Oscillations and rhythms are measured in the brain through large-scale measures like EEG (electroencephalogram) and LFP (Local Field Potential). Particularly, cortical gamma rhythms (30-90 Hz) found in different brain regions are correlated with different cognitive states. Despite vast differences in the range frequencies in gamma rhythms, the regions communicate to complete high-level tasks. One way in which this takes place is entrainment, where the postsynaptic group phase-lock to the rhythmic input from the presynaptic group (constant phase-shift). Mathematical models of the neurons and the neural networks are proposed to uncover the mechanisms behind experimentally observed phenomena. Most works have used homogeneous models of spiking networks. These simplified models provide a valuable understanding of neural dynamics. However, neural heterogeneity (variation in the neural or network parameters) has been experimentally observed and shown to have a non-trivial effect on many neural processes. Few studies have dealt with the role of different types of neural heterogeneity in the entrainment of a large network, and how it affects the frequency range the neural network entrains to. In this project, we aimed to show how different types of network heterogeneity affect the ability of the networks to entrain to gamma frequencies. We used the Pyramidal-Interneuronal Network Gamma (PING) model, a model consisting of excitatory pyramidal cells (E-cells) and inhibitory interneurons (I-cells) that are synaptically connected and generate gamma oscillations. We show that heterogeneity in the synaptic conductance from excitatory neurons to inhibitory neurons greatly increases the frequency range over which the network can entrain. The mechanism that allows this to happen requires the heterogeneity to 1. Create an I-cell excitability gradient; 2. Introduce input synchrony difference among the I-cells. The entrained I-cell subsets formed under these two conditions are necessary for well-enhanced entrainment as they support the entrainment of the whole network through feedback inhibition. This improvement is shown to be robust in large parameter space.

