Hospital Acquired Infections (HAI) are a global patient safety challenge, costly to treat, and affect hundreds of millions of patients annually worldwide. It has been shown that the majority of HAI are transferred to patients by caregivers' hands and therefore, can be prevented by proper hand hygiene (HH). However, many factors including cognitive load, cause caregivers to forget to cleanse their hands. Hand hygiene compliance among caregivers remains low around the world. In this thesis I showed that it is possible to build a wearable accelerometer-based HH reminder system to identify ongoing nursing activities with the patient, indicate the high-risk activities, and prompt the caregivers to clean their hands. Eight subjects participated in this study, each wearing five wireless accelerometer sensors on the wrist, upper arms and the back. A pattern recognition approach was used to classify six nursing activities offline. Time-domain features that included mean, standard deviation, energy, and correlation among accelerometer axes were found to be suitable features. On average, 1-Nearest Neighbour classifier was able to classify the activities with 84% accuracy. A novel algorithm was developed to adaptively segment the accelerometer signals to identify the start and stop time of each nursing activity. The overall accuracy of the algorithm for a total of 96 events performed by 8 subjects was approximately 87%. The accuracy was higher than 91% for 5 out of 8 subjects. The sequence of nursing activities was modelled by an 18-state Markov Chain. The model was evaluated by recently published data. The simulation results showed that the high-risk of cross-contamination decreases exponentially by frequency of HH and this happens more rapidly up to 50%-60% hand hygiene rate. It was also found that if the caregiver enters the room with high-risk of transferring infection to the current patient, given the assumptions in this study, only 55% HH is capable of reducing the risk of infection transfer to the lowest level. This may help to prevent the next patient from acquiring infection, preventing an infection outbreak. The model is also capable of simulating the effects of the imperfect HH on the risk of cross-contamination.

