Verbal learning in mild cognitive impairment and alzheimer's disease : behavioural and neural approaches

The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.

Tutorials for MeVEA Simulation Software

The objective of the thesis was to create three tutorials for MeVEA Simulation Software to instruct the new users to the modeling methodology used in the MeVEA Simulation Software. MeVEA Simulation Software is a real-time simulation software based on multibody dynamics. The simulation software is designed to create simulation models of complete mechatronical system. The thesis begins with a more detail description of the MeVEA Simulation Software and its components. The thesis presents the three simulation models and written theory of the steps of model creation. The first tutorial introduces the basic features which are used in most simulation models. The basic features include bodies, constrains, forces, basic hydraulics and motors. The second tutorial introduces the power transmission components, tyres and user input definitions for the different components in power transmission systems. The third tutorial introduces the definitions of two different types of collisions and collision graphics used in MeVEA Simulation Software.

Methods and Models for Accelerating Dynamic Simulation of Fluid Power Circuits

The objective of this dissertation is to improve the dynamic simulation of fluid power circuits. A fluid power circuit is a typical way to implement power transmission in mobile working machines, e.g. cranes, excavators etc. Dynamic simulation is an essential tool in developing controllability and energy-efficient solutions for mobile machines. Efficient dynamic simulation is the basic requirement for the real-time simulation. In the real-time simulation of fluid power circuits there exist numerical problems due to the software and methods used for modelling and integration. A simulation model of a fluid power circuit is typically created using differential and algebraic equations. Efficient numerical methods are required since differential equations must be solved in real time. Unfortunately, simulation software packages offer only a limited selection of numerical solvers. Numerical problems cause noise to the results, which in many cases leads the simulation run to fail. Mathematically the fluid power circuit models are stiff systems of ordinary differential equations. Numerical solution of the stiff systems can be improved by two alternative approaches. The first is to develop numerical solvers suitable for solving stiff systems. The second is to decrease the model stiffness itself by introducing models and algorithms that either decrease the highest eigenvalues or neglect them by introducing steady-state solutions of the stiff parts of the models. The thesis proposes novel methods using the latter approach. The study aims to develop practical methods usable in dynamic simulation of fluid power circuits using explicit fixed-step integration algorithms. In this thesis, twomechanisms whichmake the systemstiff are studied. These are the pressure drop approaching zero in the turbulent orifice model and the volume approaching zero in the equation of pressure build-up. These are the critical areas to which alternative methods for modelling and numerical simulation are proposed. Generally, in hydraulic power transmission systems the orifice flow is clearly in the turbulent area. The flow becomes laminar as the pressure drop over the orifice approaches zero only in rare situations. These are e.g. when a valve is closed, or an actuator is driven against an end stopper, or external force makes actuator to switch its direction during operation. This means that in terms of accuracy, the description of laminar flow is not necessary. But, unfortunately, when a purely turbulent description of the orifice is used, numerical problems occur when the pressure drop comes close to zero since the first derivative of flow with respect to the pressure drop approaches infinity when the pressure drop approaches zero. Furthermore, the second derivative becomes discontinuous, which causes numerical noise and an infinitely small integration step when a variable step integrator is used. A numerically efficient model for the orifice flow is proposed using a cubic spline function to describe the flow in the laminar and transition areas. Parameters for the cubic spline function are selected such that its first derivative is equal to the first derivative of the pure turbulent orifice flow model in the boundary condition. In the dynamic simulation of fluid power circuits, a tradeoff exists between accuracy and calculation speed. This investigation is made for the two-regime flow orifice model. Especially inside of many types of valves, as well as between them, there exist very small volumes. The integration of pressures in small fluid volumes causes numerical problems in fluid power circuit simulation. Particularly in realtime simulation, these numerical problems are a great weakness. The system stiffness approaches infinity as the fluid volume approaches zero. If fixed step explicit algorithms for solving ordinary differential equations (ODE) are used, the system stability would easily be lost when integrating pressures in small volumes. To solve the problem caused by small fluid volumes, a pseudo-dynamic solver is proposed. Instead of integration of the pressure in a small volume, the pressure is solved as a steady-state pressure created in a separate cascade loop by numerical integration. The hydraulic capacitance V/Be of the parts of the circuit whose pressures are solved by the pseudo-dynamic method should be orders of magnitude smaller than that of those partswhose pressures are integrated. The key advantage of this novel method is that the numerical problems caused by the small volumes are completely avoided. Also, the method is freely applicable regardless of the integration routine applied. The superiority of both above-mentioned methods is that they are suited for use together with the semi-empirical modelling method which necessarily does not require any geometrical data of the valves and actuators to be modelled. In this modelling method, most of the needed component information can be taken from the manufacturer’s nominal graphs. This thesis introduces the methods and shows several numerical examples to demonstrate how the proposed methods improve the dynamic simulation of various hydraulic circuits.