The corrosion-wear resistance tradeoff in conventional metals imposes a great challenge to their reliable long-term performance under extreme conditions where surface stress and corrosive environment coexist (i.e., tribocorrosion). In this work, strategies to introduce chemical and structural heterogeneity with controlled length-scale at nanometers were proposed and studied in three metallic systems (i.e., Zr-based, Al-based and Mg-based), in order to enhance their tribocorrosion resistance. In the first study, ZrCuNiAl thin film metallic glasses (TFMG) with either homogeneous or heterogeneous local composition were deposited by magnetron sputtering through controlling processing conditions (i.e., argon (Ar) pressure). It was found that the mechanical properties, wear, corrosion and tribocorrosion resistance of ZrCuNiAl TFMG were significantly affected by nanoscale chemical heterogeneity. As a result, nanoscale chemical heterogeneity promoted ductility but reduced hardness, which in turn weakened wear resistance. While, in the 0.6 M NaCl solution, the resistance to pitting corrosion and tribocorrosion was improved because the presence of nanoscale chemical heterogeneity facilitates to generate more protective passive layer with lower defect density and faster repassivated capability, compared to their homogenous counterparts. In the second study, nanoscale chemical and structural heterogeneity were introduced in Al by forming Al/X nanostructured metallic multilayers (NMMs), where X=Mg, Cu, and Ti. Compared to the respective monolithic films, the alternating nanolayer configuration not only increased strength due to the presence of abundant interfaces but also reduced surface activity and pitting susceptibility. The electrochemical performance was significantly affected by the interaction, i.e., galvanic effect, between Al layer and underlayer constituents, which in turn led to different tribocorrosion behaviors, Specifically, transmission electron microscopy revealed that the materials loss in Al/Mg and Al/Cu NMMs primarily resulted from corrosion, while Al/Ti was dominated by severe plastic deformation during tribocorrosion as a result of sustained surface passivity. Lastly, in the bulk biodegradable Mg alloys system, the surface was treated by femtosecond laser shock peening (fs-LSP) technique with ultra-low pulse energy to introduce structural heterogeneity. Treatment conditions (e.g., power density, direct ablation and confined ablation) significantly affected the ultimate peening effect and further surface performance. In this work, the optimized peening effect was obtained at 28 GW/cm2 laser power density in the confined ablation with the assistance of the adsorption layer and confining medium. Combined with transmission electron microscopy and finite element analysis, the improvement of surface performance was attributed to high dislocation density near the surface, rather than compressive residual stress. The existence of structural heterogeneity not only reduced corrosion kinetics but simultaneously improved the self-repassivation in the blood bank buffered saline solution at body temperature. / Doctor of Philosophy / In various industrial applications such as marine infrastructure, nuclear power plants, and biomedical devices, the synergistic effect of wear and corrosion, known as tribocorrosion, is an inevitable material degradation phenomenon. To resist such aggressive degradation and prolong the service life of metals in complex environments, it is crucial to simultaneously enhance the wear and corrosion resistance, i.e., tribocorrosion resistance of metals. Unfortunately, the corrosion-wear resistance tradeoff in conventional metals imposes a great challenge. For example, most precipitation-hardened Al alloys impart high strength and wear but exhibit low resistance against localized corrosion as a sacrifice owing to the micro-galvanic coupling between the matrix and precipitates. Several previous works pointed out that compositional and structural heterogeneity, even at the nanoscale, could simultaneously affect the mechanical properties and corrosion resistance of metals. However, few works have been performed to understand the effects of such heterogeneity and their length-scale during tribocorrosion of metals. In this dissertation, by combining materials processing, advanced characterization, and tribocorrosion testing, the effects of chemical and structural heterogeneity, as well as their length-scale, on the deformation and degradation mechanisms of metals were studied using model systems of Zr-, Al- and Mg-based alloys, where the chemical and/or structural heterogeneity were introduced by tuning the materials processing conditions. Firstly, the nanoscale chemical heterogeneity was introduced into ZrCuNiAl thin film metallic glasses (TFMG) by adjusting argon (Ar) pressure during magnetron sputtering. Compared with the homogeneous composition, heterogenous local composition in ZrCuNiAl TFMG improved ductility but sacrificed hardness and wear resistance. In 0.6 M NaCl solution, higher pitting corrosion and tribocorroison resistance can be observed due to the generation of low defect density protective passive film with low defect density and with fast repassivation rates in heterogeneous ZrCuNiAl TFMG. Secondly, the architecture of nanostructured metallic multilayer in Al-based with different constituents, from noble to active metals (e.g., Cu, Ti and Mg), were studied the effects of chemical and structural heterogeneity on wear, corrosion and tribocorrosion performance. The results showed that the deformation and corrosion behaviors significantly depended on the distinct interfaces and chemical modulation at the nanoscale, caused by different constituents, which ultimately resulted in various tribocorrosion resistance in 0.6 M NaCl solution at room temperature. Transmission electron microscopy of deformed and degraded sample surfaces showed characteristic different deformation and degradation modes of all samples, governed by the synergistic effects of the mechanical and corrosion properties of the constituting materials. Specifically, severe plastic deformation mainly led to material loss in Al/Ti NMMs owing to the noble surface reactivity, while corrosion was the dominant factor for material loss in Al/Mg and Al/Cu NMMs during tribocorroison. Lastly, the ultra-low pulse energy femtosecond laser shock peening technique was successfully applied to introduce structural heterogeneity in the bulk biodegradable Mg alloys since in some cases the deposition is not feasible for bulk metals. The optimizing peening effect was firstly investigated and was achieved at confined ablation conditions under 28 GW/cm2 laser power density. Results show that the high dislocation density near the surface was contributing to the surface strengthening effect, high corrosion and tribocorrosion resistance in a simulated body environment via transmission electron microscopy observation. The finite element analysis method investigated the compressive residual stress in current work that did not significantly affect the surface performance of Mg alloys. In summary, the study of this dissertation contributes to a good basis and design strategy of conventional metals for applications under complex environments.

Doctor of Philosophy / Department of Statistics / Gary Gadbury / Researches in the fields in science and statistics often go beyond the two-variable cause-and-effect relationship, and also try to understand what connects the causal relationship and what changes the magnitude or direction of the causal relationship between two variables, predictor(T) and outcome (Y). A mediator (Z) is a third variable that links a cause and an effect, whereby T causes the Z and Z causes Y. In general, a given variable may be said to function as a mediator to the extent that it accounts for the relation between the predictor and the outcome (Baron and Kenny, 1986). The initial question regards the appropriate characterization of a mediation effect. Most studies, when comparing one or more treatments focus on an average mediating effect. This average mediating effect can be misleading when the mediating effects vary from subject to subject in the population. The primary focus of this research is to investigate individual mediating effects in a population, and to define a variance of these individual mediating effects. A concept called subject-mediator (treatment) interaction is presented and its role in evaluating a mediator’s behavior on a population of units is studied. This is done using a framework sometimes called a counterfactual model. Some common experimental designs that provide different knowledge about this interaction term are studied. The subgroup analysis is the most common analytic approach for examining heterogeneity of mediating effects. In mediation analysis, situations can arise where Z and Y cannot both be measured on an individual unit. We refer to such data as terminal measures data. We show a design where a mediating effect cannot be estimated in terminal measures data and another one where it can be, with an assumption. The assumption is linked to the idea of pseudo-replication. These ideas are discussed and a simulation study illustrates the issues involved when analyzing terminal measures data. We know of no methods that are currently available that specifically address terminal measures data.

