Digital politics and voting geography. Potential connections between online storytelling and electoral results in the Campania regional elections

Digital political communication has undergone a revolution due to the emergence of new digital media platforms, significantly impacting electoral campaigns. However, there remains limited understanding of the implications of digital communication in local elections and its correlation with territorial vote concentration. The objective of this study is to investigate these relationships during the 2020 regional elections in Campania. Specifically, the focus is on four candidate profiles from the outgoing president’s political list. The employed methodology follows a quantita- tive approach, entailing a secondary analysis of an extensive dataset encompassing the candi- dates’ digital profiles and electoral outcomes within the Naples district. The digital content from their public Facebook pages is extracted using Api strategies, encompassing textual aspects, language style, political communication sentiment, and follower engagement. Through spatial analysis of the candidates’ obtained votes, potential relationships between the geographical distribution of votes and candidates’ digital activity are identified and summarized using the Digital activity index. The findings suggest promising avenues for future research concerning the evolution of political communication in the digital era and its interplay with electoral outcomes

An Add-on Model Predictive Control Strategy for the Energy Management of Hybrid Electric Tractors

The hybridization process has recently touched also the world of agricultural vehicles. Within this context, we develop an Energy Management Strategy (EMS) aiming at optimizing fuel consumption, while maintaining the battery state of charge. A typical feature of agricultural machines is that their internal combustion engine is speed controlled, tracking the reference requested by the driver. In view of avoiding any modification on this original control loop, an add-on EMS strategy is proposed. In particular, we employ a multi-objective Model Predictive Control (MPC), taking into account the fuel consumption minimization and the speed tracking requirement, including the engine speed controller in the predictive model. The proposed MPC is tested in an experimentally-validated simulation environment, representative of an orchard vineyard tractor.Comment: Submitted to IEEE Transactions on Vehicular Technolog

Multi-Variable Multi-Metric Optimization of Self-Assembled Photocatalytic CO2 Reduction Performance Using Machine Learning Algorithms

: The sunlight-driven reduction of CO2 into fuels and platform chemicals is a promising approach to enable a circular economy. However, established optimization approaches are poorly suited to multivariable multimetric photocatalytic systems because they aim to optimize one performance metric while sacrificing the others and thereby limit overall system performance. Herein, we address this multimetric challenge by defining a metric for holistic system performance that takes multiple figures of merit into account, and employ a machine learning algorithm to efficiently guide our experiments through the large parameter matrix to make holistic optimization accessible for human experimentalists. As a test platform, we employ a five-component system that self-assembles into photocatalytic micelles for CO2-to-CO reduction, which we experimentally optimized to simultaneously improve yield, quantum yield, turnover number, and frequency while maintaining high selectivity. Leveraging the data set with machine learning algorithms allows quantification of each parameter's effect on overall system performance. The buffer concentration is unexpectedly revealed as the dominating parameter for optimal photocatalytic activity, and is nearly four times more important than the catalyst concentration. The expanded use and standardization of this methodology to define and optimize holistic performance will accelerate progress in different areas of catalysis by providing unprecedented insights into performance bottlenecks, enhancing comparability, and taking results beyond comparison of subjective figures of merit

Analysis of land cover dynamics in Mozambique (2001–2016)

Land cover change (LCC) is a complex and dynamic process influenced by social, economic, and biophysical factors that can cause significant impacts on ecological processes and biodiversity conservation. The assessment of LCC is particularly relevant in a country like Mozambique where livelihood strongly depends on natural resources. In this study, LCC was assessed using a point-based sampling approach through Open Foris Collect Earth (CE), a free and open-source software for land assessment developed by the Food and Agriculture Organization of the United Nations. This study aimed to conduct an LCC assessment using CE for the entire Mozambique, and according to three different land classifications: administrative boundaries (provinces), ecoregions, and protected vs unprotected areas. A set of 23,938 randomly selected plots, with an area of 0.5 hectares, placed on a 4 × 4 km regular grid over the entire country, was assessed using CE. The analysis showed that Mozambique has gone through significant loss of forest (− 1.3 Mha) mainly to the conversion to cropland. Deforestation is not occurring evenly throughout the country with some provinces, such as Nampula and Zambezia, characterized by higher rates than others, such as Gaza and Niassa. This result can be explained considering a combination of ecological and socio-economic factors, as well as the conservative role played by the protected areas. Our study confirmed that LCC is a complex phenomenon, and the augmented visual interpretation methodology can effectively complement and integrate the LCC analyses conducted using the traditional wall-to-wall mapping to support national land assessment and forest inventories and provide training data for environmental modeling

