Novel investigation methods in Computational Social Dynamics and Complex Systems

In this thesis the evolution of the techno-social systems analysis methods will be reported, through the explanation of the various research experience directly faced. The first case presented is a research based on data mining of a dataset of words association named Human Brain Cloud: validation will be faced and, also through a non-trivial modeling, a better understanding of language properties will be presented. Then, a real complex system experiment will be introduced: the WideNoise experiment in the context of the EveryAware european project. The project and the experiment course will be illustrated and data analysis will be displayed. Then the Experimental Tribe platform for social computation will be introduced . It has been conceived to help researchers in the implementation of web experiments, and aims also to catalyze the cumulative growth of experimental methodologies and the standardization of tools cited above. In the last part, three other research experience which already took place on the Experimental Tribe platform will be discussed in detail, from the design of the experiment to the analysis of the results and, eventually, to the modeling of the systems involved. The experiments are: CityRace, about the measurement of human traffic-facing strategies; laPENSOcosì, aiming to unveil the political opinion structure; AirProbe, implemented again in the EveryAware project framework, which consisted in monitoring air quality opinion shift of a community informed about local air pollution. At the end, the evolution of the technosocial systems investigation methods shall emerge together with the opportunities and the threats offered by this new scientific path.

Water, sediment and soil physicochemical interactions in freshwater, brackish and saline systems

The physicochemical interactions between water, sediment and soil deeply influence the formation and development of the ecosystem. In this research, different freshwater, brackish and saline subaqueous environments of Northern Italy were chosen as study area to investigate the physicochemical processes which occur at the interface between water and sediments, as well as the effects of soil submergence on ecosystem development. In the freshwater system of the Reno river basin, the main purpose was to define the heavy metals hazard in water and sediments of natural and artificial water courses. Heavy metals partitioning and speciation allowed to assess the environmental risk linked to the critical action of dredging canal sediments, for the maintenance of the hydraulic safety of plain lands. In addition, some bioremediation techniques were experimented for protecting sediments from heavy metals contamination, and for giving an answer to the problem of sediments management. In the brackish system of S. Vitale park, the development of hydromorphic and subaqueous soils was investigated. The study of soil profiles highlighted the presence of a soil continuum among pedons subjected to different saturation degrees. This investigation allowed to the identification of both morphological and physicochemical indicators, which characterize the formation of subaqueous soils and describe the soil hydromorphism in transitional soil systems. In the saline system of Grado lagoon, an ecosystem approach was used to define the role of water oscillation in soil characterization and plants colonization. This study highlighted the close relationship and the mutual influence of soil submergence and aeration, tide oscillation and vegetation cover, on the soil development. In view of climate change, this study contribute to understand and suppose how soil and landscape could evolve. However, a complete evaluation of hydromorphic soil functionality will be achieved only involving physiological and biochemical expertise in these kind of studies.

Farming and processing factors for improving quality properties of poultry and rabbit meat

Recently, global meat market is facing several dramatic changes due to shifting in diet and life style, consumer demands, and economical considerations. Firstly, there was a tremendous increase in the poultry meat demand. Furthermore, current forecast and projection studies pointed out that the expansion of the poultry market will continue in future. In response to this demand, there was a great success to increase growth rate of meat-type chickens in the last few decades in order to optimize the production of poultry meat. Accordingly, the increase of growth rate induced the appearance of several muscle abnormalities such as pale-soft-exudative (PSE) syndrome and deep-pectoral-myopathy (DPM) and more recently white striping and wooden breast. Currently, there is growing interest in meat industry to understand how much the magnitude of the effect of these abnormalities on different quality traits for raw and processed meat. Therefore, the major part of the research activities during the PhD project was dedicated to evaluate the different implications of recent muscle abnormalities such as white striping and wooden breast on meat quality traits and their incidence under commercial conditions. Generally, our results showed that the incidence of these muscle abnormalities was very high under commercial conditions and had great adverse impact on meat quality traits. Secondly, there is growing market share of convenient, healthy, and functional processed meat products. Accordingly, the remaining part of research activities of the PhD project was dedicated to evaluate the possibility to formulate processed meat products with higher perceived healthy profile such as phosphate free-marinated chicken meat and low sodium-marinated rabbit meat products. Overall all findings showed that sodium bicarbonate can be considered as promising component to replace phosphates in meat products, while potassium chloride under certain conditions was successfully used to produce low marinated rabbit meat products.

