On polyhedral projection and parametric programming

Submitted versio

Physical and biogeochemical controls on the variability in surface pH and calcium carbonate saturation states in the Atlantic sectors of the Arctic and Southern Oceans

Polar oceans are particularly vulnerable to ocean acidification due to their low temperatures and reduced buffering capacity, and are expected to experience extensive low pH conditions and reduced carbonate mineral saturations states (Ω) in the near future. However, the impact of anthropogenic CO2 on pH and Ω will vary regionally between and across the Arctic and Southern Oceans. Here we investigate the carbonate chemistry in the Atlantic sector of two polar oceans, the Nordic Seas and Barents Sea in the Arctic Ocean, and the Scotia and Weddell Seas in the Southern Ocean, to determine the physical and biogeochemical processes that control surface pH and Ω. High-resolution observations showed large gradients in surface pH (0.10–0.30) and aragonite saturation state (Ωar) (0.2–1.0) over small spatial scales, and these were particularly strong in sea-ice covered areas (up to 0.45 in pH and 2.0 in Ωar). In the Arctic, sea-ice melt facilitated bloom initiation in light-limited and iron replete (dFe>0.2 nM) regions, such as the Fram Strait, resulting in high pH (8.45) and Ωar (3.0) along the sea-ice edge. In contrast, accumulation of dissolved inorganic carbon derived from organic carbon mineralisation under the ice resulted in low pH (8.05) and Ωar (1.1) in areas where thick ice persisted. In the Southern Ocean, sea-ice retreat resulted in bloom formation only where terrestrial inputs supplied sufficient iron (dFe>0.2 nM), such as in the vicinity of the South Sandwich Islands where enhanced pH (8.3) and Ωar (2.3) were primarily due to biological production. In contrast, in the adjacent Weddell Sea, weak biological uptake of CO2 due to low iron concentrations (dFe<0.2 nM) resulted in low pH (8.1) and Ωar (1.6). The large spatial variability in both polar oceans highlights the need for spatially resolved surface data of carbonate chemistry variables but also nutrients (including iron) in order to accurately elucidate the large gradients experienced by marine organisms and to understand their response to increased CO2 in the future

Modeling the Progression of Alzheimer's Disease for Cognitive Assistance and Smart homes

International audienceSmart homes provide support to cognitively impaired people (such as those suffering from Alzheimer's disease) so that they can remain at home in an autonomous and safe way. In order to be efficient and responsive, cognitive assistance requires models of this impaired population. This paper presents a way to model and simulate the progression of dementia of the Alzheimer's type by evaluating performance in the execution of an activity of daily living (ADL). This model satisfies three objectives: first, it models an activity of daily living; second, it simulates the progression of the dementia and the errors potentially made by people suffering from it, and, finally, it simulates the support needed by the impaired person. To develop this model, we chose the ACT-R cognitive architecture, which uses symbolic and subsymbolic representations. The simulated results of 100 people suffering from Alzheimer's disease closely resemble the results obtained by 106 people on an occupational assessment (the Kitchen Task Assessment)