dataesr/scientific-paragraphs-categorization huggingface dataset:
Determination of anthropogenic emission ratios of urban terpenoids The anthropogenic emission ratios (ER) of urban terpenoids versus seven anthropogenic tracers (ethyne, ethylene, propene, benzene and toluene, CO and NOx) were estimated from ambient data. As for ERtraffic in the previous section, the anthropogenic ERs are derived from the slope of a linear least square regression fit as described in  Borbon et al. , 2013. Here, the data have been first carefully examined in order to exclude the effects of biogenic emissions of terpenoids and the daytime and nighttime chemistry on the distribution of the scatterplots (see sections 4. 1 and 4. 2). The selected AVOC tracers were discussed previously  (Borbon et al. , 2018).
, 2016). As a consequence, a nighttime temporal filter has been applied to the summertime observations due to the lack of biogenic isoprene emissions and the Athens and São Paulo wintertime dataset (figure  5c  and 5d ). In winter, the effect of biogenic emissions is negligible, and no filter is applied (Figure  5b ). For monoterpenes, different patterns are depicted (Figure  6 ). Camphene and limonene in Beirut behave similarly to isoprene in summer. Other monoterpenes (pinenes), total monoterpenes (Paris), p-cymene, and 3-carene (Ha Noi) significantly correlate with anthropogenic tracers during the day and night, either during both seasons or in winter. In Beirut, an additional meteorological filter has been applied, as illustrated in Figure  2 , by retaining observations under oceanic wind regime in winter.
Accepted Article This article is protected by copyright. All rights reserved. The effect of daytime OH photochemistry and nighttime chemistry is investigated by looking at the daytime over nighttime average concentrations versus kOH kinetic constants and the nighttime R 2 versus kO3 and kNO3 following de  Gouw et al. (2018). Those effects are investigated in two contrasting urban environments, Paris and Beirut, regarding emissions, emission policies and meteorology and for which a full-detailed description of the VOC dataset is available  (Borbon et al. , 2013; Salameh et al. , 2017 ) (Figure  7  and 8 ). We also report the data from Athens as described in  Panopoulou et al. (2020)  in Figure  8. In winter, the day-to-night ratios are usually higher than 1 and are independent of kOH, suggesting that the effect of photochemistry can be neglected even for the most reactive compounds like alkenes and terpenoids (Figure  7 ).
Spatial variability of anthropogenic ER of urban terpenoids The estimated anthropogenic emission ratios of terpenoids worldwide are compared in Figure  9  for isoprene (figure  9A ) and the two commonly measured terpenes in DATAbASE : -pinene and limonene (figure  9B  and C ). The anthropogenic emission ratios follow the same trend along with the tracer and are in the same range of values for all terpenoids: the range of variability at the global scale span one order of magnitude and sometimes more when including the literature for CO (figure  9A ). The emission ratio of isoprene-to-NOx is much less scattered, probably reflecting the single traffic origin of isoprene and NOx regardless of the urban area. In midlatitude regions (Paris, London), the wintertime emission ratio is usually higher than the summertime one, while in Mediterranean or subtropical regions (Beirut, São Paulo), the emission ratios do not show any seasonal cycle.
Emission inventory and emission calculation The evaluation is carried out at both national (country level) and urban scales. Indeed, the relative importance of BVOC emissions compared to AVOC emissions is scale-dependent. France, Lebanon, and Vietnam have been selected to illustrate countries of Northern, Mediterranean, and subtropical latitudes, and they also offer a detailed in-situ dataset (see previous section). The French city of Paris is selected to represent the ERs determined at the city level. We also assume that the ERs determined at the city level represent the whole country. When comparing the worldwide isoprene and monoterpene ERs from figure  9 , their spatial variability spans one order of magnitude at the global scale. As a consequence, the error propagation from the extrapolation of urban ER to country-level will not exceed a factor of 10.
Accepted Article This article is protected by copyright. All rights reserved. including other chemical VOC functions: this is the case, for instance, for alkenes and alkynes in CAMS. The methodology for the construction of the regional anthropogenic emission database by AIRPARIF has been already decribed in  Borbon et al. (2013). In CAMS-GLOB-ANT_v4. 2, emissions are provided for the main pollutants and greenhouse gases, together with speciation of non-methane VOCs from  Huang et al. (2017). Emissions are provided for 12 anthropogenic sectors, depending on the species. Some sectors have been excluded for the calculation: ships, agricultural activities and solid waste and waste water. The spatial resolution of the inventory is 0. 1x0. 1 degree. The global emissions have been obtained from the ECCAD emissions database (https://permalink.
