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1. Artificial intelligence is becoming increasingly important in our daily professional and social lives. Although the use of AI systems has many benefits for a variety of sectors, different legal challenges remain. Some of these challenges are extensively discussed in this book. In this chapter, we will focus on the application of liability for damage caused by AI systems. The importance of liability and AI systems has already been mentioned in several recent documents issued by the European Union (EU). The White Paper on Artificial Intelligence, for instance, stresses that the main risks related to the use of AI concern the application of rules designed to protect fundamental rights as well as safety and liability-related issues. Scholars have also concluded that ‘[l]iability certainly represents one of the most relevant and recurring themes’ when it comes to AI systems.
2. This emphasis on liability is not surprising considering that AI systems will increasingly cause damage. Reference can be made to recent accidents involving autonomous vehicles. The autopilot of a Tesla car, for instance, was not able to distinguish a white tractor-trailer crossing the road from the bright sky above, leading to a fatal crash. A self-driving Uber car recently hit a pedestrian in Arizona. The woman later died in the hospital. A robot also attacked and injured a man at a tech fair in China. A surgical robot at a hospital in Philadelphia malfunctioned during a prostate surgery, thereby severely injuring the patient. In February 2015, a South Korean woman was sleeping on the floor when her robot vacuum ‘ate’ her hair forcing her to call for emergency help.
These examples show that accidents may happen despite optimising national and supranational safety rules for AI. This is when questions of liability become important. Nevertheless, the application of liability regimes for damage caused by AI systems can be challenging. The characteristics of AI systems such as opaqueness, autonomy, connectivity, data dependency or self-learning abilities make it difficult to trace back potentially problematic decisions made with the involvement of such systems.
Many shorebird populations are in decline along the East Asian-Australasian Flyway. The rapid loss of coastal wetlands in the Yellow Sea, which provide critical stop-over sites during migration, is believed to be the cause of the alarming trends. The Yalu Jiang coastal wetland, a protected area in the north Yellow Sea, supports the largest known migratory staging populations of Bar-tailed Godwits Limosa lapponica (menzbieri and baueri subspecies) and Great Knots Calidris tenuirostris. Monitoring of the macrozoobenthos food for these shorebirds from 2011 to 2016 showed declines of over 99% in the densities of the bivalve Potamocorbula laevis, the major food here for both Bar-tailed Godwits and Great Knots. The loss of the bivalve might be caused by any combination of, but not limited to: (1) change in hydrological conditions and sediment composition due to nearby port construction, (2) run-off of agrochemicals from the extensive shoreline sea cucumber farms, and (3) parasitic infection. Surprisingly, the numbers of birds using the Yalu Jiang coastal wetland remained stable during the study period, except for the subspecies of Bar-tailed Godwit L. l. menzbieri, which exhibited a 91% decline in peak numbers. The lack of an overall decline in the number of bird days in Great Knots and in the peak numbers of L. l. baueri, also given the published simultaneous decreases in their annual survival, implies a lack of alternative habitats that birds could relocate to. This study highlights that food declines at staging sites could be an overlooked but important factor causing population declines of shorebirds along the Flyway. Maintaining the quality of protected staging sites is as important in shorebird conservation as is the safeguarding of staging sites from land claim. Meanwhile, it calls for immediate action to restore the food base for these beleaguered migrant shorebirds at Yalu Jiang coastal wetland.
In the frame of the COST ACTION ‘EMBOS’ (Development and implementation of a pan-European Marine Biodiversity Observatory System), coverage of intertidal macroalgae was estimated at a range of marine stations along the European coastline (Subarctic, Baltic, Atlantic, Mediterranean). Based on these data, we tested whether patterns in macroalgal diversity and distribution along European intertidal rocky shores could be explained by a set of meteo-oceanographic variables. The variables considered were salinity, sea surface temperature, photosynthetically active radiation, significant wave height and tidal range and were compiled from three different sources: remote sensing, reanalysis technique and in situ measurement. These variables were parameterized to represent average conditions (mean values), variability (standard deviation) and extreme events (minimum and maximum values). The results obtained in this study contribute to reinforce the EMBOS network approach and highlight the necessity of considering meteo-oceanographic variables in long-term assessments. The broad spatial distribution of pilot sites has allowed identification of latitudinal and longitudinal gradients manifested through species composition, diversity and dominance structure of intertidal macroalgae. These patterns follow a latitudinal gradient mainly explained by sea surface temperature, but also by photosynthetically active radiation, salinity and tidal range. Additionally, a longitudinal gradient was also detected and could be linked to wave height.
