Ett foster har inte samma blodflöde och resistans mot förändringar i sin miljö som en vuxen människa har och kan vid små temperaturförändringar orsakas skada i till exempel den utvecklande hjärnan. Vid ultraljudsundersökning finns bevisat en viss värmeökning, men det råder ovisshet kring hur stor denna skulle kunna bli under en längre tids exponering av ultraljud. Syftet med detta arbete var att undersöka värmeutvecklingen vid obstetriskt ultraljud genom att utforma en 3D-modell i mjukvarumiljön COMSOL Multiphysics version 6.0. En modell kan bidra med kunskap för att besluta kring om riskerna med temperaturökning hos foster till följd av ultraljud behöver studeras vidare. Resultaten av framtagen modellering visade på en mycket liten uppvärmningseffekt. Slutsatsen drogs att om modellen i 3D ska kunna göra trovärdiga beräkningar i programmet krävs en mer avancerad dator än vanligt, med betydligt större minneskapacitet. Vidare utveckling av modell i COMSOL bör göras i 2D, alternativt med en mer avancerad dator, för att få tillförlitliga resultat. / A fetus does not have the same blood perfusion and resistance to changes in its environment as an adult and small changes in temperature can cause irreversible damage for example to the fetal brain. Ultrasound examinations are proven to cause some heat gain but there are uncertainties regarding the amount of heat gain during a longer time of ultrasound exposure. The purpose of this study was to analyse the heat development during obstetric ultrasound by designing a 3D-model in the software environment COMSOL Multiphysics version 6.0. A model could contribute to knowledge in making an informed decision whether the risks of heating in a fetus because of ultrasound are necessary to study further. The results of the developed model showed a very small heating effect. The conclusion was made that if the model in 3D is to be able to make correct calculations in the programme it is required to use a more advanced computer than usual, with significantly greater memory capacity. Further development of a model in COMSOL should be made in 2D, or with a more advanced computer, to get reliable results.

No / Modelling played an important role in simulation, optimisation, and control of multi-stage flash (MSF) desalination processes. Top brine temperature (TBT) is one of the many important parameters that affect optimal design and operation of MSF processes. Within the MSF process model, calculation of TBT is therefore important. For a given pressure, TBT is a function of boiling point temperature (BPT) at zero salinity and temperature elevation (TE) due to salinity. In this work, we develop several neural network (NN) based correlations for predicting TE. It is found that the NN based correlations can predict the experimental TE very closely. Also predictions by the NN based correlations were good when TE values, obtained using existing correlations from the literature are compared. Due to advancement of the microcomputer, plant automation becomes reliable means of plant maintenance. NN based correlations (models) can be updated in terms of new sets of weights and biases for the same architecture or for a new architecture reliably with new plant data.

The tropical rainforests of the Peruvian Andes are some of the most biodiverse and most vulnerable to climate warming in the world. The Andes are predicted to experience substantial increases in warming of between +2 °C to +5 °C by the end of the century, in addition to an increases in the frequency of high temperature extremes, drought and flood events. The response of these forests to climate change over the next century has global relevance, due to the high levels of endemic species present and the potential role these areas will play as refugia for lowland species. Despite this, the response of tropical montane forests (TMCFs) to climate change remains under-studied. Our current understanding of how Andean species will respond to climate change is based on studies of past compositional changes. Upslope shifts in plant communities of approximately 1.2 - 2.0 m·y-1 have been observed along elevational gradients within Central and South America over the last decade. Based on these migration rates, it has been estimated that the majority of communities will lag behind increases in temperature by 5.5 °C by the end of the century. The implications of this for populations at the trailing range edge is unclear, due to a lack of mechanistic data concerning the acclimatory limits of rainforest species. When faced with rapid warming plant species will need to rapidly adapt, acclimate or migrate in order to survive. In the case of Andean species, migration rates may not be sufficient for a species to remain within its optimal thermal niche and adaptive responses will likely be too slow to be effective, hence individuals will have to acclimate in situ to prevent a decline in performance. The acclimatory ability of species can be quantified by measuring changes in performance, leaf physiology and anatomy in response to experimental manipulations of climate, however such studies are rare within the tropics. Here we carried out a seedling transplant experiment, utilising an extensive 400-3500 m asl elevational gradient in the Peruvian Andes, to simulate climate warming and upslope migration of tree seedlings under real-world conditions. To provide context for the transplant study, natural variation in leaf anatomical traits and physiological stress were explored for twelve species belonging to lowland (LF), mid-elevation (LMF) and tropical montane cloud forest communities. Adults and seedlings from the centre and furthest-most extent of each species' elevational range were studied and compared. Seedlings of each elevational forest community were transplanted downslope and upslope of their local elevational range by the equivalent of ±2 °C and ±4 °C in mean annual temperature. The experiment followed the transplanted seedlings of eleven species over a one year period, monitoring survival, growth and physiological stress (Fv/Fm) of individuals. The acclimatory ability of a subset of these species was quantified by measuring changes in photosynthetic capacity (Vcmax and Jmax), respiratory capacity (Rd) and anatomical traits (Na, Pa, LMA, LDMC) in response to transplantation. The results showed that within the natural population there was little evidence of leaf trait acclimation to elevational shifts in climate, but also little evidence of physiological stress at the trailing range edge. There were however differences in the leaf trait strategies employed by each elevational community, increasing in abiotic stress-tolerance with elevation. Physiological stress was greatest in the seedling population and, unlike the adult population, increased slightly at the trailing edge. This indicated that seedlings were more vulnerable to warming than their adult counterparts and at mid-elevations TMCF seedlings were more vulnerable than LMF seedlings. Seedling survival and growth declined in response to transplantation away from the home elevation for the majority of species, with upslope declines as a result of abiotic limitations, and downslope declines due to biotic limitations. All seedlings were found to be able to acclimate their respiratory capacity in response to transplantation, however this was not the case for photosynthetic capacity. LMF species performed significantly better than TMCF seedlings with transplantation, demonstrating a greater acclimatory capacity for photosynthesis. LMF species were able to adjust Jmax in order to maintain rates at ambient temperatures, but were not able to upregulate Vcmax upslope, whereas TMCF species were not able to respond in either transplant direction. Overall, these findings suggest that under moderate warming scenarios LMF species will have a competitive advantage over TMCF species at mid-elevations, gradually expanding their range into TMCF species' habitat over the next century. As a result of this and due to the slow pace of upslope migration, we predict that TMCF species will undergo range retractions and possible extinctions. The speed of this response will be determined by the trajectory of future warming and the frequency of extreme climatic events.

No / The water permeability constant, (K-w), is one of the many important parameters that affect optimal design and operation of RO processes. In model based studies, e.g. within the RO process model, estimation of W-w is therefore important There are only two available literature correlations for calculating the dynamic K-w values. However, each of them is only applicable for a given membrane type, given feed salinity over a certain operating pressure range. In this work, we develop a time dependent neural network (NN) based correlation to predict K-w in RO desalination processes under fouling conditions. It is found that the NN based correlation can predict the K-w values very closely to those obtained by the existing correlations for the same membrane type, operating pressure range and feed salinity. However, the novel feature of this correlation is that it is able to predict K-w values for any of the two membrane types and for any operating pressure and any feed salinity within a wide range. In addition, for the first time the effect of feed salinity on Kw values at low pressure operation is reported. Whilst developing the correlation, the effect of numbers of hidden layers and neurons in each layer and the transfer functions is also investigated. (C) 2014 Elsevier B.V. All rights reserved.