scholarly journals Simulation modeling of phytoplankton dynamics in a large eutrophic river, Hungary — Danubian Phytoplankton Growth Model (DPGM)

Biologia ◽  
2012 ◽  
Vol 67 (2) ◽  
Author(s):  
Csaba Sipkay ◽  
Tihamér Kiss-Keve ◽  
Csaba Vadadi-Fülöp ◽  
Réka Homoródi ◽  
Levente Hufnagel
Keyword(s):  
Growth Model ◽  
Environmental Sustainability ◽  
Simulated Data ◽  
Phytoplankton Growth ◽  
Danube River ◽  
Total Biomass ◽  
Large Set ◽  
Linear Temperature ◽  
Strategic Model ◽  
Complex Models

AbstractEcological models have often been used in order to answer questions that are in the limelight of recent researches such as the possible effects of climate change. The methodology of tactical models is a very useful tool comparison to those complex models requiring relatively large set of input parameters. In this study, a theoretical strategic model (TEGM) was adapted to the field data on the basis of a 24-year long monitoring database of phytoplankton in the Danube River at the station of Göd, Hungary (at 1669 river kilometer - hereafter referred to as “rkm”). The Danubian Phytoplankton Growth Model (DPGM) is able to describe the seasonal dynamics of phytoplankton biomass (mg L−1) based on daily temperature, but takes the availability of light into consideration as well. In order to improve fitting, the 24-year long database was split in two parts in accordance with environmental sustainability. The period of 1979–1990 has a higher level of nutrient excess compared with that of the 1991–2002. The authors assume that, in the above-mentioned periods, phytoplankton responded to temperature in two different ways, thus two submodels were developed, DPGM-sA and DPGM-sB. Observed and simulated data correlated quite well. Findings suggest that linear temperature rise brings drastic change to phytoplankton only in case of high nutrient load and it is mostly realized through the increase of yearly total biomass.

The calibration of a phytoplankton growth model using batch culture data

1976 ◽  
Vol 5 (4) ◽  
pp. 431-442 ◽  
Author(s):  
Timoth C. Lederman ◽  
George M. Hornberger ◽  
Mahlon G. Kelly
Keyword(s):  
Batch Culture ◽  
Growth Model ◽  
Phytoplankton Growth

scholarly journals Evaluation of forest fire models on a large observation database

2014 ◽  
Vol 2 (5) ◽  
pp. 3219-3249 ◽  
Author(s):  
J.-B. Filippi ◽  
V. Mallet ◽  
B. Nader
Keyword(s):  
Large Set ◽  
Limited Information ◽  
Propagation Models ◽  
Ignition Point ◽  
Fire Propagation ◽  
Simulation Performance ◽  
Velocity Models ◽  
Wide Range ◽  
Complex Models

Abstract. This paper presents the evaluation of several fire propagation models using a large set of observed fires. The observation base is composed of 80 Mediterranean fire cases of different sizes, which come with the limited information available in an operational context (burned surface and approximative ignition point). Simulations for all cases are carried out with 4 different front velocity models. The results are compared with several error scoring methods applied to each of the 320 simulations. All tasks are performed in a fully automated manner, with simulations ran as first guesses with no tuning for any of the models or cases. This approach leads a wide range of simulation performance, including some of the bad simulation results to be expected in an operational context. Regardless the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more empirical ones. Data and source code used for this paper are freely available to the community.

scholarly journals Automatic calibration of a functional-structural wheat model using an adaptive design and a metamodelling approach

2021 ◽  
Author(s):  
Emmanuelle Blanc ◽  
Jérôme Enjalbert ◽  
Pierre Barbillon
Keyword(s):  
Experimental Data ◽  
Gaussian Process ◽  
Adaptive Design ◽  
Computational Cost ◽  
Simulated Data ◽  
Calibration Method ◽  
Complex Models ◽  
Competition For Light ◽  
High Computational Cost

