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A system that continuously monitors housing markets can be a highly efficient tool towards a functioning housing policy and as a basis for decisions of private market actors. Monitoring means to permanently combine, aggregate and process data from different sources in order to attain a reliable database, on which housing markets are analysed and future developments are estimated to assist housing market participants with a firm foundation to substantiate their actions. For a better illustration of the gains, requirements and functioning of monitoring systems, the example of the monitoring system of Dortmund, Germany, will be presented. On the outcomes of researching Dortmund's monitoring system, the chance of implementing and managing a monitoring system in Warsaw will be investigated. The article is based on the author's diploma thesis at the Faculty of Spatial Planning at the University of Dortmund, titled "A Monitoring System for Warsaw's Housing Market", written during a six-month lasting field study in Warsaw.
A university was examined as an object of informatization, its problem areas of activity were defined, the model of the regional system of control and assurance education quality, which includes systems of monitoring, analyzing and forecasting the statistical data obtained from all the educational institutions in the region, is proposed in this paper.
Drivers, pressures, state changes, impacts and responses (DPSIR) is a general framework for organising information about the state of the environment. The idea of the framework derives originally from the field of social studies. Now it is being applied on a much wider scale, in particular for organizing systems of indicators in the context of environmental studies and also sustainable development. Many datasets on Baltic pollution, the state of its environment, infrastructure, emissions and monitoring networks are available. Yet without suitable tools they cannot be used properly and effectively. This paper contains a review of the current state of the Baltic region and the most useful sources of relevant information. A partial analysis – including only drivers, pressures and state changes – was carried out. To this purpose two tools were utilized: an experts' poll and reports of organizations – providers of the datasets. The former resulted in the following top three Ds, Ps and Ss: D – urban waste (1), transport, shipping (2), agriculture (3); P – rivers (1), direct discharges (2), atmospheric deposition (3); and S – decrease in population density (1), individual effects (scope for growth, imposex, endocrine disruption) (2), tissue pathology (3). Moreover, both methods produced similar results, which brings us to the conclusion that instead of providing new analytical/ experimental programs, the existing databases could be better utilized. The significance of rivers should also be stressed. Limitations in access to the data were specified. These were, first of all, lack or gaps in the datasets both in spatial and temporal scale. Differences in the data formats and the principle of data presentation – tables are preferred over graphs and maps – should also be mentioned.
Lithuania has been strengthening its BSE monitoring program since July 2001. A total of 264,268 cattle were examined during the period of 2001-2006. No BSE positive case was found. A total of 93.1% of healthy slaughtered cattle, 6.3% of fallen stock, 0.4% of emergency slaughtered cattle and 0.2% of cattle with clinical signs were tested at ante mortem inspection. The number of tested adult cattle has increased 4.5 times from 4.17% in 2001 to 18.88% in 2006. 2.41% adult cattle were tested in 2002, 1.97% in 2003, 10.59 % in 2004 and 18.92% in 2005. The number of tested healthy slaughtered adult cattle has increased 4 times from 4.09% in 2001 to 17.41% in 2006. 2.11% of healthy slaughtered adult cattle were tested in 2002, 1.5% in 2003, 9.96% in 2004 and 17.66% in 2005. The number of tested risk group adult cattle has increased 18 times from 0.08% in 2001 to 1.47% in 2006. 0.3% of risk group of adult cattle were tested in 2002, 0.47% in 2003, 0.63% in 2004 and 0.96% in 2005. 94.3% of all tested cattle were from 2 to 11 years old, 0.1% of them were less than 2 years old, 3.0% were 12 years old and 2.6% were 13 years old and more. 54.3% of all tested cattle were more than 5 years old. A total of 53.9% of healthy slaughtered cattle, 59.0% of fallen stock, 61.9% emergency slaughtered cattle and 62.6% of cattle with clinical signs at ante mortem inspection were more than 5 years old. Significant correlation was found between the age of healthy slaughtered cattle and emergency slaughtered cattle and cattle with clinical signs at ante mortem inspection (P < 0.05). There was no correlation between the age of fallen stock and healthy slaughtered cattle. The mean age of healthy slaughtered cattle was 6.5 years and the mean age of fallen stock was 6.7 years in 2005. Enfer TSE and Bio-Rad rapid tests were applied for BSE monitoring. Inconclusive test results were subjected to histopathological and immunocytochemical examination.
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