144 research outputs found
Data set: Average daily minimum temperature in January and February in Corsica
No full textRaster providing the average of the daily minimum temperature in Celsius degrees over January and February in Corsica from 1995 to 2003 with a 0.016667x0.0166671 resolution in latitude and longitude.
Construction: This raster was constructed from the freely available database (PVGIS © European Communities, 2001-2008) providing, in particular, monthly averages of the daily minimum temperature reconstructed over a grid with 11km spatial resolution (Huld et al., 2006). These monthly averages correspond to the period 1995-2003 and were used by Abboud et al. (2019, 2020) to model Xylella fastidious dynamics in South Corsica.
Load the raster in the R statistical software (v4.1.2):
library(raster)
ADMT=raster("average-daily-minimum-temperature_Corsica_Abboud-et-al_Forecasting.grd")
print(ADMT)
plot(ADMT)
Summary information:
class : RasterLayer
dimensions : 108, 78, 8424 (nrow, ncol, ncell)
resolution : 0.016667, 0.016667 (x, y)
extent : 8.400708, 9.700734, 41.30018, 43.10021 (xmin, xmax, ymin, ymax)
crs : +proj=longlat +datum=WGS84 +no_defs
source : average-daily-minimum-temperature_Corsica_Abboud-et-al_Forecasting.grd
names : layer
values : -0.6748945, 6.75789 (min, max)
References:
- Abboud, C., Bonnefon, O., Parent, E., and Soubeyrand, S. (2019). Dating and localizing an invasion from post-introduction data and a coupled reaction–diffusion–absorption model. Journal of Mathematical Biology 79, 765–789.
- Abboud, C., Parent, E., Bonnefon, O., and Soubeyrand, S. (2022). Forecasting pathogen dynamics with Bayesian model-averaging: Application to Xylella fastidiosa. Preprint.
- Huld, T. A., Suri, M., Dunlop, E. D., and Micale, F. (2006). Estimating average daytime and daily temperature profiles within Europe. Environmental Modelling & Software 21, 1650–1661
Forecasting Pathogen Dynamics with Bayesian Model-Averaging: Application to Xylella fastidiosa
No full textBeyond Xylella, Integrated Management Strategies for Mitigating Xylella fastidiosa Impact in Europe (BeXyl) (Grant Agreement 101060593). Partner/Coordinador principal: Blanca B. Landa del Castillo, Investigadora Científica del Instituto de Agricultura Sostenible (IAS-CSIC).Forecasting invasive-pathogen dynamics is paramount to anticipate eradication and containment strategies. Such predictions can be obtained using a model grounded on partial differential equations (PDE; often exploited to model invasions) and fitted to surveillance data. This framework allows the construction of phenomenological but concise models relying on mechanistic hypotheses and real observations. However, it may lead to models with overly rigid behavior and possible data-model mismatches. Hence, to avoid drawing a forecast grounded on a single PDE-based model that would be prone to errors, we propose to apply Bayesian model averaging (BMA), which allows us to account for both parameter and model uncertainties. Thus, we propose a set of different competing PDE-based models for representing the pathogen dynamics, we use an adaptive multiple importance sampling algorithm (AMIS) to estimate parameters of each competing model from surveillance data in a mechanistic-statistical framework, we evaluate the posterior probabilities of models by comparing different approaches proposed in the literature, and we apply BMA to draw posterior distributions of parameters and a posterior forecast of the pathogen dynamics. This approach is applied to predict the extent of Xylella fastidiosa in South Corsica, France, a phytopathogenic bacterium detected in situ in Europe less than 10 years ago (Italy 2013, France 2015). Separating data into training and validation sets, we show that the BMA forecast outperforms competing forecast approaches.This research was funded by a PhD grant INRAE-Région PACA (Emplois Jeunes Doctorants 2016-2019), the HORIZON XF-ACTORS Project (grant SFS-09-2016), the HORIZON BeXyl Project (grant 101060593) and the ANR BEYOND Project (grant 20-PCPA-0002).Peer reviewe
Under the Rubble
No full textUnder the Rubble is an illustrated children’s short story that imagines a child’s experience of the destructive earthquake that hit Syria and Turkey in the early hours of February, the 6th, 2023.
