Wind power is a fast-growing, sustainable energy source. However, the problem of wind variability as it relates to wind power reliability is an obstacle to its large-scale deployment. It is possible to improve the reliability of wind power by interconnecting wind generation. In this study, wind power plants within the Midwest ISO were aggregated to examine the effect on reliability. Wind speed data from the North American Regional Reanalysis were used to calculate wind power data. It was found that the reliability of interconnected wind power was improved relative to individual wind power plants in both the short-term and the long-term, and that the most significant improvements were at the highest scales of interconnection. It was also found that the reliability of interconnected wind power is more directly related to the area of the network rather than the number of wind power plants in the network.

This paper considers alternative methods to estimate econometric models based on bilateral data when only aggregate information on the dependent variable is available. Such methods can be used to obtain an indication of the sign and magnitude of bilateral model parameters and, more importantly, to decompose aggregate into bilateral data, which can then be used as proxy variables in further empirical analysis. We perform a Monte Carlo study and carry out a simple real world application using intra-EU trade and capital flows, showing that the methods considered work reasonably well and are worthwhile being considered in the absence of bilateral data. (authors' abstract)

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L'autophagie est l'une des voies de signalisation qui maintiennent l'homéostasie cellulaire en condition basale, mais aussi en réponse à un stress. Son rôle est essentiel pour assurer plusieurs fonctions physiologiques, et son altération est associée à de nombreuses maladies, parmi lesquelles le cancer, les maladies immunitaires et les maladies neurodégénératives. Un nombre croissant d'études a établi que la voie autophagique est finement contrôlée. Cependant, très peu est connu sur les mécanismes moléculaires assurant sa régulation mais la famille des E3-ligases joue un rôle primordiale. La Gigaxonine est un adaptateur de la famille des E3 ligases CUL3, qui spécifie les substrats pour leur ubiquitination et leur successive dégradation. Des mutations «perte de fonction» de la Gigaxonine causent la Neuropathie à Axones Géants (NAG), une maladie neurodégénérative sévère et fatale, qui impacte tout le système nerveux et provoque une agrégation anormale des Filaments Intermédiaires (FI) dans l'organisme entier. Grâce à la modélisation de la pathologie dans les cellules de patients et chez la souris, le laboratoire a pu mettre en avant le rôle crucial de la Gigaxonine dans la dégradation de la famille des FIs, à travers son activité d'ubiquitination.Au cours de ma thèse, j'ai étudié les mécanismes de neurodégénerescence de la NAG, et la possible altération de la voie autophagique.Pour cela, j'ai développé un nouveau modèle neuronal de la maladie, à partir de notre modèle murin NAG, qui reproduit la mort neuronale et l'agrégation des FIs retrouvées chez les patients. Pour étudier l'implication de l'autophagie dans la neurodégénérescence, j'ai évalué l'effet de la déplétion de la Gigaxonine sur la formation des autophagosomes, le flux autophagique, la fusion avec le lysosome et la dégradation. J’ai ainsi révélé un défaut dans la dynamique autophagique dans les neurones NAG -/-. Pour déchiffrer les mécanismes moléculaires sous-jacents, j'ai étudié l'effet de l'absence de la Gigaxonine sur différentes régulateurs de la voie. En utilisant des techniques complémentaires, j'ai montré que la Gigaxonine est essentielle pour le turn-over d’un interrupteur autophagique, à travers son activité d’E3-ligase.En conclusion, nous avons identifié un nouveau mécanisme moléculaire impliqué dans le contrôle des premières phases de l'autophagie. Non seulement ces résultats présentent une avancée significative dans le domaine de l'autophagie, ils contribuent également à la compréhension de son dysfonctionnement dans les maladies neurodégénératives, et pourraient générer une nouvelle cible pour une intervention thérapeutique chez l'homme. / The autophagic route is one of the signaling pathways that sustain cellular homeostasis in basal condition, but also in response to stress. It has been shown to be crucial for several physiological functions and its impairment is associated with many diseases, including cancer, immune and neurodegenerative diseases. While an expanding number of studies have shown that autophagic route is finely controlled, little is known about the molecular mechanisms ensuring its function, but a fundamental role is sustained by the family of E3 ligases. Gigaxonin is an adaptor of a Cul3-E3 ligase, which specifies the substrates for their ubiquitination and their subsequent degradation. “Loss of function” mutations in Gigaxonin cause Giant Axonal Neuropathy (GAN), a severe and fatal neurodegenerative disorder that impacts broadly the nervous system and cause an abnormal aggregation of Intermediate Filaments (IFs) through the body. Modeling the disease in patient’s cells and in mouse, the laboratory has demonstrated the crucial role of Gigaxonin in degrading the entire family of IFs through its ubiquitination activity.During my PhD, I studied the neurodegenerative mechanisms in GAN disease, and the possible impairment of autophagy pathway.For that purpose, I developed a new neuronal model of the disease from our GAN mouse, which reproduced the neurodegeneration and the IF aggregation found in patients. To investigate the involvement of autophagy in neurodegeneration, I evaluated the effect of Gigaxonin depletion on autophagosome formation, autophagic flux, lysosome fusion and degradation, and I revealed a defect in autophagy dynamics. To decipher the molecular mechanism of autophagosome impairment, I investigated the effect of Gigaxonin depletion on different autophagy regulators. Using complementary techniques, I showed that Gigaxonin is essential for the turn-over of a specific molecular switch, through its E3 ligase activity.Altogether, we identified a new exciting molecular mechanism in the control of autophagy. Not only these findings present a significant advance in the comprehension of the fundamental field of autophagy, but it also contribute in the understanding of its dysfunction in neurodegenerative diseases, and may generate a new target for therapeutic intervention in humans.

