Faut-il réguler l'encombrement des sites récréatifs ? Un modèle de choix discret avec participation

En France, les sites récréatifs sont généralement en accès libre, ce qui explique qu’ils sont souvent encombrés, notamment quand ils sont attractifs et proches des zones peuplées. La théorie prévoit que l’équilibre de fréquentation est alors non optimal en raison d’un effet externe d’encombrement. Alors que des travaux anciens ont caractérisé équilibre et optimum dans le cadre de modèles mono-site à demande continue (Fisher et Krutilla, 1972), les rares articles récents utilisant les modèles de choix discret se sont limités à étudier empiriquement l’équilibre et la répartition des visites entre les sites. Notre modèle théorique permet de formaliser l’équilibre et l’optimum de fréquentation, dans le cadre d’un modèle de choix discret à deux sites intégrant la décision de participation des individus, ainsi que certains instruments de gestion permettant d’améliorer le bien-être. Il a été nécessaire de recourir à une formulation générale du bien-être définie par Erlander (2005). On montre que les individus participent trop et visitent trop le site de meilleure qualité (et pas assez le site de qualité inférieure) à l’équilibre. En exprimant les désutilités collectives liées à la participation et à la mauvaise répartition des visites entre les sites, le modèle permet d’en déduire les taxes optimales et les effets sur le bien-être collectif d’une augmentation de la qualité des sites. Une illustration simplifiée est proposée à partir d’un modèle logit multinomial estimé sur des données de pêche récréativeendogenous congestion, optimum, equilibrium, Random Utility Model, recreation demand

SVGMapping: an R package to map omic data sets onto pathways templates

SVGMapping: an R package to map omic data sets onto pathways template

Generic Platforms for Indicator Visualization in City Planning

Stadig flere urbane data har blitt tilgjengelig det siste tiåret, takket være bred bruk av sanseteknologier og flere statlige initiativer. Disse dataene kan være nyttige for ulike bruksområder, for eksempel byplanlegging basert på nøkkelindikatorer. Korrekt bruk av dem krever imidlertid effektive visualiseringsverktøy for å støtte korrekt og innsiktsfull forståelse og analyse. Det er forsket mye på modellering og integrering av geografiske data, og det er utviklet ulike verktøy for visualisering av disse. Imidlertid er disse verktøyene vanligvis applikasjonsavhengige og kan ikke enkelt skreddersys til andre problemer. Dessuten kreves det ofte noe teknisk kunnskap for å bruke dem riktig. Denne oppgaven introduserer design, implementering og validering av to fleksible indikatorvisualiserings- og vurderingsplattformer i byplanlegging. Arkitekturen til applikasjoner som støtter visualisering og vurdering av indikatorer basert på romlige data presenteres, og deretter implementert for bruk av både byplanleggere og innbyggere. Flere casestudier som involverer vurdering av tilgjengelighet for busstjenester, gangbarhet og bymobilitet i Ålesund by, Norge, er diskutert. Deretter utføres to evalueringer med grupper av brukere for å validere bruken av applikasjonene. Oppnådde resultater viser at de utviklede verktøyene er fleksible og kan brukes av byplanleggere og innbyggere. De utviklede verktøyene er tilgjengelige på https://github.com/Rylern/master-thesis – Fra og med juni 2022.Increasingly more urban data have become available in the last decade, thanks to the wide use of sensing technologies and several governmental initiatives. These data can be useful for different applications, such as urban planning based on key performance indicators. Their proper use, however, requires effective visualization tools to support correct and insightful understanding and analysis. Much research has been carried out on modeling and integrating geographical data, and different tools have been developed for their visualization. However, those tools are usually application-dependent and cannot be easily tailored to other problems. Moreover, some technical knowledge is often required to use them properly. This thesis introduces the design, implementation, and validation of two flexible indicator visualization and assessment platforms in city planning. The architecture of applications supporting the visualization and the assessment of indicators based on spatial data is presented, and then implemented for use by both urban planners and citizens. Several case studies involving the assessment of bus service availability, walkability, and city mobility in the city of Ålesund, Norway, are discussed. Then, two evaluations with groups of users are performed to validate the use of the applications. Obtained results demonstrate that the developed tools are flexible and can be used by urban planners and citizens. The developed tools are available at https://github.com/Rylern/master-thesis – As of June 2022

Effect of GA 3 and paclobutrazol on adventitious shoot regeneration of two Pelargonium sp

This study had two aims. The first was to improve the regeneration efficiency of Pelargonium leaf discs by adventitious budding. The second was to test the effect of gibberellic acid (GA 3) and paclobutrazol (PBZ) on callus formation and adventitious shoot regeneration in Pelargonium before using genetic transformation of this species for functional validation of genes involved in the process of GA regulation. GA 3 and paclobutrazol (an inhibitor of GA synthesis pathway) were added (together or separately) in the shoot regeneration media of two Pelargonium species, Pelargonium * hortorum \u27Panache sud\u27 (\u27P.sud\u27) and Pelargonium * domesticum \u27Autumn haze\u27 (\u27 P.dom\u27). In both cases, GA 3 applied alone, completely inhibited the bud regeneration. Moreover, the rate of callus formation decreased drastically when 5 M of GA 3 was applied to \u27 P. dom\u27 explants. Similar result was obtained with \u27P.sud\u27 explants using 20 M GA 3. Paclobutrazol (0.3 M) applied at the same time as GA 3 (10 M) could partially restore regeneration process of \u27 P. dom\u27. For \u27 P. dom\u27, the use of paclobutrazol alone increased callus formation and slightly improved the rate of regeneration. Moreover, initiated buds had a better appearance. For \u27P. sud\u27, which had an abundant callusing, paclobutrazol did not improve regeneration and led to hyperhydric shoots