Conclusion and implications The re-analysis of different VOC observations collected over the last decade has shown the systematic presence of anthropogenic isoprene and monoterpenes in cities worldwide and also recently demonstrated in Delhi, India  (Bryant et al. , 2023). Here we show that monoterpenes, as well as isoprene, are potentially emitted at the exhaust of fossil fuel vehicles by re-examining the DATAbASE dataset and the literature and by collecting new observations in the developing world (Vietnam). However, these results are modulated in northern mid-latitudes by the recent evidence of co-emitted personal care products won by car passengers in Northern US cities. The traffic-related fraction of monoterpenes can be significant (up to 40% of the observed levels) but is strongly space-dependent.
Details on the DATAbASE observations collected in urban atmosphere 21698996, ja, Downloaded from https://agupubs. onlinelibrary. wiley. com/doi/10. 1029/2022JD037566 by Portail BibCNRS INSU, Wiley Online Library on [15/03/2023]. See the Terms and Conditions (https://onlinelibrary. wiley. com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License.
Details on the DATAbASE observation collected in the urban atmosphere 21698996, ja, Downloaded from https://agupubs. onlinelibrary. wiley. com/doi/10. 1029/2022JD037566 by Portail BibCNRS INSU, Wiley Online Library on [15/03/2023]. See the Terms and Conditions (https://onlinelibrary. wiley. com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License.
Acknowledgments: This work was supported by the  French National program LEFE ("Les Enveloppes Fluides et l'Environnement »). The authors acknowledge the ECCAD portal for the archiving and distribution of the data (https://eccad. aeris-data. fr/). E. Liakakou  and  A. Panopoulou  acknowledge the  PANACE  project ( MIS 5021516 ), which is implemented under the Action " Reinforcement of the Research and Innovation Infrastructure ", funded by the  Operational Programme "Competitiveness, Entrepreneurship and Innovation"  ( NSRF 2014-2020 ) and cofinanced by Greece and the  European Regional Development Fund. P. Dominutti  and  J. Hopkins  thank the  NERC-UKRI   Research Grant   NE/P014771/1. P. Dominutti ,  T. Nogueira ,  T. Corrêa do Santos  and  A. Fornaro  acknowledge the  São Paulo State Research Foundation  ( FAPESP  Grant no.
18/07848-9 ,  16/18438-0  and  17/50278-6 ) and the postgraduation program in Meteorology ( IAG-USP ). We are also grateful to the master students  S. Bennoui  and  J. Plaisant  for their contribution to some of the re-analysis of VOC datasets and all the people 21698996, ja, Downloaded from https://agupubs. onlinelibrary. wiley. com/doi/10. 1029/2022JD037566by  Portail BibCNRS INSU, Wiley Online Library on  [ 15/03/2023 ]. See the Terms and Conditions (https://onlinelibrary. wiley. com/terms-and-conditions)on  Wiley Online Library  for rules of use; OA articles are governed by the applicable Creative Commons License Accepted Article This article is protected by copyright. All rights reserved. involved in the VOC field experiments:  W. Aït-Helal ,  L. Bouvier ,  B. Cetin ,  C. Gaimoz ,  J, Gilman ,  J.
Locations of field campaigns used for data re-analysis (in white characters) or reported by published studies (blue and green characters). References highlighted in blue have reported an anthropogenic origin for isoprene. References highlighted in green have reported an anthropogenic origin of monoterpenes. Figures show the mean concentrations in pbb of VOCs measured at some of these locations from the DATAbASE datasets (Los Angeles -2010, Figures Figure 1: Paris 2009/2010, Beijing 2007, São Paulo -2013, Adidjan -2016, Beirut -2011/2012). Anthropogenic VOC are in grey: Et (Ethylene) Pr (propene) Ac (acetylene) Be (benzene) To (toluene). Terpenoids are in green: Is (isoprene) aP (-pinene) bP (β-pinene) Ca (camphene) Li (limonene) mz stands for m/z 137 (sum of monoterpenes measured by PTRMS), My (myrcene), pCym (p-cymene), 3Car (3-carene), 1,8Cin (1,8-cineole).
