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References [1]. Radan, G. (2014). Micropiles axially loaded in karst terrain. Mathematical Modelling in Civil Engineering, Special Issue, Y.R.C. 2014, from http://mmce.rs.utcb.ro/wiew-articles/archive1/18-2014/58-scientific-journal-special-issue1.html . [2]. Seo, H. & Prezzi, M. (2008). Use of Micropiles for Foundations of Transportation Structures Final Report . Joint Transportation Research Program: Purdue University. [3]. Radan, G. (2015). Methods of foundation and stabilization of terrains with micropiles . Unpublished Doctoral Thesis, Technical

References Gromiec MJ. Mathematical Modeling of the Quality of Surface Waters. Warszawa: Instytut Meteorologii i Gospodarki Wodnej; 2008. Holnicki P, Nahorski Z, Żochowski A. Modelling of Environment Processes. Warszawa: Wydawnictwo Wyższej Szkoły Informatyki Stosowanej i Zarządzania; 2000. Chapra SC. Surface Water - Quality Modeling. New York - Toronto, USA: McGraw-Hill Companies, Inc.; 1997. Bielak S. Assess and predict the ecological status of river ecosystem in Biebrza National Park. [PhD Thesis]. Kraków: Technical University of Krakow; 2009. Balcerzak W

for their schools based on the application of a mathematical model of metapopulations ( Pereira, Silva, & Rosa, 2014 ). In the case of the IPG, the study is innovative in the sense that no projections have been made for this institution in the period considered. This paper is structured in five sections. In section 1 , we present an Introduction. In section 2 , we present a brief literature review about the projection models. In section 3 , the dynamic model for the study of the evolution of the number of students in a teaching institution is presented. The model

Abstract

Today the world is facing, more and more, different sources of pollution, the most affected areas being the proximity of big industrial centers (e.g.: chemistry, mining and metallurgy, machinery building etc.). Baia Mare industrial area is a typical one for such a situation. To maintain a clean and healthy environment in Baia Mare city and in the surrounding areas, important costs are needed. The usefulness of the mathematical models consists in the possibility of mathematical processing of industrial parameters evolutions, with relevant interpretations on various influences and their correction for achieving the set goals (maximizing financial efficiency, environmental protection with the compliance of legal requirements etc.)

Abstract

Broiler breeders hens (meat-type hens) have lower reproductive potential than laying-type hens. Statistical models for predicting potential laying pattern are important for economically optimal breeding strategy of egg production in a poultry flock. The aim of the study was to find the most suitable function for describing the egg-laying rate and egg weight during the broiler breeders’ production period and to characterize laying pattern in groups of hens with different egg production. The following four mathematical models were used: gamma, Narushin-Takma, logistic-curvilinear, and compartmental. The daily recorded egg production data from 100 broiler breeder hens were used. Hen-weekly egg production was described using laying rate during successive weeks after reaching sexual maturity (26 weeks of age) and daily recorded egg weight. On the basis of the total number of eggs laid (NEggs), groups of hens with low (21%), intermediate (52%), and high (27%) egg production were created. The differences between the goodness-of-fit criteria values (AIC, R2 MSE) were small, with all the examined models having the same quality of curve fitting for egg-laying rate and egg weight. The logistic-curvilinear model was able to fit well both egg-laying rate and egg weight of the whole broiler breeder hens’ flock, and also when hens were divided into three egg production groups. This model could be considered in a long-term prediction of the reproductive potential in the commercial management. Moreover, the presented model could be useful in the research on different reproduction parameters of individual hens.

Abstract

The paper presents a part of the work conducted in the first stage of a Research Grant called ”Hybrid micro-cogeneration group of high efficiency equipped with an electronically assisted ORC” acronym GRUCOHYB. The hybrid micro-cogeneration group is equipped with a four stroke Diesel engine having a maximum power of 40 kW. A mathematical model of the internal combustion engine is presented. The mathematical model is developed based on the Laws of Thermodynamics and takes into account the real, irreversible processes. Based on the mathematical model a computation program was developed. The results obtained were compared with those provided by the Diesel engine manufacturer. Results show a very high correlation between the manufacturer’s data and the simulation results for an engine running at 100% load. Future developments could involve using an exergetic analysis to show the ability of the ORC to generate electricity from recovered heat

References Britter RE. Ann Rev Fluid Mech. 1989;21:317-344. Rigas F, Sklavounos S. Computer simulation in consequence analysis and loss prevention. In: New research on hazardous materials. Warrey PB, editors. Nova Science Publishing Inc. 2007;161-209. Hanna SR, Drivas PJ. Guidelines for use of vapour cloud dispersion models. New York: Center for Chemical Process Safety, Institute of Chemical Engineers; 1989. Markiewicz M. A review of mathematical models for atmospheric dispersion of heavy gases. Part II: Procedures for the model quality evaluation and the main

Biomedical Sciences 44(4): 477–92. Cooper, S. Barry; and Maini, Philip K. 2012. The mathematics of nature at the Alan Turing centenary. Interface Focus 2: 393–6. Craver, Carl F.; and Darden, Lindley. 2013. In Search of Mechanisms: Discoveries across the life sciences . Chicago: University of Chicago Press. Dilão, Rui. 2015. Mathematical models of morphogenesis. ITM Web of Conferences 4. Dretske, Fred. 1988. Explaining Behavior: Reasons in a World of Causes . Cambridge MA: MIT Press. Economou, Andrew et al. 2012. Periodic stripe formation by a Turing mechanism

. Zeszyty Problemowe Postępów Nauk Rolniczych, 577 , 3-12. Baradaran Motie, J., Miraei Ashtiani, S. H., Abbaspour-Fard, M. H., Emadi, B. (2014). Modeling physical properties of lemon fruits for separation and classification. International Food Research Journal , 21 (5), 1901-1909. Bozokalfa, M. K., Kilic, M. (2010). Mathematical modeling in the estimation of pepper (Capsicum annum L.) fruit volume. Chilean Journal of Agricultural Research , 70 (4), 626-632. Burt, S.A. (2004). Essential oils: Their antibacterial properties and potential applications in foods: Av review

. Sorption and stability of mercury on activated carbon for emission control. Journal of hazardous materials 168(2) , 978-982. 8. Chung, ST, Kim, KI and Yun, YR 2009. Adsorption of elemental mercury vapor by impregnated activated carbon from a commercial respirator cartridge. Powder Technology 192(1) , 47-53. 9. Ren, J, Zhou, J, Luo, Z, Zhong, Y and Xu, Z 2007. Fixed-bed experiments and mathematical modeling for adsorption of mercury vapor. Challenges of Power Engineering and Environment , Springer, Berlin, Heidelberg, 843-849. 10. Camargo, CLM, de Resende, NS, de