Charles University Faculty of Pharmacy in Hradec Králové Department of Pharmacology & Toxicology Student: Nikola Kopková Supervisor: Assoc. Prof. Přemysl Mladěnka, Pharm.D., Ph.D. Title of diploma thesis: Antiplatelet effects of flavonoids The most common antioxidants in ordinary food are flavonoids. They show antioxidant and anti-aggregation effects and other positive effects on cardiovascular diseases. Flavonoids are promising candidates to be antiplatelet drugs. Although several mechanisms responsible for antiplatelet activity have been suggesteed, only a few have been documented by published studies. The inhibition of blood platelet aggregation by flavonoids is reversible, which is another important factor. Data on thrombin-induced aggregation are controversial, some claim that flavonoids have no effect, the others says they have positive effects. (In the case of quercetin and genistein, inhibition of aggregation induced by thrombin was documented). The effect on arachidonic acid in the aggregation cascade is well documented, but there are several inconsistencies resulting from the use of different materials. Other mediators of aggregation are phospholipase A2, which plays a key role in the formation of inflammatory mediators. In this case, it has been shown that mainly genistein is capable of...

Most existing data mining approaches perform data mining tasks on a single data table. However, increasingly, data repositories such as financial data and medical records, amongst others, are stored in relational databases. The inability of applying traditional data mining techniques directly on such relational database thus poses a serious challenge. To address this issue, a number of researchers convert a relational database into one or more flat files and then apply traditional data mining algorithms. The above-mentioned process of transforming a relational database into one or more flat files usually involves aggregation. Aggregation functions such as maximum, minimum, average, standard deviation, count and sum are commonly used in such a flattening process. Our research aims to address the following question: Is there a link between aggregation and possible privacy violations during relational database mining? In this research we investigate how, and if, applying aggregation functions will affect the privacy of a relational database, during supervised learning, or classification, where the target concept is known. To this end, we introduce the PBIRD (Privacy Breach Investigation in Relational Databases) methodology. The PBIRD methodology combines multi-view learning with feature selection, to discover the potentially dangerous sets of features as hidden within a database. Our approach creates a number of views, which consist of subsets of the data, with and without aggregation. Then, by identifying and investigating the set of selected features in each view, potential privacy breaches are detected. In this way, our PBIRD algorithm is able to discover those features that are correlated with the classification target that may also lead to revealing of sensitive information in the database. Our experimental results show that aggregation functions do, indeed, change the correlation between attributes and the classification target. We show that with aggregation, we obtain a set of features which can be accurately linked to the classification target and used to predict (with high accuracy) the confidential information. On the other hand, the results show that, without aggregation we obtain another different set of potentially harmful features. By identifying the complete set of potentially dangerous attributes, the PBIRD methodology provides a solution where the database designers/owners can be warned, to subsequently perform necessary adjustments to protect the privacy of the relational database. In our research, we also perform a comparative study to investigate the impact of aggregation on the classification accuracy and on the time required to build the models. Our results suggest that in the case where a database consists only of categorical data, aggregation should especially be used with caution. This is due to the fact that aggregation causes a decrease in overall accuracies of the resulting models. When the database contains mixed attributes, the results show that the accuracies without aggregation and with aggregation are comparable. However, even in such scenarios, schemas without aggregation tend to slightly outperform. With regard to the impact of aggregation on the model building time, the results show that, in general, the models constructed with aggregation require shorter building time. However, when the database is small and consists of nominal attributes with high cardinality, aggregation causes a slower model building time.

