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Published: 14 March 2023

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1

E, Farin Gerald, and Dagstuhl Seminar on Geometric Modelling (3rd : 1996 Dagstuhl, Wadern, Germany), eds. Geometric modelling: Dagstuhl 1996. Wien, Austria: Springer-Verlag, 1998.

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2

Granger, P. Past and present in DeNOx catalysis: From molecular modelling to chemical engineering. Amsterdam: Elsevier, 2007.

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3

R, Cox D., Hinkley D. V, Reid N, and Snell E. J, eds. Statistical theory and modelling: In honour of Sir David Cox, FRS. London: Chapman and Hall, 1991.

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4

1970-, Sportisse Bruno, ed. Air pollution modelling and simulation: Proceedings : Second Conference on Air Pollution Modelling and Simulation, APMS'01, Champs-sur-Marne, April 9-12, 2001. Berlin: Springer, 2002.

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5

Modelling the human impact on nature: Systems analysis of environmental problems. Oxford: Oxford University Press, 1993.

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6

Saarelainen, Seppo. Modelling frost heaving and frost penetration in soils at some observation sites in Finland: The SSR model. Espoo [Finland]: Technical Research Centre of Finland, 1992.

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7

International, Conference on Geotechnical Centrifuge Modelling (1988 Paris France). Centrifuge 88 : proceedings of the International Conference on Geotechnical Centrifuge Modelling/Paris/25-27 April 1988 =: Centrifugeuse 88 : comptes rendus du Congrès international sur la modélisation géotechnique en centrifugeuse/Paris/25-27 Avril 1988. Rotterdam: Balkema, 1988.

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8

Canadian Symposium on Remote Sensing (16th 1993 Sherbrooke, Quebec). La télédétection : un outil pour la modélisation et la gestion des changements environnementaux, 16e Symposium canadien sur la télédétection, 8e Congrès de l'Association québécoise de télédétection =: Remote sensing : a tool for modelling and managing environmental changes, 16th Canadian Symposium on Remote Sensing. Edited by Gagnon Paul 1945-, O'Neill Norman Thomas 1952-, Association québécoise de télédétection. Congrès, Canadian Remote Sensing Society, Université de Sherbrooke. Centre d'applications et de recherches en télédétection., Société canadienne de télédétection, and Symposium canadien sur la télédétection (16e : 1993 : Sherbrooke, Québec). Sherbrooke, Qué: Centre d'applications et de recherches en télédétection, 1993.

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9

Creedy, John. Fiscal policy and social welfare: An analysis of alternative tax and transfer systems. Cheltenham, UK: E. Elgar, 1996.

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10

Chemical Modelling Spr Chemical Modelling Rsc. Royal Society of Chemistry, 2006.

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11

Chemical Modelling Spr Chemical Modelling Rsc. Royal Society of Chemistry, 2004.

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12

Laurent, Julien, Randal Samstag, Jim Wicks, and Ingmar Nopens, eds. CFD Modelling for Wastewater Treatment Processes. IWA Publishing, 2022. http://dx.doi.org/10.2166/9781780409030.

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Abstract This Scientific and Technical Report (STR) provides in-depth fundamentals and guidelines regarding Computational Fluid Dynamics (CFD) simulations of Water Resources Recovery Facilities (WRRFs) unit processes (e.g. headworks, aerobic and anaerobic biological reactors, settling tanks, disinfection). Each unit process is described with respect to: Literature review and process descriptionRelevant CFD concepts and modelling approachCase studiesFuture research needs CFD Modelling for Wastewater Treatment Processes also opens the discussion on two fundamental topics: experimental validation of CFD simulations, and the complementarity between CFD and Chemical Reaction Engineering approaches. This book is intended for undergraduate and graduate students majoring in fields related to wastewater treatment and/or fluid mechanics, as well as researchers and engineers who conduct research and practices in modelling such unit processes. Water resource recovery modelling is not just about lab-scale processes. Now and in the future it is about improving our understanding of (and designing better) full-scale facilities!

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13

Powell. Website to Accompany the Art of Modelling with Spr Eadsheets. John Wiley & Sons Inc, 2003.

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14

Hinkley, D. V., and N. Reid. Statistical Theory and Modelling: In Honour of Sir David Cox Frs. Chapman & Hall, 1991.

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15

(Editor), Gerald Farin, Hanspeter Bieri (Editor), Guido Brunnett (Editor), and Tony De Rose (Editor), eds. Geometric Modelling : Dagstuhl 1996 (Computing Supplementum, No 13). Springer, 1999.

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16

Jaakkola, H. Advances in Information Modelling and Knowledge Bases (Frontiers in Artificial Intelligence and Applications Ser). Ios Pr Inc, 1990.

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17

Faust, Lisa J., Claudine André, Raphaël Belais, Fanny Minesi, Zjef Pereboom, Kerri Rodriguez, and Brian Hare. Bonobo population dynamics: Past patterns and future predictions for the Lola ya Bonobo population using demographic modelling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198728511.003.0018.