- Background and Aims Functional-structural plant models are increasingly being used by plant scientists to address a wide variety of questions. However, the calibration of these complex models is often challenging, mainly because of their high computational cost. In this paper, we applied an automatic method to the calibration of WALTer: a functional-structural wheat model that simulates the plasticity of tillering in response to competition for light. - Methods We used a Bayesian calibration method to estimate the values of 5 parameters of the WALTer model by fitting the model outputs to tillering dynamics data. The method presented in this paper is based on the Efficient Global Optimisation algorithm. It involves the use of Gaussian process metamodels to generate fast approximations of the model outputs. To account for the uncertainty associated with the metamodels approximations, an adaptive design was used. The efficacy of the method was first assessed using simulated data. The calibration was then applied to experimental data. - Key Results The method presented here performed well on both simulated and experimental data. In particular, the use of an adaptive design proved to be a very efficient method to improve the quality of the metamodels predictions, especially by reducing the uncertainty in areas of the parameter space that were of interest for the fitting. Moreover, we showed the necessity to have a diversity of field data in order to be able to calibrate the parameters. - Conclusions The method presented in this paper, based on an adaptive design and Gaussian process metamodels, is an efficient approach for the calibration of WALTer and could be of interest for the calibration of other functional-structural plant models .

Changes in the Strategic Internal Control of Companies under Crisis Pressure

2021 ◽  
Vol 15 (37) ◽  
Author(s):  
Lyudmila Mihaylova ◽  
Emil Papazov
Keyword(s):  
Internal Control ◽  
Environmental Sustainability ◽  
Business Processes ◽  
Manufacturing Sector ◽  
Research Question ◽  
Control Environment ◽  
Competitive Advantages ◽  
Online Sales ◽  
Strategic Model ◽  
The Impact

Purpose of the article: The article aims at presenting and analysing key changes in the strategic internal control of companies under the pressure of crisis phenomena. The research question is how to adapt the strategic internal control to an evolving crisis through inclusion of control environmental sustainability measures, and strategic model adaptation.Methodology: A qualitative approach has been applied along with the research of larger companies from the brewery sector and small-and medium sized enterprises from the knitted fabrics manufacturing sector in Bulgaria. The study has also taken into consideration some companies’ strategic documents, as well as interviews with companies’ managers. The gathered information has been systematized, compared and evaluated with the help of the “Relative (Competitive) Advantage Matrix” model.Scientific aim: Understanding the impact of changes in strategic internal control on management under the pressure of crisis phenomena.Findings: The analysing of the quasi-control environment and competitive advantages is an important strategic management issue during crises. Competitive advantages derive mainly from the characteristics of the product (or service) that make it better than the products (or services) of competitors and they are associated with changes in the strategic internal control of companies under the pressure of hard times.Conclusions: Strategic internal control has to be adapted to the crisis situation through control environmental sustainability measures, strategic model adaptation and selected competitive advantages. Business processes are changing as a result of crisis times, then the control environment, risk assessments and competitive advantages need to be more detailed and analysed in different aspects. At the same time, the strategic internal control in hard times faces unexpected results, such as a drastic reduction in the incomes, a decrease in retail sales or a drastic increase in online sales. Using the collected information, comparisons can be made to better outline similarities and differences that will point out ways for improvement. This information should be brought to the attention of the personnel of the companies. The change in the activities should not be delayed in time, since information quickly becomes out-dated.

High Resolution Orientation Distribution Function

2011 ◽  
Vol 702-703 ◽  
pp. 536-539 ◽  
Author(s):  
Søren Schmidt ◽  
Nicolai Fog Gade-Nielsen ◽  
Martin Høstergaard ◽  
Bernd Dammann ◽  
Ivan G. Kazantsev
Keyword(s):  
Distribution Function ◽  
High Resolution ◽  
Orientation Distribution Function ◽  
Linear Equations ◽  
Simulated Data ◽  
Orientation Distribution ◽  
Large Set ◽  
Space Groups ◽  
Graphical Processing ◽  
Crystallographic Space Groups