Margination is the migration of particles in a channel towards the outer walls of the channel. In blood microcirculation, studying the margination of microparticles is important to understand platelet migration and the kinetics of drug delivery. Many new topics in drug delivery research examine the slow release of drugs through micro particles, such as micelles. The margination of such drug carriers is related to tissue absorption and, consequently, to the efficiency of drug delivery. We hypothesized that the intensity of red blood cell (RBC) aggregation will change the level of margination in a cylindrical channel. RBC aggregation is the reversible process of RBCs clumping together over time, under low fluid shear rate. A higher level of aggregation means that this clumping occurs more quickly. The goal of this thesis is to design an experiment that measures the level margination of microparticles and the effect that RBC aggregation has on margination, in a controlled in vitro environment. Fluorescent microparticles were added to human blood preparations. The aggregation properties of the blood preparation were modulated by the addition of a macromolecule (Dextran 500). The blood preparations were injected into PDMS microfluidic devices that were modified to have circular channels in order to better mimic the geometry of physiological microcirculation. We designed a circular microchannel that worked to capture the marginating microparticles and it was found that the level of margination of the microparticles increased with an increase in aggregation of the RBCs. This increase in margination was especially sensitive to aggregation levels in the range of physiological aggregation levels of whole blood, suggesting that aggregation plays an important role in margination in vivo.

Electrical bioimpedance was used to detect local volume and aggregation changes in blood. This was done with two separate experimentation processes to improve upon current research methods. Abdominal internal hemorrhaging is bleeding and pooling of blood within the abdominal cavity which can put the welfare of the patient at risk and may cause organ failure. Electrical bioimpedance is the response of biological tissue to applied electrical current. In cooperation with Bioparhom, electrical bioimpedance was used as a detection device for abdominal internal hemorrhaging. It is hypothesized that electrical bioimpedance could be a non-invasive and cost effective avenue for the detection of internal bleeding. In this study we investigate the use of electrical bioimpedance with a custom 8x8 needle electrode array, for detecting and locating the blood pooling due to a drop in resistivity in a rat using a Z-Metrix (function generator by Bioparhom). 5 and 95 kHz signals were inputted into a dead rat experiencing internal bleeding of porcine blood at a rate of 3.33 ml/min to 10 ml. For 8 rats, the 5 kHz frequency was found to be more sensitive to internal blood pooling. Red blood cell aggregation is a physiological process where red blood cells form reversible aggregates. RBC aggregation is an important indicator for physicians for the health of the circulatory system. Utilizing electrical bioimpedance, it is hypothesized that a reactance change as a result of blood aggregation will be detected. As well, a method is developed using impedance spectroscopy to determine s frequency which exhibits the highest reactance change during blood aggregation. This sensitive frequency, found to be 304 kHz, is compared to a frequency used by previous studies (100 kHz) to validate its. Using the Z-Metrix (function generator by Bioparhom) with a custom 4 electrode configuration, 2 ml of porcine blood mixed with 2 mg/ml of EDTA is tested for 2 minutes at a single frequency. The 304 kHz is found to be the most sensitive of the frequencies tested to reactance changes during aggregation. Results found for blood samples give an average AIc of 27.32 ± 11.44, which is within the physiological range for porcine blood of 3-30. It is seen that the 304 kHz has a higher precision than the 100 kHz frequency, but the AIc is within the same magnitude. As a result, 304 kHz is found to be a more favorable frequency than the previously published 100 kHz for the trials performed based on precision of the results and the sensitivity of the reactance change to blood aggregation.