Yaman witnesses the terrifying moment the ground shook and finds himself buried under the rubble of his own family home. Quick and composed, he finds a way to alert the rescuers of his location.
Under the Rubble is a story of resilience, hope and gratitude in the face of loss and tragedy.
The dual-text (Arabic-English) story is a collaboration between the author, Mohammed Ani and the
illustrator, Malik Al Abboud, with editorial input from Feras Alkabani
Recommended from our members
Under the Rubble
No full textUnder the Rubble is an illustrated children’s short story that imagines a child’s experience of the destructive earthquake that hit Syria and Turkey in the early hours of February, the 6th, 2023.
Yaman witnesses the terrifying moment the ground shook and finds himself buried under the rubble of his own family home. Quick and composed, he finds a way to alert the rescuers of his location.
Under the Rubble is a story of resilience, hope and gratitude in the face of loss and tragedy.
The dual-text (Arabic-English) story is a collaboration between the author, Mohammed Ani and the
illustrator, Malik Al Abboud, with editorial input from Feras Alkabani
Inferring and predicting invasive species dynamics : focus on Xylella fastidiosa
No full textLa thèse porte sur la recherche d’une méthodologie générique permettant d'améliorer les prédictions d’une invasion biologique pour laquelle on ne dispose pas de modèle spécifique et dont les conditions initiales sont inconnues. Pour atteindre cet objectif, on procède suivant deux axes de recherche complémentaires. Dans le premier axe, on s’intéresse à l’inférence des invasions biologiques à partir d’un modèle spatio-temporel de propagation et de données collectées, en suivant une approche mécanistico-statistique. Elle repose sur (i) une équation aux dérivées partielles (EDP) offrant une représentation concise d’une dynamique qui envahit un domaine hétérogène, (ii) un modèle stochastique représentant le processus d’observation et (iii) une méthode d’inférence Bayésienne pour estimer les paramètres du modèle. Un modèle dérivé des processus de Markov déterministes par morceaux est proposé pour remplacer l'EDP permettant un compromis entre réalisme du modèle et facilité d’estimation. Dans le deuxième axe, on propose une approche prenant en compte les incertitudes entourant des modèles en compétition. La technique du Bayesian model-averaging combine les prédictions de ces modèles pour obtenir une prédiction unifiée améliorée. Cette technique a souvent été utilisée en sciences environnementales. Toutefois, elle n’est pas répandue dans le domaine de l’épidémiologie. L’un des buts méthodologiques de la thèse est d’en évaluer l’intérêt pour l’épidémiologie prédictive. Le cas d’étude est celui de Xylella fastidiosa, bactérie phytopathogène ayant le potentiel de causer en France une crise sanitaire majeure en santé végétale à l’image de celle qu’elle cause depuis 2013 en ItalieThe thesis research aims to provide a generic methodology that improves the predictions of an invasive species dynamics for which no dedicated model is available and whose initial conditions are unknown. In order to achieve this goal, we proceed in two complementary lines of research. The first one is to propose a model&data-based inference method of biological invasions, in the framework of the so-called mechanistic-statistical approach. This method allows us to jointly estimate the introduction point and other parameters of the dynamics related to diffusion, reproduction and death. It is hinged on (i) a partial differential equation (PDE) that offers a concise description of the invasive species dynamics in a heterogeneous domain, (ii) a stochastic model that represents the observation process and (iii) a statistical Bayesian inference procedure for estimating model parameters. We propose to replace the PDE by a model issued from the framework of Piecewise-deterministic Markov Process to balance the trade-off between model realism and estimation easiness. The second research line consists on accounting for the uncertainty about models form using the Bayesian model-averaging. This method consists of combining predictions drawn from competing models in order to obtain a unique and ameliorated prediction. This technique is not widespread in the field of epidemiology. One of the methodological goals of the PhD is to investigate its application and usefulness in predictive epidemiology. The case study of my thesis is the phytopathogenic bacterium Xylella fastidiosa which is susceptible to cause in France a major sanitary crisis as the one caused in Italy since 201