Melt convection and solid phase movement play an important role in solidification processes, which significantly influence the formation of grain structures and solute segregations. In general, the melt convection and grain movement are a result of buoyancy forces. The densities within melt are different due to the variation of temperature and concentration, leading to thermally and solutally driven melt convection. Similarly, the density differences between the grains and the bulk melt cause the grain movement, leading to solid sedimentation or grain floating, as the case may be. Free, unattached solid grains are produced by partial remelting and fragmentation of dendrites, by mechanical disturbances such as stirring or vibration and by heterogeneous nucleation of grains in solidification of grain-refined alloys. In this way, movement of solid crystals during solidification can be ascertained in the following two cases. In the first case, during columnar solidification of non-grain-refined alloys, solid movement is possible in the form of dendrite fragments detached from the columnar stalks by the process of remelting and fragmentation. Movement of grains during columnar solidification gives rise to altogether different microstructure from columnar to equiaxed. In the second case, during equiaxed solidification of grain-refined alloys, the movement of solid crystals is possible in the form of equiaxed dendrite crystals nucleated due to presence of grain refiners. The rate and manner by which the free solids settle (or float) will influence macrosegregation in metal castings. Control of the solidification process is possible through an understanding of the solid movement and its effect on macrosegregation and microstructure. With this viewpoint, the overall objective of the present thesis is to study, experimentally and numerically, the phenomenon of solid phase movement during solidification. Through this study, deeper insights of the role of solid phase movement in solidification are developed which can be used for possible control of quality in castings. Both columnar and equiaxed solidification are considered. Models for transport phenomena associated with columnar solidification with solid phase movement are rarely found in the literature, because of inherent difficulty associated with consideration of microscopic features such as remelting and fragmentation. To tackle this problem, solidification modules for remelting and fragmentation are developed first, followed by integration of these molecules in a macroscopic solidification model. A Rayleigh number based fragmentation criterion is developed for detachment of dendrite fragments from the developing mushy zone, which determines the conditions favorable for fragmentation of dendrites. The criterion developed is a function of net concentration difference, liquid fraction, permeability, growth rate of mushy layer, and thermophysical properties of the material. The effect of various solidification parameters on fragmentation is highlighted. The integrated continuum model developed is applied to stimulate the solidification of aqua-ammonia system in a side-cooled rectangular cavity. The numerical results are in good qualitative agreement with those of experiments reported in literature. A gentle ramp of the mushy zone due to settling of solid crystals, as also noticed in experimental literature, is observed towards the bottom of the cavity. The influence of various modeling parameters on solid phase movement and resulting macrosegregation is investigated through a parametric study. Movement of grains during columnar solidification gives rise to altogether different microstructure and sometimes may initiate a morphological transition of the microstructure from columnar to equiaxed if the number and size of equiaxed grains ahead of the columnar front become sufficient to arrest the columnar growth. The generalised model developed, considering solid phase movement during columnar solidification is used to predict columnar-to-equiaxed transition (CET) based on a prescribed cooling rate criterion. It is found that presence of convection significantly affects the solidification behaviour. Moreover, the movement of dendrite fragments and their accumulation at the columnar front further trigger the occurrence of CET. Cooling configuration, too significantly affects the nature of CET. In unidirectional solidification cases, the locations of CET are found to be in a plane parallel to the chill face. However, for the case of the non-unidirectional solidification (as in side-cooled cavity), the locations of CET need not be in a plane parallel to the chill face. In contrast to fixed columnar solidification, equiaxed solidification is poorly understood; in particular, the phenomena associated with solid crystal movement. Movement of unattached solid crystals, formed due to heterogeneous nucleation on grain-refiners, is induced by the convective currents as well as by buoyancy effects, causing the solid to sediment or to float, depending on density of solid compared to that of the bulk melt. While moving in the bulk melt these crystals can also remelt or grow. A series of casting experiments with AI-based alloys are performed to investigate the role and influence of movement of solid crystals on macrosegregation and microstructure evolution during equiaxed solidification. Controlled experiments are designed for studying, separately, settling and floatation of equiaxed crystals for different cooling conditions and configurations. Further, these experiments are carried out in convective and non-convective cases to understand the effect of convection on solid phase movement. Temperature measurements are performed at various locations in the mould during the experiments. After the cavity is solidified, microstructural and chemical analyses of the experimental samples are carried out, several notable features are observed in temperature histories, macrosegregation pattern, and microstructures due to settling/flotation phenomenon of solid crystals. It is found that the flow behavior of solid grains has a profound influence on the progress of solidification (in terms of grain size distribution and fraction eutectic) and macrosegregation distribution. In some cases, the induced flow due to solid phase movement can cause a flow reversal. The observations and quantitative data obtained from experiments, with the help of detailed solidification conditions provided, can be used for future validations of models for equiaxed solidification. Subsequently, numerical studies are carried out, using a modified version of the macroscopic model developed for columnar solidification with motion of solid crystals, to predict the transport phenomena during equiaxed solidification. The model is applied to simulate the solidification processes corresponding to each of the experimental cases performed in this study. For a better understanding of the phenomenon of movement of solid crystals, the following two special cases of solidification are also presented: 1) without movement of solid crystals and 2) movement of solid crystals without any relative velocity between solid and liquid phases. The numerical predictions showing nature of flow field and progress of solidification are substantiated by the experimental data for the thermal analysis, qualitative microstructural Images and quantitative microstructural analysis. It is concluded, with the help of various experiments and simulations, that movement of solid crystals influences the casting quality appreciably, in terms of macrosegregation and microstructures. It is expected that the improved understanding of the role and influence of solid phase movement during solidification processes (both columnar and equiaxed) obtained through this thesis will be useful for possible control of quality of as-cast products.