Peroxiredoxins are ubiquitous, thiol-specific proteins that have multiple functions in stress protection, including oxidative stress. Tsa1 is the major yeast peroxiredoxin and we show that it functions as a specific antioxidant to protect against oxidative stress caused by nascent protein misfolding and aggregation. Yeast mutants lacking TSA1 are sensitive to misfolding caused by exposure to the proline analogue azetidine-2-carboxylic acid (AZC). AZC promotes protein aggregation and its toxicity to a tsa1 mutant is caused by reactive oxygen species (ROS). Generation of [rho0] cells lacking mitochondrial DNA rescues the tsa1 mutant AZC sensitivity indicating that mitochondria are the source of ROS. Inhibition of nascent protein synthesis with cycloheximide prevents AZC-induced protein aggregation and abrogates ROS generation confirming that aggregate formation causes ROS production. Protein aggregation is accompanied by mitochondrial fragmentation and we show that Tsa1 localizes to the sites of protein aggregation, which are formed adjacent to mitochondria. Further investigation reveals that AZC-induced protein aggregation leads to an inhibition of mitochondrial respiration and the depolarisation of the mitochondrial membrane. Remarkably, this was entirely dependent on the presence of Tsa1. We show that the effects of protein aggregation on mitochondrial function are mediated by the Ras/PKA pathway and that Tsa1 appears to influence the activity of this pathway through its effects on the yeast phosphodiesterase, Pde2. Together, these data indicate a new role for peroxiredoxins in the response to ROS, generated as a result of protein misfolding and aggregate formation. Finally, we analysed the characteristics of proteins found within protein aggregates, isolated from different conditions during the course of the study. Our results highlight the differences between proteins that aggregate under normal, mid-exponential growth conditions (physiological aggregates) and those which aggregate during cellular stress. We were able to establish the characteristics of an archetypical physiological aggregate, through an assessment of a range of properties, identifying factors that significantly differed from genomic expectations. Furthermore, our observations indicate that, in general, cellular stress reduces the threshold of metrics associated with protein aggregation propensity. We also found that different stresses result in the aggregation of proteins that are, largely, physicochemically indistinct from one another, regardless of the mode of toxicity. Finally we show that a significant number of proteins, identified in our protein aggregates, were also present in protein aggregates isolated from aged C. elegans. This suggests that the factors and components of protein aggregates are conserved.

Passive acoustic monitoring has been successfully used on many elasmobranch species, but no such study has yet been published for the whale shark (Rhincodon typus). In some ways this is surprising as the known whale shark aggregation sites would seem to be ideal targets for this method. For this dissertation, two acoustic studies were carried out in Saudi Arabia and Tanzania. Each was performed in parallel with visual surveys and the Saudi population was also studied using satellite telemetry. Sighting and acoustic data were compared at both sites, and the results were mixed. The acoustic monitoring largely confirmed the results of visual surveys for the Saudi Arabian sharks, including seasonality, residency and a degree of parity and integration between the sexes that is unique to this site. Satellite tracks of tagged Saudi sharks were used to confirm that some animals migrated away from the aggregation site before returning in subsequent seasons, confirming philopatric behavior in this species. In contrast, the acoustic results in Tanzania demonstrated year-round residency of whale sharks in the area, despite seasonal declines in visually estimated abundance. Seasonal changes in habitat selection render the sharks at this site temporarily cryptic to visual sampling. The differing results are compelling because both the philopatric behavior demonstrated in Saudi Arabia and the cryptic residency of the Tanzanian sharks could explain the seasonal patterns in whale shark abundances reported at other aggregation sites. Despite their differences, both sites in this study can be classified as secondary whale shark nurseries and each may be a vital feeding ground for its respective population.