Appropriate technologies and natural systems for wastewater treatment in low- and middle-income countries

Wastewater management is an environmental and social burden that primarily affects populations in Low- and Middle-Income Countries and the global environment. Wastewater collection, treatment, and reuse have become urgent, especially considering that 80% of the world's wastewater is untreated or improperly treated and discharged directly into water bodies. In recent years, the role of wastewater treatment plants in a sustainable water cycle has become even more critical, as they are the final destination of the collected wastewater. Indeed, the management of wastewater treatment plants should play an essential role in achieving SDG target 6.3 of the United Nations 2030 Agenda for SD. In this context, water reuse, especially wastewater reuse, plays a key role. This research focuses on investigating the valorization of wastewater resources applying Appropriate Technologies and Natural Systems for wastewater treatment in two different Low- and Middle-Income Countries, the Palestinian Territories and Sub-Saharan Africa. The research objectives are: (1) Determine the characteristics and quality of wastewater in the two case studies analysed. (2) Identify Appropriate Technology to be used in the Palestinian Territories to treat wastewater for reuse in agriculture. (3) Assess the environmental, economic, and social impacts of this project. (4) Assess the feasibility of using natural wetlands for household wastewater treatment in Sub-Saharan region. The first study, conducted in Rafah, Gaza Strip, showed that implementing existing primary treatment plant with a natural secondary treatment plant properly optimized the wastewater quality for reuse in agriculture and was suitable for the study area. The second case study was conducted in Cape Coast, Ghana. It shows that the natural wetland studied is currently overly polluted and threatened by various anthropogenic factors that cannot remove pollutants from the incoming domestic wastewater. Therefore, some recommendations were made in order to improve the efficiency of this natural wetland.

Technologies for urban and rural internet of things

Nowadays, application domains such as smart cities, agriculture or intelligent transportation, require communication technologies that combine long transmission ranges and energy efficiency to fulfill a set of capabilities and constraints to rely on. In addition, in recent years, the interest in Unmanned Aerial Vehicles (UAVs) providing wireless connectivity in such scenarios is substantially increased thanks to their flexible deployment. The first chapters of this thesis deal with LoRaWAN and Narrowband-IoT (NB-IoT), which recent trends identify as the most promising Low Power Wide Area Networks technologies. While LoRaWAN is an open protocol that has gained a lot of interest thanks to its simplicity and energy efficiency, NB-IoT has been introduced from 3GPP as a radio access technology for massive machine-type communications inheriting legacy LTE characteristics. This thesis offers an overview of the two, comparing them in terms of selected performance indicators. In particular, LoRaWAN technology is assessed both via simulations and experiments, considering different network architectures and solutions to improve its performance (e.g., a new Adaptive Data Rate algorithm). NB-IoT is then introduced to identify which technology is more suitable depending on the application considered. The second part of the thesis introduces the use of UAVs as flying Base Stations, denoted as Unmanned Aerial Base Stations, (UABSs), which are considered as one of the key pillars of 6G to offer service for a number of applications. To this end, the performance of an NB-IoT network are assessed considering a UABS following predefined trajectories. Then, machine learning algorithms based on reinforcement learning and meta-learning are considered to optimize the trajectory as well as the radio resource management techniques the UABS may rely on in order to provide service considering both static (IoT sensors) and dynamic (vehicles) users. Finally, some experimental projects based on the technologies mentioned so far are presented.

Interference mitigation techniques for cloud-RAN deployments in 5G and beyond systems

The deployment of ultra-dense networks is one of the most promising solutions to manage the phenomenon of co-channel interference that affects the latest wireless communication systems, especially in hotspots. To meet the requirements of the use-cases and the immense amount of traffic generated in these scenarios, 5G ultra-dense networks are being deployed using various technologies, such as distributed antenna system (DAS) and cloud-radio access network (C-RAN). Through these centralized densification schemes, virtualized baseband processing units coordinate the distributed access points and manage the available network resources. In particular, link adaptation techniques are shown to be fundamental to overall system operation and performance enhancement. The core of this dissertation is the result of an analysis and a comparison of dynamic and adaptive methods for modulation and coding scheme (MCS) selection applied to the latest mobile telecommunications standards. A novel algorithm based on the proportional-integral-derivative (PID) controller principles and block error rate (BLER) target has been proposed. Tests were conducted in a 4G and 5G system level laboratory and, by means of a channel emulator, the performance was evaluated for different channel models and target BLERs. Furthermore, due to the intrinsic sectorization of the end-users distribution in the investigated scenario, a preliminary analysis on the joint application of users grouping algorithms with multi-antenna and multi-user techniques has been performed. In conclusion, the importance and impact of other fundamental physical layer operations, such as channel estimation and power control, on the overall end-to-end system behavior and performance were highlighted.

