for a high number of projects, build equal or unequal collaborative networks, and if these differences vary across disciplines with more or less tenured women. Our methodological contribution proposes an innovative way of measuring brokerage and constraint in one mode projections of bipartite networks, highly clustered and valued, and measures gender homophily by taking into account the higher or lower number of women available for collaborations in different disciplinary sectors. We find that men and women build similar collaborative networks; we also find that the more women are tenured in a discipline, the more they occupy higher ranks and lead research projects. When women's presence and high-rank roles increase, we see that men's collaborative networks are significantly more heterophilous, although women do not seem to significantly increase their collaborations with other women. We then regress the individual measures of network structure and composition against the average amount of money scholars receive per project and we interact each measure with gender, to observe if women obtain similar returns to men by building equal collaborative networks. Our results show that despite the similarities in network configurations in nearly all disciplines women still receive less funding than men. This suggests that an increased representation of women in academic fields is not enough to reduce inequalities. Our results are not directly generalizable to other international contexts, but the mechanisms that favor academic returns and exacerbate inequalities, and our methodological approach, are portable to other scientific and organizational contexts where collaborations are key to produce success. • We look at networks of collaborations to research projects in 10 years of academic funding in Italy. • We propose new brokerage and constraint measures for projections of bipartite networks. • Men and women build similar networks, and when women's numbers increase men work more with women. • Despite the similarities in network configurations women still receive less funding than men. • Gender inequalities seem to be related to the lack of women in leadership positions. [ABSTRACT FROM AUTHOR]

The most important student mobility (SM) flow in Italy is from the Southern to the Central-Northern regions, a phenomenon that has been magnified by an increasing number of outgoing students from Sicily over the last decade. In this paper, we rely upon micro-data of university enrollment and students' personal records for three cohorts of freshmen, in order to investigate preferential patterns of SM from Sicily toward universities in other regions. Our main goal is to reveal the existence of chain migrations, where students from a particular geographical area move towards a particular destination to follow other students that have previously moved. The paper provides aspects that are innovative under the view of the data, of the application, and of the statistical method. The data from each cohort is represented as a tripartite network with three sets of nodes, namely, clusters of Sicilian municipalities, students, and universities. The tripartite network is projected in a bipartite weighted network of clusters and universities, which is, then, filtered, in order to obtain a statistically validated bipartite network (SBVN). The SBVNs of the three cohorts may suggest the existence and evolution of chain migration patterns over time, which are also gender specific. [ABSTRACT FROM AUTHOR]

Abstract At the national scale, almost all of the European countries have already achieved energy transition targets, while at the regional and local scales, there is still some potential to further push sustainable energy transitions. Regions and localities have the support of political, social, and economic actors who make decisions for meeting existing social, environmental and economic needs recognizing local specificities. These actors compose the sustainable energy governance that is fundamental to effectively plan and manage energy resources. In collaborative relationships, these actors share, save, and protect several kinds of resources, thereby making energy transitions deeper and more effective. This research aimed to analyse a part of the sustainable energy governance composed of formal relationships between municipalities and public utilities and to investigate the opportunities to further spread sustainable energy development within a region. In the case study from South Tyrol, Italy, the network structures and dynamics of this part of the actual energy governance were investigated through a social network analysis and Bayesian exponential random graph models. The findings confirmed that almost all of the collaborations are based on spatial closeness relations and that the current network structures do not permit a further spread of the sustainable energy governance. The methodological approach can be replicated in other case studies and the findings are relevant to support energy planning choices at regional and local scales. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of high-speed rail (HSR) on household income inequalities in Italy at the province level. Gini index, both including and excluding rent expenses, is used as dependent variable to evaluate the effects of the policy in the timeframe 2003–2019. Two-way fixed-effects model is employed to measure the relationship, while augmented synthetic control with staggered treatment adoption, and staggered difference-in-differences explore the sensitivity of results. Main findings suggest a general reduction of inequalities among the provinces receiving HSR treatment, but the effect is not long-lasting many years over the policy outset. Heterogeneities arise depending on whether the station is basic-type or multimodal, and whether the treated province is core or intermediate. Small-sized provinces particularly benefited from the HSR introduction, showing a clear potential to pursue economic convergence objectives. Mechanisms analysis shows that HSR induced the reduction of household income inequalities by positively influencing per capita GDP and employment levels. [ABSTRACT FROM AUTHOR]

Abstract: Much of the work in the sociology of science observes scientific communities from a micro perspective, focusing on interactions in laboratories in order to uncover the impact of social and cultural norms in the everyday production of scientific results. Other studies approach the topic from a macro perspective, analysing scientific organizations and the reciprocal influence they have with wider society, or uncovering the invisible colleges that become apparent through the analysis of co-authorship and citations’ patterns. Less attention has been paid to the meso level of interaction within and between scientists and the institutions they work in. This paper extends the structural approach of and analyses the local system of public funding to physics in Italy using bipartite networks. Data cover 10 years of funding of Projects of National Interest (Prin) from the Italian Ministry of University and Research. The micro level (collaborations between scientists), macro level (collaborations between institutions) and meso level (the combination of network measures at a micro and macro level) of interactions are independently analysed, and results are used to model the total amount of money physicists have received over the 10 years against the variables that meaningfully describe the network structure of collaborations. Results show that in order to be successfully funded what counts more than being a big fish (a scientist with a lot of connections) working in a big pond (a large University), is being in a brokerage position interacting over the years with different research groups. [Copyright &y& Elsevier]

Olea europaea Geminivirus (OEGV) was recently identified in olive in Italy through HTS. In this work, we used HTS to show the presence of an OEGV isolate in Portuguese olive trees and suggest the evolution direction of OEGV. The bipartite genome (DNA-A and DNA-B) of the OEGV-PT is similar to Old World begomoviruses in length, but it lacks a pre-coat protein (AV2), which is a typical feature of New World begomoviruses (NW). DNA-A genome organization is closer to NW, containing four ORFs; three in complementary-sense AC1/Rep, AC2/TrAP, AC3/REn and one in virion-sense AV1/CP, but no AC4, typical of begomoviruses. DNA-B comprises two ORFs; MP in virion sense with higher similarity to the tyrosine phosphorylation site of NW, but in opposite sense to begomoviruses; BC1, with no known conserved domains in the complementary sense and no NSP typical of bipartite begomoviruses. Our results show that OEGV presents the longest common region among the begomoviruses, and the TATA box and four replication-associated iterons in a completely new arrangement. We propose two new putative conserved regions for the geminiviruses CP. Lastly, we highlight unique features that may represent a new evolutionary direction for geminiviruses and suggest that OEGV-PT evolution may have occurred from an ancient OW monopartite Begomovirus that lost V2 and C4, gaining functions on cell-to-cell movement by acquiring a DNA-B component. [ABSTRACT FROM AUTHOR]