The volume defined by the rigid cranium is shared by the brain, blood and cerebrospinal fluid (CSF). With every heartbeat the arterial blood volume briefly increases and venous blood and CSF are forced out of the cranium, leading to pulsatility in CSF flow and intracranial pressure (ICP). Altered CSF pulsatility has been linked to idiopathic normal pressure hydrocephalus (INPH), which involves enlarged cerebral ventricles and symptoms of gait/balance disturbance, cognitive decline and urinary incontinence that may be improved by implantation of a shunt. The overall aim of this thesis was to investigate the fluid dynamics of the CSF system, with a focus on pulsatility, and how they relate to INPH pathophysiology and treatment. Mathematical modelling was applied to data from infusion tests, where the ICP response to CSF volume manipulation is measured, to analyse the relationship between mean ICP and ICP pulse amplitude (AMP) before and after shunt surgery in INPH (paper I-II). The observed relationship, designated the pulsatility curve, was found to be constant at low ICP and linear at high ICP, corresponding to a shift from constant to ICP dependent compliance (paper I). Shunt surgery did not affect the pulsatility curve, but shifted baseline ICP and AMP along the curve towards lower values. Patients who improved in gait after surgery had significantly larger AMP reduction than those who did not, while ICP reduction was similar, suggesting that improving patients had baseline ICP in the linear zone of the curve before surgery. Use of this phenomenon for outcome prediction was promising (paper II). The fluid dynamics of an empirically derived pulsatility-based predictive infusion test for INPH was also investigated, with results showing strong influence from compliance (paper III). Clinical ICP data at different body postures was used to evaluate three models describing postural effects on ICP. ICP decreased in upright positions, whereas AMP increased. The model describing the postural effects based on hydrostatic changes in the venous system, including effects of collapse of the jugular veins in the upright position, accurately predicted the measured ICP (paper IV). Cerebral blood flow and CSF flow in the aqueduct and at the cervical level was measured with phase contrast magnetic resonance imaging, and compared between healthy elderly and INPH (paper V). Cerebral blood flow and CSF flow at the cervical level were similar in INPH patients and healthy elderly, whereas aqueductal CSF flow differed significantly. The pulsatility in the aqueduct flow was increased, and there was more variation in the net flow in INPH, but the mean net flow was normal, i.e. directed from the ventricles to the subarachnoid space (paper V). In conclusion, this thesis introduced the concept of pulsatility curve analysis, and provided evidence that pulsatility and compliance are important aspects for successful shunt treatment and outcome prediction in INPH. It was further confirmed that enhanced pulsatility of aqueduct CSF flow was the most distinct effect of INPH pathophysiology on cerebral blood flow and CSF flow. A new model describing postural and hydrostatic effects on ICP was presented, and the feasibility and potential importance of measuring ICP in the upright position in INPH was demonstrated. / <p>Forskningsfinansiär: </p><p>European Union, ERDF: Objective 2, Northern Sweden (grant no. 158715-CMTF). </p>

Type 2 diabetes is a global disease which affects an increasing number of peopleevery year. At the heart of the disease lies insulin resistance in the target tissues,primarily fat and muscle. The insulin resistance is caused by the failure of a complexsignalling network, and several mechanistic hypotheses for this failure havebeen proposed. Herein, we evaluate a hypothesis that revolves around the proteinmammalian target of rapamycin (mTOR) and its feedback signals to insulin receptorsubstrate-1 (IRS1). In particular, we have re-examined this hypothesis andrelevant biological data using a mathematical modelling approach. During the course of modelling we gained several important insights. For instance,the model was unable to reproduce the relation between the EC50-valuesin the dose-response curves for IRS1 and its serine residue 312 (Ser-312). Thisimplies that the presented hypothesis, where the phosphorylation of Ser-312 liesdownstream of the tyrosine phosphorylation of IRS1, is inconsistent with the provideddata, and that the hypothesis or the data might be incorrect. Similarly, wealso realized that in order to fully account for the information in the dose-responsedata, time curves needed to be incorporated into the model. A preliminary model is presented, which explains most of the data-sets, butstill is unable to describe all the details in the data. The originally proposed hypothesisas an explanation to the given data has been revised, and our analysisserves to exemplify that an evaluation of a mechanistic hypothesis by mere biochemicalreasoning often misses out on important details, and/or leads to incorrectconclusions. A model-based approach, on the other hand, can efficiently pin-pointsuch weaknesses, and if combined with a comprehensive understanding of biologicalvariation and generation of experimental data, mathematical modelling canprove to be a method of great potential in the search for mechanistic explanationsto the cause of insulin resistance in type 2 diabetics.