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Wildlife sanctuaries rescue, rehabilitate, reintroduce and provide life-long care for orphaned and injured animals. Understanding a sanctuary’s population dynamics—patterns in arrival, mortality and projected changes in population size—allows careful planning for future needs. Building on previous work on the population dynamics of chimpanzees (Pan troglodytes) in sanctuaries of the Pan African Sanctuary Alliance (PASA; Faust et al. 2011), this chapter extends analyses to the only PASA bonobo sanctuary. Its authors analysed historic demographic patterns and projected future population dynamics using an individual-based demographic model. The population has been growing at 6.7 per cent per year, driven by arrivals of new individuals (mean = 5.5 arrivals per year). Several model scenarios projecting varying arrival rates, releases and breeding scenarios clarify potential future growth trajectories for the sanctuary. This research illustrates how data on historic dynamics can be modelled to inform future sanctuary capacity and management needs. Les sanctuaires de faune secourent, réhabilitent, réintroduisent, et fournissent des soins pour toute la vie aux animaux orphelins et blessés. Comprendre les dynamiques de la population d’un sanctuaire—les motifs d’arrivée, mortalité, et de changements projetés de la taille de la population—permet une planification prudente pour les nécessités du futur. En se basant sur le travail déjà fait sur les dynamiques de la population chimpanzé (Pan troglodytes) dans les sanctuaires du Pan African Sanctuary Alliance (PASA; Faust et al. 2011), nous étendons notre analyse au seul sanctuaire bonobo par PASA. Nous avons analysé les motifs démographiques historiques et avons projeté les futures dynamiques de la population en utilisant un modèle démographique basé sur l’individu. La population augmente de 6.7 per cent par an, poussée par l’arrivée de nouveaux individus (moyenne = 5.5 arrivées par an). Plusieurs scénarios modèles montrent une trajectoire de potentielle croissance pour le sanctuaire. Cette recherche illustre comment modeler les données sur les dynamiques historiques pour informer la capacité future du sanctuaire et les besoins gestionnaires.

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18

Varotsos, Costas A., and Arthur P. Cracknell. Understanding Global Climate Change: Modelling the Climatic System and Human Impacts. Taylor & Francis Group, 2021.

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19

Varotsos, Costas A., and Arthur P. Cracknell. Understanding Global Climate Change: Modelling the Climatic System and Human Impacts. Taylor & Francis Group, 2021.

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20

Varotsos, Costas A., and Arthur P. Cracknell. Understanding Global Climate Change: Modelling the Climatic System and Human Impacts. Taylor & Francis Group, 2021.

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21

Luc, Heres, ed. Time in GIS: Issues in spatio-temporal modelling. Nederlandse Commissie voor Geodesie, 2000. http://dx.doi.org/10.54419/v5m55p.

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Most Geographic Information Systems started as a substitute for loose paper maps. These paper maps did not have a built-in time dimension and could only represent history indirectly as a sequence of physically separate images. This was in fact imitated by these first generation systems. The time dimension could only be represented by means of separate files. A minority of Geographic Information Systems however, started their life as a substitute for ordered lists and tables with a link to paper maps. In these lists, the inclusion of a time com-ponent in the form of a data field was quite usual. This method too was copied by the systems that replaced these paper tables. The current trend in the development of Geographic Information Systems is towards the inte-gration of the classical map-oriented concepts with the table-oriented concepts. This often leads to the explicit embedding of the time component in the GIS environment. The Subcommission Geo-Information Models of the Netherlands Geodetic Commission has organized a workshop to discuss the theory and practice of time and history in GIS on 18 May 2000. This publication contains 6 articles prepared for the workshop. The first paper, written by Donna Peuquet, gives a bird’s-eye view of the current state of the art in spatio-temporal database technology and methodology. She is a well-known expert in the field of spatio-temporal information systems and the author of many articles in this field. The second article is written by Monica Wachowicz. She describes what you can do with a GIS once it contains a historical dimension and how you can detect changes in geographic phenomena. Furthermore, her article suggests how geographic visualisation and knowledge discovery techniques can be integrated in a spatio-temporal database. How to record the time dimension in a database is one thing, how to show this dimension to users is another one. In his contribution, Menno-Jan Kraak first tells about the techniques, which were used in the age of paper maps and the limitations these methods had. He goes on to explain what kind of cartographic techniques have been developed since the mass introduc-tion of the computer. Finally he describes the powerful animation methods which currently exist and can be used on CD-ROM and Internet applications. Peter van Oosterom describes how the time dimension is represented in the information sys-tems of the Cadastre and how this is used to publish updates. The Cadastre has a very long tradition in incorporating the time component, which has always been an inherent component of the cadastral registration. In former times this was translated in very precise procedures about how to update the paper maps and registers. Today it is translated in spatio-temporal database design. The article of Luc Heres tells about the time component in the National Road Database, origi-nally designed for traffic accident registration. This is one of the systems with ''table'' roots and with quite a long tradition in handling the time dimension. He elucidates first the core objects in the conceptual model and how time is added. Next, how this model is translated in a logical design and finally how this is technically implemented. Geologists and geophysicians also have a respectable tradition in handling the time dimension in the data they collect. This is illustrated in the last paper, which is written by Ipo Ritsema. He outlines how time is handled in geological and geophysical databases maintained by TNO. By means of some practical cases he illustrates which problems can be encountered and how these can be solved.

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22

(Editor), Pascal Granger, and Vasile Pârvulescu (Editor), eds. Past and Present in DeNOx Catalysis: From Molecular Modelling to Chemical Engineering, Volume 171 (Studies in Surface Science and Catalysis) (Studies in Surface Science and Catalysis). Elsevier Science, 2007.

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23

Rejection of Emerging Organic Contaminants by Nanofiltration and Reverse Osmosis Membranes: Effects of Fouling, Modelling and Water Reuse. Taylor & Francis Group, 2010.

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24

Quintanilla, Victor Augusto Yangali. Rejection of Emerging Organic Contaminants by Nanofiltration and Reverse Osmosis Membranes: Effects of Fouling, Modelling and Water Reuse. Taylor & Francis Group, 2017.

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