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Bayesian Tensor Binary Regression
No full textIn this paper we present a binary regression model with tensor coefficients and present a Bayesian model for inference, able to recover different levels of sparsity of the tensor coefficient. We exploit the CONDECOMP/PARAFAC (CP) representation for the tensor of coefficients in order to reduce the number of parameters and adopt a suitable hierarchical shrinkage prior for inducing sparsity. We propose a MCMC procedure with data augmentation for carrying out the estimation and test the performance of the sampler in small simulated examples
Petri Nets for Modelling and Analysing Trophic Networks
No full textWe consider trophic networks, a kind of networks used in ecology to represent feeding
interactions (what-eats-what) in an ecosystem. Starting from the observation that trophic networks
can be naturally modelled as Petri nets, we explore the possibility of using Petri nets for the analysis
and simulation of trophic networks. We define and discuss different continuous Petri net models,
whose level of accuracy depends on the information available for the modelled trophic network. The
simplest Petri net model we construct just relies on the topology of the network. We also propose a
technique for deriving a more refined model that embeds into the Petri net the known constraints on
the transition rates that represent the knowledge on metabolism and diet of the species in the network.
Finally, if the information of the biomass amounts for each species at steady state is available, we
discuss a way of further refining the Petri net model in order to represent dynamic behaviour. We
apply our Petri net technology to a case study of the Venice lagoon and analyse the results
A Welcome Guest? A Preliminary Assessment of Velio Spano's Journey to Mao's China 1949-50
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Multiple stressors facilitate the spread of a non-indigenous bivalve in the Mediterranean Sea
No full textAim: The introduction of non-indigenous species (NIS) via man-made corridors connecting previously disparate oceanic regions is increasing globally. However, the environmental and anthropogenic factors facilitating invasion dynamics and their interactions are still largely unknown. This study compiles and inputs available data for the NIS bivalve Brachidontes pharaonis across the invaded biogeographic range in the Mediterranean basin into a species distribution model to predict future spread under a range of marine scenarios. Location: Mediterranean Sea. Methods: A systematic review produced the largest presence database ever assembled to inform the selection of biological, chemical and physical factors linked to the spread of B. pharaonis through the Suez Canal. We carried out a sensitivity analysis to simulate current and future trophic and salinity scenarios. A species distribution model was run to determine key drivers of invasion, quantify interactive impacts arising from a range of trophic states, salinity conditions and climatic scenarios and forecast future trajectories for the spread of NIS into new regions under multiple-parameter scenarios (based on the main factors identified from the systematic review). Results: Impacts on invasion trajectory arising from climate change and interactions with increasing salinity from the new opening of the canal were the primary drivers of expansion across the basin, the effects of which were further enhanced by eutrophication. Predictions of the current distribution were most accurate when multiple stressors were used to drive the model. A habitat suitability index developed at a subcontinental scale from model outputs identified novel favourable conditions for future colonization at specific locations under 2030 and 2050 climatic scenarios. Main conclusions: Future expansion of B. pharaonis will be enhanced by climate-facilitated increased sea temperature, interacting with increasing pressures from salinity and eutrophication. The spatially explicit risk output maps of invasions represent a powerful visual product for use in communication of the spread of NIS and decision-support tools for scientists and policymakers. The suggested approach, the observed distribution pattern and driving processes can be applied to other NIS species and regions by providing novel forecasts of species occurrences under future multiple stressor scenarios and the location of suitable recipient habitats with respect to anthropogenic and environmental parameters
Au and AuCu nanoparticles supported on SBA-15 ordered mesoporous titania-silica as catalysts for methylene blue photodegradation
No full textThe photocatalytic degradation of methylene blue (MB) dye has been performed under
UV irradiation in aqueous suspension, employing photocatalysts based on Au (1.5 wt %) and AuCu
(Au/Cu = 1, 2.0 wt %), and supported on SBA-15-ordered mesoporous silica, with and without titania
(Si/Ti = 3), in order to evaluate the versatility of this mesoporous support in this type of reaction of
great impact from the environmental point of view. Samples were characterized by X-ray diffraction
(XRD), transmission electron microscopy (TEM), N2 adsorption-desorption at −196 ◦C, and X-ray
photoelectron spectroscopy (XPS), so as to study their structural, optical, and chemical properties.
All the prepared catalysts were found to be active in the test reaction. The bimetallic AuCu-based
catalysts attained very high MB degradation values, in particular AuCu/SBA-15 titania-silica sample
reached 100% of dye oxidation after the monitored reaction period (120 min)
I paradossi dell'autodichia. Prospettive delle giurisdizioni domestiche dopo la sentenza della Corte costituzionale n. 262/2017
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Hierarchical oxygen reduction reaction electrocatalysts based on FeSn0.5species embedded in carbon nitride-graphene based supports
No full textThis work reports the synthesis, the physicochemical characterization and the electrochemical studies of new electrocatalysts (ECs) for the oxygen reduction reaction (ORR) that: (i) exhibit a hierarchical architecture; and (ii) do not comprise platinum. The active sites of the ECs consist of Fe and Sn species stabilized in “coordination nests” of a carbon nitride (CN) matrix. The latter exhibits a rough, microporous morphology and acts as a “shell” covering a graphene “core”. This paper: (i) discusses the role played by Fe as the “active metal” in this family of ECs; and (ii) examines in detail how the physicochemical properties and, correspondingly, the electrochemical performance are affected by a suitable activation procedure A meant to boost the ORR kinetics. The results lead to an improved fundamental understanding on the features of the active sites, including the impact of both A and the pH of the environment in their performance and ORR mechanism. These insights clarify the most desirable features to be included in high-performing ECs belonging to this family, paving the way to the synthesis of next-generation, efficient ECs for the ORR that do not comprise platinum