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The field of social choice dates back to the eighteenth century, when Borda and Condorcet started a never-ending discussion about the use of either positional or pairwise information. Three centuries later, after countless axiomatic characterizations of voting rules, impossibility theorems and many other study subjects, researchers still debate whether positional information is really sensitive to manipulation or pairwise information disregards the transitivity of voters' preferences. In a previous paper, we introduced the notions of supercovering relation and pairwise winner, which resulted in a meeting point for both points of view of the theory of social choice. In this paper, we continue this direction and propose the notions of superdominance relation and positional winner that will prove to be the alter egos of the supercovering relation and the pairwise winner when positional information (rather than pairwise information) is considered. Moreover, we analyse a new interesting choice set: the unsuperdominated set.

The equation xa+xb+x=xc+xd+1 considered in this paper is a particular
equiponderate equation. The number and location of the roots (w.r.t. x = 1) of this equation
are determined in case (a,b,c,d)∈]0,1[4. Based on these results, it is shown that any weight
quadruplet, a basic tool in fuzzy preference modelling, admits an interesting expression in terms
of Frank t-norms with reciprocal parameters.

Abstract. In recent decades, large wildfires have inflicted considerable damage on valuable Natura 2000 regions in Belgium. Despite these events and the general perception that global change will exacerbate wildfire prevalence, this has not been studied yet in the Belgian context. Therefore, the national government initiated the national action plan on wildfires in order to evaluate the wildfire risk, on the one hand, and the materials, procedures, and training of fire services, on the other hand. This study focuses on the spatial distribution of the ignition probability, a component of the wildfire risk framework. In a first stage, we compile a historical wildfire database using (i) newspaper articles between 1994 and 2016 and (ii) a list of wildfire interventions between 2010 and 2013, provided by the government. In a second stage, we use a straightforward method relying on Bayes' rule and a limited number of covariates to calculate the ignition probability. It appears that most wildfire-prone areas in Belgium are located in heathland where military exercises are held. The provinces that have the largest relative areas with a high or very high wildfire risk are Limburg and Antwerp. Our study also revealed that most wildfire ignitions in Belgium are caused by humans (both arson and negligence) and that natural causes such as lightning are rather scarce. Wildfire prevention can be improved by (i) excluding military activity in fire-prone areas during the fire season, (ii) improving collaboration with foreign emergency services, (iii) concentrating the dedicated resources in the areas that display the highest ignition probabilities, (iv) improving fire detection methods, and (v) raising more awareness among the public.

Abstract. Understanding the oceanic response to tropical cyclones (TCs) is of importance for studies on climate change. Although the oceanic effects induced by individual TCs have been extensively investigated, studies on the oceanic response to the passage of consecutive TCs are rare. In this work, we assess the upper-oceanic response to the passage of Hurricanes Dorian and Humberto over the western Sargasso Sea in 2019 using satellite remote sensing and modelled data. We found that the combined effects of these slow-moving TCs led to an increased oceanic response during the third and fourth post-storm weeks of Dorian (accounting for both Dorian and Humberto effects) because of the induced mixing and upwelling at this time. Overall, anomalies of sea surface temperature, ocean heat content, and mean temperature from the sea surface to a depth of 100 m were 50 %, 63 %, and 57 % smaller (more negative) in the third–fourth post-storm weeks than in the first–second post-storm weeks of Dorian (accounting only for Dorian effects), respectively. For the biological response, we found that surface chlorophyll a (chl a) concentration anomalies, the mean chl a concentration in the euphotic zone, and the chl a concentration in the deep chlorophyll maximum were 16 %, 4 %, and 16 % higher in the third–fourth post-storm weeks than in the first–second post-storm weeks, respectively. The sea surface cooling and increased biological response induced by these TCs were significantly higher (Mann–Whitney test, p<0.05) compared to climatological records. Our climatological analysis reveals that the strongest TC-induced oceanographic variability in the western Sargasso Sea can be associated with the occurrence of consecutive TCs and long-lasting TC forcing.

International audience ; Abstract•Key messagePattern recognition has become an important tool to aid in the identification and classification of timber species. In this context, the focus of this work is the classification of wood species using texture characteristics of transverse cross-section images obtained by microscopy. The results show that this approach is robust and promising.•ContextConsidering the lack of automated methods for wood species classification, machine vision based on pattern recognition might offer a feasible and attractive solution because it is less dependent on expert knowledge, while existing databases containing high-quality microscopy images can be exploited.•AimsThis work focuses on the automated classification of 1221 micro-images originating from 77 commercial timber species from the Democratic Republic of Congo.•MethodsMicroscopic images of transverse cross-sections of all wood species are taken in a standardized way using a magnification of 25 ×. The images are represented as texture feature vectors extracted using local phase quantization or local binary patterns and classified by a nearest neighbor classifier according to a triplet of labels (species, genus, family).•ResultsThe classification combining both local phase quantization and linear discriminant analysis results in an average success rate of approximately 88% at species level, 89% at genus level and 90% at family level. The success rate of the classification method is remarkably high. More than 50% of the species are never misclassified or only once. The success rate is increasing from the species, over the genus to the family level. Quite often, pattern recognition results can be explained anatomically. Species with a high success rate show diagnostic features in the images used, whereas species with a low success rate often have distinctive anatomical features at other microscopic magnifications or orientations than those used in our approach.•ConclusionThis work demonstrates the potential of a semi-automated ...

International audience ; Abstract•Key messagePattern recognition has become an important tool to aid in the identification and classification of timber species. In this context, the focus of this work is the classification of wood species using texture characteristics of transverse cross-section images obtained by microscopy. The results show that this approach is robust and promising.•ContextConsidering the lack of automated methods for wood species classification, machine vision based on pattern recognition might offer a feasible and attractive solution because it is less dependent on expert knowledge, while existing databases containing high-quality microscopy images can be exploited.•AimsThis work focuses on the automated classification of 1221 micro-images originating from 77 commercial timber species from the Democratic Republic of Congo.•MethodsMicroscopic images of transverse cross-sections of all wood species are taken in a standardized way using a magnification of 25 ×. The images are represented as texture feature vectors extracted using local phase quantization or local binary patterns and classified by a nearest neighbor classifier according to a triplet of labels (species, genus, family).•ResultsThe classification combining both local phase quantization and linear discriminant analysis results in an average success rate of approximately 88% at species level, 89% at genus level and 90% at family level. The success rate of the classification method is remarkably high. More than 50% of the species are never misclassified or only once. The success rate is increasing from the species, over the genus to the family level. Quite often, pattern recognition results can be explained anatomically. Species with a high success rate show diagnostic features in the images used, whereas species with a low success rate often have distinctive anatomical features at other microscopic magnifications or orientations than those used in our approach.•ConclusionThis work demonstrates the potential of a semi-automated ...

The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution. ; European Commission/EU RD/IST-265432 ; SONY-CS Computer Science Lab