Cognitive Functions After Traumatic Brain Injury. A 30-year Follow-up Study

Many cognitive deficits after TBI (traumatic brain injury) are well known, such as memory and concentration problems, as well as reduced information-processing speed. What happens to patients and cognitive functioning after immediate recovery is poorly known. Cognitive functioning is flexible and may be influenced by genetic, psychological and environmental factors decades after TBI. The general aim of this thesis was to describe the long-term cognitive course after TBI, to find variables that may contribute to it, and how the cognitive functions after TBI are associated with specific medical factors and reduced survival. The original study group consisted of 192 patients with TBI who were originally assessed with the Mild Deterioration Battery (MDB) on average two years after the injury, during the years 1966 – 1972. During a 30-year follow-up, we studied the risks for reduced survival, and the mortality of the patients was compared with the general population using the Standardized Mortality Ratio (SMR). Sixty-one patients were re-assessed during 1998-2000. These patients were evaluated with the MDB, computerized testing, and with various other neuropsychological methods for attention and executive functions. Apolipoprotein-E (ApoE) genotyping and magnetic resonance imaging (MRI) based on volumetric analysis of the hippocampus and lateral ventricles were performed. Depressive symptoms were evaluated with the short form of the Beck depression inventory. The cognitive performance at follow-up was compared with a control group that was similar to the study group in regard to age and education. The cognitive outcome of the patients with TBI varied after three decades. The majority of the patients showed a decline in their cognitive level, the rest either improved or stayed at the same level. Male gender and higher age at injury were significant risk factors for the decline. Whereas most cognitive domains declined during the follow-up, semantic memory behaved in the opposite way, showing recovery after TBI. In the follow-up assessment, the memory decline and impairments in the set-shifting domain of executive functions were associated with MRI-volumetric measures, whereas reduction in information-processing speed was not associated with the MRI measures. The presence of local contusions was only weakly associated with cognitive functions. Only few cognitive methods for attention were capable of discriminating TBI patients with and without depressive symptoms. On the other hand, most complex attentional tests were sensitive enough to discriminate TBI patients (non-depressive) from controls. This means that complex attention functions, mediated by the frontal lobes, are relatively independent of depressive symptoms post-TBI. The presence of ApoE4 was associated with different kinds of memory processes including verbal and visual episodic memory, semantic memory and verbal working memory, depending on the length of time since TBI. Many other cognitive processes were not affected by the presence of ApoE4. Age at injury and poor vocational outcome were independent risk factors for reduced survival in the multivariate analysis. Late mortality was higher among younger subjects (age < 40 years at death) compared with the general population which should be borne in mind when assessing the need for rehabilitation services and long-term follow-up after TBI.

Mild Cognitive Impairment and Early Detection of Alzheimer`s Disease. A Positron Emission Tomography Study