Examining how variability in population abundance and distribution is allotted among different spatial scales can inform of processes that are likely to generate that variability. Results of studies dealing with scale issues in marine benthic communities suggest that variability is concentrated at small spatial scales (from tens of centimetres to few metres) and that spatial patterns of variation are consistent across ecosystems characterized by contrasting physical and biotic conditions, but this has not been formally tested. Here we quantified the variability in the distribution of intertidal rocky shore communities at a range of spatial scales, from tens of centimetres to thousands of kilometres, both in the NE Atlantic and the Mediterranean, and tested whether the observed patterns differed between the two basins. We focused on canopy-forming macroalgae and associated understorey assemblages in the low intertidal, and on the distribution of Patella limpets at mid intertidal levels. Our results highlight that patterns of spatial variation, at each scale investigated, were consistent between the Atlantic and the Mediterranean, suggesting that similar ecological processes operate in these regions. In contrast with former studies, variability in canopy cover, species richness and limpet abundance was equally distributed among spatial scales, possibly reflecting the fingerprint of multiple processes. Variability in community structure of low intertidal assemblages, instead, peaked at the largest scale, suggesting that oceanographic processes and climatic gradients may be important. We conclude that formal comparisons of variability across scales nested in contrasting systems are needed, before any generalization on patterns and processes can be made.
Coastal ecosystems are highly complex and driven by multiple environmental factors. To date we lack scientific evidence for the relative contribution of natural and anthropogenic drivers for the majority of marine habitats in order to adequately assess the role of different stressors across the European seas. Such relationship can be investigated by analysing the correlation between environmental variables and biotic patterns in multivariate space and taking into account non-linearities. Within the framework of the EMBOS (European Marine Biodiversity Observatory System) programme, hard bottom intertidal communities were sampled in a standardized way across European seas. Links between key natural and anthropogenic drivers and hard bottom communities were analysed using Boosted Regression Trees modelling. The study identified strong interregional variability and showed that patterns of hard bottom macroalgal and invertebrate communities were primarily a function of tidal regime, nutrient loading and water temperature (anomalies). The strength and shape of functional form relationships varied widely however among types of organisms (understorey algae composing mostly filamentous species, canopy-forming algae or sessile invertebrates) and aggregated community variables (cover or richness). Tidal regime significantly modulated the effect of nutrient load on the cover and richness of understorey algae and sessile invertebrates. In contrast, hydroclimate was more important for canopy algae and temperature anomalies and hydroclimate separately or interactively contributed to the observed patterns. The analyses also suggested that climate-induced shifts in weather patterns may result in the loss of algal richness and thereby in the loss of functional diversity in European hard bottom intertidal areas.
Within the COST action EMBOS (European Marine Biodiversity Observatory System) the degree and variation of the diversity and densities of soft-bottom communities from the lower intertidal or the shallow subtidal was measured at 28 marine sites along the European coastline (Baltic, Atlantic, Mediterranean) using jointly agreed and harmonized protocols, tools and indicators. The hypothesis tested was that the diversity for all taxonomic groups would decrease with increasing latitude. The EMBOS system delivered accurate and comparable data on the diversity and densities of the soft sediment macrozoobenthic community over a large-scale gradient along the European coastline. In contrast to general biogeographic theory, species diversity showed no linear relationship with latitude, yet a bell-shaped relation was found. The diversity and densities of benthos were mostly positively correlated with environmental factors such as temperature, salinity, mud and organic matter content in sediment, or wave height, and related with location characteristics such as system type (lagoons, estuaries, open coast) or stratum (intertidal, subtidal). For some relationships, a maximum (e.g. temperature from 15–20°C; mud content of sediment around 40%) or bimodal curve (e.g. salinity) was found. In lagoons the densities were twice higher than in other locations, and at open coasts the diversity was much lower than in other locations. We conclude that latitudinal trends and regional differences in diversity and densities are strongly influenced by, i.e. merely the result of, particular sets and ranges of environmental factors and location characteristics specific to certain areas, such as the Baltic, with typical salinity clines (favouring insects) and the Mediterranean, with higher temperatures (favouring crustaceans). Therefore, eventual trends with latitude are primarily indirect and so can be overcome by local variation of environmental factors.
Having interlamellar spacings on the nanometer scale, there is no doubt about considering heavily drawn pearlitic steel wire as a nano-layered material. This extremely fine structure is of great technical importance: indeed, as the interlamellar distance determines the onset of plastic flow, the wire can be brought to a tensile strength beyond 4000 MPa and is therefore one of the strongest materials on the market nowadays.
At extremely large strains (well beyond ε = 4) and/or at moderate temperatures, the pearlitic steel loses its strength. Several possible failure mechanisms, like fragmentation of the cementite or thermal and strain-induced cementite dissolution, are put forward, but until now, there is no definite understanding of the really active mechanism.
In the present work, the calorimetric differential scanning technique, in combination with thermopower measurements and the high-resolution atomic force microscopy, have turned out to be most promising tools to reveal some of the mechanisms that are responsible for the degradation of the lamellar aggregate.
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