Inférer et Prédire les Dynamiques D’espèces Invasives Focus sur Xylella fastidiosa
No full textThe spread of invasive alien species to new areas has always been an appealing research topic for mathematicians as well as for biologists. In particular, many investigations are carried out to recon- struct the past dynamics of the alien species and to predict its future spread. In essence, the thesis research aims to provide a generic methodology (i.e. scalable to various invasive species) that im- proves the predictions of an invasive species dynamics for which no dedicated model is available and whose initial conditions (i.e. date and location of the introduction of invasive species) are unknown. In order to achieve this goal, we proceed in two complementary lines of research. The first one is to propose a model&data-based inference method of biological invasions, in the framework of the so-called mechanistic-statistical approach. This method allows us to jointly estimate the introduc- tion point (date and location of the invasive species arrival) and other parameters of the dynamics related to diffusion, reproduction and death. It is hinged on (i) a partial differential equation that offers a phenomenological and concise description of the invasive species dynamics in a heteroge- neous domain, (ii) a stochastic model that represents the observation process, which allows to fit the partial differential equation to the data and (iii) a statistical Bayesian inference procedure, the adaptive multiple importance sampling algorithm, for estimating model parameters. To gain in re- alism, the phenomenological deterministic model could be replaced by a stochastic model, as for example a stochastic partial differential equation or spatio-temporal point process. However, such models may induce additional difficulties in estimation because of the supplementary parameters and latent variables. Models issued from the framework of Piecewise-deterministic Markov Process could be an appealing and interesting alternative to balance the trade-off between model realism and estimation easiness. In the framework presented above, preference was given to the use of generic spatio-temporal propagation models since the main processes underlying the spread of an alien species are usually unknown. However, predictions that can be drawn from those models are not optimal because they are affected by the assumptions made in the corresponding models, and do not take into account the uncertainty about the model form. The approach I use to overcome this problem is the so-called Bayesian model-averaging. This method consists of combining predictions drawn from competing models in order to obtain a unique and ameliorated prediction. This tech- nique has been previously used in environmental sciences. Nevertheless, it is not widespread in the field of epidemiology. One of the methodological goals of the PhD is to investigate its application and usefulness in predictive epidemiology.The case study of my thesis is the phytopathogenic bacterium Xylella fastidiosa for which abun- dant spatio-temporal and binary post-introduction surveillance data were collected from an intensive surveillance plan implemented by governmental agencies after the first pathogen detection in Corsica in 2015. This quarantine pathogen that has significantly impacted olive production in Italy and that presents a drastic risk of change to the environment for its ability to reach a large variety of plants, is susceptible to cause in France a major sanitary crisis, as the one caused in Italy since 2013 where the socio-economical impacts are considerable.L’invasion de territoires par des espèces allogènes a toujours été un sujet attrayant pour les mathé- maticiens aussi bien que pour les biologistes. En particulier, de nombreux travaux sont menés afin de reconstruire la dynamique passée d’espèces envahissantes. Fondamentalement, le projet de thèse porte sur la recherche d’une méthodologie générique (i.e. adaptable à diverses espèces invasives), permettant l’amélioration des prédictions d’une invasion biologique pour laquelle on ne dispose pas de modèle spécifique et dont les conditions initiales (i.e. la date et le lieu d’introduction de l’espèce invasive) sont inconnues. Pour atteindre cet objectif, on procède