The benthic animals have important roles in benthic communities. Indicator organisms can tell things about a lakes status. Many of them are sensitive to acidification but there are also tolerant taxa. Some prefer eutrophic environments. The benthic fauna can therefore decide a lakes status since some species prefer different environments. The focus of this study was to compare benthic fauna within the littoral in the lakes Sidsjön and Vintertjärnen. They are situated a little south of Sundsvall, central Sweden and belong to the water system of Selångersån. The comparison was done at eight random locals in each lake at two occasions, during early and late summer to analyze if the benthic fauna differed between the two lakes and if it changed through the season. Five of the locals in each lake were protected and had soft bottoms and the remaining were exposed locals with hard bottom. Sidsjön is bigger than Vintertjärnen and has more variated bottom types so the biodiversity should be higher in Sidsjön. I also expect that the number of taxa should decrease during the later occasion due to hatchings. Three statistical analyses were done to see if these hypotheses were right or if they should be rejected. The two first analyses were ANOVA analyses, two-way with replication. The first ANOVA was for number of taxa and the second was for number of animals. The third analysis was a DCA analysis with the variables lakes, bottom types and emergent plants. ASPT index and Eq was also calculated and pH was measured during autumn for the lakes. The conclusion is that the there is no difference between the lakes but a significant effect when it comes to seasons according to the first ANOVA analysis. The second ANOVA analysis show that the lakes are not differing, that no factor is significant and there are no interactions. According to the DCA analysis there are differences between lakes and occasions when it comes to the variables. / <p>Datum för godkännande 2016-03-31</p>

This thesis sets out to investigate the Alzheimer's disease (AD) heterogeneity in an unsupervised framework. Different subtypes of AD were identified in the past from a number of studies. The major objective of the thesis is to apply clustering methods that are specialized in coping with high dimensional data sets, in a sample of AD patients. The evaluation of these clustering methods and the interpretation of the clustered groups from a statistical and a medical point of view, are some of the additional objectives. The data consist of 271 MRI images of AD patients from the AddNeuroMed and the ADNI cohorts. The raw MRI's have been preprocessed with the software Freesurfer and 82 cortical and subcortical volumes have been extracted for the needs of the analysis. The effect of different strategies in the initialization of a modified Gaussian Mixed Model (GMM) (Bouveyron et al, 2007) has been studied. Additionally, the GMM and a Bayesian clustering method proposed by Nia (2009) have been compared with respect to their performances in various distance based evaluation criteria. The later method resulted in the most compact and isolated clusters. The optimal numbers of clusters was evaluated with the Hopkins statistic and 6 clusters were decided while 2 observations formed an outlier cluster. Different patterns of atrophy were discovered in the 6 clusters. One cluster presented atrophy in the medial temporal area only (n=37,~13.65%). Another cluster resented atrophy in the lateral and medial temporal lobe and parts of the parietal lobe (n=39,~14.4%). A third cluster presented atrophy in temporoparietal areas but also in the frontal lobe (n=74,~27.3%). The remaining three clusters presented diffuse atrophy in nearly all the association cortices with some variation in the patterns (n1=40,~14.7%,n2=58,~21.4,n3=21,7.7%). The 6 subtypes also differed in their demographical, clinical and pathological features.

No description available.

Within the next decade India is expected to surpass China as the world's most populous country due to still higher fertility and a younger population. Around 2025 each country will be home to around 1.5 billion people. India is demographically very heterogeneous with some rural illiterate populations still having more than four children on average while educated urban women have fewer than 1.5 children and with great differences between states. We show that the population outlook greatly depends on the degree to which this heterogeneity is explicitly incorporated into the population projection model used. The conventional projection model, considering only the age and sex structures of the population at the national level, results in a lower projected population than the same model applied at the level of states because over time the high-fertility states gain more weight, thus applying the higher rates to more people. The opposite outcome results from an explicit consideration of education differentials because over time the proportion of more educated women with lower fertility increases, thus leading to lower predicted growth than in the conventional model. To comprehensively address this issue, we develop a five-dimensional model of India's population by state, rural/urban place of residence, age, sex, and level of education and show the impacts of different degrees of aggregation. We also provide human capital scenarios for all Indian states that suggest that India will rapidly catch up with other more developed countries in Asia if the recent pace of education expansion is maintained.

