25 resultados para ipratropium bromide plus salbutamol sulfate
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Tässä työssä tutkittiin Aspen Plus-ohjelmiston soveltuvuutta suodattimen simulointiin. Tämän työn kirjallisuusosassa on esitelty eri suodatusmekanismit sekä joitain prosessisimulointiin soveltuvia ohjelmistoja lähdekirjallisuuden perusteella. Kokeellisessa osassa on tutkittu Aspen Plus-ohjelmiston soveltuvuutta suodattimen simuloimiseen. Simulointi suoritettiin käyttäen Aspenin suodatinmoduulin suunnittelumallia. Lähtökohtana käytettiin buchnersuppilolla ZnS-suspensiolle tehtyä koesuodatusta, jonka perusteella saatiin lähtöparametrien, kuten kakun- ja kankaan vastusten arvot. Simuloinnissa mitoitettiin samalle kapasiteetille rumpusuodatin, jonka suodatuspinta-alaa ja kiintoainekakun tilavuutta verrattiin koesuodatuksen vastaaviin arvoihin. Lisäksi vastaava simulointi suoritettiin filtration-and-separation.com sivuston omaa vakiopaineisen vakuumisuodattimen simulointiin tarkoitettua laskentapohjaa käyttäen, jonka tuloksia verrattiin myös Aspenilla saatuihin simulointituloksiin.
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Lisäkartta: Plan et vue des terres du Cap de la Circoncision situé à 54 degrées de lat. méridiole et environ à 28 deg. 30 min. de longitude = Plan et gezigt van de landen van de Caap der Besnydenis gelegen op 54 gr. zuider br. en omtrent op 28 gr. 30 min. - Eteläisen pallonpuoliskon halkaisija 44,6 cm
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Targeted measures bring the greatest benefits for environmental protection in agriculture final report of the TEHO Plus project (2011–2014). Particular priority areas of the project activities included creating a training package for agri-environment advisers and testing it, farm-specific advisory services and exploitation of experiences of advice provision, putting together an information package of agri-environment issues, farm-level experiments, and development of water quality monitoring. The recommendations issued by advisers on targeting environmental measures were based on utilising geographical information material and nutrient balances. The project was implemented in cooperation by Southwest Finland Centre for Economic Development, Transport and the Environment, MTK-Satakunta and MTK-Varsinais-Suomi. The project received funding from the Ministry of Agriculture and Forestry and the Ministry of the Environment. Participating farmers, with whom environmental advice was developed and experiments were carried out, were important partners for the project. The operating area of the project was Satakunta and Varsinais-Suomi in Southwest Finland, but its outcomes can be exploited nationally. A national perspective was ensured by close cooperation with actors in different provinces. This final report describes project experiences and outcomes including environmental advisory services, training of agri-environmental advisers, farm visits and the feedback received from farmers on agri-environmental advice, development of water quality monitoring, experiments and project work.
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Kartta kuuluu A. E. Nordenskiöldin kokoelmaan
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Kartta kuuluu A. E. Nordenskiöldin kokoelmaan
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Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.
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[N. 1:4000000].
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Sosiologian tulevaisuus.