The objective of the thesis is to improve plant yield through optimization and optimal control based on the GreenLab plant growth model. Therefore, the thesis proposed a methodology for investigation of plant yield improvement，whose characteristics are that (1) investigations are all based on the functional-structural plant growth model GreenLab and (2) heuristic optimization algorithm and optimal control techniques are applied to the plant growth model in order to improve plant yield. By applying optimization techniques on different species of plants (crops or trees) and for different kinds of optimization problems, common characteristics that a plant with high yield should possess were obtained. The optimal results in the thesis revealed the source-sink dynamics during the plant growth. The optimization results can be considered as references to guide breeding for ideotype and to improve cultivation modes. The optimization application of GreenLab could thus be possibly used to the agricultural decision support system.To achieve the aims of the thesis, the thesis investigated the effects of endogenous factors and exogenous environmental factors of plant growth on plant yield separately. First, given environmental conditions, the thesis investigated endogenous factors, and then the thesis did optimal control on exogenous environmental factors given plant genotype. Therefore, the problems investigated in the thesis consist of general optimization problems and optimal control problems.The main contributions of the thesis include following issues: According to the species of plants, single optimization problems, multi-objective optimization problems and optimization problems with constraints with respect to plant endogenous factors were formulated and investigated, in order to find the ideotype of plants with high plant yield. A population based algorithm is more suitable for the optimization problems in this thesis. Due to its better performance compared with other heuristic optimization algorithms, all optimization problems were solved by a population-based, heuristic optimization algorithm, namely Particle Swarm Optimization (PSO). Optimal control on the pruning strategy was formulated and investigated in the thesis. As GreenLab can be considered as discrete dynamic system and the objective function of the optimal control problem is analytical, the gradient based method, which is based on the variational approach and Lagrange theory, was used to solve the optimal control problem. Moreover, the optimal solutions were compared with the ones found by PSO, in order to validate the PSO method. The insect population dynamics was modeled mathematically, which was compatible with the plant model GreenLab in terms of spatial and temporal scales, to study the effect of biotic factors on plant growth. The interaction among plants, pests and auxiliaries was implemented, and the ecosystem model, which involves the three tri-trophic components, was thus developed in the thesis. The tri-trophic ecosystem model can simulate the insect population dynamics and the plant growth with consideration of the interaction of insects. Moreover, the tri-trophic ecosystem model considered the partition of individuals in the insect population among plant organs, which is not taken into account in the previous works. A global sensitivity analysis method Morris method was used to analyze the most important parameters and the least influential parameters to model outputs of interest. Through optimization on pest management techniques, the optimal strategies of the application of the pest management techniques were obtained. Estimation of GreenLab parameters with about 400 sets of observation data of 44 tomato genotypes was done in the thesis, by using a generalized non-linear least square algorithm. Taking the estimated parameter values as parameter space, the GreenLab model parameters were optimized, in order to maximize the fruit yield. Through the analysis of the correlation of estimated and optimal parameters with the fruit yield by statistical analysis methods, the most important parameters that result in the difference of fruit yield were found. According to the correlation and optimization results, the phenotypic differences among genotypes were explained from the physiological point of view.

