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Tobacco smoking is still a widespread habit in pregnant and breastfeeding women. While the role of these risk factors on neonatal outcomes has been deeply studied, their effect on human milk composition is still not completely clear. This study aimed to report the most up to date evidence about the alteration of breast milk composition of smoking breastfeeding mothers compared to non-smoking ones. We performed a systematic review by searching PubMed, Embase, and Cochrane Library databases. Evaluated data were extracted and critically analyzed by two independent authors. PRISMA guidelines were applied, and the risk of bias was assessed (ROBINS), as was the methodological quality of the included studies (GRADE). After applying the inclusion criteria, we included 20 studies assessed as medium or high quality. In all the studies, we analyzed data regarding 1769 mothers (398 smokers and 971 nonsmokers). Smoking was associated with a lower content of lipids, calories, and proteins. Moreover, it was characterized by decreased antioxidant properties and an altered immune status. Smoking during pregnancy and breastfeeding is significantly associated with an alteration of milk metabolic properties. Further studies are needed to investigate how these changes can alter newborns’ development and outcomes and which molecular patterns are involved.

European consumers prefer wild over farmed aquatic food and consider it healthier and tastier. Consumers are increasingly paying attention to sustainability and welfare of farmed fish. Such expecta...

17 pages, 10 figures, Current fishing practices often do not allow adequate selection of species or sizes of fish, resulting in unwanted catches, subsequently discarded, with the consequent negative effects on both marine communities and fisheries profitability. The cross-analysis of density patches of potential unwanted catches and distribution of fishing effort can support the identification of spatial-temporal hot-spots in which the fishing pressure should be reduced to limit the amount of discards. The MinouwApp represents a technological and methodological framework to bring different, and structurally complex, sources of georeferenced data together into a simple visual interface aiming to interactively explore temporal ranges and areas of interest. The objective is to improve the understanding of fisheries dynamics, including discards, thus contributing to the implementation of discard management plans in a context of participative, ecosystem-based fisheries management strategies, Open access funding provided by Università degli Studi di Roma Tor Vergata within the CRUI-CARE Agreement. This research has received funding from the European Commission’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 634495 for the Science, Technology and Society Initiative to Minimize Unwanted Catches in European Fisheries (MINOUW), With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

Technologies within the same industry are expected to follow similar patterns of innovation, and when the dominant patterns change, this is often expected to have disruptive effects on the industry. However, the three most recent lighting technologies (fluorescent, compact fluorescent, and LED) show different patterns of innovative activities despite similarities in the determinants of innovation; and we observed multiple technological regimes within the lighting industry. Furthermore, we observed changes in these innovative patterns without widespread disruptive effects. While FL and LED quickly improved once they were introduced, CFL struggled for decades. We present an historical case study of the emergence and development of the different regimes and we present possible explanations to be found in market structure and selection criteria. The analysis shows the important role for policymakers in stimulating new technologies in industries with undesirable Mark II pattern through the influence of all the dimensions of the technological regimes.

Participation is advocated as an essential component of strategies and policies for sustainable urban mobility. This paper refers to the overall literature on participation and provides the design, test and ex-post evaluation of a deliberative-participative procedure (DPP) aimed at selecting a new scheme for the regulation of traffic and parking in the “Murat”, a central area of Bari (Italy). The potential benefits and shortcomings of participation were explicitly considered when designing a DPP which integrates three tools: an opinion poll and two deliberative arenas – the “stakeholder dialogue” and the “citizens’ jury”. The ex-post evaluation of the test confirmed ex-ante design choices. The DPP was effective and learning was generated: the use of understandable techniques for deliberation and assessment helped participants to generate an unambiguous final result which was based on the “hybridisation” of the alternative schemes proposed to the participants at the beginning of the procedure. The “last word” given to the citizens’ jury avoided that the most powerful stakeholders may capture the DPP. Only a “frustration” effect was clearly generated because of the limited involvement of the Municipality of Bari, thus confirming that the involvement of the relevant Authority is an essential requisite for successful participation. We suggest that the generation of new knowledge and learning could be further assured by the participation of citizens and stakeholders to the definition of the alternatives they will assess later.

Species distribution is the result of complex interactions that involve environmental parameters as well as biotic factors. However, methodological approaches that consider the use of biotic variables during the prediction process are still largely lacking. Here, a cascaded Artificial Neural Networks (ANN) approach is proposed in order to increase the accuracy of fish species occurrence estimates and a case study for Leucos aula in NE Italy is presented as a demonstration case. Potentially useful biotic information (i.e. occurrence of other species) was selected by means of tetrachoric correlation analysis and on the basis of the improvements it allowed to obtain relative to models based on environmental variables only. The prediction accuracy of the L. aula model based on environmental variables only was improved by the addition of occurrence data for A. arborella and S. erythrophthalmus. While biotic information was needed to train the ANNs, the final cascaded ANN model was able to predict L. aula better than a conventional ANN using environmental variables only as inputs. Results highlighted that biotic information provided by occurrence estimates for non-target species whose distribution can be more easily and accurately modeled may play a very useful role, providing additional predictive variables to target species distribution models.

Marine litter has significant ecological, social and economic impacts, ultimately raising welfare and conservation concerns. Assessing marine litter hotspots or inferring potential areas of accumulation are challenging topics of marine research. Nevertheless, models able to predict the distribution of marine litter on the seabed are still limited. In this work, a set of Artificial Neural Networks were trained to both model the effect of environmental descriptors on litter distribution and estimate the amount of marine litter in the Central Mediterranean Sea. The first goal involved the use of self-organizing maps in order to highlight the importance of environmental descriptors in affecting marine litter density. The second goal was achieved by developing a multilayer perceptron model, which proved to be an efficient method to estimate the regional quantity of seabed marine litter. Results demonstrated that machine learning could be a suitable approach in the assessment of the marine litter issues.