suivant deux axes de recherche complémentaires. Dans le premier axe, on s’intéresse à l’inférence des invasions biologiques à par- tir d’un modèle spatio-temporel de propagation et de données collectées, en suivant une approche mécanistico-statistique. Cette méthode permet d’estimer d’une façon jointe le point d’introduction (date et site de l’arrivée de l’espèce invasive) et d’autres paramètres de la dynamique reliés à la diffusion, la reproduction et la mortalité. Elle repose sur (i) une équation aux dérivées partielles offrant une représentation phénoménologique et concise d’une dynamique qui envahit un domaine hétérogène, (ii) un modèle stochastique représentant le processus d’observation permettant d’ajuster l’équation aux dérivées partielles aux données et (iii) une méthode d’inférence statistique Bayésienne, l’adaptive multiple importance sampling algorithm, pour estimer les paramètres du modèle. Pour gagner en réalisme, le modèle phénoménologique déterministe peut être remplacé par un modèle stochastique, comme par exemple une équation aux dérivées partielles stochastique ou un processus de points spatio-temporel. Cependant, de tels modèles peuvent induire des difficultés d’estimation du fait des paramètres supplémentaires et des variables latentes. Des modèles dérivés du cadre des processus de Markov déterministes par morceaux peuvent constituer une alternative intéressante en permettant un compromis entre réalisme du modèle et facilité d’estimation. Dans le cadre d’étude décrit ci-dessus, l’utilisation de modèles "tout-terrain" a été privilégiée puisque les déterminants de propagation d’une espèce localement nouvelle dans un nouvel environnement sont généralement incertains. Cependant, les prédictions pouvant être tirées de ces modèles ne sont pas optimales puisqu’elles dépendent fortement des hypothèses sous-jacentes au modèle et qu’elles ne prennent pas en compte les incertitudes pouvant l’entourer. Ma deuxième ligne de recherche consiste à proposer une approche permettant de prendre en compte les incertitudes entourant chaque modèle. La tech- nique que j’emploie est celle du Bayesian model-averaging. Cette technique consiste à combiner les prédictions des modèles en compétition d’une façon à obtenir une prédiction unifiée améliorée. Cette technique a souvent été utilisée en sciences environnementales. Toutefois, elle n’est pas répandue dans le domaine de l’épidémiologie. L’un des buts méthodologiques de la thèse est d’en évaluer l’intérêt pour l’épidémiologie prédictive.Le cas d’étude de ma thèse est celui de la bactérie phytopathogène Xylella fastidiosa pour laquelle des données de surveillance spatio-temporelles et binaires post-introduction ont été collectées à partir d’un plan de surveillance intense qui a été mis en place par l’État suite à la première détection de cette bactérie en Corse en 2015. Ce pathogène de quarantaine, qui a significativement impacté la production d’olives en Italie et présente un risque de modification drastique de l’environnement du fait de sa capacité à atteindre de nombreuses espèces végétales, a le potentiel de causer en France une crise sanitaire majeure en santé végétale, à l’image de celle qu’elle cause depuis 2013 en Italie où les impacts socio-économiques sont conséquents
Bayesian Estimation of Simultaneous Regression Quantiles Using Hamiltonian Monte Carlo
No full textThe simultaneous estimation of multiple quantiles is a crucial statistical task that enables a thorough understanding of data distribution for robust analysis and decision-making. In this study, we adopt a Bayesian approach to tackle this critical task, employing the asymmetric Laplace distribution (ALD) as a flexible framework for quantile modeling. Our methodology implementation involves the Hamiltonian Monte Carlo (HMC) algorithm, building on the foundation laid in prior work, where the error term is assumed to follow an ALD. Capitalizing on the interplay between two distinct quantiles of this distribution, we endorse a straightforward and fully Bayesian method that adheres to the non-crossing property of quantiles. Illustrated through simulated scenarios, we showcase the effectiveness of our approach in quantile estimation, enhancing precision via the HMC algorithm. The proposed method proves versatile, finding application in finance, environmental science, healthcare, and manufacturing, and contributing to sustainable development goals by fostering innovation and enhancing decision-making in diverse fields
