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Olayide F. Obidi, Onyiye V. Okoli and Simon C. U. Nwachukwu

of tributyltin. Water quality research journal of Canada 32, 453-521. Cho, J.D., Ju, H.T., Hong, J.W., 2005, Photocuring kinetics of UV-initiated free-radical photopolymerizations with and without silica nanoparticles. Journal of Polymer Science Part A: Polymer Chemistry 43, 658-670. Chung, H., Ku, M.-S., Lee, J.-S., 1999, Comparison of near-infrared and mid-infrared spectroscopy for the determination of distillation property of kerosene. Vibrational spectroscopy 20, 155-163. Contant, S., Caritá Júnior, G., Machado, P., Lona, L., 2010, Evaluation

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Andrea Galieriková and Jarmila Sosedová


Transport has an immense impact on the environment. The largest share of environmental pollution is caused by road transport. The atmosphere is threatened by fuel combustion of engines of road vehicles, thereby leading to the global warming of Earth. In addition to having an adverse impact on the environment, such as greenhouse gas emissions and carbon dioxide emissions, road transport also leads to external effects such as noise pollution, vibration, congestion and traffic accidents. The volume of transport in the world, notably on the roads, is increasing day by day. We should take the necessary steps to move to more environmentally-friendly modes of transportation, such as rail and inland navigation. Rail transportation is currently the largest competitor of road transport. If the waterways infrastructure is improved, there would be a decrease in the traffic flow of motorways and thus, we can move to a more environmentally-friendly transportation.

Open access

Claudiu-Sorin Dragomir, Vasile Meita, Daniela Dobre, Emil-Sever Georgescu and Ioan-Sorin Borcia


The main objective of the National Seismic Network for Constructions, operated by the National Institute for Research and Development in Constructions, Urban Planning and Spatial Territorial Development “URBAN-INCERC”, is the monitoring of situations generated by earthquakes or other dangerous sources of vibrations induced in constructions on the entire Romanian territory. The NIRD URBAN-INCERC seismic records obtained in-situ and on buildings were and are extremely important for designers, especially in 1977, 1986 and 1990. It is the largest network in Romania, consisting of some 60 digital acceleration recorders distributed in Bucharest and in the country. This network is strategic from the population safety point of view. Due to the specific seismic hazard and vulnerability, our country shall be in preparation for the impact of a possible earthquake, which cannot be predicted in time domain, but it is possible to occur anytime. To prevent and mitigate negative consequences of such an event, urgent actions are required to ensure structural safety. Given the facts, Romania is in a critical time on strategic options regarding the seismic risks.

Presently, a urgent necessity is the seismic network function in order to get as much as possible strong-motion data for advanced research and to understand why damages in buildings occurred. The next goal is to have more parametric and spectral data for engineering design, as well as to improve the zoning maps, having more stations at reduced distances. If possible, strong-motion micro-zonation data would explain some specific shaking differences, as a future option for local arrays.

The paper presents the necessity, means and requirements of achieving a holistic and integrative concept for the national seismic network of constructions, taking into account geological settings, environmental and local soil conditions on regional profiles, attenuation patterns, architectural and structural patterns, and number of seismic stations in specific seismic zones. Also, a case study of building seismic instrumentation in Bucharest according to the Romanian Seismic Design code, indicative P100-1:2013.

Open access

Péter Polcz and Szederkényi

analysis of an uncertain bioreactor model, Proc. Int. Symp. Stability, Vibration, and Control of Machines and Structures (SVCS 2016, Budapest, Hungary) pp. 1-12, 2016 [7] Rocha Filho, T.M.; Gléria, I.M.; Figueiredo, A.; Brenig, L.: The Lotka-Volterra canonical format, Ecol. Mod. 2005 183(1), 95-106 DOI: 10.1016/j.ecolmodel.2004.07.023 [8] Noonburg, V.W.: A neural network modeled by an adaptive Lotka-Volterra system, SIAM J. Appl. Math. 1989 49(6), 1779-1792 DOI: 10.1137/0149109 [9] Bhargava, S.: Generalized Lotka