Integrated soil fertility management in eastern and western Africa: The role of knowledge and innovation systems, its adoption and impact

The rise in population growth, as well as nutrient mining, has contributed to low agricultural productivity in Sub-Saharan Africa (SSA). A plethora of technologies to boost agricultural production have been developed but the dissemination of these agricultural innovations and subsequent uptake by smallholder farmers has remained a challenge. Scientists and philanthropists have adopted the Integrated Soil Fertility Management (ISFM) paradigm as a means to promote sustainable intensification of African farming systems. This comparative study aimed: 1) To assess the efficacy of Agricultural Knowledge and Innovation Systems (AKIS) in East (Kenya) and West (Ghana) Africa in the communication and dissemination of ISFM (Study I); 2) To investigate how specifically soil quality, and more broadly socio-economic status and institutional factors, influence farmer adoption of ISFM (Study II); and 3) To assess the effect of ISFM on maize yield and total household income of smallholder farmers (Study III). To address these aims, a mixed methodology approach was employed for study I. AKIS actors were subjected to social network analysis methods and in-depth interviews. Structured questionnaires were administered to 285 farming households in Tamale and 300 households in Kakamega selected using a stratified random sampling approach. There was a positive relationship between complete ISFM awareness among farmers and weak knowledge ties to both formal and informal actors at both research locations. The Kakamega AKIS revealed a relationship between complete ISFM awareness among farmers and them having strong knowledge ties to formal actors implying that further integration of formal actors with farmers’ local knowledge is crucial for the agricultural development progress. The structured questionnaire was also utilized to answer the query pertaining to study II. Soil samples (0-20 cm depth) were drawn from 322 (Tamale, Ghana) and 459 (Kakamega, Kenya) maize plots and analysed non-destructively for various soil fertility indicators. Ordinal regression modeling was applied to assess the cumulative adoption of ISFM. According to model estimates, soil carbon seemed to preclude farmers from intensifying input use in Tamale, whereas in Kakamega it spurred complete adoption. This varied response by farmers to soil quality conditions is multifaceted. From the Tamale perspective, it is consistent with farmers’ tendency to judiciously allocate scarce resources. Viewed from the Kakamega perspective, it points to a need for farmers here to intensify agricultural production in order to foster food security. In Kakamega, farmers with more acidic soils were more likely to adopt ISFM. Other household and farm-level factors necessary for ISFM adoption included off-farm income, livestock ownership, farmer associations, and market inter-linkages. Finally, in study III a counterfactual model was used to calculate the difference in outcomes (yield and household income) of the treatment (ISFM adoption) in order to estimate causal effects of ISFM adoption. Adoption of ISFM contributed to a yield increase of 16% in both Tamale and Kakamega. The innovation affected total household income only in Tamale, where ISFM adopters had an income gain of 20%. This may be attributable to the different policy contexts under which the two sets of farmers operate. The main recommendations underscored the need to: (1) improve the functioning of AKIS, (2) enhance farmer access to hybrid maize seed and credit, (3) and conduct additional multi-locational studies as farmers operate under varying contexts.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modeled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets Assisted by CPS

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy assisted by a cyber-physical system for supporting management decisions to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a stochastic linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modelled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Computer-based monitoring platform for renewable energy systems: Four experimental application cases using NI LabVIEW

Sustainability and responsible environmental behaviour constitute a vital premise in the development of the humankind. In fact, during last decades, the global energetic scenario is evolving towards a scheme with increasing relevance of Renewable Energy Sources (RES) like photovoltaic, wind, biomass and hydrogen. Furthermore, hydrogen is an energy carrier which constitutes a mean for long-term energy storage. The integration of hydrogen with local RES contributes to distributed power generation and early introduction of hydrogen economy. Intermittent nature of many of RES, for instance solar and wind sources, impose the development of a management and control strategy to overcome this drawback. This strategy is responsible of providing a reliable, stable and efficient operation of the system. To implement such strategy, a monitoring system is required.The present paper aims to contribute to experimentally validate LabVIEW as valuable tool to develop monitoring platforms in the field of RES-based facilities. To this aim, a set of real systems successfully monitored is exposed.

Large scale underground energy storage for renewables integration: general criteria for reservoir identification and viable technologies.