A new method for reconstructing a High Resolution Orientation Distribution Function (HRODF) from X-ray diffraction data is presented. It is shown that the method is capable of accommodating very localized features, e.g. sharp peaks from recrystallized grains on a background of a texture component from the deformed material. The underlying mathematical formalism supports all crystallographic space groups and reduces the problem to solving a (large) set of linear equations. An implementation on multi-core CPUs and Graphical Processing Units (GPUs) is discussed along with an example on simulated data.

scholarly journals Towards the environmental sustainability assessment for the viticulture

2018 ◽  
Vol 49 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Lucia Recchia ◽  
Daniele Sarri ◽  
Marco Rimediotti ◽  
Paolo Boncinelli ◽  
Enrico Cini ◽  
...  
Keyword(s):  
Environmental Risk ◽  
Environmental Sustainability ◽  
Sustainability Assessment ◽  
Crop Protection ◽  
Risk Indicator ◽  
Large Set ◽  
Environmental Pressures ◽  
Simplified Approach ◽  
Wine Sector ◽  
Operative Indications

During the last decades in Italy the wine sector focused on the environmental sustainability of the production processes, including the agricultural, the agro-industrial and the packaging phases. Recent surveys highlighted that the wine consumers are interested in the environmental certifications, even if they are not familiar with them. Several environmental pressures can be evaluated in the viticulture phase, but an elevated number of the analysed impacts require the collection of a large set of input data and significant efforts during the elaboration phase. Therefore, the aim of the present work was the identification of the inventory data and impacts, which mainly describe the environmental pressures associated with the viticulture phase. Particularly, the results of the life cycle assessment (LCA) were integrated with those of a model and a simplified approach for evaluating the risks due to the pesticides use. The LCA identified three phases, which are responsible of 70-80% of the CO2eq (CO2 equivalent), the cumulated energy utilisation, the acidification potential (expressed in SO2 equivalent) and the eutrophication (expressed in PO4 equivalent), i.e. the harvesting, the crop protection and the ligature. The phase of the pesticides use was analysed also through the pesticides risk indicator (PERI) model and a simplified approach elaborated by the Regional Agency for the Environment Protection in Tuscany, Italy. Results concerning the environmental risk showed that the PERI model, the Arpat approach and the LCA were coherent for the pesticide mix highlighting that the associated environmental risk is more than doubled from 2004 to 2010. Finally, some operative indications were elaborated in order to reduce the impacts and improve the local and global environmental sustainability of the viticulture phase.

On-Line Estimation and Prediction of Urea Kinetics during Hemodialysis: A Simulation Approach

1995 ◽  
Vol 18 (5) ◽  
pp. 245-253 ◽  
Author(s):  
G. Comai ◽  
A. Cappello ◽  
F. Grandi ◽  
G. Avanzolini
Keyword(s):  
Simulated Data ◽  
Volume Ratio ◽  
Initial Distribution ◽  
Urea Concentration ◽  
Dialysis Session ◽  
Large Set ◽  
Simulation Approach ◽  
Urea Kinetics ◽  
Pool Model ◽  
On Line

A new method for the on-line estimation of urea kinetic parameters from blood urea concentration (BUN) continuously measured during a dialysis session is proposed. The method, based on the variable-volume double-pool model, is evaluated through a simulation approach in order to easily consider a large set of well-controlled test conditions. The model is characterized by six parameters, knowledge of which enables early prediction of the end dialysis urea concentration and the dose of dialysis. The sensitivity of the model predicted BUN with respect to the parameters was first analyzed to investigate which can be reliably estimated from blood urea measurements taken at a suitable rate. This analysis showed that the model predicted BUN is highly sensitive to the initial blood urea concentration and to the dialyzer clearance, normalized with respect to the total initial distribution volume, while it is scarcely influenced by the normalized ultrafiltration and urea generation rates. The new on-line estimation technique keeps these two last parameters constant and takes advantage of an original analytic solution of the second order urea kinetics. The results of the estimation process on realistic simulated data showed that the proposed method provides early and reliable estimates of the normalized clearance and of the end dialysis concentration. The transcellular mass transfer coefficient and the intra-extra cellular volume ratio can also be estimated, although with less accuracy. Moreover, it was shown that the use of the single-pool model, instead of the double-pool one, provides systematic errors on the estimates.

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