The moose population in Sweden is one of the highest in the world. The population have positive impacts on humans but also cause problems such as browsing damages and collisions with traffic. To manage this population in an adaptive and ecological sound way, the managers need to have as much information as possible. The aim of this study was to improve the description of Sweden’s moose management areas regarding available forage for moose. This is done by describing the heterogeneity of the landscape within the moose management areas, which is done by using different landscape indexes. The heterogeneity indexes is then used to analyze if correlation exists between the variation of the landscape and firstly data that describes the available food, secondly data that indicates the moose population density. Multiple regression analysis were done in order to find a model with the indexes that best explains the variation in available forage and moose population indicators.  The results in this study showed a positive correlation between number of moose shot per 1000 hectares and patch richness awhile a negative correlation was found between number of moose shot per 1000 hectares and edge density. Results also showed a negative correlation between both edge density and the patch richness in the landscape with the presence of rowan, sallow, aspen and oak (RASE). Further developments of indexes that describe landscape heterogeneity is needed, but this study may indicate that knowledge of the variation in the landscape might provide useful information on the prerequisites for the Swedish moose population.

Cette thèse contribue à la littérature théorique et empirique concernant l’hétérogénéité des entreprises et le commerce international. La partie théorique analyse les conséquences de la libéralisation du commerce lorsque les entreprises sont hétérogènes et les pays asymétriques. La partie empirique discute le sens de causalité de la relation entre la performance des entreprises et leur statut international. Les entreprises sont-elles plus performantes parce qu’elles exportent et/ou importent ? Ou sont-ce les entreprises les plus performantes qui s’auto-sélectionnent sur le marché international ? Les deux hypothèses ne s’excluent pas mutuellement et ce travail les accrédite toutes deux. / This thesis contributes to both theoretical and empirical aspects of the literature on firm heterogeneity in international trade. On the theoretical side, I provide insights of the consequences of trade liberalisation when firms are heterogeneous and countries are asymmetric. On the empirical side, I discuss the causality of the relationship between performances and trading status of firms. Do more productive firms self-select into international markets? Do firms become more productive because they enter international markets? These hypotheses are not mutually exclusive and my work provides support for both of them.

Ascending thoracic aortic aneurysms (ATAAs) are focal dilatations in the aorta that are prone to rupture or dissect. Currently, the clinically used indicator of the rupture risk is the diameter. However, it has been demonstrated that the diameter alone may not properly predict the risk. To evaluate the rupture risk, one must look into the local mechanical conditions at the rupture site and understand how rupture is triggered in the tissue which is a layered fibrous media. A challenge facing experimental studies of ATAA rupture is that the ATAA tissue is highly heterogeneous; experimental protocols that operate under the premise of tissue homogeneity will have difficulty delineating the heterogeneous properties. In general, rupture initiates at the location where the micro-structure starts to break down and consequently, it is more meaningful to investigate the local conditions at the rupture site. In this work, a combined experimental and computational method was developed and employed to characterize wall stress, strain, and property distributions in harvested ATAA samples to a sub-millimeter resolution. The results show that all tested samples exhibit a significant degree of heterogeneous in their mechanical properties. Large inter-subject variability is also observed. A heterogeneous anisotropic finite strain hyperelastic model was introduced to describe the tissue; the distributions of the material parameters were identified. The elastic energy stored in the tissue was computed. It was found that the tissue fractures preferentially in the direction of the highest stiffness, generating orifices that are locally transverse to the peak stiffness direction. The rupture appears to initiate at the position absorbed of the highest energy. Machine learning was used to classify the curves at rupture and non-rupture locations. Features including material properties and curve geometric characteristics were used. The work showed that the rupture and non-rupture states can indeed be classified using pre-rupture response features. Support vector machine(SVM) and random forest algorithm was employed to provide insight on the importance of the features. Inspired by the importance scores provided by random forest, the rupture groups were interrogated and some strong correlations between the strength and the response features were revealed. In particular, it was found that the strength correlates strongly with the tension at the point where the curvature of the total tension strain curve attains maximum, which occurs early in the response.