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Acta Alimentaria
Authors: M. Gyalai-Korpos, A. Fehér, Zs. Barta and K. Réczey

2006 568 200 210 Liu , J., Olsson , G. & Mattiasson , B. (2004): A volumetric meter for monitoring of low

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P. Winship L. Jakobsen 2002 Monitoring snowmelt induced unsaturated flow and transport using electrical resistivity tomography

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monitoring Scirtothrips dorsalis (Thysanoptera: Thripidae). Florida Entomologist 89, 47–55. Henneberry T. J. Developing and evaluating traps for monitoring Scirtothrips dorsalis

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Vonica, I. (1996b): Monitoring for Diabrotica virgifera in Romania. IWGO-Newsletter 16, 15-16. Monitoring for Diabrotica virgifera in Romania IWGO

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Abstract

In the beginning of August 2009 a long-term monitoring started in a recently built passive house near Isaszeg. The first results were presented in the last year's conference. The present paper gives an overview about a whole-year data evaluation focusing on energy consumption. During the first year of building occupancy three types of heat suppliers and two types of heat exchangers in the ventilation systems were applied and monitored, thus different heating options could be compared.

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. European Centre for Disease PreventionControl/WHO Regional Office for Europe. 2012 Tuberculosis surveillance and monitoring in Europe 2012 European Centre for Disease Prevention and Control

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Abstract  

Microcalorimetry was used for monitoring anaerobic digestion processes of heavily polluted industrial waste waters (from cheese industry, distilleries, yeast plant). Interpreting the thermal power-time curves by HPLC, some sub-processes in batch cultures were tentatively identified as acidogenic, acetogenic and methanogenic. Processes underlying power-time curves up to 10 h were different for different wastes. In the case of cheese whey and distillery waste it was acidogenesis, in the case of sulfate containing waste - presumably reduction of sulfates. The effect of Biotreat 100 (BimKemi Eesti Ltd.), a preparation for removing H2S from waste water, was observed for these processes.

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This paper introduces the alternating conditional expectation (ACE) algorithm of Breiman and Friedman (1985) in multiple regression problems in groundwater monitoring data analysis. This special inverse nonparametric approach can be applied easily for estimating the optimal transformations of different groundwater monitoring data from the Bükk Mountains to obtain maximum correlation between observed aquifer variables. The approach does not require a priori assumptions of a mathematical form, and the optimal transformations are derived solely based on the groundwater data set. The advantages and applicability of the proposed approach to solve different multiple regression problems in hydrogeology or in groundwater management are illustrated by means of case studies from a Hungarian karst aquifer. It is demonstrated that the ACE method has certain advantages in some fitting problems of groundwater science over the traditional multiple regression.In the past, different groundwater monitoring data (like groundwater level, groundwater temperature and conductance, etc.) had been used for groundwater management purposes in the Bükk Mountains. One of the difficulties in earlier approaches has been the need to make some kind of assumption of the expected mathematical forms among the investigated reservoir and petrophysical variables. By using nonparametric regression, the need to assume a specific form of model is avoided, and a clearer vision of the relationships between aquifer parameters can be revealed in the Bükk Mountains, where karst water is the main source of potable water supply. Complex monitoring data from the Bükk Mountains were analyzed using the ACE inverse method, and results were verified successfully against quantitative and qualitative field observations.

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The pine wood nematode (PWN), Bursaphelenchus xylophilus — a quarantine pest — has been monitored since 2003 in Hungary. The present paper gives a short review of the monitoring/survey system and the results obtained.

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A Serbian government introduced a labeling system for products which contained genetically modified organisms (GMO) with threshold of 0.1% for grain and 0.9% for food and feed.In order to detect the presence of GM maize in the Serbian market, a triplex PCR was applied to maize grains and processed maize samples. In total 145 samples, 125 samples of maize seed and 25 processed maize were analysed in tree years period. The number of positive samples varied from 12% in 2006 year, to 14.5% in 2008. The estimated amounts of GM maize using Real Time PCR in 17 samples ranged between 0.1% and 0.9%, for most of them 0.2% or 0.3%. In two maize seed samples GMO content was higer than >0.9%, in 2006. Obtained results showed that maize seed has been contaminated with GM seed but in most cases under labeling treshold.Monitoring for transgenic crop plants is necessary, especially in cases, like in Serbia, when the crop has not been approved for release into the environment.

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