Hospital Acquired Infections (HAI) are a global patient safety challenge, costly to treat, and affect hundreds of millions of patients annually worldwide. It has been shown that the majority of HAI are transferred to patients by caregivers' hands and therefore, can be prevented by proper hand hygiene (HH). However, many factors including cognitive load, cause caregivers to forget to cleanse their hands. Hand hygiene compliance among caregivers remains low around the world. In this thesis I showed that it is possible to build a wearable accelerometer-based HH reminder system to identify ongoing nursing activities with the patient, indicate the high-risk activities, and prompt the caregivers to clean their hands. Eight subjects participated in this study, each wearing five wireless accelerometer sensors on the wrist, upper arms and the back. A pattern recognition approach was used to classify six nursing activities offline. Time-domain features that included mean, standard deviation, energy, and correlation among accelerometer axes were found to be suitable features. On average, 1-Nearest Neighbour classifier was able to classify the activities with 84% accuracy. A novel algorithm was developed to adaptively segment the accelerometer signals to identify the start and stop time of each nursing activity. The overall accuracy of the algorithm for a total of 96 events performed by 8 subjects was approximately 87%. The accuracy was higher than 91% for 5 out of 8 subjects. The sequence of nursing activities was modelled by an 18-state Markov Chain. The model was evaluated by recently published data. The simulation results showed that the high-risk of cross-contamination decreases exponentially by frequency of HH and this happens more rapidly up to 50%-60% hand hygiene rate. It was also found that if the caregiver enters the room with high-risk of transferring infection to the current patient, given the assumptions in this study, only 55% HH is capable of reducing the risk of infection transfer to the lowest level. This may help to prevent the next patient from acquiring infection, preventing an infection outbreak. The model is also capable of simulating the effects of the imperfect HH on the risk of cross-contamination.

Didactic proposals on modelling in mathematics education mostly give priority to models which describe, explain as well as partially forecast and provide mathematical solutions to real situations. A view of the modelling concept of informatics, which also initiates rapidly generalised deliberations of models, can also make a contribution to the spectrum of models, which are treated in a meaningful sense in mathematics lessons so as to expand some interesting aspects. In this paper, this is illustrated by means of conceptual design models – and, here, especially of process models – using the example of elevator organisation in a multi-storey construction.

Mathematical modelling problems are embedded in written, representational, and graphic text. For students to actively engage in the mathematical-modelling process, they require literacy. Of critical importance is the comprehension of the problems' text information, data, and goals. This design-research study investigated the application of top-level structuring; a literary, organisational, structuring strategy, to mathematical-modelling problems. The research documents how students' mathematical modelling was changed when two classes of Year 4 students were shown, through a series of lessons, how to apply top-level structure to two scientifically-based, mathematical-modelling problems. The methodology used a design-based research approach, which included five phases. During Phase One, consultations took place with the principal and participant teachers. As well, information on student numeracy and literacy skills was gathered from the Queensland Year 3 'Aspects of Numeracy' and 'Aspects of Literacy' tests. Phase Two was the initial implementation of top-level structure with one class of students. In Phase Three, the first mathematical-modelling problem was implemented with the two Year 4 classes. Data was collected through video and audio taping, student work samples, teacher and researcher observations, and student presentations. During Phase Four, the top-level structure strategy was implemented with the second Year 4 class. In Phase Five, the second mathematical-modelling problem was investigated by both classes, and data was again collected through video and audio taping, student work samples, teacher and researcher observations, and student presentations. The key finding was that top-level structure had a positive impact on students' mathematical modelling. Students were more focussed on mathematising, acquired key mathematical knowledge, and used high-level, mathematically-based peer questioning and responses after top-level structure instruction. This research is timely and pertinent to the needs of mathematics education today because of its recognition of the need for mathematical literacy. It reflects international concerns on the need for more research in problem solving. It is applicable to real-world problem solving because mathematical-modelling problems are focussed in real-world situations. Finally, it investigates the role literacy plays in the problem-solving process.

In 1997, the first human case of avian influenza infection was reported in Hong Kong. Since then, avian influenza has become more and more hazardous for both animal and human health. Scientists believed that it would not take long until the virus mutates to become contagious from human to human. In this thesis, we construct avian influenza with possible mutation situations in bird-human systems. Also, possible control measures for humans are introduced in the systems. We compare the analytical and numerical results and try to find the most efficient control measures to prevent the disease.

This thesis details the development of a model of driver behaviour at railway level crossings that allows the probability of an accident under different conditions and interventions to be calculated. A method for classifying different crossings according to their individual risk levels is also described.