Toxigenic cyanobacteria are one of the main health risks associated with water resources worldwide, as their toxins can affect humans and fauna exposed via drinking water, aquaculture and recreation. Microscopy monitoring of cyanobacteria in water bodies and massive growth systems is a routine operation for cell abundance and growth estimation. Here we present ACQUA (Automated Cyanobacterial Quantification Algorithm), a new fully automated image analysis method designed for filamentous genera in Bright field microscopy. A pre-processing algorithm has been developed to highlight filaments of interest from background signals due to other phytoplankton and dust. A spline-fitting algorithm has been designed to recombine interrupted and crossing filaments in order to perform accurate morphometric analysis and to extract the surface pattern information of highlighted objects. In addition, 17 specific pattern indicators have been developed and used as input data for a machine-learning algorithm dedicated to the recognition between five widespread toxic or potentially toxic filamentous genera in freshwater: Aphanizomenon, Cylindrospermopsis, Dolichospermum, Limnothrix and Planktothrix. The method was validated using freshwater samples from three Italian volcanic lakes comparing automated vs. manual results. ACQUA proved to be a fast and accurate tool to rapidly assess freshwater quality and to characterize cyanobacterial assemblages in aquatic environments.

The aim of this chapter is to show that the socio-technical map (ST-map) can be useful even to analyze the current and future dynamics of feeding: a societal function that feature complex techno-economic dynamics and contrasting political visions. First of all, the ST systems that are relevant for the today provision of food are considered: the global agribusiness system; the traditional and new local systems; the organic system; the fairtrade system. For each of them a supporting network of innovators is identified; all relevant policies—at the global, national and local scale—are also considered. Then, all food ST systems are positioned into a ST-map based on two dimensions. The first dimension is built on five alternative discourses on sustainable food: ‘Food for all’, ‘Healthy food’, ‘Environment-friendly food’, ‘Food as local culture and local development’, and ‘Food that is produced in a fair way’. The other dimension ranks supply chains from simple to complex: complexity of supply chains depends on both the distance covered and the number of steps. The chapter ends with a future analysis of sustainable food. Starting from ongoing changes and from alternative dynamics of ST-systems and networks of innovators, three scenarios are proposed. The ‘Biotech’ scenario results from a two-fold transition involving the global agribusiness system: suppliers of biotechnological inputs respond to the pressure for sustainable agriculture and food security; large-scale retailers integrate the commercial activity of the organic, fairtrade and local systems. The ‘Elite Versus Mass’ scenario features a new network led by elitist large-scale retailers that clusters the commercial activities of the organic and fair trade systems in order to serve the increasing demand for healthy and environment-friendly food. In the ‘Organic’ scenario a new dominant system integrates all the productive and commercial actors who are interested in converting to organic practices and to organic food products; also some large-scale retailers coming from the global agribusiness system join the organic network. In all scenarios the cumulative process between the empowerment of networks and the emergence of supporting policies is stressed.

In this chapter we analyse the sustainability transition pathway that made Freiburg an ‘Eco-city’ where the modal share of slow mobility is more than 50 % (pedestrians: 24 %; cycling: 28 %), and the car is less relevant (30 %). Through the sequential use of three ST-maps we are able to reconstruct the sustainability transition of Freiburg: from an emerging ‘Auto-city’, where private cars increase of importance (first ST-map: 1969), through a time of coexistence of four different systems (individual car, public transport, individual bicycle, walkability) (second ST-map: 1979), until the polarization in two systems: the individual car and the so-called ‘City of Short Distances’ (third ST-map: 2010). The reproduction of these two systems takes place at different scales: local actors support the ‘City of Short Distances’—which is today dominant in Freiburg—while national and international actors keep supporting the individual car.

In this chapter we show that the socio-technical map (ST-map) can be useful to represent sustainability transitions also when multi-scalar dynamics are at stake. This is the case of urban mobility: it takes place at a local level, but some of its constituents—actors, policies, technologies—are national or global. The analysis starts with the consideration of the ST systems and niches that concur to (and compete for) the provision of urban mobility: the dominant system of the individual car; the subaltern systems of public transport and the bicycle; the emerging carsharing schemes. Also some locally dominant systems of integrated mobility are considered. These systems are then positioned into a ST-map built on two dimensions. The first dimension consider all the relevant political discourses on urban mobility: ‘Mobility as a driver of development’; ‘Mobility as a generator of harmful impacts’; ‘Mobility as a determinant of the quality of urban spaces’; ‘Mobility as a right’. The second dimension lists three alternative business models: ‘sell vehicles’, ‘rent vehicles’, ‘manage transport systems’. Starting from the ST-map of the current situation of urban mobility—and from the consideration of the ongoing changes—three alternative scenarios are proposed. The ‘Auto-city’ scenario emerges from the reconfiguration of the existing ‘individual car’ dominant system and is generated by the absorption of the producers of batteries. In the ‘Eco-city’ scenario a coalition of urban networks supports a new political discourse of urban mobility and foster the creation of new urban systems of integrated mobility. In the ‘Electri-city’ scenario local and national electric operators takes over the individual car system because they are interested in the integration of smart grids and electric vehicles, also in order to increase grid stability and reduce demand-supply unbalances, in particular in the case of renewable sources. Multi-scalar dynamics are at the heart of the proposed scenarios of urban mobility: the ‘Auto-city’ and the ‘Electri-city’ scenarios mostly result from global dynamics, where niches are used for experimentation; the ‘Eco-city’ scenario emerges from a two-dimension diffusion process: horizontally, at the local level, where dominant positions “migrate” from an urban area to another; vertically, from the local to the national level, in order to gain greater political support.