Alzheimer`s disease (AD) is characterised neuropathologically by the presence of extracellular amyloid plaques, intraneuronal neurofibrillary tangles, and cerebral neuronal loss. The pathological changes in AD are believed to start even decades before clinical symptoms are detectable. AD gradually affects episodic memory, cognition, behaviour and the ability to perform everyday activities. Mild cognitive impairment (MCI) represents a transitional state between normal aging and dementia disorders, especially AD. The predictive accuracy of the current and commonly used MCI criteria devide this disorder into amnestic (aMCI) and non-amnestic (naMCI) MCI. It seems that many individuals with aMCI tend to convert to AD. However many MCI individuals will remain stable and some may even recover. At present, the principal drugs for the treatment of AD provide only symptomatic and palliative benefits. Safe and effective mechanism-based therapies are needed for this devastating neurodegenerative disease of later life. In conjunction with the development of new therapeutic drugs, tools for early detection of AD would be important. In future one of the challenges will be to detect at an early stage these MCI individuals who will convert to AD. Methods which can predict which MCI subjects will convert to AD will be much more important if the new drug candidates prove to have disease-arresting or even disease–slowing effects. These types of drugs are likely to have the best efficacy if administered in the early or even in the presymptomatic phase of the disease when the synaptic and neuronal loss has not become too widespread. There is no clinical method to determine with certainly which MCI individuals will progress to AD. However there are several methods which have been suggested as predictors of conversion to AD, e.g. increased [11C] PIB uptake, hippocampal atrophy in MRI, low CSF A beta 42 level, high CSF tau-protein level, apolipoprotein E (APOE) ε4 allele and impairment in episodic memory and executive functions. In the present study subjects with MCI appear to have significantly higher [¹¹C] PIB uptake vs healthy elderly in several brain areas including frontal cortex, the posterior cingulate, the parietal and lateral temporal cortices, putamen and caudate. Also results from this PET study indicate that over time, MCI subjects who display increased [¹¹C] PIB uptake appear to be significantly more likely to convert to AD than MCI subjects with negative [¹¹C] PIB retention. Also hippocampal atrophy seems to increase in MCI individuals clearly during the conversion to AD. In this study [¹¹C] PIB uptake increases early and changes relatively little during the AD process whereas there is progressive hippocampal atrophy during the disease. In addition to increased [¹¹C] PIB retention and hippocampal atrophy, the status of APOE ε4 allele might contribute to the conversion from MCI to AD.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

PET and MR imaging in Parkinson’s disease patients with cognitive impairment. A study of dopaminergic dysfunction, amyloid deposition, cortical hypometabolism and brain atrophy

Parkinson’s disease (PD) is the second most common neurodegenerative disorder. It is characterized by a severe loss of substantia nigra dopaminergic neurons leading to dopamine depletion in the striatum. PD affects movement, producing motor symptoms such as rigidity, tremor and bradykinesia. Non-motor symptoms include autonomic dysfunction, neurobehavioral problems and cognitive impairment, which may lead to dementia. The pathophysiological basis of cognitive impairment and dementia in PD is unclear. The aim of this thesis was to study the pathophysiological basis of cognitive impairment and dementia in PD. We evaluated the relation between frontostriatal dopaminergic dysfunction and the cognitive symptoms in PD patients with [18F]Fdopa PET. We also combined [C]PIB and [¹⁸F]FDG PET and magnetic resonance imaging in PD patients with and without dementia. In addition, we analysed subregional striatal [¹⁸F]Fdopa PET data to find out whether a simple ratio approach would reliably separate PD patients from healthy controls. The impaired dopaminergic function of the frontostriatal regions was related to the impairment in cognitive functions, such as memory and cognitive processing in PD patients. PD patients with dementia showed an impaired glucose metabolism but not amyloid deposition in the cortical brain regions, and the hypometabolism was associated with the degree of cognitive impairment. PD patients had atrophy, both in the prefrontal cortex and in the hippocampus, and the hippocampal atrophy was related to impaired memory. A single 15-min scan 75 min after a tracer injection seemed to be sufficient for separating patients with PD from healthy controls in a clinical research environment. In conclusion, the occurrence of cognitive impairment and dementia in PD seems to be multifactorial and relates to changes, such as reduced dopaminergic activity, hypometabolism, brain atrophy and rarely to amyloid accumulation.

Simulation of Solid Processes by Aspen Plus

Solid processes are used for obtaining the valuable minerals. Due to their worth, it is obligatory to perform different experiments to determine the different values of these minerals. With the passage of time, it is becoming more difficult to carry out these experiments for each mineral for different characteristics due to high labor costs and consumption of time. Therefore, scientists and engineers have tried to overcome this issue. They made different software to handle this problem. Aspen is one of those software for the calculation of different parameters. Therefore, the aim of this report was to do simulation for solid processes to observe different effect for minerals. Different solid processes like crushing, screening; filtration and crystallization were simulated by Aspen Plus. The simulation results are obtained by using this simulation software and they are described in this thesis. It was noticed that the results were acceptable for all solid processes. Therefore, this software can be used for the designing of crushers by calculating the power consumption of crushers, can design the filter and for the calculation of material balance for all processes.