Acknowledgments Yves Pomeau  is acknowledged for enlightening discussion on the dynamical saddle-node bifurcation. I am grateful to  Grisha Sivashinsky  for drawing my attention few years ago on the work of Joulin and  Deshaies. I thank  Misha Liberman  for fruitful discussions on DDT and comments on the manuscript. I thank also  Professors Bruno Denet ,  Guido Lodato ,  Luc Vervisch  and the Phd students  Raúl Hernández-Sánchez  and  Hassan Tofaili  for lively interactions during their numerical activities. Partial financial support of  Agence National de la Recherche  (contract  ANR-18-CE05-0030 ) is acknowledged.
Introduction Buildings are the largest energy-consuming sector in the world, accounting for over one-third of total final energy consumption, the majority of which is consumed for space heating and cooling, along with water heating, which are estimated to account for nearly 60% of global energy consumption in buildings  [1]. This share increases to about 79% in the European Union (EU) for space and water heating only (Odyssee database as cited in  [2] ). On current trends, energy needs for space cooling, almost entirely as electricity, will more than triple between 2016 and 2050, driven mainly by the residential sector  [3]. According to the British Petroleum (bp) Statistical Review of World Energy in 2021, more than 84% of the world's primary energy consumption is still generated from fossil fuels (oil, natural gas, and coal)  [4].
The recording of all measurements was performed by a data acquisition system (Keithley 3706A), and data were recorded every 20 min. For the purpose of this paper, only the temperature measurements of the air and wall of the pipe are needed. Velocity and pressure of air flow were also measured at different locations in the pipe. It is assumed that there is a negligible effect of temperature and humidity on the mechanical characteristics of the flow and that they remain constant in the given configuration. Thus, velocity and pressure measurements were performed once. Testo 435-4 device was used to make the measurements using its fan anemometer (Vane measuring probe 0635 9435) and differential pressure measuring pitot tube (model number: 0635 2145). The pressure was measured at the inlet, then just after the inlet air filter, then before the outlet fan, and at the outlet using small holes in the pipe.
Analysis Period From the database of the recorded humidity and temperature measurements in the system, the measurements of the year 2018 are chosen for the analyses. Figure  3  shows the temperature measured at the inlet and outlet of the pipe during the heating period in the coldest week of 2018 (25 February to 3 March). The graph shows how the air is heated inside the pipe where it shows the temperature increase between the inlet and the outlet where the difference reached around 8 • C on some days. The variation in the inlet and outlet temperatures also shows how the EAHE stabilizes air temperature variations which is strongly required when heating a building. The outlet air temperature exceeds the value of the wall temperature at some times (e. g. , on 03/2 00:00) because the wall temperature value is an average of three measured values along the pipe, as explained in Section 3.
Analysis Period From the database of the recorded humidity and temperature measurements in the system, the measurements of the year 2018 are chosen for the analyses. Figure  3  shows the temperature measured at the inlet and outlet of the pipe during the heating period in the coldest week of 2018 (25 February to 3 March). The graph shows how the air is heated inside the pipe where it shows the temperature increase between the inlet and the outlet where the difference reached around 8 °C on some days. The variation in the inlet and outlet temperatures also shows how the EAHE stabilizes air temperature variations which is strongly required when heating a building. The outlet air temperature exceeds the value of the wall temperature at some times (e. g. , on 03/2 00:00) because the wall temperature value is an average of three measured values along the pipe, as explained in Section 3.
Dans le cadre du projet TOP « Trajectories of agrO-Pastoral systems in mountains: land management adaptations to climate, ecological and socio-economic changes » (https://anr. fr/Projet-ANR-20-CE32-0002) financé par l'Il est donc nécessaire de mobiliser au maximum les observations disponibles pour documenter l'évolution de la pression exercée sur les écosystèmes de montagne et comprendre leur évolution. L'objectif de ce travail est donc de quantifier l'apport en termes de revisite des images historiques SPOT 1-5 sur les régions montagneuses françaises de 1986 à 2015. Ce travail se limite à la collection Theia, c'est-à-dire aux produits disponibles au niveau 1C (ortho-rectifiés) qui sont adaptés aux analyses impliquant le traitement massif de séries temporelles, contrairement aux produits au niveau 1A.
Remerciements Les auteurs tiennent à remercier l' Agence Universitaire de la Francophonie (AUF) ,  l'Agence de l'Environnement et de la Maîtrise de l'Energie (ADEME) ,  ainsi que le Ministère des Affaires Etrangères  (via  le programme ECONET)  pour leurs soutiens financiers.