“Third Mission” And Lifelong Learning: An Innovative Partnership Among Educational Institutions

The paper is the result of a substantive interest concerning the mechanisms and the processes that are leading the Italian institutions to redefine the “Third mission” in a Lifelong learning perspective. What is the role of the different actors? The practices of Lifelong learning for European citizens have a number of specific characteristics of the different institutional contexts. According to a postmodern perspective, a welfare-oriented policy agenda allows to rethink of society or learning cultures as integrative ideologies of social policy. The implementation of any theoretical-operational model requires consideration of different national guidelines, and organizational structures at the local level, where most decisions are made in order to combine efficiency and flexibility of intervention. The research show a case study of cooperation between a network of adult education centers and universities, which transformed Adult education into Lifelong learning. Through the implementation of both research and teaching activities, the “LLL Regional Research Centre” has been building a learning community for the Vocational Education and Training system in Campania. Teachers and researchers have been involved to increase both human and social capital and develop capacity building. Educational institutions redefine continuously functions and objectives in order to expand the citizens’ dimensions of meaning since they represent a collective intelligence heritage. Lifelong learning Universities and Adult School Centers represent a “clearing house” of the institutional systems dystonias, which are observable through the “agency” of the decision makers

A mixed research model to study local welfare systems. The case of Social Territorial Areas in Campania Region

In recent years, there was an increasing use of mixed methods designs in applied research, especially in welfare policies research (Brook and Holland 2018, Mason et al. 2020, Mertens 2018, Niedzwiecki and Nunnally 2017, Punziano 2012). These findings have often supported the utility of a systematic integration of qualitative and quantitative methods. It is not our intention to enter the debate about different mixed method approaches (Amaturo and Punziano 2016, Bazeley 2008, Teddlie and Tashakkori 2011) but it is certainly our purpose showing the interesting implications coming from policy research combining different methods, techniques and tools. The contribute presents the principal method steps of a study about the municipalities association in Campania (i.e. Social Territorial Areas, thereafter STA) in the context of implementation and management welfare policy. As starting point STA with strong normative structure would positively affect the performance of local services. To decline the starting hypothesis, we have identified two semantic areas: the demographic and socio-economic structure of the STA and the socio assistance offer. We have adopted a perspective integrating two different methods: one more formalized that responds to context data building; the other less formal to investigate informal relational networks and the meanings of the actors involved in decision-making processes. An emerging mixed analytical model declines the performance of the areas such as the outcome both of a pragmatist process (for example, performance indicators), and of a constructivist background (i.e. satisfaction, perceived success, etc.). Under these premises, this work tries to develop an instrument that allows to understanding not only the STA context but also, more generally, to construct an interpretative model of development trajectories and integration processes relating to emerging welfare system

L’esperienza del ReI e del RdC in Campania. Gli attori chiave nel processo di implementazione della politica tra reti di servizi e nuovi target di povertà.

In recent years, there was an increasing use of mixed methods designs in applied research, especially in welfare policies research (Brook and Holland 2018, Mason et al. 2020, Mertens 2018, Niedzwiecki and Nunnally 2017, Punziano 2012). These findings have often supported the utility of a systematic integration of qualitative and quantitative methods. It is not our intention to enter the debate about different mixed method approaches (Amaturo and Punziano 2016, Bazeley 2008, Teddlie and Tashakkori 2011) but it is certainly our purpose showing the interesting implications coming from policy research combining different methods, techniques and tools. The contribute presents the principal method steps of a study about the municipalities association in Campania (i.e. Social Territorial Areas, thereafter STA) in the context of implementation and management welfare policy. As starting point STA with strong normative structure would positively affect the performance of local services. To decline the starting hypothesis, we have identified two semantic areas: the demographic and socio-economic structure of the STA and the socio assistance offer. We have adopted a perspective integrating two different methods: one more formalized that responds to context data building; the other less formal to investigate informal relational networks and the meanings of the actors involved in decision-making processes. An emerging mixed analytical model declines the performance of the areas such as the outcome both of a pragmatist process (for example, perfor mance indicators), and of a constructivist background (i.e. satisfaction, perceived success, etc.). Under these premises, this work tries to develop an instrument that allows to understanding not only the STA context but also, more generally, to construct an interpretative model of development trajectories and integration processes relating to emerging welfare system