Simulation and optimization of IGCC technique for power generation and hydrogen production by using lignite Thar coal and cotton stalk

The purpose of this study was to simulate and to optimize integrated gasification for combine cycle (IGCC) for power generation and hydrogen (H2) production by using low grade Thar lignite coal and cotton stalk. Lignite coal is abundant of moisture and ash content, the idea of addition of cotton stalk is to increase the mass of combustible material per mass of feed use for the process, to reduce the consumption of coal and to increase the cotton stalk efficiently for IGCC process. Aspen plus software is used to simulate the process with different mass ratios of coal to cotton stalk and for optimization: process efficiencies, net power generation and H2 production etc. are considered while environmental hazard emissions are optimized to acceptance level. With the addition of cotton stalk in feed, process efficiencies started to decline along with the net power production. But for H2 production, it gave positive result at start but after 40% cotton stalk addition, H2 production also started to decline. It also affects negatively on environmental hazard emissions and mass of emissions/ net power production increases linearly with the addition of cotton stalk in feed mixture. In summation with the addition of cotton stalk, overall affects seemed to negative. But the effect is more negative after 40% cotton stalk addition so it is concluded that to get maximum process efficiencies and high production less amount of cotton stalk addition in feed is preferable and the maximum level of addition is estimated to 40%. Gasification temperature should keep lower around 1140 °C and prefer technique for studied feed in IGCC is fluidized bed (ash in dry form) rather than ash slagging gasifier

Genetically Determined Hypometabolism in Alzheimer’s Disease and Midlife Risk Factors for Cognitive Impairment

The role of genetic factors in the pathogenesis of Alzheimer’s disease (AD) is not completely understood. In order to improve this understanding, the cerebral glucose metabolism of seven monozygotic and nine dizygotic twin pairs discordant for AD was compared to that of 13 unrelated controls using positron emission tomography (PET). Traditional region of interest analysis revealed no differences between the non-demented dizygotic co-twins and controls. In contrast, in voxel-level and automated region of interest analyses, the non-demented monozygotic co-twins displayed a lower metabolic rate in temporal and parietal cortices as well as in subcortical grey matter structures when compared to controls. Again, no reductions were seen in the non-demented dizygotic co-twins. The reductions seen in the non-demented monozygotic co-twins may indicate a higher genetically mediated risk of AD or genetically mediated hypometabolism possibly rendering them more vulnerable to AD pathogenesis. With no disease modifying treatment available for AD, prevention of dementia is of the utmost importance. A total of 2 165 at least 65 years old twins of the Finnish Twin Cohort with questionnaire data from 1981 participated in a validated telephone interview assessing cognitive function between 1999 and 2007. Those subjects reporting heavy alcohol drinking in 1981 had an elevated cognitive impairment risk over 20 years later compared to light drinkers. In addition, binge drinking was associated with an increased risk even when total alcohol consumption was controlled for, suggesting that binge drinking is an independent risk factor for cognitive impairment. When compared to light drinkers, also non-drinkers had an increased risk of cognitive impairment. Midlife hypertension, obesity and low leisure time physical activity but not hypercholesterolemia were significant risk factors for cognitive impairment. The accumulation of risk factors increased cognitive impairment risk in an additive manner. A previously postulated dementia risk score based on midlife demographic and cardiovascular factors was validated. The risk score was found to well predict cognitive impairment risk, and cognitive impairment risk increased significantly as the score became higher. However, the risk score is not accurate enough for use in the clinic without further testing.

Cognitive Development of Very Low Birth Weight Children from Infancy to Pre-school Age