Il faut aussi noter l'ensemble des travaux effectués sur la solvatation des protéines, décrivant une organisation du solvant en jusqu'à six coquilles successives autour des protéines, définissant ainsi la forme de la protéine, ce qui lui confère sa fonction. La spectroscopie THz d'échantillons liquides offre de nombreuses perspectives pour mieux comprendre les effets intermoléculaires au cours    [3]. Les positions des raies en fréquence correspondent à celles prédites par la théorie, renseignées dans la base de données du Jet Propulsion Laboratory (JPL). DOSSIER de réactions chimiques. Enfin, l'étude de l'eau elle-même reste un challenge dans la gamme THz et plusieurs groupes travaillent à la détermination d'un modèle analytique de l'eau, car à l'heure actuelle seuls des modèles numériques permettent de prévoir sa réponse.
Pour ce qui est de la prévision, le modèle saisonnier a été le plus efficace, avec une erreur de 3. 26 10 5 kWh. Abstract -A study was carried out on the monthly power consumption in Togo. Four (4) parametric models were build using, the power consumption, the temperature and the relative humidity as parameters. A detailed study was carried out using a database ranging from 2001 to 2005 to enable them evaluate different models. The ARX models turned out to be the most indicated for an identification goal, with a quadratic error which represents 1 % of the minimum monthly consumption during that period. The seasonal models proved to be the most reliable for the consumption prevision during the years 2004 and 2005, with an error of 0. 326 GWh. Mots clés: Energie électrique -Modèles sinusoïdaux.
VALIDATION La validation des modèles a été conduite dans deux directions: 1. L'indentification au sens où la totalité de la base de données (60 points) a été utilisée pour le calcul des paramètres des différents modèles, 2. La simulation au sens où seuls 36 des 60 points ont été utilisés pour le calcul des paramètres des différents modèles. Leur efficacité a été mesurée sur les 24 autres points correspondant aux deux dernières années de la base.
Prédiction La prédiction a porté sur les deux dernières années de la base. L'élaboration des modèles (choix de la structure optimale, calcul de la dispersion de l'erreur) a été effectuée conformément aux procédures décrites précédemment. Les coefficients des différents modèles sont reportés dans le Tableau A. 2 en annexe. Des trois modèles A, B et C, le B reste le meilleur, si l'on se refaire aux erreurs calculées sur les échantillons bootstrappés. On note un niveau de dispersion de l'erreur de l'ordre de 1 (Tableau 4), avec toutefois un niveau d'erreur moyenne 2 fois plus élevé que dans le cas de la phase de prédiction. Le modèle B est également celui pour lequel l'erreur quadratique est la plus faible, si l'on se réfère à notre base de donnée uniquement. Cette erreur se situe autour de 3×10 5 kWh, elle est en ordre de grandeur trois plus élevée que celles obtenues lors de la phase d'identification.
L'efficacité de l'ensemble des modèles est en retrait, ceci se traduit par un coefficient de corrélation maximum de l'ordre de 50 % pour le modèle B (Tableau 5). Les faibles niveaux de corrélation reflètent notamment l'incapacité des modèles à reproduire certains aspects 'non périodiques' de la consommation lors des années 2004 et 2005. Le pic de consommation électrique de Décembre 2004 (Mois N°48 Fig. 6 ) illustre parfaitement cette situation. Car en effet, dans toute la base de données, cette situation ne survient qu'au mois de Décembre 2002. Cette situation étant peu représentative des situations observées au cours des 5 ans, aucun des modèles mis au point sur la base de données minimales n'arrive à la reproduire.
Mass spectrum A Waters Q-T of Ultima API mass spectrometer with an electrospray ionisation source (ESI) in positive mode was used for HRMS measurement. The capillary, cone and Rf lens potentials were set to 3 kV, 35 and 40 V, respectively. The source and desolvation temperature were set to 100 and 120°C and the collision energy was 10 eV in TOF-MS mode. Analyses were monitored with MassLynx 4. 0 software. To measure the exact mass of the catanionic associations, the spectrometer was calibrated with H 3 PO 4 clusters.