Gas phase protonation of diazirines: A route to N-protonated diazomethanes
No full textN-Protonated diazomethanes have been generated successfully via gas phase protonation of the corresponding diazirines.PT: J; CR: ABBOUD JLM, 1994, J AM CHEM SOC, V116, P2486 COOK F, 1966, J AM CHEM SOC, V88, P3870 FRISCH MJ, 1995, GAUSSIAN 94 LIU MTH, 1987, CHEM DIAZIRINES MISHIMA M, 1989, NIPPON KAGAKU KAISHI, P1262 MISHIMA M, 1996, B CHEM SOC JPN, V69, P445 TAFT RW, 1983, PROG PHYS ORG CHEM, V14, P247 WIBERG KB, 1966, J AM CHEM SOC, V88, P365 WIBERG KB, 1966, J AM CHEM SOC, V88, P5272 ZOLLINGER H, 1994, DIAZO CHEM 1 2; NR: 10; TC: 1; J9: CHEM COMMUN; PG: 2; GA: 113PCSource type: Electronic(1
Al-Tantawi´s notebook: examples for teaching Egyptian and Arabic folklore
No full textEn este artículo se estudia el cuaderno de al-Šayj Muhammad 'Ayyād al-
Tantāwī (1810-1861) que emigró a San Petersburgo en 1840 para enseñar a los futuros
orientalistas rusos la lengua árabe en sus dos registros, el clásico y el coloquial de El Cairo;
murió en 1861 en esta ciudad rusa. El cuaderno inédito, que se conserva en la Universidad
de San Petersburgo, se publica en su integridad como anexo a este artículo. Su contenido
se clasifica en cinco categorías: 4 anécdotas lingüísticas, 4 sobre cadíes, árbitros y
gobernadores, 3 con adivinanzas lingüísticas, 2 de contenido mágico y 10 escritas por el
autor alrededor de un refrán. Se resume cada una y se resaltan sus particularidades lingüísticas
y folclóricas como parte del legado literario popular árabe. Se concluye que el cuaderno
forma parte del patrimonio cultural popular árabe y egipcio y su contenido es un material
docente de primer orden para las aulas y para el estudio de la variedad lingüística de
Egipto en el siglo XIX.This paper analyses the notebook written by hand by al-Šay j Muhammad 'Ayyād al-Tantāwī when he emigrated to Saint Petersburg in 1840 to teach classical and
dialectal Arabic to the future Russian Orientalists. He would die there in 1861. The notebook,
part of the collection held by Saint Petersburg University, is being edited and published
for the first time. It consists of a series of anecdotes that can be divided into five cat egories:
linguistic anecdotes (4), anecdotes about cadis, arbiters and governors (4), anecdotes
with linguistic riddles (3), anecdotes about magic events (2), anecdotes written by
the author about popular sayings and verses (10). The paper summarizes each anecdote
and highlights its linguistic and folkloric content as part of the Arabic literary legacy. It
concludes that the notebook forms part of Arabic and Egyptian popular cultural heritage
and contains excellent material to be taught in universities and studied by researchers who
wish to learn more about Egyptian linguistic variety in the nineteenth century
Particle image velocimetry measurements in the wake of a cactus-shaped cylinder
No full textThe flow field past a biologically inspired cylindrical model with a cactus-shaped cross section is investigated in a wind tunnel using particle image velocimetry and surface pressure measurements at a biologically relevant Reynolds number of ∼ 2 105. For the cactus model, the mean streamwise flow heals faster in its immediate wake, the wake turbulent velocity level is lower, and the surface static pressure has better recovery compared to the circular cylinder model. © 2011 American Society of Mechanical Engineers.Amitay M, 1998, 36 AER SCI M EXH REN; Babu P, 2008, PHYS FLUIDS, V20, DOI 10.1063-1.2887982; BEARMAN PW, 1993, AIAA J, V31, P1753, DOI 10.2514-3.11844; CANTWELL B, 1983, J FLUID MECH, V136, P321, DOI 10.1017-S0022112083002189; Djeridi H, 2003, FLOW TURBUL COMBUST, V71, P19, DOI 10.1023-B:APPL.0000014930.49408.53; GELLER GN, 1984, PHOTOSYNTHETICA, V18, P482; Han D, 2003, COMBUST FLAME, V132, P565, DOI 10.1016-S0010-2180(02)00515-1; Kwon K, 1996, PHYS FLUIDS, V8, P479, DOI 10.1063-1.868801; LIM HC, 2002, AIAA J, V40, P2027, DOI 10.2514-2.1535; Ong L, 1996, EXP FLUIDS, V20, P441, DOI 10.1007-BF00189383; Owen JC, 2001, J FLUID STRUCT, V15, P597, DOI 10.1006-jfls.2000.0358; Talley S., 2001, EXPT COMPUTATIONAL I; Tu J, 2005, 43 AIAA AER SCI M EX; Walther J. H., 2002, Journal of Turbulence, V3, DOI 10.1088-1468-5248-3-1-039; Williamson CHK, 1996, ANNU REV FLUID MECH, V28, P477, DOI 10.1146-annurev.fl.28.010196.002401; You D, 2007, PHYS FLUIDS, V19, DOI 10.1063-1.275657833
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