The survival of preterm born infants has increased but the prevalence of long-term morbidities has still remained high. Preterm born children are at an increased risk for various developmental impairments including both severe neurological deficits as well as deficits in cognitive development. According to the literature the developmental outcome perspective differs between countries, centers, and eras. Definitions of preterm infant vary between studies, and the follow-up has been carried out with diverse methods making the comparison less reliable. It is essential to offer parents upto-date information about the outcome of preterm infants born in the same area. A centralized follow-up of children at risk makes it possible to monitor the consequences of changes in the treatment practices of hospitals on developmental outcome. This thesis is part of a larger regional, prospective multidisciplinary follow-up project entitled “Development and Functioning of Very Low Birth Weight Infants from Infancy to School Age” (PIeniPAinoisten RIskilasten käyttäytyminen ja toimintakyky imeväisiästä kouluikään, PIPARI). The thesis consists of four original studies that present data of very low birth weight (VLBW) infants born between 2001 and 2006, who are followed up from the neonatal period until the age of five years. The main outcome measure was cognitive development and secondary outcomes were significant neurological deficits (cerebral palsy, CP, deafness, and blindness). In Study I, the early crying and fussing behavior of preterm infants was studied using parental diaries, and the relation of crying behavior and cognitive and motor development at the age of two years was assessed. In Study II, the developmental outcome (cognitive, CP, deafness, and blindness) at the age of two years was studied in relation to demographic, antenatal, neonatal, and brain imaging data. Development was studied in relationship to a full-term born control group born in the same hospital. In Study III, the stability of cognitive development was studied in VLBW and full-term groups by comparing the outcomes at the ages of two and five years. Finally, in Study IV the precursors of reading skills (phonological processing, rapid automatized naming, and letter knowledge) were assessed for VLBW and full-term children at the age of five years. Pre-reading skills were studied in relation to demographic, antenatal, neonatal, and brain imaging data. The main findings of the thesis were that VLBW infants who fussed or cried more in the infancy were not at greater risk for problems in their cognitive development. However, crying was associated with poorer motor development. The developmental outcome of the present population was better that has been reported earlier and this improvement covered also cognitive development. However, the difference to fullterm born peers was still significant. Major brain pathology and intestinal perforation were independent significant risk factors for adverse outcome, also when several individual risk factors were controlled for. Cognitive development at the age of two years was strongly related with development at the age of five years, stressing the importance of the early assessment, and the possibility for early interventions. Finally, VLBW children had poorer pre-reading skills compared with their full-term born peers, but the IQ was an important mediator even when children with mental retardation were excluded from the analysis. The findings suggest that counseling parents about the developmental perspectives of their preterm infant should be based on data covering the same birth hospital. Neonatal brain imaging data and neonatal morbidity are important predictors for developmental outcome. The findings of the present study stress the importance of both short-term (two years) and long-term (five years) follow-ups for the individual, and for improving the quality of care.

Playing to Learn: Business Simulation Games as Leadership Learning Environments

The aim of this dissertation is to investigate if participation in business simulation gaming sessions can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. Particularly, the focus is to describe the development of leadership styles when leading virtual teams in computer-­supported collaborative game settings and to identify the outcomes of using computer simulation games as leadership training tools. To answer to the objectives of the study, three empirical experiments were conducted to explore if participation in business simulation gaming sessions (Study I and II), which integrate face-­to-­face and virtual communication (Study III and IV), can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. In the first experiment, a group of multicultural graduate business students (N=41) participated in gaming sessions with a computerized business simulation game (Study III). In the second experiment, a group of graduate students (N=9) participated in the training with a ‘real estate’ computer game (Study I and II). In the third experiment, a business simulation gaming session was organized for graduate students group (N=26) and the participants played the simulation game in virtual teams, which were organizationally and geographically dispersed but connected via technology (Study IV). Each team in all experiments had three to four students and students were between 22 and 25 years old. The business computer games used for the empirical experiments presented an enormous number of complex operations in which a team leader needed to make the final decisions involved in leading the team to win the game. These gaming environments were interactive;; participants interacted by solving the given tasks in the game. Thus, strategy and appropriate leadership were needed to be successful. The training was competition-­based and required implementation of leadership skills. The data of these studies consist of observations, participants’ reflective essays written after the gaming sessions, pre-­ and post-­tests questionnaires and participants’ answers to open-­ ended questions. Participants’ interactions and collaboration were observed when they played the computer games. The transcripts of notes from observations and students dialogs were coded in terms of transactional, transformational, heroic and post-­heroic leadership styles. For the data analysis of the transcribed notes from observations, content analysis and discourse analysis was implemented. The Multifactor Leadership Questionnaire (MLQ) was also utilized in the study to measure transformational and transactional leadership styles;; in addition, quantitative (one-­way repeated measures ANOVA) and qualitative data analyses have been performed. The results of this study indicate that in the business simulation gaming environment, certain leadership characteristics emerged spontaneously. Experiences about leadership varied between the teams and were dependent on the role individual students had in their team. These four studies showed that simulation gaming environment has the potential to be used in higher education to exercise the leadership styles relevant in real-­world work contexts. Further, the study indicated that given debriefing sessions, the simulation game context has much potential to benefit learning. The participants who showed interest in leadership roles were given the opportunity of developing leadership skills in practice. The study also provides evidence of unpredictable situations that participants can experience and learn from during the gaming sessions. The study illustrates the complex nature of experiences from the gaming environments and the need for the team leader and role divisions during the gaming sessions. It could be concluded that the experience of simulation game training illustrated the complexity of real life situations and provided participants with the challenges of virtual leadership experiences and the difficulties of using leadership styles in practice. As a result, the study offers playing computer simulation games in small teams as one way to exercise leadership styles in practice.