Gravimetric measurements The gravimetric measurements corroborate the electrochemical results. The inhibitor efficiency, IE(%), was also estimated from weight loss measurements using the relation (1): ( ) inh % 100 WW IE W - = (1) where W and W inh are rate of corrosion (g•cm -2 h -1 ) with and without inhibitor, respectively. Corresponding data are given in Table  2 , for immersion period of 7 days. Figure  5  represents the data of weight loss time curves for the system involving inhibitor or not. The samples of zinc were immersed in 3 solutions of 3% NaCl each one contains a different molecule. After 7 days of immersion, we calculated and plotted the curves of mass loss. The results of gravimetric measurements are shown in Figure  5. Figure  5  show that there is a slight decrease of the mass of zinc in the solution (3) (3% NaCl+(1,7-lactobionamidoheptanoic acid (L6)+2-aminobenzimidazole) compared to the other solutions (1) (3% NaCl) and (2) (3% NaCl+1,7-lactobionamidoheptanoic acid (L6)).
To determine the efficiency of these inhibitors, we calculated the corrosion rate in 3% NaCl solution. Corresponding data are given in Table  2. The inhibitors efficiency was estimated to be 89% for inhibitor (bolaform+2aminobenzimidazole: (B+Bz)) and 25% for inhibitor bolaform. Thus, we deduce that the inhibitor (B+Bz) has a better efficiency compared to the other inhibitor.
Retour d'expérience du projet étudiants 2 Il est intéressant de voir que ce projet a permis aux étudiantes de découvrir des logiciels industriels utilisés dans le secteur de l'automatisme et les JN. De plus, le fait qu'une des étudiantes ait effectué, suite à ce projet, son Projet de Fin d'Etude (PFE) ingénieur chez Hub Performance, le fournisseur de Emulate3D, et ensuite été embauchée en tant que « Digital Twin Simulation and Controls Testing Engineer » chez Hub Performance montre l'importance de ce projet pour sa formation professionnelle. Il est également intéressant de noter que ce projet a permis de construire un dataset de comportement défaillant du SAP qui a été utilisé pour le développement de l'approche de diagnostic à base de Machine Learning de SAP au sein du CReSTIC. Enfin, Cette expérience permet d'envisager d'utiliser les projets sur les JN en vue de faire de la formation en maintenance de processus industriels.
Cet article décrit notre expérience de l'utilisation du logiciel Emulate3D pour l'enseignement de l'industrie 4. 0 auprès de futurs ingénieurs. Nous avons constaté que l'utilisation du JN permettait d'améliorer significativement la compréhension des processus industriels et offre une représentation virtuelle précise de l'équipement ou du système étudié, permettant aux étudiants d'observer son fonctionnement en temps réel et de mieux appréhender les interactions entre les différents composants. Le JN offre ainsi aux futurs ingénieurs une expérience pratique et immersive de l'industrie 4. 0, renforçant ainsi leur compréhension des enjeux et des défis de ce secteur en constante évolution. RemerciementLes travaux présentés ont été réalisés dans le cadre du projet DeMETeRE (Déploiement de Micro-Environnements Territoriaux pour la Réussite Etudiante), lauréat du PIA4 DemoES (Démonstrateur de l'Enseignement Supérieur) et financé au titre du plan France 2030 (ANR-21-DMES-0011).
II. APPLICATIONS AU LABORATOIRE DE RECHERCHE-TRAVAUX PRATIQUES Le retour d'expérience des années précédentes des étudiants en 2ème année de master sciences et génie des matériaux, sur le module analyse et traitement de signal (15 heures de cours, 6 heurs de travaux dirigés et 6 heures de travaux pratiques pour un total de 4 crédits) a révélé plusieurs points susceptibles d'être améliorés dans la pratique de leur enseignement. Auparavant, des codes textes implémentés dans Matlab étaient utilisés pour obtenir des signaux à partir de l'oscilloscope et les analyser. La pratique a montré que leur maîtrise et leur utilisation "à la volée" est difficile pour certains étudiants. Le degré d'interactivité de l'acquisition, du traitement et de la présentation des signaux s'est également avéré insuffisant.
Ces méthodes de description/découverte sont utilisées pour améliorer la compréhension d'un phénomène observé et générer de nouvelles connaissances à partir d'une base de données Ces méthodes de regroupement visent à identifier des groupes homogènes d'individus appelés grappes dans une base de données La procédure est un processus qui détecte des sous-groupes de populations présentant des caractéristiques différentes selon les variables ciblées dans l'analyse Les individus (ou observations) d'une grappe spécifique partagent des caractéristiques similaires, mais sont différents de ceux n'appartenant pas à cette grappe En pratique, l'analyse par regroupe- ment permet de réaliser des profils à partir d'une base de données afin d'iden- tifier la dynamique des variables reflétant les caractéristiques importantes à chacune des sous-populations Pré-traitement des données Tableau 5.