Molecular and hybrid systems for solar-to-chemical energy conversion

My Ph.D. thesis was dedicated to the exploration of different paths to convert sunlight into the shape of chemical bonds, by the formation of solar fuels. During the past three years, I have focused my research on two of these, namely molecular hydrogen H2 and the reduced nicotinamide adenine dinucleotide enzyme cofactor NAD(P)H. The first could become the ideal energy carrier for a truly clean energy system; it currently represents the best chance to liberate humanity from its dependence on fossil fuels. To address this, I studied different systems which can achieve proton reduction upon light absorption. More specifically, part of my work was aimed to the development of a cost-effective and stable catalyst in combination with a well-known photochemical cycle. To this extent, I worked on transition metal oxides which, as demonstrated in this work, have been identified as promising H2 evolution catalysts, showing excellent activity, stability, and previously unreported versatility. Another branch of my work on hydrogen production dealt with the use of a new class of polymeric semiconductor materials to absorb light and convert it into H2. The second solar fuel mentioned above is a key component of the most powerful methods for chemical synthesis: enzyme catalysis. The high cost of the reduced forms prohibits large-scale utilization, so artificial photosynthetic approaches for regenerating it are being intensively studied. The first system I developed exploits the tremendous reducing properties of a scarcely known ruthenium complex which is able to reduce NAD+. Lastly, I sought to revert the classical role of the sacrificial electron donor to an active component of the system and, to boost the process, I build up an autonomous microfluidic system able to generate highly reproducible NAD(P)H amount, demonstrating the superior performance of microfluidic reactors over batch and representing another successful photochemical NAD(P)H regeneration system.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Sustainable pavements for rural scenarios: laboratory and in-situ characterization of recycled materials and innovative construction solutions

Growing need for infrastructure has led to expanding research on advances in road pavement materials. Finding solutions that are sustainable, environmentally friendly and cost-efficient is a priority. Focusing such efforts on low-traffic and rural roads can contribute with a significant progress in the vital circulatory system of transport for rural and agricultural areas. An important alternative material for pavement construction is recycled aggregates from solid wastes, including waste from civil engineering activities, mainly construction and demolition. A literature review on studies is made; it is performed a planned set of laboratory testing procedures aimed to fully characterize and assess the potential in-situ mechanical performance and chemical impact. Furthermore, monitoring the full-scale response of the selected materials in a real field construction site, including the production, laying and compaction operations. Moreover, a novel single-phase solution for the construction of semi-flexible paving layers to be used as alternative material to common concrete and bituminous layers is experimented and introduced, aiming the production and laying of a single-phase laid material instead of a traditional two phases grouted macadam. Finally, on a parallel research work for farming pavements, the possible use of common geotechnical anti-erosive products for the improvement of soil bearing capacity of paddock areas in cattle husbandries of bio-farms is evaluated. this thesis has clearly demonstrated the feasibility of using the sustainable recycled aggregates for low-traffic rural roads and the pavements of farming and agriculture areas. The pavement layers constructed with recycled aggregates provided satisfying performance under heavy traffic conditions in experimental pavements. This, together with the fact that these aggregates can be available in most areas and in large quantities, provides great impetus towards shifting from traditional materials to more sustainable alternatives. The chemical and environmental stability of these materials proves their soundness to be utilized in farming environments.

Modelling, simulations and monitoring for sustainable plant and animal production systems through precision technique

Protected crop production is a modern and innovative approach to cultivating plants in a controlled environment to optimize growth, yield, and quality. This method involves using structures such as greenhouses or tunnels to create a sheltered environment. These productive solutions are characterized by a careful regulation of variables like temperature, humidity, light, and ventilation, which collectively contribute to creating an optimal microclimate for plant growth. Heating, cooling, and ventilation systems are used to maintain optimal conditions for plant growth, regardless of external weather fluctuations. Protected crop production plays a crucial role in addressing challenges posed by climate variability, population growth, and food security. Similarly, animal husbandry involves providing adequate nutrition, housing, medical care and environmental conditions to ensure animal welfare. Then, sustainability is a critical consideration in all forms of agriculture, including protected crop and animal production. Sustainability in animal production refers to the practice of producing animal products in a way that minimizes negative impacts on the environment, promotes animal welfare, and ensures the long-term viability of the industry. Then, the research activities performed during the PhD can be inserted exactly in the field of Precision Agriculture and Livestock farming. Here the focus is on the computational fluid dynamic (CFD) approach and environmental assessment applied to improve yield, resource efficiency, environmental sustainability, and cost savings. It represents a significant shift from traditional farming methods to a more technology-driven, data-driven, and environmentally conscious approach to crop and animal production. On one side, CFD is powerful and precise techniques of computer modeling and simulation of airflows and thermo-hygrometric parameters, that has been applied to optimize the growth environment of crops and the efficiency of ventilation in pig barns. On the other side, the sustainability aspect has been investigated and researched in terms of Life Cycle Assessment analyses.