Improving Transportation and Warehousing Efficiency with Simulation-Based Decision Support Systems

Transportation and warehousing are large and growing sectors in the society, and their efficiency is of high importance. Transportation also has a large share of global carbondioxide emissions, which are one the leading causes of anthropogenic climate warming. Various countries have agreed to decrease their carbon emissions according to the Kyoto protocol. Transportation is the only sector where emissions have steadily increased since the 1990s, which highlights the importance of transportation efficiency. The efficiency of transportation and warehousing can be improved with the help of simulations, but models alone are not sufficient. This research concentrates on the use of simulations in decision support systems. Three main simulation approaches are used in logistics: discrete-event simulation, systems dynamics, and agent-based modeling. However, individual simulation approaches have weaknesses of their own. Hybridization (combining two or more approaches) can improve the quality of the models, as it allows using a different method to overcome the weakness of one method. It is important to choose the correct approach (or a combination of approaches) when modeling transportation and warehousing issues. If an inappropriate method is chosen (this can occur if the modeler is proficient in only one approach or the model specification is not conducted thoroughly), the simulation model will have an inaccurate structure, which in turn will lead to misleading results. This issue can further escalate, as the decision-maker may assume that the presented simulation model gives the most useful results available, even though the whole model can be based on a poorly chosen structure. In this research it is argued that simulation- based decision support systems need to take various issues into account to make a functioning decision support system. The actual simulation model can be constructed using any (or multiple) approach, it can be combined with different optimization modules, and there needs to be a proper interface between the model and the user. These issues are presented in a framework, which simulation modelers can use when creating decision support systems. In order for decision-makers to fully benefit from the simulations, the user interface needs to clearly separate the model and the user, but at the same time, the user needs to be able to run the appropriate runs in order to analyze the problems correctly. This study recommends that simulation modelers should start to transfer their tacit knowledge to explicit knowledge. This would greatly benefit the whole simulation community and improve the quality of simulation-based decision support systems as well. More studies should also be conducted by using hybrid models and integrating simulations with Graphical Information Systems.

Cognitive Auditory Evoked Potentials in Investigation of Hearing Discrimination

Preattentive perception of occasional deviating stimuli in the stream of standard stimuli can be recorded with cognitive event-related potential (ERP) mismatch negativity (MMN). The earlier detection of stimuli at the auditory cortex can be examined with N1 and P2 ERPs. The MMN recording does not require co-operation, it correlates with perceptual threshold, and even complex sounds can be used as stimuli. The aim of this study was to examine different aspects that should be considered when measuring discrimination of hearing with ERPs. The MMN was found to be stimulusintensity- dependent. As the intensity of sine wave stimuli was increased from 40 to 80 dB HL, MMN mean amplitudes increased. The effect of stimulus frequency on the MMN was studied so that the pitch difference would be equal in each stimulus block according to the psychophysiological mel scale or the difference limen of frequency (DLF). However, the blocks differed from each other. The contralateral white noise masking (50 dB EML) was found to attenuate the MMN amplitude when the right ear was stimulated. The N1 amplitude was attenuated and, in contrast, P2 amplitude was not affected by contralateral white noise masking. The perception and production of vowels by four postlingually deafened patients with a cochlear implant were studied. The MMN response could be elicited in the patient with the best vowel perception abilities. The results of the studies show that concerning the MMN recordings, the stimulus parameters and recording procedure design have a great influence on the results.