The increasing integration of renewable energies in the electricity grid contributes considerably to achieve the European Union goals on energy and Greenhouse Gases (GHG) emissions reduction. However, it also brings problems to grid management. Large scale energy storage can provide the means for a better integration of the renewable energy sources, for balancing supply and demand, to increase energy security, to enhance a better management of the grid and also to converge towards a low carbon economy. Geological formations have the potential to store large volumes of fluids with minimal impact to environment and society. One of the ways to ensure a large scale energy storage is to use the storage capacity in geological reservoir. In fact, there are several viable technologies for underground energy storage, as well as several types of underground reservoirs that can be considered. The geological energy storage technologies considered in this research were: Underground Gas Storage (UGS), Hydrogen Storage (HS), Compressed Air Energy Storage (CAES), Underground Pumped Hydro Storage (UPHS) and Thermal Energy Storage (TES). For these different types of underground energy storage technologies there are several types of geological reservoirs that can be suitable, namely: depleted hydrocarbon reservoirs, aquifers, salt formations and caverns, engineered rock caverns and abandoned mines. Specific site screening criteria are applicable to each of these reservoir types and technologies, which determines the viability of the reservoir itself, and of the technology for any particular site. This paper presents a review of the criteria applied in the scope of the Portuguese contribution to the EU funded project ESTMAP – Energy Storage Mapping and Planning.

Waste Heat Recovery Systems: Numerical and Experimental Analysis of organic Rankine Cycle Solutions

This thesis aims to present the ORC technology, its advantages and related problems. In particular, it provides an analysis of ORC waste heat recovery system in different and innovative scenarios, focusing on cases from the biggest to the lowest scale. Both industrial and residential ORC applications are considered. In both applications, the installation of a subcritical and recuperated ORC system is examined. Moreover, heat recovery is considered in absence of an intermediate heat transfer circuit. This solution allow to improve the recovery efficiency, but requiring safety precautions. Possible integrations of ORC systems with renewable sources are also presented and investigated to improve the non-programmable source exploitation. In particular, the offshore oil and gas sector has been selected as a promising industrial large-scale ORC application. From the design of ORC systems coupled with Gas Turbines (GTs) as topper systems, the dynamic behavior of the GT+ORC innovative combined cycles has been analyzed by developing a dynamic model of all the considered components. The dynamic behavior is caused by integration with a wind farm. The electric and thermal aspects have been examined to identify the advantages related to the waste heat recovery system installation. Moreover, an experimental test rig has been realized to test the performance of a micro-scale ORC prototype. The prototype recovers heat from a low temperature water stream, available for instance in industrial or residential waste heat. In the test bench, various sensors have been installed, an acquisitions system developed in Labview environment to completely analyze the ORC behavior. Data collected in real time and corresponding to the system dynamic behavior have been used to evaluate the system performance based on selected indexes. Moreover, various operational steady-state conditions are identified and operation maps are realized for a completely characterization of the system and to detect the optimal operating conditions.

Interoperability Challenges in Internet of Things Systems: a Service-Oriented Computing Approach

Internet of Things systems are pervasive systems evolved from cyber-physical to large-scale systems. Due to the number of technologies involved, software development involves several integration challenges. Among them, the ones preventing proper integration are those related to the system heterogeneity, and thus addressing interoperability issues. From a software engineering perspective, developers mostly experience the lack of interoperability in the two phases of software development: programming and deployment. On the one hand, modern software tends to be distributed in several components, each adopting its most-appropriate technology stack, pushing programmers to code in a protocol- and data-agnostic way. On the other hand, each software component should run in the most appropriate execution environment and, as a result, system architects strive to automate the deployment in distributed infrastructures. This dissertation aims to improve the development process by introducing proper tools to handle certain aspects of the system heterogeneity. Our effort focuses on three of these aspects and, for each one of those, we propose a tool addressing the underlying challenge. The first tool aims to handle heterogeneity at the transport and application protocol level, the second to manage different data formats, while the third to obtain optimal deployment. To realize the tools, we adopted a linguistic approach, i.e.\ we provided specific linguistic abstractions that help developers to increase the expressive power of the programming language they use, writing better solutions in more straightforward ways. To validate the approach, we implemented use cases to show that the tools can be used in practice and that they help to achieve the expected level of interoperability. In conclusion, to move a step towards the realization of an integrated Internet of Things ecosystem, we target programmers and architects and propose them to use the presented tools to ease the software development process.