21st century catch toolkit: practical approaches for sustainable inshore fishing communities

The 21st Century Catch Toolkit is a product of the INTERREG IVa 2 Seas project GIFS (Geography of Inshore Fishing and Sustainability). Work on the GIFS project was completed between January 2012 and September 2014 and was undertaken by a collaboration of six partners from four European countries bordering the Southern North Sea and English Channel. GIFS aimed to understand and capture the social, economic and cultural importance of inshore fishing to better inform fisheries policy, coastal regeneration strategies and sustainable community development. The project has involved a range of research projects, regeneration activities and case studies across southern England, northern France, Flanders and the southern Netherlands. GIFS partners have worked with local stakeholders and communities to explore the geographical diversity and similarities of fishing ports, harbours and people along the Channel and Southern North Sea. This toolkit is a product of that collaboration which provides useful findings and advice on how to value the social, economic and cultural importance of inshore fishing today

Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models

Regularized nonnegative low-rank approximations such as sparse Nonnegative Matrix Factorization or sparse Nonnegative Tucker Decomposition are an important branch of dimensionality reduction models with enhanced interpretability. However, from a practical perspective, the choice of regularizers and regularization coefficients, as well as the design of efficient algorithms, is challenging because of the multifactor nature of these models and the lack of theory to back these choices. This paper aims at improving upon these issues. By studying a more general model called the Homogeneous Regularized Scale-Invariant, we prove that the scale-invariance inherent to low-rank approximation models causes an implicit regularization with both unexpected beneficial and detrimental effects. This observation allows to better understand the effect of regularization functions in low-rank approximation models, to guide the choice of the regularization hyperparameters, and to design balancing strategies to enhance the convergence speed of dedicated optimization algorithms. Some of these results were already known but restricted to specific instances of regularized low-rank approximations. We also derive a generic Majorization Minimization algorithm that handles many regularized nonnegative low-rank approximations, with convergence guarantees. We showcase our contributions on sparse Nonnegative Matrix Factorization, ridge-regularized Canonical Polyadic decomposition and sparse Nonnegative Tucker Decomposition.Comment: Correction of the exponent in the second term of Equation 2

Genomic prediction of manganese efficiency in winter barley

Manganese efficiency is a quantitative abiotic stress trait controlled by several genes each with a small effect. Manganese deficiency leads to yield reduction in winter barley ( L.). Breeding new cultivars for this trait remains difficult because of the lack of visual symptoms and the polygenic features of the trait. Hence, Mn efficiency is a potential suitable trait for a genomic selection (GS) approach. A collection of 248 winter barley varieties was screened for Mn efficiency using Chlorophyll (Chl ) fluorescence in six environments prone to induce Mn deficiency. Two models for genomic prediction were implemented to predict future performance and breeding value of untested varieties. Predictions were obtained using multivariate mixed models: best linear unbiased predictor (BLUP) and genomic best linear unbiased predictor (G-BLUP). In the first model, predictions were based on the phenotypic evaluation, whereas both phenotypic and genomic marker data were included in the second model. Accuracy of predicting future phenotype, , and accuracy of predicting true breeding values, , were calculated and compared for both models using six cross-validation (CV) schemes; these were designed to mimic plant breeding programs. Overall, the CVs showed that prediction accuracies increased when using the G-BLUP model compared with the prediction accuracies using the BLUP model. Furthermore, the accuracies [] of predicting breeding values were more accurate than accuracy of predicting future phenotypes []. The study confirms that genomic data may enhance the prediction accuracy. Moreover it indicates that GS is a suitable breeding approach for quantitative abiotic stress traits

Maurice Reuchlin y la dialéctica de laboratorio / campo

La elección del texto que aquí se presenta responde a un doble objetivo : proponer un tema que mantiene siempre su interés, así como rendir homenaje a un gran psicólogo, Maurice Reuchlin (1920 -2015), fallecido recientemente luego de una larga enfermedad que lo condenó prematuramente al silencio. Este investigador produjo una obra significativa plasmada en libros y artículos. Citemos dos ejemplos : un tratado de Psicología reeditado varias veces y un Tratado de psicología aplicada (trabajo co..

Blind Audio Source Separation with Minimum-Volume Beta-Divergence NMF

Considering a mixed signal composed of various audio sources and recorded with a single microphone, we consider on this paper the blind audio source separation problem which consists in isolating and extracting each of the sources. To perform this task, nonnegative matrix factorization (NMF) based on the Kullback-Leibler and Itakura-Saito $\beta$-divergences is a standard and state-of-the-art technique that uses the time-frequency representation of the signal. We present a new NMF model better suited for this task. It is based on the minimization of $\beta$-divergences along with a penalty term that promotes the columns of the dictionary matrix to have a small volume. Under some mild assumptions and in noiseless conditions, we prove that this model is provably able to identify the sources. In order to solve this problem, we propose multiplicative updates whose derivations are based on the standard majorization-minimization framework. We show on several numerical experiments that our new model is able to obtain more interpretable results than standard NMF models. Moreover, we show that it is able to recover the sources even when the number of sources present into the mixed signal is overestimated. In fact, our model automatically sets sources to zero in this situation, hence performs model order selection automatically.Comment: 24 pages, 10 figures, 3 table