Development of methodologies supporting the sustainable and safe integration of offshore conventional and renewable energy production

Against a backdrop of rapidly increasing worldwide population and growing energy demand, the development of renewable energy technologies has become of primary importance in the effort to reduce greenhouse gas emissions. However, it is often technically and economically infeasible to transport discontinuous renewable electricity for long distances to the shore. Another shortcoming of non-programmable renewable power is its integration into the onshore grid without affecting the dispatching process. On the other hand, the offshore oil & gas industry is striving to reduce overall carbon footprint from onsite power generators and limiting large expenses associated to carrying electricity from remote offshore facilities. Furthermore, the increased complexity and expansion towards challenging areas of offshore hydrocarbons operations call for higher attention to safety and environmental protection issues from major accident hazards. Innovative hybrid energy systems, as Power-to-Gas (P2G), Power-to-Liquid (P2L) and Gas-to-Power (G2P) options, implemented at offshore locations, would offer the opportunity to overcome challenges of both renewable and oil & gas sectors. This study aims at the development of systematic methodologies based on proper sustainability and safety performance indicators supporting the choice of P2G, P2L and G2P hybrid energy options for offshore green projects in early design phases. An in-depth analysis of the different offshore hybrid strategies was performed. The literature reviews on existing methods proposing metrics to assess sustainability of hybrid energy systems, inherent safety of process routes in conceptual design stage and environmental protection of installations from oil and chemical accidental spills were carried out. To fill the gaps, a suite of specific decision-making methodologies was developed, based on representative multi-criteria indicators addressing technical, economic, environmental and societal aspects of alternative options. A set of five case-studies was defined, covering different offshore scenarios of concern, to provide an assessment of the effectiveness and value of the developed tools.

Green supercapacitive systems

This Ph.D. thesis addresses the challenging goal of integrating supercapacitive features in MFCs by sustainable materials and processes and valorizing wastes by their processing as key components of supercapacitors and MFCs. Three main research lines have been pursued: i) the development of green supercapacitors by exploiting natural polymers as binders and electrospun separators, ii) the improvement of the power output of MFCs by the external integration of commercial and green supercapacitors, and ii) the development of supercapacitive microbial fuel cells by the monolithic integration of supercapacitive features in MFCs. This Thesis is articulated in the following Sections. Chapter 1 introduce the energy-water nexus, highlights the role played by supercapacitors and MFCs in this context, and describes the main components, and processes in these devices.

Development of sexing systems functional to mass production of Aedes albopictus sterile males

Aedes albopictus is a vector able to transmit several arboviruses. Due to its high impact on human health, it is important to develop an efficient control strategy for this pest. Nowadays, control based on chemical insecticides is limited by the number of available active principles and the occurrence of resistance. A valuable alternative to the conventional control strategies is the sterile insect technique (SIT) which relies on releasing sterile males of the target insect. Mating between wild females and sterile males results in no viable offspring. A crucial aspect of SIT is the production of a large number of sterile males with a low presence of females that can bite and transmit viruses. The present thesis aimed to find, implement and study the most reliable mechanical sex sorter and protocol to implement male productivity and reduce female contamination. In addition, I evaluated different variables and sorting protocols to enable female recovery for breeding purposes. Furthermore, I studied the creation of a hyper-protandric strain potentially able to produce only males. I also assessed the integration of artificial intelligence with an optical unit to identify sexes at the adult stage. All these applications helped to realise a mass production model in Italy with a potential weekly production of 1 million males. Moreover, I studied and applied for aerial sterile male release in an urban environment. This technology could allow the release of males in a wide area, overcoming environmental and urban obstacles. However, the development and application of drone technologies in a metropolitan area close to airports, such as in Bologna area, must fit specific requirements. Lastly, at Réunion Island, during a Short Term Scientific Mission France (AIM-COST Action), Indian Ocean, I studied the Boosted SIT application. Coating sterile males with Pyriproxyfen may help spread the insecticide into the larval breeding sites.

Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.

Hardware-software design of embedded systems for intelligent sensing applications

This Thesis wants to highlight the importance of ad-hoc designed and developed embedded systems in the implementation of intelligent sensor networks. As evidence four areas of application are presented: Precision Agriculture, Bioengineering, Automotive and Structural Health Monitoring. For each field is reported one, or more, smart device design and developing, in addition to on-board elaborations, experimental validation and in field tests. In particular, it is presented the design and development of a fruit meter. In the bioengineering field, three different projects are reported, detailing the architectures implemented and the validation tests conducted. Two prototype realizations of an inner temperature measurement system in electric motors for an automotive application are then discussed. Lastly, the HW/SW design of a Smart Sensor Network is analyzed: the network features on-board data management and processing, integration in an IoT toolchain, Wireless Sensor Network developments and an AI framework for vibration-based structural assessment.

A framework for the environmental risk assessment of offshore carbon storage in CCS systems

Carbon capture and storage (CCS) represents an interesting climate mitigation option, however, as for any other human activity, there is the impelling need to assess and manage the associated risks. This study specifically addresses the marine environmental risk posed by CO2 leakages associated to CCS subsea engineering system, meant as offshore pipelines and injection / plugged and abandoned wells. The aim of this thesis work is to start approaching the development of a complete and standardized practical procedure to perform a quantified environmental risk assessment for CCS, with reference to the specific activities mentioned above. Such an effort would be of extreme relevance not only for companies willing to implement CCS, as a methodological guidance, but also, by uniformizing the ERA procedure, to begin changing people’s perception about CCS, that happens to be often discredited due to the evident lack of comprehensive and systematic methods to assess the impacts on the marine environment. The backbone structure of the framework developed consists on the integration of ERA’s main steps and those belonging to the quantified risk assessment (QRA), in the aim of quantitatively characterizing risk and describing it as a combination of magnitude of the consequences and their frequency. The framework developed by this work is, however, at a high level, as not every single aspect has been dealt with in the required detail. Thus, several alternative options are presented to be considered for use depending on the situation. Further specific studies should address their accuracy and efficiency and solve the knowledge gaps emerged, in order to establish and validate a final and complete procedure. Regardless of the knowledge gaps and uncertainties, that surely need to be addressed, this preliminary framework already finds some relevance in on field applications, as a non-stringent guidance to perform CCS ERA, and it constitutes the foundation of the final framework.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

A Microleakage Study Of Gutta-percha/ah Plus And Resilon/real Self-etch Systems After Different Irrigation Protocols.

The development and maintenance of the sealing of the root canal system is the key to the success of root canal treatment. The resin-based adhesive material has the potential to reduce the microleakage of the root canal because of its adhesive properties and penetration into dentinal walls. Moreover, the irrigation protocols may have an influence on the adhesiveness of resin-based sealers to root dentin. The objective of the present study was to evaluate the effect of different irrigant protocols on coronal bacterial microleakage of gutta-percha/AH Plus and Resilon/Real Seal Self-etch systems. One hundred ninety pre-molars were used. The teeth were divided into 18 experimental groups according to the irrigation protocols and filling materials used. The protocols used were: distilled water; sodium hypochlorite (NaOCl)+eDTA; NaOCl+H3PO4; NaOCl+eDTA+chlorhexidine (CHX); NaOCl+H3PO4+CHX; CHX+eDTA; CHX+ H3PO4; CHX+eDTA+CHX and CHX+H3PO4+CHX. Gutta-percha/AH Plus or Resilon/Real Seal Se were used as root-filling materials. The coronal microleakage was evaluated for 90 days against Enterococcus faecalis. Data were statistically analyzed using Kaplan-Meier survival test, Kruskal-Wallis and Mann-Whitney tests. No significant difference was verified in the groups using chlorhexidine or sodium hypochlorite during the chemo-mechanical preparation followed by eDTA or phosphoric acid for smear layer removal. The same results were found for filling materials. However, the statistical analyses revealed that a final flush with 2% chlorhexidine reduced significantly the coronal microleakage. A final flush with 2% chlorhexidine after smear layer removal reduces coronal microleakage of teeth filled with gutta-percha/AH Plus or Resilon/Real Seal SE.